she does a great job of describing how peacock's look throughout their development cycle with great vivid detail and using similes.

The imagery of scowling and shaking his head indicate annoyance and frustration at Dana. He doesn't seem to like her answer, but he only mutters about it under his breath. He doesn't care enough to talk to her about it. The imagery of the yellow chalk makes me think that the chalk is old, perhaps that it has been buried in his bag for a long time. He has to dig for it, so he's not well organized. Stevens also doesn't seem to have the motivation or the desire to become organized. He simply doesn't care.

Adam Marshall Dobrin shared a memory.

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These notes have been kept pent up in my head or spread across the memory of the "✓ of david/simple" its more to the point its ... I'm putting together a "hypothesis" on how to get to "lemma" after the initial statement of purpose.

given: i am because before "nand" gates were a thing, I was defacto obviously "him" you can "who" and "hu" all you want UHC is going to ZERO as is GOOG and if you don't believe it, cry me a criver; flowed the sun of all of the one true god's universes.

3 Years Ago

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sorry for the SE grin; I've been waiting years and years to find out what the book of "hiccups and kickboxing" was really about ... #tiscoming

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Adam Marshall Dobrin shared a memory.

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These notes have been kept pent up in my head or spread across the memory of the "✓ of david/simple" its more to the point its ... I'm putting together a "hypothesis" on how to get to "lemma" after the initial statement of purpose.

given: i am because before "nand" gates were a thing, I was defacto obviously "him" you can "who" and "hu" all you want UHC is going to ZERO as is GOOG and if you don't believe it, cry me a criver; flowed the sun of all of the one true god's universes.

3 Years Ago

See Your Memories

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Adam Marshall Dobrin

August 16, 2018  - 

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sorry for the SE grin; I've been waiting years and years to find out what the book of "hiccups and kickboxing" was really about ... #tiscoming

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Since the internalized interlocutor is so often made up from only what one thinks about another person, not their real internal experience, it's easy for the imaginative sort to construct one out of people never met. Oscar Wilde always gave the impression that his funny bits were things he found funny, not jokes told for the amusement of the masses -- at least not on a first-order level, only on that higher-order Freudian etc. etc. level.

This whole piece is fantastic because I could hear it in my head being read in a strange hybrid of Podcast Ad Read Voice and that ad for Powerthirst.

Reviewer #2 (Public Review): 

Porto et al. developed a method to image the force-induced unfolding of twitchin kinase (TwcK) by FRET at the whole organism (C. elegans) level and correlated to its motion. The twitchin kinase contains autoinhibitory domains (NL+CRD) that can be mechanically unwrapped from the kinase, leading to its activation. The authors designed experiments to see whether this mechanically-coupled activation happens or not during the muscle contraction of live C. elegans. To do so, they engineered FRET donors and acceptors (mCFP and mCit) to flanking positions around TwcK. They did so without affecting the auto-inhibitory functions of TwcK. As a control, they flanked a nearby Ig domain with the same FRET pairs. The hypothesis is that under force, the unravelling and stretching of the NL domain from TwcK will lead to FRET decrease. While in the control case, Ig domains can resist mechanical unfolding, and FRET would not change. The authors were able to image the whole organism with NIR-brightfield, mCFP and mCit. Channels simultaneously with reasonable spatial and temporal resolution. Image processing algorithms were developed to correlate the C. elegans motion (curvature along the body of C.elegans) to the fluorescence at corresponding body locations. They found propagating "waves" of curvature from the head to tail of the worm in kymographs of body curvature (as expected) and fluorescence in mCFP, mCit, and FRET channels, which is somewhat unexpected. They found the magnitude of FRET change for the mCit-TwcK-mCFP to be statistically greater than the control mCFP-Ig-mCit, although both exhibited a significant correlation with the worm's body curvature. During the contraction and relaxation cycles of the muscles, the FRET change in the mCit-TwcK-mCFP construct is also greater than that of the control group. The authors contributed the observed FRET changes in mCFP-Ig-mCit to various factors, including imaging and motion artifacts. And therefore, the difference observed between the experiment and control is due to the force-induced unfolding of the NL domain from TwcK. The authors suggested that the force-induced unfolding of autoinhibitory peptide activates the kinase, which may have physiological relevance to be discovered in future studies. 

Strengths: 

1) Traditionally, in vitro characterizations of molecules were performed to infer their biological function, which requires knowledge of their complex physiological environment that may not be available. Direct, in vivo, experimental measurement of mechanically-coupled activation of signalling proteins in this study is crucial to understand their physiologically-relevant function and allows correlation to the function at the organism level. This is a beautiful demonstration relating molecular mechanical events in the context of the system it works in. I also recognize and respect the challenges undertaken by the authors in this research. 

2) The overall idea and design of the experiment are elegant. The authors created a transgenic worm that allowed the FRET to be monitored in vivo over the entire body of the worm while simultaneously tracking its motion. The new methodology developed in this study can be potentially adopted to study other mechanically-activated systems in vivo. 

Some aspects of the analysis and interpretation of the fluorescence result require clarification: 

1) The propagating patterns in the kymographs of mCFP and mCit (Fig 5BCFG) are puzzling. The authors contributed it to inherent locomotion artifacts, noise and internal sarcomere rearrangement during motion. While some of these may be true, could these be image processing artifacts? The authors stated in the method section that the fluorescence intensity at a particular body segment is obtained by drawing a perpendicular line to the midline. The pixels that it intersects will provide the fluorescence intensity. This approach does not seem to account for the fluorophore density change due to tissue compaction and expansion, resulting in overcounting intensity in the inner circle and undercounting at the outer circle - similar to the observed intensity patterns Fig 5BCFG. Perhaps it would have been helpful if the intensities were normalized by the arclength at the different radii from the center of the curvature. 

2) As related to the previous comment, but more generally, image analysis is a critical and sensitive step towards the interpretation of the fluorescence results. The authors would need to elaborate if and how errors in the image processing might contribute to the emergence of correlation between FRET and curvature. For instance, the CFP and mCit expression levels vary significantly along the body of the worm (Fig 5) and should be time-invariant. If an error in image processing picks up nearby spatial variations as the worm moves, the detected fluorescence will become time-variant and correlate with the worm's motion. It is unclear whether this could this happen with the current algorithm. This is a crucial assessment as it is crucial to ensure the observed small FRET changes (+/- 0.015) are due to molecular stretching and not artifacts of image processing. 

3) The shape and meaning of FRET change in the contraction-relaxation cycles (Fig 7) would require further interpretation. The data shows that the extrema and phase of the FRET signal correlate to curvature, and thereby, sarcomere stretching. It is unclear whether it is valid to assume the stretching or relaxing of sarcomeres apply tension directly over each twitchin. Is the binding-unbinding transition of NL to TwcK two-state? If so, would this lead to two-state behaviour in the observed FRET? 

4) The reason behind the small observed FRET change (+/-0.015) requires further clarification. Is it because (1) all FRET sensors changed slightly, or (2) a small fraction of FRET sensors changed from high to low FRET. 

5) The manuscript provides strong evidence of FRET correlating to curvature during the muscle contraction cycle. However, the causality is less clear. It is unclear whether the contraction force causes the FRET change, or can curvature without any active contraction cause FRET change. For instance, it is unclear whether, if the worm were dead or myosin activity inhibited, the bending of the worm would cause FRET change.

Mr. Bruff outlines his thought process very clearly and explains the possible scenarios he's come up with in his head.

This is where people with a tendency to participate in JS development frequently start to go off the rails. Exercise some restraint and tell that voice in your head that has been influenced by years in the community "no".

(PS: typeof checks need not and should not be written to use triple equals. Again, this is an example of where the dominant culture of modern JS development is a bad influence—pushing people towards doing things poorly. It's like radio and TV announcers who go out of their way to say "backslash" in URLs—"stop! you're going through extra effort just to get it wrong.")

Example of clearing the mental clutter by writing using Julia Cameron's Morning Pages concept.

nuclear message;

the weaponisha of realization that our "relative to whaa" answer is the lack of discussion regarding the cold war, the increase in "musical negativity across the board per vitsivavat" at this moment in time, i cannot help but imagine it obvious only to those looking at the macroscopic and the #mitnick

that we are in fact in a controlled spiral down, ninsane as it looks--i imagine we should "pray and thank our lucky stars" that there is certainly a civilization that has pondered the puree of water, the okee of georgia and the water of seminole cycle prime.

is this flood or flaire? does malaleukimia cure the deforestation nat?

:)

sorry i got sidetracked in this note, but the relevance is clear, the "borg was e" pronounciation of this french word for the "middle class" connects the lack of understanding that slavery and the NSA "BOX" are connected to Mecca and Tzadek, vatzedek, and HASEEDICK relationshios between the circumlocutikon of the covenant not to "see, care, be pissed, or fix the problem" relate to uhh..

GOLDBUYCARDONO #BARSTOW #CANADA

Barstow and the related complex near Hilton Head Island (related of course only through the one soul, relatedly probably multiple versions of "blue-ann" and/or the one where you see it's a ...

"I was set up from the beginning of time, from before the earth; not to like giving or getting round tables or headless horsemen the key of the Berndibar Numbers and the Asmodean average

I cannot express enough how much I think nutty zoning needs to die and yet how head-ass this is. "Mobility" can also be represented as the uprooting of communities. How the hell would this make regional inequality better and not worse?

There's something so lovely about the way Joyce describes the scene in terms of the way the light is cast across the body

Is this an Irish tradition? I haven't heard of this.

The writing of this story is very interesting, because although it does not seem formal, some words are difficult for me to understand. This makes it a bit hard to follow along with the narrative a bit.

my relatable experience would be the thought coming to me about the desire to undergo 'lust' by means of self-pleasure through masturbation. The thought comes and I undergo the wrath of watching others have intercourse whilst I sit and use my hands to go back and forth to mimic real intercourse whilst being visually stimulated. After committing this act, I almost resign how I felt before and begin shaking my head in a type of disgust. The change of states is so quick that the disgust falls into reflection upon past actions instantaneously, almost as if "An invisible puppetmaster controlling the human collective and directing it to their negative agenda?"

The ROI Technique for ML Projects.

Mexican childhood, memories, family, school, bullying, violence, fighting, domestic violence;

Reviewer #1 (Public Review): 

This manuscript is a follow-up of an earlier manuscript using the LRET technology, but extends the study by identifying a new "open" state and using experimental distance constraints to provide molecular models of the different states. All in all, the manuscript is well written, the experiments are described in sufficient details and experiments are done to high quality with the appropriate controls. The data corroborate the partially open state as published early, but extend the study to a second, open state. It is very good to see that the observed states are not only present in the catalytic head but the authors also use the full-length protein and find similar states. However, in the present manuscript, I find the conceptual advance with respect to the mechanism of MR somewhat limited. The authors curiously do not include any DNA in their structural studies, so the observed states are only relevant for the free MR complex, but not the complex "in action" bound to DNA where quite different conformations might occur. As one consequence, the structurally proposed states do not directly correlate with the functional nuclease states that are necessarily bound to DNA. Perhaps as a consequence, in the author's model, Rad50 is merely a gate-keeper for Mre11, but this is not the case as recent structural work shows that Rad50 forms a joint DNA binding surface with Mre11. Likewise, biochemical studies are done with physiologically unclear/less relevant 3' exonuclease activity only, but not with the physiological important 5' endonuclease activity. In my opinion, it is important for a publication in a journal with the scope of eLife and addressed to a broad audience to provide structural analysis in the presence of DNA and validate the structures using the endonuclease activity. 

Specific recommendations: 

1) Instead of using the physiological unclear exo activity, I suggest to use the more relevant endonuclease activity to validate the mutants. 

2) Since the authors mutated one side of newly identified/proposed salt-bridges, I also suggest to test whether a charge reversal on both sides of the salt bridge rescues the phenoptype. I find this important because MR has quite many conformations, and mutating a single residue might not unambiguously validate the proposed conformation, a rescue by a charge reversed salt bridge is much stronger. 

3) Since all LRET experiments are done without DNA, the authors do not capture relevant DNA processing states and comparison of structural (w/o DNA) and biochemical data (w/ DNA) is not really justified, in my opinion. Also, they might miss critical conformations. Is there a technical reason for not including DNA in the LRET studies? 

4) If the authors want to claim processive movement coupled to partially open/open state interchanges, they should provide experimental evidence. Where would the energy come from for such a movement, this is not clear from the model? 

5) The SAXS data for the "open" state do not validate the model, in my opinion. Experimental data and model are not inconsistent, but the curve looks to me as if the open state is perhaps much more flexible (i.e. an ensemble) or extended? Please comment. 

6) Distance errors for the full complex are much smaller than those for the catalytic module only (Fig. 1d). Does that mean that the full complex is more rigid, please comment?

with substance abuse, there are other competencies that the client has to develop. How they got hooked on the substance as a way to escape the drudgery of everyday and as a way to get out of their own head for a while. It will take a fair bit of therapy and a detox lifestyle without the triggers and enablers that fueled those habits.

Like people who can't wrap their head around the idea that evolution has nothing to do with any kind of purpose to produce humans. (Even starting from the position that humans are the "end result" is fundamentally flawed.)

Reviewer #2 (Public Review): 

In this study, Imai et al. uncover a role for the truncated haemoglobin protein YjbI in biofilm formation by the model bacterium B. subtilis. They show that yjbI gene disruption results in altered biofilms, with increased wettability and different matrix stiffness relative to cells. The absence of YjbI activity results in aggregation of the amyloid-like TasA matrix protein, and the biofilm wettability defect of the yjbI mutant can be recapitulated by anti-YjbI immune serum, suggesting that YjbI is located on the cell surface. Absence of YjbI also modestly increases the sensitivity of cells growing on agar plates to the oxidant AAPH. Using the model protein substrate BSA, purified YjbI can at least partially reverse oxidant-induced BSA aggregation in vitro, convincingly showing the YjbI has protein hydroperoxide peroxidase activity, which is evidently an unusual enzymatic activity. Finally, the authors examine lipid peroxidation and conclude that YjbI is not involved. The results are interesting in that they connect YjbI to a biofilm phenotype and convincingly show protein hydroperoxide peroxidase activity by a truncated haemoglobin protein, an activity not previously attributed to this class of proteins. 

The experiments are largely well done, but some of the corresponding conclusions are overinterpreted, connecting ideas without experimental support. Moreover, the yjbI mutant has a narrow and relatively mild phenotype. 

1) The paper identifies two separate properties of YjbI: its mutant phenotype with respect to biofilm formation, and its peroxidase activity against oxidant-induced aggregation of TasA and BSA. The authors conclude that these properties are connected, but this is not formally tested. While purified YjbI can reverse hydrogen peroxide-induced aggregation of purified TasA in vitro, and the yjbI mutant shows more TasA in the insoluble fraction of B. subtilis pellicle lysates, these experiments do not show that the TasA aggregates in pellicle lysates are caused by peroxidation, nor do they show that TasA aggregation is normally kept at bay by YjbI peroxidase activity (it is possible that YjbI has a separate role in biofilm integrity). Some experiments that might lend support to this connection include examining the biofilm phenotype of a catalytically dead point mutant of YjbI (perhaps Y25 or Y63, l. 298, or other residues informed by the crystal structure of Giangiacomo et al.) to establish whether peroxidase activity is important for biofilm formation. Such a mutant would be particularly valuable, as it could also be used to test whether inactivation of enzyme activity affects other phenotypes (cell stiffness, for example). Another approach would be to use a soluble antioxidant molecule, purified YjbI, or another peroxidase to see if the yjbI biofilm can be rescued. 

2) The authors conclude on the basis of the AFM data in Fig. 1 that yjbI mutant cells are less stiff than WT cells, but the data only show relative stiffness. It is also unclear why a change in cell envelope stiffness would relate to biofilm wettability (ll. 130-131). If there truly is a change in cell envelope stiffness, a high-resolution, head-to-head AFM comparison of planktonically grown cells would be informative. 

3) The data in Fig. 2F showing hypersensitivity of yjbI mutant cells to AAPH were generated in an unusual way: stationary-phase liquid culture was spotted on an LB plate, and the colonies were "fractionated" at the noted intervals and resuspended in saline for OD measurement. Measuring sensitivity to AAPH just in shaking liquid planktonic culture would make this phenotype more convincing. Under non-biofilm forming conditions, is a surface-associated peroxidase important for cell growth or survival under oxidant challenge?

Time in the US, Violence, Gangs

Time in the US; Gang, Camaraderie/family; Friends

The fat man's word affected Leila a lot. We should be able to classify her emotions as sad instead of jolly although the word "smile" appeared here.

Return to Mexico, challenges, continuing education, cultural differences, economic well-being, employment, language, Spanish, mental health;

The author's name is linked and provided a biography. She has some credentials in the scientific field, although not specifically in paleontology: "Carolyn is the Earth & Climate writer at Science News. Previously she worked at Science magazine for six years, both as a reporter covering paleontology and polar science and as the editor of the news in brief section. … She has bachelor’s degrees in Geology and European History and a Ph.D. in marine geochemistry from MIT and the Woods Hole Oceanographic Institution."

The website is Science News. Looking at the About page, their goal appears to be to report scientific news and advancements. "Our mission is to provide independent, unbiased coverage of science and give people the tools to evaluate the news and the world around them." This is a worthy goal. However, due to its role as reporting on science, it may be worth it to go to the original source.

Searching sciencenews.org in Google (because the website title itself is so common) leads us to the Wikipedia page. It is a long-running publication (since 1922!) and there are no red flags.

Reviewer #1 (Public Review): 

Vafidis et al. propose a model of a form of synaptic plasticity in head direction cells of the Drosophila central complex, in which visual input arriving at axon-proximal locations supervises other input arriving at axon-distal locations. The authors show that this proposed plasticity rule can tune the system to perform accurate path integration and adjust to changes in gain. 

The proposal is an interesting idea that maps the extended morphology of the E-PG neurons that represent head direction in flies to a very specific functional prediction. This prediction is inspired by work in mammalian pyramidal neurons, where it appears that inputs arriving at different parts of the neuron can either be modified through learning or serve as the learning signal itself. The model functions well, and successfully produces a network that is capable of path integration. 

A concern about the model is that it is unclear whether this activity-dependent plasticity rule is actually needed to reproduce results consistent with what is shown in flies. The trained networks actually perform better than flies do in experiments, and noise must be added to make the performance comparable. Also, adult flies do not appear to be capable of adjusting to changes in gain, as the model does. 

The general ideas of the model may be applicable to a variety of systems that require some form of path integration, and thus although this study develops a model that is specific to the fly head direction system the architecture could be easily extended to other scenarios.

Reviewer #2 (Public Review): 

The ring attractor model serves as a fundamental framework to study how the brain encodes and computes based on continuous variables. One of this computation is angular path integration- the ability of animals to orient themselves using idiothetic cues to update the internal representation of their location. However, these models are usually pre-engineered and require precisely tuned connectivity, but it is unclear how such tuning emerge in the system. 

This computational work provides a model that learn to path integrate by adjusting synaptic efficacies, guided by allothetic cues. Tailored to the head direction system of the fly, this work replicates some of the experiments and findings in the literature and provides a mathematical explanation for how symmetric connectivity arise in such recurrent networks when supervised learning scheme is assumed. 

Strengths of the paper:

The paper addresses an interesting question, of the ability of the head direction system to path integrate. Putting in context, it's been almost 30 years that a ring attractor network was suggested to model the head direction system. The idea behind this model is that due to a symmetry in the recurrent connectivity in the network, a continuous attractor emerges in the system. In classical models, networks with 2 or 3 rings are used to both generate a persistent and continuous representation, but also to allow to perform angular integration. In recent years, it was suggested that a 3-ring-like structure plays a key role in the head direction system of the Drosophila. 

The strength of the paper is in building of a mechanistic network model that learns to path integrate based on a supervised learning scheme. The learning rule is local, suggesting its being biologically plausible, and following training the system develops symmetric recurrent connectivity that are reminiscent of the Fly's head direction system. Moreover, the authors provide a mathematical derivation, which shows how symmetric connectivity emerges in the network. 

Because the ability to path integrate in the system is based on learning, and not on pre-engineered connectivity, the network can also adapt to changes in the gain between the allothetic and idiothetic signals. This is consistent with the literature, where it was recently shown that the head direction system of the mouse can adapt to such gain modulations. 

The learning rule is based on a two-compartment model, which serves as a coincidence detector between external and internal inputs arriving at different compartments. The authors analyze the Fly's connectome data (visual and recurrent inputs to the E-PG neurons) to support this hypothesis. 

Weaknesses of the paper:

The paper has three main weaknesses. 

The first is that it is unclear if symmetry is a necessary outcome of the learning scheme, or if it depends on the way the network is initialized. In their mathematical derivation the authors assumed that the solution is symmetric, and while checking that this assumption is self-consistent, it is unclear if other non-symmetric solutions exist. Specifically, it is unclear if different initializations of the recurrent and feedforward connectivity will give a different- possibly asymmetric- solution. Moreover, the authors assumed a specific network architecture, which was tailored to the Fly's head direction system. It is unclear if the symmetric solution the authors found is specific to this architecture. 

The second issue is with the support the authors provide to their two-compartment model assumption. The authors analyzed the spatial locations of inputs to an E-PG neuron and claimed that the visual and recurrent inputs are spatially segregated. While this is a nice use of the new connectome data, there is no statistical analysis to support this claim, and only one example is shown in the manuscript. 

Third, the mechanism in the model seems to strongly rely on saturation of the E-PG neurons. However, it is not clear if this is a biologically relevant regime for these neurons and the authors do not address this problem. 

Finally, while the authors did a great job in building a mechanistic model that resembles the fly's head direction system, they fail to provide testable predictions. Such predictions are in general not necessary to have, but with the detailed characterization of this system in the fly, together with a mechanistic model that is tailored specifically to this system, I feel that the manuscript (and the community) will benefit from devoting a paragraph or two in the discussion to suggest new experiments, in line with their mechanistic model.

Reviewer #3 (Public Review): 

In this manuscript by Vafidis et al., the authors propose a learning mechanism that adjusts the connectivity of a head direction cell network to obtain robust angular integration. Ring attractors have been proposed long ago to account for head direction cell tunings. However, in general, continuous attractors require precise (or fine-tuned) weights in the neuronal connectivity of the circuit. It seems, a priori, unreasonable to think they are developmentally obtained, and a process requiring experience would be more likely. Hence the mechanism proposed by the authors is attractive and elegant. 

In general, the manuscript is well written and structured. The work is of timely interest, especially since the insect head direction cell circuit is currently receiving much attention.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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Reply to the reviewers

Manuscript number: RC-2021-00733

Corresponding author(s): Haiyun Gan

Sara Monaco, PhD Managing Editor Review Commons

Dear Dr. Monaco,

We would like to thank all the reviewers for their insightful and constructive comments, which have helped us to improve our work. Please find below our responses to each of the concerns raised by the reviewers.

Sincerely

Haiyun

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

**Summary:**

• In this article, Li and colleagues demonstrate the utility of a novel proximity labeling-based strategy, which they term AMAPEX (antibody-mediated protein A APEX) for the proteomic characterization of the protein environment of specific histone modifications. They apply this new methodology in mouse embryonic fibroblasts for subsequent purification of biotinylated proteins and mass-spectrometric identification. **Major comments:**

• The authors present a high quality, descriptive manuscript that introduces a novel proximity labeling approach from a mostly technical point of view. The presentation of the data and methods are mostly clear, such that they should be easy to reproduce.

  We thank the reviewer for the positive view of our work.

• The biggest shortcoming of the study in its current form seems to be the lack of a proper assessment of the method's sensitivity AND -most importantly also- specificity. The authors do not validate potentially new interactors of the modified histones experimentally, which would highlight their technology as a discovery tool. Without the assessment of newly identified proteins, these could simply represent false positives, which would point towards an additional requirement for optimization of the experimental setups. In that light the newly identified proteins are merely potential histone interactors. Validation would require establishment or purchase of additional antibodies, or alternatively cloning and transfection of respective candidates, which will probably take an extra 2-3 months of work. While the study may be publishable in its current form, this validation seems a valuable investment to strengthen the preliminary conclusions.

  We agree with the reviewer that lack of validation of our approach is the major shortcoming of our study. As described in our manuscript, we could identify most of the histone interacting proteins found by other methods in the published data(Vermeulen et al, 2010; Villasenor et al, 2020) (fig. 2A). We also provide evidence that the H3K27me3 proteins (NSD1, Brd9) identified by H3K27me3 AMAPEX are co-localized with H3K27me3 at the same genomic regions (fig. 2C). In addition, as we observed the enrichment of splicing proteins of the H4K5ac interacting proteins, we purified nucleosomes and performed SF3B1 IP and confirmed the interaction of SF3B1 with H4K5ac. We also performed H3K27me3 mono-nucleosome IP and confirmed the interaction between H3K27me3 and NSD2. Together, these results suggested that AMAPEX is a reliable method to map histone proximal proteins. We have added the SF3B1/H4K5ac, H3K27me3/NSD2 binding data to the revised manuscript (Fig. 2E and Fig. 7C).

• With two biological replicates the study fulfills the minimum requirements for reproducibility, however, it would benefit from an additional replicate.

  We added extra replicates in the assays for H3K27me3 and H3K4me3 (Fig. 2A and Fig. 6A ).

**Minor point:**

• The sentences in lines 22f (and 44f) could be misunderstood. Please rephrase statements to be unambiguous that it specifies the proteomic surrounding of post-translationally modified proteins. The proximity labeling technologies may themselves be limited in identifying post-translationally modified proteins, as they label reactive side-chains that are often targeted by PTMs. Post-translationally modified lysine residues cannot be targeted by biotin ligase-based methodologies, as tyrosine phosphorylations cannot be assessed by peroxidase-based labeling.

  We agree that these sentences are confusing. We rephrased the sentence to “cannot be applied to identify proteins surrounding of post-translationally modified proteins” and “mapping the biomolecules that are proximal to post-translationally modified (PTM) proteins like histone modifications is complex” in our revised manuscript.

Reviewer #1 (Significance (Required)):

• From a technical point of view, most of the key conclusions of this paper are convincing. Assessing the proteomic environment of post-translationally modified proteins is of extremely high interest and the methodology seems broadly applicable to address such questions. It should be noted that proximity labeling has not originally been utilized to map protein-protein interactions, as the enzymatic activities available probe their surroundings, this could be an over-interpretation. Nonetheless, the "proteomic surrounding" of target proteins, which would also include hard to identify transient interactions is of high general interest for molecular biologists.

  Thanks so much, we have rephrased our sentences in the revised manuscript.

• Although it can be generally agreed that having to express an exogenous fusion protein is a limitation of current proximity labeling setups, the methodology presented here in turn has the limitation that it cannot be performed in living cells, which is a significant disadvantage.

  We agree that it is a disadvantage that our assay cannot be done in living cells, as most of the antibody-based assays have these limitations. However, we have successfully applied the AMAPEX to the cell samples under native conditions and we have included the results in the revised manuscript (Fig. 8)

Moreover, our method working under fixation conditions can be potentially applied to FFPE samples. We will add discussion to our revised manuscript.

• My lab is establishing and constantly improving various proximity labeling methodologies in combination with mass spectrometry for sub-organellar proteomics. While the technology is sound and well executed, I am not an expert in the biology of histone modifications and the proteins involved and cannot assess the novelty nor the actual value of the generated datasets. It appears to me though that additional validation by independent experiments would strengthen the manuscript. The authors describe the usefulness of the technology mainly in confirming known interactors of modified histones, however, it would be nice (for non-specialists) to explicitly state how high the coverage of the known interactors is and discuss why some of them might have been missed.

  Thanks for the suggestion. We have added the statement of the coverage of the known interactors in our revised manuscript and we also include discussions.

• The manuscript in its current form completely lacks a discussion of the presented data. Even if the focus will remain on the technical aspects, the findings should be properly discussed by comparison to other proteomics approaches studying histones. Ideally the data should also be discussed in the light of current proximity labeling technologies and potential future directions.

  We have added the discussion part to our revised manuscript.

• While I cannot assess the value for histone research, the manuscript will be very interesting for experts focusing on proximity labeling technologies and subcellular proteomics. Reviewer #2 (Evidence, reproducibility and clarity (Required)):

• This work describes interesting approach for mapping interactome of specifically modified histone protein using antibody-based APEX2. Although it contains interesting results and useful techniques for biological community, I found that it requires revision and addition for the publication.

• I could understand the reason using antibody-based proximity labeling approach for mapping the biomolecules that interact with post-translationally modified histone because it should be complicated to map it with exogenous protein expression approach. However, the introduction of antibody-conjugated APEX2 should require fixation and permeabilization steps that can usually compromise ultrastructure. The authors should comment whether these procedures can affect protein composition and structures of nucleosome in the Discussion part of this manuscript.

  We agree with the reviewer. To address the concerns raised here, we have performed AMPEX under native conditions (H3K37me3). Our results showed that AMPEX under native conditions can still identify most of the surrounding proteins identified with crosslink approach. We have added the data to the revised manuscript.

There are also advantages to perform the AMAEX with fixed samples, which may help capture the temporary events. We have added this to the discussion of the revised manuscript.

Formaldehyde crosslinking may cause undesired effect. For instance, the nuclear proteins/loci are not equally efficiently cross-linked; cross-linking may trigger the DNA damage response; crosslinking can also mask epitopes of some antibodies, affecting antibody/antigen binding. However, most of the approaches studying chromatin/nucleosome in cells requires crosslinking and permeabilization. We have included discussion about whether fixation and permeabilization affects protein composition and structures of nucleosome.

• For generation of biotin-phenoxyl radical, HRP-conjugated antibody can be utilized as shown in BAR method (Daniel Z Bar et al. Nat Methods, 2018, 15, 127-133). Since secondary-HRP antibody is commercially available, one cannot make an effort to express and purify pA-APEX2 for this approach. The authors should clearly explain why they selected APEX2 and what is an expected advance(s) using APEX2 in their approach

  We have compared pA-APEX2 with secondary-HRP and we found that pA-APEX2 can give better specificity as there more proteins identified by H3K27me3 mediated APEX2 located in the nuclear than that of HRP. We found that while only 33.31% of proteins identified by HRP based method locates in the nuclear, 69.4% of that identified by pA-APEX2 locates in nuclear, which implicates the increased specificity of the pA-APEX2 method compared to HRP conjugated 2nd antibody. We have added to data to revised manuscript (Fig. 3C, D).

• For the detection of the APEX-mediated biotinylated proteins, direct mass identification of tyrosine-modified peptides with chemical probes can tell the most correct information of the proximal proteins (see Lee SY et al. J. Am. Chem. Soc. 2017, 139, 3651-3662; Namrata D Udeshi et al. Nature Methods 2017, 14, 1167-1170). Thus, if the authors can obtain the biotin-modified peptide information from each antibody-conjugated APEX2, the quality of their interactome results should be much improved. If authors may be under the situation that cannot conduct further mass experiments, it might be required to check whether their important finding molecules (e.g. Arid2, Brd7, Nsd2) are really "biotinylated" by conducting Streptavidin-HRP western blot experiment after enrichment of those proteins by using primary antibody. If biotinylation is specifically conducted by pA-APEX2 with H3K27me3 antibody, the authors can observe SA-HRP blot signal on the enriched protein band on the membrane. Negative controls should be the samples omit pA-APEX2, H3K27me3 antibody, biotin-phenol, H2O2, respectively or using different PTM targeted primary antibody. This result can confirm that their findings are enriched from proximity-dependent biotinylation of APEX2, not from spurious binding events to the other biotinylated proteins or self-labeled bait proteins.

  We thank the reviewer’s suggestion. We agree that finding the biotinylated peptides of the discovered proteins in our experiments could make the results more convincing. A variable modification of biotin-phenol on tyrosine was added to the search setting of MaxQuant (version 1.6.10.43), which indeed led to the identification of very few (only ten) biotinylated peptides without the ones from Arid2, Brd7, or Nsd2. However, these results were not surprising. Since, we pulled down the low abundant target proteins based on the strong binding of biotin-streptavidin (Kd ≈ 10−14–10−16 M ) (Laitinen et al, 2007)., which is also unusually stable against heat, denaturants, extremes of pH and proteolytic enzymes(Wilchek et al, 2006). These were considered as the obvious advantages of the technology. Thereafter, to obtain the better peptide coverage, on-bead tryptic digestion was performed under a relatively mild condition (50mM HEPES pH8.0, 1μM CaCl2, and 2% ACN). Therefore, it is highly likely that, the biotinylated peptides were still trapped on the streptavidin beads but not detectable in the samples.

We indeed performed the Streptavidin-HRP western blot experiment and compared to the samples omit H3K27me3 antibody, H2O2, or samples of IgG, there is increased SA-HRP blot signal in the samples conducted by pA-APEX2 with H3K27me3 antibody (Supplementary Fig. 1F).

Reviewer #2 (Significance (Required)):

• For antibody-binding APEX2 strategy, this work is not the first one and the authors should mention the precedent work in the manuscript: Jisu Lee et al. Chem. Commun., 2015, 51, 10945-10948. And the author also commented the antibody-based proximity labeling mapping works including Daniel Z Bar et al. Nat Methods, 2018, 15, 127-133 in the manuscript.

  We are sorry for the oversight. We have rephrased our sentences in the revised manuscript. In addition, we have also compared our method with the one published in Nat Methods.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

**Summary:**

• The manuscript by Li and coworkers describe an approach for detecting the PTM specific interacting proteomes through Proximity labeling strategy. In this method, cellular proteomes were first cross-linked by formaldehyde and then incubated with PTM specific antibodies. Afterwards, a protein A-APEX2 fusion protein was added to target the antibody and label the proteins in proximity with biotin. The biotinylated proteins can be enriched and subsequently identified by LC-MS/MS. The authors claim that these proteins are PTM-specific interacting proteins because they are close to the PTM-recognition antibody. They mainly applied the method to the histone marks and identified the interacting proteins for several histone modifications. They found that the identified proteins overlap partially with the published CHIP-seq data and drew complicated interaction networks based the proteomic data using the STRING database. **Major comments:**

• The APEX technology has been widely used for capturing subcellular proteome or proteome proximal to the target protein of interest. Here the authors aimed to use antibodies specific for detecting certain histone PTMs to guide the APEX enzyme for proximal labeling. While the idea is interesting, the actual applicability is rather limited as APEX does not enable identification of direct interactions. With the current methodology design, the reviewer did not see its advantage over a formaldehyde crosslinking followed by a conventional immunoprecipitation using the PTM-specific antibody. The authors are suggested to compare the head-to-head performance of these two approaches.

  We agree with the reviewer that APEX2 is for proximal labeling and we have rephrased our statement from “binding” or “interaction’ to “proximal”.

We have compared with the data of published work. (Vermeulen et al., 2010; Villasenor et al., 2020) (Fig. 2A) and we were able to identify most of the proteins identified in the published work. To improve our method, we performed AMPEX under native conditions and still got very robust labeling of nearby proteins, which is an improvement compared to the formaldehyde crosslinking followed by a conventional immunoprecipitation using the PTM-specific antibody method.

• From the methodological point of view, it is unclear why formaldehyde crosslinking is included here. Neither did the authors justify its necessity for the whole workflow. With treatment with 0.1% formaldehyde for proteome crosslinking, how about physiological status of the cells? Authors should assess survival of cells under formaldehyde treatment. After a long labeling time, will the labeling results still reflect the physiological status of the protein interaction networks in living cells?

  We agree with the reviewer regarding the role of crosslinking in our method. To this point, we have performed AMPEX under native conditions and still got very robust labeling of nearby proteins. On the other hand, crosslinking allows our method to be potentially used for FFPE samples.

• Overall, the manuscript lacks sufficient description on how the pipeline was optimized. For example, does it matter where the APEX2 is fused to protein A? The authors need to do a better job to present their optimization process.

  We found the activity is robust with current pA-APEX2. There is published data that there is only minimal effect on enzymatic activity when APEX2 is fused to Tn5 at different positions, which suggested APEX2’s enzymatic activity is unlikely to be affected by the location of fusion proteins.

• Crosslinking will result in high background in proximity labeling, in figure 1 D, the signal from IgG is obviously high. Strangely, the background signals completely disappeared in figure 2A. What are the differences between these two experiments? Similarly, in figure S4, the IgG lanes in A, B and C looked quite different from each other. The results suggested that the workflow might not be as robust as the authors have claimed.

  The high background of IgG in Fig. 4A in very possibly caused by the relatively less effective labeling by H3K4me3. As we responded before, we have included news results obtained under native conditions, which reduced background.

• The authors drew complicated interaction networks for each histone PTMs, however, a comparison between the networks for a modified histone versus the unmodified one is missing. Such data would be more valuable and informative as they can provide new clues on how the PTM mediates different interaction networks for cellular signaling.

  We have performed AMPEX with different Histone modification antibodies, while there are overlaps between these modifications, we could find proximal proteins specific identified by different histone modifications.

• The manuscript lacks the experimental validation of the identified interaction protein partners. The authors used the published CHIP-seq data, however, the cell lines of CHIP-seq are different from the one they used for APEX labeling. In this regard, an side-by-side comparison of this method with the CHIP-seq results should be performed, in terms of both purification efficiency and specificity.

  To validate our findings, we have purified nucleosomes and performed SF3B1 IP and confirmed the interaction of SF3B1 with H3K5ac. We have also performed mono-nucleosome H3K27me3 IP and confirmed the binding between H3K27me3 and NSD2. We have included these validated results in our revised manuscript.

• For the proteomic data, reproducibility calculation should use intensity ratio instead of intensity. The high dynamic of signal intensity will mislead the audience. P values between replicates should be calculated, a cutoff of

  We have calculated P values between replicates by t-test and added them in supplementary table s1.

**Minor comments:**

• Reference format should be checked. eg. redundant citation, incorrect format etc.

  We have checked our references for the errors and corrected them as many as we can find.

• Loading controls should be attached along with western blotting results (figure 1d, figure 2A).

  We have included the Ponceau S staining as loading controls of these western blotting results in our revised manuscript.

• This manuscript lacks clear conclusion or discussions. Subtitles are needed to delineate results. The overall logical organization of this manuscript should be strengthened. Currently, it is quite hard to follow and appreciate which part of the data is more technically novel and biologically significant.

  We have added subtitles and discussion in the revised manuscript.

• The title is too broad as the authors only showed the application on histone PTMs.

  We have changed our title to “Defining proximity proteomics of Histone modifications by antibody-mediated protein A-APEX2 labeling”.

• The introduction lacks proper description of other strategies for mapping PTM specific interactome, especially those by photo-affinity peptides or photo-affinity unnatural amino acids.

  We have added the other strategies for mapping PTM specific interactome in the introduction in the revised manuscript.

Reviewer #3 (Significance (Required)):

• It is more technical improvement by fusing protein A with APEX2 so that the proximity labeling can be guided around a specific PTM using the proper antibody. Researchers in the field of histone modifications will be interested in the current technique. The reviewer is with expertise in proteomics with focus on PTM analysis. References

Laitinen OH, Nordlund HR, Hytoenen VP, Kulomaa MSJTiB (2007) Brave new (strept)avidins in biotechnology. 25: 269-277

Vermeulen M, Eberl HC, Matarese F, Marks H, Denissov S, Butter F, Lee KK, Olsen JV, Hyman AA, Stunnenberg HGJC (2010) Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. 142: 967-980

Villasenor R, Pfaendler R, Ambrosi C, Butz S, Giuliani S, Bryan E, Sheahan TW, Gable AL, Schmolka N, Manzo M et al (2020) ChromID identifies the protein interactome at chromatin marks. Nat Biotechnol 38: 728-736

Wilchek M, Bayer EA, Livnah OJIL (2006) Essentials of biorecognition: the (strept)avidin-biotin system as a model for protein-protein and protein-ligand interaction. 103: 27-32

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Referee #3

Evidence, reproducibility and clarity

Summary:

The manuscript by Li and coworkers describe an approach for detecting the PTM specific interacting proteomes through Proximity labeling strategy. In this method, cellular proteomes were first cross-linked by formaldehyde and then incubated with PTM specific antibodies. Afterwards, a protein A-APEX2 fusion protein was added to target the antibody and label the proteins in proximity with biotin. The biotinylated proteins can be enriched and subsequently identified by LC-MS/MS. The authors claim that these proteins are PTM-specific interacting proteins because they are close to the PTM-recognition antibody. They mainly applied the method to the histone marks and identified the interacting proteins for several histone modifications. They found that the identified proteins overlap partially with the published CHIP-seq data and drew complicated interaction networks based the proteomic data using the STRING database.

Major comments:

1. The APEX technology has been widely used for capturing subcellular proteome or proteome proximal to the target protein of interest. Here the authors aimed to use antibodies specific for detecting certain histone PTMs to guide the APEX enzyme for proximal labeling. While the idea is interesting, the actual applicability is rather limited as APEX does not enable identification of direct interactions. With the current methodology design, the reviewer did not see its advantage over a formaldehyde crosslinking followed by a conventional immunoprecipitation using the PTM-specific antibody. The authors are suggested to compare the head-to-head performance of these two approaches.
2. From the methodological point of view, it is unclear why formaldehyde crosslinking is included here. Neither did the authors justify its necessity for the whole workflow. With treatment with 0.1% formaldehyde for proteome crosslinking, how about physiological status of the cells? Authors should assess survival of cells under formaldehyde treatment. After a long labeling time, will the labeling results still reflect the physiological status of the protein interaction networks in living cells?
3. Overall, the manuscript lacks sufficient description on how the pipeline was optimized. For example, does it matter where the APEX2 is fused to protein A? The authors need to do a better job to present their optimization process.
4. Crosslinking will result in high background in proximity labeling, in figure 1 D, the signal from IgG is obviously high. Strangely, the background signals completely disappeared in figure 2A. What are the differences between these two experiments? Similarly, in figure S4, the IgG lanes in A, B and C looked quite different from each other. The results suggested that the workflow might not be as robust as the authors have claimed.
5. The authors drew complicated interaction networks for each histone PTMs, however, a comparison between the networks for a modified histone versus the unmodified one is missing. Such data would be more valuable and informative as they can provide new clues on how the PTM mediates different interaction networks for cellular signaling.
6. The manuscript lacks the experimental validation of the identified interaction protein partners. The authors used the published CHIP-seq data, however, the cell lines of CHIP-seq are different from the one they used for APEX labeling. In this regard, an side-by-side comparison of this method with the CHIP-seq results should be performed, in terms of both purification efficiency and specificity.
7. For the proteomic data, reproducibility calculation should use intensity ratio instead of intensity. The high dynamic of signal intensity will mislead the audience. P values between replicates should be calculated, a cutoff of < 0.05 or < 0.01 is mostly used in proteome data.

Minor comments:

1. Reference format should be checked. eg. redundant citation, incorrect format etc.
2. Loading controls should be attached along with western blotting results (figure 1d, figure 2A).
3. This manuscript lacks clear conclusion or discussions. Subtitles are needed to delineate results. The overall logical organization of this manuscript should be strengthened. Currently, it is quite hard to follow and appreciate which part of the data is more technically novel and biologically significant.
4. The title is too broad as the authors only showed the application on histone PTMs.
5. The introduction lacks proper description of other strategies for mapping PTM specific interactome, especially those by photo-affinity peptides or photo-affinity unnatural amino acids.

Significance

It is more technical improvement by fusing protein A with APEX2 so that the proximity labeling can be guided around a specific PTM using the proper antibody. Researchers in the field of histone modifications will be interested in the current technique. The reviewer is with expertise in proteomics with focus on PTM analysis.

Time in the US, arriving in the US, first impressions;

Reviewer #1 (Public Review): 

The manuscript by Nakamura et al builds on previous publications reporting that research grants from Black Investigators scored worse and were less successful than those from White investigators. The authors of the current study attempt to examine the role of several variables (PI race, gender,degree, career stage, etc) on scoring of scientific reviews. The authors examined whether blinding reviewers to PI identity impacted review scores. They examined 1,200 applications, broken down to 400 from Black investigators, 400 from matched White investigators and 400 from un matched/random White applicants. The authors find that applications from White applicants scored better than those from Black applicants. The authors redacted information in the application and found that this worsened scores for the White applicants but had no impact on Black applicants. The study had several strengths including the fact that it used an experienced group of NIH grant reviewers and in fact the first author Dr. Nakamura was previously head of the CSR. Another strength is that the grant applications were actual grants submitted to NIH between 2014-2015. The study has several inherent weaknesses including that it is very hard to completely blind the reviewers to variables such as institution, career stage, PI identity, race etc. Redaction is also very time consuming and may affect the overall impact of the submitted application. Nevertheless the results provide new information to help better define the issues surrounding reviewer bias and potentially help in the search for possible solutions.

"Knowing the value of a lifetime, he never wastes his time, nor does he omit any necessary duty, so that in the light of his upright intentions, every action of his life may be considered as an adoration of God."

With this quoted sentence, as with many others, we can clearly see the impossibility of getting a useful biography of the Emperor. Because he is the emperor, his actions must necessarily align perfectly with the mores of the time—thus, while it is almost completely useless for any true exploration of Akbar the man, the document is quite useful in communicating to use those aforementioned mores. In other words, whatever the Emperor is described as doing must be what is considered most righteous in that society, as least for a head of state. What stands out to me is how the virtues seem to focus mostly on lack—what Akbar does not do, which stand in uneasy dialectic to the typical rapturous description of the King’s riches. Consider the section on the kitchen, one moment the author is describing the beautiful silver and gold dishes, tied up in red cloth. The next he is lauding the for his temperance, for never eating till he is full. Consider:

“Although surrounded by every external pomp and display, and by every inducement to lead a life of luxury and ease, he does not allow his desires, or his wrath, to renounce allegiance to Wisdom, his sovereign—how much less would he permit them to lead him to a bad deed! Even the telling of stories, which ordinary people use as a means of lulling themselves into sleep, serves to keep His Majesty awake.”

What a strange passage! Unlike the rest of the text, which seems to regard the emperor’s finery as an unquestioned good—what befits an emperor—here the text seems to regard luxury as dangerous and potentially immoral, the only saving grace here being the emperor’s superhuman self-control. Is this a response to civil unrest over the wealth gap? Or merely another way of demonstrating that Akbar is superman?

Further complicating the question, the text does not read exactly like a propaganda piece, where the only aim is to laud the ruler. On the contrary, painstaking detail is given as to how the royal lifestyle is kept up, and the work done by the servants is described in a ritualistic, almost religious manner, with a focus on a details that seem to have no reference beyond themselves. What is the significance of the copper utensils being tinned twice a month for the emperor, and once a month for princes? Who is the target audience of this piece of information—who would find it meaningful or connect it to something beyond itself? It’s a strange article, which seems to pull in many ways.

Overall though, the picture which is being painting of this mythic man, and thus of the virtue of the times, is relatively clear. Most of his virtues are abnegations, showing him to be a serious man who devotes himself to spirituality and his duties before his luxuries. But when half the text is describing his majestic harem and kitchen it seems a curious case of mixed messaging. Not being an expert on the culture I can only speculate, but despite it’s apparent contradictions, a connection could easily be made to the ideology of the modern right wing, especially here in America. On the one hand, that culture is strongly influenced by religion, and religion tends to go against riches and luxury-especially indulgence in these. On the other hand, that culture is also profoundly influenced by the doctrine of free market capitalism, where the rich deserve their riches because of their hard work and superiority. Such an ideology could well take root in a hierarchical caste system.

just banging one’s head on a task doesn’t necessarily precipitate the kind of creativity needed to get achieve meaningful research breakthroughs!

I forget that data and visualization show up in entertainment as well. It is like this section says, you have to look outside of spreadsheets and text files to see that photos and status updates could also qualify. This just reminds me that data can be used in so many different ways and not just the more common ones you may think of off the top of your head. People like their entertainment so Facebook and OkCupid were most likely successful in using their data in that way.

Too individualistic

WTF is wrong?

Where is the moral character and backbone of the American people. We know something is wrong! It smells and stinks yet no one does anything. Most of our elected politicians are useless turds floating in wastewater and the rest are multiple term professional corrupt politicians waiting for the appropriate revolving door opportunity. This has nothing to do with party affiliation, it is rampant on both sides. Political parties perpetuate the illusion as a control mechanism. We see it yet do nothing about it! WHY?

This paper (topic) is typical of the continued "head in the sand" passive financial regulatory system loaded with Sheeple and kiss-ass do nothing idiots. Alarms have been going off since 2005/6 and as predicted then, our financial system imploded in 07/08.

1. What lesson was learned?
2. Who were the players?
3. What disciplinary actions took place?
4. Who went to Jail?

Nothing has changed. Corruption and fraud fuel a dysfunctional financial system destined to cripple the American and Global economies. Economists and many within the financial sector know what is going on. Maybe they care about the average person but are afraid to come forward. Maybe they don't care and fully intend to rape and pillage as much of the global society as possible.

The question is what are YOU going to do to protect future generations, your children, grand children and so on?

I would never guess a paper file includes metadata. Before I read this article I always had the vision that everything in CS is so complicated, so reading this made me realize that it can be a lot simpler once you wrap your head around the basics of what something is. Then, you can level up to more complex ideas such as metadata in computers.

"fell asleep in the Lord" is an interesting euphemism for dying.

Here is another instance where words are written how they are pronounced instead of how they are written, it adds more to the story, I can hear Grandfather Pinner in my head. However, what problems does this cause in an analysis?

Author Response

Reviewer #1 (Public Review):

[...] My main technical concern lies in the choice of decomposition filter for SEP and alpha oscillations, and the conclusions the authors draw from that. Specifically, a CCA spatial filter is optimized here for the N20 component, which is then identically applied to isolate for alpha sources, with the logic being that this procedure extracts the alpha oscillation from the same sources (e.g., L359). I have no issues (or expertise) with using the CCA filter for the SEP, but if my understanding of the authors' intent is correct, then I don't agree with the logic that using the same filter isolate for alpha as well. The prestimulus alpha oscillation can have arbitrary source configurations that are different from the SEP sources, which may hypothetically have a different association with the behavioral responses when it's optimally isolated. In other words, just because one uses the same spatial filter, it does not imply that one is isolating alpha from the same source as the SEP, but rather simply projecting down to the same subspace - looking at a shadow on the same wall, if you will. To show that they are from the same sources, alpha should be isolated independently of the SEP (using CCA, ICA, or other methods), and compared against the SEP topology. If the topology is similar, then it would strengthen the authors' current claims, but ideally the same analyses (e.g., using the 1st and 5th quintile of alpha amplitude to partition the responses) is repeated using alpha derived from this procedure. Also, have the authors considered using individualized alpha filters given that alpha frequency vary across individuals? Why or why not?

Indeed, applying the same spatial filter to EEG signals with different spatial arrangements of the sources can lead to the extraction of neuronal activity which does not originate from the very same sources. We had chosen our approach, as it is well known that the generators of the early SEP components and the generators of the prominent somatosensory alpha rhythm co-reside at similar sites in the primary somatosensory cortex (e.g., Haegens et al., 2015). Therefore, we considered our approach appropriate to specifically focus on neural activity from the somatosensory region both in the frequency band of the SEP as well as of the alpha rhythm. Yet, we agree with the reviewer that it should be acknowledged that we may have missed or mixed-up effects of alpha activity from other sources by using this procedure (which might have led to different conclusions otherwise). In order to account for this, we repeated our analyses with an SEP-independent reconstruction of the oscillatory effects in source space (“whole brain analysis”). For this, we first reconstructed the sources of alpha activity using eLORETA and head models based on participant-specific MRI scans, and estimated the respective effects independently for all sources across the cortex using both linear-mixed effects models (LME) as well as a binning approach for the Signal Detection Theory (SDT) parameters sensitivity d’ and criterion c (consistent with the previous analyses in our manuscript). In the LME analyses, both the effects of pre-stimulus alpha activity on N20 amplitudes as well as on perceived stimulus intensity were strongest in the right primary somatosensory cortex – in accordance with the sources of the originally extracted tangential CCA component of the SEP (see Supplementary Figure 1 for Peer Review). Also, using the binning approach to examine the relation or pre-stimulus alpha activity with SDT parameter criterion c, the effects were most pronounced around the right somatosensory regions (Supplementary Figure 2 for Peer Review), yet these effects did not survive statistical correction for multiple comparisons (FDR-correction with p<.01). However, when performing the same binning analysis for our region of interest (ROI), the hand area in BA 3b of the right somatosensory cortex, a significant effect or pre-stimulus alpha on criterion c was indeed confirmed, t(31)=-2.951, p=.006, CI95%=[-.173, -.032]. Furthermore, in line with our previous CCA results, for sensitivity d’, neither the whole brain analysis nor the ROI analysis showed effects of pre-stimulus alpha amplitude, t(31)=0.633, p=.531, CI95%=[-.083, .157]. Taken together, the findings we report in our original manuscript for pre-stimulus alpha activity obtained with the spatial CCA filter can thus be replicated with a SEP-uninformed source reconstruction, both using LMEs for a “whole-brain analysis” as well as SDT analyses in a ROI-based approach. We therefore conclude that the relationships between pre-stimulus alpha activity, N20 potential of the SEP, and perceived stimulus intensity can indeed be attributed to neural activity from the same (or at least very similar) sources in the primary somatosensory cortex.

Addressing the question on filtering alpha activity in individualized frequency bands, we considered this option, too. However, the rather short length of our pre-stimulus window (-200 to -10 ms) constitutes a natural limit for the frequency resolution in the alpha range and slightly different filter ranges (adjusted with regards to the individual alpha peak frequency) are thus unlikely to lead to large differences in the estimation of pre-stimulus alpha amplitudes. Therefore, we refrained from using individualized frequency bands here and focused on the more generic approach using one common alpha band (8-13 Hz) for all participants, which should also facilitate direct comparisons with previous studies on pre-stimulus oscillatory effects.

In the same vein, both alpha and N20 amplitude relate to perceptual judgement, and to each other. I believe this is nicely accounted for in the multivariate analysis using the SEM, but the analysis that partitions the behavioral responses using the 20% and 80% are done separately, which means that different behavioral trials are used to compute the effect of N20 and alpha on sensitivity and criterion. While this is not necessarily an issue given that there IS a multivariate analysis, I would like to know how many of those trials overlap between the two analyses.

This is an interesting point indeed. We included both the binning analyses and the multivariate analyses in our manuscript as we believe they offer complimentary views on the data, and also allow a direct comparison to previous studies in the field (e.g., Iemi et al., 2017). In fact, the trial overlap between the extreme bins of the alpha and N20 data were rather small.

Since the expected trial overlap is 20% when partitioning the data into quintiles randomly, the effect-driven increments and reductions in trial overlap in our data appear to be rather small. However, they showed the expected directions: Larger alpha amplitudes were associated with more negative N20 amplitudes (and vice versa). Presumably, these small differences in trial overlap reflect the rather small effect sizes we also observed in the multivariate analyses. We have added this information to our revised manuscript in the following way to give the reader a better picture of the underlying data for the binning analyses (page 9, lines 137 ff.): “(Please note that this procedure resulted in a different trial selection as compared to the SDT analysis of pre-stimulus alpha activity. Please refer to Fig. 2—figure supplement 2 for further details on the trial overlap.)”

At multiple points, the authors comment that the covariation of N20 and alpha amplitude in the same direction is counterintuitive (e.g., L123-125), and it wasn't clear to me why that should be the case until much later on in the paper. My naive expectation (perhaps again being unfamiliar with the field) is that alpha amplitude SHOULD be positively correlated with SEP amplitude, due to the brain being in a general state of higher variability. It was explained later in the manuscript that lower alpha amplitude and higher SEP amplitude are associated with excitability, and hence should have the opposite directions. This could be explicitly stated earlier in the introduction, as well as the expected relationship between alpha amplitude and behavior.

Thank you for pointing out this unclarity. We have now made this rationale more explicit already at an early point in the introduction (page 3, lines 26 ff.): “According to the baseline sensory excitability model (BSEM; Samaha et al., 2020), higher alpha activity preceding a stimulus indicates a generally lower excitability level of the neural system, resulting in smaller stimulus-evoked responses, which are in turn associated with a lower detection rate of near-threshold stimuli but no changes in the discriminability of sensory stimuli (since neural noise and signal are assumed to be affected likewise).”

Furthermore, I have a concern with the interpretation here that's rooted in the same issue as the assumption that they are from the same sources: the authors' physiological interpretation makes sense if alpha and N20 originated from the same sources, but that is not necessarily the case. In fact, the population driving the alpha oscillation could hypothetically have a modulatory effect on the (separate) population that eventually encodes the sensory representation of the stimulus, in which case the explanation the authors provide would not be wrong per se, just not applicable. A comment on this would be appreciated in the revision.

Our extensive additional analyses suggest that the sources of behaviorally relevant alpha and N20 activity were located at very similar cortical sites. Nevertheless, this is not a proof that exactly the same neuronal populations were involved (for example, alpha and N20 effects could originate from different cortical layers). Therefore, we have added this potential limitation to our revised manuscript in the following way (page 19, lines 379 ff.): “Furthermore, with the present data, we cannot unambiguously conclude that the observed relation between pre-stimulus alpha activity and initial SEP indeed involved the very same neuronal populations – which may represent a limitation of the hypothesized mechanism. However, all approaches to localize these effects pointed to very similar cortical regions as discussed in the following section.”

In addition, given how closely related the investigation of these two quantities are in this specific study, I think it would be relevant to discuss the perspective that SEPs are potentially oscillation phase resets. Even though the SEP is extracted using an entirely different filter range, it could nevertheless be possible that when averaged over many trials, small alpha residues (or other low freq components) do have a contribution in the SEP. If the authors are motivated enough, a simulation study could be done to check this, but is not necessary from my point of view if there is an adequate discussion on this point.

Indeed, the phase reset mechanism may be a possible alternative explanation for relations between oscillations and later parts of the ERP. However, the N20 potential reflects the very first excitation of the cortex in response to a somatosensory stimulus and should therefore represent a textbook example of an additive response (EPSPs are added to ongoing background activity). Moreover, the N20 response should be over long before a possible phase reset in lower frequencies (such as alpha frequencies) would start to play a role (Hanslmayr et al., 2007; Sauseng et al., 2007). Nevertheless, we ran additional control analyses (including a simulation study) in order to exclude that some odd combination of phase-locking and filter residues led to the present findings: Please see Essential Revision #4 for details and how we included these considerations in our revised manuscript.

Reviewer #2 (Public Review):

[...] The main weaknesses of the manuscript becomes most apparent with respect to the stated impact that "The widespread belief that a larger brain response corresponds to a stronger percept of a stimulus may need to be revisited.". I am not really sure if there are many cognitive neuroscientists, that would actually subscribe to such a simplistic relationship between evoked responses and perception and that temporal differentiation (early vs late responses) and the biasing influence of prestimulus activity patterns are becoming increasingly recognized. So rather than actually changing a dominant paradigm, this work is an (excellent) contribution to a paradigm shift that is already taking place.

Thank you for this feedback. We agree that the paradigm shift away from simplistic assumptions about the relationship between variability of neural responses and perception is already taking place and that this is already being appreciated by many scientists in the field. Also, we agree that the present study contributes more evidence to this emerging notion rather than changing the whole field. However, we do think that particularly the observation of opposite amplitude modulations of initial somatosensory evoked responses associated with presented stimulus intensity on the one hand and pre-stimulus excitability state on the other, provides a novel perspective for our understanding of how fundamental features of sensory stimuli are processed at initial cortical levels. Following your suggestions to tone down claims about the controversiality as well as to avoid over-generalization, we have therefore adjusted the impact statement of this manuscript to: “Larger evoked responses during initial cortical processing may reflect states of lower excitability.”

Furthermore, we have adjusted similar statements throughout the manuscript accordingly.

Also it should be considered that with regards to the analysis approach using CCA, the claims are mainly restricted to BA3b: i.e. while I also think that this is a strength of the current study, one should refrain from overinterpreting the results in a very generalized manner. The authors do include some "thalamus" and "late" evoked response patterns as well, however that presentation of the results is somewhat changed now as compared to the N20 (e.g. using LMEs rather than comparison of extremes; not using SEMs). The readablity of results and especially the comparison of effects would profit from a more coherent approach.

We agree that our findings indeed have the specific focus on the N20 component and thus on its generators in BA3b. We did not intend to suggest that the effects we observed for this initial cortical response can be readily generalized to other (later) ERP components, too. However, we do believe (and hypothesize) that similar mechanisms may be in place for corresponding initial cortical responses in other sensory modalities, too – yet it is clear that we cannot test this generalization with the current study. To avoid misunderstandings of these interpretations and their limitations, we have further specified these aspects in the Discussion.

Regarding our analyses of the later SEP (i.e., N140 component) and thalamus-related activity (i.e., P15 component), we initially decided to use linear-mixed effects models as they are mathematically equivalent to the way the sub-equations of the structural equation model were constructed (Table 2 in the manuscript). Nevertheless, we have now additionally run binning analyses to make a direct comparison also with Signal Detection Theory (SDT) parameters possible: For the N140 component, there was a significant effect on criterion c, t(31)=-3.010, p=.005, but no effect on sensitivity d’, t(31)=0.246, p=.807. For the P15 component, no effects emerged either for criterion c or sensitivity d’, t(12)=1.201, p=.253, and t(12)=-0.201, p=.844, respectively. These findings correspond well to the previous LME analyses and may indeed further facilitate the comparison with the findings for the N20 potential and pre-stimulus alpha activity. Therefore, we have added these complimentary analyses to our manuscript in the following way:

Results: “In addition, the SDT analysis based on binning of the P15 amplitudes into quintiles neither suggested a relation with criterion c nor with sensitivity d’, t(12)=1.201, p=.253, and t(12)=-0.201, p=.844, respectively.” (page 14, lines 241 ff.)

“These findings were in line with a separate SDT analysis: N140 amplitudes were associated with an effect on criterion c, t(31)=-3.010, p=.005, but no effect on sensitivity d’ emerged, t(31)=0.246, p=.807.” (page 15, lines 263 ff.)

Discussion: “Crucially, our data are at the same time consistent with previous studies on somatosensory processing at later stages, where larger EEG potentials are typically associated with a stronger percept of a given stimulus (e.g., Al et al., 2020; Schröder et al., 2021; Schubert et al., 2006), as both our SDT and LME analyses of the N140 component showed.” (page 19, lines 367 ff.)

“Yet, neither our SDT analyses nor the LME models of the thalamus-related P15 component supported this notion.” (page 21, lines 414 ff.)

Methods (page 32, lines 681 ff.): “The effects of the EEG measures pre-stimulus alpha amplitude, N20 peak amplitude, P15 mean amplitude, and N140 mean amplitude on the SDT measures sensitivity d’ and criterion c were examined using a binning approach: […]”

I have some concerns whether the relationship between large alpha power and more negative N20s could be driven by more trivial factors rather than the model explanations the authors develop in the discussion. Concretely the question whether phase locking of large alpha power along with >30 Hz high pass filtering could produce a similar finding as shown e.g. in Figure 2c. This is an important issue, as prestimulus alpha influences the N20 amplitudes as well as the perceptual reports.

Indeed, potential phase-locking of alpha oscillations to stimulus onset and filter-related effects are important issues that could potentially offer an alternative explanation for the observed relationship between amplitudes of pre-stimulus alpha activity and the N20 potential of the SEP. Although such pre-stimulus alpha locking is rather unlikely in a paradigm with jittered stimulus onsets (in our case uniformly distributed between -50 ms and +50 ms; corresponding to a whole alpha cycle), we have run the following control analyses to fully exclude this possibility:

First, we analyzed whether pre-stimulus alpha phase values were distributed uniformly and whether these phase distributions differed between high and low alpha amplitudes as well as between high and low N20 amplitudes. The phase of pre-stimulus alpha activity was obtained from a Fast-Fourier transform in the pre-stimulus time window from -200 to -10 ms, applied to unfiltered, but otherwise identically pre-processed data as in the original manuscript (i.e., applying the spatial filter of the tangential CCA component). For the FFT, we used zero padding (extending the pre-stimulus data segments to 2048 data points each) in order to obtain an interpolated frequency resolution of around 3 Hz. The phase was extracted at the frequency 9.766 Hz (i.e., the closest available frequency to 10 Hz). As visible from Supplementary Figure 3 for Peer Review, pre-stimulus alpha phases were distributed uniformly across all five quintiles of both alpha and N20 amplitudes. This observation was confirmed by the Rayleigh test (testing for deviations from a uniform distribution; Berens, 2009): Neither in the concatenated phase data of all participants, z=1.130, p=.323, nor in single-participant analyses within every alpha amplitude or N20 amplitude bin, we found evidence for a non-uniform distribution of alpha phase, all p>.367 (after Bonferroni correction for multiple testing). Thus, there was no phase-locking of pre-stimulus alpha activity that could serve as a trivial alternative explanation of the relationship between pre-stimulus alpha amplitude and N20 amplitude.

Second, in order to examine whether the combination of our temporal filters (30 to 200 Hz band-pass for the SEP, and 8 to 13 Hz band-pass for alpha activity) could have led to the present findings, we additionally re-ran our analysis pipeline with simulated data: We mixed exemplary SEP responses with constant amplitudes (unfiltered; derived from within-participant averages), with simulated alpha band activity with randomized amplitude fluctuations, and pink noise, reflecting neural background activity as is typical for the human EEG. The SEP onsets were chosen according to our original experimental paradigm with inter-stimulus intervals of 1513 ms and a jitter of ±50 ms. Next, we filtered these mixed signals between 30 and 200 Hz in order to extract the single-trial SEPs, and estimated the pre-stimulus alpha amplitudes between -200 and -10 ms in the same way as was done in the original manuscript (i.e., by filtering the mixed signal between 8 and 13 Hz). This procedure was repeated for 32 generated data streams, containing 1000 SEPs each (corresponding to our empirical dataset of 32 participants). The resulting average SEPs did neither show a visually detectable difference between the five alpha amplitude quintiles nor indicated a random-slope linear-mixed-effects model any relation between pre-stimulus alpha amplitude and N20 amplitude on a single-trial level, βfixed=-.0005, t(255.16)=-.094, p=.925. Therefore, our findings cannot be explained by filter artifacts or residual activity leaking from the alpha frequency band to the frequency band of the N20 potential.

Third, we re-analyzed our empirical EEG data in time-frequency space to obtain a more detailed view of the effects of pre-stimulus alpha activity on N20 amplitudes. For this, we decomposed our pre-processed but unfiltered data with wavelet transformation (complex Morlet wavelets) and calculated linear-mixed effects models on the relation between signal amplitudes in the time-frequency domain and single-trial N20 amplitudes as obtained from our original analyses. As shown in Supplementary Figure 5 for Peer Review, the time-frequency representations of the effects on N20 amplitudes indeed indicated a specific role of the alpha band, with its effects (i.e., already 200 ms before stimulus and in the upper alpha frequency range) separated from the time- and frequency range of the N20 potential of the SEP (i.e., from ~20 ms after stimulus onwards and above ~20 Hz). In addition, we ran the same analysis for the behavioral effect (i.e., perceived stimulus intensity). Also here, pre-stimulus effects were predominantly visible in the alpha band. Of note, there were also strong effects in the beta band. These may be interesting to study further in future studies – in particular, whether they reflect independent physiological processes or rather harmonics of the alpha band. Furthermore, these time-frequency representations suggest that the studied pre-stimulus effects might have been even more pronounced if we had analyzed the data in pre-stimulus time windows from -300 to -10 ms. However, in order to avoid inflating effect sizes by post-hoc data digging (“p-hacking”), we prefer to keep the original, a priori chosen time window for the main analyses of the manuscript. Yet, these onsets of pre-stimulus effects at around -300 ms may be of interest for future work. Taken together, these time-frequency analyses further support the notion that the observed relation between pre-stimulus alpha activity and N20 amplitudes is not due to technical issues (such as filter leakage and phase-locking) but rather reflects genuine neurophysiological effects of alpha oscillations on SEPs.

We have added the time-frequency analysis, as well as the SEP simulation analysis as figure supplements to Figure 2 in our revised manuscript (page 8) since we believe that these control analyses comprehensively show that the observed effects were (a) specific to the alpha band and (b) not due to any data processing-related artifacts.

It is important to emphasize that the model develop is a post-hoc one, i.e. the authors do not develop already in the discussion various alternative scenario results based on different model predictions. Therefore there is no strong evidence in support of the specific one advanced in the discussion.

Thank you for raising this issue. Indeed, we cannot prove with the current findings that our proposed physiological model of the relation between alpha oscillations and the SEP is the correct model (or that it is at least the best one out of a selection of possible alternative models). To do so, future studies would be needed that can actually directly measure and/or manipulate differences in membrane potentials and trans-membrane currents. Rather, we aimed with the present study to associate a physiological meaning with the concept of excitability changes in the human EEG – offering a hypothesis that may be worthwhile to be studied (and either confirmed or rejected) in future studies. We have tried to make this motivation more explicit in the Discussion section (page 20, lines 384 ff.): “Also, we would like to emphasize that the presented mechanism reflects a hypothesized model, which shall be further supported or falsified with more targeted studies, for example, directly quantifying membrane potentials and trans-membrane currents in relation to different excitability states in somatosensation.”

Evaluation Summary:

This work is of interest to the field of reproduction. Prior to fertilization, spermatozoa undergo a series of morphological and biochemical changes to become fertilization competent, driven by a rapid and poorly understood signaling cascade, culminating in the acrosome reaction. This latter reaction releases to the outside components from a vesicle, the acrosome, in the spermatozoan head and transforms the head plasma membrane so that sperm can fuse with the egg. The work shows that a G protein modulator GIV/Girdin, influences sperm motility and the acrosome reaction. In so doing it is important for fertilization and is one more strategy to control untimely acrosome reaction. The proposed mechanism is well supported by a variety of different experimental approaches.

(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewer #1 (Public Review):

Mammalian sperm are required to mature in the female tract in a process named capacitation and to undergo the acrosome reaction, a unique exocytotic process, that allow sperm to fuse and fertilize the egg. Untimely acrosome reaction is detrimental to capacitation and therefore mechanisms that prevent it are important. This work shows that GIV, a guanine nucleotide-exchange modulator (GEM) for trimeric GTPases, is highly expressed in spermatocytes. It is phosphor-regulated during capacitation in serine and tyrosine residues in mouse and human sperm. Phosphorylation of GIV reported to be located in the flagella and the acrosome in the sperm head, activates its ability to stimulate the PI3K→Akt signaling pathway regulating sperm motility and survival, and in the head controlling premature acrosome reaction. Intracellular Ca2+ oscillations had already been shown to modulate premature acrosome reaction. Interestingly, the work also shows that GIV transcripts are downregulated in the testis and semen of infertile men. The authors reach these conclusions combining KO mice and cell-penetrating peptides. Though the findings are interesting and important, several aspects of their quantitation would require significant improvements (for example, it is not indicated how many independent mice or human samples were used and how many cells were examined). The spatiotemporal segregation of signaling programs in the sperm flagella and head relevant for fertilization are indeed notable.

The irony of this discussion, especially after finishing the novel and learning of Godfrey's true intentions, becomes more and more clear. It's great to look back and pull together all the hints that Collins was leaving.

not trying to degrade Rosanna or anything, but this is the perfect example of a creepy fan letter

Mr. Godfrey is lying and hypocritical if we can trust Miss Clack's narration of the scene in Montagu Square

Mr. Godfrey's sudden changes in opinion and inexplicably close to Miss Clack seems to be a make up for his pervious decision. He's action seems to be hypocritically. He already lost Miss Clack, he cannot loss his reputation, status, property, etc. again. He knew that Miss Clack is obsessed with him, so that Mr. Godfrey tries to make use of it to gain what he wants?

Is Rosana's face in a flush because of Mr. Franklin or is she hiding about something under Betteredge's inquiry?

Rachel seemed rather excited about the idea of marriage at first, but being "indifferent" about your recent engagement was a bit strange. She doesn't seem too surprised hearing this news but rather confused on what to do with it.

more descriptions of women 'from the eye of a man'

So many similes

Very very detailed description of Miss Rachel and her appearance. You can imagine exactly what she is wearing, what her facial features might be like, and what the is doing. This might be the most detailed character description so far.

He's clearly upset about the inequality he sees between the lives of "gentlefolk" and of working people. He sees more value and honor in work and less in more privileged pursuits like art or science (or simply having the free time to goof off or be bored).

How to create a developer mindset

note8 Despite the many problems, compromises and solutions are being made. People are always trying to protect their privacy.

Claim

Time in the US, Jobs/employment/work, Documents, Careers, Food services, Athletics

How is Audi planning on using the suits?

What kind of support do these exoskeletons provide?

That is , when we do dependency parsing, (or just see the one given in PTB), the span in which the connective's head lies, is called \(Arg2\) and the other one \(Arg1\).

This is a link between dependency parsing and discourse parsing/argument mining. Can try to extend/generalize this kind of link further!

This is the key to understanding how control is established

Author Response:

Reviewer #1:

Authors reported here the results of two experiments. The first is about the effects of continuous theta burst transcranial magnetic stimulations on single cell responses of lateral parietal cortex of the monkey. This experiment is very challenging, requiring to obtain a stable and long-lasting signal from single cortical neurons and to stimulate constantly the same cell for an hour (they succeded also for longer periods). The paper represents a technical advance in the field and deserves attention and suggests a useful, through difficult, protocol to be replicated by other scientists.

The second experiment tests the behavioral grasp-related effects of two TMS theta burst protocols. Authors demonstrate a long-lasting increase in the grasping time after TMS.

A negative aspect is that the two experiments are not carried out on the same animals, and the results of the second experiment seem somehow not completely logically connected to the results of the first. Particularly important for the scientific community is the first experiment, that shows that the neural excitability is significantly reduced within the first hour after rTMS. This experiment demonstrated also a variability of effects (hyperexcitation, hypoexcitation, variable delays of recovery), that can be seen as a potential disadvantage in such TMS protocols, and an index of the different effects that may be obtained in the same experiment across subjects.

Overall, the paper represents a step forward in the neuromodulation experiments in nonhuman primates.

Reviewer #2:

Romero and colleagues designed an experiment to describe the neural and behavioral effects of continuous theta burst stimulation with the explicit aim of solving the problem of inter-subject variability of cTBS effects on human behavior. They describe two independent experiments in which cTBS was applied to the inferior parietal lobule of two monkeys per each experiment. In the first experiment the authors measure the activity of single units in response to light-on and to single-pulse TMS (spTMS). In the second experiment the authors describe the effect of cTBS on reaching time in a reach-grasp task. The results indicate a great variability on single neurons that follow different patterns of response to cTBS. In the second experiments the results show a systematic increase in reach-grasp time following cTBS. The authors provide a reasonable description of neuronal activity following their cTBS protocol but do not respond to the main issue of explaining inter-subject variability of human cTBS. The data has the merit of providing neural bases of the "delayed" effects of human cTBS.

We thank Reviewer #2 for his/her comments and for asking us to provide a possible explanation for the inter-subject variability of human cTBS. This has now been added in the Discussion (page 20). ‘The reproducibility of our results was most likely related to the very controlled conditions in which we applied cTBS in monkeys. Most importantly, the TMS coil was rigidly anchored to the head implant of the animal, so that we kept both the position and the orientation of the coil similar across sessions. However, another possibility is that monkeys become highly overtrained in the grasping task, which may partially explain the similar behavioral effects of cTBS we reported in Merken et al. (2021). It is therefore plausible to assume that the larger variability inherent to human behavior is one reason underlying the variability of cTBS effects in humans, since stimulation is applied over a brain area in subjects at different levels of learning stages and behavioral performance, ultimately impacting on the susceptibility of that brain area to cTBS and increasing inter-individual variability of the technique.’

Author Response:

Reviewer #3:

A. Summary of what the authors were trying to achieve

The authors seek to understand how whole-animal behavior is represented in the nervous system. They approach this problem utilizing high-speed volumetric calcium imaging in freely moving nematodes (C. elegans). In recording from a majority of neurons in the head, this approach is state-of-the art in C. elegans and, arguably, far beyond what is likely to be achieved in most other organisms in the foreseeable future. Imaging data are analyzed by training a linear decoder to predict the instantaneous locomotion velocity and body curvature from instantaneous neuronal activity at single neuron resolution.

B. Major strengths and weaknesses of the methods and results

The paper has numerous strengths:

1) State-of-the art simultaneous imaging of brain-wide neuronal activity and unrestrained behavior.

2) The overall approach has been published in two papers by this group and one from another group, but this is the first paper that actually takes the next logical step: connecting the recordings back to behavior. This is a major strength.

3) Comparison of neuronal dynamics during locomotion and immobilization in the same worm.

4) Rigorous data collection and modeling.

The paper in its current form has a number of weaknesses:

1) Several of the main findings of the paper seem rather obvious. (i) "We report that a neural population more accurately decodes locomotion than any single neuron (Abstract)". Similarly, "We conclude that neural population codes are important for understanding neural dynamics of behavior in moving animals." (ii) "Our measurements suggest that neural dynamics from immobilized animals may not entirely reflect the neural dynamics of locomotion." Consider rephrasing, as this sentence is almost a tautology: "…neural dynamics in the absence of locomotion may not entirely reflect the dynamics in the presence of locomotion (line 379)." Can these conclusions be rephrased, or put in a more significant context?

Thank you for this feedback. We have completely rewritten the relevant portion of the discussion to better place our findings in context and better convey the implications.

"That C. elegans neural dynamics exhibit different correlation structure during movement than during immobilization has implications for neural representations of locomotion. For example, it is now common to use dimensionality reduction techniques like PCA to search for low-dimensional trajectories or manifolds that relate to behavior or decision making in animals undergoing move- ment (Churchland et al., 2012; Harvey et al., 2012; Shenoy et al., 2013) or in immobilized animals undergoing fictive locomotion (Briggman et al., 2005; Kato et al., 2015). PCA critically depends on the correlation structure to define its principal components. In C. elegans, the low-dimensional neural trajectories observed in immobilized animals undergoing fictive locomotion, and the un- derlying correlation structure that defines those trajectories, are being used to draw conclusions about neural dynamics of actual locomotion. Our measurements suggest that to obtain a more complete picture of C. elegans neural dynamics related to locomotion, it will be helpful to probe neural state space trajectories recorded during actual locomotion: both because the neural dy- namics themselves may differ during immobilization, but also because the correlation structure observed in the network, and consequently the relevant principal components, change upon im- mobilization. These changes may be due to proprioception (Wen et al., 2012), or due to different internal states associated with fictive versus actual locomotion."

And we have rewritten portions of the introduction, for example:

"There has not yet been a systematic exploration of the types and distribution of locomotor related signals present in the neural population during movement and their tunings. So for example, it is not known whether all forward related neurons exhibit duplicate neural signals or whether a variety of distinct signals are combined. Interestingly, results from recordings in immobile animals suggest that population neural state space trajectories in a low dimensional space may encode global motor commands (Kato et al., 2015) , but this has yet to be explored in moving animals. Despite growing interest in the role of population dynamics in the worm, their dimensionality, and their relation to behavior (Costa et al., 2019; Linderman et al., 2019; Brennan and Proekt, 2019; Fieseler et al., 2020) it is not known how locomotory related information contained at the population level compares to that contained at the level of single neurons. And importantly, current findings of population dynamics related to locomotion in C. elegans are from immobilized animals. While there are clear benefits in studying fictive locomotion (Ahrens et al., 2012; Briggman et al., 2005; Kato et al., 2015), it is not known for C. elegans how neural population dynamics during immobile fictive locomotion compare to population dynamics during actual movement."

2) The rationale for the decoding exercises seems underdeveloped. Figs. 3-6 are motivated by the question of whether "activity of the neural population might be more informative of the worm's locomotion than an individual neuron." It just seems obvious this will be the case. There might be a missed opportunity, here. Perhaps a stronger motivation would be to ask whether locomotion related signals can be found in the subset of neurons found in the head. The alternative hypothesis would be that head neurons alone are not sufficient, the implication being that the ventral cord and/or tail ganglia must be included.

We have added rationale for decoding in the results section:

“...because an effective strategy adopted by the decoder may also be available to the brain, understanding how the decoder works also illustrates plausible strategies that the brain could employ to represent locomotion.”

And added motivation in the introduction:

“...Despite growing interest in the role of population dynamics in the worm, their dimensionality, and their relation to behavior (Costa et al., 2019; Linderman et al., 2019; Brennan and Proekt, 2019; Fieseler et al., 2020) it is not known how locomotory related information contained at the population level compares to that contained at the level of single neurons. ”

The ideas about head vs ventral cord and tail are interesting, but since we are limited in what we can say about signals beyond the head we hesitated to pursue that path.

3) The logic of how decoding exercises are interpreted also seems underdeveloped: (i) Why isn't the finding of locomotion-related signals in the head a forgone conclusion? After all, the worm's head is literally "carving the furrow" that the rest of the body follows, leading to body curvatures that ought to be correlated with with neuronal activity in the head. Furthermore, a substantial fraction of head neurons are nose and neck muscle motor neurons. These contribute to overall thrust, which in the worm's fluidic regime is proportional to velocity. Thus, as stronger head motor neuron activation would generate more thrust, there a correlation with velocity is expected. (ii) What does it mean to say, "The distribution of weights assigned by the decoder provides information about how behavior is represented in the brain (p. 8)"? Who or what is reading this representation? Is the representation detected by the decoder necessarily in the same or similar language used by the worm's brain? If not, how are the decoder findings significant for understanding locomotion in the worm? (iii) It seems likely that the decoder picks up signals of neurons that causally regulate locomotion, but also signals that follow from it (e.g., efference copy, proprioception, re-entrant signals, etc.). Assuming this is true, again: how are the decoder findings significant for understanding locomotion in the worm? (iv) In what ways, if at all, is the decoder a model for worm locomotion? If it's not a model, how does it improve our understanding of locomotion, or our future ability to construct and informative model?

Response to items 3 and 4 are combined below.

4) The Discussion seems to miss key points: (i) What are the main limitations of the approach (paucity of identified neurons, inability of Ca imaging to report inhibition, etc)? (ii) Why are the limitations non-fatal? (iii) What are the broader impacts of the main conclusions? For example, what is this significance of the finding of locomotion representations in the C. elegans nervous system or, indeed, in any nervous system? How do the results illuminate neural mechanisms of behavior?

We thank the reviewer for posing these thoughtful questions. We have rewritten the discussion to better explore some of the implications of our finding that a linear model works to decode locomotion and we explicitly highlight limitations including those related to:

• Neural identities: “ Future studies using newly developed methods for identifying neurons (Yemeni et al., 2020) are needed to reveal the identities of those neurons weighted by the decoder for decoding velocity, curvature, or both.”

• Linear vs nonlinear models: “...This does not preclude the brain from using other methods for representing behavior.”

• Distinguishing motor commands from signals that monitor: “... the measurements here do not distinguish between neural signals that drive locomotion, such as motor commands; and neural signals that monitor locomotion generated elsewhere, such as proprioceptive feedback”

Reviewer #3 (Public Review): 

A. Summary of what the authors were trying to achieve 

The authors seek to understand how whole-animal behavior is represented in the nervous system. They approach this problem utilizing high-speed volumetric calcium imaging in freely moving nematodes (C. elegans). In recording from a majority of neurons in the head, this approach is state-of-the art in C. elegans and, arguably, far beyond what is likely to be achieved in most other organisms in the foreseeable future. Imaging data are analyzed by training a linear decoder to predict the instantaneous locomotion velocity and body curvature from instantaneous neuronal activity at single neuron resolution. 

B. Major strengths and weaknesses of the methods and results 

The paper has numerous strengths: 

1) State-of-the art simultaneous imaging of brain-wide neuronal activity and unrestrained behavior. 

2) The overall approach has been published in two papers by this group and one from another group, but this is the first paper that actually takes the next logical step: connecting the recordings back to behavior. This is a major strength. 

3) Comparison of neuronal dynamics during locomotion and immobilization in the same worm. 

4) Rigorous data collection and modeling. 

The paper in its current form has a number of weaknesses: 

1) Several of the main findings of the paper seem rather obvious. (i) "We report that a neural population more accurately decodes locomotion than any single neuron (Abstract)". Similarly, "We conclude that neural population codes are important for understanding neural dynamics of behavior in moving animals." (ii) "Our measurements suggest that neural dynamics from immobilized animals may not entirely reflect the neural dynamics of locomotion." Consider rephrasing, as this sentence is almost a tautology: "...neural dynamics in the absence of locomotion may not entirely reflect the dynamics in the presence of locomotion (line 379)." Can these conclusions be rephrased, or put in a more significant context? 

2) The rationale for the decoding exercises seems underdeveloped. Figs. 3-6 are motivated by the question of whether "activity of the neural population might be more informative of the worm's locomotion than an individual neuron." It just seems obvious this will be the case. There might be a missed opportunity, here. Perhaps a stronger motivation would be to ask whether locomotion related signals can be found in the subset of neurons found in the head. The alternative hypothesis would be that head neurons alone are not sufficient, the implication being that the ventral cord and/or tail ganglia must be included. 

3) The logic of how decoding exercises are interpreted also seems underdeveloped: (i) Why isn't the finding of locomotion-related signals in the head a forgone conclusion? After all, the worm's head is literally "carving the furrow" that the rest of the body follows, leading to body curvatures that ought to be correlated with with neuronal activity in the head. Furthermore, a substantial fraction of head neurons are nose and neck muscle motor neurons. These contribute to overall thrust, which in the worm's fluidic regime is proportional to velocity. Thus, as stronger head motor neuron activation would generate more thrust, there a correlation with velocity is expected. (ii) What does it mean to say, "The distribution of weights assigned by the decoder provides information about how behavior is represented in the brain (p. 8)"? Who or what is reading this representation? Is the representation detected by the decoder necessarily in the same or similar language used by the worm's brain? If not, how are the decoder findings significant for understanding locomotion in the worm? (iii) It seems likely that the decoder picks up signals of neurons that causally regulate locomotion, but also signals that follow from it (e.g., efference copy, proprioception, re-entrant signals, etc.). Assuming this is true, again: how are the decoder findings significant for understanding locomotion in the worm? (iv) In what ways, if at all, is the decoder a model for worm locomotion? If it's not a model, how does it improve our understanding of locomotion, or our future ability to construct and informative model? 

4) The Discussion seems to miss key points: (i) What are the main limitations of the approach (paucity of identified neurons, inability of Ca imaging to report inhibition, etc)? (ii) Why are the limitations non-fatal? (iii) What are the broader impacts of the main conclusions? For example, what is this significance of the finding of locomotion representations in the C. elegans nervous system or, indeed, in any nervous system? How do the results illuminate neural mechanisms of behavior? 

C. Appraisal of whether the authors achieved their aims, and whether the results support their conclusions. 

The authors convincingly demonstrate that locomotion-related signals are present in their recordings. The effects are fairly robust. But if an implied aim was also to elucidate mechanisms of locomotion in C. elegans, this was not achieved. 

D. A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community. 

The authors have not made the case that their main findings are broadly significant. We learn what the linear decoder finds in the neuronal data - sustained and transient locomotion signals and distinct populations of velocity and curvature tuned neurons - but we do not learn what these properties of the decoder have to say about biological mechanisms. This problem is especially acute given: (i) the likelihood of neural correlations with behavior that are not functional representations of behavior and (ii) the absence of evidence that the decodable information is in fact used by the worm. We also learn that, as one would expect, immobilization alters the correlation structure of neural activity, but this finding has not been placed in a mechanistic context.

fuck this is a good phrase

It's obvious that Dracula doesn't care the animals he uses as their keepers do.

alleviate the wariness

As an extreme example, BERT itself, can be thought of as a probe on word-embeddings, if we freeze word-embeddings. Now, if by chance,the weights we use to initialize classifier head(BERT) happen to be the same as that of pre-trained BERT.. then we can get awesome performance on probing task, without the our initial model(i.e., the word embeddings) having any knowledge related to probing task.

Nice logic. Can be applied anywhere we have embeddings that are supposed to work for multiple tasks/encode multiple information. Usually we add a "head" for transforming for the particular task, but forget to do dimensionality reduction!

Beware unintended consequences of radically changing your lifestyle and diet on your marriage, including your sex life.

The tone of this paragraph makes me suspicious of the whole piece

Does anyone know how bioprinting human tissue could accelerate cancer treatments?

What's the value of this word association? Does sort of remind me of The Night Circus, though

Reviewer #2 (Public Review): 

The medial septum is thought to be a central hub where generation of theta rhythm is coalesced with the regulation of movement. VGluT2-expressing (glutamatergic) MS neurons were identified as interdependently controlling both movement initiation and theta rhythm genesis. Stimulation of these neurons triggers movement and theta outlasting the duration of the stimulus. The Authors explored the mechanism whereby triggered activity persists beyond stimulation and whether movement-induction is independent of the emergence of theta. In behaving head-fixed VGluT2-Cre mice they demonstrate that specific activation of VGluT2 neurons initiated motion and theta paralleled by the persistent activity of MS neurons. Blocking synaptic transmission within the MS attenuated theta induction and reduced persistent neuronal activity without affecting movement initiation by brief VGluT2-activation. The latter manipulation reliably evoked persistent firing in MS slice preparations weakened by synaptic blockers. They conclude that movement is controlled by VGluT2 neurons independent of theta whereas for the latter interaction among the glutamatergic and other major MS neuron populations (cholinergic and especially GABAergic) is pivotal. They also claim that VGluT2 neurons' persistent activity depends on the intrinsic dynamics of these neurons modulated by the MS network. The study is nicely designed, and the Authors used well-established methods. The conclusion is in line with the major findings. However, the analysis falls short in several respects and there are some missed opportunities because of which this study is only an incremental step beyond what we already know about the "third" major neuron class of the MS. 

First, the Authors simultaneously registered the activity of multiple MS units, but they did not exploit the potential of multichannel data for separating and characterizing the response and single stimulus-triggered interaction of the major MS neuron types (seemingly, only multiunit activity was used). The timing (latency and duration) and dynamics (gradually accelerating, fluctuating or dampening alteration of activity) of their stimulus-triggered activity would reveal key details about what happens to the MS network following the injection of a brief excitatory pulse. What types of cells show persistent activity: only the regular, tonically firing (putative glutamatergic) neurons or even the theta bursting ones maintain their elevated activity outlasting the stimulus? A particularly important point would be to correlate the timing of theta and movement with that of the identifiable firing pattern types. Uncovering causal relationship among the activated interacting neurons would also be interesting: would it be possible to explain altered activity of a given type by the stimulus-evoked change of another type? 

Light stimulation would have given the opportunity of identifying the stimulated VGluT2 neurons, for example by applying a train composed of very short (1 ms) tagging light pulses at the end of a recording session for the later identification and isolation of VGluT2 units. Then, the response of these optically tagged VGluT2 neurons could have been compared to the other, unidentified neuron types. 

As stated, the in vitro experiments are especially suitable for exploring the mechanisms of persistent activity. Unfortunately, the question about the mechanism remains unanswered. While we are informed about the network-independence of persistent activity, no further attempts have been made to uncover cell-autonomous processes. We could also learn from the Results that the network dampens persistent activity probably by recurrent inhibition. Demonstrating the facilitated activity of putative inhibitory (fast, rhythmic spiking) neurons locked to the light-activation of VGluT2 neurons would disclose how stimulus-outlasting activity of VGluT2 neurons is controlled by inhibition. 

Sensory stimuli reliably evoke theta and movement comparable to what was detected in response to VGluT2 neurons' activation. Hence, an opsin-lacking reporter control should be added to the results for separating the animal's reaction to light from the effect elicited by selective VGluT2-stimulation.

• about : MindGraph

mindgraph noderunner game

This is about the unfair marketing off college athletes without the athletes making money

reflections, mexico, worst parts about being back

leaving the us, court proceedings, judge, trial

Return to Mexico, challenges, continuing education, employment, cirme and violence;

Gangs, affiliation, fitting in; Police: US, mistreatment by, racial profiling; Feelings, anger;

Mexico before the US, Mexican childhood, family; Migration from Mexico, reasons, economic;

Arrests, violent crimes, felony, assault; Judge, court proceedings, deportation; Reason for return, deportation;

Reviewer #1 (Public Review): 

Previous studies have indicated that neurons in different cortical areas have different intrinsic timescales. However, the functional significance of the difference in intrinsic timescales remains to be established. In this study, Pinto and colleagues addressed this question using optogenetic silencing of cortical areas in an evidence accumulation task in mice. While head-fixed mice performed in an accumulating-towers task in visual virtual reality, the authors silenced specific cortical regions by locally activating inhibitory neurons optogenetically. The weight of sensory evidence from different positions in the maze was estimated using logistic regressions. The authors observed that optogenetic silencing reduced the weight of sensory evidence primarily during silencing, but also preceding time windows in some cases. The authors also performed a wide-field calcium imaging and derived auto-regressive term based on a linear encoding model which include a set of predictors including various task events, coupling predictors from other brain regions in addition to auto-regressive predictors. The results indicated that inactivation of frontal regions reduced the weight of evidence accumulation on longer timescales than posterior cortical areas, and the autoregressive terms also supported the different timescales of integration. 

The question that this study addresses is very important, and the authors used elegant experimental and analytical approaches. While the results are of potential interest, some of the conclusions are not very convincing based on the presented data. Some of these issues need to be addressed before publication of this work. 

Major issues: 

1) There are several issues that reduce the strength of the main conclusion regarding the timescale of integration using cortical silencing. 

a) The main analysis relied on the data pooled across multiple animals although individual animals exhibited a large amount of variability in the weights of integration across different time windows. Also, some mice which did not show a flat integration over time were excluded. This might also affect the interpretation of the analysis based on the pooled (and selected) data. How the individual variability affected the main conclusion needs to be discussed carefully. 

b) The main conclusion that the frontal areas had longer integration windows largely depends on a few data points which relied on a very small number of samples (n = 4 or 3). This is, in part, because of the use of pooled data and because the number of samples comes from the alignment of the data with different timing of inactivation. This analysis also appears to suffer from the fact that the number of sample is biased toward the time of inactivation (y = 0 which had n = 6) compared to the preceding time windows (y = 50 and 100, which had n = 4 and 3, respectively). 

c) The clustering analysis uses only 7 data points corresponding to the cortical areas examined. The conclusions regarding the three clusters appear to be preliminary. 

2) The authors' conclusion that "the inactivation of different areas primarily affected the evidence-accumulation computation per se, rather than other decision-related processes" can be a little misleading. First, as the authors point out in the Results, the effect can be "the processing and/or memory of the evidence". Given that the reduction in the weight of evidence occurs during the inactivation period, the effect can be an impairment of passing the evidence to an integration process, and not accumulation process itself. Second, as discussed above (1b), the evidence supporting a longer timescale process (characterized as "memory" here) is not necessarily convincing. Additionally, the authors' analysis on "other decision-related processes" is limited (e.g. speed of locomotion), and it remains unclear whether the authors can make such a conclusion. Overall, whether the inactivation affected the evidence accumulation process and whether the inactivation did not affect other cortical functions remain unclear from the data. 

3) Different shapes of the autoregressive term may result from different sensory, behavioral or cognitive variables by which neurons in each brain area are modulated. In other words, if a particular brain area tracks specific variables that change on a slow timescale, the present analysis might not distinguish whether a slow autoregressive term is due to the intrinsic properties of neurons or circuits (as the authors conclude), or neuronal activities are modulated by a slowly-varying variable which was not included in the present model.

Reviewer #3 (Public Review): 

This study examines how the timescale over which sensory evidence is accumulated varies across cortical regions, and whether differences in timescales are causally relevant for sensory decisions. The authors leverage a powerful behavioral paradigm that they have previously described (Pinto et al., 2018; 2019) in which mice make a left vs. right decision in a virtual reality environment based on which side contains the larger number of visual cue "towers" passed by the "running" head-fixed mouse. The probability of tower presentation varies over time/space and between the left and right sides, requiring the mice to integrate tower counts over the course of the trial (several seconds/meters). To examine the contribution of a particular cortical region to sensory evidence accumulation, the authors optogenetically inactivated activity during several sub-epochs of the task, and examined the effect of inhibition on a) behavioral performance (% correct choices) and b) the strength of the contribution of sensory evidence to the decision as a function of time/space from the inhibition onset. Finally, the authors qualitatively compared the timescale of evidence accumulation identified for each region to the autocorrelation of activity in that region, calculated from reanalyzing the author's published calcium imaging data set (Pinto et al., 2019) with a more sophisticated regression model. 

The methodology and analyses are leading edge, ultimately allowing for a comparison of evidence accumulation dynamics across multiple cortical regions in a well-controlled behavioral task, and this is a nice extension of the authors' previous studies along these lines. The study can potentially be built on in two broad directions: a) examining how circuits within any of the regions studied here function to accumulate sensory evidence, and b) addressing how these regions coordinate to guide behavior. Overall, while the study is generally strong, addressing some points would increase confidence in the interpretation of the results. Specifically: 

In describing the contribution of evidence to the decision, and how it is affected by inhibition (primarily Fig. 2), there is a confusing conflation of time and space. These are of course related by the mouse's running speed. But given that inactivation appears to consistently cause faster speeds (Fig. 2-Fig. S1), describing the effect of inhibition on the change of the weight of evidence as a function of *space* does not seem like the optimal way to examine how inactivation changes the *time*scale of evidence accumulation. The authors note in Fig. 2-Fig S1 that inactivation does not decrease speed, but it still would confound the results if inactivation increases speed (as appears to be the case; if not, it would be helpful for the authors to state it). Showing the data (e.g., in Fig. 2) as a function of time, and not distance, from laser on would allow the authors to achieve their aim of examining the timescale of evidence accumulation. 

Performing the analyses mouse by mouse, instead of on data aggregated across mice, would increase confidence in the conclusions and therefore strengthen the study. Mice clearly exhibit individual differences in how they weight evidence (Fig. 1C), as the authors note (line 81). It therefore would make sense to compare the effect of inactivation in a given mouse to its own baseline, rather than the average (flat) baseline. If the analyses must be performed on data aggregated across mice, some justification should be given, and the resulting limitations in how the results should be interpreted should be discussed. For example, perhaps there are an insufficient number of trials for such within-mouse comparisons (which would be understandable given the ambitious number of inactivated regions and epochs)? 

The method of inactivating cortical regions by activating local inhibitory neurons is quite common, and the authors' previous paper (Pinto et al., 2019) performed experiments to verify that light delivery produced the desired effect with minimal rebound or other off-target effects. Since this method is central to interpreting the results of the current study, adding more detail about these previous experiments and results would reassure the reader that the results are not due to off-target effects. Given that the cortical regions under study are interconnected, do the previous experiments (in Pinto et al., 2019) rule out the possibility that inactivating a given target region does not meaningfully affect activity in the other regions? This is particularly important given that activity is inhibited in multiple distinct epochs in this study.

Potential feelings from being affected by ASMR.

Reviewer #2 (Public Review): 

This study by Sayre et al aims to better characterize neural circuitry of the central complex (CX) in the bee, a neuropil that is important for the control of many navigational behaviors. Much of the current knowledge of the CX circuits and function currently comes from flies, while many complex navigational behaviors have been described in other insects. Thus, this study is significant because (a) it begins to close the gap between the investigations of neural circuits in the fly and behavioral work in other insects, and (b) because it allows for cross-species comparisons of CX circuits and identification of evolutionary adaptations to perform certain behaviors. 

Besides the biological insights, which I will address below, this work demonstrates an approach to electron microscopy that balances imaging throughput with dataset completeness. Rather than image the full bumble bee CX at resolution sufficient for a complete reconstruction of all neurons in the CX, the authors collect lower resolution data and focus on reconstructing main neurites of a selected number of cell types. The authors present a "projectome", a map of neural projections between neuropils of the central complex (and in several cases to sub-regions of said neuropils). However, the method has limitations that prevent the authors from (a) fully tracing neuron processes below a certain size and (b) measuring connections between neurons. Furthermore, the morphology of some neurons cannot be fully reconstructed because the respective neurons leave the imaged volume. This limits the extent and level of detail at which different neurons can be grouped into types. The authors are very transparent about these limitations. They compare three data sets with different resolution to identify which information is lost at lower resolution and focus their analysis on cell types that can be characterized to a high degree with the data at hand: columnar neurons. 

Columnar neurons have characteristic projection patterns that are tightly linked to the function of the CX circuitry. The authors provide an atlas of the different types of columnar neurons and their numbers and compare their findings to the fly and where possible the locust. This reveals a beautiful functional homology of the head direction circuitry across the three species despite different anatomical implementations. The authors also identify several differences that could point at circuit adaptations that allow bees to excel at path integration-based navigation. 

For one region, the noduli (NO), the authors collected EM data with higher resolution, which enabled characterization intra-neuropil organization. Many studies suggest that in the central complex structure is often tightly linked with function, which makes this NO dataset a valuable contribution to further understand the organization of one of the main input structures to the central complex. In the larger neuropils, the ellipsoid body (EB) and fan-shaped body (FB), the resolution of the projectome unfortunately does not allow for detailed characterization of the intra-neuropil structure. Here, instead, the authors provide a rough characterization based on layers defined by immunolabelling of TH and 5TH as well as entry sites of primary neurites. 

This work presents an important first step to better relate findings about the central complex circuitry from fruit flies to the function of the homologous circuits in (bumble)bees, which might help us understand the adaptations that give rise to the astonishing behavioral repertoire of bees such as their ability to navigate accurate on a relatively large spatial scale.

Reviewer #3 (Public Review): 

The insect central complex (CX) is a brain part, which processes multimodal sensory input to guide orientation and directed locomotion. It is built by a large number of different neuron types with intriguing and unique connectivity patterns, which together form several interconnected and midline spanning neuropils. So far, the many neuron types have mainly been identified by sparse marking of cells in a number of insect species, which allowed for precise determination of projection patterns of selected neurons. This approach has revealed an overall conserved CX architecture but it suffers from the possibility that neuron types may be missed and that the relative position of the projections among neurons cannot be determined exactly. Recently, a comprehensive connectomics map was generated for the fruit fly Drosophila melanogaster providing projection and connectivity information in unprecedented detail. While the most thorough understanding of CX function is based on the elaborate toolkit available in the fly, the most complex navigation behaviors are known from ants and bees, calling for more comprehensive work in those species. 

Sayre et al. now provide a comprehensive projectome of the bumblebee CX by using serial block face EM and subsequent 3D reconstruction of 1,300 neurons. The projectome of the entire CX is complemented by analyses of sub-parts (with focus on the noduli) with higher resolution and with some immunohistochemical data. With this work, the authors provide a very extensive and valuable resource allowing for comparisons of neuron types and projections between species. This approach has the power to reveal on one hand the conserved core of CX projections and the specific differences, which might underlie the different navigational abilities of these insects. 

On the technical level, they find that significant additional information can be gained by adding high resolution SBFEM to the less resolved overall reconstruction. Further, the authors confirm that single cell reconstructions based on confocal microscopy can be well mapped onto the projectome, allowing for adding more detail to the reconstruction in the future. 

On the scientific side, they first establish a comprehensive resource for the bumblebee CX - the first such dataset outside Drosophila. They describe the setup of the entire bumblebee CX, defining the neuron types and their projection patterns with a focus on columnar neurons. Second, they mine this resource for conserved and diverged aspects compared to Drosophila with respect to numbers of certain neural cell types, conservation of key projection circuits and - importantly - identifying specific differences between these insects. Based on this careful analysis, several hypotheses are formulated as to what the differences might mean for the functions of the bumblebee CX. For instance, the authors confirm an overall conserved CX architecture and suggest a very conserved head direction circuit. But they also find differences in fan shaped body layering, noduli organization and other aspects like the lack of obvious deltaV and FX cells. Interestingly, they describe changes in projection patterns that could underlie the different morphologies of the ellipsoid body (bar like versus donut shaped) and the potential functional meaning of a number of bee-specific aspects of noduli projections. 

In summary, the strength of the paper lies in the establishment of a quite comprehensive cell atlas of the bumblebee CX displayed in extensive and clear figures. Further, the analysis for conservation and divergence with respect to the fly CX has been done in a very careful and comprehensive way. Intriguing divergences lead to hypotheses on the functional implications. All claims are well founded in the data. 

Almost unavoidably for data gained outside the Drosophila cosmos, the resource does not have single cell resolution when it comes to the fine terminal projections and, hence, does not provide information on specific cell-cell connectivity. Further, cells with small diameter neurites are likely missing outside of the noduli dataset. The authors are aware of these issues calling their resource projectome rather than connectome. 

The paper describes very interesting differences and respective hypotheses are presented but these are not tested. <br> The reconstructions will be available as interactive datasets, which is essential for future use.

reflection, ideologies, United States

This notion of using spatial memory to encode other concepts - or even the P-A-O sytem where a 2 digit number encodes a person performing an action is an interesting idea for someone like me who forgets quite a bit.

This is the most important part of the whole article and worth coming back to time and time again.

Moore will hier zeigen, dass D Vs Tod in der Tat kontrollierte. Das treibt er auf die Spitze in dem er versucht alle möglichen Störungen oder Abweichungen auszuschließen. Aber ist diese Art jedes mögliche Zufallsereignis auszuschließen wirklich möglich in praktischen Situationen?

Moore thematisiert hier die Problematik des Begriffs "Moral Luck". Glück stellt im Sinne des Moral lucks etwas ganz anderes dar, als wir normalerweise darunter verstehen. So kommt es, dass von Glück gesprochen wird, wenn jemand jemand anderen erfolgreich umbringen konnte. Ich stimme hier Moore absolut zu und frage mich, ob es nicht einen alternativen Begriff gibt, der das, was Moral Luck ausdrücken soll, besser ausdrückt.

I'm so rarely on Twitter, but I've wondered about that blue checkmark before. I had no idea what it did.

Wow my mind is blown on these research tips. I am definitely going try and be more vigilent and apply these techniques to get even deeper on a subject. The author is so right in how we need to change the way we do things and enhance our digital literacy.

Time in the US, Gangs, Resisting affiliation

Time in the US, Learning English; Time in the US, School, Middle School

Return to Mexico, Jobs, Call Centers

Time in the US, Immigration status, Feelings, Fear, Legal status

"Yuppie diversion" is a phrase that's gonna pop into my head forever more

SciScore for 10.1101/2021.06.30.450483: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Table 2: Resources

Results from OddPub: Thank you for sharing your data.

Results from TrialIdentifier: No clinical trial numbers were referenced.

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

Results from JetFighter: We did not find any issues relating to colormaps.

• Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
• Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
• No protocol registration statement was detected.

Results from scite Reference Check: We found no unreliable references.

About SciScore

SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

Victorian fashion accessories accentuated the significance of the female body, namely the hands, face and head, and were important in a Victorian woman’s experience of gender and class; one of these accessories is the glove. A glove was an object of refinement, class, elegance and luxury; they were worn by Queen Charlotte at the time, and also by the dandy “beau” Brummell. The belief that the moral character of a woman could be perceived through her body, and read by others, was upheld in Europe during the 1800’s, and meant that gloves acted not only as protection from the elements, but also from having their class status read from the condition of their hand. Hands were a symbol of class and gender in the Victorian era, with the white, delicate hand of the middle class expressing minimum manual labour, and being idealised above that of the working class or aristocracy. With the accessory of gloves came a series of rules and etiquette to follow, with much attention being given to the condition of one's hands and gloves. This is seen as Madame Merle examines Pansy’s hand through this lens.

Geri Walton, Glove Etiquette and Rules in the 1800s, 2014, Unique histories from the 18th and 19th centuries

Ariel Beaujot, The Beauty of Her Hands: The Glove and the Making of Middle class Womanhood, 2012, Bloomsbury Publishing

Unfortunately, I've not had any similar experiences, but I do understand the point :) An example for me would be of time when I thought of a melody in my head, and I whistled the melody, and to not forget it I would pull out the recording app on my phone to capture the idea so I can then later play it on a piano and build onto it

I love that this passage goes basically like head, shoulders, knees, and toes. Makes me think about how the whole body is God's if you think about it in a sense of Christianity where they talk about how everything belongs to him and goes back to him.

reflections, opportunity

return to mexico, challenges, employment, crime and violence, records/transcripts.diploma; return to mexico, jobs, occupation

And IMO, this is exactly what a zettelkasten gives you.

Time in the US, immigration status, being secretive, hiding/lying, in the shadows, living undocumented; Time in the US, discrimination/stigmatization, racism, xenophobia; feelings, fear, unbelonging; identity, bi-cultural

With the implementation of more digital media resources, we need to develop the habits of checking our sources before we spread misinformation.

Return to Mexico, challenges, economic well-being, employment, homelessness, mental health, crime;

Careers, working, jobs, golf course, restaurant, family, providing for, documents, ID, earnings, occupations;

6th footnote

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Responses to reviewers’ comments

We thank the reviewers for their encouraging comments and helpful suggestions.

Reviewer #1

(Evidence, reproducibility and clarity (Required)):

Sanchez et al report several new findings about the adhesive protrusions on Plasmodium falciparum infected erythrocytes. Using super resolution microscopy and correlation analysis, they tracked associations between the knob protein KAHRP and erythrocyte membrane cytoskeleton proteins. They have expanded on and improved previous work on the unusual spiral structure of the knobs, which appears to be a spiral ribbon or blade and have shown a developmental pathway for the association of KAHRP with the cytoskeleton. They have localised KAHRP close to the spiral and determined its abundance in the knobs. They have also used cryo electron tomography and subtomogram averaging to get an improved 3D view of the knob structure.

The work appears to be carefully and thoroughly done, and the paper is clearly written, though non specialists in the optical methods may find it challenging to navigate through the many super resolution images and correlation plots.

Comment 1: The writing needs minor editing to fix a variety of small linguistic errors and typos. For example, line 97 "sideway positions" (they presumably mean lateral location), line 980 typo overlay, line 366 "then could reorganizes", line 435, "a predict volume".

We apologize for the linguistic errors and typos. These have been corrected in the revised manuscript.

(Significance (Required)):

Comment 2: The study provides a distinct advance on the previous state of knowledge of the structure and biochemistry of the knobs. The knobs play a key role in virulence of P. falciparum and they are quite poorly understood. Although this paper does not represent a major breakthrough in determining the molecular structure or mechanistic role of the knobs, e.g. the biochemical identity of the spiral remains unknown, the new information is valuable and likely to be important in understanding the pathogenic actions of P falciparum.

We thank the reviewer for appreciating the importance of our study. We believe that our first-time observations on the dynamics of KAHRP are a very important advance in the field and that revealing the mechanistic basis is a great challenge that at the current stage has to be left to future work.

Comment 3: The interpretation shown in Figure 7 seems fine, except for the proposal that the actin cytoskeleton is reorganised. There is no evidence for that. The cryo tomograms of the cytoskeleton in Watermeyer et al addressed this point and did not find any evidence for reorganisation of the cytoskeleton other than the insertion of the knobs.

In two previous studies we could show that actin is indeed reorganized by the parasite. It is mined from the protofilaments to generate long actin filaments that connect the knobs with the Maurer’s clefts and which are used for trafficking of cargo vesicles from the Maurer’s clefts to the erythrocyte plasma membrane (Cyklaff et al. Hemoglobins S and C interfere with actin remodeling in Plasmodium falciparum-infected erythrocytes. Science. 2011 334:1283-1286; Cyrklaff et al. Oxidative insult can induce malaria-protective trait of sickle and fetal erythrocytes. Nat Commun. 2016 7:13401). Moreover, a life-cycle resolved AFM-study of the cytoplasmic side of iRBCs by the group of CT Lim has demonstrated dramatic coarsening of the spectrin network, which must be accompanied by changes to the actin component of the skeleton (Shi, Hui, et al. "Life cycle-dependent cytoskeletal modifications in Plasmodium falciparum infected erythrocytes." PLoS One 8.4 (2013): e61170). Coarsening of the actin-spectrin network would imply a decrease of the amount of actin in the network, which is consistent with its use in the parasite-derived long actin filaments.

\*Referee Cross-commenting***

I also agree with the other 2.

Reviewer #2

(Evidence, reproducibility and clarity (Required)):

Malaria parasites replicate within circulating red blood cells (RBC). During parasite maturation, the parasite coordinates extensive modification of the host cell, including structural modifications of the RBC cytoskeleton and surface membrane. These host cell alterations play crucial roles in the pathology of malaria, including vascular adhesion by parasitised cells and avoidance of splenic clearance, and so are of great interest. This interesting manuscript describes a detailed examination of the role in these RBC modifications of a well-described parasite protein called KAHRP. Using a combination of cutting-edge super-resolution microscopy, cryo-electron tomography, immuno-EM, SEM and parasite mutagenesis, the authors provide evidence that KHARP localisation alters during parasite maturation but eventually becomes closely associated with the previously-described spiral structures that underlie infected RBC surface membrane protrusions called knobs. The authors provide improved resolution of the spiral formations, generate a quantitative estimate of the number of KAHRP molecules per knob, and provide a model for the role of KAHRP in attaching other proteins to the spirals based on their observations.

In general, this study is thorough and well-performed, and the conclusions drawn are well-supported by the data. Although the work does not advance understanding of knob function or the parasite components that form the bulk of the spirals, it provides an interesting and useful contribution to understanding of the manner in which this important pathogen manipulates its host cell.

We thank the reviewer for appreciating the importance of our study and in acknowledging that it is an important intermediate step towards a complete understanding of skeleton remodelling by the parasite.

I have just a few minor suggestions that should improve the manuscript.

Comment 1: Line 91 (Page 2 paragraph 2). It would be greatly helpful here if the authors could provide a more detailed background on the makeup of the RBC cytoskeleton, and in particular the interactions between beta-spectrin and the actin protofilaments of the junctional complexes. The authors should make it clear that the actin-binding domain of beta-spectrin comprises 2 calponin like domains, and that these are attached to the end of the tandem spectrin repeat domains that make up the bulk of the molecule.

We thank the reviewer for this helpful suggestion and have added a new paragraph to the results section providing detailed background information on the makeup of the RBC membrane skeleton. The new text reads as follows:

“Major components of the red blood cell membrane skeleton are spectrin and actin filaments (Fig. 1B). The spectrin filaments consist of α- and ß-spectrin, which form α2ß2 heterotetramers by head-to-head association of two αß dimers (Lux, 2016; Machnicka et al., 2014). The N-termini of the ß-spectrin subunits are positioned at the tail ends of the heterotetramer and contain two calponin homology (CH) domains for binding to actin protofilaments consisting of 6 to 8 actin monomers in each of the two strands (Lux, 2016; Machnicka et al., 2014). Protein 4.1R strengthens the spectrin actin interaction (Lux, 2016; Machnicka et al., 2014). Groups of up to six spectrin heterotetramers can attach to an actin protofilaments, resulting in a pseudohexagonal meshwork (Lux, 2016). Ankyrin binds to the C-terminal domain of ß-spectrin and connects integral membrane proteins with the actin spectrin network in an ankyrin complex (Lux, 2016; Machnicka et al., 2014).”

Comment 2: Line 97 "These values are slightly larger than the reported physical dimension of the protofilament...". Please provide these reported dimensions here, as well as relevant references.

The requested information is now provided. The sentence now reads as follows:

“These values are slightly larger than the reported physical dimension of the protofilaments of ~37 nm (Lux, 2016) and might be explained by the lateral localization of the spectrin binding sites and the additional sizes of the primary and secondary antibody trees used to detect the two targets.”

Comment 3: Line 366 "reorganize"

The spelling mistake has been corrected.

(Significance (Required)):

Comment 4: This is a useful technical advance in understanding of the structure of the P. falciparum-infected red blood cell, and builds on the work of Watermeyer et al. (2016). The study should certainly be of interest to most malaria researchers, particularly those interested in the pathobiology of the organism.

We thank the reviewer for supporting our study.

\*Referee Cross-commenting***

I fully agree with and endorse the comments of the other 2 reviewers.

Reviewer #3

(Evidence, reproducibility and clarity (Required)):

The binding of P. falciparum infected erythrocyte (iRBCs) to the endothelium is mediated by protuberances (knobs). These knobs are assembled by a multi-protein complex at the iRBC surface. It acts as a scaffold for the presentation of the major virulence antigen, P. falciparum Erythrocyte Membrane Protein-1 (PfEMP1). The knob-associated histidine-rich protein (KAHRP) is an essential component of the knobs and therefore essential for the binding of iRBC to the endothelium under physiological conditions. This manuscript focusses on the knob architecture and KAHRP localization.

Comment 1: It is, at least for this reviewer - hard to assess how the "preparation of exposed membranes by hypotonic shock" and the analysis of the "inverted erythrocyte membrane ghosts" is i) reflective of the physiological architecture within the iRBC and ii) how the authors exclude remnants from Maurers clefts (MCs) in their preparation. The latter appears especially important for the interpretation of dynamic KAHRP repositioning, as MCs are mobile in early stages and non-mobile later on (e.g. McMilian et al. 2013, Grüring et al. 2011) and the authors observed at least some MAHRP1 signal (Figure S8), which is hard to interpret by the single representative image provided.

We understand the reviewer’s concerns, but are convinced that we have done the necessary controls to evaluate our approaches. For example, we evaluated the exposed membrane approach by investigating uninfected erythrocytes and comparing the findings with literature reports (see Figure 1). A high degree of agreement was observed. We further would like to point out that the exposed membrane approach has been successfully used by several other studies referenced in the manuscript (Dearnley et al., 2016; Looker et al., 2019; Shi et al., 2013). Please also allow us to explain why we have used exposed membranes instead of whole cells. The reason is that the hemozoin produced by the parasite interferes with STED microscopy, resulting in a quick and strong build-up of resonance energy in the specimen and, eventually, in the disruption of the cell.

With regard to the question of whether remnants of Maurer’s clefts are present in our preparations, we do not think so, at least we never observed membrane profiles reminiscent of Maurer’s clefts in SEM images of exposed membranes (see figure at the end of the response letter). Irrespectively, we will double check this result using STED imaging of exposed membranes treated with an antibody against the established Maurer’s clefts marker SBP1. These data could be added to a revised manuscript.

Comment 2: line 173: Please provide a detailed description about parasite synchronization (also absent in the methods section).

A detailed description including references are now added to the methods section:

“For synchronization of cultures, schizont-infected erythrocytes were sterile purified using a strong magnet (VarioMACS, Miltenyi Biotec) (Staalsoe et al., 1999) and mixed with fresh erythrocytes to high parasitaemia. 5000 heparin units (Heparin-sodium 25000, Ratiopharm) were added and the cells were returned to culture for 4 hrs (Boyle et al., 2010). Following the treatment with heparin, cells were washed with pre-warmed supplemented RMPI 1640 medium and then returned to culture for 2 hrs to allow for re-invasion of erythrocytes. Subsequently, cells were treated with 5% sorbitol to remove late parasite stages (Lambros and Vanderberg, 1979).”

Comment 3: line 136: Please re-check nomenclature of "PHIS1605w" (mixed nomenclature used throughout the manuscript). I suggest to use either LyMP or the up-to-date ID PF3D7_0532400.

We apologize for the oversight and now consistently use the ID PF3D7_0532400.

Comment 4: Please provide source and references for PfEMP1, MAHRP1 and "PHIS1605w" antibodies that are used. I cannot find them in the methods section or in Table S1.

We apologize for the oversight and now provide the requested information in the amended Table S1.

Comment 5: line 165: Warncke et al. (2016) appears to be misplaced as an appropriate MAHRP1 reference.

We now cite the original MAHRP1 publication by Spycher et al. 2003.

Comment 6: line 159: the sentence "The strong cross-correlation between KAHRP and actin is consistent with previous cryo-electron tomographic analysis showing long actin filaments connecting the knobs with Maurer's clefts in trophozoites (Cyrklaff et al., 2012; Cyrklaff et al., 2011; Cyrklaff et al., 2016)" could be moved to the discussion section.

The sentence was indeed redundant with a section in the discussion and was removed.

Comment 7: line 199: The text refers to Fig. 9AB - but should refer to 4AB or suppl. 11.

We are sorry for this mistake and now refer to the correct figures in the revised manuscript.

Comment 8: Fig. 4: A solid average for the number of subtomograms, but please provide information about what the arrowheads (4E) indicate.

Thank you for this comment. The arrowheads indicate peripheral crown-like densities. We have updated the figure legend to clarify this issue.

Comment 9: The "flexible periphery" is likely a combination of flexibility and occupancy as the average was made from subtomograms with varying number of turns in the spiral. As occupancy is likely a significant contributing factor to the average that should be discussed or at least mentioned.

Thank you for this important comment. Indeed, a significant variation was observed between the individual knobs. The spirals have variable diameter, and the number of peripheral proteins also varied. We added measurements to the supplementary figure 11D. In addition, we update the text and extended the discussion.

Comment 10. On that note, did the authors try and classify based on number of turns prior to averaging and if so did the authors see any differences in structures between few turn and many turn spirals?

We attempted several classifications on the full knobs with variable masks. However due to a limited number of particles in the dataset we could not converge to stable solutions. Instead, we decided to adopt the subboxing strategy where locally ordered segments at the periphery could be analyzed. This showed several structural snapshot at the periphery of the knobs.

Comment 11. What size mask was used? Was it a soft sphere around the core or big enough for the knobs with multiple spiral turns?

While we attempted several alignments and classifications with variable masks, the final refinement and measurement of FSC was performed with a soft contour mask mask. We overlaid it with the structure in Figure S11F and uploaded it as a part of the EMDB deposition. We further show the masks used in this study in a new Figure S14.

Comment 12. It might be useful for readers who are not familiar with Dynamo to provide a little bit more information about how the initial reference was produced. Additionally more information about the sub-boxing strategy ie: spacing etc. would helpful.

Thank you very much for the suggestion. For the initial reference we manually aligned all the particles, summed them up and low-pass filtered them. We now describe it in the methods section.

For the subboxing procedure we added more description to the main text:

“40 segments were extracted at the radius of the 2nd and 3rd spirals followed by their classification into structural classes.”

We further extended and simplified the description in the results section (line ~221).

Comment 13: Fig. 5 Additional (earlier) maturation stages of the iRBC with Ni2+NAT-gold-labelling would be a nice add on - this could help confirm the model and would itself be a control for the later stage labelling.

We thank the reviewer for this insightful suggestion. We are currently performing the proposed experiment and will include it in a revised version of the manuscript.

Comment 14: line 637: DMSI typo and please provide the supplier for DMSI (DSM1).

We corrected the typographic error and now provide the name of the supplier.

Comment 15: Figure 7: Please provide what the purple arrows indicate.

The figure legend has been updated.

Comment 16: Fig S11D: The labels X, Y and Z are confusing, describing the slicing axis as "XZ, YZ and XY" view is more intuitive.

Done as suggested by the reviewer.

Comment 17: Figure S13 B: WBs are cropped. Please provide un-cropped WB.

Uncropped Western blots will be provided in the revised manuscript.

(Significance (Required)):

In general, I highly appreciated the solid data and its thorough analysis of the microscopy data. The authors investigate the structural organization of knobs in iRBCs using high-resolution imaging techniques including STED and PALM super-resolution microscopy-based approaches and electron tomography. The beauty of this paper is that it does nicely re-investigate knob architecture in iRBC (e.g. Watermeyer et al., 2016, Cutts et al., 2017, Looker et al., 2019, McHugh et al., 2020) and provides some intriguing KHARP co-localization with cytoskeleton components. The downside of it is that - by nature - it is descriptive (and the data rather confirmative) and as it stands does not provide us with a deeper molecular dissection of the knob associated structure and its cellular function.

We thank the reviewer for appreciating our study and would like to emphasize the following novelties in our study:

• We show that the association of KAHRP with membrane skeletal components is highly dynamic and changes as the parasite matures. Our results on the dynamics of KAHRP organization reconciles conflicting reports in the literature, and establish for the first time a dynamical model for KAHRP organization.
• We further show that KAHRP finally assembles at remnant actin-junctional complexes devoid of the actin-capping factors adducin and tropomodulin.
• We further quantified the number of KAHRP molecules per knob and show that KAHRP is present as 60 copies per knob, a number one order of magnitude greater than previously thought.
• Last but not least, we provide a 35 Å map of the spiral scaffold underlaying knobs and show that KAHRP associates with the spiral scaffold.

• We conclude by providing a novel model on the biological function of KAHRP by proposing that KAHRP acts as a glue that connects spectrin and parasite-remodeled actin filaments with the knob spiral.

  \*Referee Cross-commenting***

Fully agreed.

Boyle, M.J., Wilson, D.W., Richards, J.S., Riglar, D.T., Tetteh, K.K., Conway, D.J., Ralph, S.A., Baum, J., and Beeson, J.G. (2010). Isolation of viable Plasmodium falciparum merozoites to define erythrocyte invasion events and advance vaccine and drug development. Proc Natl Acad Sci U S A 107, 14378-14383.

Lambros, C., and Vanderberg, J.P. (1979). Synchronization of Plasmodium falciparum erythrocytic stages in culture. J Parasitol 65, 418-420.

Lux, S.E.t. (2016). Anatomy of the red cell membrane skeleton: unanswered questions. Blood 127, 187-199.

Staalsoe, T., Giha, H.A., Dodoo, D., Theander, T.G., and Hviid, L. (1999). Detection of antibodies to variant antigens on Plasmodium falciparum-infected erythrocytes by flow cytometry. Cytometry 35, 329-336.

Author Response:

Reviewer #1 (Public Review):

This paper examines muscle activity at single muscle level during Drosophila ecdysis (adult hatching) behavior. The premise is that quantifying behavior or motor neuron activity is insufficient to understand how the CNS generates behavior - it is also critical to quantify muscle activity. They show that abdominal body wall muscles generate stereotyped patterns of activity during four developmental stages; (phase 0, stochastic activity; phase 1-3, each with different patterns of activity. Co-active groups of muscles form "syllables" which are used in different combinations to generate the stereotyped activity seen in phases 1-3. This analysis was facilitated by use of a convoluted neural network. Interestingly, they found examples where muscle contraction did not match muscle activity (GCaMP elevation), showing the importance of measuring both attributes.

In addition to mapping the stereotyped muscle activity at single muscle resolution in the generation of ecdysis behavior, they find that phase 1 and 3 are quite variable, and speculate that other constraints on the CNS output (e.g. during larval locomotion) may prevent a sharpening up of muscle patterns. They show that the hormone ETH is required for initiating phase 1, and the neuromodulators bursicon and CCAP are required for initiating phase 2. Failure to initiate either phase is lethal. Lastly, they show that in addition to initiating phase 1 or 2, the hormone/neuromodulators result in more coherent muscle activity.

Overall this study sets the stage for a detailed analysis of motor neuron function in driving muscle activity patterns, and then further into the CNS to understand the role of premotor neurons. Ecdysis behavior has the potential to be a powerful system for understanding how the CNS generates behavior at the single muscle /single motor neuron level, as well as for understanding how neuromodulators act to regulate muscle/motor neuron activity.

The figures are almost all too small to see the salient information, and the color scheme is often difficult to resolve. Please enlarge the key aspects of the figures; and try to use more distinctive colors where critical comparisons need to be made. Some examples: left/right colored lines in 1G; panel 3D; lines in 3E; all data in 5G (this is the worst for tiny data); 6C,D,J; all of 7.

Thank you for your thoughtful review and your suggestions on how to improve the manuscript. Some figure panels (e.g. 5G) have been completely replaced. The others mentioned have been divided into multiple figures or panels, which allowed us to enlarge the material in each. Fig. 7 was deleted from the revised manuscript because it was generally found unhelpful. We also felt that the other revisions rendered this figure unnecessary. The revised manuscript now has 11 main figures and 9 figure supplements with more generous layouts for individual panels so that details are more easily resolved. In addition, we attempted to improve the color scheme to facilitate clarity, using the color palette recommended for the color-blind. Other specific changes are referenced in our responses to individual concerns below.

Reviewer #2 (Public Review):

The manuscript by Diao et al. is an important extension of their eLife paper of 2017. Their development of new tools that allow them to follow Ca2+ transients in single muscle fibers over the whole animal through the behavioral sequence and also to independently monitor the Ca2+ transients in the endplates of the motor neurons that innervate these muscles. Their goal is to break down the movements that control the ecdysis sequence into elemental "syllables" and then to defined the role of these syllables in constructing progressively complex behavioral programs and as targets of neuropeptide modulation.

A crucial behavior that occurs during P1 in higher flies is the movement of the gas bubble but this event is largely ignored in the paper. Prior to pupal ecdysis, gas is expelled into the posterior puparial space and then actively translocated, via muscular contractions of the body wall, to the anterior end of the puparium during the latter portion of P1 (shown nicely in the author's 2017 Video). A detailed study by C.G. Chadfield & J.C.Sparrow (1985. Dev. Genetics 5: 103) of pupal ecdysis in Drosophila emphasized the importance of this translocation for head eversion. When they simply removed the operculum at the start of bubble movement, then the gas bubble could not push the animal backwards in the puparial case and head eversion could not occur. However, they saw normal pupation and head eversion if the removed operculum was immediately replaced and sealed down with petroleum jelly.

During translocation, the bubble moves in a fragmented fashion between the pupal cuticle and the puparium. Ignoring this movement leads to statements like on line 378 "Because pupal ecdysis is independent of environmental factors and executed in the absence of competing physiological needs, it is likely that its variability is intrinsic to the ecdysis network." For the pupating animal, its "environment" is the inside of the puparial case and the moving bubble is an unpredictable variable in this environment. The trajectory and route of bubble movement is not fixed, and it is likely that variation in sensory feed-back from the gas movement explains the motor variability and reduced stereotypy during P1. The role for proprioception during this phase is likely to inform the CNS of the progression of the bubble fragments. The author's finding that the blockage of proprioceptors suppresses the behavior progression could mean that this sensory information is needed to signal that an anterior space has been produced, and without this signal, the behavior does not progress to its next phase. This should be addressed in the text if not experimentally.

We very much appreciate the reviewer’s point that the environment within the puparium may affect the pupa’s motor performance. We have now amended our comment on environmental influences to include this point (ll. 479-481 [515-517]), and we elaborate in the Discussion on conditions within the puparium that may influence movement and sensory processing (ll. 457-477 [493-513]). Following the reviewer’s advice, we note that the gas bubble and its dispersion during P1 must be considered a possible determinant of pupal movement. In addition, we mention other possible determinants that we did not previously discuss, namely substrate and surface tension interactions between the body wall, puparium, and residual molting fluid. In line with the Reviewer’s point that understanding the environment of the puparium is critical, we stress the need to account for all external forces acting on the pupal body to achieve a complete understanding of the pupal motor output. In the Discussion, we also now mention the Reviewers’ interesting hypothesis that creation of the anterior space at the end of P1 may provide sensory information necessary for progression of the behavioral sequence (ll. 534-535 [601-602])

Another aspect of the background that is missing is considering earlier studies on the ontogeny of behaviors leading up to ecdysis/hatching. Notable are studies of the progressive construction of the flight motor program during metamorphosis in moths (Kammer & Rheuben 1976 J. Exp. Biol. 65:65.) and a similar feature of assembly of motor programs prior to hatching in Drosophila (Crisp et al., 2008 Development 135:3707). In the moth studies, complex motor programs were gradually assembled during ontogeny with motor neurons firing but without muscle contraction (as the authors see in prepupae during P0 - Fig 2C). A lack of excitation-contraction coupling in the moth prevents muscle movement through most of development. This suppression of contraction is essential because prior to production of adult cuticle, muscle contraction would rip the developing animal apart. The same requirement to suppress muscle contraction would be seen in fly prepupa until sufficient pupal cuticle has been secreted to prevent rupture from actual muscle contractions! This should be addressed in the text.

We thank the reviewer for his comments and for the references on motor program assembly. We agree that this is topic deserved more attention than it was originally given. We have now amended our discussion of P0 to contextualize our observations, pointing to the previous literature on both suppressed muscle activity and latent motor programs observed in other developing animals (ll. 487-500 [523-536]).

Besides not being explicit about how the syllables combine to build the eight basic movements, it is not clear how these basic movements then combine to support the major behaviors of each phase. This is seen in P1, where we see that swing and brace movements can co-occur (e.g., Fig 3D) but is a swing on one side always associated with a brace on the other? What are their phase relationships? Does their temporal association remain stable as the bouts progress? Another example is in Phase 3. There appear to be 5 basic behaviors associated with bouts in Phase 3. The example in Fig 1H shows double peak bouts in phase 3, and the bulk Ca data show a preponderance of double peaks. The different shapes suggest that there are different movements during the two peaks. Their discussion of P3 movements (around line 273), though, does not address this feature of the double peaks. The example in Fig 7A suggests that some movements, like the PostSwing occur at half the frequency of other movements such as the PostCon and AntComp. Is this the basis of the double peaks and how is that reflected in the movements that are finally produced? This should be addressed in the text.

We regret the confusion on these points. As described there, we have made numerous changes to the manuscript to clarify how elements of behavior at one level (e.g. movements) derive from lower-level elements (e.g. syllables) and are used to build higher-level elements (e.g. phases). We describe the phase relationships at all levels for P1 and P2 and summarize the more variable constituents of P3 movements in the text (Figs. Fig. 7D, E and ll. 247-275 [274-302]). The specific questions raised by the reviewer are also now answered in the text. In brief, early P2 bouts (roughly those prior to head eversion) differ from later bouts in containing only a Swing. Later bouts contain in addition to the Swing a Brace performed concomitantly on the contralateral side of the body (l. 182-183 [197-199]). The movements contributing to the peak-double peak motif common to P3 are now more carefully described at ll. 351-360 [383-393])

One approach that I did not find useful was dividing the analysis into compartments - anterior versus posterior and dorsal-lateral-ventral. This may provide a way of generating some statistical analysis, but it did not illuminate anything about the behavior. The line between anterior and posterior segments seems to be arbitrary. Of course, it is important to know if there is directionality of movement [waves going anteriorly versus posteriorly], but beyond that, I am not sure what it adds. [Indeed, it made Fig 7 very confusing!] Also, I could not see a rationale for considering separate dorsal-lateral-ventral compartments. This should be addressed in the text.

We thank the reviewer for this question, which we now address in a revised section of the Discussion on the topic of neuromodulation and compartmentalization (ll. 539-588 [606-655]). To briefly expand upon our explanation there, we think that compartmental activity allows a useful coarse-grained description of the sequential body wall contractions that give rise to movement as indicated by the SequenceMatcher similarity scores (Fig. 6E in the revised manuscript). Second, and more important, we think that how activity flows across compartments provides clues about both the central organization and the neuromodulatory control of ecdysis behavior. Both ETHRB and CCAP neuron suppression exert selective effects on A-P compartments. ETHRB neuron suppression blocks the Lift, a movement of the posterior compartment, while suppressing CCAP neurons prematurely terminates the first (and only) swing-like movement by blocking its progression into the anterior compartment. Additionally, the distribution of CCAP-R appears to reflect mechanisms for selectively regulating distinct D-V compartments. Myotopic maps of larval motor neuron dendrites show that MNs innervating dorsal and ventral muscles are spatially segregated from those innervating lateral muscles and have distinct inputs. This suggests distinct regulation of activity in D-V and L compartments and likely distinct functions. Importantly, CCAP-R is expressed only in motor neurons of the D and V compartments, but in the L compartment it is expressed in muscles. As we suggest, this may allow the different regulatory mechanisms of compartmental regulation to synergize during P2. Finally, our subdivision of the A-P axis at the boundary between segments 5 and 6 has both anatomical and functional importance. At the pupal stage, selective muscle loss imposes differences in muscle composition of segments anterior and posterior to this boundary. Most importantly, anterior segments contain M12, which is a major contributor to behavior only after P1 and is targeted by neuromodulatory Type III terminals containing CCAP and Bursicon. In addition, the A-P boundary also conforms to the functionally and neuroanatomically defined “hinge” region of Tastekin et al. (2018, eLife,), which regulates the switch from forward to backward movement in the larva. Because the compartmental subdivisions we define conform with neuroanatomical differences and appear to underlie functional differences, our working hypothesis is that they will be important landmarks for mapping behaviorally relevant CNS activity as we begin to image it in the next phase of our work.

This actually makes me think about battle at the time. It would make sense that we would reuse armor and weapons from those who had died on the battlefield, whether enemy or friend. They would likely be sent somewhere to be refurbished or rebranded first, but it makes a lot of sense and that is one more aspect about the times that I did not know about.

A multi-decade effort has helped the country better understand historic injustice, what it meant to be enslaved, and how that legacy shapes the country today. The National Museum of African American History and Culture opened in 2016 with extensive exhibitions chronicling the impact of slavery. Historic homes, like Monticello, have dealt head-on with the issue; a new exhibit that opened at the institution this summer explores President Thomas Jefferson’s relationship with an enslaved woman, Sally Hemings.

And in Montgomery, Alabama, the National Memorial to Peace and Justice, a stirring monument and museum dedicated to victims of lynching and racial injustice, opened its doors this spring, aiming to create what the founders call “a sober, meaningful site where people can gather and reflect on America’s history of racial inequality.”

Julia Chatterley. (2021, May 21). "I think the #EU needs to be on the right side of history.” @JNkengasong Head of @AfricaCDC welcomes news of $1.2 bn EU investment but says the continent can produce vaccines at scale IF #patents are waived. ‘The time is always right to do the right thing...’ PART I https://t.co/N1Xw9QLFhu [Tweet]. @jchatterleyCNN. https://twitter.com/jchatterleyCNN/status/1395755122320416775

Define exactly what horizontal and vertical integrations are.

Reviewer #1 (Public Review):

Cohen and Baldassano study the neural response to narrative videos over development in a very large sample (N > 400), especially for an fMRI study. They investigate these neural responses using sophisticated computational analyses, including intersubject correlations and hidden Markov models of event segmentation. These outstanding features of the study are especially impressive given the naturalistic nature of the experimental paradigm, i.e. having participants watch narrative movies (cartoons). Analysing such continuous rather than trial-based data in a meaningful way is challenging, and Cohen and Baldassano's efforts at this are highly impressive.

Cohen and Baldassano reveal that, with age, cortical event segmentation becomes more consistent over participants. Furthermore, event representations shift earlier in time, possibly reflecting increased anticipation of upcoming events. The relatively unconstrained nature of the stimuli does make it difficult to fully rule out all possible alternative interpretations of the findings, such as differences in eye movements and head motion between age groups.

Both the insights gleaned from these results, as well as the experimental approach developed here, are likely to have a big impact on the field of developmental neuroscience.