Reviewer #3 (Public review):

Summary:

This manuscript, "Estimating bone marrow adiposity from head MRI and identifying its genetic 2 architecture", brings together the groups of Drs. Kaufmann and Hughes in a tour de force work to develop an artificial neural network that localizes calvaria bone marrow in T1-weighted MRI head scans, with the goal of studying its composition in several large MRI datasets, and to model sex-dimorphic age trajectories, including the effect of menopause.

Strengths:

Bone marrow adiposity is a very active tissue with far-reaching implications for tissue crosstalk and human health than we had initially recognized. Although MRI has been used to measure BM, studies such as the one by these two groups are still lacking whereas very large datasets are analyzed using advanced AI machine learning tools coupled with genetic studies and a specific pathology. The groups had to develop new methods and new AI machine-learning tools for the imaging analyses.

Weaknesses:

Some aspects of the work that authors could add additional clarification.

(1) Imaging Limitations: The authors provide an excellent overview and references supporting the use of MRI as a method for assessing marrow fat, particularly with some specific modifications. However, MRI images can be affected by various factors, including the presence of other tissues as well as specific MRI settings, which are much harder to precisely control when using different datasets.

(2) The specific density of cranial bones as it relates to the types of bone marrow: Cranial bones are extremely dense structures, which naturally interfere with MRI imaging. While it is thought that cranial bones have mostly "red bone marrow", this is only true for a short time in humans. How sensitive is their system in differentiating between red and yellow BM?

(3) Both items above are further complicated by aging, but aging is not a linear event as we have learned. There are specific bursts of aging in humans around the age of 45 and early 60s. How do the system and model predict or incorporate these peaks of aging? It seems from the data shown that aging is reflected more as a linear phenomenon. Is this because additional aging datasets are needed?

(4) The authors describe in richness of detail their AI learning programming and how it extracted the data from datasets. The authors also show some important correlations with specific genes, SNPs. What is not clear is how conditions such as anemia for example. An expected finding would be that patients with chronic anemia have lower bone marrow (BM) signal intensity on MRI scans than healthy people. This is because the signal intensity of BM depends on the fat-to-cell ratio in the tissue. Furthermore, patients with a host of musculoskeletal disorders ranging from osteopenia to osteoporosis, sarcopenia, and osteosarcopenia will also have altered MRI scans. When using such large datasets how did the authors control or exclude these pathological conditions, or were all these conditions likely present?

(5) Some of the genes and SNPs although significant showed very small correlations. What is their likely physiological significance?

(6) The authors could use this excellent manuscript to expand their discussion to include the need for studies like theirs to be also complemented by multi-OMICS studies that will include proteomics and lipidomics of BM, bones, and muscles.

Update v1.1

Based on the FDA approvals for pembrolizumab for patients with recurrent or metastatic cutaneous squamous cell carcinoma [Ref 108, 169] and toripalimab in combination with cisplatin and gemcitabine for first-line treatment of patients with metastatic or recurrent locally advanced nasopharyngeal carcinoma, or as a monotherapy for treatment of adult patients with recurrent, unresectable, or metastatic nasopharyngeal carcinoma with disease progression on or after platinum-containing chemotherapy [Ref 170, 171], the guideline has been updated.

The following recommendations were added or amended:

• Cemiplimab or pembrolizumab, if not contraindicated (eg, organ transplant recipients), should be prescribed for patients with metastatic or locally-advanced cSCC in the head and neck region who are not candidates for curative surgery or radiation, or for whom neoadjuvant response reduces the morbidity of definitive therapy.

• For patients with metastatic or recurrent locally advanced nasopharyngeal carcinoma, first-line treatment with toripalimab in combination with cisplatin and gemcitabine is recommended.

  • There is clinical evidence for other PD-1 inhibitors as well, and these may be substituted if toripalimab is unavailable.

• For patients with recurrent unresectable or metastatic nasopharyngeal carcinoma who have disease progression on or after platinum-containing chemotherapy, toripalimab monotherapy is recommended.

  • There is clinical evidence for other PD-1 inhibitors as well, and these may be substituted if toripalimab is unavailable.

Update v1.1

The following references have been added:

1. FDA approves pembrolizumab for cutaneous squamous cell carcinoma. https://www.fda.gov/drugs/drug-approvals-and-databases/fda-approves-pembrolizumab-cutaneous-squamous-cell-carcinoma

2. FDA approves toripalimab-tpzi for nasopharyngeal carcinoma. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-toripalimab-tpzi-nasopharyngeal-carcinoma

3. Food and Drug Administration, Coherus BioSciences. LOQTORZ (toripalimab-tpzi) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=761240 Accessed 6/27/24.

4. Gillison ML, Blumenschein Jr G, Fayette J, Guigay J, Colevas AD, Licitra L, Harrington KJ, Kasper S, Vokes EE, Even C, Worden F, Saba NF, Iglesias Docampo LC, Haddad R, Rordorf T, Kiyota N, Tahara M, Monga M, Lynch M, Li L, Ferris RL. CheckMate 141: 1‐Year Update and Subgroup Analysis of Nivolumab as First‐Line Therapy in Patients with Recurrent/Metastatic Head and Neck Cancer. The Oncologist, 2018 Sept. https://doi.org/10.1634%2Ftheoncologist.2017-0674"10.1634/theoncologist.2017-0674

5. Dzienis MR, Cundom JE, Fuentes CS, Hansen AR, Nordlinger MJ, Pastor AV, Oppelt P, Neki A, Gregg RW, Lima IPF, Franke FA, daCunha Junior GF, Tsent JE, Loree T, Joshi AJ, Mccarthy JS, Naicker N, Sidi Y, Gumuscu B, De Castro Jr G. 651O Pembrolizumab (pembro) + carboplatin (carbo) + paclitaxel (pacli) as first-line (1L) therapy in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC): Phase VI KEYNOTE-B10 study. Annals of Oncology, 2022 Sept. https://doi.org/10.1016/j.annonc.2022.07.775

6. Fayette J, Cropet C, Gautier J, Toullec C , Burgy M, Bruyas A, Sire C, Lagrange A, Clatot F, Calderon B, Vinches M, Iacob M, Martin L, Neidhardt Berard EM, Kaminsky MC, Vansteene D, Salas S, Champagnac A, Pérol D, Bourhis J. Results of the multicenter phase II FRAIL-IMMUNE trial evaluating the efficacy and safety of durvalumab combined with weekly paclitaxel carboplatin in first-line in patients (pts) with recurrent/metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) not eligible for cisplatin-based therapies. J Clin Oncol 41, 2023 (suppl 16; abstr 6003).

The Rape of the Lock is a mock-heroic narrative poem written by Alexander Pope, first published 1712. This poem satirises a minor incident of life, by comparing it to the epic world of the gods. The passage referred to by Eliot is in the first canto of the poem, specifically verses 121-148:

And now, unveil'd, the toilet stands display'd, / Each silver vase in mystic order laid. / First, rob'd in white, the nymph intent adores / With head uncover'd, the cosmetic pow'rs. / A heav'nly image in the glass appears, / To that she bends, to that her eyes she rears; / Th' inferior priestess, at her altar's side, / Trembling, begins the sacred rites of pride. / Unnumber'd treasures ope at once, and here / The various off'rings of the world appear; / From each she nicely culls with curious toil, / And decks the goddess with the glitt'ring spoil. / This casket India's glowing gems unlocks, / And all Arabia breathes from yonder box. / The tortoise here and elephant unite, / Transform'd to combs, the speckled and the white. / Here files of pins extend their shining rows, / Puffs, powders, patches, bibles, billet-doux. / Now awful beauty puts on all its arms; / The fair each moment rises in her charms, / Repairs her smiles, awakens ev'ry grace, / And calls forth all the wonders of her face; / Sees by degrees a purer blush arise, / And keener lightnings quicken in her eyes. / The busy Sylphs surround their darling care; / These set the head, and those divide the hair, / Some fold the sleeve, whilst others plait the gown; / And Betty's prais'd for labours not her own.

(Pope’s The Rape of the Lock, Canto I, ll. 121 - 148)

Reviewer #2 (Public review):

In this manuscript, Li and collaborators set out to investigate the neuronal mechanisms underlying "subjective time estimation" in rats. For this purpose, they conducted calcium imaging in the prefrontal cortex of water-restricted rats that were required to perform an action (nose-poking) for a short duration to obtain drops of water. The authors provided evidence that animals progressively improved in performing their task. They subsequently analyzed the calcium imaging activity of neurons and identify start, duration, and stop cells associated with the nose poke. Specifically, they focused on duration cells and demonstrated that these cells served as a good proxy for timing on a trial-by-trial basis, scaling their pattern of actvity in accordance with changes in behavioral performance. In summary, as stated in the title, the authors claim to provide mechanistic insights into subjective time estimation in rats, a function they deem important for various cognitive conditions.

This study aligns with a wide range of studies in system neuroscience that presume that rodents solve timing tasks through an explicit internal estimation of duration, underpinned by neuronal representations of time. Within this framework, the authors performed complex and challenging experiments, along with advanced data analysis, which undoubtedly merits acknowledgement. However, the question of time perception is a challenging one, and caution should be exercised when applying abstract ideas derived from human cognition to animals. Studying so-called time perception in rats has significant shortcomings because, whether acknowledged or not, rats do not passively estimate time in their heads. They are constantly in motion. Moreover, rats do not perform the task for the sake of estimating time but to obtain their rewards are they water restricted. Their behavior will therefore reflect their motivation and urgency to obtain rewards. Unfortunately, it appears that the authors are not aware of these shortcomings. These alternative processes (motivation, sensorimotor dynamics) that occur during task performance are likely to influence neuronal activity. Consequently, my review will be rather critical. It is not however intended to be dismissive. I acknowledge that the authors may have been influenced by numerous published studies that already draw similar conclusions. Unfortunately, all the data presented in this study can be explained without invoking the concept of time estimation. Therefore, I hope the authors will find my comments constructive and understand that as scientists, we cannot ignore alternative interpretations, even if they conflict with our a priori philosophical stance (e.g., duration can be explicitly estimated by reading neuronal representation of time) and anthropomorphic assumptions (e.g., rats estimate time as humans do). While space is limited in a review, if the authors are interested, they can refer to a lengthy review I recently published on this topic, which demonstrates that my criticism is supported by a wide range of timing experiments across species (Robbe, 2023). In addition to this major conceptual issue that casts doubt on most of the conclusions of the study, there are also several major statistical issues.

Main Concerns

(1) The authors used a task in which rats must poke for a minimal amount of time (300 ms and then 1500 ms) to be able to obtain a drop of water delivered a few centimeters right below the nosepoke. They claim that their task is a time estimation task. However, they forget that they work with thirsty rats that are eager to get water sooner than later (there is a reason why they start by a short duration!). This task is mainly probing the animals ability to wait (that is impulse control) rather than time estimation per se. Second, the task does not require to estimate precise time because there appear to be no penalties when the nosepokes are too short or when they exceed. So it will be unclear if the variation in nosepoke reflects motivational changes rather than time estimation changes. The fact that this behavioral task is a poor assay for time estimation and rather reflects impulse control is shown by the tendency of animals to perform nose-pokes that are too short, the very slow improvement in their performance (Figure 1, with most of the mice making short responses), and the huge variability. Not only do the behavioral data not support the claim of the authors in terms of what the animals are actually doing (estimating time), but this also completely annihilates the interpretation of the Ca++ imaging data, which can be explained by motivational factors (changes in neuronal activity occurring while the animals nose poke may reflect a growing sens of urgency to check if water is available).

(2) A second issue is that the authors seem to assume that rats are perfectly immobile and perform like some kind of robots that would initiate nose pokes, maintain them, and remove them in a very discretized manner. However, in this kind of task, rats are constantly moving from the reward magazine to the nose poke. They also move while nose-poking (either their body or their mouth), and when they come out of the nose poke, they immediately move toward the reward spout. Thus, there is a continuous stream of movements, including fidgeting, that will covary with timing. Numerous studies have shown that sensorimotor dynamics influence neural activity, even in the prefrontal cortex. Therefore, the authors cannot rule out that what the records reflect are movements (and the scaling of movement) rather than underlying processes of time estimation (some kind of timer). Concretely, start cells could represent the ending of the movement going from the water spout to the nosepoke, and end cells could be neurons that initiate (if one can really isolate any initiation, which I doubt) the movement from the nosepoke to the water spout. Duration cells could reflect fidgeting or orofacial movements combined with an increasing urgency to leave the nose pokes.

(3) The statistics should be rethought for both the behavioral and neuronal data. They should be conducted separately for all the rats, as there is likely interindividual variability in the impulsivity of the animals.

(4) The fact that neuronal activity reflects an integration of movement and motivational factors rather than some abstract timing appears to be well compatible with the analysis conducted on the error trials (Figure 4), considering that the sensorimotor and motivational dynamics will rescale with the durations of the nose poke.

(5) The authors should mention upfront in the main text (result section) the temporal resolution allowed by their Ca+ probe and discuss whether it is fast enough in regard of behavioral dynamics occurring in the task.

Comments on the revised version

I have read the revised version of the manuscript and the rebuttal letter. My major concern was that the task used is not a time estimation task but primarily taps into impulse control and that animals are not immobile during the nose-poking epoch. I provided factual evidence for this (the animal's timing performance is poor and, on average, animals struggle to wait long enough), and I pointed to a review that discusses the results of many studies congruent with the importance of movement/motivation, not only in constraining the timing of reward-oriented actions during so-called time estimation tasks but also in powerfully modulating neuronal activity.

The authors' responses to my comments are puzzling and unconvincing. First, on the one hand, they acknowledge in their rebuttal letter the difficulty of demonstrating a neuronal representation of explicit internal estimation of time. Then, they seem to imply that this issue is beyond the scope of their study and focus in the rebuttal on whether the neuronal activity they report shows signs of being sensitive to movement and motivation, which they claim is independent of movement and motivation. This leads the authors to make no major changes in their manuscript. Their title, abstract, introduction, and discussion are largely unchanged and do not reflect the possibility that there are major confounding factors in so-called time estimation (rodents are not disembodied passive information processors) that may well explain some of the neuronal patterns. Evidently, the dismissive treatment by the authors is not satisfying. I will briefly restate my comments and reply to their responses and their new figure, which not only is unconvincing but raises new questions.

My comments were primarily focused on the behavioral task. The authors replied: "Studying the neural representation of any internal state may suffer from the same ambiguity [by ambiguity they meant that it is difficult to know if animals are explicitly estimating time]. With all due respect, however, we would like to limit our response to the scope of our results. According to the reviewer, two alternative interpretations of the task-related sequential activity exist." The authors imply that my comments are beyond the scope of their study. That is not true. My comments were targeted at the behavior of the animals, behavior they rely on to title their study: "Stable sequential dynamics in prefrontal cortex represents a subjective estimation of time." When I question whether the task and behavioral data presented are congruent with "subjective estimation of time," my comments are not beyond the scope of the study-they directly tackle the main point of the authors. Other researchers will read the title and abstract of this manuscript and conclude: "Here is a paper that provides evidence of a mechanism for animals estimating duration internally (because subjective time perception is assumed to be different from using clocks)." Still, there is a large body of literature showing that the behavior of animals in such tasks can be entirely explained without invoking subjective time perception and internal representation. How can the authors acknowledge that they can't be sure that mice are estimating time and then have such an affirmative title and abstract?

In my opinion, science is not just about forcing ideas (often reflecting philosophical preconceptions) on data and dismissing those who disagree. It is about discussing alternative possibilities fairly and being humble. In their revised version, I see no effort by the authors to investigate the importance of movement and motivation during their task or seriously engage with this idea. It's much easier to dismiss my comments as being beyond the scope of their results. According to the authors, it seems that movements and motivations play no role in the task. Still, the animals are water-restricted, and during the task, they will display decreased motivation (due to increased satiety), and their history of rewarded vs. non-rewarded trials will affect their behavior. This is one of the most robust effects seen across all behavioral studies. Moreover, the animals are constantly moving. Maybe the authors used a special breed of mice that behave like some kind of robots? I acknowledge that this is not easy to investigate, but if the authors did not use high-quality video recording or an experimental paradigm that allows disentangling motivational confounds, then they should refrain from using big words such as subjective time estimation and discuss alternative representations by acknowledging the studies that do find that movement and motivation are present during reward-based timing tasks and do in fact modulate neuronal activity, even in associative brain regions.

To sustain their claim that what they reported is movement-independent, the authors provided a supplementary figure in which they correlated neuronal activity and head movement tracked using DeepLabCut. I have to say that I was particularly surprised by this figure. First, in the original manuscript, there was absolutely no mention of video recording. Now it appears in the methods section, but the description is very short. There is no information on how these video recordings were made. The quality of the images provided in Figure S2 is far from reassuring. It is unclear whether the temporal and spatial resolution would be good enough to make meaningful correlations. Fast head/orofacial movements that occur during nose-poking can be on the order of 20 Hz. To be tracked, this would require at least a 40 Hz sampling rate. But no sampling information is provided. The authors should explain how they synchronized behavioral and neuronal data acquisition. Could the authors share behavioral videos of the 5 sessions shown in Figure S2 so we can judge the behavior of the animals, the quality of the video, and the possibility of making correlations?

Figure S2A-F: I am not sure why the authors correlated nose-poking duration (time estimation) and the duration between upper and lower nose-pokes (reward-oriented movement). It is not relevant to the issue I raised. Without any information about video acquisition frame rate, the y-axis legend (frame) is not very informative. Still, in Figure S2A-F, Rat 5 shows a clear increase in nose-poke duration, which is congruent with decreased impulsivity. Is the time coding different in this rat compared to other rats? There are some similar trends in other animals (Rat 1 and maybe Rat 3), but what is surprising is the huge variability (big downward deflections in the nose-poke duration). I would not be surprised if those deflections occurred after a long pause in activity. Could the authors plot trial time instead of trial number? How do the authors explain such a huge deflection if the animals are estimating time?

Regarding Figure S2H: I don't see how it addresses my concern. My concern is that some of the Ca activity recorded during nose-poking reflects head movements. The authors need to show if they can detect head movement during nose-poking. Aligning the Ca data relative to head movement should give the same result as when aligning the data relative to the time at which the animals pull out of the upper nose-poke.

Minor comments:

In their introduction, the authors wrote: "While these findings [correlates of time perception] provide strong evidence for a neural mechanism of time coding in the brain, true causal evidence at single-cell resolution remains beyond reach due to technical limitations. Although inhibiting certain brain regions (such as medial prefrontal cortex, mPFC,22) led to disruption in the performance of the timing task, it is difficult to attribute the effect specifically to the ramping or sequential activity patterns seen in those regions as other processes may be involved. Lacking direct experimental evidence, one potential way of testing the causal involvement of 'time codes' in time estimation function is to examine their correlation at a finer resolution."<br /> This statement is inaccurate at two levels. First, very good causal evidence has been obtained on this topic (see Monteiro et al., 2023, Nature Neuroscience), and see my News & Views on the strengths and weaknesses of this paper. Second, their proposal is inaccurate. Looking at a finer correlation will still be a correlative approach, and the authors will not be able to disentangle motor/motivation confounds.

cool imagery

Fantastic way to wrap up the writing. It explains so much of Kendrick's life and how he came to make "u" and "i." It's a full circle moment, and you nailed this whole thing right on the head! (Also, I appreciate the parenthesis explaining what you will do with the media; I think that would take this writing to an even higher level after its added!)

The official number of transgender people who attempt suicide hangs around 42%

Reviewer #2 (Public review):

In this study, Solyga and Keller use multimodal closed-loop paradigms in conjunction with multiphoton imaging of cortical responses to assess whether and how sensorimotor prediction errors in one modality influence the computation of prediction errors in another modality. Their work addresses an important open question pertaining to the relevance of non-hierarchical (lateral cortico-cortical) interactions in predictive processing within the neocortex.

Specifically, they monitor GCaMP6f responses of layer 2/3 neurons in the auditory cortex of head-fixed mice engaged in VR paradigms where running is coupled to auditory, visual, or audio-visual sensory feedback. The authors find strong auditory and motor responses in the auditory cortex, as well as weak responses to visual stimuli. Further, in agreement with previous work, they find that the auditory cortex responds to audiomotor mismatches in a manner similar to that observed in visual cortex for visuomotor mismatches. Most importantly, while visuomotor mismatches by themselves do not trigger significant responses in the auditory cortex, simultaneous coupling of audio-visual inputs to movement non-linearly enhances mismatch responses in the auditory cortex.

Their results thus suggest that prediction errors within a given sensory modality are non-trivially influenced by prediction errors from another modality. These findings are novel, interesting, and important, especially in the context of understanding the role of lateral cortico-cortical interactions and in outlining predictive processing as a general theory of cortical function.

Comments on revisions:

The authors thoroughly addressed the concerns raised. In my opinion, this has substantially strengthened the manuscript, enabling much clearer interpretation of the results reported. I commend the authors for the response to review. Overall, I find the experiments elegantly designed, and the results robust, providing compelling evidence for non-hierarchical interactions across neocortical areas and more specifically for the exchange of sensorimotor prediction error signals across modalities.

Reviewer #3 (Public review):

This study explores sensory prediction errors in sensory cortex. It focuses on the question of how these signals are shaped by non-hierarchical interactions, specifically multimodal signals arising from same level cortical areas. The authors used 2-photon imaging of mouse auditory cortex in head-fixed mice that were presented with sounds and/or visual stimuli while moving on a ball. First, responses to pure tones, visual stimuli and movement onset were characterized. Then, the authors made the running speed of the mouse predictive of sound intensity and/or visual flow (closed loop). Mismatches were created through the interruption of sound and/or visual flow for 1 second, disrupting the expected sensory signal. As a control, sensory stimuli recorded during the close loop phase were presented again decoupled from the movement (open loop). The authors suggest that auditory responses to the unpredicted interruption of the sound, which affected neither running speed nor pupil size, reflect mismatch responses. That these mismatch responses were enhanced when the visual flow was congruently interrupted, indicates cross-modal influence of prediction error signals.

This study's strengths are the relevance of the question and the design of the experiment. The authors are experts in the techniques used. The analysis explores neither the full power of the experimental design nor the population activity recorded with 2-photon, leaving open the question of to what extend what the authors call mismatch responses are not sensory responses to sound interruption (offset responses). The auditory system is sensitive to transitions and indeed responses to the interruption of the sound are similar in quality, if not quantity, in the predictive and the control situation.

Comments on revisions:

The incorporation of the analysis of the animal's running speed and the pupil size upon sound interruption improves the interpretation of the data. The authors can now conclude that responses to the mismatch are not due to behavioral effects.<br /> The issue of the relationship between mismatch responses and offset responses remains uncommented. The auditory system is sensitive to transitions, also to silence. See the work of the Linden or the Barkat labs (including the work of the first author of this manuscript) on offset responses, and also that of the Mesgarani lab (Khalighinejad et al., 2019) on responses to transitions 'to clean' (Figure 1c) in human auditory cortex. Offset responses, as the first author knows well, are modulated by intensity and stimulus length (after adaptation?). That responses to the interruption of the sound are similar in quality, if not quantity, in the closed and open loop conditions suggest that offset response might modulate the mismatch response. A mismatch response that reflects a break in predictability would presumably be less modulated by the exact details of the sensory input than an offset response. Therefore, what is the relationship between the mismatch response and the mean sound amplitude prior to the sound interruption (for example during the preceding 1 second)? And between the mismatch response and the mean firing rate over the same period?<br /> Finally, how do visual stimuli modulate sound responses in the absence of a mismatch? Is the multimodal response potentiation specific to a mismatch?

I like this sentence and think that it should be move further up in the paragraph. All the other things that have been said should be "evidence" for that statement.

I think this is a great topic sentence and like where it is however is sounds very similar to some of the things that you were saying in the intro. Because I think that, structural, this sentence fits better here its best to revise the intro paragraph to remove some of the more hyper-specific pieces of info to make room for this topic sentence to stand out.

It's a bit unclear whether or not this is your personal analysis of this line or the author's analysis of this line. Either way helps contribute to the overall argument, but it might be helpful to the reader to include who's analysis it is.

This is a bit of a run on to me and I believe there are some redundancies throughout. You might be able to rewrite it as "In her cover of 'Fight Song.' Bri Heart adds her own personality through different elements like riffs, note changes, staccatos, slides, and a breathier tone to the original"

How so? I understand the syncopation and palm muting contributes to the unpredictability, but I don't know how to make that connection in my head

Yes, it is true that there is a big connection behind the creation of the song "Greatest Love of All". However, is it possible to talk about the more direct connections there are musically? The current argument is that the producer just realized 'a connection', which is not the strongest connection to show.

Great imagery. This immediately sets the scene in my head and sets me to be immersed into your playlist.

I really like how you continued your descriptive wording at the end of the playlist as you do in the introduction. This idea of mentioning the reader's actions is really interesting since they are most likely encountering these things.

Bennett, as a fan of the Harriet novel and movie, this was such a creative and enjoyable project to read through.

In "Our Story," the way you vividly depict the emotions running through the runaway slave's head and connect each song to a different emotion (from fear to confidence to elation) really helps the story jump out of the page. I also liked how you wove in Harriet Tubman's role as a conductor on the Underground Railroad, integrating some factual history into a made-up story.

I think, overall, you integrated multimedia to the benefit of your project, especially in the "Connections" section, where hearing and seeing the films helped me understand your points about the connection between music and emotion. I think you could embed a Spotify playlist into "Our Story" so that the listener is truly immersed in the runaway slave's journey, and you could (not sure how feasible this is in Scalar) include pictures of Harriet Tubman directing real-life slaves to freedom so the reader has the visuals to match the pictures you paint with your words.

The only issue I have with the structure of this project is that sometimes, there aren't transitions between different pages, which makes the jump into different topics feel abrupt and disconnected. For example, I would suggest adding a transition sentence or two to the beginning of your last page, "Connections," so that the transition from the runaway slave story to the utilization of music in film to elicit certain emotions doesn't feel so sudden.

Most of my comments were minor, mainly about adding context about people you cite as sources, editing overly wordy sentences that could confuse readers, and fixing grammatical errors (such as capitalization).

One last nitpicky thing is that I noticed you use the word "delve" a lot in your writing. Maybe you could use some synonyms like "explore," "dive into," or "investigate," just to avoid redundancies and repetition.

Otherwise, you struck a great balance between visual elements and text on your site, and your prose is incredibly vivid and detailed. For example, I could imagine the Civil Rights Protestors marching right next to me and envision Harriet Tubman helping slaves escape to freedom.

Again, this project was so informative, and I loved how you weaved in so many different disciplines from history to film to music--and made it work well!

Reviewer #3 (Public review):

Summary:

Boffi and colleagues sought to quantify the single-trial, azimuthal information in the dorsal cortex of the inferior colliculus (DCIC), a relatively understudied subnucleus of the auditory midbrain. They accomplished this by using two complementary recording methods while mice passively listened to sounds at different locations: calcium imaging that recorded large neuronal populations but with poor temporal precision and multi-contact electrode arrays that recorded smaller neuronal populations with exact temporal precision. DCIC neurons respond variably, with inconsistent activity to sound onset and complex azimuthal tuning. Some of this variably was explained by ongoing head movements. The authors used a naïve Bayes decoder to probe the azimuthal information contained in the response of DCIC neurons on single trials. The decoder failed to classify sound location better than chance when using the raw population responses but performed significantly better than chance when using the top principal components of the population. Units with the most azimuthal tuning were distributed throughout the DCIC, possessed contralateral bias, and positively correlated responses. Interestingly, inter-trial shuffling decreased decoding performance, indicating that noise correlations contributed to decoder performance. Overall, Boffi and colleagues, quantified the azimuthal information available in the DCIC while mice passively listened to sounds, a first step in evaluating if and how the DCIC could contribute to sound localization.

Strengths:

The authors should be commended for collection of this dataset. When done in isolation (which is typical), calcium imaging and linear array recordings have intrinsic weaknesses. However, those weaknesses are alleviated when done in conjunction - especially when the data is consistent. This data set is extremely rich and will be of use for those interested in auditory midbrain responses to variable sound locations, correlations with head movements, and neural coding.

The DCIC neural responses are complex with variable responses to sound onset, complex azimuthal tuning and large inter-sound interval responses. Nonetheless, the authors do a decent job in wrangling these complex responses: finding non-canonical ways of determining dependence on azimuth and using interpretable decoders to extract information from the population.

Weaknesses:

The decoding results are a bit strange, likely because the population response is quite noisy on any given trial. Raw population responses failed to provide sufficient information concerning azimuth for significant decoding. Importantly, the decoder performed better than chance when certain principal components or top ranked units contributed but did not saturate with the addition of components or top ranked units. So, although there is azimuthal information in the recorded DCIC populations - azimuthal information appears somewhat difficult to extract.

Although necessary given the challenges associated with sampling many conditions with technically difficult recording methods, the limited number of stimulus repeats precludes interpretable characterization of the heterogeneity across the population. Nevertheless, the dataset is public so those interested can explore the diversity of the responses.

The observations from Boffi and colleagues raises the question: what drives neurons in the DCIC to respond? Sound azimuth appears to be a small aspect of the DCIC response. For example, the first 20 principal components which explain roughly 80% of the response variance are insufficient input for the decoder to predict sound azimuth above chance. Furthermore, snout and ear movements correlate with the population response in the DCIC (the ear movements are particularly peculiar given they seem to predict sound presentation). Other movements may be of particular interest to control for (e.g. eye movements are known to interact with IC responses in the primate). These observations, along with reported variance to sound onsets and inter-sound intervals, question the impact of azimuthal information emerging from DCIC responses. This is certainly out of scope for any one singular study to answer, but, hopefully, future work will elucidate the dominant signals in the DCIC population. It may be intuitive that engagement in a sound localization task may push azimuthal signals to the forefront of DCIC response, but azimuthal information could also easily be overtaken by other signals (e.g. movement, learning).

Boffi and colleagues set out to parse the azimuthal information available in the DCIC on a single trial. They largely accomplish this goal and are able to extract this information when allowing the units that contain more information about sound location to contribute to their decoding (e.g., through PCA or decoding on their activity specifically). Interestingly, they also found that positive noise correlations between units with similar azimuthal preferences facilitate this decoding - which is unusual given that this is typically thought to limit information. The dataset will be of value to those interested in the DCIC and to anyone interested in the role of noise correlations in population coding. Although this work is first step into parsing the information available in the DCIC, it remains difficult to interpret if/how this azimuthal information is used in localization behaviors of engaged mice.

Perfect introduction. I like how you incorporated the tips we got in class to "show not tell." Your prose is so descriptive and clear that I can really imagine the march in my head; it's as if I am there.

Reviewer #1 (Public review):

Summary:

This impressive study presents a comprehensive scRNAseq atlas of the cranial region during neural induction, patterning, and morphogenesis. The authors collected a robust scRNAseq dataset covering six distinct developmental stages. The analysis focused on the neural tissue, resulting in a highly detailed temporal map of neural plate development. The findings demonstrate how different cell fates are organized in specific spatial patterns along the anterior-posterior and medial-lateral axes within the developing neural tissue. Additionally, the research utilized high-density single-cell RNA sequencing (scRNAseq) to reveal intricate spatial and temporal patterns independent of traditional spatial techniques.

The investigation utilized diffusion component analysis to spatially order cells based on their positioning along the anterior-posterior axis, corresponding to the forebrain, midbrain, hindbrain, and medial-lateral axis. By cross-referencing with MGI expression data, the identification of cell types was validated, affirming the expression patterns of numerous known genes and implicating others as differentially expressed along these axes. These findings significantly advance our understanding of the spatially regulated genes in neural tissues during early developmental stages. The emphasis on transcription factors, cell surface, and secreted proteins provides valuable insights into the intricate gene regulatory networks underpinning neural tissue patterning. Analysis of a second scRNAseq dataset where Shh signaling was inhibited by culturing embryos in SAG identified known and previously unknown transcripts regulated by Shh, including the Wnt pathway.

The data includes the neural plate and captures all major cell types in the head, including the mesoderm, endoderm, non-neural ectoderm, neural crest, notochord, and blood. With further analyses, this high-quality data promises to significantly advance our understanding of how these tissues develop in conjunction with the neural tissue, paving the way for future breakthroughs in developmental biology and genomics.

Strengths:

The data is well presented in the figures and thoroughly described in the text. The quality of the scRNAseq data and bioinformatic analysis is exceptional.

Weaknesses:

No weaknesses were identified by this reviewer.

I get what you're saying here, but it might come across clearer if you italicized "it" so that the reader knows to place the emphasis on that word in their head instead of reading it as a grammatical error.

I think Johnson meant " You just humiliated us in front of the masses"

animals having emotional connections with their caregivers.

actual posted reply to https://old.reddit.com/r/Zettelkasten/comments/1gpx62s/is_a_zettelkasten_a_largely_unknown_form_of/

Taking too narrow a definition of zettelkasten is antithetical to the combinatorial creativity inherent in one of the zettelkasten's most important affordances.

OP was right on track, perhaps without knowing why... I appreciate that you scratch some of the historical surface, but an apple/tomato analogy is flimsy and the family tree is a lot closer. Too often we're ignoring the history of ars excerpendi, commonplacing, waste books, summas, early encyclopedias, etc. from the broad swath of intellectual history. What we now call a zettelkasten evolved very closely out of all these traditions. It's definitely not something that Luhmann suddenly invented one morning while lounging in the bath.

Stroll back a bit into the history to see what folks like Pliny the Elder, Konrad Gessner, Theodor Zwinger, Laurentius Beyerlink, or even the Brothers Grimm were doing centuries back and you'll realize it's all closer to a wide variety of heirloom apples and a modern Gala or Fuji. They were all broadly using zettelkasten methods in their work. Encyclopedias and dictionaries are more like sons and daughters, or viewed in other ways, maybe even parents to the zettelkasten. Almost everyone using them has different means and methods because their needs and goals are all different.

If you dig a bit you'll find fascinating tidbits like Samuel Hartlib describing early versions of "cut and paste" in 1641: “Zwinger made his excerpta by being using [sic] of old books and tearing whole leaves out of them, otherwise it had beene impossible to have written so much if every thing should have beene written or copied out.” (Talk about the collector's fallacy turned on its head!) As nice as Obsidian's new Web Clipper is this month, it's just another tool in a long line of tools that all do the same thing for much the same reasons.

Ignoring these contributions and their closeness means that you won't be able to take advantage of the various affordances all these methods in your own slip box, whichever form it takes. How will you ever evolve it into the paper machine that students a century hence are copying and mimicking and pontificating about in their generation's version of Reddit? Why couldn't a person's slip box have some flavor of an evolving encyclopedia? Maybe it's closer to Adler's Syntopicon? Maybe something different altogether for their particular use?

Those interested in expanding their practice might try some of the following for more details:

• Blair, Ann M. Too Much to Know: Managing Scholarly Information before the Modern Age. Yale University Press, 2010. https://yalebooks.yale.edu/book/9780300165395/too-much-know.
• Krajewski, Markus. Paper Machines: About Cards & Catalogs, 1548-1929. Translated by Peter Krapp. History and Foundations of Information Science. MIT Press, 2011. https://mitpress.mit.edu/books/paper-machines.
• Wright, Alex. Cataloging the World: Paul Otlet and the Birth of the Information Age. 1st ed. Oxford, New York: Oxford University Press, 2014.

For deeper dives on methods, try: https://www.zotero.org/groups/4676190/tools_for_thought/tags/note%20taking%20manuals/items/F8WSEABT/item-list

cc: u/JasperMcGee u/dasduvish u/Quack_quack_22

Hes waiting for someone or something.

This was the perception that was implemented in society and i'm happy to see that in ways things have changed in the way we look at things in school. One thing i've seen as I work in a school is i know we do not go based off genders of doing what they would do to us from girls to boys. Another thing i can add and a new law basically implemented in schools so kids would feel left out is if they have head lice, crazy to think that the automatic answers are to keep them home until they're clean and now we are not allowed to send them home so they won't feel any kind of way.

The Iambic tetrameter here establishes a steady, calming rhythm, reflecting peaceful unity of lovers. The image of the pillow on the bed creates a sense of comfort and intimacy- physical closeness

Reviewer #1 (Public review):

This study is part of an ongoing effort to clarify the effects of cochlear neural degeneration (CND) on auditory processing in listeners with normal audiograms. This effort is important because ~10% of people who seek help for hearing difficulties have normal audiograms and current hearing healthcare has nothing to offer them.

The authors identify two shortcomings in previous work that they intend to fix. The first is a lack of cross-species studies that make direct comparisons between animal models in which CND can be confirmed and humans for which CND must be inferred indirectly. The second is the low sensitivity of purely perceptual measures to subtle changes in auditory processing. To fix these shortcomings, the authors measure envelope following responses (EFRs) in gerbils and humans using the same sounds, while also performing histological analysis of the gerbil cochleae, and testing speech perception while measuring pupil size in the humans.

The study begins with a comprehensive assessment of the hearing status of the human listeners. The only differences found between the young adult (YA) and middle-aged (MA) groups are in thresholds at frequencies > 10 kHz and DPOAE amplitudes at frequencies > 5 kHz. The authors then present the EFR results, first for the humans and then for the gerbils, showing that amplitudes decrease more rapidly with increasing envelope frequency for MA than for YA in both species. The histological analysis of the gerbil cochleae shows that there were, on average, 20% fewer IHC-AN synapses at the 3 kHz place in MA relative to YA, and the number of synapses per IHC was correlated with the EFR amplitude at 1024 Hz.

The study then returns to the humans to report the results of the speech perception tests and pupillometry. The correct understanding of keywords decreased more rapidly with decreasing SNR in MA than in YA, with a noticeable difference at 0 dB, while pupillary slope (a proxy for listening effort) increased more rapidly with decreasing SNR for MA than for YA, with the largest differences at SNRs between 5 and 15 dB. Finally, the authors report that a linear combination of audiometric threshold, EFR amplitude at 1024 Hz, and a few measures of pupillary slope is predictive of speech perception at 0 dB SNR.

I only have two questions/concerns about the specific methodologies used:

(1) Synapse counts were made only at the 3 kHz place on the cochlea. However, the EFR sounds were presented at 85 dB SPL, which means that a rather large section of the cochlea will actually be excited. Do we know how much of the EFR actually reflects AN fibers coming from the 3 kHz place? And are we sure that this is the same for gerbils and humans given the differences in cochlear geometry, head size, etc.?

(2) Unless I misunderstood, the predictive power of the final model was not tested on held-out data. The standard way to fit and test such a model would be to split the data into two segments, one for training and hyperparameter optimization, and one for testing. But it seems that the only split was for training and hyperparameter optimization.

While I find the study to be generally well executed, I am left wondering what to make of it all. The purpose of the study with respect to fixing previous methodological shortcomings was clear, but exactly how fixing these shortcomings has allowed us to advance is not. I think we can be more confident than before that EFR amplitude is sensitive to CND, and we now know that measures of listening effort may also be sensitive to CND. But where is this leading us?

I think what this line of work is eventually aiming for is to develop a clinical tool that can be used to infer someone's CND profile. That seems like a worthwhile goal but getting there will require going beyond exploratory association studies. I think we're ready to start being explicit about what properties a CND inference tool would need to be practically useful. I have no idea whether the associations reported in this study are encouraging or not because I have no idea what level of inferential power is ultimately required.

That brings me to my final comment: there is an inappropriate emphasis on statistical significance. The sample size was chosen arbitrarily. What if the sample had been half the size? Then few, if any, of the observed effects would have been significant. What if the sample had been twice the size? Then many more of the observed effects would have been significant (particularly for the pupillometry). I hope that future studies will follow a more principled approach in which relevant effect sizes are pre-specified (ideally as the strength of association that would be practically useful) and sample sizes are determined accordingly.

So, in summary, I think this study is a valuable but limited advance. The results increase my confidence that non-invasive measures can be used to infer underlying CND, but I am unsure how much closer we are to anything that is practically useful.

Author response:

eLife Assessment

This valuable study uses consensus-independent component analysis to highlight transcriptional components (TC) in high-grade serous ovarian cancers (HGSOC). The study presents a convincing preliminary finding by identifying a TC linked to synaptic signaling that is associated with shorter overall survival in HGSOC patients, highlighting the potential role of neuronal interactions in the tumor microenvironment. This finding is corroborated by comparing spatially resolved transcriptomics in a small-scale study; a weakness is in being descriptive, non-mechanistic, and requiring experimental validation.

We sincerely thank the editors for the valuable and constructive feedback. We appreciate the recognition of our findings and the significance of identifying transcriptional components in high-grade serous ovarian cancers. We acknowledge the insightful point on our study's descriptive nature and limited mechanistic depth. While further experimental validation would indeed enhance our conclusions, such work extends beyond the current scope of this manuscript. However, we would like to highlight that mechanistic studies demonstrating the impact of tumor-infiltrating nerves on disease progression are emerging (Zahalka et al., 2017; Allen et al., 2018; Balood et al., 2022; Jin et al., 2022; Globig et al., 2023; Restaino et al., 2023; Darragh et al., 2024). Importantly, members of our group have contributed to these findings. These studies, including in vitro and in vivo work in head and neck squamous cell carcinoma as well as high-grade serous ovarian carcinoma, demonstrate that substance P released from tumor-infiltrating nociceptors potentiates MAP kinase signaling in cancer cells, thereby influencing disease progression. This effect can be mitigated in vivo by blocking the substance P receptor (Restaino et al., 2023). Our present work identifies a transcriptional component that aligns with the presence of functional nerves within malignancies. These published mechanistic studies support our findings and suggest that this transcriptional component could serve as a potential screening tool to identify innervated tumors. Such information is clinically relevant, as patients with innervated tumors may benefit from more aggressive therapy.

Reviewer #1 (Public review):

This manuscript explores the transcriptional landscape of high-grade serous ovarian cancer (HGSOC) using consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs) associated with patient outcomes. The study analyzes 678 HGSOC transcriptomes, supplemented with 447 transcriptomes from other ovarian cancer types and noncancerous tissues. By identifying 374 TCs, the authors aim to uncover subtle transcriptional patterns that could serve as novel drug targets. Notably, a transcriptional component linked to synaptic signaling was associated with shorter overall survival (OS) in patients, suggesting a potential role for neuronal interactions in the tumor microenvironment. Given notable weaknesses like lack of validation cohort or validation using another platform (other than the 11 samples with ST), the data is considered highly descriptive and preliminary.

Strengths:

(1) Innovative Methodology:

The use of c-ICA to dissect bulk transcriptomes into independent components is a novel approach that allows for the identification of subtle transcriptional patterns that may be overshadowed in traditional analyses.

We sincerely thank the reviewer for recognizing the strengths and novelty of our study. We appreciate the positive feedback on our use of consensus-independent component analysis (c-ICA) to decompose bulk transcriptomes, which we believe allowed us to detect subtle transcriptional signals often overlooked in traditional analyses.

(2) Comprehensive Data Integration:

The study integrates a large dataset from multiple public repositories, enhancing the robustness of the findings. The inclusion of spatially resolved transcriptomes adds a valuable dimension to the analysis.

Thank you for recognizing the robustness of our study through comprehensive data integration. We appreciate the acknowledgment of our efforts to leverage a large, multi-source dataset, as well as the additional insights gained from spatially resolved transcriptomes. We believe this integrative approach enhances the depth of our analysis and contributes to a more nuanced understanding of the tumor microenvironment.

(3) Clinical Relevance:

The identification of a synaptic signaling-related TC associated with poor prognosis highlights a potential new avenue for therapeutic intervention, emphasizing the role of the tumor microenvironment in cancer progression.

We appreciate the reviewer’s recognition of the clinical implications of our findings. The identification of a synaptic signaling-related transcriptional component associated with poor prognosis underscores the potential for novel therapeutic targets within the tumor microenvironment. We agree that this insight could open new avenues for intervention and further highlights the role of neuronal interactions in cancer progression.

Weaknesses:

(1) Mechanistic Insights:

While the study identifies TCs associated with survival, it provides limited mechanistic insights into how these components influence cancer progression. Further experimental validation is necessary to elucidate the underlying biological processes.

We appreciate the reviewer’s point regarding the limited mechanistic insights provided in our study. We agree that further experimental validation would enhance our understanding of how the biology captured by these transcriptional components influence cancer progression. However, we respectfully note that such validation is beyond the current scope of this article.   Our current analyses are done on publicly available expression array and spatial transcriptomic array datasets. For future studies, we therefore intend to combine spatial transcriptomic data with immunohistochemical analysis of the same tumors for validation purposes. We have started with setting up in vitro cocultures of neurons and ovarian cancer cells to obtain mechanistic insight in how genes with a large weight in TC121 regulate synaptic signaling and how that affects ovarian cancer cells.

(2) Generalizability:

The findings are primarily based on transcriptomic data from HGSOC. It remains unclear how these results apply to other subtypes of ovarian cancer or different cancer types.

In Figure 5, we present the activity of TC121 across various cancer types, demonstrating broader applicability. However, due to limited treatment response data, we were unable to assess associations between TC activity scores and patient response. Additionally, transcriptomic and survival data specific to other ovarian cancer subtypes beyond HGSOC are currently not available, limiting our ability to generalize these findings to those groups. We intend to leverage survival data from TCGA to explore associations between TC activity scores and overall survival of patients with other cancer types. Nonetheless, we recognize limitations with TCGA survival data, as outlined in this article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8726696/.

(3) Innovative Methodology:

Requires more validation using different platforms (IHC) to validate the performance of this bulk-derived data. Also, the lack of control over data quality is a concern.

We acknowledge the reviewer’s suggestion to validate our results with alternative platforms, such as IHC; however, we regret that such validation is beyond the scope of this article. Regarding data quality control, we implemented a series of checks:

• Bulk Transcriptional Profiles: We applied principal component analysis (PCA) on the sample Pearson product-moment correlation matrix, focusing on the first principal component (PCqc), which accounted for approximately 80-90% of the variance, primarily reflecting technical rather than biological variability  (Bhattacharya et al., 2020). Samples with a correlation below 0.8 with PCqc were removed as outliers. Additionally, we generated unique MD5 hashes for each CEL file to identify and exclude duplicate samples. Per gene, expression values were standardized to a mean of zero and a variance of one across the GEO, CCLE, GDSC, and TCGA datasets to minimize probeset- or gene-specific variability.

• Spatial Transcriptional Profiles: We used PCA for quality control here as well, retained samples only if their loading factors for the first principal component showed consistent signs across all profiles (i.e., all profiles had either positive or negative loading factors for the first PC) from that individual spatial transcriptomic sample. Samples that did not meet this criterion were excluded from analyses.

(4) Clinical Application:

Although the study suggests potential drug targets, the translation of these findings into clinical practice is not addressed. Probably given the lack of some QA/QC procedures it'll be hard to translate these results. Future studies should focus on validating these targets in clinical settings.

While this study is exploratory in nature, we agree that future studies should focus on validating these potential drug targets in clinical settings. As suggested, QA/QC procedures were integral to our analyses. We applied rigorous quality control, including PCA-based checks and duplicate removal across datasets, to ensure data integrity (detailed in our previous response).

In terms of clinical application, which we partially discussed in the manuscript, we will discuss additional strategies to prevent synaptic signaling and neurotransmitter release in the tumor microenvironment (TME). Drugs such as ifenprodil and lamotrigine are used in treating neuronal disorders to block glutamate release responsible for subsequent synaptic signaling, whereas the vesicular monoamine transporter (VMAT) inhibitor reserpine can block the formation of synaptic vesicles (Reid et al., 2013; Williams et al., 2001). Previous in vitro studies with HGSOC cell lines showed a significant effect of ifenprodil alone on cancer cell proliferation, whereas reserpine seemed to trigger apoptosis in cancer cells (North et al., 2015; Ramamoorthy et al., 2019). Such strategies could potentially be used to inhibit synaptic neurotransmission in the TME.

Reviewer #2 (Public review):

Summary:

Consensus-independent component analysis and closely related methods have previously been used to reveal components of transcriptomic data that are not captured by principal component or gene-gene coexpression analyses.

Here, the authors asked whether applying consensus-independent component analysis (c-ICA) to published high-grade serous ovarian cancer (HGSOC) microarray-based transcriptomes would reveal subtle transcriptional patterns that are not captured by existing molecular omics classifications of HGSOC.

Statistical associations of these (hitherto masked) transcriptional components with prognostic outcomes in HGSOC could lead to additional insights into underlying mechanisms and, coupled with corroborating evidence from spatial transcriptomics, are proposed for further investigation.

This approach is complementary to existing transcriptomics classifications of HGSOC.

The authors have previously applied the same approach in colorectal carcinoma (Knapen et al. (2024) Commun. Med).

Strengths:

(1) Overall, this study describes a solid data-driven description of c-ICA-derived transcriptional components that the authors identified in HGSOC microarray transcriptomics data, supported by detailed methods and supplementary documentation.

We thank the reviewer for acknowledging the strength of our data-driven approach and the use of consensus-independent component analysis (c-ICA) to identify transcriptional components within HGSOC microarray data. We aimed to provide comprehensive methodological detail and supplementary documentation to support the reproducibility and robustness of our findings. We believe this approach allows for the identification of subtle transcriptional signals that might be overlooked by traditional analysis methods.

(2) The biological interpretation of transcriptional components is convincing based on (data-driven) permutation analysis and a suite of analyses of association with copy-number, gene sets, and prognostic outcomes.

We appreciate the reviewer’s positive feedback on the biological interpretation of our transcriptional components. We are pleased that our approach, which includes data-driven permutation testing and analyses of associations with copy-number alterations, gene sets, and prognostic outcomes, was found convincing. These analyses were integral to enhancing the robustness and biological relevance of our findings.

(3) The resulting annotated transcriptional components have been made available in a searchable online format.

Thank you for acknowledging the availability of our annotated transcriptional components in a searchable online format.

(4) For the highlighted transcriptional component which has been annotated as related to synaptic signalling, the detection of the transcriptional component among 11 published spatial transcriptomics samples from ovarian cancers appears to support this preliminary finding and requires further mechanistic follow-up.

Thank you for acknowledging the accessibility of our annotated transcriptional components. We prioritized making these data available in a searchable online format to facilitate further research and enable the community to explore and validate our findings.

Weaknesses:

(1) This study has not explicitly compared the c-ICA transcriptional components to the existing reported transcriptional landscape and classifications for ovarian cancers (e.g. Smith et al Nat Comms 2023; TCGA Nature 2011; Engqvist et al Sci Rep 2020) which would enable a further assessment of the additional contribution of c-ICA - whether the c-ICA approach captured entirely complementary components, or whether some components are correlated with the existing reported ovarian transcriptomic classifications.

We appreciate the reviewer’s insightful suggestion to compare our c-ICA-derived transcriptional components with previously reported ovarian cancer classifications, such as those from Smith et al. (2023), TCGA (2011), and Engqvist et al. (2020). To address this, we will incorporate analyses comparing the activity scores of our transcriptional components with these published landscapes and classifications, particularly focusing on any associations with overall survival. Additionally, we plan to evaluate correlations between gene signatures from these studies and our identified TCs, enhancing our understanding of the unique contributions of the c-ICA approach.

(2) Here, the authors primarily interpret the c-ICA transcriptional components as a deconvolution of bulk transcriptomics due to the presence of cells from tumour cells and the tumour microenvironment. However, c-ICA is not explicitly a deconvolution method with respect to cell types: the transcriptional components do not necessarily correspond to distinct cell types, and may reflect differential dysregulation within a cell type. This application of c-ICA for the purpose of data-driven deconvolution of cell populations is distinct from other deconvolution methods that explicitly use a prior cell signature matrix.

Thank you for highlighting this nuanced aspect of c-ICA interpretation. We acknowledge that c-ICA, unlike traditional deconvolution methods, is not specifically designed for cell-type deconvolution and does not rely on a predefined cell signature matrix. While we explored the transcriptional components in the context of tumor and microenvironmental interactions, we agree that these components may not correspond directly to distinct cell types but rather reflect complex patterns of dysregulation, potentially within individual cell populations.

Our goal with c-ICA was to uncover hidden transcriptional patterns possibly influenced by cellular heterogeneity. However, we recognize these patterns may also arise from regulatory processes within a single cell type. To investigate further, we plan to use single-cell transcriptional data (~60,000 cell-types annotated profiles from GSE158722) and project our transcriptional components onto these profiles to obtain activity scores, allowing us to assess each TC’s behavior across diverse cellular contexts after removing the first principal component to minimize background effects.

References

Allen JK, Armaiz-Pena GN, Nagaraja AS, Sadaoui NC, Ortiz T, Dood R, Ozcan M, Herder DM, Haemerrle M, Gharpure KM, Rupaimoole R, Previs R, Wu SY, Pradeep S, Xu X, Han HD, Zand B, Dalton HJ, Taylor M, Hu W, Bottsford-Miller J, Moreno-Smith M, Kang Y, Mangala LS, Rodriguez-Aguayo C, Sehgal V, Spaeth EL, Ram PT, Wong ST, Marini FC, Lopez-Berestein G, Cole SW, Lutgendorf SK, diBiasi M, Sood AK. 2018. Sustained adrenergic signaling promotes intratumoral innervation through BDNF induction. Cancer Res 78:canres.1701.2016.

Balood M, Ahmadi M, Eichwald T, Ahmadi A, Majdoubi A, Roversi Karine, Roversi Katiane, Lucido CT, Restaino AC, Huang S, Ji L, Huang K-C, Semerena E, Thomas SC, Trevino AE, Merrison H, Parrin A, Doyle B, Vermeer DW, Spanos WC, Williamson CS, Seehus CR, Foster SL, Dai H, Shu CJ, Rangachari M, Thibodeau J, Rincon SVD, Drapkin R, Rafei M, Ghasemlou N, Vermeer PD, Woolf CJ, Talbot S. 2022. Nociceptor neurons affect cancer immunosurveillance. Nature 611:405–412.

Bhattacharya A, Bense RD, Urzúa-Traslaviña CG, Vries EGE de, Vugt MATM van, Fehrmann RSN. 2020. Transcriptional effects of copy number alterations in a large set of human cancers. Nat Commun 11:715.

Darragh LB, Nguyen A, Pham TT, Idlett-Ali S, Knitz MW, Gadwa J, Bukkapatnam S, Corbo S, Olimpo NA, Nguyen D, Court BV, Neupert B, Yu J, Ross RB, Corbisiero M, Abdelazeem KNM, Maroney SP, Galindo DC, Mukdad L, Saviola A, Joshi M, White R, Alhiyari Y, Samedi V, Bokhoven AV, John MSt, Karam SD. 2024. Sensory nerve release of CGRP increases tumor growth in HNSCC by suppressing TILs. Med 5:254-270.e8.

Globig A-M, Zhao S, Roginsky J, Maltez VI, Guiza J, Avina-Ochoa N, Heeg M, Hoffmann FA, Chaudhary O, Wang J, Senturk G, Chen D, O’Connor C, Pfaff S, Germain RN, Schalper KA, Emu B, Kaech SM. 2023. The β1-adrenergic receptor links sympathetic nerves to T cell exhaustion. Nature 622:383–392.

Jin M, Wang Y, Zhou T, Li W, Wen Q. 2022. Norepinephrine/β2-adrenergic receptor pathway promotes the cell proliferation and nerve growth factor production in triple-negative breast cancer. J Breast Cancer 26:268–285.

eLife Assessment

This valuable study combined whole-head magnetoencephalography (MEG) and subthalamic (STN) local field potential (LFP) recordings in patients with Parkinson's disease undergoing deep brain stimulation surgery. The paper provides solid evidence that cortical and STN beta oscillations are sensitive to movement context and may play a role in the coordination of movement redirection.

Reviewer #1 (Public review):

Summary:

Winkler et al. present brain activity patterns related to complex motor behaviour by combining whole-head magnetoencephalography (MEG) with subthalamic local field potential (LFP) recordings from people with Parkinson's disease. The motor task involved repetitive circular movements with stops or reversals associated with either predictable or unpredictable cues. Beta and gamma frequency oscillations are described, and the authors found complex interactions between recording sites and task conditions. For example, they observed stronger modulation of connectivity in unpredictable conditions. Moreover, STN power varied across patients during reversals, which differed from stopping movements. The authors conclude that cortex-STN beta modulation is sensitive to movement context, with potential relevance for movement redirection.

Strengths:

This study employs a unique methodology, leveraging the rare opportunity to simultaneously record both invasive and non-invasive brain activity to explore oscillatory networks.

Weaknesses:

It is difficult to interpret the role of the STN in the context of reversals because no consistent activity pattern emerged.

Reviewer #1 (Public review):

Summary:

The study by Hu et al. investigated the role of olfactory ErbB4 in regulating olfactory information processing. The authors demonstrated that ErbB4 deletion impairs odor discrimination, sensitivity, habituation, and dishabituation by using an impressive combination of techniques from morphological to electrophysiology (both slice and in vivo) and from viral injection to cell-type-specific mutation to behavioral analysis. The findings underscore the crucial role of ErbB4 in olfactory PV neurons in modulating mitral cell function and odor perception.

Strengths:

This study contains a pretty comprehensive set of experiments.

Major concerns:

(1) Line 151 page 7, "PV-Erbb4+/+ mice (generated by crossing PV-Cre mice (Wen et al., 2010) with loxP flanked Erbb4 mice". Does this mean mice carrying PV-Cre and ErbB4 floxed allele? Or with the WT allele? This is confusing. Figures 2B and 2C, ErbB4 expression was evident in many cells that were not positive for PV. What are the identities of those cells? Are they important?

(2) In Figure 4, the authors performed tetrode recordings in awake head-fixed animals. Although individual neuron spikes could be obtained by spike-sorting, this is not a "single-unit" experiment due to the nature of this approach.

What is the odor used in Figure 4? How did the authors clean up the odor to limit the stimulation within 2 seconds? In what layer were the tetrodes placed? What is the putative cell type presented in Figure 4C? If Figure 4C is a representative neuron recorded, the odor-induced suppression of spike activity seems to be impaired in PV-ErbB4-/- animals. However, Figure 4D shows that suppressed neurons were similar between the two types of animals. Such comparisons among individual mice are difficult for in vivo electrophysiological experiments because the recorded cell type and placement of electrodes would be different. The authors should apply ErbB4 inhibitors to the same animals and compare the effects before and after. This would ensure the recoding of the same population of neurons.

(3) At a glance in the heatmap in Figure 4D, excited neurons were reduced in PV-ErbB4-/- mice, but not inhibited neurons. This was different from Figure 4L. The authors need to have a criteria or threshold to show how they categorized each population.

(4) Figure 4D, 4F and 4J seemed to be inconsistent. In Figure 4D before odor, there was no clear increase in the spontaneous activity in PV-ErbB4-/- mice; in Figure 4F-4G and 4J-4K, clearly, there was a high spontaneous activity in PV-ErbB4-/- mice.

(5) What are the neurons recorded in Figure 6E-6F? If they were MCs, loss of ErbB4 in PV neurons should not alter their intrinsic electrical properties. Rather GABAergic inputs could be altered. Indeed, the authors presented a reduction of GABAergic inputs from PV neurons to MCs.

(6) Figure 8E-8H, a better experiment would be specifically expressing ErbB4 or PV neurons. In Figure 8F and Figure 8I, was it the excitability after the current injection? Why not perform the spontaneous activity recording?

Literally the actual policy logic of gup. Most important piece of code right here for gup

eLife Assessment

This is a valuable work that convincingly reveals that place cells in the hippocampus that exhibit repeated firing fields incorporate information about non-positional variables in each firing field. They reveal that individual firing fields of a single place cell can exhibit tuning to different head orientations, suggesting hippocampal neurons are flexible in terms of how they incorporate non-positional inputs.

I don't know if this is necessary, depending on the audience, but it might be relevant to define what head voice is?

eLife Assessment

This valuable study investigates how the neural representation of individual finger movements changes during the early period of sequence learning. By combining a new method for extracting features from human magnetoencephalography data and decoding analyses, the authors provide incomplete evidence of an early, swift change in the brain regions correlated with sequence learning, including a set of previously unreported frontal cortical regions. The addition of more control analyses to rule out that head movement artefacts influence the findings, and to further explain the proposal of offline contextualization during short rest periods as the basis for improvement performance would strengthen the manuscript.

Reviewer #1 (Public review):

Summary:

This study addresses the issue of rapid skill learning and whether individual sequence elements (here: finger presses) are differentially represented in human MEG data. The authors use a decoding approach to classify individual finger elements, and accomplish an accuracy of around 94%. A relevant finding is that the neural representations of individual finger elements dynamically change over the course of learning. This would be highly relevant for any attempts to develop better brain machine interfaces - one now can decode individual elements within a sequence with high precision, but these representations are not static but develop over the course of learning.

Strengths:

The work follows a large body of work from the same group on the behavioural and neural foundations of sequence learning. The behavioural task is well established and neatly designed to allow for tracking learning and how individual sequence elements contribute. The inclusion of short offline rest periods between learning epochs has been influential because it has revealed that a lot, if not most of the gains in behaviour (ie speed of finger movements) occur in these so-called micro-offline rest periods.

The authors use a range of new decoding techniques, and exhaustively interrogate their data in different ways, using different decoding approaches. Regardless of the approach, impressively high decoding accuracies are observed, but when using a hybrid approach that combines the MEG data in different ways, the authors observe decoding accuracies of individual sequence elements from the MEG data of up to 94%.

Weaknesses:

There are a few concerns which the authors may well be able to resolve. These are not weaknesses as such, but factors that would be helpful to address as these concern potential contributions to the results that one would like to rule out.

Regarding the decoding results shown in Figure 2 etc, a concern is that within individual frequency bands, the highest accuracy seems to be within frequencies that match the rate of keypresses. This is a general concern when relating movement to brain activity, so is not specific to decoding as done here. As far as reported, there was no specific restraint to the arm or shoulder, and even then it is conceivable that small head movements would correlate highly with the vigor of individual finger movements. This concern is supported by the highest contribution in decoding accuracy being in middle frontal regions - midline structures that would be specifically sensitive to movement artefacts and don't seem to come to mind as key structures for very simple sequential keypress tasks such as this - and the overall pattern is remarkably symmetrical (despite being a unimanual finger task) and spatially broad. This issue may well be matching the time course of learning, as the vigor and speed of finger presses will also influence the degree to which the arm/shoulder and head move.

This is not to say that useful information is contained within either of the frequencies or broadband data. But it raises the question of whether a lot is dominated by movement "artefacts" and one may get a more specific answer if removing any such contributions.

A somewhat related point is this: when combining voxel and parcel space, a concern is whether a degree of circularity may have contributed to the improved accuracy of the combined data, because it seems to use the same MEG signals twice - the voxels most contributing are also those contributing most to a parcel being identified as relevant, as parcels reflect the average of voxels within a boundary. In this context, I struggled to understand the explanation given, ie that the improved accuracy of the hybrid model may be due to "lower spatially resolved whole-brain and higher spatially resolved regional activity patterns". Firstly, there will be a relatively high degree of spatial contiguity among voxels because of the nature of the signal measured, ie nearby individual voxels are unlikely to be independent. Secondly, the voxel data gives a somewhat misleading sense of precision; the inversion can be set up to give an estimate for each voxel, but there will not just be dependence among adjacent voxels, but also substantial variation in the sensitivity and confidence with which activity can be projected to different parts of the brain. Midline and deeper structures come to mind, where the inversion will be more problematic than for regions along the dorsal convexity of the brain, and a concern is that in those midline structures, the highest decoding accuracy is seen.

Some of these concerns could be addressed by recording head movement (with enough precision) to regress out these contributions. The authors state that head movement was monitored with 3 fiducials, and their timecourses ought to provide a way to deal with this issue. The ICA procedure may not have sufficiently dealt with removing movement-related problems, but one could eg relate individual components that were identified to the keypresses as another means for checking. An alternative could be to focus on frequency ranges above the movement frequencies. The accuracy for those still seems impressive, and may provide a slightly more biologically plausible assessment.

One question concerns the interpretation of the results shown in Figure 4. They imply that during the course of learning, entirely different brain networks underpin the behaviour. Not only that, but they also include regions that would seem rather unexpected to be key nodes for learning and expressing relatively simple finger sequences, such as here. What then is the biological plausibility of these results? The authors seem to circumnavigate this issue by moving into a distance metric that captures the (neural network) changes over the course of learning, but the discussion seems detached from which regions are actually involved; or they offer a rather broad discussion of the anatomical regions identified here, eg in the context of LFOs, where they merely refer to "frontoparietal regions".

If I understand correctly, the offline neural representation analysis is in essence the comparison of the last keypress vs the first keypress of the next sequence. In that sense, the activity during offline rest periods is actually not considered. This makes the nomenclature somewhat confusing. While it matches the behavioural analysis, having only key presses one can't do it in any other way, but here the authors actually do have recordings of brain activity during offline rest. So at the very least calling it offline neural representation is misleading to this reviewer because what is compared is activity during the last and during the next keypress, not activity during offline periods. But it also seems a missed opportunity - the authors argue that most of the relevant learning occurs during offline rest periods, yet there is no attempt to actually test whether activity during this period can be useful for the questions at hand here.

I don't think so

Garrick's multiple revivals of Shakespeare as a playwright, head of Drury Lane, and an extremely popular actor kept his works alive

Author response:

eLife Assessment

This valuable study reveals extensive binding of eukaryotic translation initiation factor 3 (eIF3) to the 3' untranslated regions (UTRs) of efficiently translated mRNAs in human pluripotent stem cell-derived neuronal progenitor cells. The authors provide solid evidence to support their conclusions, although this study may be enhanced by addressing potential biases of techniques employed to study eIF3:mRNA binding and providing additional mechanistic detail. This work will be of significant interest to researchers exploring post-transcriptional regulation of gene expression, including cellular, molecular, and developmental biologists, as well as biochemists.

We thank the reviewers for their positive views of the results we present, along with the constructive feedback regarding the strengths and weaknesses of our manuscript, with which we generally agree. We acknowledge our results will require a deeper exploration of the molecular mechanisms behind eIF3 interactions with 3'-UTR termini and experiments to identify the molecular partners involved. Additionally, given that NPC differentiation toward mature neurons is a process that takes around 3 weeks, we recognize the importance of examining eIF3-mRNA interactions in NPCs that have undergone differentiation over longer periods than the 2-hr time point selected in this study. Finally, considering the molecular complexity of the 13-subunit human eIF3, we agree that a direct comparison between Quick-irCLIP and PAR-CLIP will be highly beneficial and will determine whether different UV crosslinking wavelengths report on different eIF3 molecular interactions. Additional comments are given below to the identified weaknesses.

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors perform irCLIP of neuronal progenitor cells to profile eIF3-RNA interactions upon short-term neuronal differentiation. The data shows that eIF3 mostly interacts with 3'-UTRs - specifically, the poly-A signal. There appears to be a general correlation between eIF3 binding to 3'-UTRs and ribosome occupancy, which might suggest that eIF3 binding promotes protein synthesis, possibly through inducing mRNA closed-loop formation.

Strengths:

The study provides a wealth of new data on eIF3-mRNA interactions and points to the potential new concept that eIF3-mRNA interactions are polyadenylation-dependent and correlate with ribosome occupancy.

Weaknesses:

(1) A main limitation is the correlative nature of the study. Whereas the evidence that eIF3 interacts with 3-UTRs is solid, the biological role of the interactions remains entirely unknown. Similarly, the claim that eIF3 interactions with 3'-UTR termini require polyadenylation but are independent of poly(A) binding proteins lacks support as it solely relies on the absence of observable eIF3 binding to poly-A (-) histone mRNAs and a seeming failure to detect PABP binding to eIF3 by co-immunoprecipitation and Western blotting. In contrast, LC-MS data in Supplementary File 1 show ready co-purification of eIF3 with PABP.

We agree the molecular mechanisms underlying the crosslinking between eIF3 and the end of mRNA 3’-UTRs remains to be determined. We also agree that the lack of interaction seen between eIF3 and PABP in Westerns, even from HEK293T cells, is a puzzle. The low sequence coverage in the LC-MS data gave us pause about making a strong statement that these represent direct eIF3 interactions, given the similar background levels of some ribosomal proteins.

(2) Another question concerns the relevance of the cellular model studied. irCLIP is performed on neuronal progenitor cells subjected to neuronal induction for 2 hours. This short-term induction leads to a very modest - perhaps 10% - and very transient 1-hour-long increase in translation, although this is not carefully quantified. The cellular phenotype also does not appear to change and calling the cells treated with differentiation media for 2 hours "differentiated NPCs" seems a bit misleading. Perhaps unsurprisingly, the minor "burst" of translation coincides with minor effects on eIF3-mRNA interactions most of which seem to be driven by mRNA levels. Based on the ~15-fold increase in ID2 mRNA coinciding with a ~5-fold increase in ribosome occupancy (RPF), ID2 TE actually goes down upon neuronal induction.

We agree that it will be interesting to look at eIF3-mRNA interactions at longer time points after induction of NPC differentiation. However, the pattern of eIF3 crosslinking to the end of 3’-UTRs occurs in both time points reported here, which is likely to be the more general finding in what we present.

(3) The overlap in eIF3-mRNA interactions identified here and in the authors' previous reports is minimal. Some of the discrepancies may be related to the not well-justified approach for filtering data prior to assessing overlap. Still, the fundamentally different binding patterns - eIF3 mostly interacting with 5'-UTRs in the authors' previous report and other studies versus the strong preference for 3'-UTRs shown here - are striking. In the Discussion, it is speculated that the different methods used - PAR-CLIP versus irCLIP - lead to these fundamental differences. Unfortunately, this is not supported by any data, even though it would be very important for the translation field to learn whether different CLIP methodologies assess very different aspects of eIF3-mRNA interactions.

We agree the more interesting aspect of what we observe is the difference in location of eIF3 crosslinking, i.e. the end of 3’-UTRs rather than 5’-UTRs or the pan-mRNA pattern we observed in T cells. The reviewer is right that it will be important in the future to compare PAR-CLIP and Quick-irCLIP side-by-side to begin to unravel the differences we observe with the two approaches.

Reviewer #2 (Public review):

Summary:

The paper documents the role of eIF3 in translational control during neural progenitor cell (NPC) differentiation. eIF3 predominantly binds to the 3' UTR termini of mRNAs during NPC differentiation, adjacent to the poly(A) tails, and is associated with efficiently translated mRNAs, indicating a role for eIF3 in promoting translation.

Strengths:

The manuscript is strong in addressing molecular mechanisms by using a combination of next-generation sequencing and crosslinking techniques, thus providing a comprehensive dataset that supports the authors' claims. The manuscript is methodologically sound, with clear experimental designs.

Weaknesses:

(1) The study could benefit from further exploration into the molecular mechanisms by which eIF3 interacts with 3' UTR termini. While the correlation between eIF3 binding and high translation levels is established, the functionality of these interactions needs validation. The authors should consider including experiments that test whether eIF3 binding sites are necessary for increased translation efficiency using reporter constructs.

We agree with the reviewer that the molecular mechanism by which eIF3 interacts with the 3’-UTR termini remains unclear, along with its biological significance, i.e. how it contributes to translation levels. We think it could be useful to try reporters in, perhaps, HEK293T cells in the future to probe the mechanism in more detail.

(2) The authors mention that the eIF3 3' UTR termini crosslinking pattern observed in their study was not reported in previous PAR-CLIP studies performed in HEK293T cells (Lee et al., 2015) and Jurkat cells (De Silva et al., 2021). They attribute this difference to the different UV wavelengths used in Quick-irCLIP (254 nm) and PAR-CLIP (365 nm with 4-thiouridine). While the explanation is plausible, it remains a caveat that different UV crosslinking methods may capture different eIF3 modules or binding sites, depending on the chemical propensities of the amino acid-nucleotide crosslinks at each wavelength. Without addressing this caveat in more detail, the authors cannot generalize their findings, and thus, the title of the paper, which suggests a broad role for eIF3, may be misleading. Previous studies have pointed to an enrichment of eIF3 binding at the 5' UTRs, and the divergence in results between studies needs to be more explicitly acknowledged.

We agree with the reviewer that the two methods of crosslinking will require a more detailed head-to-head comparison in the future. However, we do think the title is justified by the fact that we see crosslinking to the termini of 3’-UTRs across thousands of transcripts in each condition. Furthermore, the 3’-UTR crosslinking is enriched on mRNAs with higher ribosome protected fragment counts (RPF) in differentiated cells, Figure 3F.

(3) While the manuscript concludes that eIF3's interaction with 3' UTR termini is independent of poly(A)-binding proteins, transient or indirect interactions should be tested using assays such as PLA (Proximity Ligation Assay), which could provide more insights.

This is a good idea, but would require a substantial effort better suited to a future publication. We think our observations are interesting enough to the field to stimulate future experimentation that we may or may not be most capable of doing in our lab.

Reviewer #3 (Public review):

Summary:

In this manuscript by Mestre-Fos and colleagues, authors have analyzed the involvement of eIF3 binding to mRNA during differentiation of neural progenitor cells (NPC). The authors bring a lot of interesting observations leading to a novel function for eIF3 at the 3'UTR.

During the translational burst that occurs during NPC differentiation, analysis of eIF3-associated mRNA by Quick-irCLIP reveals the unexpected binding of this initiation factor at the 3'UTR of most mRNA. Further analysis of alternative polyadenylation by APAseq highlights the close proximity of the eIF3-crosslinking position and the poly(A) tail. Furthermore, this interaction is not detected in Poly(A)-less transcripts. Using Riboseq, the authors then attempted to correlate eIF3 binding with the translation efficacy of mRNA, which would suggest a common mechanism of translational control in these cells. These observations indicate that eIF3-binding at the 3'UTR of mRNA, near the poly(A) tail, may participate to the closed-loop model of mRNA translation, bridging 5' and 3', and allowing ribosomes recycling. However, authors failed to detect interactions of eIF3, with either PABP or Paip1 or 40S subunit proteins, which is quite unexpected.

Strength:

The well-written manuscript presents an attractive concept regarding the mechanism of eIF3 function at the 3'UTR. Most mRNA in NPC seems to have eIF3 binding at the 3'UTR and only a few at the 5'end where it's commonly thought to bind. In a previous study from the Cate lab, eIF3 was reported to bind to a small region of the 3'UTR of the TCRA and TCRB mRNA, which was responsible for their specific translational stimulation, during T cell activation. Surprisingly in this study, the eIF3 association with mRNA occurs near polyadenylation signals in NPC, independently of cell differentiation status. This compelling evidence suggests a general mechanism of translation control by eIF3 in NPC. This observation brings back the old concept of mRNA circularization with new arguments, independent of PABP and eIF4G interaction. Finally, the discussion adequately describes the potential technical limitations of the present study compared to previous ones by the same group, due to the use of Quick-irCLIP as opposed to the PAR-CLIP/thiouridine.

Weaknesses:

(1) These data were obtained from an unusual cell type, limiting the generalizability of the model.

We agree that unraveling the mechanism employed by eIF3 at the mRNA 3’-UTR termini might be better studied in a stable cell line rather than in primary cells.

(2) This study lacks a clear explanation for the increased translation associated with NPC differentiation, as eIF3 binding is observed in both differentiated and undifferentiated NPC. For example, I find a kind of inconsistency between changes in Riboseq density (Figure 3B) and changes in protein synthesis (Figure 1D). Thus, the title overstates a modest correlation between eIF3 binding and important changes in protein synthesis.

We thank the reviewer for this question. Riboseq data and RNASeq data are not on absolute scales when comparing across cell conditions. They are normalized internally, so increases in for example RPF in Figure 3B are relative to the bulk RPF in a given condition. By contrast, the changes in protein synthesis measured in Figure 1D is closer to an absolute measure of protein synthesis.

(3) This is illustrated by the candidate selection that supports this demonstration. Looking at Figure 3B, ID2, and SNAT2 mRNA are not part of the High TE transcripts (in red). In contrast, the increase in mRNA abundance could explain a proportionally increased association with eIF3 as well as with ribosomes. The example of increased protein abundance of these best candidates is overall weak and uncertain.

We agree that using TE as the criterion for defining increased eIF3 association would not be correct. By “highly translated” we only mean to convey the extent of protein synthesis, i.e. increases in ribosome protected fragments (RPF), rather than the translational efficiency.

(4) Despite several attempts (chemical and UV cross-linking) to identify eIF3 partners in NPC such as PABP, PAIP1, or proteins from the 40S, the authors could not provide any evidence for such a mechanism consistent with the closed-loop model. Overall, this rather descriptive study lacks mechanistic insight (eIF3 binding partners).

We agree that it will be important to identify the molecular mechanism used by eIF3 to engage the termini of mRNA 3’-UTRs. Nevertheless, the identification of eIF3 crosslinking to that location in mRNAs is new, and we think will stimulate new experiments in the field.

(5) Finally, the authors suspect a potential impact of technical improvement provided by Quick-irCLIP, that could have been addressed rather than discussed.

We agree a side-by-side comparison of eIF3 crosslinks captured by PAR-CLIP versus Quick-irCLIP will be an important experiment to do. However, NPCs or other primary cells may not be the best system for the comparison. We think using an established cell line might be more informative, to control for effects such as 4-thiouridine toxicity.

We sympathize with osvald, and pastor manders seems like a babbling fool. As a modern audience, we sympathize with him. However, at the time perhaps he seems like a disrespectful, rebellious child.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

(1) The sample size of the in-house dataset used for training the model was relatively small (34 patients), which might limit the generalizability of the findings.

(2) The authors did not perform functional experiments to directly validate the roles of the identified key genes in radiotherapy sensitivity, relying instead on associations with immune features and signaling pathways.

(3) The study did not discuss the potential limitations of using machine learning algorithms, such as the risk of overfitting and the need for larger, diverse datasets for more robust model development and validation.

(1) Currently, we are actively expanding the dataset by incorporating additional patient samples to enhance the model's robustness and generalizability. Furthermore, we implement advanced statistical techniques, including cross-validation, during model development to mitigate the potential limitations associated with the small sample size on our results. This limitation has been comprehensively addressed in the discussion section of our manuscript.

(2) Given the current resource limitations, our study predominantly employed bioinformatics analyses. We acknowledge the critical importance of experimental validation and are actively pursuing additional funding and collaborative opportunities to facilitate future experimental studies. Concurrently, we have enhanced the discussion section to comprehensively address the limitations of our approach and emphasize the necessity for future experimental validation.

(3) We appreciate the reviewers' insightful comments regarding the potential limitations of machine learning algorithms, particularly the risk of overfitting. In response, we have incorporated a comprehensive discussion of these concerns, detailing the measures implemented to mitigate such risks, including the application of regularization techniques and the adoption of more rigorous cross-validation methodologies. We further acknowledge the necessity for larger and more diverse datasets to enhance model validity and generalizability, a concern we intend to address in our future research endeavors. The revised manuscript includes an expanded discussion on these critical points.

Here is the limitation section in the revised Manuscript:

“This study primarily focuses on specific subtypes of nasopharyngeal carcinoma (NPC), potentially limiting its direct generalizability to other NPC subtypes or related head and neck malignancies. Furthermore, the limited sample size of our dataset may impact the model's generalizability and extrapolation capabilities. To mitigate the potential limitations associated with the small sample size, we employed advanced statistical methodologies, including cross-validation, to enhance the robustness and reliability of our findings. Nevertheless, we acknowledge the necessity for larger datasets and are actively collaborating with other research institutions to expand our sample size, thereby enhancing the robustness and broader applicability of our findings. Additionally, while our study utilizes bioinformatics approaches to identify and analyze key genes, we recognize that the absence of direct experimental functional validation represents a significant limitation. To address this limitation, we are actively pursuing additional funding and establishing collaborations with specialized laboratories to conduct crucial functional validation experiments, which will further elucidate the specific roles of these genes in radiotherapy response. Moreover, we acknowledge the potential risk of overfitting inherent in the application of machine learning algorithms to biomedical data analysis. To mitigate this risk, we implemented regularization techniques during model development and adopted a rigorous cross-validation strategy for model validation. These methodological approaches aim to ensure that our models maintain robust predictive performance on unseen data. Notwithstanding these limitations, our study offers novel insights into the molecular mechanisms underlying radiotherapy sensitivity in NPC and indicates promising avenues for future investigation. Future research endeavors will prioritize expanding the dataset, conducting comprehensive experimental validation, and refining our predictive model to enhance its accuracy and clinical applicability.”

Reviewer #2 (Public Review):

(1) The study focuses on a specific type of nasopharyngeal carcinoma (NPC) and may not be generalizable to other subtypes or related head and neck cancers. The applicability of NPC-RSS to a broader range of patients and tumor types remains to be determined.

(2) The study does not account for potential differences in radiotherapy protocols, doses, and techniques between the training and validation cohorts, which could influence the performance of the predictive model. Standardization of treatment parameters would be important for future validation studies.

(3) The binary classification of patients into radiotherapy-sensitive and resistant groups may oversimplify the complex spectrum of treatment responses. A more granular stratification system that captures intermediate responses could provide more nuanced predictions and better guide personalized treatment decisions.

(4) The study does not address the potential impact of other relevant factors, such as tumor stage, histological subtype, and concurrent chemotherapy, on the predictive performance of NPC-RSS. Incorporating these clinical variables into the model could enhance its accuracy and clinical utility.

(1) We appreciate the reviewers' interest in the applicability of our study. This study specifically focuses on a particular subtype of nasopharyngeal carcinoma (NPC), which may limit its direct generalizability to other NPC subtypes or related head and neck malignancies. We have incorporated a detailed discussion of this limitation in the Discussion section and intend to investigate the applicability of NPC-RSS across a broader spectrum of tumor types and subtypes in subsequent studies.

(2) We acknowledge the reviewers' emphasis on the significance of potential variations in radiotherapy regimens, doses, and techniques. In the current study, we did not sufficiently account for these factors, potentially impacting the model's generalizability and accuracy. We aim to improve data consistency and strengthen model validation by standardizing treatment parameters in future investigations.

(3) We concur with the reviewers' assessment that binary categorization may oversimplify the intricate nature of treatment responses. Indeed, radiotherapy responses likely exist on a continuous spectrum. Consequently, we intend to develop more refined stratification systems to capture intermediate responses, thereby enhancing the accuracy of treatment outcome predictions and facilitating personalized treatment decisions.

(4) We appreciate the reviewers' recommendation to incorporate clinical variables, including tumor stage, histological subtype, and concurrent chemotherapy, into the model. We acknowledge that these factors are crucial for enhancing the accuracy and clinical applicability of predictive models. We are presently compiling these additional data and intend to integrate these variables into subsequent model iterations.

Reviewer #1 (Recommendations For The Authors):

(1) The manuscript would benefit from a more comprehensive comparison of the NPC-RSS with existing prognostic models or biomarkers for nasopharyngeal carcinoma. This would help highlight the unique value and potential superiority of the NPC-RSS in predicting radiotherapy sensitivity.

2) The authors should consider expanding their discussion on the potential molecular mechanisms underlying the association between the key NPC-RSS genes and radiotherapy response. They could explore whether these genes have been previously implicated in radiotherapy resistance in other cancer types and discuss the potential functional roles of these genes in the context of nasopharyngeal carcinoma.

(1) We appreciate your thorough review and valuable suggestions concerning our study. In response to the suggestion of comparing the Nasopharyngeal Carcinoma Radiotherapy Sensitivity Score (NPC-RSS) with existing prognostic models or biomarkers, we have carefully considered this proposal and determined that such a comparison is beyond the scope of our current study. The primary focus of our research is on the development and internal validation of the NPC-RSS model's accuracy and reliability. At present, we do not have access to the necessary external data to conduct a valid comparison, and the integration of such data extends beyond the parameters of this study. We intend to incorporate this comparative analysis in future studies to further validate the efficacy and explore the clinical application potential of the NPC-RSS model. We appreciate your understanding and continued support for our research endeavors.(2) In the revised manuscript, we have incorporated a comprehensive review of the functions of these key genes in various cancer types and explored their potential mechanisms of action in nasopharyngeal carcinoma (NPC). Through the citation of pertinent studies, we have elucidated the impact of these genes on radiotherapy sensitivity and resistance. Furthermore, we have proposed future research directions to elucidate the specific roles of these genes in the radiotherapy response of NPC.

The following are new additions to the revised draft：

“Previous studies have demonstrated that SMARCA2 significantly influences the radiotherapy response in non-small cell lung cancer (NSCLC). Depletion of SMARCA2 has been shown to enhance radiosensitivity, suggesting its potential as a therapeutic target for radiosensitization [30478150]. Additionally, the DMC1 gene has been incorporated into the radiosensitivity index (RSI) to evaluate radiotherapy sensitivity and prognosis, particularly in endometrial cancers. This inclusion provides valuable insights into the DNA damage repair process [38628740]. Studies on CD9 in glioblastoma multiforme (GBM) have revealed that post-radiotherapy increases in CD9 and CD81 levels in extracellular vesicles (EVs) are strongly correlated with the cytotoxic response to treatment. This finding suggests the potential of CD9 as a novel biomarker for monitoring radiotherapy efficacy [36203458]. In contrast, the association of PSG4 and KNG1 with radiotherapy resistance remains unexplored in the current literature.

Future research should focus on analyzing the expression patterns of SMARCA2 in NPC patients and its correlation with radiotherapy efficacy using clinical samples. This analysis could elucidate its potential as a target for radiosensitization therapy. Investigating the correlation between DMC1 expression levels and radiotherapy sensitivity in NPC could potentially aid in predicting treatment efficacy and optimizing therapeutic regimens. Furthermore, analysis of extracellular vesicles, particularly those containing CD9, in post-radiotherapy NPC patients could assess their feasibility as biomarkers for monitoring treatment response. These proposed studies would not only contribute to a deeper understanding of the mechanisms underlying the role of these genes in NPC radiotherapy but could also potentially lead to the development of novel strategies for enhancing radiotherapy efficacy.”

Minor Recommendations:

(1) It is recommended that the author share the code for the article on Github or a similar open source platform.

(2) The manuscript would benefit from a thorough review of the punctuation and sentence structure to improve readability and clarity.

(1) You suggest sharing the code utilized in this study on GitHub or a comparable open-source platform to enhance the transparency and reproducibility of the research. I fully recognize the significance of this suggestion. However, due to the sensitivity of the data involved and the existing intellectual property agreement with my research team, we are unable to make the code publicly available at this time. We are actively seeking a method to safeguard the intellectual property of the project while also planning to share our tools and methodologies in the future. At this stage, we are open to collaborating with other researchers under appropriate frameworks and conditions to validate and replicate our findings by providing essential code execution snippets or assisting with data analysis.

(2) Your suggestions are vital for enhancing the quality of the manuscript. I will perform a comprehensive linguistic and structural review of the manuscript to ensure that statements flow coherently and punctuation is employed correctly. We also intend to engage a professional scientific and technical writing editor to ensure that the manuscript adheres to the high standards required for academic publishing.

Reviewer #2 (Recommendations For The Authors):

(1) The manuscript would benefit from a more in-depth discussion of the potential clinical implications of the NPC-RSS. The authors should elaborate on how this score could be integrated into clinical decision-making and patient management.

(2) The authors should consider including a section discussing the limitations of their study and potential areas for future research. This could include the need for prospective validation of the NPC-RSS in larger patient cohorts and the exploration of additional biological mechanisms.

(1) We concur that a more comprehensive discussion regarding the application of the NPC-RSS in clinical decision-making would significantly enhance the practical value of this study. In the revised draft, we will include a section that elaborates on the integration of the NPC-RSS scoring system into daily clinical practice, detailing how it can assist physicians in developing individualized treatment plans and optimize patient management by predicting treatment responses.

The following are new additions to the revised draft:

“The incorporation of the NPC-RSS scoring system into clinical decision-making and patient management involves several key steps: first, establishing genetic testing as a standard component of nasopharyngeal cancer diagnosis and ensuring that physicians have prompt access to scoring results to guide treatment planning. Second, physicians should utilize the scoring results to tailor individualized treatment plans and engage in multidisciplinary discussions to optimize decision-making. Concurrently, physicians should elucidate the clinical significance of the scores and effectively communicate with patients to facilitate shared decision-making. Furthermore, continuous monitoring of the relationship between scoring and treatment outcomes, optimizing the scoring model based on empirical data, and ensuring the integration of technological platforms along with regulatory compliance are essential for safeguarding the effective operation of the scoring system and the protection of patient information.

(2) In light of the reviewers' valuable suggestions, we acknowledge the significance of prospective validation of the NPC-RSS scoring system in a broader patient population and the necessity for thorough exploration of the underlying biological mechanisms. Accordingly, we are incorporating a new section in the revised manuscript that elaborates on the limitations of the current study and outlines potential directions for future research. This encompasses plans to increase the sample size for validation and further investigations into the biological basis of the scoring system to enhance its predictive validity and clinical applicability. We believe that these additions will significantly enrich the depth and breadth of the study, thereby serving the scientific community and clinical practice more effectively.”

Minor Recommendations:

(1) The authors should ensure that all abbreviations are defined at their first mention in the text.

(2) The figure legends should be more descriptive and self-explanatory, allowing readers to understand the main findings without referring back to the main text.

(1) You pointed out the need to define all acronyms at the first mention in the text and suggested that a comprehensive list of acronyms be included in the revised draft. We fully concur and have included a comprehensive list of acronyms in the revised text. Additionally, to enhance clarity, we have included the full name and definition of each acronym alongside its first occurrence in the text. This will assist readers in comprehending the study without the need to repeatedly refer to the glossary.

(2) You recommended enhancing the descriptive quality of the figure legends to enable readers to discern the key findings from the figures without consulting the text. We have redesigned and refined all charts and legends to ensure they provide adequate information and are more descriptive. Each legend now outlines the experimental conditions, the variables employed, and the primary conclusions, ensuring that the charts themselves sufficiently convey the key findings of the study.

Reviewer #2 (Public review):

Summary:

This article utilizes machine learning methods and transcriptomic data from nasopharyngeal carcinoma (NPC) patients to construct a biomarker called NPC-RSS that can predict the radiosensitivity of NPC patients. The authors further explore the biological mechanisms underlying the relationship between NPC-RSS and radiotherapy response in NPC patients. The main objective of this study is to guide the selection of radiotherapy strategies for NPC patients, thereby improving their clinical outcomes and prognosis.

Strengths:

(1) The combination of multiple machine learning algorithms and cross-validation was used to select the best predictive model for radiotherapy sensitivity from 71 differentially expressed genes, enhancing the robustness and reliability of the predictions.<br /> (2) Functional enrichment analysis revealed close associations between NPC-RSS key genes and immune characteristics, expression of radiotherapy sensitivity-related genes, and signaling pathways related to disease progression, providing a biological basis for NPC-RSS in predicting radiotherapy sensitivity.<br /> (3) Grouping NPC samples according to NPC-RSS showed that the radiotherapy-sensitive group exhibited a more enriched and activated state of immune infiltration compared to the radioresistant group. In single-cell samples, NPC-RSS was higher in the radiotherapy-sensitive group, with immune cells playing a dominant role. These results clarify the mechanism of NPC-RSS in predicting radiotherapy sensitivity from an immunological perspective.<br /> (4) The study used public datasets and in-house cohort data for validation, confirming the good predictive performance of NPC-RSS and increasing the credibility of the results.

Limitation:

(1) The study focuses on a specific type of nasopharyngeal carcinoma (NPC) and may not be generalizable to other subtypes or related head and neck cancers. The applicability of NPC-RSS to a broader range of patients and tumor types remains to be determined.<br /> (2) The study does not account for potential differences in radiotherapy protocols, doses, and techniques between the training and validation cohorts, which could influence the performance of the predictive model. Standardization of treatment parameters would be important for future validation studies.<br /> (3) The binary classification of patients into radiotherapy-sensitive and resistant groups may oversimplify the complex spectrum of treatment responses. A more granular stratification system that captures intermediate responses could provide more nuanced predictions and better guide personalized treatment decisions.<br /> (4) The study does not address the potential impact of other relevant factors, such as tumor stage, histological subtype, and concurrent chemotherapy, on the predictive performance of NPC-RSS. Incorporating these clinical variables into the model could enhance its accuracy and clinical utility.

Some trending topics on the internet often lose their positive impact as they spread. I've seen some people on TikTok using instruments to collaborate on duets, and it's genuinely interesting. But the thing like this aren't a good thing. Still, we can't entirely prevent these things from happening—it’s always a mix of pros and cons.

Author response:

The following is the authors’ response to the previous reviews.

Public Reviews:

Reviewer #1 (Public Review):

In their paper, Kang et al. investigate rigidity sensing in amoeboid cells, showing that, despite their lack of proper focal adhesions, amoeboid migration of single cells is impacted by substrate rigidity. In fact, many different amoeboid cell types can durotax, meaning that they preferentially move towards the stiffer side of a rigidity gradient. 

The authors observed that NMIIA is required for durotaxis and, buiding on this observation, they generated a model to explain how durotaxis could be achieved in the absence of strong adhesions. According to the model, substrate stiffness alters the diffusion rate of NMAII, with softer substrates allowing for faster diffusion. This allows for NMAII accumulation at the back, which, in turn, results in durotaxis. 

The authors responded to all my comments and I have nothing to add. The evidence provided for durotaxis of non adherent (or low-adhering) cells is strong. I am particularly impressed by the fact that amoeboid cells can durotax even when not confined. I wish to congratulate the authors for the excellent work, which will fuel discussion in the field of cell adhesion and migration.

We thank the reviewer for critically evaluating our work and giving kind suggestions. We are glad that the reviewer found our work to be of potential interest to the broad scientific community.

Reviewer #2 (Public Review):

Summary:

The authors developed an imaging-based device that provides both spatialconfinement and stiffness gradient to investigate if and how amoeboid cells, including T cells, neutrophils, and Dictyostelium, can durotax. Furthermore, the authors showed that the mechanism for the directional migration of T cells and neutrophils depends on non-muscle myosin IIA (NMIIA) polarized towards the soft-matrix-side. Finally, they developed a mathematical model of an active gel that captures the behavior of the cells described in vitro.

Strengths:

The topic is intriguing as durotaxis is essentially thought to be a direct consequence of mechanosensing at focal adhesions. To the best of my knowledge, this is the first report on amoeboid cells that do not depend on FAs to exert durotaxis. The authors developed an imaging-based durotaxis device that provides both spatial confinement and stiffness gradient and they also utilized several techniques such as quantitative fluorescent speckle microscopy and expansion microscopy. The results of this study have well-designed control experiments and are therefore convincing.

Weaknesses:

Overall this study is well performed but there are still some minor issues I recommend the authors address:

(1) When using NMIIA/NMIIB knockdown cell lines to distinguish the role of NMIIA and NMIIB in amoeboid durotaxis, it would be better if the authors took compensatory effects into account.

We thank the reviewer for this suggestion. We have investigated the compensation of myosin in NMIIA and NMIIB KD HL-60 cells using Western blot and added this result in our updated manuscript (Fig. S4B, C). The results showed that the level of NMIIB protein in NMIIA KD cells doubled while there was no compensatory upregulation of NMIIA in NMIIB KD cells. This is consistent with our conclusion that NMIIA rather than NMIIB is responsible for amoeboid durotaxis since in NMIIA KD cells, compensatory upregulation of NMIIB did not rescue the durotaxis-deficient phenotype. 

(2) The expansion microscopy assay is not clearly described and some details are missed such as how the assay is performed on cells under confinement.

We thank the reviewer for this comment. We have updated details of the expansion microscopy assay in our revised manuscript in line 481-485 including how the assay is performed on cells under confinement:

Briefly, CD4+ Naïve T cells were seeded on a gradient PA gel with another upper gel providing confinement. 4% PFA was used to fix cells for 15 min at room temperature. After fixation, the upper gradient PA gel is carefully removed and the bottom gradient PA gel with seeded cells were immersed in an anchoring solution containing 1% acrylamide and 0.7% formaldehyde (Sigma, F8775) for 5 h at 37 °C.

(3) In this study, an active gel model was employed to capture experimental observations. Previously, some active nematic models were also considered to describe cell migration, which is controlled by filament contraction. I suggest the authors provide a short discussion on the comparison between the present theory and those prior models.

We thank the reviewer for this suggestion. Active nematic models have been employed to recapitulate many phenomena during cell migration (Nat Commun., 2018, doi: 10.1038/s41467-018-05666-8.). The active nematic model describes the motion of cells using the orientation field, Q, and the velocity field, u. The director field n with (n = −n) is employed to represent the nematic state, which has head-tail symmetry. However, in our experiments, actin filaments are obviously polarized, which polymerize and flow towards the direction of cell migration. Therefore, we choose active gel model which describes polarized actin field during cell migration. In the discussion part, we have provided the comparison between active gel model and motor-clutch model. We have also supplemented a short discussion between the present model and active nematic model in the main text of line 345-347:

The active nematic model employs active extensile or contractile agents to push or pull the fluid along their elongation axis to simulate cells flowing (61). 

(4) In the present model, actin flow contributes to cell migration while myosin distribution determines cell polarity. How does this model couple actin and myosin together?

We thank the reviewer for this question. In our model, the polarization field is employed to couple actin and myosin together. It is obvious that actin accumulate at the front while myosin diffuses in the opposite direction. Therefore, we propose that actin and myosin flow towards the opposite direction, which is captured in the convection term of actin ) and myosin () density field.

Author response:

The following is the authors’ response to the current reviews.

We are grateful to the reviewers for their positive assessment of the revised version of the article.

Please find below our answers to the last, minor comments of the reviewers.

We thank the reviewer for this important comment. In our live imaging experiments, we actually tracked the dorsal and ventral borders of the omp:yfp positive clusters in control and sly mutant embryos. These measurements showed that the omp:yfp positive clusters are more elongated along the DV axis in mutants as compared with control siblings, as seen on fixed samples (data not shown), suggesting that this difference in tissue shape is not due to fixation.

Reviewer #4 (Public review):

Summary:

In this elegant study XX and colleagues use a combination of fixed tissue analyses and live imaging to characterise the role of Laminin in olfactory placode development and neuronal pathfinding in the zebrafish embryo. They describe Laminin dynamics in the developing olfactory placode and adjacent brain structures and identify potential roles for Laminin in facilitating neuronal pathfinding from the olfactory placode to the brain. To test whether Laminin is required for olfactory placode neuronal pathfinding they analyse olfactory system development in a well-established laminin-gamma-1 mutant, in which the laminin-rich basement membrane is disrupted. They show that while the OP still coalesces in the absence of Laminin, Laminin is required to contain OP cells during forebrain flexure during development and maintain separation of the OP and adjacent brain region. They further demonstrate that Laminin is required for growth of OP neurons from the OP-brain interface towards the olfactory bulb. The authors also present data describing that while the Laminin mutant has partial defects in neural crest cell migration towards the developing OP, these NCC defects are unlikely to be the cause of the neuronal pathfinding defects upon loss of Laminin. Altogether the study is extremely well carried out, with careful analysis of high-quality data. Their findings are likely to be of interest to those working on olfactory system development, or with an interest in extracellular matrix in organ morphogenesis, cell migration, and axonal pathfinding.

Strengths:

The authors describe for the first time Laminin dynamics during the early development of the olfactory placode and olfactory axon extension. They use an appropriate model to perturb the system (lamc1 zebrafish mutant), and demonstrate novel requirements for Laminin in pathfinding of OP neurons towards the olfactory bulb.

The study utilises careful and impressive live imaging to draw most of its conclusions, really drawing upon the strengths of the zebrafish model to investigate the role of laminin in OP pathfinding. This imaging is combined with deep learning methodology to characterise and describe phenotypes in their Laminin-perturbed models, along with detailed quantifications of cell behaviours, together providing a relatively complete picture of the impact of loss of Laminin on OP development.

Weaknesses:

Some of the statistical tests are performed on experiments where n=2 for each condition (for example the measurements in Figure S2) - in places the data is non-significant, but clear trends are observed, and one wonders whether some experiments are under-powered.

We initially planned the electron microscopy experiments in order to analyse 3 embryos per genotype per stage. However, because of technical issues we could not perform the measurements in all the cases, explaining why we have n = 2 in some of the graphs. The trends were quite clear, so we chose to keep these data in the article. We believe they nicely complement the immunostaining data assessing basement membrane integrity in control and mutant embryos.

The following is the authors’ response to the original reviews.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

The authors describe the dynamic distribution of laminin in the olfactory system and forebrain. Using immunohistochemistry and transgenic lines, they found that the olfactory system and adjacent brain tissues are enveloped by BMs from the earliest stages of olfactory system assembly. They also found that laminin deposits follow the axonal trajectory of axons. They performed a functional analysis of the sly mutant to analyse the function of laminin γ1 in the development of the zebrafish olfactory system. Their study revealed that laminin enables the shape and position of placodes to be maintained late in the face of major morphogenetic movements in the brain, and its absence promotes the local entry of sensory axons into the brain and their navigation towards the olfactory bulb. 

Strengths: 

- They showed that in the sly mutants, no BM staining of laminin and Nidogen could be detected around the OP and the brain. The authors then elegantly used electron microscopy to analyse the ultrastructure of the border between the OP and the brain in control and sly mutant conditions. 

- To analyse the role of laminin γ1-dependent BMs in OP coalescence, the authors used the cluster size of Tg(neurog1:GFP)+ OP cells at 22 hpf as a marker. They found that the mediolateral dimension increased specifically in the mutants. However, proliferation did not seem to be affected, although apoptosis appeared to increase slightly at a later stage. This increase could therefore be due to a dispersal of cells in the OP. To test this hypothesis, the authors then analysed the cell trajectories and extracted 3D mean square displacements (MSD), a measure of the volume explored by a cell in a given period of time. Their conclusion indicates that although brain cell movements are increased in the absence of BM during coalescence phases, overall OP cell movements occur within normal parameters and allow OPs to condense into compact neuronal clusters in sly mutants. The authors also analysed the dimensions of the clusters composed of OMP+ neurons. Their results show an increase in cluster size along the dorso-ventral axis. These results were to be expected since, compared with BM, early neurog1+ neurons should compact along the medio-lateral axis, and those that are OMP+ essentially along the dorso-ventral axis. In addition to the DV elongation of OP tissue, the authors show the existence of isolated and ectopic (misplaced) YFP+ cells in sly mutants. 

- To understand the origin of these phenotypes, the authors analysed the dynamic behaviour of brain cells and OPs during forebrain flexion. The authors then quantitatively measured brain versus OPs in the sly mutant and found that the OP-brain boundary was poorly defined in the sly mutant compared with the control. Once again, the methods (cell tracks, brain size, and proliferation/apoptosis, and the shape of the brain/OP boundary) are elegant but the results were expected. 

- They then analysed the dynamic behaviour of the axon using live imaging. Thus, olfactory axon migration is drastically impaired in sly mutants, demonstrating that Laminin γ1dependent BMs are essential for the growth and navigation of axons from the OP to the olfactory bulb. 

- The authors therefore performed a quantitative analysis of the loss of function of Laminin γ1. They propose that the BM of the OP prevents its deformation in response to mechanical forces generated by morphogenetic movements of the neighbouring brain. 

Weaknesses: 

- The authors did not analyse neurog1 + axonal migration at the level of the single cell and instead made a global analysis. An analysis at the cell level would strengthen their hypotheses.  

- Rescue experiments by locally inducing Laminin expression would have strengthened the paper. 

- The paper lacks clarity between the two neuronal populations described (early EONs and late OSNs).  

- The authors quantitatively measured brain versus OPs in the sly mutant and found that the OP-brain boundary was poorly defined in the sly mutant compared with the control. Once again, the methods (cell tracks, brain size, proliferation/apoptosis, and the shape of the brain/OP boundary) are elegant but the results were expected. 

- A missing point in the paper is the effect of Laminin γ1 on the migration of cranial NCCs that interact with OP cells. The authors could have analysed the dynamic distribution of neural crest cells in the sly mutant. 

We thank the reviewer for the overall positive assessment of our work, and we carefully responded to all her/his insightful comments below. Live imaging experiments to (1) visualise exit and entry point formation with only a few axons labelled, (2) characterise the behaviour of single neurog1:GFP-positive neurons/axons during OP coalescence and to (3) analyse the migration of cranial NCC are now included in the revised manuscript to address the reviewer’s questions, and reinforce our initial conclusions.

Reviewer #2 (Public Review): 

Summary: 

This manuscript addresses the role of the extracellular matrix in olfactory development. Despite the importance of these extracellular structures, the specific roles and activities of matrix molecules are still poorly understood. Here, the authors combine live imaging and genetics to examine the role of laminin gamma 1 in multiple steps of olfactory development. The work comprises a descriptive but carefully executed, quantitative assessment of the olfactory phenotypes resulting from loss of laminin gamma. Overall, this is a constructive advance in our understanding of extracellular matrix contributions to olfactory development, with a well-written Discussion with relevance to many other systems. 

Strengths: 

The strengths of the manuscript are in the approaches: the authors have combined live imaging, careful quantitative analyses, and molecular genetics. The work presented takes advantage of many zebrafish tools including mutants and transgenics to directly visualize the laminin extracellular matrix in living embryos during the developmental process. 

Weaknesses: 

The weaknesses are primarily in the presentation of some of the imaging data. In certain cases, it was not straightforward to evaluate the authors' interpretations and conclusions based on the single confocal sections included in the manuscript. For example, it was difficult to assess the authors' interpretation of when and how laminin openings arise around the olfactory placode and brain during olfactory axon guidance. 

We thank the reviewer for the overall positive assessment of our work, and we carefully responded to all her/his insightful comments below. To address these comments, live imaging data to visualise exit and entry point formation with a sparse labelling of axons, and z-stacks showing how exit and entry points are organised in 3D, have been added to the revised manuscript.

Reviewer #3 (Public Review): 

This is a beautifully presented paper combining live imaging and analysis of mutant phenotypes to elucidate the role of laminin γ1-dependent basement membranes in the development of the zebrafish olfactory placode. The work is clearly illustrated and carefully quantified throughout. There are some very interesting observations based on the analysis of wild-type, laminin γ1, and foxd3 mutant embryos. The authors demonstrate the importance of a Laminin γ1-dependent basement membrane in olfactory placode morphogenesis, and in establishing and maintaining both boundaries and neuronal connections between the brain and the olfactory system. There are some very interesting observations, including the identification of different mechanisms for axons to cross basement membranes, either by taking advantage of incompletely formed membranes at early stages, or by actively perforating the membrane at later ones. 

This is a valuable and important study but remains quite descriptive. In some cases, hypotheses for mechanisms are stated but are not tested further. For example, the authors propose that olfactory axons must actively disrupt a basement membrane to enter the brain and suggest alternative putative mechanisms for this, but these are not tested experimentally. In addition, the authors propose that the basement membrane of the olfactory placode acts to resist mechanical forces generated by the morphogenetic movement of the developing brain, and thus to prevent passive deformation of the placode, but this is not tested anywhere, for example by preventing or altering the brain movements in the laminin γ1 mutant. 

We thank the reviewer for the overall positive assessment of our work and for suggesting interesting experiments to attempt in the future, and we carefully responded to all her/his constructive comments below.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

In general, it would be easier to draw conclusions and compare data if the authors used similar stages throughout the article. 

Throughout the article we tried to focus on a series of stages that cover both the coalescence of the OP (up to 24 hpf) and later stages of olfactory system development spanning the brain flexure process (28, 32, 36 hpf). However, for technical reasons it was not always possible to stick to these precise stages in some of our experiments. Also, in Fig. 1E-J, we picked in the movies some images illustrating specific cell or axonal behaviours, and thus the corresponding stages could not match exactly the stage series used in Fig. 1A-D and elsewhere in the article. Nevertheless, this stage heterogeneity does not affect our main conclusions.

It would be useful to schematise the olfactory placode and the brain in an insert to clearly visualise the system in each figure. 

We hope that the schematic which was initially presented in Fig. 1K already helps the reader to understand how the system is organised. Although we have not added more schematic views to represent the system in each figure (we think this would make the figures overcrowded), we have added additional legends to point to the OP and the brain in the pictures in order to clarify the localisation of each tissue.

In the Summary, the authors refer to the integrity of the basement membrane. I don't think there is any attempt to affect basement membrane integrity in the article. It would be important to do so to look at the effect on CNS-PNS separation and axonal elongation. 

In the Summary, we use the term « integrity of the basement membrane » to mention that we have analysed this integrity in the sly mutant. Given the results of our immunostainings against three main components of the basement membrane (Laminin, Collagen IV and Nidogen), as well as our EM observations, we see the sly mutant as a condition in which the integrity of the basement membrane is strongly affected.

Rescue experiments by locally inducing Laminin expression would have strengthened the paper. 

We have attempted to rescue the sly mutant phenotypes by introducing the mutation in the transgenic TgBAC(lamC1:lamC1-sfGFP) background, in which Laminin γ1 tagged with sfGFP is expressed under the control of its own regulatory sequences (Yamaguchi et al., 2022). To do so, we crossed sly+/-;Tg(omp:yfp) fish with sly+/-; Tg(lamC1:LamC1-sfGFP) fish. Surprisingly, while a rescue of the global embryo morphology was observed, no clear rescue of the olfactory system defects could be detected at 36 hpf. This could be due to the fact that the expression level of LamC1-sfGFP obtained with one copy of the transgene is not sufficient to rescue the olfactory system phenotypes, or that the sfGFP tag specifically affects the function of the Laminin 𝛾1 chain during the development of the olfactory system, making it unable to rescue the defects. Given the results of our first attemps, we decided not to continue in this direction.

(1) Developing OP & brain are surrounded by laminin-containing BM (already described by Torrez-Pas & Whitlock in 2014). 

"we first noticed the appearance of a continuous Laminin-rich BM surrounding the brain from 14-18 hpf, while around the OP, only discrete Laminin spots were detected at this stage (Fig. 1A, A'). " 

Around 8ss for Torrez-Pas & Whitlock (before 14 hpf). Can you modify the text, or show an 8ss stage embryo? As far as I know, the authors do not show images at 14hpf. Please correct this sentence or show a 14 hpf picture. 

The reviewer is right, we do not show any 14 hpf stage in the images and thus have removed this stage in the text and replaced it by 17 hpf.

In Figure 1A, the labelling of laminin 111 does not appear to be homogeneous along the brain.

Is this true? 

At this stage the brain’s BM revealed by the Laminin immunostaining appears fairly continuous (while the OP’s one is clearly dotty and less defined), but indeed very tiny/local interruptions of the signal can been seen along the structure as detected by the reviewer. We thus modified the text to mention these tiny interruptions.

How is the Laminin antibody used by the authors specific to laminin 111?  

We thank the reviewer for raising this important point. The immunogen used to produce this rabbit polyclonal antibody is the Laminin protein isolated from the basement membrane of a mouse Engelbreth Holm-Swarm sarcoma (EHS). It is thus likely to recognise several Laminin isoforms and not only Laminin 111. We thus replaced Laminin 111 by Laminin when mentioning this antibody in the text and Figures.

Please schematise in Figure 1K the stages you have tested and shown here in the article i.e. stages 18 - 22 - 28 -36 hpf using immunohistochemistry and 17-26-27-29-33 and 38 hpf using transgenics for laminin 111 and LamC1 respectively.  

As suggested by the reviewer, we changed the stages in the schematics for stages we have presented in Figure 1 (analysed either with immunostaining or in live imaging experiments). We chose to represent 17 - 22 - 26 - 33 hpf (and thus adapted some of the schematics for them to match these stages).  

Please specify in the Figure 1 legend for panels A to D whether this is a 3D projection or a zsection.

We indicated in the Figure 1 legend that all these images are single z-sections (as well as for panels E-J).

Furthermore, the schematisation in Fig. 1K does not reflect what the authors show: at 22 hpf laminin 111 labelling appears to be present only near the brain, and no labelling lateral to the olfactory placode and anteriorly and posteriorly. Thus, the schematisation in Figure 1K needs to be modified to reflect what the authors show.

We agree with the reviewer that the Laminin staining at this stage is observed around the medial region of the OP, but not more laterally. We modified the schematic view accordingly in Figure 1K. Anterior and posterior sides of the OP are not represented in this schematic because we chose to represent a frontal view rather than a dorsal view.

The authors suggest that" the laminin-rich BM of OP assembles between 18 and 22 hpf, during the late phase of OP coalescence". However, their data indicate that this BM assembles around 28hpf (Figure 1C). Can they clarify this point?

What we meant with this sentence is that we cleary see two distinct BMs from 22 hpf. However, as noticed by the reviewer, the OP’s BM is only present around the medial/basal regions of the OP and does not surround the whole OP tissue at this stage. We modified the text to clarify this point (in particular by mentioning that the OP’s BM starts to assemble between 18 and 22 hpf), and replaced the image shown in Figure 1B, B’ with a more representative picture (the previous z-section was taken in very dorsal regions of the OP).

It would be useful to disrupt these cells that have a cytoplasmic expression of Laminin-sfGFP, to analyse their contribution to BM and OP coalescence.

Indeed it will be interesting in the future to test specifically the role of the cells expressing cytoplasmic Laminin-sfGFP around and within the OP, as proposed by the reviewer. Laser ablation of these cells could be attempted, but due to their very superficial localisation, close to the skin, we believe these ablations (with the protocol/set-up we currently use in the lab) would impair the skin integrity, preventing us to conclude. We consider that the optimisation of this experiment is out of the scope of the present work.

Tg(-2.0ompb:gapYFP)rw032 marks ciliated olfactory sensory neurons (OSNs) (Sato et al., 2005). The authors should mention this. 

Please see our detailed response to the next point below.

Points to be clarified: 

-Tg(-2.0ompb:gapYFP)rw032 marks ciliated olfactory sensory neurons (OSNs) (Sato et al., 2005). The authors should mention this here. Moreover, the authors refer to "OP neurons" throughout the article. In the development of the olfactory organ, two types of neurons have been described in the literature: early EONs (12hpf-26hpf) and later OSNs. Each could have a specific role in the establishment and maintenance of the BM described by the authors. The authors need to clarify this point as, in Figure 1 for example, they use a marker for Tg(neurog1:GFP) EONs and a marker for ciliated OSNs without distinction. The distinction between EONs and OSNs comes a little late in the text and should be placed higher up. 

As mentioned by the reviewer, according to the initial view of neurogenesis in the OP, OP neurons are born in two waves. A transient population of unipolar, dendrite-less pioneer neurons would differentiate first, in the ventro-medial region of the OP and elongate their axons dorsally out of the placode, along the brain wall. These pioneer axons would then be used as a scaffold by later born OSNs located in the dorso-lateral rosette to outgrow their axons towards the olfactory bulb (Whitlock and Westerfield, 1998). 

Another study further characterised OP neurogenesis and showed that the first neurons to differentiate in the OP (the early olfactory neurons or EONs) express the Tg(neurog1:GFP) transgene (Madelaine et al., 2011). As mentioned by the authors in the discussion of this article, neurog1:GFP+ neurons appear much more numerous than the previously described pioneer neurons, and may thus include pioneers but also other neuronal subtypes.

We would like here to share additional, unpublished observations from our lab that further suggest that the situation is more complex than the pioneer/OSN and EON/OSN nomenclatures. First, in many of our live imaging experiments, we can clearly visualise some neurog1:GFP+ unipolar neurons, initially located in a medial position in the OP, which intercalate and contribute to the dorsolateral rosette (where OSNs are proposed to be located) at the end of OP coalescence, from 22-24 hpf. Second, in fixed tissues, we observed that most neurog1:GFP+ neurons located in the rosette at 32 hpf co-express the Tg(omp:meRFP) transgene (Sato et al., 2005). These observations suggest that at least a subpopulation of neurog1:GFP+ neurons could incorporate in the dorsolateral rosette and become ciliated OSNs during development. We can share these results with the reviewer upon request. Further studies are thus needed to clarify and describe the neuronal subpopulations and lineage relationships in the OP, but this detailed investigation is out of the scope and focus of the present study. 

An additional complication comes from the fact that, as shown and acknowledged by the authors in Miyasaka et al., 2005, the Tg(omp:meYFP) line (6kb promoter) labels ciliated OSNs in the rosette but also some unipolar, ventral neurons (around 10 neurons at 1 dpf, Miyasaka et al. 2005, Figure 3A, white arrowheads). This was also observed using the 2 kb promoter Tg(omp:meYFP) line (see for instance Miyasaka et al., 2007) and in our study, we can indeed detect these ventro-medial neurons labelled in the Tg(omp:meYFP) line (2 kb promoter), see for instance Figure 1C’, D’ or Movie 6. It is unclear whether these unipolar omp:meYFPpositive cells are pioneer neurons or EONs expressing the omp:meYFP transgene, or OSN progenitors that would be located basally/ventrally in the OP at these stages.

For all these reasons, we decided to present in the text the current view of neurogenesis in the OP but instead of attributing a definitive identity to the neurons we visualise with the transgenic lines, we prefer to mention them in the manuscript (and in the rest of the response to the reviewers) as neurons expressing neurog1:GFP or omp:meYFP transgenes (or cells/axons/neurons expressing RFP in the Tg(cldnb:Gal4; UAS:RFP) background).

What we also changed in the text to be more clear on this point:

- we moved higher up in the text, as suggested by reviewer 1, the description of the current model of neurogenesis in the OP,

- we mentioned that neurog1:GFP+ neurons are more numerous than the initially described pioneer neurons, as discussed in Madelaine et al., 2011,

- we wrote more clearly that the Tg(omp:meYFP) line labels ciliated OSNs but also a subset of unipolar, ventral neurons (Miyasaka et al., 2005), and pointed to these ventral neurons in Figure 1C’, D’,

- in the initial presentation of the current view of OP neurogenesis we renamed neurog1:GFP+ into EONs to be coherent with Madelaine et al., 2011.

- To visualise pioneer axons, the authors should use an EONS marker such as neurog1 because, to my knowledge, OMP only marks OSN axons and not pioneer axons.  

To visualise neurog1:GFP+ axons during OP coalescence, we performed live imaging upon injection of the neurog1:GFP plasmid (Blader et al., 2003) in the Tg(cldnb:Gal4; UAS:RFP) background (n = 4 mutants and n = 4 controls from 2 independent experiments). We observed some GFP+ placodal neurons exhibiting retrograde axon extension in both controls and sly mutants. In such experiments it is very difficult to quantify and compare the number of neurons/axons showing specific behaviours between different experimental conditions/genetic background. Indeed, due to the cytoplasmic localisation of GFP, the axons can only be seen in neurons expressing high levels of GFP, and due to the injection the number of such neurons varies a lot in between embryos, even in a given condition. Nevertheless, our qualitative observations reinforce the idea that the basement membrane is not absolutely required for mediolateral movements and retrograde axon extension of neurog1:GFP+ neurons in the OP. We added examples of images extracted from these new live imaging experiments in the revised Fig. S5A, B.

- The authors should analyse the presence of laminin in the OP and forebrain in conjunction with neural crest cell dynamics (using a Sox10 transgenic line for example) to refine their entry and exit point hypotheses. 

As described in the answer to the next point, we performed new experiments in which we visualised NCC migration in the Tg(neurog1:GFP) background, which allowed us to analyse the localisation of NCC at the forebrain/OP boundary, in ventral and dorsal positions, both in sly mutant embryos and control siblings.

- A dynamic analysis of the distribution of neural crest cells in the sly mutant over time and during OP coalescence would be important. 

The dynamics of zebrafish cranial NCC migration in the vicinity of the OP has been previously analysed using sox10 reporter lines (Harden et al., 2012, Torres-Paz and Whitlock, 2014, Bryan et al., 2020). To address the point raised by the reviewer, we performed live imaging from 16 to 32 hpf on sly mutants and control siblings carrying the Tg(neurog1:GFP) and Tg(UAS:RFP) transgenes and injected with a sox10(7.2):KalTA4 plasmid (Almeida et al., 2015). This allows the mosaic labelling of cells that express or have expressed sox10 during their development which, in the head region at these stages, represents mostly NCC and their derivatives. 3 independent experiments were carried out (n = 4 mutant embryos in which 8 placodes could be analysed; n = 6 control siblings in which 10 placodes could be analysed). A new movie (Movie 9) has been added to the revised article to show representative examples of control and mutant embryos.

From these new data, we could make the following observations:

- As expected from previous studies (Harden et al., 2012, Torres-Paz and Whitlock, 2014, Bryan et al., 2020), in control embryos a lot of NCC had already migrated to reach the vicinity of the OP when the movies begin at 16 hpf, and were then seen invading mainly the interface between the eye and the OP (10/10 placodes). Surprisingly, in sly mutants, a lot of motile NCC had also reached the OP region at 16 hpf in all the analysed placodes (8/8), and populated the eye/OP interface in 7/8 placodes (10/10 in controls). Counting NCC or tracking individual NCC during the whole duration of the movies was unfortunately too difficult to achieve in these movies, because of the low level of mosaicism (a high number of cells were labelled) and of the high speed of NCC movements (as compared with the 10 min delta t we chose for the movies). 

- in some of the control placodes we could detect a few NCC that populated the forebrain/OP interface, either ventrally, close to the exit point of the axons (4/10 placodes), or more dorsally (8/10 placodes). By contrast, in sly mutants, NCC were observed in the dorsal region of the brain/OP boundary in only 2/8 placodes, and in the ventral brain/OP frontier in only 2/8 placodes as well. Interestingly, in these 2 last samples, NCC that had initially populated the ventral region of the brain/OP interface were then expelled from the boundary at later stages.

We reported these observations in a new Table that is presented in revised Fig. S6B. In addition, instances of NCC migrating at the eye/OP or forebain/OP interfaces are indicated with arrowheads on Movie 9. Previous Figure S6 was splitted into two parts presenting NCC defects in sly mutants (revised Figure S6) and in foxd3 mutants (revised Figure S7).

Altogether, these new data suggest that the first postero-anterior phase of NCC migration towards the OP, as well as their migration in between the eye and OP tissues, is not fully perturbed in sly mutants. The subset of NCC that populate the OP/forebrain seem to be more specifically affected, as these NCC show defects in their migration to the interface or the maintenance of their position at the interface. Since the crestin marker labels mostly NCC at the OP/forebrain interface at 32 hpf (revised Fig. S6A), this could explain why the crestin ISH signal is almost lost in sly mutants at this stage.

(2) Laminin distribution suggests a role in olfactory axon development 

"Laminin 111 immunostaining revealed local disruptions in the membrane enveloping the OP and brain, precisely where YFP+ axons exit the OP (exit point) and enter the brain (entry point) (Fig. 1C-D')." Can the authors quantify this situation? It would be important to analyse this behaviour on the scale of a neuron and thus axonal migration to strengthen the hypotheses. 

As suggested by the reviewer, to better visualise individual axons at the exit and entry point, we used mosaic red labelling of OP axons. To achieve this sparse labelling, we took advantage of the mosaic expression of a red fluorescent membrane protein observed in the Tg(cldnb:Gal4; UAS:lyn-TagRFP) background. The unpublished Tg(UAS:lyn-TagRFP) line was kindly provided by Marion Rosello and Shahad Albadri from the lab of Filippo Del Bene. We crossed the Tg(cldnb:Gal4; UAS:lyn-TagRFP) line with the TgBAC(lamC1:lamC1-sfGFP) reporter and performed live imaging on 2 embryos/4 placodes, in a frontal view. A new movie (Movie 3 in the revised article) shows examples of exit and entry point formation in this context.This allowed us to visualise the formation of the exit and entry points in more samples (6 embryos and 12 placodes in total when we pool the two strategies for labelling OP axons) and through the visualisation of a small number of axons, and reinforce our initial conclusions. 

(3) The integrity of BMs around the brain and the OP is affected in the sly mutant 

Why do the authors analyse the distribution of collagen IV and Nidogen and not proteoglycans and heparan sulphate? 

We attempted to label more ECM components such as proteoglycans and heparan sulfate, but whole-mount immunostainings did not work in our hands.

A dynamic analysis of the distribution of neural crest cells in the sly mutant over time and during OP coalescence would be important. 

See our detailed response to this point above.  

(4) Role of Laminin γ1-dependent BMs in OP coalescence 

The authors use the size of the Tg(neurog1:GFP)+ OP cell cluster at 22 hpf as a marker.  The authors should count the number of cells in the OP at the indicated time using a nuclear dye to check that in the sly mutant the number of cells is the same over time. Two time points as analysed in Figure S2 may not be sufficient to quantify proliferation which at these stages should be almost zero according to Whitlock & Westerfield and Madelaine et al.

Counting the neurog1:GFP+ cell numbers in our existing data was unfortunately impossible, due to the poor quality of the DAPI staining. We are nevertheless confident that the number of cells within neurog1:GFP+ clusters is fairly similar between controls and sly mutants at 22 hpf, since the OP dimensions are the same for AP and DV dimensions, and only slightly different for the ML dimension. In addition, we analysed proliferation and apoptosis within the neurog1:GFP+ cluster at 16 and 21 hpf and observed no difference between controls and mutants.

(5) Role of Laminin γ1-dependent BMs during the forebrain flexure 

In Figure 4F at 32hpf, the presence of 77% ectopic OMP+ cells medially should result in an increase in dimensions along the M-L? This is not the case in the article. The authors should clarify this point. 

As we explained in the Material and Methods, ectopic fluorescent cells (cells that are physically separated from the main cluster) were not taken into account for the measurement of the OP dimensions. This is now also also mentioned in the legends of the Figures (4 and S3) showing the quantifications of OP dimensions.

Cell distribution also seems to be affected within the OMP+ cluster at 36hpf, with fewer cells laterally and more medially. The authors should analyse the distribution of OMP+ cells in the clusters. in sly mutants and controls to understand whether the modification corresponds to the absence of BM function. 

On the pictures shown in Figure 4F,G, we agree that omp:meYFP+ cells appear to be more medially distributed in the mutant, however this is not the case in other sections or samples, and is rather specific to the z-section chosen for the Figure. We found that the ML dimension is unchanged in mutants as compared with controls, except for the 28 hpf stage where it is smaller, but this appears to be a transient phenomenon, since no change is detected at earlier or later stages (Figure 4A-D and Figure S3A-L). The difference we observe at 28 hpf is now mentioned in the revised manuscript.

The conclusions of Figures 4 and S3 would rather be that laminin allows OMP+ cells to be oriented along the medio-lateral axis whereas it would control their position along the dorsoventral axis. The authors should modify the text. It would be useful to map the distribution of OMP+ cells along the dorsoventral and mediolateral axes. The same applies to Neurog1+ cells. An analysis of skin cell movements, for example, would be useful to determine whether the effects are specific.  

We are confident that the measurements of OP dimensions in AP, DV and ML are sufficient to describe the OP shape defects observed in the sly mutants. Analysing cell distribution along the 3 axes as well as skin cell movements will be interesting to perform in the future but we consider these quantifications as being out of the scope of the present work.

(6) Laminin γ1-dependent BMs are required to define a robust boundary between the OP and the brain 

The authors must weigh this conclusion "Laminin γ1-dependent BMs serve to establish a straight boundary between the brain and OP, preventing local mixing and late convergence of the two OPs towards each other during flexion movement." Indeed, they don't really show any local mixing between the brain and OP cells. They would need to quantify in their images (Figure 5A-A' and Figure S4 A-A') the percentage of cells co-labelled by HuC and Tg(cldnb:GFP). 

We agree with the reviewer and thus replaced « reveal » by « suggest » in the conclusion of this section. 

(7) Role of Laminin γ1-dependent BMs in olfactory axon development 

An analysis of the retrograde extension movement in the axons of OMP+ ectopic neurons in the sly1 mutant condition would be useful to validate that the loss of laminin function does not play a role in this event. 

Indeed, even though we can visualise instances of retrograde extension occurring normally in sly mutants, we can not rule out that this process is affected in a subset of OP neurons, for instance in ectopic cells, which often show no axon or a misoriented axon. We added a sentence to mention this in the revised manuscript.

Minor comments and typos: 

Please check and mention the D-V/L-M or A-P/L-M orientation of the images in all figures. 

This has been checked.

Legend Figure 1: "distalmost" is missing a space "distal most". 

We checked and this word can be written without a space.

Figure 1 panel C: check the orientation (I am not sure that Dorsal is up). 

We double-checked and confirm that dorsal is up in this panel.

Movie 1 Legend: "aroung "the OP should be around the OP. 

Thanks to the reviewer for noticing the typo, we corrected it.

Reviewer #2 (Recommendations For The Authors):

The comments below are relatively minor and mostly raise questions regarding images and their presentation in the manuscript. 

• Figure 1, visualization of exit and entry points: It is a bit difficult to visualize the axon exit and entry points in these images, and in particular, to understand how the exit and entry points in C and D correspond to what is seen in F, F', H, and H'. There appears to be one resolvable break in the staining in C and D, whereas there are two distinct breaks in F-H'. Are these single optical sections? Is it possible to visualize these via 3-dimensional rendering? 

All the images presented in Figure 1 are single z-sections, which is now indicated in the Figure legend. As noticed by the reviewer, Laminin immunostainings on fixed embryos at 28 and 36 hpf suggested that the exit and entry points are facing each other, as shown in Figure 1C-D’. However, in our live imaging experiments we always observed that the exit point is slightly more ventral than the entry point (of about 10 to 20 µm). This discrepancy could be due to the fixation that precedes the immunostaining procedure, which could modify slightly the size and shape of cells/tissues. We added a sentence on this point in the text. In addition, we added new movies of the LamC1-sfGFP reporter with sparse red axonal labelling (Movie 3, see response to reviewer 1), as well as z-stacks presenting the organisation of exit and entry points in 3D (Movie 4), which should help to better illustrate the mechanisms of exit and entry point formation.

• Movie 2, p. 6, "small interruptions of the BM were already present near the axon tips, along the ventro-medial wall of the OP." This is a bit difficult to assess since the movie seems to show at least one other small interruption in the BM in addition to the exit point, in particular, one slightly dorsal to the exit point. Was this seen in other samples, or in different optical sections? 

Indeed the exit and entry points often appear as regions with several, small BM interruptions, rather than single holes in the BM. We now show in revised Movie 4 the two z-stacks (the merge and the single channel for green fluorescence) corresponding to the last time points of the movies showing exit and entry point formation in Movie 2, where several BM interruptions can be seen for both the exit and entry points. We had already mentioned this observation in the legend of Movie 2, and we added a sentence on this point in the main text of the revised manuscript. This is also represented for both exit and entry points in the new schematics in revised Fig. 1K and its legend. 

• Movie 2, p. 6, "The opening of the entry point through the brain BM was concomitant with the arrival of the RFP+ axons, suggesting that the axons degrade or displace BM components to enter the brain." Similar to the questions regarding the exit point, it was a bit difficult to evaluate this statement. There appears to be a broader region of BM discontinuity more dorsal to the arrowhead in Movie 2. A single-channel movie of just the laminin fluorescence might help to convey the extent of the discontinuity. As with above, was this seen in other samples, or in different optical sections?  

See our response to the previous comment.

• Figure 1H, I, "the distal tip of the RFP+ axons migrated in close proximity with the brain's BM." This is again a bit difficult to see, and quite different than what is seen in Figure 4A, in which the axons do not seem close to the BM in this section. Is it possible to visualize this via 3-dimensional rendering? 

In fixed embryos or in live imaging experiments, we observed that, once entered in the brain, the distal tips (the growth cones) of the axons are located close to the BM of the brain. However, this is not the case of the axon shafts which, as development proceeds, are located further away from the BM. This can clearly be seen at 36 hpf in Figure 1D’ and Figure 4A, as spotted by the reviewer. We modified the text to clarify this point.

• Figure 2J, J', p. 7, the gap between the OP and brain cells of sly mutants "was most often devoid of electron-dense material." It is difficult to see this loss of electron-dense material in 2J'. The thickness of the space is quantified well and is clearly smaller, but the change in electron-dense material is more difficult to see.  

We looked at Figure 2 again and it seems clear to us that there is electron-dense material between the plasma membranes in controls, which is practically not seen (rare spots) in the mutants. We added a sentence mentioning that we rarely see electron-dense spots in sly mutants.

• Figure 5E-F': There are concerns about evaluating the shape of a tissue based on nuclear position. Is there a way to co-stain for cell boundaries (maybe actin?), and then quantify distortion of the dlx+ cell population using the cell boundaries, rather than nuclear staining? 

We agree with the reviewer that it is not ideal to evaluate the shape of the OP/brain boundary based on a nuclear staining. As explained in the text, we could not use the Tg(eltC:GFP) or Tg(cldnb:Gal4; UAS:RFP) reporter lines for this analysis, due to ectopic or mosaic expression. However we are confident that the segmentation of the Dlx3b immunostaining reflects the organisation of the cells at the OP/brain tissue boundary: in other data sets in which we performed Dlx3b staining with membrane labelling independently of the present study and in the wild type context, we clearly see that cell membranes are juxtaposed to the Dlx3b nuclear staining (in other words, the cytoplasm volume of OP cells is very small). 

• Figure S5E: It would be helpful to see representative images for each of the categories (Proper axon bundle; Ventral projections; Medial projections) or a schematic to understand how the phenotypes were assessed. 

To address this point we added a schematic view to illustrate the phenotypes assessed in each column of the table in revised Figure S5G.

• Figure 6, p. 12, "Laminin gamma 1-dependent BMs are essential for growth and navigation of the axons...": What fraction of the tracked axons managed to exit the OP? Given the quantitative analyses in Figure 6, one might interpret this to mean that laminin gamma 1 is not essential for axon growth (speed and persistence are largely unchanged), but rather, primarily for navigation. 

As noticed by the reviewer, the speed and persistence of axonal growth cones are largely unchanged in the sly mutants (except for the reduced persistence in the 200-400 min window, and an increased speed in the 800-1000 min window), showing that the growth cones are still motile. However, as shown by the tracks, they tend to wander around within the OP, close to the cell bodies, which results in the end in a perturbed growth of the axons. The navigation issues are rather revealed by the analysis of fixed Tg(omp:meYFP) embryos presented in the table of Figure S5G. We modified the text to separate more clearly the conclusions of the two types of experiments (fixed, transgenic embryos versus live, mosaically labelled embryos).

Reviewer #3 (Recommendations For The Authors):

Testing the hypotheses mentioned in the public review will be interesting experiments for a follow-up study, but are not essential revisions for this manuscript. 

I have only a few minor suggestions for revisions: 

P8 subheading 'Role of Laminin γ1-dependent BMs in OP coalescence' - since no major role was demonstrated here, this heading should be reworded.  

We agree with the reviewer and replaced the previous title by « OP coalescence still occurs in the sly mutant ».

P11, line 3 - the authors conclude that the forebrain is smaller 'due to' the inward convergence of the OPs. I do not think it is possible to assign causation to this when the mutant disrupts Laminin γ1 systemically - it is equally possible that the OPs move inward due to a failure of the brain to form in the normal shape. Thus, the wording should be changed here. (In the Discussion on p15, the authors mention the 'apparent distortion' of the brain, and say that it is 'possibly due' to the inward migration of the placodes', but again this could be toned down.) 

We agree with the reviewer’s comment and changed the wording of our conclusions in the Results section.

P11 and Fig. S5 - The table and text seem to be saying opposite things here. The text on p11 (3rd paragraph) indicates that the normal exit point is ventral and that this is disrupted in the mutant, with axons exiting dorsally. However, in the table, at each time point there is a higher % of axons exiting ventrally in the mutant. Please clarify. The table does not provide a % value for axons exiting dorsally - it might help to add a column to show this value. 

We are grateful to the reviewer for pointing this out, and we apologize for the lack of clarity in the first version of the manuscript. We have modified the text and Figure S5 in order to clarify the different points raised by the reviewer in this comment. The Table in Fig. S5G does not represent the % of axons showing defects, but the % of embryos showing the phenotypes. In addition, an embryo is counted in the ventral or medial projection category if it shows at least one ventral or medial projection (even if its shows a proper bundle). This is now clearly indicated in the title of the columns in the table itself and in the legend. The embryos in which the axons exit dorsally in sly mutants are actually those counted in the left column of the Table (they exit dorsally and form a bundle), as shown by the new schematics added below the table. We also added this information in the title of the left column, and mention in the legend the pictures in which this dorsal exit can be observed in the article (Figures 4B and S3E’). Having more sly mutant embryos with axons exiting dorsally is thus compatible with more embryos showing at least one ventral projection.

Fig. S6, shows the lack of neural crest cells between the olfactory placode and the brain in both laminin γ1 mutants (without a basement membrane) and foxd3 mutants (which retain the membrane). Comparison of the two mutants here is a neat experiment and the result is striking, demonstrating that it is the basement membrane, and not the neural crest, that is required for correct morphology of the olfactory placode. I think this figure should be presented as a main figure, rather than supplementary.  

Our new live imaging characterisation of NCC migration in sly mutants and control siblings (Movie 9) revealed that at 32 hpf, in the vicinity of the OP, NCC (or their derivatives) are much more numerous than the subset of NCC showing crestin expression by in situ hybridisation (compare the end of our control movie – 32 hfp, with crestin ISH shown in Figure S6A for instance). 

Thus, the extent of the NCC migration defects should be analysed in more detail in the foxd3 mutant in the future (using live imaging or other NCC markers), and for this reason we chose to keep this dataset in the supplementary Figures.

One of the first topics covered in the Discussion section is the potential role of Collagen. I was surprised to see the description on P15 'the dramatic disorganization of the Collagen IV pattern observed by immunofluorescence in the sly mutant', as I hadn't picked this up from the Results section of the paper. I went back to the relevant figure (Fig. 2) and description on p7, which does not give the same impression: 'in sly mutants, Collagen IV immunoreactivity was not totally abolished'. This suggested to me that there was only minor (not dramatic) disorganisation of the Collagen IV. This needs clarification.  

The linear, BM-like Collagen IV staining was lost in sly mutants, but not the fibrous staining which remained in the form of discrete patches surrounding the OP. We modified the text in the Results section as well as in the Figure 2 legend to clarify our observations made on embryos immunostained for Collagen IV.

Typos etc 

P5 - '(ii) above of the neuronal rosette' - delete the word 'of'. 

P5 two lines below this - ensheathed. 

P10 - '3 distinct AP levels' (delete s from distincts). 

P10 - distortion (not distorsion) . 

P12 - 'From 14 hpf, they' should read 'From 14 hpf, neural crest cells'. 

P15, line 1 - 'is a consequence of' rather than 'is consecutive of'? 

P22 'When the data were not normal,' should read 'When the data were not normally distributed,'. 

We thank the reviewer for noticing these typos and have corrected them.

General 

Please number lines in future manuscripts for ease of reference. 

This has been done.

original source?

BEGINNINGS WITH "THE THE" AND LL and EL ELtelitenkigniYONNA

This article is about the U.S. government project on psychics. For other uses, see Stargate (disambiguation). Part of a series on the Paranormal Main articles Skepticism Parapsychology Related

vte

The Stargate Project was a secret U.S. Army unit established in 1977[1][2] at Fort Meade, Maryland, by the Defense Intelligence Agency (DIA) and SRI International (a California contractor) to investigate the potential for psychic phenomena in military and domestic intelligence applications. The project, and its precursors and sister projects, originally went by various code names – 'Gondola Wish', 'Stargate', 'Grill Flame', 'Center Lane', 'Project CF', 'Sun Streak', 'Scanate' – until 1991 when they were consolidated and rechristened as the "Stargate Project".

The Stargate Project's work primarily involved remote viewing, the purported ability to psychically "see" events, sites, or information from a great distance.[3] The project was overseen until 1987 by Lt. Frederick Holmes "Skip" Atwater, an aide and "psychic headhunter" to Maj. Gen. Albert Stubblebine, and later president of the Monroe Institute.[4] The unit was small scale, comprising about 15 to 20 individuals, and was run out of "an old, leaky wooden barracks".[5]

The Stargate Project was terminated and declassified in 1995 after a CIA report concluded that it was never useful in any intelligence operation. Information provided by the program was vague and included irrelevant and erroneous data, and there were suspicions of inter-judge reliability.[6]: 5–4  The program was featured in the 2004 book and 2009 film, both titled The Men Who Stare at Goats,[7][8][9][10] although neither mentions it by name. George Stephanopoulos, in his 2024 book The Situation Room, mentions the project by the name Grill Flame, in discussing a May 8, 1980, Situation Room briefing for President Carter, after Carter's failed hostage rescue mission in Iran on April 24, 1980.[11] Background

The CIA and DIA decided they should investigate and know as much about it as possible. Various programs were approved yearly and re-funded accordingly. Reviews were made semi-annually at the Senate and House select committee level. Work results were reviewed, and remote viewing was attempted with the results being kept secret from the "viewer". It was thought that if the viewer was shown they were incorrect it would damage the viewer's confidence and skill. This was standard operating procedure throughout the years of military and domestic remote viewing programs. Feedback to the remote viewer of any kind was rare; it was kept classified and secret.[12]

Remote viewing attempts to sense unknown information about places or events. Normally it is performed to detect current events, but during military and domestic intelligence applications viewers claimed to sense things in the future, experiencing precognition.[13] History 1970s

In 1970 United States intelligence sources believed that the Soviet Union was spending 60 million roubles annually on "psychotronic" research. In response to claims that the Soviet program had produced results, the CIA initiated funding for a new program known as SCANATE ("scan by coordinate") in the same year.[14] Remote viewing research began in 1972 at the Stanford Research Institute (SRI) in Menlo Park, California.[14][15] Proponents (Russell Targ and Harold Puthoff) of the research said that a minimum accuracy rate of 65% required by the clients was often exceeded in the later experiments.[14]

Physicists Targ and Puthoff began testing psychics for SRI in 1972, including one who would later become an international celebrity, Israeli Uri Geller. Their apparently successful results garnered interest within the U.S. Department of Defense. Ray Hyman, professor of psychology at the University of Oregon, was asked by Air Force psychologist Lt. Col. Austin W. Kibler (1930–2008) – then Director of Behavioral Research for ARPA – to go to SRI and investigate. He was to specifically evaluate Geller. Hyman's report to the government was that Geller was a "complete fraud" and as a consequence Targ and Puthoff lost their government contract to work further with him. The result was a publicity tour for Geller, Targ, and Puthoff to seek private funding for further research work on Geller.[16]

One of the project's successes was the location of a lost Soviet spy plane in 1976 by Rosemary Smith, a young administrative assistant recruited by project director Dale Graff.[17]

In 1977 the Army Assistant Chief of Staff for Intelligence (ACSI) Systems Exploitation Detachment (SED) started the Gondola Wish program to "evaluate potential adversary applications of remote viewing".[14] Army Intelligence then formalized this in mid-1978 as an operational program Grill Flame, based in buildings 2560 and 2561 at Fort Meade, in Maryland (INSCOM "Detachment G").[14] 1980s

In early 1979 the research at SRI was integrated into 'Grill Flame', which was redesignated INSCOM 'Center Lane' Project (ICLP) in 1983. In 1984 the existence of the program was reported by Jack Anderson, and in that year it was unfavorably received by the National Academy of Sciences National Research Council. In late 1985 the Army funding was terminated, but the program was redesignated 'Sun Streak' and funded by the DIA's Scientific and Technical Intelligence Directorate (office code DT-S).[14] 1990s

In 1991 most of the contracting for the program was transferred from SRI to Science Applications International Corporation (SAIC), with Edwin May controlling 70% of the contractor funds and 85% of the data. Its security was altered from Special Access Program (SAP) to Limited Dissemination (LIMDIS), and it was given its final name, STARGATE.[14] Closure (1995)

In 1995 the defense appropriations bill directed that the program be transferred from DIA to CIA oversight. The CIA commissioned a report by the American Institutes for Research (AIR) that found that remote viewing had not been proved to work by a psychic mechanism, and said it had not been used operationally.[6]: 5–4  The CIA subsequently cancelled and declassified the program.[14]

In 1995 the project was transferred to the CIA and a retrospective evaluation of the results was done. The appointed panel consisted primarily of Jessica Utts, Meena Shah and Ray Hyman. Hyman had produced an unflattering report on Uri Geller and SRI for the government two decades earlier, but the psychologist David Marks found Utts' appointment to the review panel "puzzling" given that she had published papers with Edwin May, considering this joint research likely to make her "less than [im]partial".[3] A report by Utts claimed the results were evidence of psychic functioning; however, Hyman in his report argued Utts's conclusion that ESP had been proven to exist, especially precognition, was premature and the findings had not been independently replicated.[18] Hyman came to the conclusion:

Psychologists, such as myself, who study subjective validation find nothing striking or surprising in the reported matching of reports against targets in the Stargate data. The overwhelming amount of data generated by the viewers is vague, general, and way off target. The few apparent hits are just what we would expect if nothing other than reasonable guessing and subjective validation are operating.[19]

A later report by AIR came to a negative conclusion. Joe Nickell has written:

Other evaluators – two psychologists from AIR – assessed the potential intelligence-gathering usefulness of remote viewing. They concluded that the alleged psychic technique was of dubious value and lacked the concreteness and reliability necessary for it to be used as a basis for making decisions or taking action. The final report found "reason to suspect" that in "some well publicised cases of dramatic hits" the remote viewers might have had "substantially more background information" than might otherwise be apparent.[20]

According to AIR, which performed a review of the project, no remote viewing report ever provided actionable information for any intelligence operation.[21][6]: 5–4 

Based upon the collected findings, which recommended a higher level of critical research and tighter controls, the CIA terminated the 20 million dollar project, citing a lack of documented evidence that the program had any value to the intelligence community. Time magazine stated in 1995 three full-time psychics were still working on a $500,000-a-year budget out of Fort Meade, Maryland, which would soon close.[21]

David Marks in his book The Psychology of the Psychic (2000) discussed the flaws in the Stargate Project in detail.[3] Marks wrote that there were six negative design features of the experiments. The possibility of cues or sensory leakage was not ruled out, no independent replication, some experiments were conducted in secret, making peer-review impossible. Marks noted that the judge Edwin May was also the principal investigator for the project and this was problematic, making a huge conflict of interest with collusion, cuing and fraud being possible. Marks concluded the project was nothing more than a "subjective delusion" and after two decades of research it had failed to provide any scientific evidence for the legitimacy of remote viewing.[3]

The Stargate Project was terminated in 1995 following an independent review which concluded:

The foregoing observations provide a compelling argument against continuation of the program within the intelligence community. Even though a statistically significant effect has been observed in the laboratory, it remains unclear whether the existence of a paranormal phenomenon, remote viewing, has been demonstrated. The laboratory studies do not provide evidence regarding the origins or nature of the phenomenon, assuming it exists, nor do they address an important methodological issue of inter-judge reliability.

Further, even if it could be demonstrated unequivocally that a paranormal phenomenon occurs under the conditions present in the laboratory paradigm, these conditions have limited applicability and utility for intelligence gathering operations. For example, the nature of the remote viewing targets are vastly dissimilar, as are the specific tasks required of the remote viewers. Most importantly, the information provided by remote viewing is vague and ambiguous, making it difficult, if not impossible, for the technique to yield information of sufficient quality and accuracy of information for actionable intelligence. Thus, we conclude that continued use of remote viewing in intelligence gathering operations is not warranted.[6]: E-4–E-5

In January 2017, the CIA published records online of the Stargate Project as part of the CREST archive.[22] Methodology

The Stargate Project created a set of protocols designed to make the research of clairvoyance and out-of-body experiences more scientific, and to minimize as much as possible session noise and inaccuracy. The term "remote viewing" emerged as shorthand to describe this more structured approach to clairvoyance. Project Stargate would only receive a mission after all other intelligence attempts, methods, or approaches had already been exhausted.[13]: 21 

It was reported that at peak manpower there were over 22 active military and civilian remote viewers providing data. People leaving the project were not replaced. When the project closed in 1995 this number had dwindled down to three. One was using tarot cards. According to Joseph McMoneagle, "The Army never had a truly open attitude toward psychic functioning". Hence, the use of the term "giggle factor"[23] and the saying, "I wouldn't want to be found dead next to a psychic".[12] Civilian personnel Hal Puthoff Main article: Harold E. Puthoff

In the 1970s, CIA and DIA granted funds to Harold E. Puthoff to investigate paranormal abilities, collaborating with Russell Targ in a study of the purported psychic abilities of Uri Geller, Ingo Swann, Pat Price, Joseph McMoneagle and others, as part of the Stargate Project,[24] of which Puthoff became a director.[25]

As with Ingo Swann and Pat Price, Puthoff attributed much of his personal remote viewing skills to his involvement with Scientology whereby he had attained, at that time, the highest level. All three eventually left Scientology in the late 1970s.

Puthoff worked as the principal investigator of the project. His team of psychics is said[who?] to have identified spies, located Soviet weapons and technologies, such as a nuclear submarine in 1979 and helped find lost SCUD missiles in the first Gulf War and plutonium in North Korea in 1994.[26] Russell Targ Russell Targ Main article: Russell Targ

In the 1970s, Russell Targ began working with Harold Puthoff on the Stargate Project, while working with him as a researcher at Stanford Research Institute.[27][28] Edwin May

Edwin C. May joined the Stargate Project in 1975 as a consultant and was working full-time in 1976. The original project was part of the Cognitive Sciences Laboratory managed by May. With more funding in 1991 May took the project to the Palo Alto offices at SAIC. This would last until 1995 when the CIA closed the project.[3]

May worked as the principal investigator, judge and the star gatekeeper for the project. Marks says this was a serious weakness for the experiments as May had conflict of interest and could have done whatever he wanted with the data. Marks has written that May refused to release the names of the "oversight committee" and refused permission for him to give an independent judging of the Stargate transcripts. Marks found this suspicious, commenting "this refusal suggests that something must be wrong with the data or with the methods of data selection."[3] Ingo Swann Main article: Ingo Swann

Originally tested in the "Phase One" were OOBE-Beacon "RV" experiments at the American Society for Psychical Research,[29][unreliable source?] under research director Karlis Osis.[citation needed] A former OT VII Scientologist,[30][self-published source] who alleged to have coined the term 'remote viewing' as a derivation of protocols originally developed by René Warcollier, a French chemical engineer in the early 20th century, documented in the book Mind to Mind, Classics in Consciousness Series Books by (ISBN 978-1571743114)[citation needed]. Swann's achievement was to break free from the conventional mold of casual experimentation and candidate burn out, and develop a viable set of protocols that put clairvoyance within a framework named "Coordinate Remote Viewing" (CRV).[31] In a 1995 letter Edwin C. May wrote he had not used Swann for two years because there were rumors of him briefing a high level person at SAIC and the CIA on remote viewing and aliens, ETs.[32] Pat Price

A former Burbank, California, police officer and former Scientologist who participated in a number of Cold War era remote viewing experiments, including the US government-sponsored projects SCANATE and the Stargate Project. Price joined the program after a chance encounter with fellow Scientologists (at the time) Harold Puthoff and Ingo Swann near SRI.[33] Working with maps and photographs provided to him by the CIA, Price claimed to have been able to retrieve information from facilities behind Soviet lines. He is probably best known for his sketches of cranes and gantries which appeared to conform to CIA intelligence photographs. At the time, the CIA took his claims seriously.[34] Military personnel Lieutenant General James Clapper Main article: James Clapper

The project leader[failed verification] in the 1990s was Lt. Gen. Clapper who later rose to infamy[unbalanced opinion?] as the Director of National Intelligence.[35] Albert Stubblebine Major General Albert Stubblebine Main article: Albert Stubblebine

A key sponsor of the research internally at Fort Meade, Maryland, Maj. Gen. Stubblebine was convinced of the reality of a wide variety of psychic phenomena. He required that all of his battalion commanders learn how to bend spoons à la Uri Geller, and he himself attempted several psychic feats, even attempting to walk through walls. In the early 1980s he was responsible for the United States Army Intelligence and Security Command (INSCOM), during which time the remote viewing project in the US Army began. Some commentators have confused a "Project Jedi", allegedly run by Special Forces primarily out of Fort Bragg, with Stargate. After some controversy involving these experiments, including alleged security violations from uncleared civilian psychics working in Sensitive Compartmented Information Facilities (SCIFs), Stubblebine was placed on retirement. His successor as the INSCOM commander was Maj. Gen. Harry Soyster, who had a reputation as a much more conservative and conventional intelligence officer. Soyster was not amenable to continuing paranormal experiments and the Army's participation in Project Stargate ended during his tenure.[12] David Morehouse

In his book, Psychic Warrior: Inside the CIA's Stargate Program : The True Story of a Soldier's Espionage and Awakening (2000, St. Martin's Press, ISBN 978-1902636207), Morehouse claims to have worked on hundreds of remote viewing assignments, from searching for a Soviet jet that crashed in the jungle carrying an atomic bomb, to tracking suspected double agents.[36] Joseph McMoneagle Main article: Joseph McMoneagle

McMoneagle claims he had a remarkable memory of very early childhood events. He grew up surrounded by alcoholism, abuse and poverty. As a child, he had visions at night when scared, and began to hone his psychic abilities in his teens for his own protection when he hitchhiked. He enlisted to get away. McMoneagle became an experimental remote viewer while serving in U.S. Army Intelligence.[12] Ed Dames

Dames' role was intended to be as session monitor and analyst as an aid to Fred Atwater[37][self-published source] rather than a remote viewer, Dames received no formal remote viewing training. After his assignment to the remote viewing unit at the end of January 1986, he was used to "run" remote viewers (as monitor) and provide training and practice sessions to viewer personnel. He soon established a reputation for pushing CRV to extremes, with target sessions on Atlantis, Mars, UFOs, and aliens. He has been a frequent guest on the Coast to Coast AM radio shows.[38] References

"Government-Sponsored Research On Parapsychology". www.encyclopedia.com. "Defense Intelligence Agency (DT-S)" (PDF). nsarchive2.gwu.edu. Marks, David. (2000). The Psychology of the Psychic (2nd ed.). Buffalo, NY: Prometheus Books. pp. 71–96. ISBN 1-57392-798-8 Atwater, F. Holmes (2001), Captain of My Ship, Master of My Soul: Living with Guidance; Hampton Roads Publishing Company Weeks, Linton (December 4, 1995). "Up Close & Personal With a Remote Viewer: Joe McMoneagle Defends the Secret Project". The Washington Post. p. B1. ISSN 0190-8286. Mumford, Michael D.; Rose, Andrew M.; Goslin, David A. (September 29, 1995). An Evaluation of Remote Viewing: Research and Applications (PDF) (Report). The American Institutes for Research – via Federation of American Scientists. "[R]emote viewings have never provided an adequate basis for 'actionable' intelligence operations – that is, information sufficiently valuable or compelling so that action was taken as a result." Heard, Alex (10 April 2010), "Close your eyes and remote view this review", Union-Tribune San Diego, Union-Tribune Publishing Co. [Book review of The Men Who Stare at Goats]: "This so-called "remote viewing" operation continued for years, and came to be known as Star Gate." Clarke, David (2014), Britain's X-traordinary Files, London: Bloomsbury Publishing, p. 112: "The existence of the Star Gate project was not officially acknowledged until 1995... then became the subject of investigations by journalists Jon Ronson [etc]... Ronson's 2004 book, The Men Who Stare at Goats, was subsequently adapted into a 2009 movie..." Shermer, Michael (November 2009), “Staring at Men Who Stare at Goats” @ Michaelshermer.com: "... the U.S. Army had invested $20 million in a highly secret psychic spy program called Star Gate. ... In The Men Who Stare at Goats Jon Ronson tells the story of this program, how it started, the bizarre twists and turns it took, and how its legacy carries on today." Krippner, Stanley and Harris L. Friedman (2010), Debating Psychic Experience: Human Potential Or Human Illusion?, Santa Barbara, CA: Praeger/Greenwood Publishing Group, p. 154: "The story of Stargate was ... featured in a film based on the book The Men Who Stare at Goats, by British investigative journalist Jon Ronson (2004)". "CNN.com - Transcripts (Amanpour)". transcripts.cnn.com. June 3, 2024. Retrieved June 9, 2024. McMoneagle, Joseph (2006). Memoirs of a psychic spy : the remarkable life of U.S. Government remote viewer 001. Charlottesville, VA: Hampton Roads Pub. Co. ISBN 978-1-5717-4482-1. McMoneagle, Joseph (1998). The ultimate time machine : a remote viewer's perception of time and predictions for the new millennium. Charlottesville, VA: Hampton Roads Pub. Co. ISBN 978-1-5717-4102-8. Pike, John (December 29, 2005). "Star Gate [Controlled Remote Viewing]". Federation of American Scientists. May, Edwin C. (1996). "The American Institutes for Research review of the Department of Defense's STAR GATE program: A commentary" (PDF). Journal of Scientific Exploration. 10 (1): 89–107. Interview, Ray Hyman, in An Honest Liar, a 2014 documentary film by Left Turn Films; Pure Mutt Productions; Part2 Filmworks. (The quoted remarks commence at 21 min, 45 sec.) Jacobsen, Annie (2017). "Paraphysics". Phenomena: The Secret History of the U.S. Government's Investigations into Extrasensory Perception and Psychokinesis. Little, Brown. ISBN 978-0-316-34937-6. Evaluation of a Program on Anomalous Mental Phenomena Archived June 16, 2017, at the Wayback Machine by Ray Hyman. "The Evidence for Psychic Functioning: Claims vs. Reality" by Ray Hyman; Skeptical Inquirer, Vol. 20.2, Mar/Apr 1996. "Remotely Viewed? The Charlie Jordan Case" by Joe Nickell; Skeptical Inquirer, Vol. 11.1, Mar 2001. Waller, Douglas (December 11, 1995). "The Vision Thing". Time magazine. p. 45. Archived from the original on February 9, 2007. "Search: 'Stargate'". Freedom of Information Act Electronic Reading Room. Central Intelligence Agency. McMoneagle, Joseph (1997). Mind trek : exploring consciousness, time, and space through remote viewing (Revised ed.). Norfork, VA: Hampton Roads Pub. p. 247. ISBN 978-1-8789-0172-9. Popkin, Jim (November 12, 2015). "Meet the former Pentagon scientist who says psychics can help American spies". Newsweek. Pilkington, Mark (June 5, 2003). "The remote viewers". The Guardian. "Fort Meade, Maryland, where psychics gathered to remotely spy on the U.S. Embassy in Iran during the hostage crisis". Miami Herald. Nickell, Joe (March 2001). "Remotely viewed? The Charlie Jordan case". Skeptical Inquirer. Vol. 11, no. 1. "Dr. Harold Puthoff". arlingtoninstitute.org. The Arlington Institute. 2008. Archived from the original on March 3, 2013. "Interview: A New Biopic Charts the Life of Ingo Swann, the 'Father of Remote Viewing'". Outerplaces.com. Archived from the original on April 29, 2018. Retrieved April 28, 2018. "An Interview with Indo Swann". The Wise Old Goat – The Personal Website of Michel Snoeck. Retrieved April 28, 2018. "An Outsider's Remote View of All Things: Ingo Swann". Chelseanow.com. Archived from the original on April 29, 2018. Retrieved April 28, 2018. "A Dynamic PK Experiment with Ingo Swann". Central Intelligence Agency. Archived from the original on April 29, 2018. Retrieved April 28, 2018. Pat Price URL:http://www.scientolipedia.org/info/Pat_Price (Scientolipedia) Sources:

Schnabel, Jim (1997) Remote Viewers: The Secret History of America's Psychic Spies Dell, 1997 , ISBN 0-440-22306-7
Richelson, Jeffrey T The Wizards of Langley: Inside the CIA's Directorate of Science and Technology
Mandelbaum, W. Adam The Psychic Battlefield: A History of the Military-Occult Complex
Picknett, Lynn, Prince Clive The Stargate Conspiracy
Chalker, Bill Hair of the Alien: DNA and Other Forensic Evidence of Alien Abductions
Constantine, Alex Psychic Dictatorship in the USA

https://documents2.theblackvault.com/documents/cia/stargate/STARGATE%20%2311%20549/Part0003/CIA-RDP96-00789R002500240004-5.pdf [bare URL PDF] "Psychic Warrior: Inside the CIA's Stargate Program: The True Story of a Soldier's Espionage and Awakening". Publishers Weekly. Retrieved April 28, 2018. "Stargate: People and researchers". Bibliotecapleyades.net.

Ronson, Jon (2006). The Men Who Stare at Goats. Simon & Schuster. pp. 93–94. ISBN 978-0-7432-7060-1.

Further reading

Burnett, Thom, ed. (2006). "Psi-War: Operations Grillflame and Stargate". Conspiracy Encyclopedia: The encyclopedia of conspiracy theories. Franz Steiner Verlag. p. 153. ISBN 978-1-84340-381-4.
Caroll, Robert Todd (2012). "Remote Viewing". In the Skeptic's Dictionary. John Wiley & Sons. ISBN 0-471-27242-6.
Hines, Terence (2003). Pseudoscience and the Paranormal. Prometheus Books. ISBN 1-57392-979-4.
Hyman, Ray (1996). "Evaluation of the Military's Twenty-year Program on Psychic Spying". Skeptical Inquirer 20: 21–26.
Morehouse, David (1996). Psychic Warrior, St. Martin's Paperbacks, ISBN 978-0-312-96413-9. Morehouse was a psychic in the program.
Ronson, Jon (2004). The Men Who Stare at Goats. Picador. ISBN 0-330-37547-4. Written to accompany the TV series Crazy Rulers of the World. The US military budget cuts after the Vietnam war and how it all began.
Sessions, Abigail (2016). "STARGATE, Project (1970s–1995)". In Goldman, Jan (ed.). The Central Intelligence Agency: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies, Volume 1. ABC-CLIO. pp. 352–353. ISBN 978-1-61069-092-8.
Smith, Paul (2004). Reading the Enemy's Mind: Inside Star Gate: America's Psychic Espionage Program, Forge Books. ISBN 0-312-87515-0
Utts, Jessica (1996). "An Assessment of the Evidence for Psychic Functioning". Journal of Scientific Exploration. 10 (1): 3–30. CiteSeerX 10.1.1.685.2525. 0892-3310/96.

External links

Report from 1995 about the program from American Institutes for Research
Declassified analytical report (1983) related to the project
Declassified documents about the project on the website of the CIA

vte

Defense Intelligence Agency Categories:

1978 establishments in MarylandAmerican secret government programsCentral Intelligence Agency operationsCold War tacticsDefense Intelligence AgencyEspionage projectsHuman subject research in the United StatesPseudoscienceRemote viewing

image.png /en-us/articles/360023851591-How-do-I-view-DRM-protected-content

This is ABSSOLUTELY NOTHING BUT "UN SE LINUX ALED" MACROMEDIA SHOCKWAVE FLASH all over again; it is embarrassingly not just "bugs in advanced mathematics hidden inside frame buffer mathematics and "OpenGL" it's a significant glaring opening that brave has sbrvaely alerted me to as a "Google add-on to Chome" that makes yet another floating .VA inside Virginia or .IT ... your "Infomration Technology" departments are patenty compromised by Plex sovereignty, weither it be of Menlo or Sunnyvale;

the Mountain will not prevail against Veritae Trantor.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED SURVIVABILITY, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF IMMORTALITY NOR MORTALITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The third law of thermodynamics states that the entropy of a closed system at thermodynamic equilibrium approaches a constant value when its temperature approaches absolute zero. This constant value cannot depend on any other parameters characterizing the system, such as pressure or applied magnetic field. At absolute zero (zero kelvins) the system must be in a state with the minimum possible energy.

Entropy is related to the number of accessible microstates, and there is typically one unique state (called the ground state) with minimum energy.^[1]^ In such a case, the entropy at absolute zero will be exactly zero. If the system does not have a well-defined order (if its order is glassy, for example), then there may remain some finite entropy as the system is brought to very low temperatures, either because the system becomes locked into a configuration with non-minimal energy or because the minimum energy state is non-unique. The constant value is called the residual entropy of the system.^[2]^

In physics, physical chemistry and engineering, fluid dynamics is a subdiscipline of fluid mechanics that describes the flow of fluids---liquids and gases. It has several subdisciplines, including aerodynamics (the study of air and other gases in motion) and hydrodynamics (the study of liquids in motion). Fluid dynamics has a wide range of applications, including calculating forces and moments on aircraft, determining the mass flow rate of petroleum through pipelines, predicting weather patterns, understanding nebulae in interstellar space and modelling fission weapon detonation.

Fluid dynamics offers a systematic structure---which underlies these practical disciplines---that embraces empirical and semi-empirical laws derived from flow measurement and used to solve practical problems. The solution to a fluid dynamics problem typically involves the calculation of various properties of the fluid, such as flow velocity, pressure, density, and temperature, as functions of space and time.

Before the twentieth century, hydrodynamics was synonymous with fluid dynamics. This is still reflected in names of some fluid dynamics topics, like magnetohydrodynamics and hydrodynamic stability, both of which can also be applied to gases.^[1]^

In ufology, a close encounter is an event in which a person witnesses an unidentified flying object (UFO). This terminology and the system of classification behind it were first suggested in astronomer and UFO researcher J. Allen Hynek's 1972 book The UFO Experience: A Scientific Inquiry.[1] Categories beyond Hynek's original three have been added by others but have not gained universal acceptance, mainly because they lack the scientific rigor that Hynek aimed to bring to ufology.[2]

Sightings more than 150 metres (500 ft) from the witness are classified as daylight discs, nocturnal lights or radar/visual reports.[3] Sightings within about 150 metres (500 ft) are subclassified as various types of close encounters. Hynek and others argued that a claimed close encounter must occur within about 150 metres (500 ft) to greatly reduce or eliminate the possibility of misidentifying conventional aircraft or other known phenomena.[4]

Hynek's scale became well known after being referenced in a 1977 film, Close Encounters of the Third Kind, which is named after the third level of the scale. Promotional posters for the film featured the three levels of the scale, and Hynek himself makes a cameo appearance near the end of the film.

https://www.independent.co.uk/tech/project-star-gate-cia-central-intelligence-agency-a7534191.html What is "remote coordinate viewing" .... and "how do I get on the payroll?

Maybe if I waste some more time writing about "the perpetual motion machine" and the absolute simplicity of the duality of that and of course, the First Law, you know "an object in motion tends to stay in motion, unless opposed by an equal an opposite force--either that or some kind of mass hysteria against the idea that things can just keep on going and going and going without any kind of propulsion.

It's things like "the air we breathe" and the course our rockets veer the Holy vessel of all humanity off by "just a smidgen" that sort of remind me what "equal and opposite force" mean, in sum and total, of all the things we've done and all the things we will ever do.

that's not fiction; that remote cooridate viewing thing; they actually "had a program investigating psychic powers--like "we give you longitude and latitude and you "scry" look into a crystall ball and tell me if you can see what's there. honestly; icalled it "on the payroll" a way to pay people for being ... "over their head on the floor about the hub of dark.fail

Isn't that sweet?

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

This is an interesting and valuable study that uses multiple approaches to understand the role of bursting involving voltage-gated calcium channels within the mediodorsal thalamus in the sedative-hypnotic effects of alcohol. Given its unique functional roles and connectivity pattern, the idea that the mediodorsal thalamus may have a fundamental role in regulating alcohol-induced transitions in consciousness state would be both important for researchers investigating thalamocortical dynamics and more broadly interesting for understanding brain function. In addition, the author's examination of the role of the voltage-gated calcium channel Cav3.1 provides some evidence that burst-firing mediated by this channel in the thalamus is functionally important for behavioral-state transitions. While many previous studies have suggested an analogous role for sleep-state regulation, the evidence for an analogous role of this type of bursting in sedative-induced transitions is more limited. Despite the importance of these results, however, there is some concern that the manipulations and recording approaches employed by the authors may affect other thalamic nuclei adjacent to the MD, such as the central lateral nucleus, which has also been implicated in controlling state transitions. The evidence for a specific role of the mediodorsal thalamus is therefore somewhat incomplete, and so additional validation is needed.

Strengths:

This study employs multiple, complementary research approaches including behavioral assays, sh-RNAbased localized knockdown, single-unit recordings, and patterned optogenetic interventions to examine the role of activity in the mediodorsal thalamus in the sedative-hypnotic effects of alcohol. Experiments and analyses included in the manuscript generally appear well conceived and are also generally well executed. Sample sizes are sufficiently large and statistical analysis appears generally appropriate though in some cases additional quantification would be helpful. The findings presented are novel and provide some interesting insight into the role of the thalamus as well as voltage-gated calcium channels within this region in controlling behavioral state transitions induced by alcohol. In particular, the observed effects of selective knockout along with recordings in total knockout of the voltage-gated calcium channel, Cav3.1, which has previously been implicated in bursting dynamics as well as state transitions, particularly in sleep, together suggest that the transition of thalamic neurons to a bursting pattern of firing from a more constant firing is important for transition to the sedated state produced by ethanol intoxication. While previous studies have similarly implicated Cav3.1 bursting in behavioral state transitions, the direct optogenetic interventions and single-unit recordings provide valuable new insight. These findings may also have interesting implications for the relationship between sleep process disruption associated with ethanol dependence, although the authors do not appear to examine this directly or extensively discuss these implications of their findings.

Weaknesses:

A key claim of the study is that the mediodorsal thalamus is specifically important for the sedative-hypnotic effect of ethanol and that a transition to a bursting pattern of firing in this circuit facilitates these effects due to a loss of a more constant tonic firing pattern. Despite the generally clear observed effects across the included experiments, however, the evidence presented does not fully support that the mediodorsal thalamus, in particular, is involved. This distinction is important because some previous studies have suggested that another thalamic nucleus which is very close to the mediodorsal thalamus, the central-lateral thalamus, has previously been suggested to play a role in preventing sedative-induced transitions. Despite its proximity to the mediodorsal thalamus, the central-lateral thalamus has a substantially different pattern of connectivity so distinguishing which region is impacted is important for understanding the findings in the manuscript. While sh- RNA knockdown appears to be largely centered in the mediodorsal thalamus in the example shown, (Figure 2) this is rather minimal evidence and it is also not well explained (indeed, the relevant panels do not even appear to be referenced in the text of the manuscript) and the consistency of the knockdown targeting is not quantified. Additional evidence should be provided to validate this approach. Similarly, while an example is shown for the expression of ChR2 (Fig. 5) there seems to be some spread of expression outside of the mediodorsal thalamus even in his example raising a concern about how regionally specific this effect.

The recordings targeting the mediodorsal thalamus could provide evidence of a direct association between changes in activity specifically in this part of the thalamus with the behavioral measures but there are currently some issues with making this link. One difficulty is that, although lesions are shown in Figure S5 to validate recording locations, this figure is relatively unclear and the examples appear to be taken from a different anterior/posterior location compared to the reference diagram. A larger image and improved visualization of the overall set of lesion locations that includes multiple anterior/posterior coronal sections would be helpful. Moreover, even for these example images, it is difficult to evaluate whether these are in the mediodorsal thalamus, particularly given the small size of the image shown. Ideally, an example image that is more obviously in the mediodorsal thalamus would also be included. Finally, an assessment of the relationship between the approximate locations of recorded neurons across the tetrode arrays and the behavioral measures would be very helpful in supporting the unique role of the mediodorsal thalamus. The lack of these direct links, in combination with the histological issues, reduces the insight that can be gained from this study.

In addition to the key experimental issues mentioned above, there are often problems in the text of the manuscript with reasoning or at least explanation as well as numerous minor issues with editing. The most substantial such issue is the lack of clarity in discussing the mediodorsal thalamus and other adjacent thalamic nuclei, such as the central-lateral nucleus, in the author's discussion of previous findings. Given that at last one of the manuscripts cited by the authors (Saalman, Front. Sys. Neuro. 2014) has directly claimed that central-lateral, rather than the mediodorsal, thalamus is important for arousal regulation related to a conscious state, this distinction should be addressed clearly in the discussion rather than papered over by grouping multiple thalamic nuclei as being medial. As part of this discussion, it would be important to consider additional relevant literature including Bastos et al., eLife, 2021 and Redinbaugh et al., Neuron, 2020 which are quite critical but currently do not appear to be cited. Considering additional literature relevant to the function of the mediodorsal thalamus would also be beneficial. While the methods employed generally seem sound, the description in the methods section is lacking in detail and is often difficult to follow. Analysis methods such as the burst index appear to only be given a brief explanation in the text and appear not to be mentioned in the methods section. Similarly, the staining method used in Figure 2 does not appear to be described in the methods section. The most substantial case is for the UMAP approach used in Figure 4-E which does not appear to be described in the methods or even described in the main text. The lack of detailed descriptions makes it difficult to evaluate the applicability and quality of the experimental and analytical approaches. Citations justifying the use of methods such as the approach to separate regular spiking and narrow spiking neuron subtypes are also needed.

Beyond the problems with content and reasoning discussed above, there are also some relatively minor issues with the clarity of writing throughout the paper (for example, in the abstract the authors refer to "the ethanol resistance behavior in WT mice" but it is difficult to parse what they mean by this statement. Similarly, the next sentence "These results support that the maintenance..." while clearer, is not well phrased. Though individually minor, issues like this re-occur throughout the manuscript and sometimes make it difficult to follow so the text should be revised to correct them. There are also some problems with labels such as the labels of A1/A2 in Figure 4, which appear to be incorrect. Also, S7 has no label] on the B panels. Finally, some references are not included (only a label of [ref]).

Reviewer #2 (Public Review):

In the current study, Latchoumane and collaborators focus on the Cav3.1 calcium channels in the mediodorsal thalamic nucleus as critical players in the regulation of brain-states and ethanol resistance in mice. By combining behavioural, electrophysiological, and genetic techniques, they report three main findings. First, KO Cav3.1 mice exhibit resistance to ethanol-induced sedation and sustained tonic firing in thalamocortical units. Second, knocked-down Cav3.1 mice reproduce the same behaviour when the mediodorsal, but not the ventrobasal, thalamic nucleus is targeted. Third, either optogenetic or electric stimulation of the mediodorsal thalamus reduces ethanol-induced sedation in control animals.

Overall, the study is well designed and performed, correctly controlled for confounds, and properly analysed. Nonetheless, it is important to address some aspects of the report. The results support the conclusions of the study. These results are likely to be relevant in the field of systems neuroscience, as they increase the molecular evidence showing how the thalamus regulates brain states.

Reviewer #1 (Recommendations For The Authors):

Aside from the additional quantification and clarification of the analysis discussed in the weakness section, in general, the experiments included in the manuscript seem reasonable. However, I would suggest one additional experiment as well as one control, both of which are relatively straightforward optogenetic experiments, that I feel would be helpful to further improve the study. First, as the authors note, the optogenetic interventions used do not directly address the relevance of the changes in bursting patterns observed in the knockout (KO), which are by far the most robust effect, with the changes in alcohol sensitivity. One approach that could help address this would be to use patterned suppression via inhibitory opsins (e.g. halorhodopsin) to "rescue" the periods of inhibition associated with bursting in the KO. Localizing this inhibition to the mediodorsal thalamus would also lend further credence to their claim that this nuclei is the relevant circuit for their observed effects. For the control, tonic activation of the ventrobasal nucleus, as the authors did for the mediodorsal nucleus, would be beneficial to rule out the possibility that the observed effect would occur with any thalamic nucleus. In addition to these experiments, I did not note the strategy for sharing data obtained through this study so this should be added.

R1 – 1: A key claim of the study is that the mediodorsal thalamus is specifically important for the sedative-hypnotic effect of ethanol and that a transition to a bursting pattern of firing in this circuit facilitates these effects due to a loss of a more constant tonic firing pattern. Despite the generally clear observed effects across the included experiments, however, the evidence presented does not fully support that the mediodorsal thalamus, in particular, is involved. This distinction is important because some previous studies have suggested that another thalamic nucleus which is very close to the mediodorsal thalamus, the central-lateral thalamus, has previously been suggested to play a role in preventing sedative-induced transitions. Despite its proximity to the mediodorsal thalamus, the central-lateral thalamus has a substantially different pattern of connectivity so distinguishing which region is impacted is important for understanding the findings in the manuscript.

R1-A1: The reviewer is right that CL has been pointed as another candidate structure with causal influence on arousal and consciousness. We have focused our efforts in including only recording single units that were from tetrode located in the MD specifically using the lesion code we explain in the method section and in response to R1 question#3. We also produced a quantification of Cav3.1 knock-down that clearly demonstrates that the KD experiment was itself specific to MD, bilaterally, and that CL to CM were minimally impacted by the knock-down process (Fig. 2C and D). Moreover, the optogenetic  (fiber incidence was 30 degrees guaranteeing a central coverage rather than lateral; Fiber optic NA = 0.22) and electric stimulation (bipolar twisted electrodes, 50uA) experiments were also very selective and specific to the MD (Fig.S5). It remains clear that MD might not be the sole structure involved in the brain state control towards sedation and “anesthetic states”, and CL might be a significant contributor as well, however, we show that CL manipulations were rather irrelevant in our experiments  (Fig. 2, S5, S9 and S11).

R1-2: While sh-RNA knockdown appears to be largely centered in the mediodorsal thalamus in the example shown, (Figure 2) this is rather minimal evidence and it is also not well explained (indeed, the relevant panels do not even appear to be referenced in the text of the manuscript) and the consistency of the knockdown targeting is not quantified. Additional evidence should be provided to validate this approach.

R1-A2: In order to address this important question, we have created an additional panel quantification to fig2D. We have then quantified the intensity per area of Cav3.1 expression in sub zones of 4 regions of interest: MD (left, right; 2 subzones each), Centro Medial (CM; 1 subzones in total), Centrolateral/Paraventricular nucleus (CL/PCN; left, right; 2 subzones each) and the submedial nucleus (SMT; left, right; used as a control for the intensity normalization; 1 subzones in total). This panel clearly illustrates that MD was knocked-down bilaterally (p<0.001). Moreover, CM (p<0.05) and CL (p<0.01) were also partially and unilaterally knocked down, as well. This analysis confirms that our KD had a high specificity to MD.

We added the relevant figure caption and text:

[Result section, Cav3.1 silencing in the MD, but not VB, increased ethanol resistance in mice, paragraph 3]

“We then characterized the change in Cav3.1 expression following the shControl and shCav3.1 knockdown injections in three test regions MD (left and right), CM (centromedial nucleus) and CL (centrolateral nuclei, left and right side) and a negative control region SMT (submedial thalamic nuclei, left and right side). The average intensity was obtained from two coronal brain slices for each mice used in the experiment (see Methods sections, Cav3.1 Intensity quantification). Our results show that the targeting of the knockdown was very specific to the bilateral MD (p<0.001; Fig. 2D). We noted that the CM (p<0.05) and a marginal unilateral knock-down of the CL were also observed (p<0.01). Notably, we tested the correlation between the level of knock-down in MD and the total time in LOM and observed a significant association (Fig. 2D inset; R = 0.599, p = 0.018). This result highlights that the Cav3.1 knock-down was specific to MD and with an intensity associated with ethanol-induced loss of motion.”

R1-3: One difficulty is that, although lesions are shown in Figure S5 to validate recording locations, this figure is relatively unclear and the examples appear to be taken from a different anterior/posterior location compared to the reference diagram. A larger image and improved visualization of the overall set of lesion locations that includes multiple anterior/posterior coronal sections would be helpful. Moreover, even for these example images, it is difficult to evaluate whether these are in the mediodorsal thalamus, particularly given the small size of the image shown. Ideally, an example image that is more obviously in the mediodorsal thalamus would also be included. Finally, an assessment of the relationship between the approximate locations of recorded neurons across the tetrode arrays and the behavioral measures would be very helpful in supporting the unique role of the mediodorsal thalamus.

R1-A3: Related to fig.S5, we re-distributed the position of the recordings from the tetrode electrode burned positions over 3 representative coronal planes that best represent the implant positions. We also provided additional snapshots of tetrode location. To identify the positions of four tetrodes in each animal, we encoded the positions with different electrical lesion strategies as follows: 1 lesion(tetrode 1), 2 lesions while we redrew the tetrode with 100 um interval (tetrode 2), 3 lesions with 200um interval (tetrode 3), 4 lesions with 50um intervals (tetrode4). Tetrodes that were found outside of the MD delimited region were discarded post analysis. A straight relationship between the closeness of the electrode is unfortunately not possible for tetrode recording, a straight silicone probe which maintains the spatial spacing in recording would have been a better approach in that case, but unfortunately, it was not performed in our study.

R1-4: In addition to the key experimental issues mentioned above, there are often problems in the text of the manuscript with reasoning or at least explanation as well as numerous minor issues with editing. The most substantial such issue is the lack of clarity in discussing the mediodorsal thalamus and other adjacent thalamic nuclei, such as the central-lateral nucleus, in the author's discussion of previous findings. Given that at last one of the manuscripts cited by the authors (Saalman, Front. Sys. Neuro. 2014) has directly claimed that central-lateral, rather than the mediodorsal, thalamus is important for arousal regulation related to a conscious state, this distinction should be addressed clearly in the discussion rather than papered over by grouping multiple thalamic nuclei as being medial. As part of this discussion, it would be important to consider additional relevant literature including Bastos et al., eLife, 2021 and Redinbaugh et al., Neuron, 2020 which are quite critical but currently do not appear to be cited. Considering additional literature relevant to the function of the mediodorsal thalamus would also be beneficial.

R1-A4: We thank the reviewer for his comments and suggestions. We agree that the added references mentioned by the reviewers are highly relevant and should be integrated in the manuscript. We have integrated the above-mentioned references and further developed on the discussion on the role of MD relative to other thalamic nuclei (ILN and CL in particular). We believe that this better-referenced and clarified text does improve the manuscript greatly.

[introduction section, paragraph 3]

“The centrolateral (CL) thalamic nucleus has been implicated in the modulation of arousal, behavior arrest 31, and improvement of level of consciousness during seizures 32. Notably, the direct electrical stimulation of the intralaminar nuclei (ILN) and, in particular CL, promoted hallmarks of arousal and awakening in primate under propofol and ketamine propofol anesthesia.”

[Discussion section, paragraph 1]

“In this work, we identified that the neural activity in MD plays a causal role in the maintenance of consciousness. Whole body Cav3.1 KO and MD-specific Cav3.1 KD mice showed resistance to loss of consciousness induced by hypnotic dose of ethanol. In WT mice, MD neurons demonstrated a reduced firing rate in natural (sleep) and ethanol-induced unconscious states compared to awake states. This neural activity reduction was impaired in KO mice. In particular, transition to an unconscious state was accompanied with a switch of firing mode from tonic firing to burst firing in WT mice whereas this modeshift disappeared in KO mice. Finally, optogenetic or electric stimulations of the MD after ethanol injection were sufficient to induce a resistance to loss of motion, supporting that the level of neural firing in the MD is critical to maintain conscious state and delay unconscious state. We showed that the expression of Cav3.1 t-type calcium channels in MD is a cellular modulator associated with this effect.”

[Discussion section, MD is a modulator of consciousness, paragraph 2 and 3]

“The MD is known to innervate limbic region, basal ganglia and medial prefrontal cortex 50 and increased activity in MD might modulate the stability of cortical UP states (e.g. awaken, aroused and attentive states) and synchronization 9,26. Thus, MD might be a major hub involved in cortical state control and brain state stabilization.

Supporting the brain state stabilization theory and the ethanol resistance of Cav3.1 mutants, Choi et al.34 demonstrated that the loss of Cav3.1 T-type calcium channel reduced the bilateral coherence between PFC and MD under ketamine anesthesia and ethanol hypnosis, especially in the delta frequency bands. More importantly, under propofol anesthesia, Bastos et al.35 showed that intralaminar nucleus and MD stimulation lead to increased wake-up subscore and arousal, together with an increased in cortico-cortico and thalamo-cortical slow (delta) frequency power.

In the present study, we observed that MD KD (Fig. 2A), but not VB KD (Fig. S3) of Cav3.1 increased and is associated (Fig. 2D) with ethanol resistance in mice. We found that MD neurons in Cav3.1 mutant mice exhibited tonic firing within range of wakefulness (Fig. 3 and 4), indicative of resistance to ethanol and wake-like brain state. In addition, we found a strong association between the normalized tonic firing in MD and the arousal through brain states (i.e. walk to wake to sleep states), supporting that MD tonic firing could be interpreted both as a thalamic readout and a modulator of the brain state 11 (Fig. 3). Finally, direct optogenetic and electric MD stimulation increased resistance to loss of consciousness in WT mice (Fig.5 and Fig. S10). To our knowledge, this is the first report demonstrating the causal involvement of mediodorsal thalamic nucleus in the modulation of wakefulness and the resistance to ethanol-induced loss of consciousness in mice.”

R1-5: While the methods employed generally seem sound, the description in the methods section is lacking in detail and is often difficult to follow. Analysis methods such as the burst index appear to only be given a brief explanation in the text and appear not to be mentioned in the methods section.

R1-A5: We have added a clear definition in the supplementary method following the original work used:

[Supplementary Method section, Single Unit recording, sorting and analysis, last paragraph]

“The bursting index was derived as described in (Royer et al. 2012). Namely, the burst index was estimated from the spike auto-correlogram (1-ms bin size) by subtracting the mean value between 40 and 50 ms (baseline) from the peak measured between 0 and 10 ms. Positive burst amplitudes were normalized to the peak and negative amplitudes were normalized to the baseline to obtain indexes ranging from −1 to 1.” We also edited its mention in the text for clarity:

[Result section, Lack of Ca3.1 in MD neurons removes thalamic burst in NREM sleep, paragraph 2]

“[…] and a clear reduction in total bursting represented as bursting index (Fig. 3-B; ratio of spikes count <10 ms and >50 ms based on auto-cross-correlogram).”

R1-6: Similarly, the staining method used in Figure 2 does not appear to be described in the methods section.

R1-A6: The staining method can be found in the supplementary method of the paper. [supplementary method, Immunohistochemistry]

R1-7: The most substantial case is for the UMAP approach used in Figure 4-E which does not appear to be described in the methods or even described in the main text.

R1-A7: Regarding the method, the UMAP approach is described in the supplementary method document [Uniform Manifold Approximation and Projection (UMAP)]. We believe that only a succinct description was needed here considering the extent of the analysis. Regarding the inserts in the main text, we agree that the main text was lacking the description of these results and we have amended the main text to reflect a clear description of this result and what it entails. The following paragraph was added:

[Result section, Under ethanol, MD neurons lacking Cav3.1 show no burst and a wake state-like neural activity, second to last paragraph]

“Finally, we asked whether the firing modes and properties (tonic firing rate, burst firing rate; see supplementary methods) of single MD neurons would form distinct qualitative representation of “brain stages” using a lowered dimensional UMAP representation (Uniform Manifold Approximation and Projection42 ). We observed that for awake and active (i.e. walk), the brain state representation formed two adjacent clusters that confounded both wild and mutant neurons (Fig. 4E, left panel). The REM and NREM states, the wild type neurons formed 2 additional interconnected clusters, whereas the mutant neurons tend to overlap with the clusters attributed to the “awake” brain state (Fig. 4E, second to left panel). Ethanol induced fLOM, similarly to REM and NREM clusters, was distinct from awake clusters in wild type mice and overlapped with the NREM clusters (Fig. 4E, third to left panel). Here also, mutant MD neurons showed overlap with the awake clusters rather than the “low consciousness” brain states. These results indicate that the firing mode and properties could define a brain state representation that shows distinctions in levels of consciousness. Moreover, the mutant showed a representation of “low consciousness” states overlapping with wild type “awake” states consistent with the hypothesis of resistance to loss of consciousness.”

R1-8: Citations justifying the use of methods such as the approach to separate regular spiking and narrow spiking neuron subtypes are also needed.

R1-A8: We have added two references related to the observation of the two subpopulations of spiking neurons [Schiff and Reyes, 2012; Destexhe, 2008].

R1-9: Beyond the problems with content and reasoning discussed above, there are also some relatively minor issues with the clarity of writing throughout the paper (for example, in the abstract the authors refer to "the ethanol resistance behavior in WT mice" but it is difficult to parse what they mean by this statement.

R1-A9: We addressed this issue by editing and revising the manuscript for clarity and flow.

R1-10: Similarly, the next sentence "These results support the maintenance..." while clearer, is not well phrased. Though individually minor, issues like this re-occur throughout the manuscript and sometimes make it difficult to follow so the text should be revised to correct them.

R1-A10: We thank the reviewer for highlighting this point. We have edited the overall text to improve clarity and flow.

[abstract] 

These results suggest that maintaining MD neural firing at a wakeful level is sufficient to induce resistance to ethanol-induced hypnosis in WT mice.

R1-11: There are also some problems with labels such as the labels of A1/A2 in Figure 4, which appear to be incorrect.

R1-A11: We noted this issue and have rectified the figure for clarity.

R1-12: Also, S7 has no label on the B panels.

R1-A12: We thank the reviewer for pointing out this lack. We have added the y-label on the panel for clarity.

R1-13: Finally, some references are not included (only a label of [ref]).

R1-A13: We have completed the missing reference and thank the reviewer for pointing that out.

Additional comments

R1-14: Aside from the additional quantification and clarification of the analysis discussed in the weakness section, in general, the experiments included in the manuscript seem reasonable. However, I would suggest one additional experiment as well as one control, both of which are relatively straightforward optogenetic experiments, that I feel would be helpful to further improve the study. First, as the authors note, the optogenetic interventions used do not directly address the relevance of the changes in bursting patterns observed in the knockout (KO), which are by far the most robust effect, with the changes in alcohol sensitivity. One approach that could help address this would be to use patterned suppression via inhibitory opsins (e.g. halorhodopsin) to "rescue" the periods of inhibition associated with bursting in the KO.

R1-A14: Here the reviewer proposes an interesting experiment which we have attempted to perform, however, poses several technical challenges. First, the KO do not have burst firing as they are depleted from Cav3.1 low-threshold calcium channel. Therefore, under ethanol, even if there might exist a rhythmic inhibition that activates Cav3.1 channels and causes a rebound burst, the KO are unable to have it. Therefore, an optogenetic inhibition would only accentuate the total inhibition and could potentially induce an overall decrease in MD firing, resulting in an increase in LOM features. Alternatively, we showed that in a WT with low ethanol dose (where LOM induction is harder), the increased rhythmic inhibition does indeed increase significantly LOM duration and marginally decreases latency to LOM (Fig. S12), indicating that increased inhibition could indeed explain the hypothesis: “ the stronger the decrease in MD firing, the faster and longer the LOM.” The only caveat of using WT here is that optogenetic inhibition might also include rebound burst post-inhibition. Injecting bursts only did not alter the response to ethanol (Fig. S10). These results point to the role of loss of firing in MD as a main factor for LOM, and potentially the contribution of burst necessitating a concurrent inhibition/loss of firing.

We agree that inhibition in KO would further validate this hypothesis, controlling for the role of burst. We regret that we are not in the capacity to perform additional experiments involving the KO mice.

R1-15: For the control, tonic activation of the ventrobasal nucleus, as the authors did for the mediodorsal nucleus, would be beneficial to rule out the possibility that the observed effect would occur with any thalamic nucleus.

R1-A15: We agree with the reviewer that we could have added an additional region control to the gain/loss of function experiments. We would even go further as to suggest that a better control nucleus would be a high order nucleus such as PO or an unrelated sensory relay nucleus such as LGN. VB being a motor relay nucleus, could also mediate movement initiation, which could be hard to interpret. Since the complete control study for all thalamic nuclei Cav3.1 KD is outside the scope of this study, we opted not to redo these experiments and keep the focus of the manuscript on the manipulation of MD activity rather than the various available thalamic nuclei. We also do not claim that MD is the sole center able to initiate a switch in the loss of consciousness, and a more in-depth study on that matter would be clearly needed.

R1-16: In addition to these experiments, I did not note the strategy for sharing data obtained through this study so this should be added.

R1-A16: We have uploaded data and code for most figures at the following repository and provided a clearer statement regarding data sharing. We thank the reviewer for pointing out this missing element.

The link for the repository is the following:

It contains:

- Excel spreadsheet file of all behavior values, including the newly quantified Cv3.1 expression in MD/CL/SMT

- Excel spreadsheet follow-up of all MD cells (single unit; tetrode) analyzed

- Folders for all groups studied with representative figures showing EEG power over time and normalized activity (WT vs KO for 2, 3 and 4 g/kg; MDshKD vs shCTR, VBshKD vs shCTR; CHR2 NOSTIM vs STIM; ESTIM Groups and ARCH NOSTIM vs STIM)

- A1G LORRvsLOM and OPEN FIELD Matlab data

- Matlab and ImageJ Codes: single unit analysis, characterization, brain state characterization, sleep stages, LOM, open field analysis and statistical analysis.

We have added the data sharing subsection in the acknowledgements:

“Part of the analyzed data and codes are available on the open access platform, mendeley:

Latchoumane, Charles-francois (2024), “Mediodorsal thalamic nucleus mediates resistance to ethanol through Cav3.1 T-type Ca2+ regulation of neural activity”, Mendeley Data, V1, doi: 10.17632/7fr427426m.1

Additional data (large size recording and images) can be provided upon reasonable requests.”

Reviewer #2 (Recommendations For The Authors):

R2-1. Consciousness is a contentious subject. Even in humans, there is still intense research on the topic, not to mention animals, about which we still know very little. Moreover, consciousness is not quantified in this study, as there is no standard metric to do so. Accordingly, talking about 'modulation', 'transition', ́level ', or 'reduction' of consciousness can be misleading. Hence, it is probably safer to strictly refer to brain-states and/or stages of the sleep-wake cycle in this study and reframe it entirely around these concepts.

R2-A1. The reviewer points to an important point and we appreciate this highlight. Agreeing that the definition of consciousness is rather loose and arguably difficult to pinpoint. Here, we settle on a definition that relies on the loss of motion and loss of righting reflex. This definition is widely accepted as the “verified” state in which the absence of responsiveness (to continuous stimuli, inducing reflex or discomfort) is observed and uninterrupted by jerks and spurious movements. Additional metrics needed would be the recording of EMG to quantify atonia and EEG to the settling of a dominantly slow-wave frequency (~4 Hz; ethanol-induced sedation at theta rhythm), as shown in Fig S1A. The driver of this 4Hz frequency and its correlation has been investigated previously (e.g. Choi et al, PNAS, 2012), leading to the accepted link between LOM/LORR and loss of consciousness. Our data present the advantage of showing single neuron recordings and that LOM is a state where the lowest firing activity is present (Fig S7AB) and comparable to deep sleep state activity (Fig3D). The first LOM is the most important as it highlights the deepest loss of consciousness before the ethanol starts to be metabolized and cleared, which would be consistent between animals.

As a result, we have edited the manuscript to clarify all mentions related to brain states and states of unconsciousness.

R2-2. It is not clear why the authors focus on the mediodorsal nucleus. This should be better explained in the introduction and developed in the discussion.

R2-A2. This comment converges with the Reviewer 1 comments and we are addressing this lack in the discussion as suggested. We have addressed it with this previous comment and believe it is now clearer.

R2-3. The discussion mentions that 'increased activity in MD might modulate the stability of cortical UP state and synchronization' (pg 21). This point should be either further developed and put into context, or removed. In its current state, it does not seem to contribute much to the discussion of results.

R2-A3. We understand that the working “UP state” might not be clear enough. We have modified this sentences as follows to clarify that UP state could be either a state of where the animal is awake, aroused or attentive:

[Discussion section, MD is a modulator of consciousness, first paragraph]

“The MD is known to innervate limbic region, basal ganglia and medial prefrontal cortex 50 and increased activity in MD might modulate the stability of cortical UP states (e.g. awaken, aroused and attentive states) and synchronization 9,26. Thus, MD might be a major hub involved in cortical state control and brain state stabilization.“

R2-4. The discussion states that 'mutant mice did not exhibit a decreased arousal level (i.e. increased locomotor activity)' (pg 23). This is confusing as decreased arousal should be reflected in decreased locomotor activity.

R2-A4. We understand that the formulation of this sentence may be confusing and we have edited this portion of the text to improve quality in the revised version of the manuscript. To clarify, mutant mice do not exhibit reduced or increased arousal (not quantified, just observational), they do have a phenotypic hyperlocomotion. This comes in contrast with a lower basal firing rate in the MD, which in our interpretation, is not synonymous with lower arousal. We believe that the relative change in MD determines the change in arousal, and that the absolute firing is not indicative of arousal in itself, only in comparison.

[Discussion section, The lower variability in MD Firing reflects Ethanol Resistance in Cav3.1 mutant mice, paragraph 2]

“Mutant RS neurons in MD showed an overall lower excitability and variability of firing in various natural conscious and unconscious states compared to wild type mice. Remarkably, Cav3.1 mutant mice exhibited a clear increased locomotor activity and an increased resistance to ethanol. The general lower firing rate and the high “arousal” observed in mutant mice suggests that the relative change from state to state in tonic firing in MD, and not the absolute value of firing, might be a better correlate of change in brain state in the mice.”

R2-5. The methods (pg 27) state that two genetic backgrounds (129/svjae and C57BL/6J ) were used in the study. Authors should show whether there were significant differences between those backgrounds in the key parameters assessed in the study (particularly resistance to ethanol sedation).

R2-A5. As mentioned in the method section, we only used the F1-background mice, which are the firstgeneration offspring produced by crossing 129/svjae and C57BL/6J strains. To produce F1 KO mice, we kept the heterozygote mice in two strains. We unfortunately did not study the particular difference of the respective KO of these two backgrounds; however, the pure C57BL/6J KO has been used in other studies by our group (Kim et al 2001; Na et al, 2008; Park et al., 2010). The F1 background allows us to work with mice that are less aggressive and can be handled with less inherent stress.

R2-6. It would be convenient to produce a supplementary figure associated with Figure 1C to show the same data with averages per mouse. That is, 9 points for control and 9 points for KO mice. This also applies to all cases where data is not presented per mouse but pooled between animals.

R2-A6. We have added a panel C in Figure S1, to show the scatter values for all the mice corresponding to the figure 1C. We have also generalized this presentation for all behavior graphics showing all the animals in the scatter plot next to the boxplot. We believe that this presentation increases further the transparency of the manuscript. We have then added the scatter plot for all mice in figure Fig1, Fig2, Fig5, Fig.S2, Fig.S3, Fig.S10 and Fig.S12.

R2-7. It would be informative to make a supplementary figure associated with Figure 1D to compare baseline raw activity levels (i.e., baseline walking recording) between control and KO mice. That is, do KO and control mice cover comparable distances and at similar speeds during baseline conditions? Figure 1D and Figure 4A suggest that the variability of locomotor activity is larger in KO mice. Hence, this parameter should be quantified and reported.

R2-A7. We thank the reviewer for this comment. We strived to answer to this question in the manuscript in two ways:

- We first measure the overall hyperlocomotion of the mice using the open field total distance parkoured in our mice cohorts (FigS4C). We did observe that the KO mutant showed hyperlocomotion, but not MD or VB knock-down mice. Which indicates that the hyperlocomotion component is not specific to the two thalamic nuclei studied.

- Using the forced walking task, we impose on the animal to keep a steady pace of roughly 6cm/s. This assay allows to normalize the general walking behavior to a relatively fixed pace making it comparable for all animals.

The reviewer suggested reporting the mean and variance in walking of WT and KO during baseline (prior to the ethanol I.P. injection). We believe that the two points mentioned above are sufficient to describe in a more quantitative way the WT vs KO locomotion differences. Moreover, by construction the normalized locomotion on the forced walking task will return similar means for the baseline, the standard deviation would, however, potentially show differences but would remain inconclusive.

R2-8. The legend in Figure 1 states that 'the loss of consciousness is evaluated using normalized moving index using either video analysis (differential pixel motion), on- head accelerometer-based motion, or neck electromyograms'. Authors should clarify whether these methods are equivalent and support it with data.

R2-A8. We understand the reviewer point and we have made a few modifications to the method description aligning better with what was done. For most mice, video analysis was used to obtain the moving index. When video recording was not available (2 mice), we had an accelerometer attached to the animal’s head stage which helped us derive a moving index that was similar to the video moving index. The neck electromyogram was rather used for animals implanted with the tetrodes to identify sleep stages based on local field potential frequency and muscle tone.  We have then clarified the method for this matter and Figure 1 to avoid this confusion. Since no concurrent recording of both video and accelerometer was performed, we do not have the data to compute the correlation between the two measures, however, no noticeable deviation from loss of motion was observed between the two methods. We realize that this may be a weak argument, however, our observations showed that video and accelerometers returned very similar timings for loss of motion (only a few comparative instances insufficient to present a statistical comparison).

R2-9. How were spike bursts defined? The authors should try different criteria and verify the consistency of results.

R2-A9 For in vivo single unit recording, we opted for a definition that is validated from our works and others as a silencing of at least 100 ms followed by a minimum of 3 spikes with:

- First spike pairs interspike interval less than 4 ms

- Remaining spike pairs interspike interval less than 20 ms

We have performed this analysis using a minimum of 2 spikes, and varied silencing periods between 50 and 100ms, without observing significant deviation of the results. As shown in Figure S6B, with this approach we observed that the burst distribution had a majority with <10 spikes per burst. Figure S6C indicated that with a clear distribution of ISI for first spike within 2-4ms as observed in previous works (Desai and Varela, 2021; Alitto et al, 2019), importantly, not clearly capped at 4 ms, showing that the range for the first ISI might indeed be lower than 4ms for thalamic burst. Within burst spike waveforms can become very variable and the choice of 3 over 2 spikes minimum per burst stems from the aim to reduce false positive detection of ultra-short bursts, which in single unit recording remains controversial (Gray et al. 1995).

Minor:

R2-10: Figure 4A2 'Cav3.1(+/+)' should presumably be Cav3.1(-/-).

R2-A10: this is correct and we have corrected the figure label [This sentence is ambiguous. What is ‘this’ that is correct?]

R2-11: Figure S2C legend states 'Post-hoc group comparison was performed using.' The sentence seems to be incomplete.

R2-A11: We have completed the sentence for clarity.

R2-12: In the methods (pg 29) virus concentration is reported as '107 TU/ul', which probably refers to 10e7.

R2-A12: We have corrected it by superscripting the power 7.

R2-13: Verify Fig 1C1 and correct Y-axis overlap between title and units.

R2-A13: We edited the figure for clarity, thank you.

R2-14: On page 24 there is a '[ref]' that probably stands for (a missing) reference.

R2-A14: the missing reference has been added.

The biggest deviation the movie takes from this account, or from history itself, is the age of Pocahontas. In an earlier paragraph, she is described as being ten years old. This is far different from how she is depicted in the movie, where she is being depicted at around 19. There was no romance between the two historical figures as they hardly knew each other, and were fairly far apart in age. In this version of John Smiths time in Virginia, he only mentions Pocahontas once. Not only that, but there is no mention of her saving him from being clubbed in the head by her father. (Smith, John “A True Relation of Such Occurrences) From learning about John Smith in various history classes, I know that his story about being saved by Pocahontas is largely untrue and was a story he came up with after the fact. In this volume of events, there is also no mention or instance where he is captured and threatened to be killed which is not the case for the movie. ("Goldberg, Eric, and Mike Gabriel. 1995. Pocahontas")

When the head is thrust forward, it results in exaggerated cervical hyperextension...contradicting your previous analysis that her back is mostly straight

Yes! Good analysis.

The trunk is flexed forward; I don't see extreme extension--I see flattened lumbar curve (you correctly identified), a relatively natural kyphotic curve (correctly identified), and exaggerated cervical lordosis with forward head protrusion (head thrust forward). Feet are neutral; femurs are flexed at the hips.

Scapulae are retracted in this position as she pulls the barbell close to her body.

The lumbar curve is somewhat flattened as her spine is flexed forward; however the thoracic kyphosis does not appear exaggerated. Her cervical curve is exaggerated in extension because she is protruding her head forward.

The lumbar curve is flattened. Since you accurately stated her head is in the forward head posture, what is happening in her neck?

Alet tepsisi, hasta koltuğunun baş kısmına doğru yerleştirilmeli ve aletlere ve malzemelere kolay erişim sağlamak için konumlandırılmalıdır.

Kolaylığı ve görünürlüğü arttırmak için hastanın başı operatöre doğru çevrilebilir.

head is protruded forward. "Tilt" is used to describe the pelvis.

Her lumbar curve is flattened and her cervical spine is also somewhat flattened by the forward head protrusion

The lumbar curve is flattened; I would say the cervical curve is exaggerated with the forward head protrusion

The head is protruded forward---would you say they neck is flexed or extended?

Tilt is used to describe the pelvis; the head is described as protruded forward

What is happening to the head? Is it rotated? Usually it is protruded forward.

The spine is flexed causing the lumbar lordosis to flatten and the thoracic kyphosis to be exaggerated. The cervical vertebrae are hyperextended and the head is forward. Scapulae are elevated.

This was a little shocking to me, sorry to those who may not want to know about this. But on the right side of the photo, you can visibly make out a figure of what looks like a head. But the body is like really tiny? I can’t imagine how traumatizing that would look in real time. I hope those soldiers got the heal they needed.

Sorry if I missed this, but what was the motivation for choosing these particular discriminator models? They seem very reasonable given the results, but I'm curious how these two types of models were chosen based on the structure of the initial problem?

I as well as many others are guilty of ignoring whatever pops up on the screen and skip to downloading the app. This is a habit that I need to fix. Especially as I head into the field of education. It is not just my information that I have to protect, but also my students as an educator. It will be my job to ensure that I am protecting my student's information.

reply to michaljjwilk at https://hypothes.is/a/rwiI4rJYEe62aaN50r2zzQ to ensure it's properly indexed:

Most following my argument will have likely read The Two Definitions of Zettelkasten which may cover some of your initial question, or at least from my perspective. (Others certainly have different views.)

Some of your questions relate to what Robert Hutchins calls "The Great Conversation" (1952) and efforts over time to create Summa or compilations of all knowledge.

Variations of your remark about Plato can be seen in later Greeks' aphorism that "Everywhere I go in my head, I meet Plato coming back." or more recently in A.N. Whitehead's statement that everything is "a footnote to Plato".

Example of a a war metaphor. The entailments of this metaphor are visual. It brings up the vivid pictures in your head about 9/11.

Does not make sense considering the rest of the sentence.

There is no cause and effect--he has a posterior tilt of the pelvis most likely due to the forward head posture and excessive thoracic kyphosis.

Tilt is used to describe the pelvis, not the head.

This quote highlights how the library, recreation center, and church function as literacy spaces supported by staff who view themselves as educators. Interviews reveal that these spaces encourage literacy through structured activities, reflecting the belief that literacy is a skill children master through active engagement in provided programs.

Head does not tilt. Tilting is a descriptor for the pelvis.

Neck. There is no such thing as an anterior tilt to the head. Anterior tilt is a descriptor for the pelvis.

Upon reviewing the total number of reads assigned per sample day and head type, we observe that the number of reads detected on Days 1 and 2 is very similar for both heads. However, on the third day, the PM2.5 head shows a significantly lower number of reads compared to the PM10 head. This is an intriguing observation, as we would expect PM10 to include the PM2.5 fraction, suggesting that PM10 should have a higher mass. While this assumption holds true in terms of DNA yield, it is not reflected in two out of the three experiments.

If you are actively listening to a presenter, then it becomes easier to show your attentiveness and it becomes a thing that you do without thinking about it. the tricks listed should be something that you do without thinking like nodding your head and keeping your eyes on the speaker.

Relationship between Ubiquitous Computing and Augmented Reality (AR): Ubiquitous computing and AR represent different approaches to integrating digital information with the physical world. While ubiquitous computing brings computational intelligence to the physical environment, AR overlays digital information onto the real-world view. Ubicomp focuses on embedding processing capabilities within the environment, whereas AR enhances human perception of reality by displaying digital elements in real-time. Together, they can enrich user interaction with digital systems without immersing users entirely in a simulated world like virtual reality.

Reviewer #3 (Public review):

Summary:

This study investigates evidence for a hypothesised, causal relationship between education, specifically the number of years spent in school, and brain structure as measured by common brain phenotypes such as surface area, cortical thickness, total volume, and diffusivity.

To test their hypothesis, the authors rely on a "natural" intervention, that is, the 1972 ROSLA act that mandated an extra year of education for all 15-year-olds. The study's aim is to determine potential discontinuities in the outcomes of interest at the time of the policy change, which would indicate a causal dependence. Naturalistic experiments of this kind are akin to randomised controlled trials, the gold standard for answering questions of causality.

Using two complementary, regression-based approaches, the authors find no discernible effect of spending an extra year in primary education on brain structure. The authors further demonstrate that observational studies showing an effect between education and brain structure may be confounded and thus unreliable when assessing causal relationships.

Strengths:

(1) A clear strength of this study is the large sample size totalling up to 30k participants from the UK Biobank. Although sample sizes for individual analyses are an order of magnitude smaller, most neuroimaging studies usually have to rely on much smaller samples.

(2) This study has been preregistered in advance, detailing the authors' scientific question, planned method of inquiry, and intended analyses, with only minor, justifiable changes in the final analysis.

(3) The analyses look at both global and local brain measures used as outcomes, thereby assessing a diverse range of brain phenotypes that could be implicated in a causal relationship with a person's level of education.

(4) The authors use multiple methodological approaches, including validation and sensitivity analyses, to investigate the robustness of their findings and, in the case of correlational analysis, highlight differences with related work by others.

(5) The extensive discussion of findings and how they relate to the existing, somewhat contradictory literature gives a comprehensive overview of the current state of research in this area.

Weaknesses:

(1) This study investigates a well-posed but necessarily narrow question in a specific setting: 15-year-old British students born around 1957 who also participated in the UKB imaging study roughly 60 years later. Thus conclusions about the existence or absence of any general effect of the number of years of education on the brain's structure are limited to this specific scenario.

(2) The authors address potential concerns about the validity of modelling assumptions and the sensitivity of the regression discontinuity design approach. However, the possibility of selection and cohort bias remains and is not discussed clearly in the paper. Other studies (e.g. Davies et al 2018, https://www.nature.com/articles/s41562-017-0279-y) have used the same policy intervention to study other health-related outcomes and have established ROSLA as a valid naturalistic experiment. Still, quoting Davies et al. (2018), "This assumes that the participants who reported leaving school at 15 years of age are a representative sample of the sub-population who left at 15 years of age. If this assumption does not hold, for example, if the sampled participants who left school at 15 years of age were healthier than those in the population, then the estimates could underestimate the differences between the groups.". Recent studies (Tyrrell 2021, Pirastu 2021) have shown that UK Biobank participants are on average healthier than the general population. Moreover, the imaging sub-group has an even stronger "healthy" bias (Lyall 2022).

(3) The modelling approach used in this study requires that all covariates of no interest are equal before and after the cut-off, something that is impossible to test. Mentioned only briefly, the inclusion and exclusion of covariates in the model are not discussed in detail. Standard imaging confounds such as head motion and scanning site have been included but other factors (e.g. physical exercise, smoking, socioeconomic status, genetics, alcohol consumption, etc.) may also play a role.

This chapter captures Descartes's attempt to link our mental images of the physical world with the actuality of those items. He highlights the difference between imagination and actuality and addresses doubt about existence by claiming that our concepts of bodily forms originate from actual entities. Aiming to provide a basis of knowledge that recognizes the truth of the physical universe while also being skeptical of sensory experience, this argument is important to his philosophical study.

Emphasizing how people could be caught in false beliefs resulting from a disordered state of mind, this chapter shows Descartes's investigation of mental clarity against delusion. By means of striking images and contrasts, he challenges the continuation of illusion, therefore highlighting the more general philosophical concerns of identity, perception, and the character of reality. This is a sobering meditation on the need of clear thinking and the perils of letting irrationality or negativity color one's impressions.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

This research offers an in-depth exploration and quantification of social vocalization within three families of Mongolian gerbils. In an enlarged, semi-natural environment, the study continuously monitored two parent gerbils and their four pups from P14 to P34. Through dimensionality reduction and clustering, a diverse range of gerbil call types was identified. Interestingly, distinct sets of vocalizations were used by different families in their daily interactions, with unique transition structures exhibited across these families. The primary results of this study are compelling, although some elements could benefit from clarification

Strengths:

Three elements of this study warrant emphasis. Firstly, it bridges the gap between laboratory and natural environments. This approach offers the opportunity to examine natural social behavior within a controlled setting (such as specified family composition, diet, and life stages), maintaining the social relevance of the behavior. Secondly, it seeks to understand short-timescale behaviors, like vocalizations, within the broader context of daily and life-stage timescales. Lastly, the use of unsupervised learning precludes the injection of human bias, such as pre-defined call categories, allowing the discovery of the diversity of vocal outputs.

Weaknesses:

(1) While the notable differences in vocal clusters across families are convincing, the drivers of these differences remain unclear. Are they attributable to "dialect," call usage, or specific vocalizing individuals (e.g., adults vs. pups)? Further investigation, via a literature review or additional observation, into acoustic differences between adult and pup calls is recommended. Moreover, a consistent post-weaning decrease in the bottom-left cluster (Fig. S3) invites interpretation: could this reflect drops in pup vocalization?

Thank you for bringing up this point of clarification. Without knowledge of individual vocalizers, we are unable to rigorously assess pronunciation differences between individuals, however we can get a clear proxy for dialect through observing usage differences between families. We’ve added the following text (blue) in the Discussion to help clarify:

“To address whether gerbils also exhibit family specific vocal features, we compared GMM-labeled vocal cluster usages across the three recorded families and showed differences in vocal type usage (Figure 3). The differences in this study align with the definition of human vocal dialect, which is a regional or social variety of language that can differ in pronunciation, grammatical, semantic and/or language use differences (Henry et al., 2015). This definition of dialect is inclusive of both pronunciation differences (e.g. a Bostonian’s characteristic pronunciation of “car” as “cah”) and usage differences (e.g. a Bostonian’s preferential usage of the words “Go Red Sox” vs. a New Yorker’s preferential usage of the words “Go Yankees”). In our case, vocal clusters can be rarely observed in some families yet highly over-expressed in others (e.g. analogous to language usage differences in humans), or highly expressed in both families, but contain subtle spectrotemporal variations (Figure 3D, Family 1 cluster 11 vs. Family 3 clusters 2, 18, 30; e.g. analogous to pronunciation differences in humans).”

Indeed, our recordings obtained after pup removal could suggest that adults may use fewer low frequency calls (bottom left cluster in UMAP). However, this dataset does not permit a proper assessment of post-weaning pup calls. In fact, our results and the literature shows that adults are likely to use low frequency calls, but only during social interactions with pups or other adults. For example, Furuyama et al. 2022 describe a number of low frequency call types used by adults in agonistic social interactions, which look similar to a low frequency call type used by pups described in Silberstein et al. 2023. Similarly, Ter-Mikaelian et al. 2012 (their Figure 6) recorded several types of sonic vocalizations during adult social interaction. To our knowledge, it has not been shown whether gerbil pups and adults produce distinct call types. It is a challenging problem to solve, as animals placed in isolation (i.e. an experimental condition for which the identity of the vocalizer is known) vocalize infrequently and of the limited number they might emit, they do not use the full range of vocalizations described in the literature (RP personal observations). To properly address this question, one would need to elicit full use of the vocal repertoire through free social interaction, then attribute calls to individual vocalizers via sound source localization and/or head-mounted microphones — we are currently pursuing both of these technical challenges, but this is outside the scope of this manuscript.

Although the literature reflects the limitations discussed above, we have added a brief paragraph to the Discussion (limitations section) that addresses the reviewer’s question about the development of vocalizations:

“Although we were not able to attribute vocalizations to individual family members, we did seek to determine the importance of family structure by comparing audio recordings before and after removal of the pups at P30. The results show a clear effect of family integrity, and the sudden reduction of sonic calls following pup removal (Figure S3) could suggest that these vocalizations are produced selectively by pups.

However, there is ample evidence that adult gerbils also produce sonic vocalizations. For example, a number of low frequency call types are used by adults during a range of social interactions (Ter-Mikaelian et al., 2012; Furuyama et al., 2022), some of which are similar to a low frequency call type used by pups (Silberstein et al., 2023). Vocalization patterns of developing gerbils depend on isolation or staged interactions. Thus, when gerbil pups are recorded during isolation, ultrasonic vocalization rate declines and sonic vocalizations increase for animals that are in a high arousal state (De Ghett 1974, Silberstein et al., 2023). As gerbils progress from juvenile to adolescent development (P17-55) a significant increase in ultrasonic vocalization rate is observed during dyadic social encounters, with a distinct change in usage pattern that depends upon the sex of each animal (Holman & Seale 1991, Holman et al. 1995). The development of vocalization types has been assessed in another member of the Gerbillinae subfamily, called fat-tailed gerbils (Pachyuromys duprasi), during isolation and handling. Here, the number of ultrasonic vocalization syllable types increase from neonatal to adult animals (Zaytseva et al. 2019), while some very low frequency sonic call types were rarely observed after P20 (Zaytseva et al. 2020). By comparison, mouse syllable usage changes during development, but pups produced 10 of the 11 syllable types produced by adults (Grimsley et al. 2011). In summary, our understanding of the maturation of vocalization usage remains limited by our inability to obtain longitudinal data from individual animals within their natural social setting. For example, when recorded in their natural environment, chimpanzees display a prolonged maturation of vocalization complexity, such as the probability of a unique utterance in a sequence, with the greatest changes occuring when animals begin to experience non-kin social interactions (Bortolato et al. 2023).”

(2) Developmental progression, particularly during pre-weaning periods when pup vocal output remains unstable, might be another factor influencing cross-family vocal differences. Representing data from this non-stationary process as an overall density map could result in the loss of time-dependent information. For instance, were dominating call types consistently present throughout the recording period, or were they prominent only at specific times? Displaying the evolution of the density map would enhance understanding of this aspect.

This is a great suggestion. Thank you for bringing it up. To address this, we have added an additional figure (Figure 4) to the main text (Note that the former Figure 4 is now Figure 5). New text associated with this new figure was added to the Results and Discussion sections:

Results

“Vocal usage differences remain stable across days of development It is possible that the observed vocal usage differences could result from varying developmental progression of vocal behavior or overexpression of certain vocal types during specific periods within the recording. To assess the potential effect of daily variation on family specific vocal usage, we visualized density maps of vocal usage across days for each of the families (Figure 4A). There are two noteworthy trends: 1.) the density map remains coarsely stable across days (rows) and 2.) the maps look distinct across families on any given day (columns). This is a qualitative approximation for the repertoire’s stability, but does not take into account variation of call type usage (as defined by GMM clustering of the latent space). Figure 4B, shows the normalized usage of each cluster type over development for each family. Cluster usages during the period of “full family, shared recording days” (postnatal days beneath the purple bars) are stable across days within families – as is apparent by the horizontal striations in the plot – though each family maintains this stability through using a unique set of call types. This is addressed empirically in Figure 4C, which shows clearly separable PCA projections of the cluster usages shown in Figure 4B (purple days). Finally, we computed the pairwise Mean Max Discrepancy (MMD) between latent distributions of vocalizations from individual recording days for each of the families (Figure 4D). This shows that across-family repertoire differences are substantially larger than within-family differences. This is visualized in a multidimensional scaling projection of the MMD matrix in Figure 4E.”

Discussion

“The described family differences collapse data from multiple days into a single comparison, however it’s possible that factors such as vocal development and/or high usage of particular vocal types during specific periods of the recording could explain family differences. Therefore, we took advantage of the longitudinal nature of our dataset to assess whether repertoire differences remain stable across time. First, we visualized vocal repertoire usage across days as either UMAP probability density maps (Figure 4A) or daily GMM cluster usages (Figure 4B). Though qualitative, one can appreciate that family repertoire usage remains stable across days and appears to differ on a consistent daily basis across families. To formally quantify this, we first projected GMM cluster usages from Figure 4B into PC space and show that family GMM cluster usage patterns are highly separable, regardless of postnatal day (Figure 4C). If families had used a more overlapping set of call types, then the projections would have appeared intermixed. Next, we performed a cluster-free analysis by computing the pairwise MMD distance between VAE latent distributions of vocalizations from each family and day (Figure 4D). This analysis shows very low MMD values across days within a family (i.e. the repertoire is highly consistent with itself), and high MMD values across families/days (greater than would be expected by chance; see shuffle control in Figure S2D). The relative differences in this matrix are made clear in Figure 4E, which provides additional evidence that family vocal repertoires remain stable across days and are consistently different from other families. Taken together, we believe that this is compelling evidence that differences in vocal repertoires between families are not driven by dominating call types during specific phases in the recording period; rather, families consistently emit characteristic sets of call types across days. This opens up the possibility to assess repertoire differences over much shorter time periods (e.g. 24 hours) in future studies.”

(3) Family-specific vocalizations were credited to the transition structure, a finding that may seem obvious if the 1-gram (i.e., the proportion of call types) already differs. This result lacks depth unless it can be demonstrated that, firstly, the transition matrix provides a robust description of the data, and secondly, different families arrange the same set of syllables into unique sequences.

Thank you for these important suggestions. We agree that it is true that the 2-gram transition structure must vary based on the 1-gram structure. To determine whether this influences the interpretation of the finding, we have added Figure S5 and the following text in the Results section:

“To determine whether differences in 1-gram structure contribute to differences in the transition (2-gram) structure, we performed a number of controls. Although subtle, vertical streaks are clearly present in shuffled transition matrices that correspond to 1-gram usages (Figure S5A-B). Given the shuffled data structure, we sought to determine whether the observed transition probabilities differed significantly from chance levels. We randomly shuffled label sequences 1000 times independently for each family to generate a null transition matrix distribution. Using these null distributions and the observed transition probabilities, we computed a p-value for each transition using a one-sample t-test and created a binary transition matrix indicating which transitions happen above chance levels (Figure S5C, black pixels, p <= 0.05 after post hoc Benjamini-Hochberg multiple comparisons correction). As is made clear in Figure S5C, most transitions for each family occur significantly above chance levels, despite the inherent 1-gram structure. Moreover, by looking at transitions from a highly usage cluster type used roughly the same proportion across families (cluster 12), we show that families arrange the same sets of vocal clusters into unique sequences (Figure S5D). We believe that this provides compelling evidence that the 1-gram structure does not change the interpretation of the main claim that transition structure varies by family. “””

To address your second point, we inspected frequent transitions from individual syllables to all other syllables using bigram transition probability graphs. This revealed a common trend that across all families, many shared and unshared transitions existed, suggesting that families use the same sets of syllables to make unique transition patterns. Figure S5D shows a single syllable example of the phenomenon, with red lines indicating the shared transition types between families and black showing transition patterns not shared between families (i.e. unique family-specific transitions, or lack thereof).”

Reviewer #2 (Public Review):

Peterson et al., perform a series of behavioral experiments to study the repertoire and variance of Mongolian gerbil vocalizations across social groups (families). A key strength of the study is the use of a behavioral paradigm which allows for long term audio recordings under naturalistic conditions. This experimental set-up results in the identification of additional vocalization types. In combination with state of the art methods for vocalization analysis, the authors demonstrate that the distribution of sound types and the transitions between these sound types across three gerbil families is different. This is a highly compelling finding which suggests that individual families may develop distinct vocal repertoires. One potential limitation of the study lies in the cluster analysis used for identifying distinct vocalization types. The authors use a Gaussian Mixed Model (GMM) trained on variational auto Encoder derived latent representation of vocalizations to classify recorded sounds into clusters. Through the analysis the authors identify 70 distinct clusters and demonstrate a differential usage of these sound clusters across families. While the authors acknowledge the inherent challenges in cluster analysis and provide additional analyses (i.e. maximum mean discrepancy, MMD), additional analysis would increase the strength of the conclusions. In particular, analysis with different cluster sizes would be valuable. An additional limitation of the study is that due to the methodology that is used, the authors can not provide any information about the bioacoustic features that contribute to differences in sound types across families which limits interpretations about how the animals may perceive and react to these sounds in an ethologically relevant manner.

The conclusions of this paper are well supported by data, but certain parts of the data analysis should be expanded and more fully explained.

• Can the authors comment on the potential biological significance of the 70 sound clusters? Does each cluster represent a single sound type? How many vocal clusters can be attributed to a single individual? Similarly, can the authors comment on the intra-individual and inter-individual variability of the sound types within and across families?

Previous work documenting the Mongolian gerbil repertoire (Ter-Mikaelian 2012, Kobayasi 2012) has revealed ~12 vocalization types that vary with social context. Our thinking is that we are capturing these ~12 (plus a few more, as illustrated in Figure 2C) as well as individual or family-specific variations of some call types. Although the number of discrete call types is likely less than 70, it’s plausible that variation due to vocalizer identity pushes some calls into unique clusters. This idea is supported by the fact that both naked mole rats and Mongolian gerbils have been shown to exhibit individual-specific variation in vocalizations, though only in single call types (Barker 2021, Figure 1; Nishiyama 2011, Table I). The current study is not ideal to test this prediction, as we cannot attribute each vocalization to individual family members. Using our 4-mic array, we attempted to apply established sound source localization techniques to assign vocalizations to individuals (Neunuebel 2015), but the technique failed, presumably due to high amounts of reverberation in the arena. We are currently developing a custom deep learning based sound localization algorithm, and had hoped to extract individual animal vocalizations from our data set (part of the reason why this manuscript has taken longer than expected to return!), but the performance is not yet satisfactory for large groups of animals. We have added text to the Methods sections with the context outlined above to further justify the use of ~70 clusters.

• As a main conclusion of the paper rests on the different distribution of sound clusters across families, it is important to validate the robustness of these differences across different cluster parameters. Specifically, the authors state that "we selected 70 clusters as the most parsimonious fit". Could the authors provide more details about how this was fit? Specifically, could the authors expand upon what is meant by "prior domain knowledge about the number of vocal types...". If the authors chose a range of cluster values (i.e. 10, 30, 50, 90) does the significance of the results still hold?

Thank you for the suggestion, this is an important point that we have addressed with new analyses in the revision (see GMM clustering methods and new Figure S4). The prior domain knowledge referenced is with respect to the information known about the Mongolian gerbil vocal types provided in the response above. We have made this more clear in the discussion.

We mainly based our selection of the number of clusters using the elbow method on GMM held-out log likelihood (Figure S2C). Around 70 clusters is when the likelihood begins to plateau, though it’s clear that there are a number of reasonable cluster sizes. To assess whether cluster size has an effect on interpretation of the family differences result, we added Figure S5, where we varied the number of GMM clusters used and compared cluster usage differences across families (Figure S4A). We quantified pairwise family differences in cluster usage by computing the sum of the absolute value of differential cluster usages, for each GMM cluster value (Figure S4B). We find that relative usage differences remain unchanged across the range of cluster values used, indicating that GMM cluster size does bias the finding.

• While VAEs are powerful tools for analyzing complex datasets in this case they are restricted to analysis of spectrogram images. Have the authors identified any acoustic differences (i.e. in pitch, frequency, and other sound components) across families?

Though it’s true that this VAE is limited to spectrograms, the VAE latent space has been shown to correspond to real acoustic features such as frequency and duration, and contain a higher representational capacity than traditional acoustic features (Goffinet 2021, Figure 2). Therefore, clustering of the latent space necessarily means that vocalizations with similar acoustic features are clustered together regardless of their family identity.

Despite this, your point is well taken that there could be systematic differences in certain acoustic features for specific call types. We are not able to ascertain this with the current dataset. This is addressed in Barker 2021 by recording a single call type (soft chirp) from individuals within and across families. Mongolian gerbils have been shown to exhibit individual differences in the initial, terminal, minimum, and maximum frequency of the ultrasonic up-frequency modulated call type (Figure 2, top right green; Nishiyama 2011, Figure 1A ). Therefore it’s possible that family-specific differences exist for that particular call type. To assess whether other call types show family or individual differences, it’s necessary to either 1.) elicit all call types from an animal in isolation or 2.) determine vocalizer identity in social-vocal interactions. The problem with the former idea is that gerbils only produce up-frequency modulated USVs in isolation and there is no known way to elicit the full vocal repertoire in single animals. The latter idea would allow for full use of the vocal repertoire, but requires invasive techniques (e.g., skull-implanted microphones, or awake-behaving laryngeal nerve recordings) that permit assignment of vocalizations to individuals during a natural social interaction. We are actively exploring solutions to both problems.

It’s likely that future studies will look deeper into acoustic differences between individuals and families. Therefore, we have added acoustic feature quantification of vocalizations in each of the GMM clusters as a reference (Figure S6).

Reviewer #3 (Public Review):

Summary:

In this study, Peterson et al. longitudinally record and document the vocal repertoires of three Mongolian gerbil families. Using unsupervised learning techniques, they map the variability across these groups, finding that while overall statistics of, e.g., vocal emission rates and bout lengths are similar, families differed markedly in their distributions of syllable types and the transitions between these types within bouts. In addition, the large and rich data are likely to be valuable to others in the field.

Strengths:

- Extensive data collection across multiple days in multiple family groups.

-  Thoughtful application of modern analysis techniques for analyzing vocal repertoires. - Careful examination of the statistical structure of vocal behavior, with indications that these gerbils, like naked mole rats, may differ in repertoire across families.

Weaknesses:

- The work is largely descriptive, documenting behavior rather than testing a specific hypothesis.

- The number of families (N=3) is somewhat limited.

We agree that the number of families is relatively small. However, our new analysis of vocal repertoire by postnatal day (Figure 4) demonstrates that the finding is quite robust. A high sample-size study was outside the scope of this initial observational study given the difficulty of obtaining and processing longitudinal data of this scale. In light of new analyses in Figure 4, we are confident that future studies will not need so much data to characterize family-specific differences. A single 24-hour recording should be sufficient, making comparison of many more families relatively straightforward.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Several minor concerns:

(1) The three thresholds used for vocalization segmentation lack explanation.

Figure 1C's first vocal event appears to define the first gap via the gray threshold (th_2, as the trace does not cross the black line) and the second gap via the black threshold (th_1 or th_3). And this is not addressed in the Methods section.

Thank you for bringing this to our attention. We agree, this is presented in an unnecessarily complicated way. We have updated the methods section describing the thresholding procedure.

“Sound onsets are detected when the amplitude exceeds 'th_3' (black dashed line, Figure 1C), and sound offset occurs when there is a subsequent local minimum e.g., amplitude less than 'th_2' (gray dashed line, Figure 1C), or 'th_1' (black dashed line, Figure 1C), whichever comes first. In this specific use case, th_2 (5) will always come before th_1 (2), therefore the gray dashed line will always be the offset. A subsequent onset will be marked if the sound amplitude crosses th_2 or th_3, whichever comes first. For example, the first sound event detected in Figure 1C shows the sound amplitude rising above the black dashed line (th_3) and marks an onset. Subsequently, the amplitude trace falls below the gray dashed line (th_2) and an offset is marked. Finally, the amplitude rises above th_2 without dipping below th_3 and an onset for a new sound event is marked. Had the amplitude dipped below th_3, a new sound event onset would be marked when the amplitude trace subsequently exceeded th_3 (e.g. between sound event 2 and 3, Figure 1C). The maximum and minimum syllable durations were selected based on published duration ranges of gerbil vocalizations (Ter-Mikaelian et al. 2012, Kobayasi & Riquimaroux, 2012).”

(2) The determination of multi-syllabic calls could be explained further. In Figure 1C, for instance, do syllables separated by short gaps (e.g., the first syllable and the rest of the first group, and the third group in this example) belong to the same call or different calls?

We have added an operational definition of mono vs. multisyllabic calls in the Results section:

“Vocalizations occur as either single syllables bounded by silence (monosyllabic) or consist of combinations of single syllables without a silent interval (multisyllabic).”

Under this definition, the examples you mentioned in Figure 1C are considered monosyllabic. One could reasonably expand the definition to include calls separated by less than X ms of silence for example, however we choose not to do that in this study. A deeper understanding of the phonation mechanisms for different gerbil vocalization types would be helpful to more rigorously determine the distinction between mono vs. multisyllabic vocalizations.

(3) Labeling the calls shown in Fig. 3D in the latent feature space would help highlight within-family diversity and between-family similarities.

Great suggestion. We have updated Figure 3 to include where in UMAP space each family’s preferred clusters are.

(4) In the introduction, the statement, "Therefore, our study considers the possibility that there is a diversity of vocalizations within the gerbil family social group" doesn't naturally follow from the previous example. This could be rephrased.

Agreed, thank you. We revised this section of the introduction to flow better.

Reviewer #2 (Recommendations For The Authors):

While outside the scope of the current study the authors may consider the following experiments and analysis for future studies:

• Do vocal repertories retain their family signatures across subsequent generations of pups? (i.e. if vocalizations are continually monitored during second or third litters of the same parents).

• Do the authors observe any long-term changes in family repertoires related to the developmental trajectory of the pups? Are there changes in individual pup vocal features or sound type usage throughout development?

Thank you for these great suggestions. Given that naked mole rats learn vocalizations through cultural transmission, it would be interesting to see whether other subterranean species with complex social structures (gerbils, voles, rats) have similar abilities. A straightforward way to assess this possibility could be as you suggest — are latent distributions of vocalizations from multi-generational families closer together than cross-family differences? If true, this would provide compelling evidence to investigate further.

We partially address your second suggestion in our response to Reviewer 1 and in Figure S4, which shows that the family repertoire remains stable throughout this particular period of development. This doesn’t rule out the possibility that there could be other phases of development that undergo more vocal change. Your final suggestion is an area that we are actively researching and eager to know the answer to. A follow-up question: could differences in pup vocal features contribute to differential care by parents?

Reviewer #3 (Recommendations For The Authors):

In all, I found the paper clearly written and the figures easy to follow. One small suggestion:

Figure 1: I can't see the black and gray thresholds described in the caption very well. Perhaps a zoom-in to the first 0.15s or so of the normalized amplitude plot would better display these.

Agreed, thank you. We added a zoom-in to Figure 1.

known as Hemedti or Little Mohamad - also holds position of deputy head of Sudan's ruling soverign council

Reviewer #2 (Public review):

This manuscript by Petty and Bruno delves into the still poorly understood role of higher-order thalamic nuclei in the encoding of sensory information by examining the activity in the Pom and LP cells in mice performing an associative learning task. They developed an elegant paradigm in which they conditioned head-fixed mice to attend to a stimulus of one sensory modality (visual or tactile) and ignore a second stimulus of the other modality. They recorded simultaneously from POm and LP, using 64-channels electrode arrays, to reveal the context-dependency of the firing activity of cells in higher-order thalamic nuclei. They concluded that behavioral training reshapes activity in these secondary thalamic nuclei. The authors brought new analyses and figures which greatly improve their manuscript and support their conclusion. The manuscript benefits now from a better communication about both the methodology and the results. I have no more major concerns, but I feel that the readability of the manuscript could be improved with the following revisions.

Strengths

The authors developed an original and elegant paradigm in which they conditioned head-fixed mice to attend to a stimulus of one sensory modality, either visual or tactile and ignore a second stimulus of the other modality. As a tactile stimulus, they applied gentle air puffs on the distal part of the vibrissae, ensuring that the stimulus was innocuous and therefore none aversive which is crucial in their study.

It is commonly viewed that first-order thalamus performs filtering and re-encoding of the sensory flow; in contrast the computations taking place in high-order nuclei are poorly understood. They may contribute to cognitive functions. By integrating top-down control, high-order nuclei may participate in generating update models of the environment based on sensory activity; how this can take place is a key question that Petty and Bruno addressed in the present study.

Weaknesses

(1) It's difficult when reading the text to understand which results were quantified and which were not, in part because mean data as well as (s.e.m. or S.D.) do not appear either in the main text nor in the legends of the figures. Only vague and unquantified data are given in the main text. I understand that the authors may want to make the main text less heavy, but having these data fully written somewhere (i.e., main text, summary table, figure legends) rather than having to estimate through looking at a graph (especially when the data are constraint in the first 20% of the graph (Figure 4c)), would greatly improve the text's clarity and precision.

For instance, Line #173, "At the population level, POm cells in both conditioning groups had a peak of activity 40ms after air puff onset (Figure 4a)." Is this 40 ms a result of quantified data, then a s.e.m. would be informative, or a reading measurement on the Figure 4a graphs? As it stands, it is too vague a value.

(2) The authors give clearer definition of what they analyzed, which greatly improved the readability of the manuscript. The clarity of the manuscript could still be improved by solving remaining ambiguities about sensory- versus non-sensory-responses to the applied stimuli throughout the manuscript, in order to better convey the authors' conclusion that behavioral training reshapes activity in these secondary thalamic nuclei which then may participate in generating update models of the context in which the animal is performing the task.

Line #24 in the abstract "In mice trained to respond to tactile stimuli and ignore visual stimuli, POm was robustly activated by touch and largely unresponsive to visual stimuli". The abstract would better reflect the manuscript conclusions indicating that POm was robustly activated during tactile stimuli.

(3) The new analysis of the "early" responses in Pom cells pointed out, Line #173, that "At the population level, POm cells in both conditioning groups had a peak of activity 40ms after air puff onset (Figure 4a)." Previous works cited by the authors, Diamond et al. (1992), described tactile responses in Pom cells at 15-20ms latency which were suppressed by the barrel cortex inactivation.

The 40ms-latency responses described in this manuscript therefore do not fit with "purely sensory" and barely with S1-feedbacks, as proposed on line #168 "Such responses could be "purely sensory" (i.e. driven by ascending brainstem inputs)" or line #334 "It is likely that the observed activity in lateral dorsal POm is driven by true whisker responses in SpVi and S1."

In the same way, Line #315 "we observed POm cells that responded to the onset of the air puff in both conditioning groups". This conclusion should be dampened, to better fit the results, by "we observed POm cells that responded 40 ms after the onset of the air puff in both conditioning groups."

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review): 

Petty and Bruno investigate how response characteristics in the higher-order thalamic nuclei POm (typically somatosensory) and LP (typically visual) change when a stimulus (whisker air puff or visual drifting grating) of one or the other modality is conditioned to a reward. Using a two-step training procedure, they developed an elegant paradigm, where the distractor stimulus is completely uninformative about the reward, which is reflected in the licking behavior of trained mice. While the animals seem to take on to the tactile stimulus more readily, they can also associate the reward with the visual stimulus, ignoring tactile stimuli. In trained mice, the authors recorded single-unit responses in both POm and LP while presenting the same stimuli. The authors first focused on POm recordings, finding that in animals with tactile conditioning POm units specifically responded to the air puff stimulus but not the visual grating. Unexpectedly, in visually conditioned animals, POm units also responded to the visual grating, suggesting that the responses are not modality-specific but more related to behavioral relevance. These effects seem not be homogeneously distributed across POm, whereas lateral units maintain tactile specificity and medial units respond more flexibly. The authors further ask if the unexpected cross-modal responses might result from behavioral activity signatures. By regressing behavior-coupled activity out of the responses, they show that late activity indeed can be related to whisking, licking, and pupil size measures. However, cross-modal short latency responses are not clearly related to animal behavior. Finally, LP neurons also seem to change their modality-specificity dependent on conditioning, whereas tactile responses are attenuated in LP if the animal is conditioned to visual stimuli.

The authors make a compelling case that POm neurons are less modality-specific than typically assumed. The training paradigm, employed methods, and analyses are mostly to the point, well supporting the conclusions. The findings importantly widen our understanding of higher-order thalamus processing features with the flexibility to encode multiple modalities and behavioral relevance. The results raise many important questions on the brain-wide representation of conditioned stimuli. E.g. how specific are the responses to the conditioned stimuli? Are thalamic cross-modal neurons recruited for the specific conditioned stimulus or do their responses reflect a more global shift of attention from one modality to another? 

To elaborate on higher-order thalamic activity in relationship to conditioned behavior, a trialby-trial analysis would be very useful. Is neuronal activity predictive of licking and at which relative timing? 

To elaborate on the relationship between neuronal activity and licking, we have created a new supplementary figure (Figure S1), where we present the lick latency of each mouse on the day of recording. We also perform more in-depth analysis of neural activity that occurs before lick onset, which is presented in a new main figure (new Figure 4). 

Furthermore, I wonder why the (in my mind) major and from the data obvious take-away, "POm neurons respond more strongly to visual stimuli if visually conditioned", is not directly tested in the summary statistics in Figure 3h.

We have added a summary statistic to Figure 3h and to the Results section (lines 156-157) comparing the drifting grating responses in visually and tactilely conditioned mice.  

The remaining early visual responses in POm in visually conditioned mice after removing behavior-linked activity are very convincing (Figure 5d). It would help, however, to see a representation of this on a single-neuron basis side-by-side. Are individual neurons just coupled to behavior while others are independent, or is behaviorally coupled activity a homogeneous effect on all neurons on top of sensory activity?

In lieu of a new figure, we have performed a new analysis of individual neurons to classify them as “stimulus tuned” and/or “movement tuned.” We find that nearly all POm cells encode movement and arousal regardless of whether they also respond to stimuli. This is presented in the Results under the heading “POm correlates with arousal and movement regardless of conditioning” (Lines 219-231).

The conclusions on flexible response characteristics in LP in general are less strongly supported than those in POm. First, the differentiation between POm and LP relies heavily on the histological alignment of labeled probe depth and recording channel, possibly allowing for wrong assignment. 

We appreciate the importance in differentiating between POm, LP, and surrounding regions to accurately assign a putative cell to a brain region. The method we employed (aligning an electrode track to a common reference atlas) is widely used in rodent neuroscience, especially in regions like POm and LP which are difficult to differentiate molecularly (for example, see Sibille, Nature Communications, 2022; and Schröder, Neuron, 2020). 

Furthermore, it seems surprising, but is not discussed, that putative LP neurons have such strong responses to the air puff stimuli, in both conditioning cases. In tactile conditioning, LP air puff responses seem to be even faster and stronger than POm. In visual conditioning, drifting grating responses paradoxically seem to be later than in tactile conditioning (Fig S2e). These differences in response changes between POm and LP should be discussed in more detail and statements of "similar phenomena" in POm and LP (abstract) should be qualified.  

We have further developed our analysis and discussion of LP activity. Our analysis of LP stimulus response latencies are now presented in greater detail in Figure S3, and we have expanded the results section accordingly (lines 266-275). We have also expanded the discussion section to both address these new analyses and speculate on what might drive these surprising “tactile responses” in LP.

Reviewer #2 (Public Review): 

Summary  

This manuscript by Petty and Bruno delves into the still poorly understood role of higherorder thalamic nuclei in the encoding of sensory information by examining the activity in the Pom and LP cells in mice performing an associative learning task. They developed an elegant paradigm in which they conditioned head-fixed mice to attend to a stimulus of one sensory modality (visual or tactile) and ignore a second stimulus of the other modality. They recorded simultaneously from POm and LP, using 64-channel electrode arrays, to reveal the contextdependency of the firing activity of cells in higher-order thalamic nuclei. They concluded that behavioral training reshapes activity in these secondary thalamic nuclei. I have no major concerns with the manuscript's conclusions, but some important methodological details are lacking and I feel the manuscript could be improved with the following revisions.

Strengths 

The authors developed an original and elegant paradigm in which they conditioned headfixed mice to attend to a stimulus of one sensory modality, either visual or tactile, and ignore a second stimulus of the other modality. As a tactile stimulus, they applied gentle air puffs on the distal part of the vibrissae, ensuring that the stimulus was innocuous and therefore none aversive which is crucial in their study. 

It is commonly viewed that the first-order thalamus performs filtering and re-encoding of the sensory flow; in contrast, the computations taking place in high-order nuclei are poorly understood. They may contribute to cognitive functions. By integrating top-down control, high-order nuclei may participate in generating updated models of the environment based on sensory activity; how this can take place is a key question that Petty and Bruno addressed in the present study.

Weaknesses  

(1) Overall, methods, results, and discussion, involving sensory responses, especially for the Pom, are confusing. I have the feeling that throughout the manuscript, the authors are dealing with the sensory and non-sensory aspects of the modulation of the firing activity in the Pom and LP, without a clear definition of what they examined. Making subsections in the results, or a better naming of what is analyzed could convey the authors' message in a clearer way, e.g., baseline, stim-on, reward.  

We thank Reviewer 2 for this suggestion. We have adjusted the language throughout the paper to more clearly state which portions of a given trial we analyzed. We now consistently refer to “baseline,” “stimulus onset,” and “stimulus offset” periods. 

In line #502 in Methods, the authors defined "Sensory Responses. We examined each cell's putative sensory response by comparing its firing rate during a "stimulus period" to its baseline firing rate. We first excluded overlapping stimuli, defined as any stimulus occurring within 6 seconds of a stimulus of a different type. We then counted the number of spikes that occurred within 1 second prior to the onset of each stimulus (baseline period) and within one second of the stimulus onset (stimulus period). The period within +/-50ms of the stimulus was considered ambiguous and excluded from analysis." 

Considering that the responses to whisker deflection, while weak and delayed, were shown to occur, when present, before 50 ms in the Pom (Diamond et al., 1992), it is not clear what the authors mean and consider as "Sensory Responses"? 

We have addressed this important concern in three ways. First, we have reanalyzed our data to include the 50ms pre- and post-stimulus time windows that were previously excluded. This did not qualitatively change our results, but updated statistical measurements are reflected in the Results and the legends of figures 3 and 7. Second, we have created a new figure (new Figure 4) which provides a more detailed analysis of early POm stimulus responses at a finer time scale. Third, we have amended the language throughout the paper to refer to “stimulus responses” rather than “sensory responses” to reflect how we cannot disambiguate between bottom-up sensory input and top-down input into POm and LP with our experimental setup. We refer only to “putative sensory responses” when discussing lowlatency (<100ms) stimulus responses.

Precise wording may help to clarify the message. For instance, line #134: "Of cells from tactilely conditioned mice, 175 (50.4%) significantly responded to the air puff, as defined by having a firing rate significantly different from baseline within one second from air puff onset (Figure 3d, bottom)", could be written "significantly responded to the air puff" should be written "significantly increased (or modified if some decreased) their firing rate within one second after the air puff onset (baseline: ...)". This will avoid any confusion with the sensory responses per se.

We have made this specific change suggested by the reviewer (lines 145-146) and made similar adjustments to the language throughout the manuscript to better communicate our analysis methods. 

(2) To extend the previous concern, the latency of the modulation of the firing rate of the Pom cells for each modality and each conditioning may be an issue. This latency, given in Figure S2, is rather long, i.e. particularly late latencies for the whisker system, which is completely in favor of non-sensory "responses" per se and the authors' hypothesis that sensory-, arousal-, and movement-evoked activity in Pom are shaped by associative learning. Latency is a key point in this study. 

Therefore, 

- latencies should be given in the main text, and Figure S2 could be considered for a main figure, at least panels c, d, and e, could be part of Figure 3. 

- the Figure S2b points out rather short latency responses to the air puff, at least in some cells, in addition to late ones. The manuscript would highly benefit from an analysis of both early and late latency components of the "responses" to air puffs and drafting grating in both conditions. This analysis may definitely help to clarify the authors' message. Since the authors performed unit recordings, these data are accessible.

- it would be highly instructive to examine the latency of the modulation of Pom cells firing rate in parallel with the onset of each behavior, i.e. modification of pupil radius, whisking amplitude, lick rate (Figures 1e, g and 3a, b). The Figure 1 does not provide the latency of the licks in conditioned mice.

- the authors mention in the discussion low-latency responses, e.g., line #299: "In both tactilely and visually conditioned mice, movement could not explain the increased firing rate at air puff onset. These low-latency responses across conditioning groups is likely due in part to "true" sensory responses driven by S1 and SpVi."; line #306: "Like POm, LP displayed varied stimulus-evoked activity that was heavily dependent on conditioning. LP responded to the air puff robustly and with low latency, despite lacking direct somatosensory inputs."  But which low-latency responses do the authors refer to? Again, this points out that a robust analysis of these latencies is missing in the manuscript but would be helpful to conclude.

We have moved our analysis of stimulus response latency in POm to new Figure 4 in the main text and have expanded both the Results and Discussion sections accordingly. We have also analyzed the lick latency on the day of recording, included in a new supplemental Figure S1. 

(3) Anatomical locations of recordings in the dorsal part of the thalamus. Line #122 "Our recordings covered most of the volume of POm but were clustered primarily in the anterior and medial portions of LP (Figure 2d-f). Cells that were within 50 µm of a region border were excluded from analysis." 

How did the authors distinguish the anterior boundary of the LP with the LD nucleus just more anterior to the LP, another higher-order nucleus, where whisker-responsive cells have been isolated (Bezdudnaya and Keller, 2008)? 

Cells within 50µm of any region boundary were excluded, including those at the border of LP and LD. We also reviewed our histology images by eye and believe that our recordings were all made posterior of LD. 

(4) The mention in the Methods about the approval by an ethics committee is missing.  All the surgery (line #381), i.e., for the implant, the craniotomy, as well as the perfusion, are performed under isoflurane. But isoflurane induces narcosis only and not proper anesthesia. The mention of the use of analgesia is missing. 

We thank Reviewer 2 for drawing our attention to this oversight. All experiments were conducted under the approval of the Columbia University IACUC. Mice were treated with the global analgesics buprenorphine and carprofen, the local analgesic bupivacaine, and anesthetized with isoflurane during all surgical procedures. We have amended the Methods section to include this information (Lines 458-470).

Reviewer #3 (Public Review): 

Petty and Bruno ask whether activity in secondary thalamic nuclei depends on the behavioral relevance of stimulus modality. They recorded from POm and LP, but the weight of the paper is skewed toward POm. They use two cohorts of mice (N=11 and 12), recorded in both nuclei using multi-electrode arrays, while being trained to lick to either a tactile stimulus (air puff against whiskers, first cohort) or a visual stimulus (drifting grating, second cohort), and ignore the respective other. They find that both nuclei, while primarily responsive to their 'home' modality, are more responsive to the relevant modality (i.e. the modality predicting reward). 

Strengths: 

The paper asks an important question, it is timely and is very well executed. The behavioral method using a delayed lick index (excluding impulsive responses) is well worked out. Electrophysiology methods are state-of-the-art with information about spike quality in Figure S1. The main result is novel and important, convincingly conveying the point that encoding of secondary thalamic nuclei is flexible and clearly includes aspects of the behavioral relevance of a stimulus. The paper explores the mapping of responses within POm, pointing to a complex functional structure, something that has been reported/suggested in earlier studies. 

Weaknesses: 

Coding: It does not become clear to which aspect of the task POm/LP is responding. There is a motor-related response (whisking, licking, pupil), which, however, after regressing it out leaves a remaining response that the authors speculate could be sensory.

Learning: The paper talks a lot about 'learning', although it is only indirectly addressed. The authors use two differently (over-)trained mice cohorts rather than studying e.g. a rule switch in one and the same mouse, which would allow us to directly assess whether it is the same neurons that undergo rule-dependent encoding. 

We disagree that our animals are “overtrained,” as every mouse was fully trained within 13 days. We agree that it would be interesting to study a rule-switch type experiment, but such an experiment is not necessary to reveal the profound effect that conditioning has on stimulus responses in POm and LP. 

Mapping: The authors treat and interpret the two nuclei very much in the same vein, although there are clear differences. I would think these differences are mentioned in passing but could be discussed in more depth. Mapping using responses on electrode tracks is done in POm but not LP.

The mapping of LP responses by anatomical location is presented in the supplemental Figure S4 (previously S3). We have expanded our discussion of LP and how it might differ from POm.

Reviewer #1 (Recommendations For The Authors):  

Minor writing issues: 

122 ...67 >LP< cells?

301 plural "are”

We have fixed these typos.

Figure issues

*  3a,b time ticks are misaligned and the grey bar (bottom) seems not to align with the visual/tactile stimulus shadings.

*  legend to Figure 3b refers to Figure 1c which is a scheme, but if 1g is meant, this mouse does not seem to have a session 12? 

*  3c,e time ticks slightly misaligned. 

*  5e misses shading for the relevant box plots, assuming it should be like Figure 3h.  

We thank Reviewer 1 for pointing out these errors. We have adjusted Figures 1, 3, and 5 accordingly.

Analyses 

I am missing a similar summary statistics for LP as in Figure 3h 

We have added a summary box chart of LP stimulus responses (Figure 7g), similar to that of POm in Figure 3. We have also performed similar statistical analyses, the results of which are presented in the legend for Figure 7. 

Reviewer #2 (Recommendations For The Authors): 

More precisions are required for the following points: 

(1) The mention of the use of analgesia is missing and this is not a minor concern. Even if the recordings are performed 24 hours after the surgery for the craniotomy and screw insertion and several days after the main surgery for the implant, taking into account the pain of the animals during surgeries is crucial first for ethical reasons, and second because it may affect the data, especially in Pom cells: pain during surgery may induce the development of allodynia and/or hyperalgesia phenomenae and Pom responses to sensory stimuli were shown to be more robust in behavioral hyperalgesia (Masri et al., 2009).  

We neglected to include details on the analgesics used during surgery and post-operation recovery in our original manuscript. Mice were administered buprenorphine, carprofen, and bupivacaine immediately prior to the head plate surgery and were treated with additional carprofen during recovery. Mice were similarly treated with analgesics for the craniotomy procedure. Mice were carefully observed after craniotomy, and we saw no evidence of pain or discomfort. Furthermore, mice performed the behavior at the same level pre- and postcraniotomy (now presented in Figure 1j), which also indicates that they were not in any pain. 

(2) The head-fixed preparation is only poorly described.

Line #414: "Prior to conditioning, mice were habituated to head fixation and given ad libitum water in the behavior apparatus for 15-25 minutes." 

And line #425 "Mice were trained for one session per day, with each session consisting of an equal number of visual stimuli and air puffs. Sessions ranged from 20-60 minutes and about 40-120 of each stimulus. " 

More details should be given about the head-fixation training protocol. Are 15-25 minutes the session time duration, 60 minutes, or other time duration? How long does it take to get mice well trained to the head fixation, and on which criteria?  

Line #389: "Mice were then allowed to recover for 24 hours, after which the sealant was removed and recordings were performed. At the end of experiments,"

The timeline is not clear: is there one day or several days of recordings? 

We have expanded on our description of the head fixation protocol in the Methods. We describe in more detail how mice were habituated to head fixation, the timing of water restriction, and the start of conditioning/training (Habituation and Conditioning, lines 492-500).

(4) Line #411: "Mice were deprived of water 3 days prior to the start of conditioning" followed by line #414 "Prior to conditioning, mice were habituated to head fixation and given ad libitum water in the behavior apparatus for 15-25 minutes".

If I understood correctly, the mice were then not fully water-deprived for 3 days since they received water while head-fixed. This point may be clarified. 

We addressed these concerns in the changes to the Methods section mentioned in the preceding point (3).

(5) Line #157: "Modality selectivity varies with anatomical location in Pom" while the end of the previous paragraph is "This suggests that POm encoding of reward and/or licking is insensitive to task type, an observation we examine further below."

The authors then come to anatomical concerns before coming back to what the Pom may encode in the following section. This makes the story quite confusing and hard to follow even though pretty interesting.  

We have reordered our Figures and Results to improve the flow of the paper and remove this point of confusion. We now present results on the encoding of movement before analyzing the relationship between POm stimulus responses and anatomical location. What was old Figure 5 now precedes what was old Figure 4.

(6) Licks Analysis. Line #99 "However, this mouse also learned that the air puff predicted a lack of reward in the shaping task, as evidenced by withholding licking upon the onset of the air puff. The mouse thus displayed a positive visual lick index and a negative tactile lick index, suggesting that it attended to both the tactile and visual stimuli (Figure 1f, middle arrow)."

Line #105 "All visually conditioned mice exhibited a similar learning trajectory (Figure 1i left, 1j left)". 

Interestingly, the authors revealed that mice withheld licking upon the onset of the air puff in the visual conditioning, which they did not do at the onset of the drifting grating in the tactile conditioning. This withholding was extinguished after the 8th session, which the authors interpret as the mice finally ignoring the air puff. Is this effect significant, is there a significant withholding licking upon the onset of the air puff on the 12 tested mice? 

The withholding of licking was significant (assessed with a sign-rank test) in visually conditioned mice prior to switching to the full version of the task. Indeed, it was the abolishment of this effect after conditioning with the full version of the task that was our criterion for when a mouse was fully trained. We have elaborated on this in the Habituation and Conditioning section in the Methods.

(1) Throughout the manuscript "Touch" is used instead of passive whisker deflection, and may be confusing with "active touch" for the whisker community readers. I recommend avoiding using "touch" instead of "passive whisker deflection".

We appreciate that “touch” can be an ambiguous term in some contexts. However, we have limited our use of the word to refer to the percept of whisker deflection; we do not describe the air puff stimulus as a “touch.” We respectfully would like to retain the use of the word, as it is useful for comparing somatosensory stimuli to visual stimuli.

(2) Line #395: "Air puffs (0.5-1 PSI) were delivered through a nozzle (cut p1000 pipet tip, approximately 3.5mm diameter aperture)".

Are air puffs of <1 PSI applied, not <1 bar?  

We thank Reviewer 3 for pointing out this inaccuracy. The air puffs were indeed between 0.5 and 1 bar, not PSI. We have addressed this in the Methods.

(3) Line #441: "In the full task, the stimuli and reward were identical, but stimuli were presented at uncorrelated and less predictable intervals."  Do the authors mean that all stimuli are rewarded?  

The stimuli and reward were identical between the shaping and full versions of the task. In the full version of the task, the unrewarded stimulus was truly uncorrelated with reward, rather than anticorrelated. 

(4) Line #445 "for a mean ISI of 20 msec." ISI is not defined, I guess that it means interstimulus interval. Even if pretty obvious, to avoid any confusion for future readers, I would recommend using another acronym, especially in a manuscript about electrophysiology, since ISI is a dedicated acronym for inter-spike interval. 

We have defined the acronym ISI as “inter-stimulus interval” when first introduced in the results (Line 82) and in the Methods (Line 511).

(5) Line #416 "In the first phase of conditioning ("shaping"), mice were separated into two cohorts: a "tactile" cohort and a "visual" cohort. Mice were presented with tactile stimuli (a two-second air puff delivered to the distal whisker field) and visual stimuli (vertical drifting grating on a monitor). Throughout conditioning, mice were monitored via webcam to ensure that the air puff only contacted the whiskers and did not disturb the facial fur nor cause the mouse to blink, flinch, or otherwise react - ensuring the stimulus was innocuous. The stimulus types were randomly ordered. In the visual conditioning cohort, the visual stimulus was paired with a water reward (8-16µL) delivered at the time of stimulus offset. In the tactile conditioning cohort, the reward was instead paired with the offset of the air puff. Regardless of the type of conditioning, stimulus type was a balanced 50:50 with an inter-stimulus interval of 8-12 seconds (uniform distribution)." 

The mention of the "full version of the task" will be welcome in this paragraph to clarify what the task is for the mouse in the Methods part.

We have more clearly defined the full version of the task in a later paragraph (line 506). We believe this addresses the potential confusion caused by the original description of the conditioning paradigm. 

(6) Line #467: "Units were assigned to the array channel on which its mean waveform was largest". 

Should it read mean waveform "amplitude"? 

This is correct, we have adjusted the statement accordingly. 

(7) Line #482 "The eye camera was positioned on the right side of the face and recorded at 60 fps." Then line #487 "The trace of pupil radius over time was smoothed over 5 frames (8.3 msec).” 5 frames, with a 60fps, represent then 83 ms and not 8.3 ms.

We have corrected this error.  

(8) Line #121: "257 POm cells and 67 cells from 12 visually conditioned mice" 

67 LP cells, LP is missing 

We have corrected this error. 

(9) Line #354: "A consistent result of attention studies in humans and nonhuman primates is the enhancement of cortical and thalamic sensory responses to an attended visual stimuli. Here, we show not just enhancement of sensory responses to stimuli within a single modality, but also across modalities. It is worth investigating further how secondary thalamus and high-order sensory cortex encode attention to stimuli outside of their respective modalities. Our surprising conclusion that the nuclei are equivalently activated by behaviorally relevant stimuli is nevertheless compatible with these previous studies."  Since higher-order thalamic nuclei are integrative centers of many cortical and subcortical inputs, they cannot be viewed simply as relay nuclei, and there is therefore no "surprising" conclusion in these results. Not surprising, but still an elegant demonstration of the contextdependent activity/responses of the Pom/LP cells. 

We disagree. Visual stimuli activating strong POm responses and tactile stimuli activating strong LP responses - however they do it - is a surprising result. We agree that higher-order thalamic nuclei are integrative centers, but exactly what they integrate and what the integrated output means is still poorly understood.

this story is significant to the historical context of the native Americans as it describes there history and how happy they were until a great bird came to disrupt there life, we don’t know what this bird represents but it ruined there lives and stole there children and moshup put a stop to it and killed the bird

Restoration to 18th Century Notes Restoration and the Glorious Revolution Death of Cromwell: Leads to political instability. Charles II's Return: Parliament invites him to rule, marking the start of the Restoration. Initial Anarchy: Political turmoil follows; Charles II serves as a "figurehead." James II's Absolute Rule: Attempts to restore Catholicism create insecurity in Parliament. William of Orange's Intervention: Invited to intervene, leading to the Glorious Revolution (bloodless). The Bill of Rights: Establishes Parliament as the de facto ruler, with the king as titular head, ending conflict between king and Parliament. Jonathan Swift (1667-1745) Background: Irish author, clergyman, and master of satire. Faced hardships: father died, raised in poverty by an uncle. Moved to England during the Glorious Revolution. Career Highlights: Became an Anglican priest. Wrote political tracts, poems, and notable satirical works. Notable Works: A Modest Proposal: Satirical essay addressing poverty in Ireland. Gulliver’s Travels: Most popular work, blending adventure with social critique. A Tale of a Tub: Another significant satire. Themes: Ranges from love/beauty to death/revenge; darker tones reflect personal struggles. A Modest Proposal (1729) Overview: Addresses poverty and overpopulation in Ireland through an absurd proposal. Key Elements: Humor: Uses absurdity to draw attention. Criticism: Critiques societal neglect of the poor. Moral Voice: Presents a moral argument ironically. Irony and Sarcasm: Highlights the ridiculousness of the proposal. Taboo Topics: Engages with sensitive issues to provoke discussion. Five Elements of Satire Ridicule: Makes subjects seem absurd, inviting scorn and amusement. Seriousness: Addresses significant societal issues humorously. Problem Identification: Aims to highlight and correct flaws in society. Mock-Heroic Tone: The speaker may be oblivious to their own absurdity. Modern Satire Examples The Onion: Satirical news outlet that parodies journalism. Comments on real and fictional events humorously. The Colbert Report: Satirical TV show featuring Stephen Colbert as a conservative pundit. Uses satire to critique political and media landscapes.

Crash course on typewriter maintenance and repair

A list of resources and references for the budding typewriter repair person. There is a lot here that I've compiled and consumed over the last six months, so don't be overwhelmed. Half the battle is figuring out where to find all these things, so if nothing else, this should shave off a month of reading and researching.

Basic Introductory Material

Get a notebook and be ready to take some notes so you'll remember where you found the random information you're bound to pick up over time and are able to occasionally review it.

Work your way through Sarah Everett's excellent Typewriter 101 videos (at least the first five): https://www.youtube.com/playlist?list=PLJtHauPh529XYHI5QNj5w9PUdi89pOXsS

Read Richard Polt's book which is a great overview to the general space:<br /> Polt, Richard. The Typewriter Revolution: A Typist’s Companion for the 21st Century. 1st ed. Woodstock, VT: Countryman Press, 2015.

Next watch the documentary California Typewriter. Documentary. Gravitas Pictures, 2016. https://www.imdb.com/title/tt5966990/. It has some interesting subtle material hiding within it, but it will give you a good idea of where you're headed off to.

Get a machine (or four) you can practice on. Get a flat head screwdriver and maybe a small adjustable wrench. Buy some mineral spirits and a small headed toothbrush and clean out your first machine. Buy some light sewing machine oil and try oiling it. Search YouTube for videos about how to repair anything that may be wrong with it.

Basic restoration advice: https://site.xavier.edu/polt/typewriters/tw-restoration.html

On colloquial advice for degreasing, cleaning, and oiling manual typewriters https://boffosocko.com/2024/08/09/on-colloquial-advice-for-degreasing-cleaning-and-oiling-manual-typewriters/

Repair Manuals

Create an account on typewriterdatabase.com which will give you some additional access to catalogs, manuals, and dealer catalogs.

They also have some openly accessible material like:<br /> * https://typewriterdatabase.com/manuals.php

Printed manuals: https://www.lulu.com/search?adult_audience_rating=00&contributor=Ted+Munk&page=1&pageSize=50 PDF manuals: https://sellfy.com/twdb

Ted Munk's website also has a plethora of ephemera that is often useful * https://munk.org/typecast/

Richard Polt's list of service manuals, which also includes some correspondence course typewriter repair classes: https://site.xavier.edu/polt/typewriters/tw-manuals.html#servicemanuals

Tools

In rough order of increasing complexity:

• Typewriter Tool Kit from the DOLLAR TREE by Just My Typewriter https://www.youtube.com/watch?v=R-7E4fM6gBw
• Some simple basics and where to get them: https://boffosocko.com/2024/08/11/adding-to-my-typewriter-toolset/
• Typewriter tools of the trade: https://www.youtube.com/watch?v=x5bKk93rtxs
• Lucas Dul's Toolset presentation: https://virtualhermans.com/lucas-dul
• Tour of an advanced hobbyist/semi-pro shop: https://www.youtube.com/watch?v=lZjf6InMlgU

Tools can be expensive, so start out small with just a few things and expand as you need them. You'll be amazed at what you can accomplish with a single thin bladed flathead screwdriver, an adjustable wrench, a rag, a bottle of Simple Green cleaning solution, and a bottle of isopropyl alcohol.

Videos

Subscribe to and become acquainted with YouTube channels like the following:

• Duane Jensen's Phoenix Typewriter https://www.youtube.com/@phoenixtypewriter2136
• Gerren Balch's HotRod Typewriter Company https://www.youtube.com/@HotRodTypewriter
• Joe Van Cleave https://www.youtube.com/@Joe_VanCleave
• Sarah Everett's Just My Typewriter https://www.youtube.com/@JustMyTypewriter

While watching a variety of videos is great, as you're doing specific repairs search YouTube and you're likely to find full demos of the repairs you're doing yourself.

I've compiled a playlist of videos for repair of an Olympia SM3 which, while specific to the SM3, is a an excellent outline/overview of how to disassemble a portable typewriter, where many of the adjustment points are as well as an outline of the order to do them in.

If you're not a good typist or don't have experience in the area, try out some of the following short films which will also provide some useful historical perspective:

• Basic Typing: Methods. Vol. MN-1512a. United States Navy Training Film, 1943. https://www.youtube.com/watch?v=ztyzGit1dTI.
• Basic Typing: Machine Operation. Vol. MN-1512b. United States Navy Training Film, 1943. https://www.youtube.com/watch?v=b-REJEArnjE.
• Advanced Typing: Shortcuts. Vol. MN-1512c. United States Navy Training Film, 1943. https://www.youtube.com/watch?v=JUJfCfqgsX0.
• Advanced Typing: Duplicating and Manuscript. Vol. MN-1512d. United States Navy Training Film, 1943. https://www.youtube.com/watch?v=7ve5JnTUzvo.
• Maintenance Of Office Machines. Vol. MN-1513. United States Navy Training Film, 1943. https://www.youtube.com/watch?v=ocdxgkxKAKo.

Internships & Apprenticeships

If you have the time and flexibility try arranging an internship or apprenticeship with a local typewriter repair shop. Meet your local repair people even if you can't spend the time on an internship. You'll learn a lot and create relationships with businesses who will more easily swap/supply you with machines they're parting out or access to tools which may otherwise be difficult to source.

• https://site.xavier.edu/polt/typewriters/tw-repair.html

Podcasts

• Austin Typewriter Ink https://www.austintypewriterink.com/ati-the-podcast.html
• Charm Type Repair https://charmtypepodcast.podbean.com/

Some useful Bibliography

• Athey, Ralph S. Typewriter Repair Training Course. Tarentum, PA: Typewriter Repair Training, 1957. https://site.xavier.edu/polt/typewriters/AtheyTypewriterRepair.pdf.
• Atkinson, Annelise. Typewriter SOS: The DIY Guide to Fixing Common Problems with Typewriters, 2014. https://www.amazon.com/Typewriter-SOS-Fixing-Problems-Typewriters/dp/1520902700/.
• Hausrath, Alfred H., and Eugene L. Dahl. Typewriter Care. Edited by Walter K.M. Slavik. Federal Work Improvement Program United States Civil Service Commission and Government Division, U.S. Treasury Department, 1945. http://archive.org/details/twcare-1945.
• Jones, Clarence LeRoy. The Manual Typewriter Repair Bible. Edited by Theodore Munk. The Typewriter Repair Bible Series, 2017. https://www.lulu.com/shop/ted-munk/the-manual-typewriter-repair-bible/paperback/product-1vgk72jp.html.
• Kasten, R. M. “First Aid for Typewriters.” Popular Science Monthly, May 1941.
• Kravitz, Bryan. Hints for a Happy Typewriter. Bryan Kravitz, 1983. https://site.xavier.edu/polt/typewriters/Hints-Happy-TW.pdf.
• Hutchison, Howard. The Typewriter Repair Manual. 1st ed. Blue Ridge Summit, Pa: Tab Books, 1981. https://www.amazon.com/typewriter-repair-manual-Howard-Hutchison/dp/0830600345.
• Munk, Theodore. “The Typewriter Database,” 2012. https://typewriterdatabase.com/.
• Pearce, H. G. Complete Instructions: How to Repair, Rebuild, and Adjust Underwood Typewriters With Handy Reference for Locating Trouble Quickly. Bridgeport, CT: Typewriter Mechanics Publishing Co., 1920. https://johnesimmons.com/Typewriter/Articles/Manualpdf/Underwood_Repair_Manual.pdf.
• Polt, Richard. “The Classic Typewriter Page : All About Typewriters,” 2009. https://site.xavier.edu/polt/typewriters/index.html.
• Scadden, David T. Approved Home Study Course in Typewriter Repair and Service. Little Falls, NJ: Typewriter Repair School, 1959. https://site.xavier.edu/polt/typewriters/homestudycourse.pdf.

Good luck on your journey!

reply to u/fontinalispluma at https://old.reddit.com/r/typewriters/comments/1gaza5x/learning_typewriter_maintenance_and_repair/

16:30 "But the only fatwa that has, in fact, said that no images of Mohammed are permitted, and that includes Islamic paintings, not just the cartoons, came out in 2013 in Saudi Arabia by a Salafi cleric whose name is Al-Munajid. And there are other fatwas like Asistani, the Shi'i cleric, who says these images are perfectly fine, as long as they're respectful."

20:00 Fatwas can be issued (like the above) in a vacuum without any real conversation within the Islamic community. Few years back even building a snowman fatwa as haram. Animals are decapitated in Saudi textbooks. People in 20th century having 14th century book that depicts a head, decapitating it (al-ras).

Reviewer #1 (Public review):

Summary:

Sun et al. are interested in how experience can shape the brain and specifically investigate the plasticity of the Toll-6 receptor-expressing dopaminergic neurons (DANs). To learn more about the role of Toll-6 in the DANs, the authors examine the expression of the Toll-6 receptor ligand, DNT-2. They show that DNT-2 expressing cells connect with DANs and that loss of function of DNT-2 in these cells reduces the number of PAM DANs, while overexpression causes alterations in dendrite complexity. Finally, the authors show that alterations in the levels of DNT-2 and Toll-6 can impact DAN-driven behaviors such as climbing, arena locomotion, and learning and long-term memory.

Strengths:

The authors methodically test which neurotransmitters are expressed by the 4 prominent DNT-2 expressing neurons and show that they are glutamatergic. They also use Trans-Tango and Bac-TRACE to examine the connectivity of the DNT-2 neurons to the dopaminergic circuit and show that DNT-2 neurons receive dopaminergic inputs and output to a variety of neurons including MB Kenyon cells, DAL neurons, and possibly DANS.

Weaknesses:

(1) To identify the DNT-2 neurons, the authors use CRISPR to generate a new DN2-GAL4. They note that they identified at least 12 DNT-2 plus neurons. In Supplementary Figure 1A, the DNT-2-GAL4 driver was used to express a UAS-histoneYFP nuclear marker. From these figures, it looks like DNT-2-GAL4 is labeling more than 12 neurons. Is there glial expression?

(2) In Figure 2C the authors show that DNT-2 upregulation leads to an increase in TH levels using q-RT-PCR from whole heads. However, in Figure 3H they also show that DNT-2 overexpression also causes an increase in the number of TH neurons. It is unclear whether TH RNA increases due to expression/cell or the number of TH neurons in the head.

(3) DNT-2 is also known as Spz5 and has been shown to activate Toll-6 receptors in glia (McLaughlin et al., 2019), resulting in the phagocytosis of apoptotic neurons. In addition, the knockdown of DNT-2/Spz5 throughout development causes an increase in apoptotic debris in the brain, which can lead to neurodegeneration. Indeed Figure 3H shows that an adult-specific knockdown of DNT-2 using DNT2-GAL4 causes an increase in Dcp1 signal in many neurons and not just TH neurons.

Author response:

Reviewer #1 (Public review):

Summary:

Sun et al. are interested in how experience can shape the brain and specifically investigate the plasticity of the Toll-6 receptor-expressing dopaminergic neurons (DANs). To learn more about the role of Toll-6 in the DANs, the authors examine the expression of the Toll-6 receptor ligand, DNT-2. They show that DNT-2 expressing cells connect with DANs and that loss of function of DNT-2 in these cells reduces the number of PAM DANs, while overexpression causes alterations in dendrite complexity. Finally, the authors show that alterations in the levels of DNT-2 and Toll-6 can impact DAN-driven behaviors such as climbing, arena locomotion, and learning and long-term memory.

Strengths:

The authors methodically test which neurotransmitters are expressed by the 4 prominent DNT-2 expressing neurons and show that they are glutamatergic. They also use Trans-Tango and Bac-TRACE to examine the connectivity of the DNT-2 neurons to the dopaminergic circuit and show that DNT-2 neurons receive dopaminergic inputs and output to a variety of neurons including MB Kenyon cells, DAL neurons, and possibly DANS.

We are very pleased that Reviewer 1 found our connectivity analysis a strength.

Weaknesses:

(1) To identify the DNT-2 neurons, the authors use CRISPR to generate a new DN2-GAL4. They note that they identified at least 12 DNT-2 plus neurons. In Supplementary Figure 1A, the DNT-2-GAL4 driver was used to express a UAS-histoneYFP nuclear marker. From these figures, it looks like DNT-2-GAL4 is labeling more than 12 neurons. Is there glial expression?

Indeed, we claimed that DNT-2 is expressed in at least 12 neurons (see line 141, page 6 of original manuscript), which means more than 12 could be found. The membrane tethered reporters we used – UAS-FlyBow1.1, UASmcD8-RFP, UAS-MCFO, as well as UAS-DenMark:UASsyd-1GFP – gave a consistent and reproducible pattern. However, with DNT-2GAL4>UAS-Histone-YFP more nuclei were detected that were not revealed by the other reporters. We have found also with other GAL4 lines that the patterns produced by different reporters can vary. This could be due to the signal strength (eg His-YFP is very strong) and perdurance of the reporter (e.g. the turnover of His-YFP may be slower than that of the other fusion proteins).

We did not test for glial expression, as it was not directly related to the question addressed in this work.

(2) In Figure 2C the authors show that DNT-2 upregulation leads to an increase in TH levels using q-RT-PCR from whole heads. However, in Figure 3H they also show that DNT-2 overexpression also causes an increase in the number of TH neurons. It is unclear whether TH RNA increases due to expression/cell or the number of TH neurons in the head.

Figure 3H shows that over-expression of DNT-2 FL increased the number of Dcp1+ apoptotic cells in the brain, but not significantly (p=0.0939). The ability of full-length neurotrophins to induce apoptosis and cleaved neurotrophins promote cell survival is well documented in mammals. We had previously shown that DNT-2 is naturally cleaved, and that over-expression of DNT-2 does not induce apoptosis in the various contexts tested before (McIlroy et al 2013 Nature Neuroscience; Foldi et al 2017 J Cell Biol; Ulian-Benitez et al 2017 PLoS Genetics). Similarly, throughout this work we did not find DNT-2FL to induce apoptosis.

Instead, in Figure 3G we show that over-expression of DNT-2FL causes a mild yet statistically significant increase in the number of TH+ cells. This is an important finding that supports the plastic regulation of PAM cell number. We thank the Reviewer for highlighting this point, as we had forgotten to add the significance star in the graph. In this context, we cannot rule out the possibility that the increase in TH mRNA observed when we over-express DNT-2FL could not be due to an increase in cell number instead. Unfortunately, it is not possible for us to separate these two processes at this time. Either way, the result would still be the same: an increase in dopamine production when DNT-2 levels rise.

(3) DNT-2 is also known as Spz5 and has been shown to activate Toll-6 receptors in glia (McLaughlin et al., 2019), resulting in the phagocytosis of apoptotic neurons. In addition, the knockdown of DNT-2/Spz5 throughout development causes an increase in apoptotic debris in the brain, which can lead to neurodegeneration. Indeed Figure 3H shows that an adult-specific knockdown of DNT-2 using DNT2-GAL4 causes an increase in Dcp1 signal in many neurons and not just TH neurons.

Indeed, we did find Dcp1+ cells in TH-negative cells too (although not widely throughout the brain). This is not surprising, as DNT-2 neurons have large arborisations that can reach a wide range of targets; DNT-2 is secreted, and could reach beyond its immediate targets; Toll-6 is expressed in a vast number of cells in the brain; DNT-2 can bind promiscuously at least also Toll-7 and other Keks, which are also expressed in the adult brain (Foldi et al 2017 J Cell Biology; Ulian-Benitez et al 2017 PLoS Genetics; Li et al 2020 eLife). Together with the findings by McLaughlin et al 2019, our findings further support the notion that DNT-2 is a neuroprotective factor in the adult brain. It will be interesting to find out what other neuron types DNT-2 maintains.

We would like to thank Reviewer 1 for their positive comments on our work and their interesting and valuable feedback.

Reviewer #2 (Public review):

This paper examines how structural plasticity in neural circuits, particularly in dopaminergic systems, is regulated by Drosophila neurotrophin-2 (DNT-2) and its receptors, Toll-6 and Kek-6. The authors show that these molecules are critical for modulating circuit structure and dopaminergic neuron survival, synaptogenesis, and connectivity. They show that loss of DNT-2 or Toll-6 function leads to loss of dopaminergic neurons, dendritic arborization, and synaptic impairment, whereas overexpression of DNT-2 increases dendritic complexity and synaptogenesis. In addition, DNT-2 and Toll-6 modulate dopamine-dependent behaviors, including locomotion and long-term memory, suggesting a link between DNT-2 signaling, structural plasticity, and behavior.

A major strength of this study is the impressive cellular resolution achieved. By focusing on specific dopaminergic neurons, such as the PAM and PPL1 clusters, and using a range of molecular markers, the authors were able to clearly visualize intricate details of synapse formation, dendritic complexity, and axonal targeting within defined circuits. Given the critical role of dopaminergic pathways in learning and memory, this approach provides a good opportunity to explore the role of DNT-2, Toll-6, and Kek-6 in experience-dependent structural plasticity. However, despite the promise in the abstract and introduction of the paper, the study falls short of establishing a direct causal link between neurotrophin signaling and experience-induced plasticity.

Simply put, this study does not provide strong evidence that experience-induced structural plasticity requires DNT-2 signaling. To support this idea, it would be necessary to observe experience-induced structural changes and demonstrate that downregulation of DNT-2 signaling prevents these changes. The closest attempt to address this in this study was the artificial activation of DNT-2 neurons using TrpA1, which resulted in overgrowth of axonal arbors and an increase in synaptic sites in both DNT-2 and PAM neurons. However, this activation method is quite artificial, and the authors did not test whether the observed structural changes were dependent on DNT-2 signaling. Although they also showed that overexpression of DNT-2FL in DNT-2 neurons promotes synaptogenesis, this phenotype was not fully consistent with the TrpA1 activation results (Figures 5C and D).

In conclusion, this study demonstrates that DNT-2 and its receptors play a role in regulating the structure of dopaminergic circuits in the adult fly brain. However, it does not provide convincing evidence for a causal link between DNT-2 signaling and experience-dependent structural plasticity within these circuits.

We would like to thank Reviewer 2 for their very positive assessment of our approach to investigate structural circuit plasticity. We are delighted that this Reviewer found our cellular resolution impressive. We are also very pleased that Reviewer 2 found that our work demonstrates that DNT-2 and its receptors regulate the structure of dopaminergic circuits in the adult fly brain. This is already a very important finding that contributes to demonstrating that, rather than being hardwired, the adult fly brain is plastic, like the mammalian brain.

We are very pleased that this Reviewer acknowledges that this work provides a good opportunity to explore the role of DNT-2, Toll-6, and Kek-6 in experience-dependent structural plasticity. We provide a molecular mechanism and proof of principle, and we demonstrate a direct link between the function of DNT-2 and its receptors in circuit plasticity, and a suggestive link to neuronal activity. Finding out the direct link to lived experience is a big task, beyond the scope of this manuscript, and we will be testing this with future projects. Nevertheless, it is important to place our findings within this context, as it opens opportunities for discovery by the neuroscience community.

We would like to thank Reviewer 2 for the positive and thoughtful evaluation of our work, and for their feedback.

Reviewer #3 (Public review):

Summary:

The authors used the model organism Drosophila melanogaster to show that the neurotrophin Toll-6 and its ligands, DNT-2 and kek-6, play a role in maintaining the number of dopaminergic neurons and modulating their synaptic connectivity. This supports previous findings on the structural plasticity of dopaminergic neurons and suggests a molecular mechanism underlying this plasticity.

Strengths:

The experiments are overall very well designed and conclusive. Methods are in general state-of-the-art, the sample sizes are sufficient, the statistical analyses are sound, and all necessary controls are in place. The data interpretation is straightforward, and the relevant literature is taken into consideration. Overall, the manuscript is solid and presents novel, interesting, and important findings.

We are delighted that Reviewer 3 found our work solid, novel, interesting and with important findings. We are also very pleased that this Reviewer found that all necessary controls have been carried out.

Weaknesses:

There are three technical weaknesses that could perhaps be improved.

First, the model of reciprocal, inhibitory feedback loops (Figure 2F) is speculative. On the one hand, glutamate can act in flies as an excitatory or inhibitory transmitter (line 157), and either situation can be the case here. On the other hand, it is not clear how an increase or decrease in cAMP level translates into transmitter release. One can only conclude that two types of neurons potentially influence each other.

Thank you for pointing out that glutamate can be inhibitory. In mammals, the neurotrophin BDNF has an important function in glutamatergic synapses, thus we were intrigued by a potential evolutionary conservation. Our evidence that DNT-2A neurons could be excitatory is indirect, yet supportive: exciting DNT-2 neurons with optogenetics resulted in an increase in GCaMP in PAMs (data not shown); over-expression of DNT-2 in DNT-2 neurons increased TH mRNA levels; optogenetic activation of DNT-2 neurons results in the Dop2R-dependent downregulation of cAMP levels in DNT-2 neurons. Dop2R signals in response to dopamine, which would be released only if dopaminergic neurons had been excited. Accordingly, glutamate released from DNT-2 neurons would have been rather unlikely to inhibit DANs.

cAMP is a second messenger that enables the activation of PKA. PKA phosphorylates many target proteins, amongst which are various channels. This includes the voltage gated calcium channels located at the synapse, whose phosphorylation increases their opening probability. Thus, a rise in cAMP could facilitate neurotransmitter release, and a downregulation would have the opposite effect. Other targets of PKA include CREB, leading to changes in gene expression. Conceivably, a decrease in PKA activity could result in the downregulation of DNT-2 expression in DNT-2 neurons. This negative feedback loop would restore the homeostatic relationship between DNT-2 and dopamine levels.

Our data indeed demonstrate that DNT-2 and PAM neurons influence each other, not potentially, but really. We have provided data that: DNT-2 and PAMs are connected through circuitry; that the DNT-2 receptors Toll-6 and kek-6 are expressed in DANs, including in PAMs; that alterations in the levels of DNT-2 (both loss and gain of function) and loss of function for the DNT-2 receptors Toll-6 and Kek-6 alter PAM cell number, alter PAM dendritic complexity and alter synaptogenesis in PAMs; alterations in the levels of DNT-2, Toll-6 and kek-6 in adult flies alters dopamine dependent behaviours of climbing, locomotion in an arena and learning and long-term memory. These data firmly demonstrate that the two neuron types DNT-2 and PAMs influence each other.

We have also shown that over-expression of DNT-2 in DNT-2 neurons increases TH mRNA levels, whereas activation of DNT-2 neurons decreases cAMP levels in DNT-2 neurons in a dopamine/Dop2R-dependent manner. These data show a functional interaction between DNT-2 and PAM neurons.

Second, the quantification of bouton volumes (no y-axis label in Figure 5 C and D!) and dendrite complexity are not convincingly laid out. Here, the reader expects fine-grained anatomical characterizations of the structures under investigation, and a method to precisely quantify the lengths and branching patterns of individual dendritic arborizations as well as the volume of individual axonal boutons.

Figure 5C, D do contain Y-axis labels, all our graphs in main manuscript and in supplementary files contain Y-axis labels.

In fact, we did use a method to precisely quantify the lengths and branching patterns of individual dendritic arborisations, volume of individual boutons and bouton counting. These analyses were carried out using Imaris software. For dendritic branching patterns, the “Filament Autodetect” function was used. Here, dendrites were analysed by tracing semi-automatically each dendrite branch (ie manual correction of segmentation errors) to reconstruct the segmented dendrite in volume. From this segmented dendrite, Imaris provides measurements of total dendrite volume, number and length of dendrite branches, terminal points, etc. For bouton size and number, we used the Imaris “Spot” function. Here, a threshold is set to exclude small dots (eg of background) that do not correspond to synapses/boutons. All samples and genotypes are treated with the same threshold, thus the analysis is objective and large sample sizes can be analysed effectively. We have already provided a description of the use of Imaris in the methods section.

Third, Figure 1C shows two neurons with the goal of demonstrating between-neuron variability. It is not convincingly demonstrated that the two neurons are actually of the very same type of neuron in different flies or two completely different neurons.

We thank Reviewer 3 for raising this interesting point. It is not possible to prove which of the four DNT-2A neurons per hemibrain, which we visualised with DNT-2>MCFO, were the same neurons in every individual brain we looked at. This is because in every brain we have looked at, the soma of the neurons were not located in exactly the same location. Furthermore, the arborisation patterns are also different and unique, for each individual brain. Thus, there is natural variability in the position of the soma and in the arborisation patterns. Such variability presumably results from the combination of developmental and activity-dependent plasticity.

We would like to thank Reviewer 3 for the very positive evaluation of our work and the interesting and valuable feedback.

This was a good necessary quote to input as it sort of clears the air and sets a different perspective for me being the reader in the sense that the players wanna play and do their job instead of not playing. Although it would have been smart to take him out I feel as if this is the reality of the injury.

No captain spells a very bad time

that took a turn

Uhh this reminds me of that racist stereotype that black people are violent. Yikes

In-human, creepy description of black people...yikes

oh, um, that escalated quickly.

could this mean the captian or the actual ship itself?

a lot of detail about this ship man.....

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

This study evaluates whether species can shift geographically, temporally, or both ways in response to climate change. It also teases out the relative importance of geographic context, temperature variability, and functional traits in predicting the shifts. The study system is large occurrence datasets for dragonflies and damselflies split between two time periods and two continents. Results indicate that more species exhibited both shifts than one or the other or neither, and that geographic context and temp variability were more influential than traits. The results have implications for future analyses (e.g. incorporating habitat availability) and for choosing winner and loser species under climate change. The methodology would be useful for other taxa and study regions with strong community/citizen science and extensive occurrence data.

We thank Reviewer 1 for their time and expertise in reviewing our study. The suggestions are very helpful and will improve the quality of our manuscript.

Strengths:

This is an organized and well-written paper that builds on a popular topic and moves it forward. It has the right idea and approach, and the results are useful answers to the predictions and for conservation planning (i.e. identifying climate winners and losers). There is technical proficiency and analytical rigor driven by an understanding of the data and its limitations.

We thank Reviewer 1 for this assessment.

Weaknesses:

(1) The habitat classifications (Table S3) are often wrong. "Both" is overused. In North America, for example, Anax junius, Cordulia shurtleffii, Epitheca cynosura, Erythemis simplicicollis, Libellula pulchella, Pachydiplax longipennis, Pantala flavescens, Perithemis tenera, Ischnura posita, the Lestes species, and several Enallagma species are not lotic breeding. These species rarely occur let alone successfully reproduce at lotic sites. Other species are arguably "both", like Rhionaeschna multicolor which is mostly lentic. Not saying this would have altered the conclusions, but it may have exacerbated the weak trait effects.

We thank the reviewer for their expertise on this topic. We obtained these habitat classifications from field guides and trait databases, and we will review our primary sources to clarify the trait classifications. We will also reclassify the species according to the expertise of this reviewer and perform our analysis again. 

(2) The conservative spatial resolution (100 x 100 km) limits the analysis to wide- ranging and generalist species. There's no rationale given, so not sure if this was by design or necessity, but it limits the number of analyzable species and potentially changes the inference.

It is really helpful to have the opportunity to contextualize study design decisions like this one, and we thank the reviewer for the query. Sampling intensity is always a meaningful issue in research conducted at this scale, and we addressed it head-on in this work.

Very small quadrats covering massive geographical areas will be critically and increasingly afflicted by sampling weaknesses, as well as creating a potentially large problem with pseudoreplication. There is no simple solution to this problem. It would be possible to create interpolated predictions of species’ distributions using Species Distribution Models, Joint Species Distribution Models, or various kinds of Occupancy Models. None of these approaches then leads to analyses that rely on directly observed patterns. Instead, they are extrapolations, and those extrapolations typically fail when tested, (for example, papers by Lee-Yaw demonstrate that it is rare for SDMs to predict things well; occupancy models often perform less well than SDMs and do not capture how things change over time - Briscoe et al. 2021, Global Change Biology). The result of employing such techniques would certainly be to make all conclusions speculative, rather than directly observable. 

Rather than employing extrapolative models, we relied on transparent techniques that are used successfully in the core macroecology literature that address spatial variation in sampling explicitly and simply. Moreover, we constructed extensive null models that show that range and phenology changes, respectively, are contrary to expectations that arise from sampling difference. 100km quadrats make for a reasonable “middle-ground” in terms of the effects of sampling, and we will add a reference to the methods section to clarify this.

(3) The objective includes a prediction about generalists vs specialists (L99-103) yet there is no further mention of this dichotomy in the abstract, methods, results, or discussion.

Thank you for pointing this out - it is an editing error that should have been resolved prior to submission. We will replace the terms specialist and generalist with specific predictions based on traits.

(4) Key references were overlooked or dismissed, like in the new edition of Dragonflies & Damselflies model organisms book, especially chapters 24 and 27.

We thank Reviewer 1 for making us aware of this excellent reference. We will review this text and include it as a reference, in addition to other references recommended by Reviewer 1 and other reviewers.

Reviewer #2 (Public review):

Summary:

This paper explores a highly interesting question regarding how species migration success relates to phenology shifts, and it finds a positive relationship. The findings are significant, and the strength of the evidence is solid. However, there are substantial issues with the writing, presentation, and analyses that need to be addressed. First, I disagree with the conclusion that species that don't migrate are "losers" - some species might not migrate simply because they have broad climatic niches and are less sensitive to climate change. Second, the results concerning species' southern range limits could provide valuable insights. These could be used to assess whether sampling bias has influenced the results. If species are truly migrating, we should observe northward shifts in their southern range limits. However, if this is an artifact of increased sampling over time, we would expect broader distributions both north and south. Finally, Figure 1 is missed panel B, which needs to be addressed.

We thank Reviewer 2 for their time and expertise in reviewing our study.

It is possible that some species with broad niches may not need to migrate, although in general failing to move with climate change is considered an indicator of “climate debt”, signaling that a species may be of concern for conservation (ex. Duchenne et al. 2021, Ecology Letters). We will revise the discussion to acknowledge potential differences in outcomes.

We used null models to test whether our results regarding range shifts were robust, and if they varied due to increased sampling over time. We found that observed northern range limit shifts are not consistent with expectations derived from changes in sampling intensity (Figure S1, S2). 

We thank Reviewer 2 for pointing out this error in Figure 1. This conceptual figure was a challenge to construct, as it must illustrate how phenology and range shifts can occur simultaneously or uniquely to enable a hypothetic odonate to track its thermal niche over time. In a previous version of the figure, we had a second panel and we failed to remove the reference to that panel when we simplified the figure. 

Reviewer #3 (Public review):

Summary:

In their article "Range geographies, not functional traits, explain convergent range and phenology shifts under climate change," the authors rigorously investigate the temporal shifts in odonate species and their potential predictors. Specifically, they examine whether species shift their geographic ranges poleward or alter their phenology to avoid extreme conditions. Leveraging opportunistic observations of European and North American odonates, they find that species showing significant range shifts also exhibited earlier phenological shifts. Considering a broad range of potential predictors, their results reveal that geographical factors, but not functional traits, are associated with these shifts.

We thank Reviewer 3 for their expertise and the time they spent reviewing our study. Their suggestions are very helpful and will improve the quality of our manuscript.

Strengths:

The article addresses an important topic in ecology and conservation that is particularly timely in the face of reports of substantial insect declines in North America and Europe over the past decades. Through data integration the authors leverage the rich natural history record for odonates, broadening the taxonomic scope of analyses of temporal trends in phenology and distribution to this taxon. The combination of phenological and range shifts in one framework presents an elegant way to reconcile previous findings improving our understanding of the drivers of biodiversity loss.

We thank Reviewer 3 for this assessment.

Weaknesses:

The introduction and discussion of the article would benefit from a stronger contextualization of recent studies on biological responses to climate change and the underpinning mechanism.

The presentation of the results (particularly in figures) should be improved to address the integrative character of the work and help readers extract the main results. While the writing of the article is generally good, particularly the captions and results contain many inconsistencies and lack important detail. With the multitude of the relationships that were tested (the influence of traits) the article needs more coherence.

We thank Reviewer 3 for these suggestions. We will revise the introduction and discussion to better contextualize species’ responses to climate change and the mechanisms behind them. We will carefully review all figures and captions, and we will make changes to improve the clarity of the text and the presentation of results.

this is too long

Author response:

The following is the authors’ response to the original reviews.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

This manuscript from So et al. describes what is suggested to be an improved protocol for single-nuclei RNA sequencing (snRNA-seq) of adipose tissue. The authors provide evidence that modifications to the existing protocols result in better RNA quality and nuclei integrity than previously observed, with ultimately greater coverage of the transcriptome upon sequencing. Using the modified protocol, the authors compare the cellular landscape of murine inguinal and perigonadal white adipose tissue (WAT) depots harvested from animals fed a standard chow diet (lean mice) or those fed a high-fat diet (mice with obesity). 

Strengths: 

Overall, the manuscript is well-written, and the data are clearly presented. The strengths of the manuscript rest in the description of an improved protocol for snRNA-seq analysis. This should be valuable for the growing number of investigators in the field of adipose tissue biology that are utilizing snRNA-seq technology, as well as those other fields attempting similar experiments with tissues possessing high levels of RNAse activity. 

Moreover, the study makes some notable observations that provide the foundation for future investigation. One observation is the correlation between nuclei size and cell size, allowing for the transcriptomes of relatively hypertrophic adipocytes in perigonadal WAT to be examined. Another notable observation is the identification of an adipocyte subcluster (Ad6) that appears "stressed" or dysfunctional and likely localizes to crown-like inflammatory structures where proinflammatory immune cells reside. 

Weaknesses:  

Analogous studies have been reported in the literature, including a notable study from Savari et al. (Cell Metabolism). This somewhat diminishes the novelty of some of the biological findings presented here. Moreover, a direct comparison of the transcriptomic data derived from the new vs. existing protocols (i.e. fully executed side by side) was not presented. As such, the true benefit of the protocol modifications cannot be fully understood. 

We agree with the reviewer’s comment on the limitations of our study. Following the reviewer's suggestion, we performed a new analysis by integrating our data with those from the study by Emont et al. Please refer to the Recommendation for authors section below for further details.

Reviewer #2 (Public Review):

Summary: 

In the present manuscript So et al utilize single-nucleus RNA sequencing to characterize cell populations in lean and obese adipose tissues. 

Strengths: 

The authors utilize a modified nuclear isolation protocol incorporating VRC that results in higherquality sequencing reads compared with previous studies. 

Weaknesses:  

The use of VRC to enhance snRNA-seq has been previously published in other tissues. The snRNA-seq snRNA-seq data sets presented in this manuscript, when compared with numerous previously published single-cell analyses of adipose tissue, do not represent a significant scientific advance. 

Figure 1-3: The snRNA-seq data obtained by the authors using their enhanced protocol does not represent a significant improvement in cell profiling for the majority of the highlighted cell types including APCs, macrophages, and lymphocytes. These cell populations have been extensively characterized by cytoplasmic scRNA-seq which can achieve sufficient sequencing depth, and thus this study does not contribute meaningful additional insight into these cell types. The authors note an increase in the number of rare endothelial cell types recovered, however this is not translated into any kind of functional analysis of these populations. 

We acknowledge the reviewer's comments on the limitations of our study, particularly the lack of extension of our snRNA-seq data into functional studies of new biological processes. However, this manuscript has been submitted as a Tools and Resources article. As an article of this type, we provide detailed information on our snRNA-seq methods and present a valuable resource of high-quality mouse adipose tissue snRNA-seq data. In addition, we demonstrate that our improved method offers novel biological insights, including the identification of subpopulations of adipocytes categorized by size and functionality. We believe this study offers powerful tools and significant value to the research community.

Figure 4: The authors did not provide any evidence that the relative fluorescent brightness of GFP and mCherry is a direct measure of the nuclear size, and the nuclear size is only a moderate correlation with the cell size. Thus sorting the nuclei based on GFP/mCherry brightness is not a great proxy for adipocyte diameter. Furthermore, no meaningful insights are provided about the functional significance of the reported transcriptional differences between small and large adipocyte nuclei. 

To address the reviewer's point, we analyzed the Pearson correlation coefficient for nucleus size vs. adipocyte size and found R = 0.85, indicating a strong positive correlation. In addition, we performed a new experiment to determine the correlation between nuclear GFP intensity and adipocyte nucleus size, finding a strong correlation with R = 0.91. These results suggest that nuclear GFP intensity can be a strong proxy for adipocyte size. Furthermore, we performed gene ontology analysis on genes differentially regulated between large and small adipocyte nuclei. We found that large adipocytes promote processes involved in insulin response, vascularization and DNA repair, while inhibiting processes related to cell migration, metabolism and the cytoskeleton. We have added these new data as Figure 4E, S6E, S6G, and S6H (page 11)

Figure 5-6: The Ad6 population is highly transcriptionally analogous to the mAd3 population from Emont et al, and is thus not a novel finding. Furthermore, in the present data set, the authors conclude that Ad6 are likely stressed/dying hypertrophic adipocytes with a global loss of gene expression, which is a well-documented finding in eWAT > iWAT, for which the snRNA-seq reported in the present manuscript does not provide any novel scientific insight. 

As the reviewer pointed out, a new analysis integrating our data with the previous study found that Ad3 from our study is comparable to mAd3 from Emont et al. in gene expression profiles. However, significant discrepancies in population size and changes in response to obesity were observed, likely due to differences in technical robustness. The dysfunctional cellular state of this population, with compromised RNA content, may have hindered accurate capture in the previous study, while our protocol enabled precise detection. This underscores the importance of our improved snRNA-seq protocol for accurately understanding adipocyte population dynamics. We have revised the manuscript to include new data in Figure S7 (page 14).

Reviewer #3 (Public Review): 

Summary:  

The authors aimed to improve single-nucleus RNA sequencing (snRNA-seq) to address current limitations and challenges with nuclei and RNA isolation quality. They successfully developed a protocol that enhances RNA preservation and yields high-quality snRNA-seq data from multiple tissues, including a challenging model of adipose tissue. They then applied this method to eWAT and iWAT from mice fed either a normal or high-fat diet, exploring depot-specific cellular dynamics and gene expression changes during obesity. Their analysis included subclustering of SVF cells and revealed that obesity promotes a transition in APCs from an early to a committed state and induces a pro-inflammatory phenotype in immune cells, particularly in eWAT. In addition to SVF cells, they discovered six adipocyte subpopulations characterized by a gradient of unique gene expression signatures. Interestingly, a novel subpopulation, termed Ad6, comprised stressed and dying adipocytes with reduced transcriptional activity, primarily found in eWAT of mice on a high-fat diet. Overall, the methodology is sound, the writing is clear, and the conclusions drawn are supported by the data presented. Further research based on these findings could pave the way for potential novel interventions in obesity and metabolic disorders, or for similar studies in other tissues or conditions. 

Strengths:  

• The authors developed a robust snRNA-seq technique that preserves the integrity of the nucleus and RNA across various tissue types, overcoming the challenges of existing methods. 

• They identified adipocyte subpopulations that follow adaptive or pathological trajectories during obesity. 

• The study reveals depot-specific differences in adipose tissues, which could have implications for targeted therapies. 

Weaknesses: 

• The adipose tissues were collected after 10 weeks of high-fat diet treatment, lacking the intermediate time points for identifying early markers or cell populations during the transition from healthy to pathological adipose tissue. 

We agree with the reviewers regarding the limitations of our study. To address the reviewer’s comment, we revised the manuscript to include this in the Discussion section (page 17).  

• The expansion of the Ad6 subpopulation in obese iWAT and gWAT is interesting. The author claims that Ad6 exhibited a substantial increase in eWAT and a moderate rise in iWAT (Figure 4C). However, this adipocyte subpopulation remains the most altered in iWAT upon obesity. Could the authors elaborate on why there is a scarcity of adipocytes with ROS reporter and B2M in obese iWAT?

We observed an increase in the levels of H2DCFA reporter and B2M protein fluorescence in adipocytes from iWAT of HFD-fed mice, although this increase was much less compared to eWAT, as shown in Figure 6B (left panel). These increases in iWAT were not sufficient for most cells to exceed the cutoff values used to determine H2DCFA and B2M positivity in adipocytes during quantitative analysis. We have revised the manuscript to clarify these results (page 13).

• While the study provides extensive data on mouse models, the potential translation of these findings to human obesity remains uncertain. 

To address the reviewer’s point, we expanded our discussion on the differences in adipocyte heterogeneity between mice and humans. We attempted to identify human adipocyte subclusters that resemble the metabolically unhealthy Ad6 adipocytes found in mice in our study; however, we did not find any similar adipocyte types. It has been reported that human adipocyte heterogeneity does not correspond well to that of mouse adipocytes (Emont et al. 2022). In addition, the heterogeneity of human adipocyte populations is not reproducible between different studies (Massier et al. 2023). Interestingly, this inconsistency is unique to adipocytes, as other cell types in adipose tissues display reproducible sub cell types across species and studies (Massier et al. 2023). Our findings indicate that adipocytes may exhibit a unique pathological cellular state with significantly reduced RNA content, which may contribute to the poor consistency in adipocyte heterogeneity in prior studies with suboptimal RNA quality. Therefore, using a robust method to effectively preserve RNA quality may be critical for accurately characterizing adipocyte populations, especially in disease states. It may be important to test in future studies whether our snRNA-seq protocol can identify consistent heterogeneity in adipocyte populations across different species, studies, and individual human subjects. We have revised the manuscript to include this new discussion (page 17).

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors): 

Suggested points to address: 

(1) The authors suggest that their improved protocol for maintaining RNA/nucleus integrity results in a more comprehensive analysis of adipose tissue heterogeneity. The authors compare the quality of their snRNA-seq data to those generated in prior studies (e.g., Savari et al.). What is not clear is whether additional heterogeneity/clusters can be observed due directly to the protocol modifications. A direct head-to-head comparison of the protocols executed in parallel would of course be ideal; however, integrating their new dataset with the corresponding data from Savari et al. could help address this question and help readers understand the benefits of this new protocol vs. existing protocols. 

The data from Savari et al. are of significantly lower quality, likely because they were generated using earlier versions of the 10X Genomics system, and this study lacks iWAT data. To address the reviewer’s point, we instead integrated our data with those from the other study by Emont et al. (2022), which used comparable tissue types and experimental systems. The integrated analysis confirmed the improved representation of all cell types present in adipose tissues in our study, with higher quality metrics such as increased Unique Molecular Identifiers (UMIs) and the number of genes per nucleus. These results indicate that our protocol offers significant advantages in generating a more accurate representation of each cell type and their gene expression profiles. New data are included in Figure S2 (page 7).

(2) The exact frequency of the Ad6 population in eWAT of mice maintained on HFD is a little unclear. From the snRNA-seq data, it appears that roughly 47% of the adipocytes are in this "stressed state." In Figure 6, it appears that greater than 75% of the adipocytes express B2M (Ad6 marker) and greater than 75% of adipocytes are suggested to be devoid of measurable PPARg expression. The latter seems quite high as PPARg expression is essential to maintain the adipocyte phenotype. Is there evidence of de-differentiation amongst them (i.e. acquisition of progenitor cell markers)? Presenting separate UMAPs for the chow vs. HFD state may help visualize the frequency of each adipocyte population in the two states. Inclusion of the stromal/progenitor cells in the visualization may help understand if cells are de-differentiating in obesity as previously postulated by the authors. Related to Point # 1 above, is this population observed in prior studies and at a similar frequency?

To address the reviewer’s point, we analyzed the expression of adipocyte progenitor cell (APC) markers, such as Pdgfra, in the Ad6 population. We did not detect significant expression of APC markers, suggesting that Ad6 does not represent dedifferentiating adipocytes. Instead, they are likely stressed and dying cells characterized by an aberrant state of transcription with a global decline.

When integrating our data with the datasets by Emont et al., we observed an adipocyte population in the previous study, mAd3, comparable to Ad6 in our study, with similar marker gene expression and lower transcript abundance. However, the population size of mAd3 was much smaller than that of Ad6 in our data and did not show consistent population changes during obesity. This discrepancy may be due to different technical robustness; the dysfunctional cellular state of this population, with its severely compromised RNA contents, may have made it difficult to accurately capture using standard protocols in the previous study, while our protocol enabled robust and precise detection. We added new data in Figure S6I and S7 (page 14) and revised the Discussion (page 17).

Additional points  

(1) The authors should be cautious in describing subpopulations as "increasing" or "decreasing" in obesity as the data are presented as proportions of a parent population. A given cell population may be "relatively increased." 

To address the reviewer's point, we revised the manuscript to clarify the "relative" changes in cell populations during obesity in the relevant sections (pages 8, 9, 10, 11, and 15).

(2) The authors should also be cautious in ascribing "function" to adipocyte populations based solely on their expression signatures. Statements such as those in the abstract, "...providing novel insights into the mechanisms orchestrating adipose tissue remodeling during obesity..." should probably be toned down as no such mechanism is truly demonstrated. 

To address the reviewer's point, we revised the manuscript by removing or replacing the indicated terms or phrases with more suitable wording in the appropriate sections (page 2, 10, 12, 14)

Reviewer #3 (Recommendations For The Authors): 

(1) The authors might consider expanding a discussion on the potential implications of their findings, especially the newly identified adipocyte subpopulations and depot-specific differences for human studies. 

To address the reviewer’s point, we attempted to identify human adipocyte subclusters that resembled our dysfunctional Ad6 adipocytes in mice; however, we did not find any similar adipocyte types. It has been reported that human adipocyte heterogeneity does not correspond well to that of mouse adipocytes (Emont et al. 2022). In addition, the heterogeneity of human adipocyte populations is not reproducible between different studies (Massier et al. 2023). Interestingly, this inconsistency is unique to adipocytes, as other cell types in adipose tissues display reproducible sub cell types across species and studies (Massier et al. 2023). Our findings indicate that adipocytes may exhibit a unique pathological cellular state with significantly reduced RNA content, which may contribute to the poor consistency in adipocyte heterogeneity in prior studies with suboptimal RNA quality. Therefore, using a robust method to effectively preserve RNA quality may be critical for accurately characterizing adipocyte populations, especially in disease states. It may be important to test in future studies whether our snRNA-seq protocol can identify consistent heterogeneity in adipocyte populations across different species, studies, and individual human subjects. We have revised the manuscript to include this new discussion (page 17)

(2) typo: "To generate diet-induced obesity models". 

We revised the manuscript to correct it.

Niet-zichtbare inspanning komt niet vaak voor, maar als het gebeurt, gebeurt het redelijk consistent. Dit betekent dat het soms moeilijk is om te zien of iemand wel echt zijn best doet bij een taak of test. Vooral bij kinderen met aanhoudende klachten na een lichte hoofdwond komt dit vaker voor. Meer dan 60% van de kinderen die psychologische tests doen om te kijken of ze ergens voor in aanmerking komen, vertoont tekenen van simulatie (doen alsof ze zieker zijn dan ze werkelijk zijn). In veel gevallen komt dit door de ouders, die hun kinderen aanmoedigen om zieker te lijken (malingering by proxy). Er is echter niet veel onderzoek naar dit onderwerp gedaan, dus we weten er nog niet alles over.

Bij kinderen is het niet goed meedoen aan tests vaak te wijten aan familieomstandigheden, vooral bij kinderen met een lichte hoofdwond. Dit maakt het anders dan bij volwassenen, waar financiële redenen (zoals geld krijgen van verzekeringen) vaak de reden zijn waarom ze niet hun best doen tijdens tests.

Reviewer #3 (Public review):

Summary:

Boffi and colleagues sought to quantify the single-trial, azimuthal information in the dorsal cortex of the inferior colliculus (DCIC), a relatively understudied subnucleus of the auditory midbrain. They accomplished this by using two complementary recording methods while mice passively listened to sounds at different locations: calcium imaging that recorded large neuronal populations but with poor temporal precision and multi-contact electrode arrays that recorded smaller neuronal populations with exact temporal precision. DCIC neurons respond variably, with inconsistent activity to sound onset and complex azimuthal tuning. Some of this variably was explained by ongoing head movements. The authors used a naïve Bayes decoder to probe the azimuthal information contained in the response of DCIC neurons on single trials. The decoder failed to classify sound location better than chance when using the raw population responses but performed significantly better than chance when using the top principal components of the population. Units with the most azimuthal tuning were distributed throughout the DCIC, possessed contralateral bias, and positively correlated responses. Interestingly, inter-trial shuffling decreased decoding performance, indicating that noise correlations contributed to decoder performance. Overall, Boffi and colleagues, quantified the azimuthal information available in the DCIC while mice passively listened to sounds, a first step in evaluating if and how the DCIC could contribute to sound localization.

Strengths:

The authors should be commended for collection of this dataset. When done in isolation (which is typical), calcium imaging and linear array recordings have intrinsic weaknesses. However, those weaknesses are alleviated when done in conjunction - especially when the data is consistent. This data set is extremely rich and will be of use for those interested in auditory midbrain responses to variable sound locations, correlations with head movements, and neural coding.

The DCIC neural responses are complex with variable responses to sound onset, complex azimuthal tuning and large inter-sound interval responses. Nonetheless, the authors do a decent job in wrangling these complex responses: finding non-canonical ways of determining dependence on azimuth and using interpretable decoders to extract information from the population.

Weaknesses:

The decoding results are a bit strange, likely because the population response is quite noisy on any given trial. Raw population responses failed to provide sufficient information concerning azimuth for significant decoding. Importantly, the decoder performed better than chance when certain principal components or top ranked units contributed but did not saturate with the addition of components or top ranked units. So, although there is azimuthal information in the recorded DCIC populations - azimuthal information appears somewhat difficult to extract.

Although necessary given the challenges associated with sampling many conditions with technically difficult recording methods, the limited number of stimulus repeats precludes interpretable characterization of the heterogeneity across the population. Nevertheless, the dataset is public so those interested can explore the diversity of the responses.

The observations from Boffi and colleagues raises the question: what drives neurons in the DCIC to respond? Sound azimuth appears to be a small aspect of the DCIC response. For example, the first 20 principal components which explain roughly 80% of the response variance are insufficient input for the decoder to predict sound azimuth above chance. Furthermore, snout and ear movements correlate with the population response in the DCIC (the ear movements are particularly peculiar given they seem to predict sound presentation). Other movements may be of particular interest to control for (e.g. eye movements are known to interact with IC responses in the primate). These observations, along with reported variance to sound onsets and inter-sound intervals, question the impact of azimuthal information emerging from DCIC responses. This is certainly out of scope for any one singular study to answer, but, hopefully, future work will elucidate the dominant signals in the DCIC population. It may be intuitive that engagement in a sound localization task may push azimuthal signals to the forefront of DCIC response, but azimuthal information could also easily be overtaken by other signals (e.g. movement, learning).

Boffi and colleagues set out to parse the azimuthal information available in the DCIC on a single trial. They largely accomplish this goal and are able to extract this information when allowing the units that contain more information about sound location to contribute to their decoding (e.g., through PCA or decoding on their activity specifically). Interestingly, they also found that positive noise correlations between units with similar azimuthal preferences facilitate this decoding - which is unusual given that this is typically thought to limit information. The dataset will be of value to those interested in the DCIC and to anyone interested in the role of noise correlations in population coding. Although this work is first step into parsing the information available in the DCIC, it remains difficult to interpret if/how this azimuthal information is used in localization behaviors of engaged mice.

Mayors of French coastal towns across the country passed bans on women's head-to-toe beachwear. The debate between human rights associations denouncing the laws and politicians supporting them rages.

Cultural intelligence is something that comes to mind when I think of the number of different ways Japanese people communicate with each other. Depending on what context one is in, there are different words and expressions used exclusively in those contexts. For example, if one is talking to a friend you would use terms like "I", "Hello", "Sorry", and more in casual ways. However, they'd never use such terms with a Boss, always opting with formal speech. As a matter of fact, there is something called "Business Japanese" which is its own thing. I find it interesting that in English, when we switch from casual to formal speech, the differences are not as prominent in Japanese (I think atleast). For example, there's no other way in English you'd say "I", but there are three in Japanese at the top of my head.

Reviewer #1 (Public review):

Summary:

The planarian flatworm Schmidtea mediterranea is widely used as a model system for regeneration because of its remarkable ability to regenerate its entire body plan from very small fragments of tissue, including the complete and rapid regeneration of the CNS. Prior to this study, analysis of CNS regeneration in planaria has mostly been performed on a gross anatomical level. Despite its simplicity compared to vertebrates, the CNS of many invertebrates, including planaria, is nonetheless complex, intricate, and densely packed. Some invertebrate models allow the visualization of individual cellular components of the CNS using transgenic techniques. Until transgenesis becomes commonplace in planaria, the visualization and analysis of detailed CNS anatomy must rely on alternate approaches in order to capitalize on the immense promise of this system as a model for CNS regeneration. Another challenge for the study of the CNS more broadly is how to perform imaging of a complete CNS on a reasonable timescale such that multiple individuals per experimental condition can be imaged.

Strengths:

In this report, Lu et al. describe a careful and detailed analysis of the planarian neuroanatomy and musculature in both the homeostatic and regenerating contexts. To improve the effective resolution of their imaging, the authors optimized a tissue expansion protocol for planaria. Imaging was performed by light sheet microscopy, and the resulting optical sections were tiled to reconstruct whole worms. Labelled tissues and cells were then segmented to allow quantification of neurons and muscle fibers, as well as all cells in individual worms using a DNA dye. The resulting workflow can produce highly detailed and quantifiable 3D reconstructions at a rate that is fast enough to allow the analysis of large numbers of animals.

Weaknesses:

Lu et al. use their workflow to visualize RNA expression of five enzymes that are each involved in the biosynthetic pathway of different neurotransmitters/modulators, namely chat (cholinergeric), gad (GABAergic), tbh (octopaminergic), th (dopaminergic), and tph (serotonergic). In this way, they generate an anatomical atlas of neurons that produce these molecules. Collectively these markers are referred to as the "neuronpool." They overstate when they write, "The combination of these five types of neurons constitutes a neuron pool that enables the labeling of all neurons throughout the entire body." This statement does not accurately represent the state of our knowledge about the diversity of neurons in S. mediterranea. There are several lines of evidence that support the presence of glutamatergic and glycinergic neurons, including the following. The glutamate receptor agonists NMDA and AMPA both produce seizure-like behaviors in S. mediterranea that are blocked by the application of glutamate receptor antagonists MK-801 and DNQX (which antagonize NMDA and AMPA glutamate receptors, respectively; Rawls et al., 2009). scRNA-Seq data indicates that neurons in S. mediterranea express a vesicular glutamate transporter, a kainite-type glutamate receptor, a glycine receptor, and a glycine transporter (Brunet Avalos and Sprecher, 2021; Wyss et al., 2022). Two AMPA glutamate receptors, GluR1 and GluR2, are known to be expressed in the CNS of another planarian species, D. japonica (Cebria et al., 2002). Likewise, there is abundant evidence for the presence of peptidergic neurons in S. mediterranea (Collins et al., 2010; Fraguas et al., 2012; Ong et al., 2016; Wyss et al., 2022; among others) and in D. japonica (Shimoyama et al., 2016). For these reasons, the authors should not assume that all neurons can be assayed using the five markers that they selected. The situation is made more complex by the fact that many neurons in S. mediterranea appear to produce more than one neurotransmitter/modulator/peptide (Brunet Avalos and Sprecher, 2021; Wyss et al., 2022), which is common among animals (Vaaga et al., 2014; Brunet Avalos and Sprecher, 2021). However the published literature indicates that there are substantial populations of glutamatergic, glycinergic, and peptidergic neurons in S. mediterranea that do not produce other classes of neurotransmission molecule (Brunet Avalos and Sprecher, 2021; Wyss et al., 2022). Thus it seems likely that the neuronpool will miss many neurons that only produce glutamate, glycine or a neuropeptide.

The authors use their technique to image the neural network of the CNS using antibodies raised vs. Arrestin, Synaptotagmin, and phospho-Ser/Thr. They document examples of both contralateral and ipsilateral projections from the eyes to the brain in the optic chiasma (Figure 1C-F). These data all seem to be drawn from a single animal in which there appears to be a greater than normal number of nerve fiber defasciculatations. It isn't clear how well their technique works for fibers that remain within a nerve tract or the brain. The markers used to image neural networks are broadly expressed, and it's possible that most nerve fibers are too densely packed (even after expansion) to allow for image segmentation. The authors also show a close association between estrella-positive glial cells and nerve fibers in the optic chiasma.

The authors count all cell types, neuron pool neurons, and neurons of each class assayed. They find that the cell number to body volume ratio remains stable during homeostasis (Figure S3C), and that the brain volume steadily increases with increasing body volume (Figure S3E). They also observe that the proportion of neurons to total body cells is higher in worms 2-6 mm in length than in worms 7-9 mm in length (Figure 2D, S3F). They find that the rate at which four classes of neurons (GABAergic, octopaminergic, dopaminergic, serotonergic) increase relative to the total body cell number is constant (Figure S3G-J). They write: "Since the pattern of cholinergic neurons is the major cell population in the brain, these results suggest that the above observation of the non-linear dynamics between neurons and cell numbers is likely from the cholinergic neurons." This conclusion should not be reached without first directly counting the number of cholinergic neurons and total body cells. Given that glutamatergic, glycinergic, and peptidergic neurons were not counted, it also remains possible that the non-linear dynamics are due (in part or in whole) to one or more of these populations.

The authors next assayed the production of different classes of neurons in regenerating post-pharyngeal tail fragments. At 14 dpa, they find significantly reduced proportions of octopaminergic, GABAergic, and dopaminergic neurons in these regenerated animals (Figure 3K). Given that these three neuron classes are primarily found in the brain region (Figure S2A), this suggests that the brains of these animals may not have finished regenerating by 14 dpa.

The authors next applied their imaging and segmentation technique to the musculature using the 6G10 antibody. They find that the body wall muscle fibers from the dorsal and ventral body walls integrate differently at the anterior end (to form a cobweb-like arrangement) compared to the posterior end (Figure 4I). They knock down β-catenin in regenerating head anterior fragments and find that the resulting double-headed worms produce a cobweb-like arrangement at both ends (Figure 4J).

RNAi knockdown of inr-1 is known to produce mobility defects and have elongated bodies relative to control animals (Lei et al., 2016; Figure S6A). To understand the nature of these defects, the authors image the muscle of inr-1 RNAi animals and find increased circular body wall muscle fibers on both dorsal and ventral sides, while β-catenin RNAi animals have increased longitudinal muscle fibers on the dorsal side (Figure 6C). The inr-1 RNAi animals also have reduced cholinergic neurons (Figure S6B), and ectopic expression of the GABAergic marker gad in the periphery (Figure S6B). Lastly the authors simultaneously image muscle and estrella-positive glia and find that these glia lack their typically elaborate stellate morphology in inr-1 RNAi animals (Figure 6E, S6E-K). The combination of this muscle, neuronal, and glial defects may account for the mobility defects observed in inr-1 RNAi worms.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors apply tissue expansion and tiling light sheet microscopy to study allometric growth and regeneration in planaria. They developed image analysis pipelines to help them quantify different neuronal subtypes and muscles in planaria of different sizes and during regeneration. Among the strengths of this work, the authors provide beautiful images that show the potential of the approaches they are taking and their ability to quantify specific cell types in relatively large numbers of whole animal samples. Many of their findings confirm previous results in the literature, which helps validate the techniques and pipelines they have applied here. Among their new observations, they find that the body wall muscles at the anterior and posterior poles of the worm are organized differently and show that the muscle pattern in the posterior head of beta-catenin RNAi worms resembles the anterior muscle pattern. They also show that glial cell processes appear to be altered in beta-catenin or insulin receptor-1 RNAi worms. Weaknesses include some over-interpretation of the data and lack of consideration or citation of relevant previous literature, as discussed below.

Strengths:

This method of tissue expansion will be useful for researchers interested in studying this experimental animal. The authors provide high-quality images that show the utility of this technique. Their analysis pipeline permits them to quantify cell types in relatively large numbers of whole animal samples.

The authors provide convincing data on changes in total neurons and neuronal sub-types in different-sized planaria. They report differences in body wall muscle pattern between the anterior and posterior poles of the planaria, and that these differences are lost when a posterior head forms in beta-catenin RNAi planaria. They also find that glial cell projections are reduced in insulin receptor-1 RNAi planaria.

Weaknesses:

The work would have been strengthened by a more careful consideration of previous literature. Many papers directly relevant to this work were not cited. Such omissions do the authors a disservice because in some cases, they fail to consider relevant information that impacts the choice of reagents they have used or the conclusions they are drawing.

For example, when describing the antibody they use to label muscles (monoclonal 6G10), they do not cite the paper that generated this reagent (Ross et al PMCID: PMC4307677), and instead, one of the papers they do cite (Cebria 2016) that does not mention this antibody. Ross et al reported that 6G10 does not label all body wall muscles equivalently, but rather "predominantly labels circular and diagonal fibers" (which is apparent in Figure S5A-D of the manuscript being reviewed here). For this reason, the authors of the paper showing different body wall muscle populations play different roles in body patterning (Scimone et al 2017, PMCID: PMC6263039, also not cited in this paper) used this monoclonal in combination with a polyclonal antibody to label all body wall muscle types. Because their "pan-muscle" reagent does not label all muscle types equivalently, it calls into question their quantification of the different body wall muscle populations throughout the manuscript. It does not help matters that their initial description of the body wall muscle types fails to mention the layer of thin (inner) longitudinal muscles between the circular and diagonal muscles (Cebria 2016 and citations therein).

Ipsilateral and contralateral projections of the visual axons were beautifully shown by dye-tracing experiments (Okamoto et al 2005, PMID: 15930826). This paper should be cited when the authors report that they are corroborating the existence of ipsilateral and contralateral projections.

The proportional decrease of neurons with growth in S. mediterranea was shown by counting different cell types in macerated planarians (Baguna and Romero, 1981; https://link.springer.com/article/10.1007/BF00026179) and earlier histological observations cited there. These results have also been validated by single-cell sequencing (Emili et al, bioRxiv 2023, https://www.biorxiv.org/content/10.1101/2023.11.01.565140v). Allometric growth of the planaria tail (the tail is proportionately longer in large vs small planaria) can explain this decrease in animal size. The authors never really discuss allometric growth in a way that would help readers unfamiliar with the system understand this.

In some cases, the authors draw stronger conclusions than their results warrant. The authors claim that they are showing glial-muscle interactions, however, they do not provide any images of triple-stained samples labeling muscle, neurons, and glia, so it is impossible for the reader to judge whether the glial cells are interacting directly with body wall muscles or instead with the well-described submuscular nerve plexus. Their conclusion that neurons are unaffected by beta-cat or inr-1 RNAi based on anti-phospho-Ser/Thr staining (Fig. 6E) is unconvincing. They claim that during regeneration "DV muscles initially regenerate into longitudinal fibers at the anterior tip" (line 373). They provide no evidence for such switching of muscle cell types, so it is unclear why they say this.

The authors show how their automated workflow compares to manual counts using PI-stained specimens (Figure S1T). I may have missed it, but I do not recall seeing a similar ground truth comparison for their muscle fiber counting workflow. I mention this because the segmented image of the posterior muscles in Figure 4I seems to be missing the vast majority of circular fibers visible to the naked eye in the original image.

It is unclear why the abstract says, "We found the rate of neuron cell proliferation tends to lag..." (line 25). The authors did not measure proliferation in this work and neurons do not proliferate in planaria.

It is unclear what readers are to make of the measurements of brain lobe angles. Why is this a useful measurement and what does it tell us?

The authors repeatedly say that this work lets them investigate planarians at the single-cell level, but they don't really make the case that they are seeing things that haven't already been described at the single-cell level using standard confocal microscopy.

When President Richard Nixon created the Council in 1970 and announced its first three members, he described CEQ to the press as "the environmental conscience of the nation." https://www.jstor.org/stable/27551558

In his and many subsequent administrations, Republican as well as Democratic, the CEQ played a central role coordinating environmental policy across the agencies. Trump's nomination of Mary Neumayr to head the CEQ came after the rest of his White House-based political appointees. Though she was at the time considered moderate politically, the Council's work under her leadership focused on circumscribing NEPA's requirements and scope under the guise of "streamlining." https://www.washingtonpost.com/news/energy-environment/wp/2018/06/13/trump-tries-a-more-middle-of-the-road-pick-for-top-white-house-environment-post/

Welcome back and in this demo lesson you're going to be creating an ECS cluster with the Fargate cluster mode and using the container of CATS container that we created together earlier in this section of the course, you're going to deploy this container into your Fargate cluster.

So you're going to get some practical experience of how to deploy a real container into a Fargate cluster.

Now you won't need any cloud formation templates applied to perform this demo because we're going to use the default VPC.

All that you'll need is to be logged in as the IAM admin user inside the management account of the organization and just make sure that you're in the Northern Virginia region.

Once you've confirmed that then just click in Find Services and type ECS and then click to move to the ECS console.

Once you're at the ECS console, step one is to create a Fargate cluster.

So that's the cluster that our container is going to run inside.

So click on clusters, then create cluster.

You'll need to give the cluster a name.

You can put anything you want here, but I recommend using the same as me and I'll be putting all the CATS.

Now Fargate mode requires a VPC.

I'm going to be suggesting that we use the default VPC because that's already configured, remember, to give public IP addresses to anything deployed into the public subnets.

So just to keep it simple and avoid any extra configuration, we'll use the default VPC.

Now it should automatically select all of the subnets within the default VPC, in my case all six.

If yours doesn't, just make sure you select all of the available subnets from this dropdown, but it should do this by default.

Then scroll down and just note how AWS Fargate is already selected and that's the default.

If you wanted to, you could check to use Amazon EC2 instances or external instances using ECS anywhere, but for this demo, we won't be doing that.

Instead, we'll leave everything else as default, scroll down to the bottom and click create.

If this is the first time you're doing this in an AWS account, it's possible that you'll get the error that's shown on screen now.

If you do get this error, then what I would suggest is to wait a few minutes, then go back to the main ECS console, go to cluster again and then create the all the cats cluster again.

So follow exactly the same steps, call the cluster all the cats, make sure that the animals for live default VPC is selected and all those subnets are present, and then click on create.

You should find that the second time that you run this creation process, it works okay.

Now this generally happens because there's an approval process that needs to happen behind the scenes.

So if this is the first time that you're using ECS within this AWS account, then you might get this error.

It's nothing to worry about, just rerun the process and it should create fine the second time.

Once you've followed that process through again, or if it works the first time, then just go ahead and click on the all the cats cluster.

So this is the Fargate based cluster.

It's in an active state, so we're good to deploy things into this cluster.

And we can see that we've got no active services.

If I click on tasks, we can see we've got no active tasks.

There's a tab here, metrics where you can see cloud watch metrics about this cluster.

And again, because this is newly created and it doesn't have any activity, all of this is going to be blank.

For now, that's fine.

What we need to do for this demonstration is create a task definition that will deploy our container, our container of cats container into this Fargate cluster.

To do that, click on task definitions and create a new task definition.

You'll need to pick a name for your task definition.

Go ahead and put container of cats.

And then inside this task definition, the first thing to do set the details of the container for this task.

So under container details under name, go ahead and put container of cats web.

So this is going to be the web container for the container of cats task.

Then next to the name under image URI, you need to point this at the docker image that's going to be used for this container.

So I'm going to go ahead and paste in the URI for my docker image.

So this is the docker image that I created earlier in the course within the EC2 docker demo.

You might have also created your own container image.

You can feel free to use my container image or you can use yours.

If you want to keep things simple, you should go ahead and use mine.

Yours should be the same anyway.

Now just to be careful, this isn't a URL.

This is a URI to point at my docker image.

So it consists of three parts.

First we have docker.io, which is the docker hub.

Then we have my username, so acantral.

And then we have the repository name, which is container of cats.

So if you want to use your own docker image, you need to change both the username and the repository name.

Again, to keep things simple, feel free to use my docker image.

Then scrolling down, we need to make sure that the port mappings are correct.

It should show what's on screen now, so container port 80, TCP.

And then the port name should be the same or similar to what's on screen now.

Don't worry if it's slightly different and the application protocol should be HTTP.

This is controlling the port mapping from the container through to the Fargate IP address.

And I'll talk more about this IP address later on in this demo.

Everything else looks good, so scroll down to the bottom and click on next.

We need to specify some environment details.

So under operating system/architecture, it needs to be linux/x86_64.

Under task size for memory, go ahead and select 1GB and then under CPU, 0.5 vCPU.

That should be enough resources for this simple docker application.

Scroll down and under monitoring and logging, uncheck use log collection.

We won't be needing it for this demo lesson.

That's everything we need to do.

Go ahead and click on next.

This is just an overview of everything that we've configured, so you can scroll down to the bottom and click on create.

And at this point, the task definition has been created successfully.

And this is where you can see all of the details of the task definition.

If you want to see the raw JSON for the task definition itself, you don't need this for the exam, but this is actually what a task definition looks like.

So it contains all of this different information.

What it has got is one or more container definitions.

So this is just JSON.

This is a list of container definitions.

We've only got the one.

And if you're looking at this, you can see where we set the port mapping.

So we're mapping port 80.

You can see where it's got the image URL, which is where it pulls the docker image from.

This is exactly what a normal task and container definition look like.

They can be significantly more complex, but this format is consistent across all task definitions.

Okay, so now it's time to launch a task.

It's time to take the container and task definitions that we've defined and actually run up a container inside ECS using those definitions.

So to do that, click on clusters and then select the all the cats cluster.

Click on tasks and then click on run a new task.

Now, first we need to pick the compute options and we're going to select launch type.

So check that box.

If appropriate for the certification that you're studying for, I'll be talking about the differences between these two in a different lesson.

Once you've clicked on launch type, make sure Fargate is selected in the launch type drop down and latest is selected under platform version.

Then scroll down and we're going to be creating a task.

So make sure that task is selected.

Scroll down again and under family, make sure container of cats is selected.

And then under revision, select latest.

We want to make sure the latest version is used and we'll leave desired tasks at one and task group blank.

Scroll down and expand networking.

Make sure the default VPC is selected and then make sure again that all of the subnets inside the default VPC are present under subnets.

The default is that all of them should be in my case six.

Now the way that this task is going to work is that when the task is run within Fargate, an elastic network interface is going to be created within the default VPC.

And that elastic network interface is going to have a security group.

So we need to make sure that the security group is appropriate and allows us to access our containerized application.

So check the box to say create a new security group and then for security group name and description, use container of cats -sg.

We need to make sure that the rule on this security group is appropriate.

So under type select HTTP and then under source change this to anywhere.

And this will mean that anyone can access this containerized application.

Finally make sure that public IP is turned on.

This is really important because this is how we'll access our containerized application.

Everything else looks good.

We can scroll down to the bottom and click on create.

Now give that a couple of seconds.

It should initially show last status.

So the last status should be set to provisioning and the desired state should be set to running.

So we need to wait for this task provisioning to complete.

So just keep hitting refresh.

You'll see it first change into pending.

Now at this point we need this task to be in a running state before we can continue.

So go ahead and pause the video and wait for both of these states.

So last status and desired status both of those need to be running before we continue.

So pause the video, wait for both of those to change and then once they have you can resume and will continue.

After another refresh the last status should now be running and in green and the desired state should also be running.

So at that point we're good to go.

We can click on the task link below.

We can scroll down and our task has been allocated a private IP version for address in the default VPC and also a public IP version for address also in the default VPC.

So if we copy this public IP into our clipboard and then open a new tab and browse to this IP we'll see our very corporate professional web application.

If it fits, I sits in a container in a container.

So we've taken a Docker image that we created earlier in this section of the course.

We've created a Fargate cluster, created a task definition with a container definition inside and deployed our container image as a container to this Fargate cluster.

So it's a very simple example, but again this scales.

So you could deploy Docker containers which are a lot more complex in what functionality they offer.

In this case it's just an Apache web server loading up a web page but we could deploy any type of web application using the same steps that you've performed in this demo lesson.

So congratulations, you've learned all of the theory that you'll need for the exam and you've taken the steps to implement this theory in practice by deploying a Docker image as a container on an ECS Fargate cluster.

So great job.

At this point all that remains is to tidy up.

So go back to the AWS console.

Just stop this container.

Click on stop.

Click on task definitions and then go into this task definition.

Select this.

Click on actions, deregister and then click on deregister.

Click back on task definitions and make sure there's no results there.

That's good.

Click on clusters.

Click on all the cats.

Delete the cluster.

You'll need to type delete space all the cats and then click on delete to confirm.

And at that point the Fargate cluster has been deleted.

The running container has been stopped.

The task definitions been deleted and our account is back in the same state as when we started.

So at this point you've completed the demo.

You've done great and you've implemented some pretty complex theory.

So you should already have a head start on any exam questions which involve ECS.

We're going to be using ECS a lot more as we move through the course and we're going to be using it in some of the Animals for Life demos as we implement progressively more complex architectures later on in the course.

For now I just wanted to give you the basics but you've done really well if you've implemented this successfully without any issues.

So at this point go ahead, complete this video and when you're ready join me in the next.

Coming back to what I said in a previous annotation about actions getting darker as night comes, this seems to flip that idea on its head a bit when saying "Only at nightfall, aethereal rumours / Revive for a moment a broken Coriolanus". Coriolanus is a Shakespeare character who is notably a bit of an antihero, so these lines seem to say that "aethereal rumors" at nightfall are what temporarily redeem Coriolanus, despite a previous annotation of mine arguing that peoples' actions get darker as the night falls. For Coriolanus, it seems to be the opposite.

This is also interesting when you consider Francis Herbert Bradley's Appearance and Reality where he argues that much of what humans perceive is an illusion, which makes it hard for people to truly connect with each other. This makes me wonder if these "aethereal rumours" are then actually other people and not supernatural beings, but Eliot is referring to them this way to show the true distance between ourselves and the reality of other people.

Beginning this stanza of “What the Thunder Said”, Eliot describes a woman who manipulated her hair, and “fiddled whisper music on those strings”. Interpreting “those strings” as the woman’s own hair we can interpret a curious instance of a woman using her body as an instrument to play music. Of course, we must acknowledge that realistically, one can’t make any substantial sounds with their hair, and thus we can interpret her “whisper music” as imagined, or only perceived by her. In terms of the human body, especially in relation to hair, we can further understand this passage by looking at page 298 of the Visuddhi-Magga. This page discusses the superficiality of beauty and the ego, as it declares that the human body is repulsive. The repulsiveness of the human body is argued, as the Visuddhi Magga reads, “When any part of the body becomes detached, as, for instance, the hair of the head … people are unwilling so much as to touch it”. According to the Visuddhi Magga, humans assign significance and beauty to discardable parts of their body, and when those parts are discarded, humans view them with disgust. When comparing the teachings of the Visuddhi-Magga with the long-haired woman, there seems to be a contrast in appreciation for the human body. While the Visuddhi-Magga argues that the body, especially the hair, is repulsive, the woman is using her own hair as an instrument, something of significance and beauty in and of itself. I believe another important aspect of this analysis lies in the consideration of Eliot’s notion of “conceptual death”. In “The Waste Land” Eliot has challenged the reader’s literal understanding of death, and instead seems to propose the idea that death is a complex and cultural state that cannot be so easily defined. Literally, our hair is dead, but when attached to our body, it becomes a part of a living thing, and thus seems to gain significance through what I argue is “conceptual vitality”. Interpeting the lesson of the Visuddhi-Magga, hair loses its “vitality” when it is cut off, and becomes recognizably repulsive. Though it was always dead, it has lost its significance to the body. I would argue that the woman using her hair as an instrument is an affirmation of the hair’s significance to herself, and thus, a part of her own conceptual vitality.

Here Eliot references the passage from Dracula when Dracula climbs down the side of the wall: “I saw the whole man slowly emerge from the window and begin to crawl down the castle wall over that dreadful abyss, face down with his cloak spreading out around him like great wings” (Stoker, 2), and subsequently Byron’s Dark Tower: “Into that ominous tract which, all agree, // Hides the Dark Tower” (Byron, 14-15). To break this down, the “bats” in “The Waste Land” represent Dracula, a symbol of terror and psychological torment. Through Dracula’s perspective, Lord Byron’s Dark Tower has been inverted. The word “ominous” recalls Eliot’s fascination with Tarot cards and brings to mind the “Tower” tarot card, which, read upright, signifies impending doom and destruction. However, inverted, that unfavorable omen changes its meaning, commonly associated with the denial of the aforementioned doom and destruction. Because of his upside down perspective, Dracula has essentially controlled the inversion of this card. Potentially, this would translate as a voluntary dismissal or rejection of chaos and destruction by the human psyche, specifically, the part of the human psyche that drives fear and terror.

Additionally, a second read of these two lines reveals that the orientation of Dracula in the scene may not actually be as simple as it seems. Eliot uses a rather redundant “downward down,” which is aligned with “upside down” in the next line. Perhaps the double “down” simply serves to emphasize. But, alternatively, it might negate itself, thus the orientation of the bats is actually right-side-up, making the orientation of the towers upside down from a right-side-up perspective, truly hanging from the “air.” Likely, Eliot meant to disorient the reader by confusing the orientation of perspective. In the context of our tarot card, this means the prophecy flips in every permutation of upside down and right-side-up in these lines–an ever changing future. Furthermore, the idea of a turbulent prophecy is nested within the context of the meaning of the card itself–chaos. Thus, Eliot has managed to completely muddle the perspective of the reader, as well as any definition in the image of the future.

Parth’s annotation on this line introduces an interesting interpretation of its origins in Antony and Cleopatra. He identifies that “this line is an imitation of a line we see early on in Antony and Cleopatra—with one change: the word "barge" is changed to a capitalized "Chair" here…Chair might not be referring to a literal chair, which isn't a proper noun—but an organizational position. A "Chair" in a company is an executive position; likewise, a metaphorical Chair in a kingdom may refer to one's supreme status” (Jain). I’d like to expand the scope of the Antony and Cleopatra reference beyond specific lines that Eliot incorporated into “The Waste Land,” now through Parth’s lens of Cleopatra’s status and power within the play, her “Chair” within Antony and Cleopatra, and therefore “The Waste Land” as well. When reading Antony and Cleopatra, I couldn’t help but take note of the many ways in which Cleopatra both adopts the role of the queen in a literal game of chess. In a very broad sense, Cleopatra’s decision to fake her own suicide, to temp Antony with her death, is quite analogous to the physical and strategic features of the queen on a chess board. For example, while Cleopatra plots to win the attention of Antony, she says, “I have nothing Of woman in me: now from head to foot // I am marble-constant” (Shakespeare, V.II). In portraying herself as hard as marble, she renders herself part of a chess set, as they are often made of marble. The image of a chess board is then transferred to the marble as it appears here in “The Waste Land,” further convincing me that Cleopatra is the queen of Eliot’s chess set as it is understood in “A Game of Chess.” Additionally, Cleopatra embodies the characteristics of a chess piece as a powerful strategic asset when used correctly. She even says, “come hither, come! come, come, and take a queen worth many babes and beggars” (Shakespeare, V.II). “Take” is the terminology in a game of chess for the capture of a piece. I believe it’s possible that both Shakespeare and Eliot recognized the parallels between Cleopatra’s actions and the act of sacrificing a piece in the game of chess. However, Cleopatra’s move was in vain, and ultimately, when she sacrifices her life, amounts to nothing. In other words, the power she possessed through her “Chair” is only valuable insofar as it is spent to win the Game of Chess. Meanwhile, the woman in “The Waste Land” also sits dead on her throne, her status reduced, presumably having met a similarly wasteful fate.

This line is lifted from a translation of the Visuddhi-Magga, where a woman adorned in accessories (such that she looks like a goddess) leaves her husband’s house to return home. On her way, she is met by an elder who bestows “saintship” upon her based on her teeth. Physical beauty is in indicator of divinity, but perhaps an erroneous one. He declares, "Was it a woman, or a man, /That passed this way? I cannot tell / But this I know, a set of bones / Is traveling on upon this road."

The ambiguity on gender suggests it is not feminity nor masculinity that constitutes this third creature, this mysterious other whose presence is alluded to but unknown. In the passage, it is a woman, dressed in accessories to look like a goddess, that walks the road. Yet to the elder, gender is irrelevant; all he sees is “a set of bones”. The human identity is thus defined by the physical structures that support us. The bones that prop, the skin that wraps, the muscles that hold – the human being is whittled down into strictly anatomy. The personification of “a set of bones” also evokes a sense of resurrection, where the skeleton - now a symbol of the core of a human being, not the death of one - travels directionlessly on the road. The use of demonstrative pronoun “this” reemphasizes the proximity of the skeleton - this divine -, correlating the road it travels on to the one the speaker (and us) are on.

The focus shifts later in the passage to the vulnerability of bodies in their indiviudal, amputated form. Hair, when detached from the scalp, flies loose and tangled in clumps in the drain or kots on a comb. Nails, clipped or fallen, become trash. Teeth, the most animalistic mechanism that chews and rips and tears, when fallen out, becomes useless and remains, if lucky enough, in a dusty wooden box. In this way all our bodily extensions are accessories – external decor to conceal the throbbing, vulnerable creature that resides within. Hair insulates the head and covers the neck, teeth flank our soft greedy mouths, and nails protect nerve bundles and, by extension, physical touch. What can be perceived outward is a disguise for what lies within, which I suppose must be the soul. While alive, a human’s exterior features can be come detached; joints can loosen, organs can fail, and skin can callous. And in death, organs liquify, hair decomposes, and muscles decay. Yet bones, in their stubborn white glory, remain. They are firmly rooted in the ground, a testament of a human’s existence, a mere indicator of the body it held, the life it contained.

Eliot references bones throughout TWL – they are lost in rats’ alley, they rattle by Sweet Thames, they are in the bottom of sunken ships. Of all the disguises a human wears, (the queens no different form the cadavers in “A Game of Chess”, the dead buried and regrown), at their core they are all bones. Perhaps that is where the truth lies – in that which cannot be decomposed.