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Referee #3

Evidence, reproducibility and clarity

Summary:

In the manuscript by Frommeyer, Gigengack et al. entitled "The UAP56 mRNA Export Factor is Required for Dendrite and Synapse Pruning via Actin Regulation in Drosophila" the authors surveyed a number of RNA export/processing factors to identify any required for efficient dendrite and/or synapse pruning. They describe a requirement for a general poly(A) RNA export factor, UAP56, which functions as an RNA helicase. They also study links to aspects of actin regulation.

Overall, while the results are interesting and the impact of loss of UAP56 on the pruning is intriguing, some of the data are overinterpreted as presented. The argument that UAP56 may be specific for the MICAL RNA is not sufficiently supported by the data presented. The two stories about poly(A) RNA export/processing and the actin regulation seem to not quite be connected by the data presented. The events are rather distal within the cell, making connecting the nuclear events with RNA to events at the dendrites/synapse challenging.

There are a number of specific statements that are not supported by references. See, for example, these sentences within the Introduction- "Dysregulation of pruning pathways has been linked to various neurological disorders such as autism spectrum disorders and schizophrenia. The cell biological mechanisms underlying pruning can be studied in Drosophila." The Drosophila sentence is followed by some specific examples that do include references. The authors also provide no reference to support the variant that they create in UAP56 (E194Q) and whether this is a previously characterized fly variant or based on an orthologous protein in a different system. If so, has the surprising mis-localization been reported in another system?

Specific Comments:

Figure 1 shows the impact of loss of UAP56 on neuron dendrite pruning. The experiment employs both two distinct dsRNAs and a MARCM clone, providing confidence that there is a defect in pruning upon loss of UAP56. As the authors mention screening against 92 genes that caused splicing defects in S2 cells, inclusion of some examples of these genes that do not show such a defect would enhance the argument for specificity with regard to the role of UAP56. This control would be in addition to the more technical control that is shown, the mCherry dsRNA. Later the authors demonstrate a delay in the accumulation of the Mical protein, so if they assayed these pruning events at later times, would the loss of UAP56 cause a delay in these events as well? Such a correlation would enhance the causality argument the authors make for Mical levels and these pruning events.

Figure 2 provides data designed to test the requirement for the ATPase/helicase activity of UAP56 for these trimming events. The first observation, which is surprising, is the mislocalization of the variant (E194Q) that the authors generate. The data shown does not seem to indicate how many cells the results shown represent as a single image and trace is shown the UAP56::GFP wildtype control and the E194Q variant.

Given the rather surprising finding that the ATPase activity is not required for the function of UAP56 characterized here, the authors do not provide sufficient references or rationale to support the ATPase mutant that they generate. The E194Q likely lies in the Walker B motif and is equivalent to human E218Q, which can prevent proper ATP hydrolysis in the yeast Sub2 protein. There is no reference to support the nature of the variant created here.

Given the surprising results, the authors could have included additional variants to ensure the change has the biochemical effect that the authors claim. Previous studies have defined missense mutations in the ATP-binding site- K129A (Lysine to Alanine): This mutation, in both yeast Sub2 and human UAP56, targets a conserved lysine residue that is critical for ATP binding. This prevents proper ATP binding and consequently impairs helicase function. There are also missense mutations in the DEAD-box motif, (Asp-Glu-Ala-Asp) involved in ATP binding and hydrolysis. Mutations in this motif, such as D287A in yeast Sub2 (corresponding to D290A in human UAP56), can severely disrupt ATP hydrolysis, impairing helicase activity. In addition, mutations in the Walker A (GXXXXGKT) and Walker B motifs are can impair ATP binding and hydrolysis in DEAD-box helicases. Missense mutations in these motifs, like G137A (in the Walker A motif), can block ATP binding, while E218Q (in the Walker B motif)- which seems to be the basis for the variant employed here- can prevent proper ATP hydrolysis.

The co-IP results shown in Figure 2C would also seem to have multiple potential interpretations beyond what the authors suggest, an inability to disassemble a complex. The change in protein localization with the E194Q variant could impact the interacting proteins. There is no negative control to show that the UAP56-E194Q variant is not just associated with many, many proteins. Another myc-tagged protein that does not interact would be an ideal control.

With regard to Figure 3, the authors never define EB1::GFP in the text of the Results, so a reader unfamiliar with this system has no idea what they are seeing. Reading the Materials and Methods does not mitigate this concern as there is only a brief reference to a fly line and how the EB1::GFP is visualized by microscopy. This makes interpretation of the data presented in Figure 3A-C very challenging. The data shown for MICAL MS2 reporter localization in Figure 4 is nice, but is also fully expected on many former studies analyzing loss of UAP56 or UAP56 hypomorphs in different systems. While creating the reporter is admirable, to make the argument that MICAL localization is in some way preferentially impacted by loss of UAP56, the authors would need to examine several other transcripts. As presented, the authors can merely state that UAP56 seems to be required for the efficient export of an mRNA transcript, which is predicted based on dozens of previous studies dating back to the early 2000s.

Minor (and really minor) points:

In the second sentence of the Discussion, the word 'developing' seems to be mis-typed "While a general inhibition of mRNA export might be expected to cause broad defects in cellular processes, our data in develoing c4da neurons indicate that loss of UAP56 mainly affects pruning mechanisms related to actin remodeling."

Sentence in the Results (lack of page numbers makes indicating where exactly a bit tricky)- "We therefore reasoned that Mical expression could be more challenging to c4da neurons." This is a complete sentence as presented, yet, if something is 'more something'- the thing must be 'more than' something else. Presumably, the authors mean that the length of the MICAL transcript could make the processing and export of this transcript more challenging than typical fly transcripts (raising the question of the average length of a mature transcript in flies?).

Significance

Understanding how post-transcriptional events are linked to key functions in neurons is important and would be of interest to a broad audience.

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Referee #2

Evidence, reproducibility and clarity

In this paper, the authors describe dendrite pruning defects in c4da neurons in the DEXD box ATPase UAP56 mutant or in neuronal RNAi knockdown. Overexpression UAP56::GFP or UAP56::GFPE194Q without ATPase activity can rescue dendrite pruning defects in UAP56 mutant. They further characterized the mis-localization of UAP56::GFPE194Q and its binding to nuclear export complexes. Both microtubules and the Ubiquitin-proteasome system are intact in UAP56RNAi neurons. However, they suggest a specific effect on MICAL mRNA nuclear export shown by using the MS2-MCP system., resulting in delay of MICAL protein expression in pruned neurons. Furthermore, the authors show that UAP56 is also involved in presynaptic pruning of c4da neuros in VNC and Mica and actin are also required for actin disassembly in presynapses. They propose that UAP56 is required for dendrite and synapse pruning through actin regulation in Drosophila. Following are my comments.

Major comments

1. The result that UAP56::GFPE194Q rescues the mutant phenotype while the protein is largely mis-localized suggests a novel mechanism or as the authors suggested rescue from combination of residual activities. The latter possibility requires further support, which is important to support the role mRNA export in dendrite and pre-synapse pruning. One approach would be to examine whether other export components like REF1, and NXF1 show similar mutant phenotypes. Alternatively, depleting residual activity like using null mutant alleles or combining more copies of RNAi transgenes could help.

2. The localization of UAP56::GFP (and E194Q) should be analyzed in more details. It is not clear whether the images in Fig. 2A and 2B are from confocal single sections or merged multiple sections. The localization to the nuclear periphery of UAP56::GFP is not clear, and the existence of the E194Q derivative in both nucleus and cytosol (or whether there is still some peripheral enrichment) is not clear if the images are stacked.

3. The Ub-VV-GFP is a new reagent, and its use to detect active proteasomal degradation is by the lack of GFP signals, which could be also due to the lack of expression. The use of Ub-QQ-GFP cannot confirm the expression of Ub-VV-GFP. The proteasomal subunit RPN7 has been shown to be a prominent component in the dendrite pruning pathway (Development 149, dev200536). Immunostaining using RPN7 antibodies to measure the RPN expression level could be a direct way to address the issue whether the proteasomal pathway is affected or not.

4. Using the MS2/MCP system to detect the export of MICAL mRNA is a nice approach to confirm the UAP56 activity; lack of UAP56 by RNAi knockdown delays the nuclear export of MS2-MICAL mRNA. The rescue experiment by UAS transgenes could not be performed due to the UAS gene dosage, as suggested by the authors. However, this MS2-MICAL system is also a good assay for the requirement of UAP56 ATPase activity (absence in the E194Q mutant) in this process. Could authors use the MARCM (thus reduce the use of UAS-RNAi transgene) for the rescue experiment? Also, the c4da neuronal marker UAS-CD8-GFP used in Fig4 could be replaced by marker gene directly fused to ppk promoter, which can save a copy of UAS transgene. The results from the rescue experiment would test the dependence of ATPase activity in nuclear export of MICAL mRNA.

5. The UAP56 is also involved in presynaptic pruning through regulating actin assembly, and the authors suggest that Mical and cofilin are involved in the process. However, direct observation of lifeact::GFP in Mical or cofilin RNAi knockdown is important to support this conclusion.

Minor comments

1. RNA localization is important for dendrite development in larval stages (Brechbiel JL, Gavis ER. Curr Biol. 20;18(10):745-750). Yet, the role of UAP56 is relatively specific and shown only in later-stage pruning. It would need thorough discussion.

2. Could authors elaborate on the possible upstream regulators that might be involved, as described in "alternatively, several cofilin upstream regulators have been described (Rust, 2015) which might also be involved in presynapse pruning and subject to UAP56 regulation" in Discussion?

3. In Discussion, the role of cofilin in pre- and post-synaptic processes was described. The role of Tsr/Cofilin regulating actin behaviors in dendrite branching has been described in c3da and c4da neurons (Nithianandam and Chien, 2018 and other references) should be included in Discussion.

4. The authors speculate distinct actin structures have to be disassembled in dendrite and presynapse pruning in Discussion. What are the possible actin structures in both sites could be elaborated.

Significance

The study initiated a genetic screen for factors involved in a dendrite pruning system and reveals the involvement of nuclear mRNA export is an important event in this process. They further identified the mRNA of the actin disassembly factor MICAL is a candidate substrate in the exporting process. This is consistent with previous finding that MICAL has to be transcribed and translated when pruning is initiated. As the presynapses of the model c4da neuron in this study is also pruned, the dependence on nuclear export and local actin remodeling were also shown. Thus, this study has added another layer of regulation (the nuclear mRNA export) in c4da neuronal pruning, which would be important for the audience interested in neuronal pruning. The study is limited for the confusing result whether ATPase activity of the exporting factor is required.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Frommeyer et al. explores the role of the helicase and regulator of nuclear export, UAP56, in the control of dendrite and presynaptic pruning in Drosophila larval da sensory neurons. The authors present evidence showing that UAP56 regulates these processes via the actin cytoskeleton and suggest that this is occurs by controlling the expression of the actin severing enzyme, Mical.

Major comments:

The most signficant issue with the manuscript is that some of the major conclusions are not supported by the data. Additional experiment would need to be completed in order support these claims. These (and other) major comments are as follows:

1. For Figure 4, the ms2/MCP system is not quantitative. Using this technique, it is impossible to determine how many RNAs are located in each "dot". Each of these dots looks quite large and likely corresponds to some phase-separated RNP complex where multiple RNAs are stored and/or transported. Thus, these data do not support the conclusion that Mical mRNA levels are reduced upon UAP56 knockdown. A good quantitative microscopic assay would be something like smFISH. Additinally, the localization of Mical mRNA dots to dendrites is not convincing as it looks like regions where there are dendritic swellings, the background is generally brighter.

2. Alternatively, levels of Mical mRNA could be verified by qPCR in the laval brain following pan-neuronal UAP56 knockdown or in FACS-sorted fluorescently labeled da sensory neurons. Protein levels could be analyzed using a similar approach.

3. In Figure 5, the authors state that Mical expression could not be detected at 0 h APF. The data presented in Fig. 5C, D suggest the opposite as there clearly is some expression. Moreover, the data shown in Fig. 5D looks significantly brighter than the Orco dsRNA control and appears to localize to some type of cytoplasmic granule. So the expression of Mical does not look normal.

4. Sufficient data are not presented to conclude any specificity in mRNA export pathways. Data is presented for one export protein (UAP56) and one putative target (Mical). To adequately assess this, the authors would need to do RNA-seq in UAP56 mutants.

5. In summary, better quantitative assays should be used in Figures 4 and 5 in order to conclude the expression levels of either mRNA or protein. In its current form, this study demonstrates the novel finding that UAP56 regulates dendrite and presynaptic pruning, potentially via regulation of the actin cytoskeleton. However, these data do not convincingly demonstrate that UAP56 controls these processes by regulating of Mical expression and defintately not by controlling export from the nucleus.

6. While there are clearly dendrites shown in Fig. 1C', the cell body is not readily identifiable. This makes it difficult to assess attachment and suggests that the neuron may be dying. This should be replaced with an image that shows the soma.

7. The level of knockdown in the UAS56 RNAi and P element insertion lines should be determined. It would be useful to mention the nature of the RNAi lines (long/short hairpin). Some must be long since Dcr has been co-expressed. Another issue raised by this is the potential for off-target effects. shRNAi lines would be preferable because these effects are minimized.

Minor comments:

1. The authors should explain what EB1:GFP is marking when introduced in the text.

2. The da neuron images througout the figures could be a bit larger.

Significance

Strengths:

The methodology used to assess dendrite and presynaptic prunings are strong and the phenotypic analysis is conclusive.

Weakness:

The evidence demonstrating that UAP56 regulates the expression of Mical is unconvincing. Similarly, no data is presented to show that there is any specificity in mRNA export pathways. Thus, these major conclusions are not adequately supported by the data.

Advance:

The findings that UAP56 regulate dendrite and synaptic pruning are novel. As is its specific regulation of the actin cytoskeleton. These findings are restricted to a phenotypic analysis and do not show that it is not simply due to the disruption of general mRNA export.

Audience:

In its current form the manuscript whould be of interest to an audience who specializes in the study of RNA binding proteins in the control of neurodevelopment. This would include scientists who work in invertebrate and vertebrate model systems.

My expertise:

My lab uses Drosophila to study the role of RNA binding proteins in neurodevelopment and neurodegeneration. Currently, we use flies as a model to better understand the molecular pathogenesis of neurodevelopmenal disorders such as FXS and ASD.

Reviewer #1 (Public review):

Summary:

The study of Drosophila mating behaviors has offered a powerful entry point for understanding how complex innate behaviors are instantiated in the brain. The effectiveness of this behavioral model stems from how readily quantifiable many components of the courtship ritual are, facilitating the fine-scale correlations between the behaviors and the circuits that underpin their implementation. Detailed quantification, however, can be both time-consuming and error-prone, particularly when scored manually. Song et al. have sought to address this challenge by developing DrosoMating, software that facilitates the automated and high-throughput quantification of 6 common metrics of courtship and mating behaviors. Compared to a human observer, DrosoMating matches courtship scoring with high fidelity. Further, the authors demonstrate that the software effectively detects previously described variations in courtship resulting from genetic background or social conditioning. Finally, they validate its utility in assaying the consequences of neural manipulations by silencing Kenyon cells involved in memory formation in the context of courtship conditioning.

Strengths:

(1) The authors demonstrate that for three key courtship/mating metrics, DrosoMating performs virtually indistinguishably from a human observer, with differences consistently within 10 seconds and no statistically significant differences detected. This demonstrates the software's usefulness as a tool for reducing bias and scoring time for analyses involving these metrics.

(2) The authors validate the tool across multiple genetic backgrounds and experimental manipulations to confirm its ability to detect known influences on male mating behavior.

(3) The authors present a simple, modular chamber design that is integrated with DrosoMating and allows for high-throughput experimentation, capable of simultaneously analyzing up to 144 fly pairs across all chambers.

Weaknesses:

(1) DrosoMating appears to be an effective tool for the high-throughput quantification of key courtship and mating metrics, but a number of similar tools for automated analysis already exist. FlyTracker (CalTech), for instance, is a widely used software that offers a similar machine vision approach to quantifying a variety of courtship metrics. It would be valuable to understand how DrosoMating compares to such approaches and what specific advantages it might offer in terms of accuracy, ease of use, and sensitivity to experimental conditions.

(2) The courtship behaviors of Drosophila males represent a series of complex behaviors that unfold dynamically in response to female signals (Coen et al., 2014; Ning et al., 2022; Roemschied et al., 2023). While metrics like courtship latency, courtship index, and copulation duration are useful summary statistics, they compress the complexity of actions that occur throughout the mating ritual. The manuscript would be strengthened by a discussion of the potential for DrosoMating to capture more of the moment-to-moment behaviors that constitute courtship. Even without modifying the software, it would be useful to see how the data can be used in combination with machine learning classifiers like JAABA to better segment the behavioral composition of courtship and mating across genotypes and experimental manipulations. Such integration could substantially expand the utility of this tool for the broader Drosophila neuroscience community.

(3) While testing the software's capacity to function across strains is useful, it does not address the "universality" of this method. Cross-species studies of mating behavior diversity are becoming increasingly common, and it would be beneficial to know if this tool can maintain its accuracy in Drosophila species with a greater range of morphological and behavioral variation. Demonstrating the software's performance across species would strengthen claims about its broader applicability.

Author response:

Thank you very much for the constructive feedback on our manuscript, "Simple Methods to Acutely Measure Multiple Timing Metrics among Sexual Repertoire of Male Drosophila," and for the opportunity to address the reviewers' comments. We appreciate the time and effort the reviewers have invested in evaluating our work, and we agree that their suggestions will significantly strengthen the manuscript.

We are currently working diligently to address all the concerns raised in the public reviews and recommendations. Below is an outline of the major revisions we plan to implement in the revised version:

(1) Statistical Rigor and Analysis

We acknowledge the statistical limitations pointed out by Reviewer #2. We will re-analyze the multi-group data in Figures 3 and 4 using One-way and Two-way ANOVA with appropriate post-hoc tests (e.g., Tukey's HSD), respectively, to properly account for multiple comparisons and interaction effects between genotype and training conditions.

(2) Comparison with Existing Tools

As suggested by both reviewers, we will provide a detailed comparison of DrosoMating with established automated tracking systems (e.g., FlyTracker, JAABA, Ctrax)，and specific use cases where DrosoMating offers distinct advantages in terms of cost, accessibility, and ease of use for high-throughput screening.

(3) Control for Locomotor Activity

To address the potential confound of general locomotor deficits in w1118 and y1 mutants, we will calculate and present general locomotion metrics (e.g., average velocity, total distance traveled) from our tracking data to dissociate motor defects from specific courtship deficits.

(4) Software Capabilities and Cross-Species Applicability

We will clarify how DrosoMating handles fly identification during mating (including occlusion management). We will also discuss or test the software's applicability across different *Drosophila* species, as requested.

(5) Minor Corrections

We will address all textual errors, standardize terminology (e.g., "Mating Duration" vs. "Copulation Duration"), improve figure legibility, and provide complete statistical details for all figures.

We believe these revisions will substantially improve the rigor, clarity, and utility of our manuscript. We aim to resubmit the revised version within the standard timeframe and will ensure the preprint is updated accordingly.

Reviewer #1 (Public review):

Summary:

This fundamental study identifies a new mechanism that involves a mycobacterial nucleomodulin manipulation of the host histone methyltransferase COMPASS complex to promote infection. Although other intracellular pathogens are known to manipulate histone methylation, this is the first report demonstrating specific targeting the COMPASS complex by a pathogen. The rigorous experimental design using of state-of-the art bioinformatic analysis, protein modeling, molecular and cellular interaction and functional approaches, culminating with in vivo infection modeling provide convincing, unequivocal evidence that supports the authors claims. This work will be of particular interest to cellular microbiologist working on microbial virulence mechanisms and effectors, specifically nucleomodulins, and cell/cancer biologists that examine COMPASS dysfunction in cancer biology.

Strengths:

(1) The strengths of this study include the rigorous and comprehensive experimental design that involved numerous state-of-the-art approaches to identify potential nucleomodulins, define molecular nucleomodulin-host interactions, cellular nucleomodulin localization, intracellular survival, and inflammatory gene transcriptional responses, and confirmation of the inflammatory and infection phenotype in a small animal model.

(2) The use of bioinformatic, cellular and in vivo modeling that are consistent and support the overall conclusions is a strengthen of the study. In addition, the rigorous experimental design and data analysis including the supplemental data provided, further strengthens the evidence supporting the conclusions.

Weaknesses:

(1) This work could be stronger if the MgdE-COMPASS subunit interactions that negatively impact COMPASS complex function were more well defined. Since the COMPASS complex consists of many enzymes, examining functional impact on each of the components would be interesting.

(2) Examining the impact of WDR5 inhibitors on histone methylation, gene transcription and mycobacterial infection could provide additional rigor and provide useful information related to mechanisms and specific role of WDR5 inhibition on mycobacteria infection.

(3) The interaction between MgdE and COMPASS complex subunit ASH2L is relatively undefined and studies to understand the relationship between WDR5 and ASH2L in COMPASS complex function during infection could provide interesting molecular details that are undefined in this study.

(4) The AlphaFold prediction results for all the nuclear proteins examined could be useful. Since the interaction predictions with COMPASS subunits range from 0.77 for WDR5 and 0.47 for ASH2L, it is not clear how the focus on COMPASS complex over other nuclear proteins was determined.

Comments on revisions:

The authors have addressed the weaknesses that were identified by this reviewer by providing rational explanation and specific references that support the findings and conclusions.

Reviewer #3 (Public review):

In this study, Chen L et al. systematically analyzed the mycobacterial nucleomodulins and identified MgdE as a key nucleomodulin in pathogenesis. They found that MgdE enters into host cell nucleus through two nuclear localization signals, KRIR108-111 and RLRRPR300-305, and then interacts with COMPASS complex subunits ASH2L and WDR5 to suppress H3K4 methylation-mediated transcription of pro-inflammatory cytokines, thereby promoting mycobacterial survival.

Comments on revisions:

The authors have adequately addressed previous concerns through additional experimentation. The revised data robustly support the main conclusions, demonstrating that MgdE engages the host COMPASS complex to suppress H3K4 methylation, thereby repressing pro-inflammatory gene expression and promoting mycobacterial survival. This work represents a significant conceptual advance.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This fundamental study identifies a new mechanism that involves a mycobacterial nucleomodulin manipulation of the host histone methyltransferase COMPASS complex to promote infection. Although other intracellular pathogens are known to manipulate histone methylation, this is the first report demonstrating the specific targeting of the COMPASS complex by a pathogen. The rigorous experimental design using state-of-the art bioinformatic analysis, protein modeling, molecular and cellular interaction, and functional approaches, culminating with in vivo infection modeling, provides convincing, unequivocal evidence that supports the authors' claims. This work will be of particular interest to cellular microbiologists working on microbial virulence mechanisms and effectors, specifically nucleomodulins, and cell/cancer biologists that examine COMPASS dysfunction in cancer biology.

Strengths:

(1) The strengths of this study include the rigorous and comprehensive experimental design that involved numerous state-of-the-art approaches to identify potential nucleomodulins, define molecular nucleomodulin-host interactions, cellular nucleomodulin localization, intracellular survival, and inflammatory gene transcriptional responses, and confirmation of the inflammatory and infection phenotype in a small animal model.

(2) The use of bioinformatic, cellular, and in vivo modeling that are consistent and support the overall conclusions is a strength of the study. In addition, the rigorous experimental design and data analysis, including the supplemental data provided, further strengthen the evidence supporting the conclusions.

Weaknesses:

(1) This work could be stronger if the MgdE-COMPASS subunit interactions that negatively impact COMPASS complex function were better defined. Since the COMPASS complex consists of many enzymes, examining the functional impact on each of the components would be interesting.

We thank the reviewer for this insightful comment. A biochemistry assays could be helpful to interpret the functional impact on each of the components by MgdE interaction. However, the purification of the COMPASS complex could be a hard task itself due to the complexity of the full COMPASS complex along with its dynamic structural properties and limited solubility.

(2) Examining the impact of WDR5 inhibitors on histone methylation, gene transcription, and mycobacterial infection could provide additional rigor and provide useful information related to the mechanisms and specific role of WDR5 inhibition on mycobacterial infection.

We thank the reviewer for the comment. A previous study showed that WIN-site inhibitors, such as compound C6, can displace WDR5 from chromatin, leading to a reduction in global H3K4me3 levels and suppression of immune-related gene expression (Hung et al., Nucleic Acids Res, 2018; Bryan et al., Nucleic Acids Res, 2020). These results closely mirror the functional effects we observed for MgdE, suggesting that MgdE may act as a functional mimic of WDR5 inhibition. This supports our proposed model in which MgdE disrupts COMPASS activity by targeting WDR5, thereby dampening host pro-inflammatory responses.

(3) The interaction between MgdE and COMPASS complex subunit ASH2L is relatively undefined, and studies to understand the relationship between WDR5 and ASH2L in COMPASS complex function during infection could provide interesting molecular details that are undefined in this study.

We thank the reviewer for the comment. In this study, we constructed single and multiple point mutants of MgdE at residues S⁸⁰, D²⁴⁴, and H²⁴⁷ to identify key amino acids involved in its interaction with ASH2L (Figure 5A and B; New Figure S4C). However, these mutations did not interrupt the interaction with MgdE, suggesting that more residues are involved in the interaction.

ASH2L and WDR5 function cooperatively within the WRAD module to stabilize the SET domain and promote H3K4 methyltransferase activity with physiological conditions (Couture and Skiniotis, Epigenetics, 2013; Qu et al., Cell, 2018; Rahman et al., Proc Natl Acad Sci U S A, 2022). ASH2L interacts with RbBP5 via its SPRY domain, whereas WDR5 bridges MLL1 and RbBP5 through the WIN and WBM motifs (Chen et al., Cell Res, 2012; Park et al., Nat Commun, 2019). The interaction status between ASH2L and WDR5 during mycobacterial infection could not be determined in our current study.

(4) The AlphaFold prediction results for all the nuclear proteins examined could be useful. Since the interaction predictions with COMPASS subunits range from 0.77 for WDR5 and 0.47 for ASH2L, it is not clear how the focus on COMPASS complex over other nuclear proteins was determined.

We thank the reviewer for the comment. We employed AlphaFold to predict the interactions between MgdE and the major nuclear proteins. This screen identified several subunits of the SET1/COMPASS complex as high-confidence candidates for interaction with MgdE (Figure S4A). This result is consistent with a proteomic study by Penn et al. which reported potential interactions between MgdE and components of the human SET1/COMPASS complex based on affinity purification-mass spectrometry analysis (Penn et al., Mol Cell, 2018).

Reviewer #2 (Public review):

Summary:

The manuscript by Chen et al addresses an important aspect of pathogenesis for mycobacterial pathogens, seeking to understand how bacterial effector proteins disrupt the host immune response. To address this question, the authors sought to identify bacterial effectors from M. tuberculosis (Mtb) that localize to the host nucleus and disrupt host gene expression as a means of impairing host immune function.

Strengths:

The researchers conducted a rigorous bioinformatic analysis to identify secreted effectors containing mammalian nuclear localization signal (NLS) sequences, which formed the basis of quantitative microscopy analysis to identify bacterial proteins that had nuclear targeting within human cells. The study used two complementary methods to detect protein-protein interaction: yeast two-hybrid assays and reciprocal immunoprecipitation (IP). The combined use of these techniques provides strong evidence of interactions between MgdE and SET1 components and suggests that the interactions are, in fact, direct. The authors also carried out a rigorous analysis of changes in gene expression in macrophages infected with the mgdE mutant BCG. They found strong and consistent effects on key cytokines such as IL6 and CSF1/2, suggesting that nuclear-localized MgdE does, in fact, alter gene expression during infection of macrophages.

Weaknesses:

There are some drawbacks in this study that limit the application of the findings to M. tuberculosis (Mtb) pathogenesis. The first concern is that much of the study relies on ectopic overexpression of proteins either in transfected non-immune cells (HEK293T) or in yeast, using 2-hybrid approaches. Some of their data in 293T cells is hard to interpret, and it is unclear if the protein-protein interactions they identify occur during natural infection with mycobacteria. The second major concern is that pathogenesis is studied using the BCG vaccine strain rather than virulent Mtb. However, overall, the key findings of the paper - that MgdE interacts with SET1 and alters gene expression are well-supported.

We thank the reviewer for the comment. We agree that the ectopic overexpression could not completely reflect a natural status, although these approaches were adopted in many similar experiments (Drerup et al., Molecular plant, 2013; Chen et al., Cell host & microbe, 2018; Ge et al., Autophagy, 2021). Further, the MgdE localization experiment using Mtb infected macrophages will be performed to increase the evidence in the natural infection.

We agree with the reviewer that BCG strain could not fully recapitulate the pathogenicity or immunological complexity of M. tuberculosis infection. We employed BCG as a biosafe surrogate model since it was acceptable in many related studies (Wang et al., Nat Immunol, 2025; Wang et al., Nat Commun, 2017; Péan et al., Nat Commun, 2017; Li et al., J Biol Chem, 2020).

Reviewer #3 (Public review):

In this study, Chen L et al. systematically analyzed the mycobacterial nucleomodulins and identified MgdE as a key nucleomodulin in pathogenesis. They found that MgdE enters into host cell nucleus through two nuclear localization signals, KRIR^108-111 and RLRRPR^300-305, and then interacts with COMPASS complex subunits ASH2L and WDR5 to suppress H3K4 methylation-mediated transcription of pro-inflammatory cytokines, thereby promoting mycobacterial survival. This study is potentially interesting, but there are several critical issues that need to be addressed to support the conclusions of the manuscript.

(1) Figure 2: The study identified MgdE as a nucleomodulin in mycobacteria and demonstrated its nuclear translocation via dual NLS motifs. The authors examined MgdE nuclear translocation through ectopic expression in HEK293T cells, which may not reflect physiological conditions. Nuclear-cytoplasmic fractionation experiments under mycobacterial infection should be performed to determine MgdE localization.

We thank the reviewer for this insightful comment. In the revised manuscript, we addressed this concern by performing nuclear-cytoplasmic fractionation experiments using M. bovis BCG-infected macrophages to assess the subcellular localization of MgdE (New Figure 2F) (Lines 146–155). Nuclear-cytoplasmic fractionation experiments showed that WT MgdE and the NLS single mutants (MgdE^ΔNLS1 and MgdE^ΔNLS2) could be detected both in the cytoplasm and in the nucleus, while the double mutant MgdE^ΔNLS1-2 was detectable only in the cytoplasm. These findings strongly indicate that MgdE is capable of translocating into the host cell nucleus during BCG infection, and that this nuclear localization relies on the dual NLS motifs.

(2) Figure 2F: The authors detected MgdE-EGFP using an anti-GFP antibody, but EGFP as a control was not detected in its lane. The authors should address this technical issue.

We thank the reviewer for this question. In the revised manuscript, we have included the uncropped immunoblot images, which clearly show the EGFP band in the corresponding lane. These have been provided in the New Figure 2E.

(3) Figure 3C-3H: The data showing that the expression of all detected genes in 24 h is comparable to that in 4 h (but not 0 h) during WT BCG infection is beyond comprehension. The issue is also present in Figure 7C, Figure 7D, and Figure S7. Moreover, since Il6, Il1β (pro-inflammatory), and Il10 (anti-inflammatory) were all upregulated upon MgdE deletion, how do the authors explain the phenomenon that MgdE deletion simultaneously enhanced these gene expressions?

We thank the reviewer for the comment. A relative quantification method was used in our qPCR experiments to normalize the WT expression levels in Figure 3C–3H, Figure 7C, 7D, and New Figure S6.

The concurrent induction of both types of cytokines likely represents a dynamic host strategy to fine-tune immune responses during infection. This interpretation is supported by previous studies (Podleśny-Drabiniok et al., Cell Rep, 2025; Cicchese et al., Immunological Reviews, 2018).

(4) Figure 5: The authors confirmed the interactions between MgdE and WDR5/ASH2L. How does the interaction between MgdE and WDR5 inhibit COMPASS-dependent methyltransferase activity? Additionally, the precise MgdE-ASH2L binding interface and its functional impact on COMPASS assembly or activity require clarification.

We thank the reviewer for this insightful comment. We cautiously speculate that the MgdE interaction inhibits COMPASS-dependent methyltransferase activity by interfering with the integrity and stability of the COMPASS complex. Accordingly, we have incorporated the following discussion into the revised manuscript (Lines 303-315):

“The COMPASS complex facilitates H3K4 methylation through a conserved assembly mechanism involving multiple core subunits. WDR5, a central scaffolding component, interacts with RbBP5 and ASH2L to promote complex assembly and enzymatic activity (Qu et al., 2018; Wysocka et al., 2005). It also recognizes the WIN motif of methyltransferases such as MLL1, thereby anchoring them to the complex and stabilizing the ASH2L-RbBP5 dimer (Hsu et al., Cell, 2018). ASH2L further contributes to COMPASS activation by interacting with both RbBP5 and DPY30 and by stabilizing the SET domain, which is essential for efficient substrate recognition and catalysis (Qu et al., Cell, 2018; Park et al., Nat Commun, 2019). Our work shows that MgdE binds both WDR5 and ASH2L and inhibits the methyltransferase activity of the COMPASS complex. Site-directed mutagenesis revealed that residues D²²⁴ and H²⁴⁷ of MgdE are critical for WDR5 binding, as the double mutant MgdE-D²²⁴A/H²⁴⁷A fails to interact with WDR5 and shows diminished suppression of H3K4me3 levels (Figure 5D).”

Regarding the precise MgdE-ASH2L binding interface, we attempted to identify the key interaction site by introducing point mutations into ASH2L. However, these mutations did not disrupt the interaction (Figure 5A and B; New Figure S4C), suggesting that more residues are involved in the interaction.

(5) Figure 6: The authors proposed that the MgdE-regulated COMPASS complex-H3K4me3 axis suppresses pro-inflammatory responses, but the presented data do not sufficiently support this claim. H3K4me3 inhibitor should be employed to verify cytokine production during infection.

We thank the reviewer for the comment. We have now revised the description in lines 220-221 and lines 867-868 "MgdE suppresses host inflammatory responses probably by inhibition of COMPASS complex-mediated H3K4 methylation."

(6) There appears to be a discrepancy between the results shown in Figure S7 and its accompanying legend. The data related to inflammatory responses seem to be missing, and the data on bacterial colonization are confusing (bacterial DNA expression or CFU assay?).

We thank the reviewer for the comment. New Figure S6 specifically addresses the effect of MgdE on bacterial colonization in the spleens of infected mice, which was assessed by quantitative PCR rather than by CFU assay.

We have now revised the legend of New Figure S6 as below (Lines 986-991):

“MgdE facilitates bacterial colonization in the spleens of infected mice. Bacterial colonization was assessed in splenic homogenates from infected mice (as described in Figure 7A) by quantifying bacterial DNA using quantitative PCR at 2, 14, 21, 28, and 56 days post-infection.”

(7) Line 112-116: Please provide the original experimental data demonstrating nuclear localization of the 56 proteins harboring putative NLS motifs.

We thank the reviewer for the comment. We will provide this data in the New Table S3.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

There are a few concerns about specific experiments:

Major Comments:

(1) Questions about the exact constructs used in their microscopy studies and the behavior of their controls. GFP is used as a negative control, but in the data they provide, the GFP signal is actually nuclear-localized (for example, Figure 1c, Figure 2a). Later figures do show other constructs with clear cytoplasmic localization, such as the delta-NLS-MgdE-GFP in Figure 2D. This raises significant questions about how the microscopy images were analyzed and clouds the interpretation of these findings. It is also not clear if their microscopy studies use the mature MdgE, lacking the TAT signal peptide after signal peptidase cleavage (the form that would be delivered into the host cell) or if they are transfecting the pro-protein that still has the TAT signal peptide (a form that would present in the bacterial cell but that would not be found in the host cell). This should be clarified, and if their construct still has the TAT peptide, then key findings such as nuclear localization and NLS function should be confirmed with the mature protein lacking the signal peptide.

We thank the reviewer for this question.  EGFP protein can passively diffuse through nuclear pores due to its smaller size (Petrovic et al., Science, 2022; Yaseen et al., Nat Commun, 2015; Bhat et al., Nucleic Acids Res, 2015). However, upon transfection with EGFP-tagged wild-type MdgE and its NLS deletion mutants (MdgE^ΔNLS1, MdgE^ΔNLS2, and MdgE^ΔNLS1-2), we observed significantly stronger nuclear fluorescence in cells expressing wild-type MdgE compared to the EGFP protein. Notably, the MdgE^ΔNLS1-2-EGFP mutant showed almost no detectable nuclear fluorescence (Figure 2C, D, and E). These results indicate that (i) MdgE-EGFP fusion protein could not enter the nucleus by passive diffusion, and (ii) EGFP does not interfere with the nuclear targeting ability of MdgE.

We did not construct a signal peptide-deleted MgdE for transfection assays. Instead, we performed an infection experiment using recombinant M. bovis BCG strains expressing Flag-tagged wild-type MgdE. The mature MgdE protein (signal peptide cleaved) can be detected in the nucleus fractionation (New Figure 2F), suggesting that the signal peptide does not play a role for the nuclear localization of MgdE.

(2) The localization of MdgE is not shown during actual infection. The study would be greatly strengthened by an analysis of the BCG strain expressing their MdgE-FLAG construct.

We thank the reviewer for the comment. In the revised manuscript, we constructed M. bovis BCG strains expressing FLAG-tagged wild-type MdgE as well as NLS deletion mutants (MdgE^ΔNLS1, MdgE^ΔNLS2, and MdgE^ΔNLS1-2). These strains were used to infect THP-1 cells, and nuclear-cytoplasmic fractionation was performed 24 hours post-infection.

Nuclear-cytoplasmic fractionation experiments showed that WT MgdE and the NLS single mutants could be detected both in the cytoplasm and in the nucleus by immunoblotting, while the double mutant MgdE^ΔNLS1-2 was detectable only in the cytoplasm (New Figure 2F) (Lines 146–155). These findings indicate that MdgE is capable of entering the host cell nucleus during BCG infection, and that this nuclear localization depends on the presence of both its N-terminal and C-terminal NLS motifs.

(3) Their pathogenesis studies suggesting a role for MdgE would be greatly strengthened by studying MdgE in virulent Mtb rather than the BCG vaccine strain. If this is not possible because of technical limitations (such as lack of a BSL3 facility), then at least a thorough discussion of studies that examined Rv1075c/MdgE in Mtb is important. This would include a discussion of the phenotype observed in a previously published study examining the Mtb Rv1075c mutant that showed a minimal phenotype in mice (PMID: 31001637) and would also include a discussion of whether Rv1075c was identified in any of the several in vivo Tn-Seq studies done on Mtb.

We thank the reviewer for this insightful comment. In the revised manuscript, we have incorporated a more thorough discussion of prior studies that examined Rv1075c/MgdE in Mtb, including the reported minimal phenotype of an Mtb MgdE mutant in mice (PMID: 31001637) (Lines 288–294).

In the latest TnSeq studies in M. tuberculosis, Rv1075c/MgdE was not classified as essential for in vivo survival or virulence (James et al., NPJ Vaccines, 2025; Zhang et al., Cell, 2013). However, this absence should not be interpreted as evidence of dispensability since these datasets also failed to identify some well characterized virulence factors including Rv2067c (Singh et al., Nat Commun, 2023), PtpA (Qiang et al., Nat Commun, 2023), and PtpB (Chai et al., Science, 2022) which were demonstrated to be required for the virulence of Mtb.

Minor Comments:

(1) Multiple figures with axes with multiple discontinuities used when either using log-scale or multiple graphs is more appropriate, including 3B, 7A.

We sincerely thank the reviewer for pointing this out. In the revised manuscript, we have updated Figure 3B and Figure 7A.

(2) Figure 1C - Analysis of only nuclear MFI can be very misleading because it is affected by the total expression of each construct. Ratios of nuclear to cytoplasmic MFI are a more rigorous analysis.

We thank the reviewer for this comment. We agree that analyzing the ratio of nuclear to cytoplasmic mean fluorescence intensity (MFI) provides a more rigorous quantification of nuclear localization, particularly when comparing constructs with different expression levels. However, the analysis presented in Figure 1C was intended as a preliminary qualitative screen to identify Tat/SPI-associated proteins with potential nuclear localization, rather than a detailed quantitative assessment.

(3) Figure 5C - Controls missing and unclear interpretation of their mutant phenotype. There is no mock or empty-vector control transfection, and their immunoblot shows a massive increase in total cellular H3K4me3 signal in the bulk population, although their prior transfection data show only a small fraction of cells are expressing MdgE. They also see a massive increase in methylation in cells transfected with the inactive mutant, but the reason for this is unclear. Together, these data raise questions about the specificity of the increasing methylation they observe. An empty vector control should be included, and the phenotype of the mutant explained.

We thank the reviewer for this comment. In the revised manuscript, we transfected HEK293T cells with an empty EGFP vector and performed a quantitative analysis of H3K4me3 levels. The results demonstrated that, at the same time point, cells expressing MdgE showed significantly lower levels of H3K4me3 compared to both the EGFP control and the catalytically inactive mutant MdgE (D²⁴⁴A/H²⁴⁷A) (New Figure 5D) (Lines 213–216). These findings support the conclusion that MdgE specifically suppresses H3K4me3 levels in cells.

(4) Figure S1A - The secretion assay is lacking a critical control of immunoblotting a cytoplasmic bacterial protein to demonstrate that autolysis is not releasing proteins into the culture filtrate non-specifically - a common problem with secretion assays in mycobacteria.

We thank the reviewer for this comment. To address the concerns, we examined FLAG-tagged MgdE and the secreted antigen Ag85B in the culture supernatants by monitoring the cytoplasmic protein GlpX. The absence of GlpX in the supernatant confirmed that there was no autolysis in the experiment. We could detect MgdE-Flag in the culture supernatant (New Figure S2A), indicating that MgdE is a secreted protein.

(5) The volcano plot of their data shows that the proteins with the smallest p-values have the smallest fold-changes. This is unusual for a transcriptomic dataset and should be explained.

We thank the reviewer for this comment. We are not sure whether the p-value is correlated with fold-change in the transcriptomic dataset. This is probably case by case.

Reviewer #3 (Recommendations for the authors):

There are several minor comments:

(1) Line 104-109: The number of proteins harboring NLS motifs and candidate proteins assigned to the four distinct pathways does not match the data presented in Table S2. Please recheck the details. Figure 1A and B, as well as Figure S1A and B, should also be corrected accordingly.

We thank the reviewer for the comment. We have carefully checked the details and the numbers were confirmed and updated.

(2) Please add the scale bar in all image figures, including Figure 1C, Figure 2D, Figure 5C, Figure 7B, and Figure S2.

We thank the reviewer for this suggestion. We have now added scale bars to all relevant image figures in the revised manuscript, including Figure 1C, New Figure 2C, Figure 5C, Figure 7B, and New Figure S2B.

(3) Please add the molecular marker in all immunoblotting figures, including Figure 2C, Figure 2F, Figure 4B, Figure 4C, Figure 5B, Figure 5D, and Figure S5.

We thank the reviewer for this suggestion. We have now added the molecular marker in all immunoblotting figures in the revised manuscript, including New Figure 2E–F, Figure 4B–C, Figure 5B and D, Figure S2A, New Figure S2E and New Figure S4C.

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Reviewer #1 (Public review):

Summary:

The authors develop a Python-based analysis framework for cellular organelle segmentation, feature extraction, and analysis for live-cell imaging videos. They demonstrate that their pipeline works for two organelles (mitochondria and lysosomes) and provide a step-by-step overview of the AutoMorphoTrack package.

Strengths:

The authors provide evidence that the package is functional and can provide publication-quality data analysis for mitochondrial and lysosomal segmentation and analysis.

Weaknesses:

(1) I was enthusiastic about the manuscript as a good end-to-end cell/organelle segmentation and quantification pipeline that is open-source, and is indeed useful to the field. However, I'm not certain AutoMorphoTrack fully fulfills this need. It appears to stitch together basic FIJI commands in a Python script that an experienced user can put together within a day. The paper reads as a documentation page, and the figures seem to be individual analysis outputs of a handful of images. Indeed, a recent question on the image.sc forum prompted similar types of analysis and outputs as a simple service to the community, and with seemingly better results and integrated organelle identity tracking (which is necessary in my opinion for live imaging). I believe this is a better fit in the methods section of a broader work. https://forum.image.sc/t/how-to-analysis-organelle-contact-in-fiji-with-time-series-data/116359/5.

(2) The authors do not discuss or compare to any other pipelines that can accomplish similar analyses, such as Imaris, CellProfiler, or integrate options for segmentation, etc., such as CellPose, StarDist.

(3) Although LLM-based chatbot integration seems to have been added for novelty, the authors do not demonstrate in the manuscript, nor provide instructions for making this easy-to-implement, given that it is directed towards users who do not code, presumably.

Reviewer #2 (Public review):

Summary:

AutoMorphoTrack provides an end-to-end workflow for organelle-scale analysis of multichannel live-cell fluorescence microscopy image stacks. The pipeline includes organelle detection/segmentation, extraction of morphological descriptors (e.g., area, eccentricity, "circularity," solidity, aspect ratio), tracking and motility summaries (implemented via nearest-neighbor matching using cKDTree), and pixel-level overlap/colocalization metrics between two channels. The manuscript emphasizes a specific application to live imaging in neurons, demonstrated on iPSC-derived dopaminergic neuronal cultures with mitochondria in channel 0 and lysosomes in channel 1, while asserting adaptability to other organelle pairs.

The tool is positioned for cell biologists, including users with limited programming experience, primarily through two implemented modes of use: (i) a step-by-step Jupyter notebook and (ii) a modular Python package for scripted or batch execution, alongside an additional "AI-assisted" mode that is described as enabling analyses through natural-language prompts.

The motivation and general workflow packaging are clear, and the notebook-plus-modules structure is a reasonable engineering choice. However, in its current form, the manuscript reads more like a convenient assembly of standard methods than a validated analytical tool. Key claims about robustness, accuracy, and scope are not supported by quantitative evidence, and the 'AI-assisted' framing is insufficiently defined and attributes to the tool capabilities that are provided by external LLM platforms rather than by AutoMorphoTrack itself. In addition, several figure, metric, and statistical issues-including physically invalid plots and inconsistent metric definitions-directly undermine trust in the quantitative outputs.

Strengths:

(1) Clear motivation: lowering the barrier for organelle-scale quantification for users who do not routinely write custom analysis code.

(2) Multiple entry points: an interactive notebook together with importable modules, emphasizing editable parameters rather than a fully opaque black box.

(3) End-to-end outputs: automated generation of standardized visualizations and tables that, if trustworthy, could help users obtain quantitative summaries without assembling multiple tools.

Weaknesses:

(1) "AI-assisted / natural-language" functionality is overstated.

The manuscript implies an integrated natural-language interface, but no such interface is implemented in the software. Instead, users are encouraged to use external chatbots to help generate or modify Python code or execute notebook steps. This distinction is not made clearly and risks misleading readers.

(2) No quantitative validation against trusted ground truth.

There is no systematic evaluation of segmentation accuracy, tracking fidelity, or interaction/overlap metrics against expert annotations or controlled synthetic data. Without such validation, accuracy, parameter sensitivity, and failure modes cannot be assessed.

(3) Limited benchmarking and positioning relative to existing tools.

The manuscript does not adequately compare AutoMorphoTrack to established platforms that already support segmentation, morphometrics, tracking, and colocalization (e.g., CellProfiler) or to mitochondria-focused toolboxes (e.g., MiNA, MitoGraph, Mitochondria Analyzer). This is particularly problematic given the manuscript's implicit novelty claims.

(4) Core algorithmic components are basic and likely sensitive to imaging conditions.

Heavy reliance on thresholding and morphological operations raises concerns about robustness across varying SNR, background heterogeneity, bleaching, and organelle density; these issues are not explored.

(5) Multiple figure, metric, and statistical issues undermine confidence.

The most concerning include:<br /> (i) "Circularity (4πA/P²)" values far greater than 1 (Figures 2 and 7, and supplementary figures), which is inconsistent with the stated definition and strongly suggests a metric/label mismatch or computational error.

(ii) A displacement distribution extending to negative values (Figure 3B). This is likely a plotting artifact (e.g., KDE boundary bias), but as shown, it is physically invalid and undermines confidence in the motility analysis.

(iii) Colocalization/overlap metrics that are inconsistently defined and named, with axis ranges and terminology that can mislead (e.g., Pearson r reported for binary masks without clarification).

(iv) Figure legends that do not match the displayed panels, and insufficient reporting of Ns, p-values, sampling units, and statistical assumptions.

Reviewer #3 (Public review):

Summary:

AutoMorphoTrack is a Python package for quantitatively evaluating organelle shape, movement, and colocalization in high-resolution live cell imaging experiments. It is designed to be a beginning-to-end workflow from segmentation through metric graphing, which is easy to implement. The paper shows example results from their images of mitochondria and lysosomes within cultured neurons, demonstrating how it can be used to understand organelle processing.

Strengths:

The text is well-written and easy to follow. I particularly appreciate tables 1 and 2, which clearly define the goals of each module, the tunable parameters, and the input and outputs. I can see how the provided metrics would be useful to other groups studying organelle dynamics. Additionally, because the code is open-source, it should be possible for experienced coders to use this as a backbone and then customize it for their own purposes.

Weaknesses:

Unfortunately, I was not able to install the package to test it myself using any standard install method. This is likely fixable by the authors, but until a functional distribution exists, the utility of this tool is highly limited. I would be happy to re-review this work after this is fixed.

The authors claim that there is "AI-Assisted Execution and Natural-Language Interface". However, this is never defended in any of the figures, and from quickly reviewing the .py files, there does not seem to be any built-in support or interface for this. Without significantly more instructions on how to connect this package to a (free) LLM, along with data to prove that this works reproducibly to produce equivalent results, this section should be removed.

Additionally, I have a few suggestions/questions:

(1) Red-green images are difficult for colorblind readers. I recommend that the authors change all raw microscopy images to a different color combination.

(2) For all of the velocity vs displacement graphs (Figure 3C and subpart G of every supplemental figure), there is a diagonal line clearly defining a minimum limit of detected movement. Is this a feature of the dataset (drift /shakiness /etc) or some sort of minimum movement threshold in the tracking algorithm? This should be discussed in the text.

(3) Integrated Correlation Summary (Figure 5) - Pearson is likely the wrong metric for most of these metric pairs because even interesting relationships may be non-linear. Please replace with Spearman correlation, which is less dependent on linearity.

Author response:

Reviewer #1

We thank the reviewer for their thoughtful and constructive assessment of AutoMorphoTrack and for recognizing its potential utility as an open-source end-to-end workflow for organelle analysis.

(1) Novelty and relationship to existing tools / FIJI workflows

We appreciate this concern and agree that many of the underlying image-processing operations (e.g., thresholding, morphological cleanup, region properties) are well-established. Our goal with AutoMorphoTrack is not to introduce new segmentation algorithms, but rather to provide a curated, reproducible, and extensible end-to-end workflow that integrates segmentation, morphology, tracking, motility, and colocalization into a single, transparent pipeline tailored for live-cell organelle imaging.

While an experienced user could assemble similar analyses ad hoc using FIJI or custom scripts, our contribution lies in:

Unifying these steps into a single workflow with consistent parameterization and outputs

Generating standardized, publication-ready visualizations and tables at each step,

Enabling batch and longitudinal analyses across cells and conditions, and

Lowering the barrier for users who do not routinely write custom analysis code.

We note that the documentation-style presentation of the manuscript is intentional, as it serves both as a methods paper and a practical reference for users implementing the workflow. We agree, however, that the manuscript currently overemphasizes step-by-step execution at the expense of positioning. In revision, we will more explicitly frame AutoMorphoTrack as a workflow integration and usability contribution, rather than a fundamentally new algorithmic advance.

We will also cite and discuss the image.sc example referenced by the reviewer, clarifying conceptual overlap and differences in scope.

(2) Comparison to existing pipelines (Imaris, CellProfiler, CellPose, StarDist)

We agree and thank the reviewer for highlighting this omission. In the revised manuscript, we will expand the related-work and positioning section to explicitly compare AutoMorphoTrack with established commercial (e.g., Imaris) and open-source (e.g., CellProfiler, MiNA, MitoGraph) platforms, as well as learning-based segmentation tools such as CellPose and StarDist.

Rather than claiming superiority, we will clarify trade-offs, emphasizing that AutoMorphoTrack prioritizes:

Transparency and parameter interpretability,

Lightweight dependencies suitable for small live-imaging datasets

Direct integration of morphology, tracking, and colocalization in a single workflow, and

Ease of modification for domain-specific use cases.

(3) AI / chatbot integration

We appreciate this critique and agree that the current description is insufficiently precise. AutoMorphoTrack does not implement a native natural-language interface. Instead, our intent was to convey that the workflow can be executed and modified with assistance from external large language models (LLMs) in a notebook-based environment.

In revision, we will revise this section to:

Clearly distinguish AutoMorphoTrack’s functionality from that of external LLM tools,

Remove any implication of a built-in AI interface, and

Provide concrete, reproducible examples of how non-coding users may interact with the pipeline using natural-language prompts mediated by external tools.

Reviewer #2

We thank the reviewer for their detailed and technically rigorous evaluation. We appreciate the recognition of the workflow’s motivation and structure, and we agree that several aspects of validation, positioning, and quantitative reporting must be strengthened.

(1) AI-assisted / natural-language functionality

We agree with this critique. AutoMorphoTrack does not provide a native natural-language execution layer, and the manuscript currently overstates this aspect. In revision, we will explicitly scope any reference to AI assistance as external, optional support for code generation and parameter editing, with clearly documented examples and stated limitations.

We agree that conflating external LLM capabilities with the software itself risks misleading readers, and we will correct this accordingly.

(2) Lack of quantitative validation

We fully agree that the current manuscript lacks formal quantitative validation. In the revised version, we will add a dedicated validation section including:

Segmentation accuracy compared to expert annotations using overlap metrics (e.g., Dice / IoU),

Tracking fidelity assessed using manually annotated tracks and/or synthetic ground truth,

Sensitivity analyses for key parameters (e.g., thresholding and linking distance), and

Explicit discussion of failure modes and quality-control indicators.

We acknowledge that without such validation, claims of robustness are not sufficiently supported.

(3) Benchmarking and positioning relative to existing tools

We agree and will substantially strengthen AutoMorphoTrack’s benchmarking and positioning relative to existing platforms. Rather than framing novelty algorithmically, we will clarify that the primary contribution is a reproducible, integrated workflow designed specifically for two-organelle live imaging in neurons, with transparent parameters and standardized outputs.

We note that our goal is not to exhaustively benchmark against all available tools, but rather to provide representative comparisons that clarify operating regimes, assumptions, and trade-offs. We will add a comparative table and/or qualitative comparison highlighting strengths, assumptions, and limitations relative to existing tools.

(4) Core algorithms and robustness

We agree that reliance on threshold-based segmentation introduces sensitivity to imaging conditions. In revision, we will:

Explicitly discuss the operating regime and assumptions under which AutoMorphoTrack performs reliably,

Clarify that the framework is modular and can accept alternative segmentation backends, and

Include guidance on when outputs should be treated with caution.

(5) Figure, metric, and statistical issues

We thank the reviewer for identifying several critical issues and agree that these undermine confidence. In revision, we will correct all figure, metric-definition, and reporting inconsistencies, including:

Resolving circularity values exceeding 1 by correcting computation and/or labeling errors,

Revising physically invalid displacement plots and clarifying kernel-density limitations,

Ensuring colocalization metrics are consistently defined, named, and interpreted, with explicit clarification of whether calculations are intensity- or mask-based,

Correcting figure legends to match displayed panels, and

Clearly reporting sample size, sampling units, and statistical assumptions, including handling of multiple comparisons where applicable.

(6) Value-added demonstration

We agree that the manuscript would benefit from a clearer demonstration of value-added use cases. In revision, we will include at least one realistic example showing how AutoMorphoTrack enables a complete, reproducible analysis workflow with reduced setup burden compared to manually assembling multiple tools.

(7) Editorial suggestions

We agree and will streamline the Results section to reduce procedural repetition and focus more on validation, limitations, and quality-control guidance.

Reviewer #3

We thank the reviewer for their positive assessment of clarity and organization, and for the constructive practical feedback.

Installation issues

We appreciate the detailed report of installation failures and acknowledge that the current packaging and distribution are inadequate. Prior to revision, we will:

Fix the package structure to support standard installation methods,

Ensure all required files (e.g., setup configuration, README) are correctly included,

Test installation on clean environments across platforms, and

Correct broken links to notebooks and documentation.

We agree that without a functional installation pathway, the utility of the tool is severely limited.

AI-assisted claims

We agree with the reviewer and echo our responses above. The AI-assisted description will be clarified and appropriately scoped in the revised manuscript.

Additional suggestions

Color accessibility: We will revise all figures to use colorblind-safe palettes.

Velocity–displacement diagonal: We will explicitly explain the origin of this relationship, including whether it reflects dataset properties, tracking assumptions, or minimum detectable motion.

Integrated correlation metric: We agree that Spearman correlation is more appropriate for many of these relationships and will replace Pearson correlations accordingly.

Supplementary movies: We agree that providing raw movies would improve interpretability and will add representative examples as supplementary material.

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What is this?

If most lithogenous sediment enters the ocean through rivers, how does this affect sediment distribution in areas far from major river systems?

This part stood out to me because it shows how sediment characteristics can be used as evidence of past environmental conditions. By looking at grain size, scientists can infer whether an area experienced high energy processes like strong currents or low energy conditions where finer sediments were able to settle.

Most agreed!

I agree with the reward system, it works.

I find it less distracting to study at a library vs. at home. At home there are so many distractions and escape routes that can lead to procrastination.

Some people work well under pressure, and even perform at their best.

Sometimes a quick walk outside or take a few steps around the house, or even do a short 10-15 minute exercise; jump-n-jacks, arm circles, jump rope, sit ups, legs lifts. It gets the blood flowing and combats tiredness.

Sometimes, before tackling an assignment or task, its better to properly fuel and rest the body and mind.

This applies to life as well.

Most of this is not planned, most people just manage as it comes. Its good to have a plan, however so many set-backs can happen, so we plan for every single kind there is? Sounds impossible

With so much weighing on a college student , I think it not fair to have this thought of finances lingering over your head. Focusing on classes, studying and just surviving is enough.

I find this a bit extreme, a SINGLE mishap, just one can send ones success crashing and burning ?

I made a connection during this section, especially the idea that power is usually unspoken but predictable. The examples about the types of rules reminded me of groups that I have seen in school and at work. It is when certain peoples preferences automatically get prioritized even when they dont have an offical supirior title like professor or manager. It connects to the idea that power doesnt come from a title, it can come from personality, populatirty, or confidence. It helped me to better understand how informational power show up everyday settings. It also made me realized how easiy it is to follow this pattern.

I also made a connection to cumulative stress and identity based harm. The sections on micro affirmations and micro interventions stood out because they go beyond just identifying harm and instead focusing on smaller, more practical actions people can take. That makes the topic feel more like action, instead of just theoretical , especially for people in this field.

Question 2: What steps can a leader or counselor take to balance their power leadership style?

Question 1: How can leaders or counselors realize when they are relying too much on coercive or legitimate power instead of expert or referent power?

If the target is comfortable with sharing their experience with a family member or friend, then they can give them support and encouragement. An example from my personal life would be like from my example in my previous paragraph but after I called my mom and she assured me and offered encouragement. This gave me the motivation I needed to go back to class and sit with a new group of people and make new friends.

A microaggression is when someone makes remark or action against another of a marginalized group such as a race or ethnic minority. I've experienced a situation like this where I was the only one of my race and someone of a different race blocked me off from talking with the rest of the group of the same race as them. We were at a long straight table and I was at the end trying to lean over to hear what people were saying. This makes me question why people do this and what do they get from doing it? If I were a bystander, I would do my best to include this person. I would try to invite them to sit next to me or ask for their input in a conversation to make them feel included.

I think I could be comfortably uncomfortable in trying to "Open the Front Door" more often. I am someone who very much avoids confrontation, but I have tried to make it a goal for myself to be kindly confrontational in situations that warrant it. I think microaggressions are things that I can address in this way. Hopefully, using this strategy of microresistance is away I can help people be aware of what they might do unintentionally.

I think the part that scares me the most about this, aside from the confrontation, is providing relevant data. I think this is the best way to back up a point, but I find myself being hesitant of quoting the research wrong, so I say nothing at all. Hopefully by practicing this, I can get more confident in using this strategy. I also think the desire part of this strategy can be tricky because I don't find it easy to request things of other people, but I am finding that good leaders need to be able to communicate in this way, so I am motivated to get better at it.

After reading the chart below, which basis of power was the President of the United States designed to have? I find this role fitting many of the different categories, not just one.

When people are singled out in a group, they seem to be ignored above all things. Even the people that what to claim that they are exclusive also want to show that they are being "inclusive" to the one singled out by choice. I've seen a lot of people purposefully act a different way to the one known as different to show they rest of the public that their interactions aren't truly genuine and related. A lot of us want to be friends with the "outcast" but not associated with them or their group I believe, and this is even noticeable in the most loving communities. It makes me feel uncomfortable, but I can also relate to those insecurities. It is human nature to want to flip in, and this is where the necessity for countering culture comes in.

what does this mean?

Just writing this as a note, I want to highlight the three impacts to later see how microaggressions could lead to large or even global predicaments: structural: interpersonal: intrapersonal: -- whats the difference between these three?

From the first grounding question in the beginning of the chapter, the basic definition of micro aggressions was sort of how I predicted to to be, but this example I found to be a surprise. I didn't think that this is what microagressions would look like but more so derogatory comments in school or exclusion, so I need to learn more about the specific of what microaggression could look like to truly notice it. For questions 2 and 3, at first I didn't believe that I've seen microaggressions often in my life, but now I'm rethinking that. In addition, I thought I would be the person to stand up for others in situations of microaggressions, but in examples similar to this one about the siblings, I would probably be uncomfortable saying anything.

Seeing all of these bases make power feel so much more dangerous then just the singular word. When I think of power, I immediately think of diplomatic events/conflict, striving for power in the workplace, or the government. If I had to guess these different categories I would've first thought of the "reward", "coercive" and "informational" branch, but I didn't initially reflect on how common people not in higher positions can hold a lot of power as well. The "expert" and "referent" categories are the ones that I see majority of the general community use to increase their status because those are the two besides legitimate that can be displayed more outwardly. Things like bribery, violence, force or secrecy have to be more hidden. I wonder how each of these bases are shown or micro manners as well to where they wouldn't necessarily be frowned upon.

Now this could relate to authoritative and parental figures, but how does this specific branch differ between cultures? What do each of these branches teach a person about another's culture? Are there certain people that bleed into multiple bases of power?

I feel like I have seen this very prominently growing up, but I am wondering what this looks like practically? Where can this be seen differently between parent relationships, friendships and relationships between authoritative figures like parents?

The section on microinterventions and microresistance makes me think about how public figures on social media call out subtle bias and offer support to targets of discrimination. On platforms like TikTok or Twitter, small acts like explaining why a comment hurts — even to strangers — can have a ripple effect, encouraging others to rethink their words. It connects the chapter’s leadership concepts to real-world interpersonal influences in everyday life, showing that leadership isn’t just formal authority but also everyday relational action.

As I read the chapter’s explanation of microaggressions as “death by a thousand cuts,” I immediately connected it to moments in my own life where small comments about my identity, even when not intended to hurt, accumulated and felt emotionally heavy. Academically, it reminded me of class discussions on implicit bias and how subtle everyday interactions can reinforce stereotypes or exclusion without overt hostility. Recognizing these patterns helps me see why leaders must intentionally disrupt them rather than assume people get it.

Do you think changing the language (e.g., abuse, subtle acts of exclusion) might help groups take interpersonal bias more seriously?

How might a leader use informational or referent power differently to interrupt everyday microaggressions in a group setting?

In my personal life, I most often use the “check in” method from the four categories of microintervention strategies. When I believe something may have hurt someone, I try to be present and create space for them to talk through the situation, express their feelings, and articulate any specific pain they are experiencing. I especially appreciate the question “What do you need?” because it centers the person who was impacted and prioritizes their needs rather than assumptions. This is a strategy I plan to intentionally use in future situations.

A connection I made was with the chart’s definition of microinvalidation. A few weeks ago, my roommate was on FaceTime with a male friend I had never met, and we began casually talking. During the conversation, he asked about my ethnicity, and when I shared that I am Hispanic and of Mexican descent, he immediately began asking about my family’s political views, specifically regarding ICE. Although I do not believe his question was intentionally meant to be harmful, it reduced my identity and cultural background to a political stereotype. In that moment, it felt as though my heritage was being framed solely through politics rather than as a lived experience. The comment was especially isolating because it placed me in an uncomfortable position where any response could have led to conflict. Notably, he did not ask my other roommate, who is a white woman with blonde hair and blue eyes, similar questions about her political views. Understanding the concept of microinvalidation helped me put this experience into perspective, as it highlighted how certain identities are often singled out.

This description of “slipper, slimy words and behaviors” has left me wondering where the line is drawn between harm and intent, and how we can better recognize microaggressions in everyday interactions so that we can respond with accountability rather than defensiveness.

This would always happen with my siblings. My older brother wanted to hug my younger brother and he would exaggerate and tell my mother that my older brother wanted to hit him and so that’s where my mom would ask my brother what happened? And he would respond with, “I just wanted to give him a hug”, but in this case they would both get in trouble. One for being exaggerated and the other one for “bothering”.

Usually when someone is "othering" another person they use microaggression. The use of microaggression is a subtle jab of discrimination towards someone. The othering contained microaggression that while I was younger, I wasn't that familiar with. Now that I am older and able to understand the sounds of microaggression, it makes me feel sad knowing people use this as a tactic of discrimination.

An experience that I had was with a cop. Since he knew he had the power to do so, even though it was wrong to do what he did, yet he still did it to intimidate me. I got stopped, and just because of my color and ethnicity I got cussed at and started interrogating me to intimidate and get me nervous. I see this as a coercive power. Also I do not agree with what the cop did, it happens daily in colored people’s life sadly.

A connection that I made with this is , when we’re all young we usually get in trouble by our parents. although when for example, my family and I would visit a friends house, my parents would tell us to behave because they did not want to get on us in front of their friends. When we were in that friends house just by my mom’s look or my dads action I knew it was time for me to behave. So I connect these actions as being an unspoken rule. We see often how parents don’t even have to say nothing to their kids, but just by giving them a look, that child knows to behave. This shows how much “power” or “respected” parents can and have .

Reading this reminded me of Taylor Swift's song "Death by a Thousand Cuts" where she perfectly captures the feeling of the breaking point that microaggressions can lead to. Popular culture has the unique ability to convey lasting messages through art. Taylor Swift has undoubtedly played an integral role in this. Her music gives words to feelings we often can't put words to. While both Taylor Swift and I are part of many privileged demographics, we can also relate to microaggressions in the sense that we are women.

Simply the way our society is designed to confine women to their traditional role instead of encouraging them to thrive is an example of this. Taylor says in her song "My heart, my hips, my body, my love//Trying to find a part of me that you didn't touch." Society both subtly and unsubtly places expectations and policies on every aspect of women's lives. Like we discussed last class, just because things have gotten dramatically better for women, that does not mean they are equitable. Taylor describes the feeling that accompanies the exhaustion of this fight by saying "Gave you too much but it wasn't enough//But I'll be all right, it's just a thousand cuts." All of the small stabs women take on a daily basis might just lead to "death by a thousand cuts" if they are not addressed, and still we will persist as we bleed out.

Is it possible that using the term microaggression as opposed to abuse makes people more likely to listen to the problem because they are not focused on analyzing if such a strong word was appropriate (even if it is)?

One connection I made was interpersonal power and group dynamics that I’ve seen in real life. These sentences explain that power doesnt have to be formally put into the world to exist, but it can show up through unspoken rules and patterns. I’ve seen this in classrooms and peer groups since being in college where certain student's opinions carry more weight even when they are not professors or TA's. This connects to social hierarchies and sometimes even bias, where influence can be socially constructed rather than formally stated like how a professor and student are explicitly laid out. It helped me see that leadership responsibility has to include noticing these invisible power patterns, not just formal authority roles that are laid out obviously.

Question 2: Would changing the terminology of microaggressions alter the way that people respond, or would the behavior still be minimized regardless of the term we use?

Question 1: How should a counselor address a microaggression that happened in the life of a client, while validating that the "micro" aggression may have not had a "micro" effect on the client's life?

In my life I have experienced microaggression. At times I had no idea it was considered a microaggression until I was told later. An example of an experience I have gone through is when my aunt took my cousin and I into a predominantly white area just to have us look at a store she wanted to take us to. As we were going down each isle my aunt told us of an employee who would follow us down each isle as well. When we exited the store, she explained to us what the situation was really about. This leads me to the question of, do people know that they are being micro aggressive and if so, do they know how much they are affecting the people that this action is being directed towards?

Like this piece of text says micro mean small. I find that although micro means small the word microaggression is quite deceiving. The action may seem minor, but the outcome of this action can have a big impact on someone or a group of people.

Hardworking, Professional, and Organized

professional, organized, and straight-forward.

1 used as a means to reward validators who propose blocks, or call out dishonest behaviour by other validators. 2. staked by validators, acting as collateral agains dishonest behaviour. 3. it is used to weigh 'votes' for newly proposed blcoks. (fork-choice)

This section helped me clearly see how different data types represent different kinds of information. Booleans are especially interesting because they force complex situations into true/false decisions, which can oversimplify reality. It also made me realize how choices about numbers and strings affect what computers can accurately store and how much meaning might be lost through rounding or categorization.

I like the dictionary analogy because it makes clear how data gets structured and labeled. By assigning names to values, dictionaries don’t just store information, they also shape how programmers interpret and access it. This made me realize that how data is organized can influence what questions are easy—or hard—to ask later.

This section helped clarify that not all automation on social media counts as a bot. I found it especially useful that the definition focuses on whether the account is operated by computer code rather than by humans, even if those humans behave mechanically, like in click farms. This distinction makes it easier to think more precisely about responsibility and accountability when automation affects online spaces.

Did the DEA as a part of their police force trainings teach the to use racial profiling as a methods when investigating potential drug crimes?

Also after 09/11 many middle eastern people ( which includes many varying nationalities, most of which had nothing to do with 09/11, were profiled and detained at airports, pulled over and harassed by cops, assaulted and ridiculed by people who just lumped the middle east into one pot.

Another big reason for lack of reporting

It is shocking to me that Hate crimes were not investigated prior to the early 1900's. No wonder they go unreported! Our world has not taken the seriously in the least bit until the 1900's. I would imagine many victims feel as though there is no point

In my opinion, these laws were unjust to begin with, and it is sad that people like Rosa Parks had to fight so hard simply to sit where she wanted to on the bus, or that anyone was deprived their right to an education, or their right to vote. People had to die just to bring attention to the fact that these laws were discriminatory and unjust.

My husband and his siblings were raised by the same mother and father. One son, my husband, the middle child, always stayed between the lines and followed tall of he rules, he was well liked, got good grades, put himself through college while working full time and became an aeronautical engineer.and would often accept punishment for deviant behavior committed by his brother to keep the peace.He also got the least attention. He is the most conscientious loving , trustworthy and loyal person I know. To me this contradicts Edwin Sutherlands differential association theory.

His older brother, began using drugs at a very early age, sniffed glue at 9, took downers or reds at 12, and essentially became sexually active at 12 or 13m because their adult neighbor seduced him. Much of this his parents were oblivious to. He was put on behavioral medications as a child, and commanded a lot of attention. As a young man he joined the military and after going AWOL several times was ulitimatley dishonorably discharged. In later life he became an i.v. meth user, contracted HIV from sharing needles, went through countless rehabs, and ultimately died as an overdose. To this day his parents are in denial about who he had become.

His youngest brother by 7 years also became sexually active at a very young age. The same neighbor sexually abused him. He became a womanizer often having 3 to 4 women who all thought the were the only one. He has never held a real job, Had two children that he loves but never really helped the Mom with any sort of support , financially or in caring for the kids. but has managed to find women with lots of money support him. He lived with their parents on and off into his 50's. Just recently at 60 years old he seems to have settled down with one woman. She is also a very wealthy woman who is happy to take care of him.

This alligns with the fact that the first 3 to 4 years of life play the largest role in who we become.

resources.

of little importance, too small to be considered

creativity is transformative

i.e., creativity

So, creative decisions lead to originality of a work...creativity makes something original

What's the distinction between originality and creativity? From the way it's used in this opinion it seems like creativity leads to originality...you can't have originality without creativity?

Is there an agreed upon legal definition of creativity or is it "I know it when I see it?"

something necessary, indispensable

delete the following text: "Experten schätzen, dass bislang nur etwa 3 % der Krypto-Gewinne korrekt versteuert wurden. Die Steuerfahndung NRW hat im September 2025 rund 4.000 Konto-Datensätze einer Kryptobörse übernommen."

After this paragraph add a new paragraph with the following text: "Experten schätzen, dass aktuell gerade einmal 3 % dieser Gewinne korrekt versteuert werden."

This I very much buy and think is cool

Reviewer #3 (Public review):

Summary:

Authors mapped monosynaptic inputs to dopamine, GABA, and glutamate neurons in the ventral tegmental area (VTA) under different anesthesia methods, and under drug (cocaine, morphine, methamphetamine, amphetamine, nicotine, fluoxetine). First, they propose an analysis method to separate the actual manipulation effects from the variability caused by experimental procedures. Using this method, they found differences in the anatomical location of monosynaptic inputs to dopamine neurons under different conditions, and identified some key brain areas for such separation. They also searched the database for gene expression patterns that are common across input brain areas, with some changes by anesthesia or drug administration.

Strengths:

The whole-brain approach to address drug effects is appealing, and their conclusion is clear. The methodology and motivation are clearly explained.

Weaknesses:

While gene expression analyses may not be related to their findings on the anatomical effects of drugs, this is a nice starting point for follow-up studies.

Author response:

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

Public Reviews:

Reviewer #1(Public review):

Summary:

In this study, the authors distinguished afferent inputs to different cell populations in the VTA using dimensionality reduction approaches and found significantly distinct patterns between normal and drug treatment conditions. They also demonstrated negative correlations of the inputs induced by drugs with gene expression of ion channels or proteins involved in synaptic transmission and demonstrated the knockdown of one of the voltage-gated calcium ion channels caused decreased inputs.

Weaknesses:

(1) For quantifications of brain regions in this study, boundaries were based on the Franklin-Paxinos (FP) atlas according to previous studies (Beier KT et al 2015, Beier KT et al 2019). It has been reported significant discrepancies exist between the anatomical labels on the FP atlas and the Allen Brain Atlas (ref: Chon U et al., Nat Commun 2019). Although a summary of conversion is provided as a sheet, the authors need to describe how consistent or different the brain boundaries they defined in the manuscript with Allen Brain Atlas by adding histology images. Also, I wonder how reliable the annotations were for over a hundred of animals with manual quantification. The authors should briefly explain it rather than citing previous studies in the Material and Methods Section.

We thank the reviewer for attention to this point; indeed, neuroanatomical detail is often overlooked in modern neuroscience, occasionally leading to spurious conclusions. We acknowledge that there are significant discrepancies in brain region definitions across atlases, which can make cross-study comparisons difficult. Here, all cells were manually quantified by Dr. Kevin Beier, as in previous studies (Beier et al., Cell 2015; Nature 2017; Cell Reports 2019; Tian et al., Cell Reports 2022; Tian et al., Neuron 2024; Hubbard et al., Neuropsychopharmacology, 2025). As such, these studies are internally consistent as relates to the definition of brain regions, which is critical here since our analysis in this manuscript relates to data quantified only by a single individual. Several brain regions were quite easy to distinguish anatomically, such as the medial habenula and lateral habenula. Others, such as the extended amygdala area, are much more difficult. We have now provided example images in Figure S1 that detail the anatomical boundaries that we used, overlayed on images of Neurotrace blue (fluorescent Nissl stain).

(2) Regarding the ellipsoids in the PC, although it's written in the manuscript that "Ellipsoids were centered at the average coordinate of a condition and stretched one standard deviation along the primary and secondary axes", it's intuitively hard to understand in some figures such as Figure 2O, P and Figure S1. The authors need to make their data analysis methods more accessible by providing source code to the public.

The source code is now available to the public at https://github.com/ktbartas/Bartas_et_al_eLife_2024, which is noted in the Code Availability statement. The code for generating ellipsoids is in the first notebook, `0-dataexploration-master-euclidean.ipynb`, in the function `confidence_ellipse`, which is called from `make_pca_plots` and `umap_and_heatmap`. Example plots are all live in the notebooks as can be viewed directly from GitHub.

(3) In histology images (Figure 1B and 3K), the authors need to add dashed lines or arrows to guide the reader's attention.

Dashed lines have been added to these figure panels as requested.

(4) In Figure 2A and G, apparently there are significant differences in other brain regions such as NAcMed or PBN. If they are also statistically significant, the authors should note them as well and draw asterisks(*).

We appreciate the care in ensuring that statistics are being applied and shown appropriately. In panel A (now Figure 3A), the Two-way ANOVA interaction term was not significant (p = 0.9365), we did not find it justified to do further comparisons. However, for Figure 3G, the interaction term was significant (p = 0.0001), and thus further pairwise comparisons were performed with Sidak's correction for multiple comparisons. When done, the only two brain regions that were significantly different were the DStr (p = 0.0051) and GPe (p = 0.0036). While the NAcMed and PBN visually look different, according to the corrected statistics, they were not significantly different (NAcMed p = 0.5037, PBN p = 0.8123). The notations in our original figure thus accurately reflected these statistics.

(5) In Figure 2N about the spatial distribution of starter cells, the authors need to add histology images for each experimental condition (i.e. saline, fluoxetine, cocaine, methamphetamine, amphetamine, nicotine, and morphine) as supplement figures

We have now provided these as Figure S2.

(6) In the manuscript, it is necessary to explain why Cacna1e was selected among other calcium ion channels.

We have added a sentence to the "Functional validation of link between gene expression and RABV labeling" section (lines 722-724).

Reviewer #2 (Public review):

The application of rabies virus (RabV)-mediated transsynaptic tracing has been widely utilized for mapping celltype-specific neural connectivities and examining potential modifications in response to biological phenomena or pharmacological interventions. Despite the predominant focus of studies on quantifying and analyzing labeling patterns within individual brain regions based on labeling abundance, such an approach may inadvertently overlook systemic alterations. There exists a considerable opportunity to integrate RabV tracing data with the global connectivity patterns and the transcriptomic signatures of labeled brain regions. In the present study, the authors take an important step towards achieving these objectives. Specifically, the authors conducted an intensive reanalysis of a previously generated large dataset of RabV tracing to the ventral tegmental area (VTA) using dimension reduction methods such as PCA and UMPA. This reaffirmed the authors' earlier conclusion that different cell types in the VTA, namely dopamine neurons (DA) and GABAergic neurons, exhibit quantitatively distinct input patterns, and a single dose of addictive drugs, such as cocaine and morphine, induced altered labeling patterns. Additionally, the authors illustrate that distinct axes of PCA can discriminate experimental variations, such as minor differences in the injection site of viral tracers, from bona fide alternations in labeling patterns caused by drugs of abuse. While the specific mechanisms underlying altered labeling in most brain regions remain unclear, whether involving synaptic strength, synaptic numbers, pre-synaptic activities, or other factors, the present study underscores the efficacy of an informatics approach in extracting more comprehensive information from the RabV-based circuit mapping data. Moreover, the authors showcased the utility of their previously devised bulk gene expression patterns inferred by the Allen Gene Expression Atlas (AGEA) and "projection portrait" derived from bulk axon mapping data sourced from the Allen Mouse Brain Connectivity Atlas. The utilization of such bulk data rests upon several limitations. For instance, the collection of axon mapping data involves an arbitrary selection of both cell type-specific and non-specific data, which might overlook crucial presynaptic partners, and often includes contamination from neighboring undesired brain regions. Concerns arise regarding the quantitativeness of AGEA, which may also include the potential oversight of key presynaptic partners. Nevertheless, the authors conscientiously acknowledged these potential limitations associated with the dataset. Notably, building on the observation of a positive correlation between the basal expression levels of Ca2+ channels and the extent of drug-induced changes in RabV labeling patterns, the authors conducted a CRISPRi-based knockdown of a single Ca2+ channel gene. This intervention resulted in a reduction of RabV labeling, supporting that the observed gene expression patterns have causality in RabV labeling efficiency. While a more nuanced discussion is necessary for interpreting this result (see below), overall I commend the authors for their efforts to leverage the existing dataset in a more meaningful way. This endeavor has the potential to contribute significantly to our understanding of the mechanisms underlying alterations in RabV labeling induced by drugs of abuse. Finally, drawing upon the aforementioned reanalysis of previous data, the authors underscored that a single administration of ketamine/xylazine anesthesia could induce enduring modifications in RabV labeling patterns for VTA DA neurons, specifically those projecting to the nucleus accumbens and amygdala. Given the potential impact of such alterations on motivational behaviors at a broader level, I fully agree that prudent consideration is warranted when employing ketamine/xylazine for the investigation of motivational behaviors in mice.

Specific Points:

(1) Beyond advancements in bioinformatics, readers may find it insightful to explore whether the PCA/UMPAbased approach yields novel biological insights. For example, the authors are encouraged to discuss more functional implications of PBN and LH in the context of drugs of abuse, as their labeling abundance could elucidate the PC2 axis in Fig. 2M.

Thank you for this suggestion: we added text (Lines 787-795) discussing the LH and PBN (and GPe) specifically, but also highlighted the importance of our approach in hypothesis-generating science.

(2) While I appreciate the experimental data on Cacna1e knockdown, I am unclear about the rationale behind specifically focusing on Cacna1e. The logic behind the statement, "This means that expression of this gene is not inhibitory towards RABV transmission," is also unclear. Loss-of-function experiments only signify the necessity or permissive functions of a gene. In this context, Cacna1e expression levels are required for efficient RabV labeling, but this neither supports nor excludes the possibility that this gene expression instructively suppresses RabV labeling/transmission, which could be assessed through gain-of-function experiments.

We thank the reviewer for their suggestions regarding this result, and agree that a gain-of-function would be required to provide clearer evidence on this point.  We therefore understand that our original phrasing may be misleading. Thus, we have edited this section to the more conservative statement: “These results indicate that reduced levels of Cacna1e likely lower the number of RABV-labeled inputs from the NAcLat, and directly link the levels of Cacna1e and RABV input labeling” (lines 742-744) - we refrain from over-interpreting the results. As mentioned above in response to R1, we added a sentence to explain the rationale behind focusing on Cacna1e (lines 722-724).

Reviewer #3 (Public Review):

Summary:

Authors mapped monosynaptic inputs to dopamine, GABA, and glutamate neurons in VTA under different anesthesia methods, and under drugs (cocaine, morphine, methamphetamine, amphetamine, nicotine, fluoxetine). They found that input patterns under different conditions are separated, and identified some key brain areas to contribute to such separation. They also searched a database for gene expression patterns that are common across input brain areas with some changes by anesthesia or drug administration.

Strengths:

The whole-brain approach to address drug effects is appealing and their conclusion is clear. The methodology and motivation are clearly explained.

Weaknesses:

While gene expression analyses may not be related to their findings on the anatomical effects of drugs, this will be a nice starting point for follow-up studies. 

We understand and agree with the suggestion that gene expression allows us to provide correlative observations between in situ hybridization datasets and rabies mapping datasets, and that these results do not show causality. As such, future studies would be needed to assess this in more detail. We have added a line in the discussion to this effect (lines 851-853).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Recommendations for improving the writing and presentation:

(1) There are a couple of packages available for 3D whole-brain reconstructions based on Allen Brain Atlas (eg. https://github.com/tractatus/wholebrain, https://github.com/lahammond/BrainJ), which would be helpful to align with the gene expression or other data from Allen Institute.

This comment is related to the noted weakness we responded to previously in this rebuttal also from R1 (see comment 1), about the discrepancies between the Franklin-Paxinos atlas and Allen Brain atlas. We agree that a systematic comparison of these two atlases using a tool like wholebrain or BrainJ would be valuable for the field. However, it would be a substantial amount of work, and likely would be an independent study in itself. We believe that the resolution of these atlases was sufficient to make our key conclusions here (e.g., identify gene expression patterns that relate to drug-induced changes rabies virus labeling patterns, and develop a testable hypothesis for CRISPR-based gene editing). They are also based on the same atlases and region definitions that have been applied in our previous studies (e.g., Beier et al., Cell 2015; Beier et al., Nature 2017; Beier et al., Cell Reports 2019; Tian et al., Cell Reports 2022; Tian et al., Neuron 2024; Hubbard et al., Neuropsychophamacology 2025, etc.)  The expression of Cacna1e is relatively consistent across the NAc, as we have now detailed in Figure S13.

(2) There are so far two kinds of rabies virus strains available in the neuroscience field (SAD-B19 or CVS-N2c). It is recommended to describe which strain was used in the Material and Methods Section because labeling efficiency and toxicity is quite different between the strains (Reardon TR et al., Neuron 2016).

We have now noted that we used SAD B19 for all experiments (Lines 141-142).

Minor corrections to the text and figures:

(1)  In Figure 1A, the color differences are not clear (i.e. light gray and dark gray). The figure can be simplified.

In addition, generally, images/figures are recommended not to be overlapped with other figures/images (Figures 2A-F, 2G-L).

(2)  In Figures 7C and D, the authors could add enlarged views of starter cells in VTA and NAcLat.

We have attempted to simplify schematics and figures throughout. High-magnification images of cells have been added as insets in what is now Figure 10 (formerly Figure 7).

Reviewer #2 (Recommendations For the authors):

The number of animals for each graph should be explicated within the figure legend. For example, Figure 1C and Figure 7E lack this information. It is also advisable to delineate the definition of error bars within the figure legend.

We have now added mouse numbers to all figures and/or legends, as appropriate. We also indicated in the legend at the end of Figure 1 how error bars and asterisks are defined. Furthermore, we added a sentence to the methods saying that in UMAP and PCA plots each dot is an animal (lines 244-245).

The visual representations, particularly in Figures 1 and 3, are overcrowding. Furthermore, the arrangement of figure subpanels does not consistently adhere to the sequence of explication in the main text, significantly compromising the readability of the text. The authors are encouraged to consider the possibility of segmenting dense figures into two if there exists no upper limit for the number of figure displays. To illustrate, in Figure 3Q, crucial details about experimental conditions are denoted by numerical references, owing to spatial constraints.

We agree that the figure layout and mis-alignment with a linear read of the text was unideal. Therefore, we broke our figures, especially the original Figures 1-4, into multiple sub-figures, including both main and supplemental figures. This facilitated the use of space to rearrange the figure panels, allowing the story to be told in a linear fashion. All figures and panels should now be read in order.

I am seeking clarification on how to interpret the term "overlap" at the bottom of figures illustrating Gene Ontology analysis.

We have clarified the meaning of overlap in this context (lines 324-325): The ‘overlap’ term on the x-axis of these plots means the number of genes in the correlated gene lists that were also within the list of genes for the corresponding GO term.

The authors could provide Cacna1e gene expression patterns within the NAc from the AGEA data.

Cacna1e expression data are now provided in Figure S13.

Additionally, the meaning of "controls" in Figure 7F, along with the "No gRNA" condition, remains ambiguous. While the text mentions "no shRNA", the involvement of shRNA in this experiment lacks clarity.

We now clarify that the control conditions are based on previously published data where no AAVs were injected into NAcLat. This is now clarified in the legend for Figure 10F (lines 1277-1578). We also corrected “shRNA” to “gRNA” in the text.

this is a sobering image. Signal at 70 million monthly active users. Apple imessage 1,3 billion Whatsapp 3 billion Instagram 2 billion FB Messenger 1 billion Telegram 1 billion Snapchat 900 million Discord 200million WeChat 1.3 billion Dingtalk 191million QQ 553 million no mention of Threema too tiny I suppose.

Scale of WhatsApp is close to 3 billion people.

Reviewer #3 (Public review):

Summary:

The authors demonstrate that CRF neurons in the extended amygdala form GABAergic synapses on to cholinergic interneurons and that CRF can excite these neurons. The evidence is strong, however the authors lack to make a compelling connection showing CRF released from these extended amygdala neurons is mediating any of these effects. Further, they show that acute alcohol appears to modulate this action, although the effect size is not particularly robust.

Strengths:

This is an exciting connection from the extended amygdala to the striatum that provides a new direction for how these regions can modulate behavior. The work is rigorous and well done.

Weaknesses:

The effects of acute ethanol are modest but consistent, the potential role of this has yet to be determined. Further, the opto stim experiments are conducted in an ai32 mouse, so it is impossible to determine if that is from CEA and BNST, vs. another population of CRF containing neurons. This is an important caveat that was acknowledged.

Author response:

The following is the authors’ response to the original reviews

We appreciate the reviewers’ insightful comments. In response, we conducted three new experiments, summarized in Author response table 1. After the table, we provide detailed responses to each comment.

Author response table 1.

Summary of new experiments and results.

Reviewer #1 (Public review):

The authors show that corticotropin-releasing factor (CRF) neurons in the central amygdala (CeA) and bed nucleus of the stria terminalis (BNST) monosynaptically target cholinergic interneurons (CINs) in the dorsal striatum of rodents. Functionally, activation of CRFR1 receptors increases CIN firing rate, and this modulation was reduced by pre-exposure to ethanol. This is an interesting finding, with potential significance for alcohol use disorders, but some conclusions could use additional support.

Strengths:

Well-conceived circuit mapping experiments identify a novel pathway by which the CeA and BNST can modulate dorsal striatal function by controlling cholinergic tone. Important insight into how CRF, a neuropeptide that is important in mediating aspects of stress, affective/motivational processes, and drug-seeking, modulates dorsal striatal function.

Weaknesses:

(1) Tracing and expression experiments were performed both in mice and rats (in a mostly nonoverlapping way). While these species are similar in many ways, some conclusions are based on assumptions of similarities that the presented data do not directly show. In most cases, this should be addressed in the text (but see point number 2).

In the revised manuscript, we have clarified this limitation in the first paragraph of the Methods and the third paragraph of the Discussion and avoid cross-species claims, limiting our conclusions to the species in which each assay was performed. Specifically, we now state that while mice and rats share many conserved amygdalostriatal components, our tracing and expression studies were performed in a species-specific manner, and direct cross-species comparisons of CRF–CIN connectivity and CRFR1 expression were not assessed. We further note that future studies will be needed to determine the extent to which these observations are conserved across species as more tools become available.

(2) Experiments in rats show that CRFR1 expression is largely confined to a subpopulation of striatal CINs. Is this true in mice, too? Since most electrophysiological experiments are done in various synaptic antagonists and/or TTX, it does not affect the interpretation of those data, but non-CIN expression of CRFR1 could potentially have a large impact on bath CRF-induced acetylcholine release.

To address whether CRFR1 expression in striatal CINs is conserved across species, we performed new histological experiments using CRFR1-GFP mice. Striatal sections were immunostained with anti-ChAT, and we found that approximately 10% of CINs express CRFR1 (new Fig. 4D, 4E). This result indicates that, similar to rats, a subset of CINs in mice express CRFR1. However, the proportion of CRFR1⁺ CINs is lower than the proportion of CRF-responsive CINs observed during electrophysiology experiments, suggesting that CRF may also modulate CIN activity indirectly through network or synaptic mechanisms. We have also noted in the revised Discussion that while CRFR1 expression is confirmed in a subset of CINs, the broader distribution of CRFR1 among other striatal cell types remains to be determined (third paragraph of Discussion).

In our study, bath application of CRF increased striatal ACh release. Because striatal ACh is released primarily from CINs, and CRFR1 is an excitatory receptor, this effect is most likely mediated by CRF activation of CRFR1 on CINs, leading to enhanced CIN activity and ACh release. Although CRFR1 may also be expressed on other striatal neurons, these cell types—medium spiny neurons and GABAergic interneurons—are inhibitory. If CRF were to activate CRFR1 on these GABAergic neurons, the resulting increase in GABA release would suppress CIN activity and consequently reduce, rather than enhance, ACh release. Given that most CINs responded functionally while only a small subset expressed CRFR1, these findings imply that indirect mechanisms, such as CRF modulation of local circuits influencing CIN excitability, may also contribute to the observed increase in ACh release. Together, these data support a model in which CRF primarily enhances ACh release via activation of CRFR1-expressing CINs, while indirect network effects may further amplify this response.

(3) Experiments in rats show that about 30% of CINs express CRFR1 in rats. Did only a similar percentage of CINs in mice respond to bath application of CRF? The effect sizes and error bars in Figure 5 imply that the majority of recorded CINs likely responded. Were exclusion criteria used in these experiments?

We thank the reviewer for this insightful question. In our mouse cell-attached recordings, ~80% of CINs increased firing during CRF bath application, and all recorded cells were included in the analysis (no exclusions based on response direction/magnitude; cells were only required to meet standard recording-quality criteria such as stable baseline firing and seal).

Using a CRFR1-GFP reporter mouse, we found that ~10% of striatal CINs are GFP+, suggesting that the high proportion of CRF-responsive CINs cannot be explained solely by somatic reporter-labeled CRFR1 expression. Importantly, the CRF-induced increase in CIN firing is blocked by the selective CRFR1 antagonist NBI 35695 (Fig. 5B–C), supporting a CRFR1-dependent mechanism at the circuit level. We now discuss several non-mutually exclusive explanations for this apparent discrepancy: (i) reporter lines (e.g., CRFR1-GFP) may underestimate functional CRFR1 expression, particularly for low-level or compartmentalized receptor pools; (ii) bath-applied CRF may act indirectly via CRFR1 on presynaptic afferents, thereby enhancing excitatory drive onto CINs; and (iii) electrical coupling among CINs could allow direct effects in a subset of CINs to propagate through the CIN network (Ren, Liu et al. 2021). We added this discussion to the revised manuscript (fourth paragraph of the Discussion).

(4) The conclusion that prior acute alcohol exposure reduces the ability of subsequent alcohol exposure to suppress CIN activity in the presence of CRF may be a bit overstated. In Figure 6D (no ethanol preexposure), ethanol does not fully suppress CIN firing rate to baseline after CRF exposure. The attenuated effect of CRF on CIN firing rate after ethanol pre-treatment (6E) may just reduce the maximum potential effect that ethanol can have on firing rate after CRF, due to a lowered starting point. It is possible that the lack of significant effect of ethanol after CRF in pre-treated mice is an issue of experimental sensitivity. Related to this point, does pre-treatment with ethanol reduce the later CIN response to acute ethanol application (in the absence of CRF)?

In the revised manuscript, we have tempered our interpretation in the final Results section and throughout the Discussion to emphasize that ethanol pre-exposure attenuates, rather than abolishes, the CRFinduced increase in CIN firing. We also note the reviewer’s important point that in Figure 6D, ethanol does not fully suppress firing to baseline after CRF exposure, consistent with a partial effect. Regarding the reviewer’s question, our experiments were specifically designed to test interactions between CRF and ethanol, so we did not assess whether ethanol pre-treatment alters subsequent responses to ethanol alone. We now explicitly acknowledge CRF-dependent and CRF-independent effects of ethanol on CIN activity as an important point for future studies to disentangle (sixth paragraph of the Discussion). For example, comparing ethanol responses with and without prior ethanol without any treatment with CRF could resolve this question.

(5) More details about the area of the dorsal striatum being examined would be helpful (i.e., a-p axis).

We now provide more detail regarding the anterior–posterior axis of the dorsal striatum examined. Most recordings and imaging were performed in the posterior dorsomedial striatum (pDMS), corresponding to coronal slices posterior to the crossing of the anterior commissure and anterior to the tail of the striatum (starting around 0.62 mm and ending at −1.3 mm relative to the Bregma). While our primary focus was on posterior slices, some anterior slices were included to increase the sample size. These details have been added to the Methods (Last sentence of the ‘Histology and cell counting’ section and of the ‘Slice electrophysiology’ section).

Reviewer #2 (Public review):

Essoh and colleagues present a thorough and elegant study identifying the central amygdala and BNST as key sources of CRF input to the dorsal striatum. Using monosynaptic rabies tracing and electrophysiology, they show direct connections to cholinergic interneurons. The study builds on previous findings that CRF increases CIN firing, extending them by measuring acetylcholine levels in slices and applying optogenetic stimulation of CRF+ fibers. It also uncovers a novel interaction between alcohol and CRF signaling in the striatum, likely to spark significant interest and future research.

Strengths:

A key strength is the integration of anatomical and functional approaches to demonstrate these projections and assess their impact on target cells, striatal cholinergic interneurons.

Weaknesses:

(1) The nature of the interaction between alcohol and CRF actions on cholinergic neurons remains unclear. Also, further clarification of the ACh sensor used and others is required

We have clarified the nature of the interaction between alcohol and CRF signaling in CINs and have provided additional details regarding the acetylcholine sensor used. These issues are addressed in detail in our responses to the specific comments below.

Reviewer #2 (Recommendations for the authors):

(1) The interaction between the effects of alcohol and CRF is a novel and important part of this study. When considering possible mechanisms underlying the findings in the discussion, there is no mention of occlusion. Given that incubation with alcohol produced a similar increase in firing of CINs as CRF, occlusion could be a parsimonious explanation for the observed interaction. Have the author considered blocking the effects of alcohol on CIN with CRF-R1 antagonist? Another experiment that could address the occlusion would be to test if alcohol also increases ACh levels as it did CRF.

We thank the reviewer for proposing occlusion as a potential mechanism underlying the interaction between alcohol and CRF. We agree that, in principle, alcohol-induced endogenous CRF release could occlude subsequent exogenous CRF-mediated potentiation of CIN firing, and we carefully considered this possibility.

However, several observations from our data argue against occlusion driven by acute alcohol exposure or withdrawal in this preparation. First, as shown in Fig. 6A, bath application of alcohol transiently reduced CIN firing, and firing recovered to baseline levels after washout without any rebound increase. Second, in Fig. 6D–E, the baseline firing rates under control conditions and following alcohol pretreatment were comparable, indicating that acute alcohol exposure and short-term withdrawal did not produce a sustained increase in CIN excitability. Together, these results suggest that acute withdrawal in slices is less likely to trigger substantial endogenous CRF release capable of occluding subsequent exogenous CRF effects.

While we and others have previously reported increased spontaneous CIN firing following prolonged in vivo alcohol exposure and extended withdrawal periods (e.g., 21 days), short-term withdrawal (e.g., 1 day) does not robustly alter baseline CIN firing (Ma, Huang et al. 2021, Huang, Chen et al. 2024). Consistent with these prior findings, the absence of a rebound or elevated baseline firing in the present slice experiments discouraged further pursuit of an endogenous CRF occlusion mechanism under acute conditions.

We also considered experimentally testing occlusion by blocking CRFR1 signaling during alcohol pre-treatment. However, this approach is technically challenging in slice recordings, as CRFR1 antagonists require prolonged incubation (~1 hour) during alcohol exposure. Because it is unclear whether endogenous CRF release is triggered by alcohol incubation itself or by withdrawal, the antagonist would need to remain present throughout both the incubation and withdrawal periods. This leaves insufficient time for complete washout of the CRFR1 antagonist prior to subsequent bath application of exogenous CRF to assess its effects on CIN firing. Consequently, residual antagonist presence would confound the interpretation of the exogenous CRF response.

Finally, regarding the possibility that alcohol increases acetylcholine release, we did not observe alcohol-induced increases in CIN firing in slices, arguing against elevated ACh signaling under these conditions. Consistent with prior work (Ma, Huang et al. 2021, Huang, Chen et al. 2024), alcohol-induced increases in CIN excitability and cholinergic signaling appear to depend on prolonged in vivo exposure and extended withdrawal rather than acute slice-level manipulations.

We have now incorporated discussion of occlusion as a potential mechanism (seventh paragraph) and clarified why our data and technical considerations argue against it in the present study. We thank the reviewer for this wonderful suggestion, which we will test in future in vivo studies.

(2) Retrograde monosynaptic tracing of inputs to CIN. Results state the finding of labeling in all previously reported area..." Can the authors report these areas? A list in the text or a bar plot, if there is quantification, will suffice. This formation will serve as important validation and replication of previous findings.

We thank the reviewer for this constructive suggestion. We agree that summarizing the anatomical sources of CIN input provides important validation of our tracing results. In the revised Results, we now list the major input regions observed, including the striatum itself, cortex (e.g., cingulate cortex, motor cortex, somatosensory cortex), thalamus (e.g., parafascicular thalamic nucleus, centrolateral thalamic nucleus), globus pallidus, and midbrain (first paragraph of the Results). Quantitative analysis of relative input strength will be presented in a separate study that expands on these findings. Here, we limit the current manuscript to the functional characterization of CRF and alcohol modulation of CINs.

(3) Given the difference in connectivity among striatal subregions, it would be important to describe in more detail the injection site in the results and figures. In the figure, for example, you might want to include the AP coordinates, given that it is such a zoomed-in image, it is hard to tell how anterior/posterior the site is. I imagine that the picture is a representative image of the injection site, but maybe having a side image with overlay of injection sites in all the animals used, would help.

The anterior–posterior (AP) coordinates for representative images have been included in the panels and reiterated more clearly in the revised Results section and figure legends. In the legend for Figure 3B, a list of AP coordinates for each animal used for Figure 3A-3E has been added.

(4) Figure 1D inset, there seem to be some double-labeled cells in the zoomed in BNST images. The authors might want to comment on this. It seemed far from the injection site. Do D1-MSN so far away show connectivity to CINs?

Upon closer inspection of the BNST images, we noted a small number of double-labeled cells were indeed present, consistent with prior reports that a subset of D1R-expressing neurons (~10%) has been reported previously in our lab in the BNST, with the majority being D2R-expressing neurons (Lu, Cheng et al. 2021). Given the BNST’s anatomical proximity to the dorsal striatum, it is plausible that some D1Rexpressing neurons in this region provide monosynaptic input to CINs, highlighting a potential ventral-to-dorsal connection that merits further study.

(5) Can the author provide quantification of the onset delay of the optogenetic evoked CRF+ axon responses onto CINs? The claim of monosynaptic connectivity is well supported by the TTX/4AP experiment but additional information on the timing will strengthen that conclusion.

We thank the reviewer for this insightful suggestion. Quantifying the onset latency of optogenetically evoked CRFMsup+</sup> axon responses onto CINs provides valuable confirmation of monosynaptic connectivity. To address this, we performed new latency measurements under the same recording conditions as the TTX/4-AP experiments. The average onset latency from the start of the optical stimulation was 5.85 ± 0.37 ms (new Figure 3J), consistent with direct monosynaptic transmission.

As an additional reference, we analyzed latency data from a separate project in which we optogenetically stimulated cholinergic interneurons and recorded synaptic responses in medium spiny neurons. This circuit, known to involve disynaptic transmission from CINs to MSNs via nAChR-expressing interneurons (Autor response image 1) (English, Ibanez-Sandoval et al. 2011), exhibited a significantly longer latency (18.34 ± 0.70 ms; t₍₂₉₎ = 10.3, p < 0.001) compared to CRF⁺ CeA/BNST inputs to CINs (5.85 ± 0.37 ms). Together, these results further support that CRF⁺ axons form direct functional synapses onto CINs.

Author response image 1.

Latency of disynaptic transmission from CINs to MSNs via interneurons A) Schematic illustrating optogenetic stimulation of Chrimson-expressing CINs, leading to excitation of nAChRexpressing interneurons that release GABA onto recorded MSNs. B) Sample trace of disynaptic transmission (left) and bar graph summarizing onset latency (right) from light stimulation to synaptic response onset (n = 23 neurons from 3 mice).

(6) The ACh sensor reported is "AAV-GRABACh4m" but the reference is for GRAB-ACh3.0. Also, BrainVTA has GRAB-ACh4.3. Is this the vector? Could you please check the name of the construct and report the corresponding reference, as well as clarify the meaning of the additional "m". They have a mutant version of the GRAB-ACH that researchers use for control, and of course, you want to use it as a control, but not for the test experiment.

GRAB-ACh4m is the correct acetylcholine sensor used in this study. The ACh4 series (including ACh4h, ACh4m, and ACh4l; personal communication with Dr. Yulong Li’s lab) represents an updated generation following GRAB-ACh3.0. Although the ACh4 family has not yet been formally published, these constructs are publicly available through BrainVTA (https://www.brainvta.tech/plus/view.php?aid=2680).

The suffix “m” does not indicate a mutant control; rather, it denotes a medium-affinity variant within the ACh4 sensor family. Importantly, the mutant (non-responsive) control sensor is only available for GRAB-ACh3.0 (ACh3.0mut) and does not exist for the ACh4 series.

Our laboratory has previously used GRAB-ACh4m in multiple peer-reviewed publications (Huang, Chen et al. 2024, Gangal, Iannucci et al. 2025, Purvines, Gangal et al. 2025), and its use has also been reported by independent groups in recent preprints (Potjer, Wu et al. 2025, Touponse, Pomrenze et al. 2025). We have now clarified the construct name, its relationship to GRAB-ACh3.0, in the Methods ‘Reagents’ section, and we have corrected the reference accordingly.

(7) Are CRF-R1+ CINs equally abundant in the DMS and DLS? From the image in Figure 4, it seems that a larger percentage of CINs are CRFR1+ in the DLS than in DMS. Is this true? The authors probably already have this data, or it should be easy to get, and it could be additional information that was not studied before.

We did not perform a quantitative comparison of CRFR1+ CIN abundance between the DMS and DLS in the present study. While the representative images in Figure 4 may appear to suggest regional differences, these panels were selected to illustrate labeling quality rather than relative density and should not be interpreted as evidence of unequal distribution. We have clarified this point in the revised Discussion (last sentence of the third paragraph) and note that future studies will be needed to systematically evaluate potential regional differences in CRFR1 expression, which could have important implications for dorsal striatal function.

(8) The manuscript states several times that there are no CRF+ neurons in the dorsal striatum. At the same time, there are reports of the CRF+ neuron in the ventral striatum and its role in learning. Could the authors include mention of the studies by the Lemos group (10.1016/j.biopsych.2024.08.006)

We have revised the Discussion section to clarify that our findings pertain specifically to the dorsal striatum and now acknowledge the presence and functional relevance of CRF+ neurons in the ventral striatum, citing the Lemos group’s study (fifth paragraph of the Discussion).

(9) For the histology analysis, please express cell counts as "density", not just number of cells, by providing an area (e.g., "number of cell/ µm2").

In the revised manuscript, all histological outcomes have been recalculated as cell density (cells/mm²) by normalizing raw cell counts to the measured area of each region of interest (ROI). Figures that previously displayed absolute counts now present densities (cells/mm²), with corresponding updates made to figure legends and text. We note one exception in Figure 4B, where the comparison between the total number of CINs and CRFR1+ CINs is best represented as cell counts rather than normalized values, as the counting was conducted in the same area (within the same ROI) of the dorsostriatal subregion.

(10) Figure 2C, we can see there are some labeled fibers in the striatum cut. Would it be possible to get a better confocal image?

Figure 2C has been replaced with a higher-quality confocal image captured at the same magnification and scale. The updated image provides improved clarity and resolution, ensuring accurate visualization of labeled CRF+ fibers, but not cell bodies, within the striatum.

(11) The ACh measurements in the slice are very informative and an important addition. I first thought that these experiments with the GRAB-ACh sensor were performed in ChAT-eGFP mice. After reading more carefully, I realized they were done in wild-type mice. Would you include the wildtype label in the figure as well? The ChATeGFP BAC transgenic line was reported to have enhanced ACh packaging and increased ACh release, which could have magnified the signals. So, it is important to highlight the experiments were done in wildtype mice.

We now label with ‘WT mice’ and note in the legend that all GRAB-ACh experiments were performed in wild-type mice, not ChAT-eGFP, to avoid confounds in ACh release. We thank the reviewer for this important suggestion.

Reviewer #3 (Public review):

The authors demonstrate that CRF neurons in the extended amygdala form GABAergic synapses onto cholinergic interneurons and that CRF can excite these neurons. The evidence is strong, however, the authors fail to make a compelling connection showing CRF released from these extended amygdala neurons is mediating any of these effects. Further, they show that acute alcohol appears to modulate this action, although the effect size is not particularly robust.

Strengths:

This is an exciting connection from the extended amygdala to the striatum that provides a new direction for how these regions can modulate behavior. The work is rigorous and well done.

Weaknesses:

(1) While the authors show that opto stim of these neurons can increase firing, this is not shown to be CRFR1 dependent. In addition, the effects of acute ethanol are not particularly robust or rigorously evaluated. Further, the opto stim experiments are conducted in an Ai32 mouse, so it is impossible to determine if that is from CEA and BNST, vs. another population of CRF-containing neurons. This is an important caveat.

We added recordings with the CRFR1 antagonist antalarmin. Light-evoked increases in CIN firing were abolished under CRFR1 blockade, linking the effect to CRFR1 (Figure 5J, 5K). We also clarify that CRFCre;Ai32 does not isolate CeA versus BNST sources, so we temper regional claims and highlight this as a limitation. The acute ethanol effects are modest but consistent; we expanded the discussion of dose and preparation constraints in acute slice physiology and note that in vivo studies will be needed to define the network-level impact.

Reviewer #3 (Recommendations for the authors):

(1) The authors could bring some of this data together by examining CRFR1 dependence of optical stimulationinduced increases in firing. Further, the authors have devoted significant effort to exploring how the BNST and CEA project to the CIN, yet their ephys does not explore site-specific infusion of ChR2 into either region. How are we to be sure it is not some other population of CRF neurons mediating this effect? The alcohol data does not appear particularly robust, but I think if the authors wanted to, they could explore other concentrations. Mostly I think it is important to discuss the limitations of acute alcohol on 5a brain slice.

We thank the reviewer for these thoughtful comments, which helped us strengthen the mechanistic interpretation of the CRF-CIN interaction. In the revised manuscript, we have addressed each point as follows:

- CRFR1 dependence of optogenetically evoked responses: We performed new recordings in which optogenetic stimulation of CRF⁺ terminals in the dorsal striatum was conducted in the presence of the CRFR1 antagonist antalarmin. The increase in CIN firing evoked by light stimulation was abolished under CRFR1 blockade, confirming that this effect is mediated through CRFR1 activation (new Figure 5J, 5K, third paragraph of the corresponding Result section). These results directly link the functional effects of CRF⁺ terminal activation to CRFR1 signaling on CINs.

- CeA vs. BNST projection specificity: The reviewer is correct that CeA and BNST projections were not analyzed separately. As unknown pathways, our experiment was designed to first establish the monosynaptic connections between CeA/BNST CRF neurons to striatal CINs. Future studies would further explore the specific contribution of each site. However, our data exclude the possibility of other CRF neurons as we selectively infused Cre-dependent opsins into both CeA and BNST of CRF-Cre mice (Figure 3G-3J).

- Limitations of acute slice experiments: We have expanded the Discussion (sixth paragraph) to acknowledge that acute slice physiology cannot fully capture the dynamic and network-level effects of ethanol observed in vivo. While this preparation enables mechanistic precision, factors such as washout, diffusion constraints, and the absence of systemic feedback may underestimate ethanol’s impact on CINs. We now explicitly note this limitation and highlight the need for in vivo studies to examine behavioral and circuit-level implications of CRF–alcohol interactions.

Collectively, these revisions clarify the CRFR1 dependence of CRF⁺ terminal effects and reaffirm that both CeA and BNST projections contribute to CIN modulation while addressing the methodological limitations of the slice preparation.

Reviewer #4 Public Review):

This manuscript presents a compelling and methodologically rigorous investigation into how corticotropin-releasing factor (CRF) modulates cholinergic interneurons (CINs) in the dorsal striatum - a brain region central to cognitive flexibility and action selection-and how this circuit is disrupted by alcohol exposure. Through an integrated series of anatomical, optogenetic, electrophysiological, and imaging experiments, the authors uncover a previously uncharacterized CRF⁺ projection from the central amygdala (CeA) and bed nucleus of the stria terminalis (BNST) to dorsal striatal CINs.

Strengths:

Key strengths of the study include the use of state-of-the-art monosynaptic rabies tracing, CRF-Cre transgenic models, CRFR1 reporter lines, and functional validation of synaptic connectivity and neurotransmitter release. The finding that CRF enhances CIN excitability and acetylcholine (ACh) release via CRFR1, and that this effect is attenuated by acute alcohol exposure and withdrawal, provides important mechanistic insight into how stress and alcohol interact to impair striatal function. These results position CRF signaling in CINs as a novel contributor to alcohol use disorder (AUD) pathophysiology, with implications for relapse vulnerability and cognitive inflexibility associated with chronic alcohol intake. The study is well-structured, with a clear rationale, thorough methodology, and logical progression of results. The discussion effectively contextualizes the findings within broader addiction neuroscience literature and suggests meaningful future directions, including therapeutic targeting of CRFR1 signaling in the dorsal striatum.

Weaknesses:

(1) Minor areas for improvement include occasional redundancy in phrasing, slightly overlong descriptions in the abstract and significance sections, and a need for more concise language in some places. Nevertheless, these do not detract from the manuscript's overall quality or impact. Overall, this is a highly valuable contribution to the fields of addiction neuroscience and striatal circuit function, offering novel insights into stress-alcohol interactions at the cellular and circuit level, which requires minor editorial revisions.

We have streamlined the abstract and significance statement, reduced redundancy, and improved conciseness throughout the text. We appreciate the reviewer’s feedback, which has helped us further strengthen the clarity and readability of the manuscript.

Reviewer #4 (Recommendations for the authors):

(1) Line 29-30: Slightly verbose. Consider: "Alcohol relapse is associated with corticotropin-releasing factor (CRF) signaling and altered reward pathway function, though the precise mechanisms are unclear."

The sentence has been revised as recommended to improve clarity and conciseness in the introductory section (Lines 31-32).

(2) Lines 39-43: Good synthesis, but could better emphasize the novelty of identifying a CRF-CIN pathway.

The abstract has been revised to more clearly emphasize the novelty of identifying a CRF-CIN pathway and its functional significance (Line 42-43).

(3) Lines 66-68: Consider integrating clinical relevance more directly, e.g., "AUD affects over 14 million adults in the U.S., with relapse often triggered by stress...".

The introduction has been revised to more directly emphasize the clinical relevance of alcohol use disorder, including its high prevalence and the role of stress in relapse, thereby underscoring the translational significance of our findings (Lines 68-69).

(4) Line 83: Repetition of "goal-directed learning, habit formation, and behavioral flexibility" appears multiple times; consider variety.

We have varied the phrasing in the Introduction to avoid redundancy. Specifically, in place of repeating “goal-directed learning, habit formation, and behavioral flexibility,” we now use alternative terms such as “action selection,” “habitual responding,” and “cognitive flexibility,” depending on the context.

(5) Lines 107-116: Clarify why both rats and mice were used-do they serve different experimental purposes?

We now explain that each species was used for complementary experimental purposes. Rats were used for histological validation of CRFR1 expression using the CRFR1-Cre-tdTomato line, which has been extensively characterized in this species. Mice were used for the majority of electrophysiological, optogenetic, and GRAB-ACh sensor experiments due to the availability of well-established transgenic CRF-Cre-driver lines. This division allowed us to leverage the most appropriate tools in each species to address different aspects of the study. We have clarified this rationale in the Methods (first paragraph of the “Animals” section) and Discussion (third paragraph).

(6) Electrophysiology section: The distinction between acute exposure vs. withdrawal could be further emphasized.

To better highlight the distinction between acute alcohol exposure and withdrawal, we have clarified the timing and context of each condition within the Results section for Figure 6. Specifically, we now distinguish the immediate suppressive effects of alcohol observed during bath application (acute exposure) from the subsequent changes in CIN firing measured after washout (withdrawal). These revisions clarify the temporal dynamics and functional implications of CRF–alcohol interactions in our experimental design.

(7) Lines 227-229: Reword for clarity: "Significantly more BNST neurons projected to CINs compared to the CeA...".

The sentence has been reworded to clarify as recommended (Lines 247-248).

(8) Lines 373-374: Consider connecting the CRF-CIN circuit to behavioral inflexibility in AUD more directly.

We have modified the sentence (Lines 390-395) to more explicitly link alcohol-induced dysregulation of the CRF–CIN circuit to behavioral inflexibility in AUD, consistent with the established role of CINs in action selection and cognitive flexibility.

(9) Lines 387-389: This is an excellent point about stress resilience; consider expanding with examples or potential implications.

We thank the reviewer for this insightful suggestion. In the revised Discussion (sixth paragraph), we expanded this section to more directly connect alcohol-induced disruption of CRF–CIN signaling with impaired stress resilience and behavioral inflexibility. Specifically, we now note that such dysregulation may compromise stress resilience mechanisms mediated by CRF–cholinergic interactions in the striatum and related corticostriatal circuits. We further discuss how impaired CIN responsiveness could blunt adaptive behavioral adjustments under stress, biasing animals toward habitual or compulsive alcohol seeking. This addition highlights the broader implication that alcohol-induced alterations in CRF–CIN signaling may contribute to relapse vulnerability by undermining adaptive stress coping.

References

English, D. F., O. Ibanez-Sandoval, E. Stark, F. Tecuapetla, G. Buzsaki, K. Deisseroth, J. M. Tepper and T. Koos (2011). "GABAergic circuits mediate the reinforcement-related signals of striatal cholinergic interneurons." Nat Neurosci 15(1): 123–130.

Gangal, H., J. Iannucci, Y. Huang, R. Chen, W. Purvines, W. T. Davis, A. Rivera, G. Johnson, X. Xie, S. Mukherjee, V. Vierkant, K. Mims, K. O'Neill, X. Wang, L. A. Shapiro and J. Wang (2025). "Traumatic brain injury exacerbates alcohol consumption and neuroinflammation with decline in cognition and cholinergic activity." Transl Psychiatry 15(1): 403.

Huang, Z., R. Chen, M. Ho, X. Xie, H. Gangal, X. Wang and J. Wang (2024). "Dynamic responses of striatal cholinergic interneurons control behavioral flexibility." Sci Adv 10(51): eadn2446.

Lu, J. Y., Y. F. Cheng, X. Y. Xie, K. Woodson, J. Bonifacio, E. Disney, B. Barbee, X. H. Wang, M. Zaidi and J. Wang (2021). "Whole-Brain Mapping of Direct Inputs to Dopamine D1 and D2 Receptor-Expressing Medium Spiny Neurons in the Posterior Dorsomedial Striatum." Eneuro 8(1).

Ma, T., Z. Huang, X. Xie, Y. Cheng, X. Zhuang, M. J. Childs, H. Gangal, X. Wang, L. N. Smith, R. J. Smith, Y. Zhou and J. Wang (2021). "Chronic alcohol drinking persistently suppresses thalamostriatal excitation of cholinergic neurons to impair cognitive flexibility." J Clin Invest 132(4): e154969.

Potjer, E. V., X. Wu, A. N. Kane and J. G. Parker (2025). "Parkinsonian striatal acetylcholine dynamics are refractory to L-DOPA treatment." bioRxiv.

Purvines, W., H. Gangal, X. Xie, J. Ramos, X. Wang, R. Miranda and J. Wang (2025). "Perinatal and prenatal alcohol exposure impairs striatal cholinergic function and cognitive flexibility in adult offspring." Neuropharmacology 279: 110627.

Ren, Y., Y. Liu and M. Luo (2021). "Gap Junctions Between Striatal D1 Neurons and Cholinergic Interneurons." Front Cell Neurosci 15: 674399.

Touponse, G. C., M. B. Pomrenze, T. Yassine, V. Mehta, N. Denomme, Z. Zhang, R. C. Malenka and N. Eshel (2025). "Cholinergic modulation of dopamine release drives effortful behavior." bioRxiv.

Reviewer #1 (Public review):

Summary:

This study presents an interesting behavioral paradigm and reveals interactive effects of social hierarchy and threat type on defensive behaviors. However, addressing the aforementioned points regarding methodological detail, rigor in behavioral classification, depth of result interpretation, and focus of the discussion is essential to strengthen the reliability and impact of the conclusions in a revised manuscript.

Strengths:

The paper is logically sound, featuring detailed classification and analysis of behaviors, with a focus on behavioral categories and transitions, thereby establishing a relatively robust research framework.

Weaknesses:

Several points require clarification or further revision.

(1) Methods and Terminology Regarding Social Hierarchy:

The study uses the tube test to determine subordinate status, but the methodological description is quite brief. Please provide a more detailed account of the experimental procedure and the criteria used for determination.

The dominance hierarchy is established based on pairs of mice. However, the use of terms like "group cohesion" - typically applied to larger groups - to describe dyadic interactions seems overstated. Please revise the terminology to more accurately reflect the pairwise experimental setup.

(2) Criteria and Validity of Behavioral Classification:

The criteria for classifying mouse behaviors (e.g., passive defense, active defense) are not sufficiently clear. Please explicitly state the operational definitions and distinguishing features for each behavioral category.

How was the meaningfulness and distinctness of these behavioral categories ensured to avoid overlap? For instance, based on Figure 3E, is "active defense" synonymous with "investigative defense," involving movement to the near region followed by return to the far region? This requires clearer delineation.

The current analysis focuses on a few core behaviors, while other recorded behaviors appear less relevant. Please clarify the principles for selecting or categorizing all recorded behaviors.

(3) Interpretation of Key Findings and Mechanistic Insights:

Looming exposure increased the proportion of proactive bouts in the dominant zone but decreased it in the subordinate zone (Figure 4G), with a similar trend during rat exposure. Please provide a potential explanation for this consistent pattern. Does this consistency arise from shared neural mechanisms, or do different behavioral strategies converge to produce similar outputs under both threats?

(4) Support for Claims and Study Limitations:

The manuscript states that this work addresses a gap by showing defensive responses are jointly shaped by threat type and social rank, emphasizing survival-critical behaviors over fear or stress alone. However, it is possible that the behavioral differences stem from varying degrees of danger perception rather than purely strategic choices. This warrants a clear description and a deeper discussion to address this possibility.

The Discussion section proposes numerous brain regions potentially involved in fear and social regulation. As this is a behavioral study, the extensive speculation on specific neural circuitry involvement, without supporting neuroscience data, appears insufficiently grounded and somewhat vague. It is recommended to focus the discussion more on the implications of the behavioral findings themselves or to explicitly frame these neural hypotheses as directions for future research.

Reviewer #2 (Public review):

Summary:

The authors investigate how dominance hierarchy shapes defensive strategies in mice under two naturalistic threats: a transient visual looming stimulus and a sustained live rat. By comparing single versus paired testing, they report that social presence attenuates fear and that dominant and subordinate mice exhibit different patterns of defensive and social behaviors depending on threat type. The work provides a rich behavioral dataset and a potentially useful framework for studying hierarchical modulation of innate fear.

Strengths:

(1) The study uses two ecologically meaningful threat paradigms, allowing comparison across transient and sustained threat contexts.

(2) Behavioral quantification is detailed, with manual annotation of multiple behavior types and transition-matrix level analysis.

(3) The comparison of dominant versus subordinate pairs is novel in the context of innate fear.

(4) The manuscript is well-organized and clearly written.

(5) Figures are visually informative and support major claims.

Weaknesses:

Lack of neural mechanism insights.

Reviewer #3 (Public review):

Summary:

This study examines how dominance hierarchy influences innate defensive behaviors in pair-housed male mice exposed to two types of naturalistic threats: a transient looming stimulus and a sustained live rat. The authors show that social presence reduces fear-related behaviors and promotes active defense, with dominant mice benefiting more prominently. They also demonstrate that threat exposure reinforces social roles and increases group cohesion. The work highlights the bidirectional interaction between social structure and defensive behavior.

Strengths:

This study makes a valuable contribution to behavioral neuroscience through its well-designed examination of socially modulated fear. A key strength is the use of two ethologically relevant threat paradigms - a transient looming stimulus and a sustained live predator, enabling a nuanced comparison of defensive behaviors. The experimental design is robust, systematically comparing animals tested alone versus with their cage mate to cleanly isolate social effects. The behavioral analysis is sophisticated, employing detailed transition maps that reveal how social context reshapes behavioral sequences, going beyond simple duration measurements. The finding that social modulation is rank-dependent adds significant depth, linking social hierarchy to adaptive defense strategies. Furthermore, the demonstration that threat exposure reciprocally enhances social cohesion provides a compelling systems-level perspective. Together, these elements establish a strong behavioral framework for future investigations into the neural circuits underlying socially modulated innate fear.

Weaknesses:

The study exhibits several limitations. The neural mechanism proposed is speculative, as the study provides no causal evidence.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary: 

This study presents an interesting behavioral paradigm and reveals interactive effects of social hierarchy and threat type on defensive behaviors. However, addressing the aforementioned points regarding methodological detail, rigor in behavioral classification, depth of result interpretation, and focus of the discussion is essential to strengthen the reliability and impact of the conclusions in a revised manuscript. 

Strengths: 

The paper is logically sound, featuring detailed classification and analysis of behaviors, with a focus on behavioral categories and transitions, thereby establishing a relatively robust research framework. 

Weaknesses: 

Several points require clarification or further revision. 

(1) Methods and Terminology Regarding Social Hierarchy: 

The study uses the tube test to determine subordinate status, but the methodological description is quite brief. Please provide a more detailed account of the experimental procedure and the criteria used for determination. 

We will add more details about how the tube test was performed in the revised manuscript.

The dominance hierarchy is established based on pairs of mice. However, the use of terms like "group cohesion" - typically applied to larger groups - to describe dyadic interactions seems overstated. Please revise the terminology to more accurately reflect the pairwise experimental setup.

Thanks for the comment. We agree that the term “group cohesion” can be misleading and will replace it with “social engagement”.

(2) Criteria and Validity of Behavioral Classification: 

The criteria for classifying mouse behaviors (e.g., passive defense, active defense) are not sufficiently clear. Please explicitly state the operational definitions and distinguishing features for each behavioral category. 

Passive defense was defined as an immobility-based defensive strategy characterized by suppression of locomotor activity. This category included freezing and tail rattling, which in our study involved minimal body displacement aside from rapid tail vibration. Active defense was defined as movement- or posture-dependent defensive strategy, encompassing behaviors that involved locomotor engagement or spatial repositioning relative to the threat, including approach, investigation, withdrawal, and stretch-attend. We will clarify this in the revised manuscript.

How was the meaningfulness and distinctness of these behavioral categories ensured to avoid overlap? For instance, based on Figure 3E, is "active defense" synonymous with "investigative defense," involving movement to the near region followed by return to the far region? This requires clearer delineation. 

Defensive behaviors in the rat exposure paradigm were grouped into two categories: passive and active defense, each comprising distinct behaviors. All the manually annotated behaviors were mutually exclusive; that is, each video frame was assigned a single behavioral label to avoid overlap across behaviors. Active defense includes four behaviors: approach, investigation, withdrawal, and stretch-attend. We will clarify these points in the revised manuscript.

The current analysis focuses on a few core behaviors, while other recorded behaviors appear less relevant. Please clarify the principles for selecting or categorizing all recorded behaviors.

Thank you for pointing this out. In the current study, we focused primarily on defensive and social behaviors. We also included several neutral solitary behaviors related to anxiety and defensive state, such as sniffing, grooming, and rearing, which were consistently expressed across animals and closely linked to our main findings. We will clarify this rationale in the revised manuscript.

(3) Interpretation of Key Findings and Mechanistic Insights:

Looming exposure increased the proportion of proactive bouts in the dominant zone but decreased it in the subordinate zone (Figure 4G), with a similar trend during rat exposure. Please provide a potential explanation for this consistent pattern. Does this consistency arise from shared neural mechanisms, or do different behavioral strategies converge to produce similar outputs under both threats?

Thanks for bringing up this important question. The consistent increase in proactive bouts in dominant mice across both paradigms suggests a consistent rank-dependent reorganization of dyadic interaction under threats. We propose that this convergence reflects a shared neural mechanism that links defensive state with social-rank information, potentially mediated by overlapping hypothalamic and prefrontal circuits. We will expand the Discussion to incorporate this explanation.

(4) Support for Claims and Study Limitations:

The manuscript states that this work addresses a gap by showing defensive responses are jointly shaped by threat type and social rank, emphasizing survival-critical behaviors over fear or stress alone. However, it is possible that the behavioral differences stem from varying degrees of danger perception rather than purely strategic choices. This warrants a clear description and a deeper discussion to address this possibility.

We thank the reviewer for this insightful comment. We agree that, in principle, behavioral differences could arise from variations in perceived danger rather than strategic choice. In humans, decisions can sometimes reflect value-based strategies that override perceived danger. In contrast, under naturalistic threat conditions, mice likely rely predominantly on danger perception to make behavioral decisions, and such responses are expected to be consistent with value-based strategies shaped by natural selection. In the revised manuscript, we will expand the Discussion to address the role of threat perception and its relationship to decision-making in our behavioral paradigms.

The Discussion section proposes numerous brain regions potentially involved in fear and social regulation. As this is a behavioral study, the extensive speculation on specific neural circuitry involvement, without supporting neuroscience data, appears insufficiently grounded and somewhat vague. It is recommended to focus the discussion more on the implications of the behavioral findings themselves or to explicitly frame these neural hypotheses as directions for future research.

We will revise the Discussion to focus more directly on behavioral findings and add explicit neural hypotheses as potential future directions.

Reviewer #2 (Public review):

Summary:

The authors investigate how dominance hierarchy shapes defensive strategies in mice under two naturalistic threats: a transient visual looming stimulus and a sustained live rat. By comparing single versus paired testing, they report that social presence attenuates fear and that dominant and subordinate mice exhibit different patterns of defensive and social behaviors depending on threat type. The work provides a rich behavioral dataset and a potentially useful framework for studying hierarchical modulation of innate fear.

Strengths:

(1) The study uses two ecologically meaningful threat paradigms, allowing comparison across transient and sustained threat contexts.

(2) Behavioral quantification is detailed, with manual annotation of multiple behavior types and transition-matrix level analysis.

(3) The comparison of dominant versus subordinate pairs is novel in the context of innate fear.

(4) The manuscript is well-organized and clearly written.

(5) Figures are visually informative and support major claims.

Weaknesses:

Lack of neural mechanism insights.

The current study focused on behavior. In the revised manuscript, we will incorporate a discussion of potential neural mechanisms and highlight this as an important direction for future work.

Reviewer #3 (Public review):

Summary:

This study examines how dominance hierarchy influences innate defensive behaviors in pair-housed male mice exposed to two types of naturalistic threats: a transient looming stimulus and a sustained live rat. The authors show that social presence reduces fear-related behaviors and promotes active defense, with dominant mice benefiting more prominently. They also demonstrate that threat exposure reinforces social roles and increases group cohesion. The work highlights the bidirectional interaction between social structure and defensive behavior.

Strengths:

This study makes a valuable contribution to behavioral neuroscience through its well-designed examination of socially modulated fear. A key strength is the use of two ethologically relevant threat paradigms - a transient looming stimulus and a sustained live predator, enabling a nuanced comparison of defensive behaviors. The experimental design is robust, systematically comparing animals tested alone versus with their cage mate to cleanly isolate social effects. The behavioral analysis is sophisticated, employing detailed transition maps that reveal how social context reshapes behavioral sequences, going beyond simple duration measurements. The finding that social modulation is rank-dependent adds significant depth, linking social hierarchy to adaptive defense strategies. Furthermore, the demonstration that threat exposure reciprocally enhances social cohesion provides a compelling systems-level perspective. Together, these elements establish a strong behavioral framework for future investigations into the neural circuits underlying socially modulated innate fear.

Weaknesses:

The study exhibits several limitations. The neural mechanism proposed is speculative, as the study provides no causal evidence.

Establishing causal evidence for neural mechanisms is beyond the scope of the current behavioral study. We highlight this as an important direction for future work.

Reviewer #2 (Public review):

Summary:

Tan et al. examined how multivoxel patterns shift in time windows surrounding event boundaries caused by both prediction errors and prediction uncertainty. They observed that some regions of the brain show earlier pattern shifts than others, followed by periods of increased stability. The authors combine their recent computational model to estimate event boundaries that are based on prediction error vs. uncertainty and use this to examine the moment-to-moment dynamics of pattern changes. I believe this is a meaningful contribution that will be of interest to memory, attention, and complex cognition research.

Strengths:

The authors have shown exceptional transparency in terms of sharing their data, code, and stimuli which is beneficial to the field for future examinations and to the reproduction of findings. The manuscript is well written with clear figures. The study starts from a strong theoretical background to understand how the brain represents events and have used a well-curated set of stimuli. Overall, the authors extend the event segmentation theory beyond prediction error to include prediction uncertainty which is an important theoretical shift that has implications in episodic memory encoding, use of semantic and schematic knowledge and to attentional processing.

Weaknesses:

(1) I am not fully satisfied with the author's explanation of pattern shifts occurring 11.9s prior to event boundaries. The average length of time for an event was 21.4 seconds. The window around the identified event boundaries was 20 seconds on either side. The earliest identified pattern shift peaks occur at 11.9s prior to the actual event boundary. This would mean on average, a pattern shift is occurring approximately at the midway point of the event (11.9s prior to a boundary of a 21.4s event is approx. the middle of an event). The authors offer up an explanation in which top down regions signal an update that propagates to lower order regions closer to the boundary. To make this interpretation concrete, they added an example: "in a narrative where a goal is reached midway-for instance, a mystery solved before the story formally ends-higher-order regions may update the event representation at that point, and this updated model then cascades down to shape processing in lower-level regions". This might make sense in a one-off case of irregular storytelling, but it is odd to think this would generalize. If an event is occurring and a given collection of regions represent that event, it doesn't follow the accepted convention of multivariate representational analysis that that set of regions would undergo such a large shift in patterns in the middle of an event. The stabilization of these patterns taking so long is also odd to me. I suspect some of these findings may be due to the stimuli used in this experiment and I am not confident this would generalize and invite the authors to disagree and explain. In the case of the exercise routine video, I try to imagine going from the push-up event to the jumping jack event. The actor stops doing pushups, stands up, and moves minimally for 16 seconds (these lulls are not uncommon). At that point they start doing jumping jacks. It is immediately evident from that moment on that jumping jacks will be the kind of event you are perceiving which may explain the long delay in event pattern stabilisation. Then about 11.9s prior to the end of the event, when the person is still performing jumping jacks (at this point they have been performing jumping jacks for 6 seconds), I would expect the brain to still be expecting this " jumping jacks event". For some reason at this point multivariate patterns in higher order regions shift. I do not understand what kind of top down processing is happening here and the reviewers need to be more concrete in their explanation because as of right now it is ill-defined. I also recognize that being specific to jumping jacks is maybe unfair, but this would apply to the push-ups, granola bar eating, or table cleaning events in the same manner. I suspect one possibility is that the participants realize that the stereotyped action of jumping jacks is going to continue and, thus, mindwander to other thoughts while waiting for novel, informative information to be presented. This explanation would challenge the more active top down processing assumed by the authors.

I had provided a set of concerns to the authors that were not part of the public review and were not addressed. I was unaware of the exact format of the eLife approach, but I think they are worth open discussion so I am adding them here for consideration. Apologies for any confusion.

(2) Why did the authors not examine event boundary activity magnitude differences from the uncertainty vs error boundaries? I see that the authors have provided the data on the openneuro. However, it seems like the difference in activity maps would not only provide extra contextualization of the findings, but also be fairly trivial. Just by eye-balling the plots, it appears as though there may be activity differences in the mPFC occurring shortly after a boundary between the two. Given this regions role in prediction error and schema, it would be important to understand whether this difference is merely due to thresholding effects or is statistically meaningful.

(3) Further, the authors omitted all subcortical regions some of which would be especially interesting such as the hippocampus, basal ganglia, ventral tegmental area. These regions have a rich and deep background in event boundary activity, and prediction error. Univariate effects in these regions may provide interesting effects that might contextualize some of the pattern shifts in the cortex.

(3) I see that field maps were collected, but the fmriprep methods state that susceptibility distortion correction was not performed. Is there a reason to omit this?

(4) How many events were present in the stimuli?

Reviewer #3 (Public review):

Summary:

The aim of this study was to investigate the temporal progression of the neural response to event boundaries in relation to uncertainty and error. Specifically, the authors asked 1. How neural activity changes before and after event boundaries 2. If uncertainty and error both contribute to explaining the occurrence of event boundaries and 3. If uncertainty and error have unique contributions to explaining the temporal progression of neural activity.

Strengths:

One strength of this paper is that it builds on an already validated computational model. It relies on straightforward and interpretable analysis techniques to answer the main question, with a smart combination of pattern similarity metrics and FIR. This combination of methods may also be an inspiration to other researchers in the field working on similar questions. The paper is well written and easy to follow. The paper convincingly shows that 1. There is a temporal progression of neural activity change before and after an event boundary 2. Event boundaries are predicted best by the combination of uncertainty and error signals.

Weaknesses:

Regarding question 3, the results are less convincing. Although the analyses in Figure S1 show that there are some unique contributions of uncertainty and error, it is unclear to what extent the results in Figure 7 are driven by shared variance. Therefore, it is not clear to what extent the main claim in the abstract is due to shared or unique variance. More specific comments are provided below.

The other issue is the distance between events is short compared to the pre-onset effects that are observed. Halfway the distance between two events there are already neural signatures of change relating to the upcoming event boundary. I wonder if methodological issues could explain this effect and if not, what could allow participants to notice the impending event boundary.

Impact:

If these comments can be addressed sufficiently, I expect that this work will impact the field in its thinking on what drives event boundaries and spur interest in understanding the mechanisms behind the temporal progression of neural activity around these boundaries.

Comments

(1) The correlation between uncertainly and prediction error is very high, which makes it challenging to disentangle the effects of both on the neural response. The analysis in Figure S1 shows that the two predictors indeed have dissociable contributions. However, the results mainly reported in the discussion section and abstract still rely on models where only one of these factors is included at a time. This makes it debatable whether these specific networks mentioned really reflect unique contributions of each of these components. I specifically refer to this statement in the abstract: "Error-driven boundaries were associated with early pattern shifts in ventrolateral prefrontal areas, followed by pattern stabilization in prefrontal and temporal areas. Uncertainty-driven boundaries were linked to shifts in parietal regions within the dorsal attention network, with minimal subsequent stabilization. ". I would encourage repeating all analyses (also the ones in figure 7) with a models that includes both predictors and showing both results in the manuscript, so it is clear which regions really show unique variance related to one of the predictors. I also wonder why it is necessary to look at model comparisons between the combined and unique models, rather than simply reporting the significance of each predictor in the combined model.

(2) The distance between event boundaries ranges between 20 and 30 seconds. The early pre-boundary effect that are observed in the manuscript occur at -12 seconds. This means that these effects occur roughly halfway between the previous and current event. This seems much earlier than expected. That is why I worry that the FIR analyses might not be able to distinguish effects of the previous event from effects of the upcoming event. What evidence is there that the FIR analyses can actually properly show the return to baseline? One way to address this might be to randomize the locations of the event boundaries while preserving the distance between them and rerun the models. This will give a null-model with the same event distances and should be able to distinguish this temporal overlap from the true effects of event boundaries.

(3) If the analyses in point 2 confirm that there is indeed an event-boundary related change that occurs 12 seconds before event onset, it is important to consider what might cause these changes. Are there cues in the movie that indicate that an event boundary is coming? It would be interesting to investigate whether uncertainty and error are higher than expected at 12 seconds pre-onset.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This paper investigates the control signals that drive event model updating during continuous experience. The authors apply predictions from previously published computational models to fMRI data acquired while participants watched naturalistic video stimuli. They first examine the time course of BOLD pattern changes around human-annotated event boundaries, revealing pattern changes preceding the boundary in anterior temporal and then parietal regions, followed by pattern stabilization across many regions. The authors then analyze time courses around boundaries generated by a model that updates event models based on prediction error and another that uses prediction uncertainty. These analyses reveal overlapping but partially distinct dynamics for each boundary type, suggesting that both signals may contribute to event segmentation processes in the brain.

Strengths:

(1) The question addressed by this paper is of high interest to researchers working on event cognition, perception, and memory. There has been considerable debate about what kinds of signals drive event boundaries, and this paper directly engages with that debate by comparing prediction error and prediction uncertainty as candidate control signals.

(2) The authors use computational models that explain significant variance in human boundary judgments, and they report the variance explained clearly in the paper.

(3) The authors' method of using computational models to generate predictions about when event model updating should occur is a valuable mechanistic alternative to methods like HMM or GSBS, which are data-driven.

(4) The paper utilizes an analysis framework that characterizes how multivariate BOLD pattern dissimilarity evolves before and after boundaries. This approach offers an advance over previous work focused on just the boundary or post-boundary points.

We appreciate this reviewer’s recognition of the significance of this research problem, and of the value of the approach taken by this paper.

Weaknesses:

(1) While the paper raises the possibility that both prediction error and uncertainty could serve as control signals, it does not offer a strong theoretical rationale for why the brain would benefit from multiple (empirically correlated) signals. What distinct advantages do these signals provide? This may be discussed in the authors' prior modeling work, but is left too implicit in this paper.

We added a brief discussion in the introduction highlighting the complementary advantages of prediction error and prediction uncertainty, and cited prior theoretical work that elaborates on this point. Specifically, we now note that prediction error can act as a reactive trigger, signaling when the current event model is no longer sufficient (Zacks et al., 2007). In contrast, prediction uncertainty is framed as proactive, allowing the system to prepare for upcoming changes even before they occur (Baldwin & Kosie, 2021; Kuperberg, 2021). Together, this makes clearer why these two signals could each provide complementary benefits for effective event model updating.

"One potential signal to control event model updating is prediction error—the difference between the system’s prediction and what actually occurs. A transient increase in prediction error is a valid indicator that the current model no longer adequately captures the current activity. Event Segmentation Theory (EST; Zacks et al., 2007) proposes that event models are updated when prediction error increases beyond a threshold, indicating that the current model no longer adequately captures ongoing activity. A related but computationally distinct proposal is that prediction uncertainty (also termed "unpredictability") can serve as a control signal (Baldwin & Kosie, 2021). The advantage of relying on prediction uncertainty to detect event boundaries is that it is inherently proactive: the cognitive system can start looking for cues about what might come next before the next event starts (Baldwin & Kosie, 2021; Kuperberg, 2021). "

(2) Boundaries derived from prediction error and uncertainty are correlated for the naturalistic stimuli. This raises some concerns about how well their distinct contributions to brain activity can be separated. The authors should consider whether they can leverage timepoints where the models make different predictions to make a stronger case for brain regions that are responsive to one vs the other.

We addressed this concern by adding an analysis that explicitly tests the unique contributions of prediction error– and prediction uncertainty–driven boundaries to neural pattern shifts. In the revised manuscript, we describe how we fit a combined FIR model that included both boundary types as predictors and then compared this model against versions with only one predictor. This allowed us to identify the variance explained by each boundary type over and above the other. The results revealed two partially dissociable sets of brain regions sensitive to error- versus uncertainty-driven boundaries (see Figure S1), strengthening our argument that these signals make distinct contributions.

"To account for the correlation between uncertainty-driven boundaries and error-driven boundaries, we also fitted a FIR model that predicted pattern dissimilarity from both types of boundaries (combined FIR) for each parcel. Then, we performed two likelihood ratio tests: combined FIR to error FIR, which measures the unique contribution of uncertainty boundaries to pattern dissimilarity, and combined FIR to uncertainty FIR, which measures the unique contribution of error boundaries to pattern dissimilarity. The analysis also revealed two dissociable sets of brain regions associated with each boundary type (see Figure S1)."

(3) The authors refer to a baseline measure of pattern dissimilarity, which their dissimilarity measure of interest is relative to, but it's not clear how this baseline is computed. Since the interpretation of increases or decreases in dissimilarity depends on this reference point, more clarity is needed.

We clarified how the FIR baseline is estimated in the methods section. Specifically, we now explain that the FIR coefficients should be interpreted relative to a reference level, which reflects the expected dissimilarity when timepoints are far from an event boundary. This makes it clear what serves as the comparison point for observed increases or decreases in dissimilarity.

"The coefficients from the FIR model indicate changes relative to baseline, which can be conceptualized as the expected value when far from event boundaries."

(4) The authors report an average event length of ~20 seconds, and they also look at +20 and -20 seconds around each event boundary. Thus, it's unclear how often pre- and post-boundary timepoints are part of adjacent events. This complicates the interpretations of the reported time courses.

This is related to reviewer's 2 comment, and it will be addressed below.

(5) The authors describe a sequence of neural pattern shifts during each type of boundary, but offer little setup of what pattern shifts we might expect or why. They also offer little discussion of what cognitive processes these shifts might reflect. The paper would benefit from a more thorough setup for the neural results and a discussion that comments on how the results inform our understanding of what these brain regions contribute to event models.

We thank the reviewer for this advice on how better to set the context for the different potential outcomes of the study. We expanded both the introduction and discussion to better set up expectations for neural pattern shifts and to interpret what these shifts may reflect. In the introduction, we now describe prior findings showing that sensory regions tend to update more quickly than higher-order multimodal regions (Baldassano et al., 2017; Geerligs et al., 2021, 2022), and we highlight that it remains unclear whether higher-order updates precede or follow those in lower-order regions. We also note that our analytic approach is well-suited to address this open question. In the discussion, we then interpret our results in light of this framework. Specifically, we describe how we observed early shifts in higher-order areas such as anterior temporal and prefrontal cortex, followed by shifts in parietal and dorsal attention regions closer to event boundaries. This pattern runs counter to the traditional bottom-up temporal hierarchy view and instead supports a model of top-down updating, where high-level representations are updated first and subsequently influence lower-level processing (Friston, 2005; Kuperberg, 2021). To make this interpretation concrete, we added an example: in a narrative where a goal is reached midway—for instance, a mystery solved before the story formally ends—higher-order regions may update the event representation at that point, and this updated model then cascades down to shape processing in lower-level regions. Finally, we note that the widespread stabilization of neural patterns after boundaries may signal the establishment of a new event model.

Excerpt from Introduction:

“More recently, multivariate approaches have provided insights into neural representations during event segmentation. One prominent approach uses hidden Markov models (HMMs) to detect moments when the brain switches from one stable activity pattern to another (Baldassano et al., 2017) during movie viewing; these periods of relative stability were referred to as "neural states" to distinguish them from subjectively perceived events. Sensory regions like visual and auditory cortex showed faster transitions between neural states. Multi-modal regions like the posterior medial cortex, angular gyrus, and intraparietal sulcus showed slower neural state shifts, and these shifts aligned with subjectively reported event boundaries. Geerligs et al. (2021, 2022) employed a different analytical approach called Greedy State Boundary Search (GSBS) to identify neural state boundaries. Their findings echoed the HMM results: short-lived neural states were observed in early sensory areas (visual, auditory, and somatosensory cortex), while longer-lasting states appeared in multi-modal regions, including the angular gyrus, posterior middle/inferior temporal cortex, precuneus, anterior temporal pole, and anterior insula. Particularly prolonged states were found in higher-order regions such as lateral and medial prefrontal cortex.

The previous evidence about evoked responses at event boundaries indicates that these are dynamic phenomena evolving over many seconds, with different brain areas showing different dynamics (Ben-Yakov & Henson, 2018; Burunat et al., 2024; Kurby & Zacks, 2018; Speer et al., 2007; Zacks, 2010). Less is known about the dynamics of pattern shifts at event boundaries (e.g. whether shifts observed in higher-order regions precedes or follow shifts observed in lower-level regions), because the HMM and GSBS analysis methods do not directly provide moment-by-moment measures of pattern shifts. Both the spatial and temporal aspects of evoked responses and pattern shifts at event boundaries have the potential to provide evidence about two potential control processes (error-driven and uncertainty-driven) for event model updating.”

Excerpt from Discussion:

“We first characterized the neural signatures of human event segmentation by examining both univariate activity changes and multivariate pattern changes around subjectively identified event boundaries. Using multivariate pattern dissimilarity, we observed a structured progression of neural reconfiguration surrounding human-identified event boundaries. The largest pattern shifts were observed near event boundaries (~4.5s before) in dorsal attention and parietal regions; these correspond with regions identified by Geerligs et. al as shifting their patterns on a fast to intermediate timescale (2022). We also observed smaller pattern shifts roughly 12 seconds prior to event boundaries in higher-order regions within anterior temporal cortex and prefrontal cortex, and these are slow-changing regions identified by Geerligs et. al (2022). This is puzzling. One prevalent proposal, based on the idea of a cortical hierarchy of increasing temporal receptive windows (TRWs), suggests that higher-order regions should update representations after lower-order regions do (Chang et al., 2021). In this view, areas with shorter TRWs (e.g., word-level processors) pass information upward, where it is integrated into progressively larger narrative units (phrases, sentences, events). This proposal predicts neural shifts in higher-order regions to follow those in lower-order regions. By contrast, our findings indicate the opposite sequence. Our findings suggest that the brain might engage in top-down event representation updating, with changes in coarser-grain representations propagating downward to influence finer-grain representations. (Friston, 2005; Kuperberg, 2021). For example, in a narrative where the main goal is achieved midway—such as a detective solving a mystery before the story formally ends—higher-order regions might update the overarching event representation at that point, and this updated model could then cascade down to reconfigure how lower-level regions process the remaining sensory and contextual details. In the period after a boundary (around +12 seconds), we found widespread stabilization of neural patterns across the brain, suggesting the establishment of a new event model. Future work could focus on understanding the mechanisms behind the temporal progression of neural pattern changes around event boundaries.”

Reviewer #2 (Public review):

Summary:

Tan et al. examined how multivoxel patterns shift in time windows surrounding event boundaries caused by both prediction errors and prediction uncertainty. They observed that some regions of the brain show earlier pattern shifts than others, followed by periods of increased stability. The authors combine their recent computational model to estimate event boundaries that are based on prediction error vs. uncertainty and use this to examine the moment-to-moment dynamics of pattern changes. I believe this is a meaningful contribution that will be of interest to memory, attention, and complex cognition research.

Strengths:

The authors have shown exceptional transparency in terms of sharing their data, code, and stimuli, which is beneficial to the field for future examinations and to the reproduction of findings. The manuscript is well written with clear figures. The study starts from a strong theoretical background to understand how the brain represents events and has used a well-curated set of stimuli. Overall, the authors extend the event segmentation theory beyond prediction error to include prediction uncertainty, which is an important theoretical shift that has implications in episodic memory encoding, the use of semantic and schematic knowledge, and attentional processing.

We thank the reader for their support for our use of open science practices, and for their appreciation of the importance of incorporating prediction uncertainty into models of event comprehension.

Weaknesses:

The data presented is limited to the cortex, and subcortical contributions would be interesting to explore. Further, the temporal window around event boundaries of 20 seconds is approximately the length of the average event (21.4 seconds), and many of the observed pattern effects occur relatively distal from event boundaries themselves, which makes the link to the theoretical background challenging. Finally, while multivariate pattern shifts were examined at event boundaries related to either prediction error or prediction uncertainty, there was no exploration of univariate activity differences between these two different types of boundaries, which would be valuable.

The fact that we observed neural pattern shifts well before boundaries was indeed unexpected, and we now offer a more extensive interpretation in the discussion section. Specifically, we added text noting that shifts emerged in higher-order anterior temporal and prefrontal regions roughly 12 seconds before boundaries, whereas shifts occurred in lower-level dorsal attention and parietal regions closer to boundaries. This sequence contrasts with the traditional bottom-up temporal hierarchy view and instead suggests a possible top-down updating mechanism, in which higher-order representations reorganize first and propagate changes to lower-level areas (Friston, 2005; Kuperberg, 2021). (See excerpt for Reviewer 1’s comment #5.)

With respect to univariate activity, we did not find strong differences between error-driven and uncertainty-driven boundaries. This makes the multivariate analyses particularly informative for detecting differences in neural pattern dynamics. To support further exploration, we have also shared the temporal progression of univariate BOLD responses on OpenNeuro (BOLD_coefficients_brain_animation_pe_SEM_bold.html and BOLD_coefficients_brain_animation_uncertainty_SEM_bold.html in the derivatives/figures/brain_maps_and_timecourses/ directory; https://doi.org/10.18112/openneuro.ds005551.v1.0.4) for interested researchers.

Reviewer #3 (Public review):

Summary:

The aim of this study was to investigate the temporal progression of the neural response to event boundaries in relation to uncertainty and error. Specifically, the authors asked (1) how neural activity changes before and after event boundaries, (2) if uncertainty and error both contribute to explaining the occurrence of event boundaries, and (3) if uncertainty and error have unique contributions to explaining the temporal progression of neural activity.

Strengths:

One strength of this paper is that it builds on an already validated computational model. It relies on straightforward and interpretable analysis techniques to answer the main question, with a smart combination of pattern similarity metrics and FIR. This combination of methods may also be an inspiration to other researchers in the field working on similar questions. The paper is well written and easy to follow. The paper convincingly shows that (1) there is a temporal progression of neural activity change before and after an event boundary, and (2) event boundaries are predicted best by the combination of uncertainty and error signals.

We thank the reviewer for their thoughtful and supportive comments, particularly regarding the use of the computational model and the analysis approaches.

Weaknesses:

(1) The current analysis of the neural data does not convincingly show that uncertainty and prediction error both contribute to the neural responses. As both terms are modelled in separate FIR models, it may be that the responses we see for both are mostly driven by shared variance. Given that the correlation between the two is very high (r=0.49), this seems likely. The strong overlap in the neural responses elicited by both, as shown in Figure 6, also suggests that what we see may mainly be shared variance. To improve the interpretability of these effects, I think it is essential to know whether uncertainty and error explain similar or unique parts of the variance. The observation that they have distinct temporal profiles is suggestive of some dissociation,but not as convincing as adding them both to a single model.

We appreciate this point. It is closely related to Reviewer 1's comment 2; please refer to our response above.

(2) The results for uncertainty and error show that uncertainty has strong effects before or at boundary onset, while error is related to more stabilization after boundary onset. This makes me wonder about the temporal contribution of each of these. Could it be the case that increases in uncertainty are early indicators of a boundary, and errors tend to occur later?

We also share the intuition that increases in uncertainty are early indicators of a boundary, and errors tend to occur later. If that is the case, we would expect some lags between prediction uncertainty and prediction error. We examined lagged correlation between prediction uncertainty and prediction error, and the optimal lag is 0 for both uncertainty-driven and error-driven models. This indicates that when prediction uncertainty rises, prediction error also simultaneously rises.

Author response image 1.

(3) Given that there is a 24-second period during which the neural responses are shaped by event boundaries, it would be important to know more about the average distance between boundaries and the variability of this distance. This will help establish whether the FIR model can properly capture a return to baseline.

We have added details about the distribution of event lengths. Specifically, we now report that the mean length of subjectively identified events was 21.4 seconds (median 22.2 s, SD 16.1 s). For model-derived boundaries, the average event lengths were 28.96 seconds for the uncertainty-driven model and 24.7 seconds for the error-driven model.

" For each activity, a separate group of 30 participants had previously segmented each movie to identify fine-grained event boundaries (Bezdek et al., 2022). The mean event length was 21.4 s (median 22.2 s, SD 16.1 s). Mean event lengths for uncertainty-driven model and error-driven model were 28.96s, and 24.7s, respectively (Nguyen et al., 2024)."

(4) Given that there is an early onset and long-lasting response of the brain to these event boundaries, I wonder what causes this. Is it the case that uncertainty or errors already increase at 12 seconds before the boundaries occur? Or if there are other makers in the movie that the brain can use to foreshadow an event boundary? And if uncertainty or errors do increase already 12 seconds before an event boundary, do you see a similar neural response at moments with similar levels of error or uncertainty, which are not followed by a boundary? This would reveal whether the neural activity patterns are specific to event boundaries or whether these are general markers of error and uncertainty.

We appreciate this point; it is similar to reviewer 2’s comment 2. Please see our response to that comment above.

(5) It is known that different brain regions have different delays of their BOLD response. Could these delays contribute to the propagation of the neural activity across different brain areas in this study?

Our analyses use ±20 s FIR windows, and the key effects we report include shifts ~12s before boundaries in higher-order cortex and ~4.5s pre-boundary in dorsal attention/parietal areas. Given the literature above, region-dependent BOLD delays are much smaller (~1–2s) than the temporal structure we observe (Taylor et al., 2018), making it unlikely that HRF lag alone explains our multi-second, region-specific progression.

(6) In the FIR plots, timepoints -12, 0, and 12 are shown. These long intervals preclude an understanding of the full temporal progression of these effects.

For page length purposes, we did not include all timepoints. We uploaded a brain animation of all timepoints and coefficients for each parcel in Openneuro (PATTERN_coefficients_brain_animation_human_fine_pattern.html and PATTERN_coefficients_lines_human_fine.html in the derivatives/figures/brain_maps_and_timecourses/ directory; https://doi.org/10.18112/openneuro.ds005551.v1.0.4) for interested researchers.

References

Taylor, A. J., Kim, J. H., & Ress, D. (2018). Characterization of the hemodynamic response function across the majority of human cerebral cortex. NeuroImage, 173, 322–331. https://doi.org/10.1016/j.neuroimage.2018.02.061

Reviewer #1 (Public review):

Summary:

This manuscript offers a careful and technically impressive dissection of how subpopulations within the subthalamic nucleus support reward‑biased decision‑making. The authors recorded from STN neurons in monkeys performing an asymmetric‑reward version of a visual motion discrimination task and combined single‑unit analyses, regression modeling, and drift‑diffusion framework fitting to reveal functionally distinct clusters of neurons. Each subpopulation demonstrated unique relationships to decision variables - such as the evidence‑accumulation rate, decision bound, and non‑decision processes - as well as to post‑decision evaluative signals like choice accuracy and reward expectation. Together, these findings expand our understanding of the computational diversity of STN activity during complex, multi‑attribute choices.

Strengths:

(1) The use of an asymmetric‑reward paradigm enables a clean separation between perceptual and reward influences, making it possible to identify how STN neurons blend these different sources of information.

(2) The dataset is extensive and well‑controlled, with careful alignment between behavioral and neural analyses.

(3) Relating neuronal cluster activity to drift‑diffusion model parameters provides an interpretable computational link between neural population signals and observed behavior.

(4) The clustering analyses, validated across multiple parameters and distance metrics, reveal robust functional subgroups within STN. The differentiation of clusters with respect to both evidence and reward coding is an important advance over treating the STN as a unitary structure.

(5) By linking neural activity to predicted choice accuracy and reward expectation, the study extends the discussion of the STN beyond decision formation to include outcome monitoring and post‑decision evaluation.

Weaknesses:

(1) The inferred relationships between neural clusters and specific drift‑diffusion parameters (e.g., bound height, scaling factor, non‑decision time) are intriguing but inherently correlational. The authors should clarify that these associations do not necessarily establish distinct computational mechanisms.

(2) While the k‑means approach is well described, it remains somewhat heuristic. Including additional cross‑validation (e.g., cluster reproducibility across monkeys or sessions) would strengthen confidence in the four‑cluster interpretation.

(3) The functional dissociations across clusters are clearly described, but how these subgroups interact within the STN or through downstream basal‑ganglia circuits remains speculative.

(4) A natural next step would be to construct a generative multi‑cluster model of STN activity, in which each cluster is treated as a computational node (e.g., evidence integrator, bound controller, urgency or evaluative signal).

(5) Such a low‑dimensional, coupled model could reproduce the observed diversity of firing patterns and predict how interactions among clusters shape decision variables and behavior.

(6) Population‑level modeling of this kind would move the interpretation beyond correlational mapping and serve as an intermediate framework between single‑unit analysis and in‑vivo perturbation.

(7) Causal inference gap - Without perturbation data, it is difficult to determine whether the identified neural modulations are necessary or sufficient for the observed behavioral effects. A brief discussion of this limitation - and how future causal manipulations could test these cluster functions - would be valuable.

Reviewer #3 (Public review):

Summary:

In this study, the authors investigate single neuron activity in the subthalamic nucleus (STN) of two monkeys performing a perceptual decision-making task in which both perceptual evidence and reward were manipulated. They find rich representations of decision variables (such as choice, perceptual evidence and reward) in neural activity, and following prior work, cluster a subset of these neurons into subpopulations with varying activity profiles. Further, they relate the activity of neurons within these clusters to parameters of drift diffusion models (DDMs) fit to animal behaviour on trial subsets by neural firing rates, finding heterogeneous and temporally varying relationships between different clusters and DDM parameters, suggesting that STN neurons may play multiple roles in decision formation and evaluation.

Strengths:

The behavioural task used by the authors is rich and affords disambiguation between decision variables such as perceptual evidence, value and choice, by independently manipulating stimulus strength and reward size. Both their monkeys show good performance on the task, and their population of ~150 neurons across monkeys reveals a rich repertoire of decision-related activity in single neurons, with individual neurons showing strong tuning to choice, stimulus strength and reward bias. There is little doubt that neurons in the STN are tuned to several decision variables and show heterogeneous tuning profiles.

Weaknesses:

The primary weakness of the paper lies in the claim that STN contains multiple sub-populations with distinct involvements in decision making, which is inadequately supported by the paper's methods and analyses.

First, while it is clear that the ~150 recorded neurons across 2 monkeys (91, 59 respectively) display substantial heterogeneity in their activity profiles across time and across stimulus/reward conditions, the claim of sub-populations largely rests on clustering a *subset of less than half the population - 66 neurons (48, 15 respectively) - chosen manually by visual inspection*. The full population seems to contain far more decision-modulated neurons, whose response profiles seem to interpolate between clusters. Moreover, it is unclear if the 4 clusters hold for each of the 2 monkeys, and the choice of 4-5 clusters does not seem well supported by metrics such as silhouette score, etc, that peak at 3 (1 or 2 were not attempted). From the data, it is easier to draw the conclusion that the STN population contains neurons with heterogeneous response profiles that smoothly vary in their tuning to different decision variables, rather than distinct sub-populations.

Second, assuming the existence of sub-populations, it is unclear how their time- and condition-varying relationship with DDM parameters is to be interpreted. These relationships are inferred by splitting trials based on individual neurons' firing rates in different task epochs and reward contexts, and regressing onto the parameters of separate DDMs fit to those subsets of trials. The result is that different sub-populations show heterogeneous relationships to different DDM parameters over time - a result that, while interesting, leaves the computational involvement of these sub-populations/implementation of the decision process unclear.

Outlook:

This is a paper with a rich dataset of neural activity in the STN in a rich perceptual decision-making task, and convincing evidence of heterogeneity in choice, value and evidence tuning across the STN, suggesting the STN may be involved in several aspects of decision-making. However, the authors' specific claims about sub-populations in the STN, each having distinct relationships to decision processes, are not adequately supported by their analyses.

Reviewer #2 (Public review):

Summary:

This study, conducted by Esmaeili and colleagues, investigates the functional connectivity signatures of different auditory, visual, and motor states in 42 ECoG patients. Patients performed three tasks: picture naming, visual word reading, and auditory word repetition. They use an SVM classifier on correlation patterns across electrodes during these tasks, separating speech production from sensory perception, and incorporating baseline silence as another state. They find that it is possible to classify five states (auditory perception, picture viewing, word reading, speech production, and baseline) based on their connectivity patterns alone. Furthermore, they find a sparser set of "discriminative connections" for each state that can be used to predict each of these states. They then relate these connectivity matrices to high-gamma evoked data, and show largely overlapping relationships between the discriminative connections and the active high-gamma electrodes. However, there are still some connectivity nodes that are important in discriminating states, but that do not show high evoked activity, and vice versa. Overall, the study has a large number of patients, and the ability to decode cognitive state is compelling. The main weaknesses of the work are in placing the findings into a wider context for what additional information the connectivity analysis provides about brain processing of speech, since, as it stands, the analysis mostly reidentifies areas already known to be important for speaking, listening, naming, and visual processing.

Strengths:

(1) The authors were able to assess their connectivity analysis on a large cohort of patients with wide coverage across speech and language areas.

(2) The use of controlled tasks for picture naming, visual word reading, and auditory word repetition allows for parcellating specific components of stimulus perception and speech production.

(3) The authors chose not to restrict their connectivity analysis to previously identified high amplitude responses, which allowed them to find regions that are discriminative between different states in their speech tasks, but not necessarily highly active.

Weaknesses:

(1) Although the work identifies some clear connectivity between brain areas during speech perception and production, it is not clear whether this approach allows us to learn anything new about brain systems for speech. The areas that are identified have been shown in other studies and are largely unsurprising - the auditory cortex is involved in hearing words, picture naming involves frontal and visual cortical interactions, and overt movements include the speech motor cortex. The temporal pole is a new area that shows up, but (see below) it is important to show that this region is not affected by artifacts. Overall, it would help if the authors could expand upon the novelty of their approach.

(2) Because the connectivity is derived from single trials, it is possible that some of the sparse connectivity seen in noncanonical areas is due to a common artifact across channels. The authors do employ a common average reference, which should help to reduce common-mode noise across all channels, but not smaller subsets. Could the authors include more information to show that this is not the case in their dataset? For example, the temporal pole electrodes show strong functional connectivity, but these areas can tend to include more EMG artifact or ocular artifact. Showing single-trial traces for some of these example pairs of electrodes and their FC measures could help in interpreting how robust the findings are.

(3) The connectivity matrices are defined by taking the correlation between all pairs of electrodes across 500-ms epochs for each cognitive state, presumably for electrodes that are time-aligned. However, it is likely that different areas will interact with different time delays - for example, activity in one area may lead to activity in another. It might be helpful to include some time lags between different brain areas if the authors are interested in dynamics between areas that are not simultaneous.

(4) In Figure 3, the baseline is most commonly confused with other categories (most notably, speech production, 22% of the time). Is there any intuition for why this might be? Could some of this confusion be due to task-irrelevant speech occurring during the baseline / have the authors verified that all pre-stimulus time periods were indeed silent?

(5) How similar are discriminative connections across participants? Do they tend to reflect the same sparse anatomical connections? It is not clear how similar the results are across participants.

(6) The results in Figure 5F are interesting and show that frontal electrodes are often highly functionally connected, but have low evoked activity. What do the authors believe this might reflect? What are these low-evoked activity electrodes potentially doing? Some (even speculative) mention might be helpful.

(7) One comparison that seems to be missing, if the authors would like to claim the utility of functional connectivity over evoked measures, is to directly compare a classifier based on the high gamma activity patterns alone, rather than the pairwise connectivity. Does the FC metric outperform simply using evoked activity?

Reviewer #3 (Public review):

I read this manuscript with great interest. The purpose of this paper is to use human intracranial recordings in patients undergoing routine epilepsy surgery evaluation to investigate speech production and perception during five specific and controlled tasks (auditory perception, picture perception, reading perception, speech production, and baseline). Linear classifiers were used to decode specific states with a mean accuracy of 64.4%. The interpretation of these findings is that the classifiers reveal distinct network signatures "underlying auditory and visual perception as well as speech production." Perhaps the most interesting finding is that the network signatures, including both regions with robust local neuronal activity and those without. Further, this study addresses an important gap by examining functional connectivity during overt speech production.

The abbreviation ECoG is used throughout the manuscript, and the methods state that grids and strips were placed, though many epilepsy centers now employ intracerebral recordings. Does this manuscript only include patients with surface electrodes? Or are depth electrodes also included? The rendering maps show only the cortical surface, but depth recordings could be very interesting, given that this is a connectivity analysis.

Also interesting, given both the picture and reading task, is whether there is coverage of the occipitotemporal sulcus?

A major strength of the chosen paradigm is the combination of both perception (auditory or visual) and production (speech). Have the authors considered oculomotor EMG artifacts that can be associated with the change in visual stimuli during the task (see Abel et al. for an example PMID: 27075536, but see also PMID: 19234780 and PMID: 20696256).

I'm very interested in the findings in Figure 4D, with regard to the temporal pole. I would recommend that the authors unpack what it means that the ratio of electrodes with the strongest connections is highest, but active and discriminative is perhaps the lowest. We (I think many groups!) are interested in this region as a multimodal hub that provides feedback in various contexts (like auditory or visual perception).

Given the varieties of tasks and the fact that electrodes are always placed based on clinical necessity, are there concerns about electrode sampling bias?

This manuscript makes an important contribution by demonstrating that functional connectivity analysis reveals task-specific network signatures beyond what is captured by local neuronal activity measures (LFP). The finding that low-activity regions are engaged in task-specific classifications has important implications for future human LFP connectivity work.

DOI: 10.1038/s41598-022-16758-3

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DOI: 10.64898/2026.01.26.701495

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DOI: 10.1016/j.jbc.2026.111225

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DOI: 10.1038/s41467-025-65995-3

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Curator: @dhovakimyan1

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DOI: 10.1038/s41467-025-65995-3

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What is this?

all of the fast reactions run out easily, with the slow step being the reaction that exists at the end of the energy diagram.

Robin ends with a rhyming couplet. I think this is meant to bring emphasis to what he is saying. Possibly shows how he is playful with his tone just as he is known to be a mischievous character.

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Through this conflict, we can see Helena and Hermia become more well rounded characters. Their flaws emerge in interesting ways. New dimension is given to Helena's jealousy and remorse while we learn that Hermia has a chip on her shoulder about her height, which causes her to make the situation worse.

This monologue illuminates the relationship between Hermia and Helena. Throughout this scene, we come to learn of their once great friendship and this love affair has driven them apart.

Synthesis DNA synthesis has historically been implemented with large machines, using hoses, valves, and plastic containers known in the life sciences as well plates. Hoses and valves will not disappear; however, advances in the semiconductor industry have enabled silicon technology-based implementations that miniaturize the synthesis device and can achieve higher write throughput by synthesizing more sequences in parallel (thousands in well plates versus billions on chips). For example, chips akin to static RAM arrays have been used to synthesize sequences of DNA, one sequence per array position8 (Figure 6)

pos quote 3

I was wondering about what could happen to a watershed if one part of the hydrologic cycle is changed. According to Google, changes in the water cycle can affect the whole watershed, like causing floods, low water, or harming plants and animals.

April 3 letter - Indian victory and accelerating catastrophe: the Pinnace capture arms/ammunition, kill the captain, and muster 200 canoes with 1000 warriors. The English are outnumbered and outgunned. This escalation shows the colony is losing control and facing near-total annihilation.

points towards long-term effects of survivors

Las Casas shows how the Spaniards viewed the Indigenous people as worthless. This helped us understand why they were so extremely cruel and violent.

This shows that almost the entire population was wided out because of the Spanish's violence and abuse to the Native people.

Las Casas says that the Native people were peaceful. They also said that the Spaniards attacked them badly like they were wild animals.

I remember a few years back playing a video game. I forget which one, but at some point a character said something along the lines of "After everything, all you've got to show is some metal," in relation to the pursuit of gold. That's always stuck with me. Metal has value, yes, but it's not worth blood. People shouldn't die for it, and no man with an ounce of honor should kill for it. I think that Bartolomé would've thought much the same.

Although the religious focus feels strange to me, as someone who isn't religious, I also know that this is a clear sign of how deeply his compassion for these people ran. To see them as children of God in his age was radical and needed.

This man was a saint in many ways. He saw the writing on the wall, saw that the ink was blood, and did what he could to try and prevent the coming storm. It's a true shame that he didn't make more progress in that goal.

I've had the opportunity to see some of these sites, and it really is amazing how well they did. Keep in mind, the best pack animal they had was a lama. They had to carry most of this stuff themselves.

Important consideration if there is any validity to this claim

Organizing ideas clearly in writing helps show a writer's critical and analytical thinking. The order of ideas should match the purpose of the assignments, such as telling a story, describing a setting, or making an argument.

1. So is miosis a key symptom?
2. The samples were taken several weeks after death. Might this affect the samples, or does the substance not degrade?
3. Might any other demographic info (age, location, etc.) affect the samples?

Analyse Approfondie du Conflit : Stratégies, Bénéfices et Psychologie

Résumé Exécutif

Ce document synthétise une analyse approfondie de la nature des disputes, s'éloignant de la perception traditionnelle du conflit comme étant purement négatif.

La thèse centrale est que le conflit, loin d'être un obstacle au bien-être, est un phénomène naturel et un moteur essentiel de développement personnel, relationnel et sociétal.

Son caractère constructif ou destructeur dépend entièrement de la manière dont il est géré.

Les points clés révèlent que la maîtrise du conflit repose sur la régulation émotionnelle, l'application de techniques de communication spécifiques et une volonté de remettre en question ses propres certitudes.

Les bénéfices d'une dispute bien menée sont multiples : elle permet * d'affirmer ses valeurs, de poser des limites, * de renforcer les liens en créant un sentiment d'appartenance et de confiance, * et même de stimuler l'excellence en milieu professionnel.

La gestion efficace des émotions, notamment le stress et la colère, est fondamentale.

Des stratégies comme la reconnaissance de ses émotions, le recadrage de la montée d'adrénaline en énergie positive et des techniques d'ancrage physique sont des outils puissants.

L'analyse met également en lumière l'influence déterminante des expériences de l'enfance sur notre rapport adulte au conflit, soulignant que des schémas de communication peuvent être consciemment modifiés.

Enfin, des méthodes concrètes pour désamorcer les tensions et dialoguer, même avec des interlocuteurs aux opinions radicalement opposées, sont présentées, insistant sur l'importance de présumer la bonne foi et de rechercher des solutions communes.

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1. La Perception Évolutive du Conflit

La compréhension psychologique du conflit a radicalement changé.

Si elle a longtemps prôné l'évitement des disputes, considérées comme nuisibles au bien-être, la perspective moderne est tout autre.

• Vision Traditionnelle vs. Moderne :

◦ Anciennement : La psychologie défendait l'idée qu'il fallait "éviter les conflits autant que possible".

Le bonheur était assimilé à l'absence de conflit.   

◦ Aujourd'hui : Le conflit est considéré comme "tout à fait naturel".

Ce qui est déterminant n'est pas le conflit en soi, mais "la façon dont on se dispute".

• Le Conflit comme Moteur Social :

◦ Le sociologue Georg Simmel est cité pour affirmer que "le conflit est ce qui fait bouger une société".  

◦ L'harmonie et le consensus total mènent à la stagnation : "quand on vient en harmonie et qu'on est tous du même avis, il ne se passe rien, tout se met à l'arrêt".  

◦ Éviter systématiquement la confrontation ne résout pas les problèmes sous-jacents, qui continuent de "s'aggraver jusqu'à ce que plus rien ne puisse sauver le couple".

2. Les Multiples Bénéfices d'un Conflit Constructif

Lorsqu'il est abordé de manière saine, le conflit devient une source de force et de croissance à plusieurs niveaux.

• Développement Personnel :

◦ Affirmation de soi : Une dispute est une occasion "d'affirmer ses propres valeurs, poser ses limites et savoir qui on est".

Même sans solution, elle permet de "s'exprimer" et de "formuler son opinion à haute voix".  

◦ Connaissance de soi : La confrontation peut mener à une meilleure connaissance de soi-même et des autres.

Andj, musicien de punk hardcore, témoigne qu'une "confrontation violente avec ses parents" lui a permis de mieux se connaître et de les voir sous un autre jour, améliorant considérablement leurs relations.

• Renforcement des Relations :

◦ Création de liens : Le conflit peut paradoxalement créer un "sentiment d'appartenance" lorsqu'on réalise qu'on est finalement d'accord avec l'autre sur certains points.   

◦ Signe de confiance : Une première dispute avec une nouvelle connaissance peut "briser la glace".

Andj déclare : "je ne me dispute qu'avec les personnes qui comptent pour moi [...] si j'ai une confrontation avec quelqu'un, ça veut dire que je tiens à cette relation".  

◦ Évolution commune : Le plus grand bonheur réside dans le fait que l'autre "n'a pas pris la fuite" et a surmonté l'épreuve ensemble, ce qui "nous a fait évoluer ensemble".

• Efficacité Professionnelle :

◦ En management, des équipes "un peu trop harmonieuses" où la critique constructive est absente n'atteignent qu'un "résultat moyen".  

◦ Pour "atteindre l'excellence, on a besoin du conflit".

3. La Psychologie du Conflit : Maîtriser le "Tsunami Émotionnel"

La clé d'une dispute constructive réside dans la capacité à gérer le flux d'émotions intenses qu'elle génère.

• La Nature des Émotions en Conflit :

◦ La dispute est décrite comme un "grand tsunami émotionnel".  

◦ Les émotions proviennent de trois sources :      

1. L'objet direct de la dispute.     

2. Les "émotions coptées" : stress ou frustration accumulés durant la journée.    

3. Les émotions de la petite enfance.

• Stratégies de Régulation Émotionnelle :

◦ Reconnaissance et acceptation : La première étape est de reconnaître ses émotions ("oui je suis en colère et c'est légitime").

Le simple fait d'accepter et d'accueillir mentalement le stress "le réduit déjà de 30 %".  

◦ Recadrage cognitif : Il est possible de "requalifier ce sentiment" et de voir la montée d'adrénaline comme un "surcroix d'énergie" positif.

Cette technique, enseignée en négociation, peut réduire la tension de 40 % supplémentaires.  

◦ Ancrage physique : En cas de confusion mentale ou émotionnelle, il est important de "sentir le sol sous mes pieds" pour retrouver un ancrage.  

◦ La pause stratégique : Proposer de "quitter la pièce" lorsque la discussion tourne en rond est "très efficace".

En 3 minutes, "le stress disparaît, la colère s'estompe".  

◦ L'expression physique : Le cri, pratiqué par Andj, est présenté comme "une forme puissante d'expression de soi et un outil pour réguler ses émotions".

• Le Rôle Positif de la Colère :

◦ La colère n'est pas systématiquement négative. Hasnain Kazim, écrivain, déclare : "j'aime la colère, je trouve qu'elle a quelque chose d'extrêmement direct.

Elle dit clairement : ça me va, ça ça ne me convient pas".  

◦ Il la préfère à l'agressivité passive : "ce que je trouve horrible, c'est quand tu vois bien que tu as vexé une personne [...] et qu'elle ne dit rien".

4. Techniques Pratiques pour une Communication Efficace en Situation de Conflit

Des outils rhétoriques et des approches spécifiques peuvent transformer une querelle en un dialogue productif.

| Technique | Description | Exemple / Citation | | --- | --- | --- | | Éviter les Généralisations | Les mots comme "jamais" ou "toujours" enferment l'autre dans une position inconfortable et ferment le dialogue. Il faut "débarrasser le dialogue de ces mots". | "Il est toujours de mauvaise humeur." | | Utiliser le "Je" | Remplacer le "tu accusateur" par des formulations commençant par "je" pour désamorcer l'agressivité et prendre la responsabilité de sa propre perception. | Au lieu de "Tu ne m'as pas compris", dire "Je me suis mal exprimé". | | Formuler son Point de Vue | Argumenter en commençant par "de mon point de vue" pour éviter de présenter son opinion comme une vérité absolue et agressive. | "De mon point de vue, si je dis à l'autre c'est toi qui est stressé, ça ne va faire qu'attiser le débat." | | Poser des Questions Ouvertes | Utiliser des questions qui commencent par "pourquoi", "comment" ou "qu'est-ce que" pour encourager une réponse développée et maintenir la discussion ouverte. | "Qu'est-ce que tu veux dire exactement ?" | | Utiliser les Questions Fermées | Poser des questions auxquelles on ne peut répondre que par "oui", "non" ou "peut-être" pour "fixer quelque chose qui n'était pas clair". | "Ça, ça te dérange ? - Oui." | | Désamorcer les Attaques Déloyales | Identifier les techniques rhétoriques visant à déstabiliser (ex: ad hominem), puis les neutraliser en recentrant calmement le débat sur le sujet principal. | Attaque : "Ça ne vous dérange pas de passer à la télé avec la même veste qu'avanthière ?" Réponse : "Bon, à part la couleur de la veste \[...\] comment peut-on faire pour avancer sur notre sujet ?" |

5. Le Conflit Idéologique : Dialoguer avec l'Opposition

Le journaliste Hasnain Kazim partage son expérience sur la nécessité et la méthode pour engager le dialogue avec des personnes aux opinions radicalement différentes, notamment politiques.

• Principes Fondamentaux :

◦ Quitter sa zone de confort : Il faut être prêt à "remettre en question ses propres certitudes".  

◦ Éviter l'étiquetage : Ne pas immédiatement ranger l'autre dans un camp ("droitard", "réac", "gauchiste") pour ne pas le considérer comme un "ennemi" et couper l'échange.  

◦ Présomption de bonne foi : Partir du principe que "l'autre ne me tend pas de piège" et qu'il est "honnête et sincère".

Si ses propos semblent contradictoires, au lieu de le juger "stupide", il faut chercher à comprendre "ce qu'il y a derrière".  

◦ Courtoisie et absence de condescendance : Ne pas arriver en "donneur de leçon" ou en "maître d'école".

• Stratégies d'Engagement :

◦ L'importance d'initier le dialogue : Le plus important est "déjà de le faire, tout simplement".  

◦ Se fixer des limites : Il est crucial de savoir se protéger et de "riposter" si nécessaire.

On n'est pas obligé de "témoigner de l'empathie à tout le monde".  

◦ Les effets à retardement : Même si un débat semble échouer sur le moment, il peut avoir des "effets rétroactifs".

L'interlocuteur peut plus tard réfléchir au courage de la démarche, ce qui peut faire évoluer sa pensée.

6. L'Héritage de l'Enfance et son Impact sur le Conflit

Notre manière de gérer les disputes à l'âge adulte est profondément façonnée par les modèles et les expériences de notre enfance.

• L'Apprentissage par l'Exemple :

◦ La relation à la dispute est "héritière de ce que nous ont montré nos modèles d'identification" (parents, figures d'autorité).  

◦ Si un enfant apprend qu'il est aimé lorsqu'il est "passif", "discret" et "d'accord avec tout le monde", il évitera la confrontation à l'âge adulte.

• Exemple d'Andj :

◦ Il a grandi dans une famille où les disputes étaient gérées par des cris et parfois des "agressions physiques".   

◦ Ses parents "réprimaient leurs propres besoins", générant une "énorme frustration".   

◦ Enfant, il essayait de se "rendre invisible".   

◦ La musique punk lui a permis de réaliser qu'il n'était pas seul, en entendant d'autres "hurler cette injustice".   

◦ Le processus de guérison a nécessité plusieurs années de confrontations directes avec ses parents, où il a pu "verbaliser tout ce qui [l]'avait blessé", ce qui a finalement permis de rétablir une relation saine.

7. La Résolution : Clore la Dispute de Manière Constructive

Une bonne dispute doit avoir une bonne conclusion pour que ses effets soient bénéfiques.

• Rituels de Réconciliation : Des rituels comme "la bise de réconciliation" ou une poignée de main sont particulièrement efficaces, notamment avec les enfants, pour clore un conflit.

• Règles Familiales : Établir des règles claires, comme celle de ne pas "emporter la dispute au lit", aide à contenir le conflit et à préserver la relation.

• Savoir Ne Pas Disputer : Parfois, la dispute "n'en vaut pas la peine".

Lors de retrouvailles familiales, la préservation des liens peut être "plus importante que le sujet qui vient de surgir".

• Le Piège de l'Empathie pour les Spectateurs : Lors d'une dispute de groupe, les spectateurs doivent se méfier de l'empathie, qui peut les transformer en "partie prenante", leur faisant voir le débat d'un seul côté et transformant les autres en "adversaires".

Synthèse sur les Systèmes d'Émulation en Milieu Scolaire

Résumé Exécutif

Ce document synthétise les principes, les applications et les conditions d'efficacité des systèmes d'émulation (ou systèmes de renforcement) en contexte scolaire, basés sur l'expertise de Nancy Goudreau, docteure en psychopédagogie.

L'utilisation de ces systèmes vise à instaurer ou à renforcer des comportements spécifiques par le biais d'une motivation externe.

L'idée centrale est que ces outils doivent être employés de manière ciblée, judicieuse et temporaire. Ils sont principalement indiqués pour les élèves présentant des difficultés de comportement importantes et pour qui la motivation intrinsèque est faible.

Une erreur fréquente est de les appliquer à des élèves déjà motivés, ce qui risque de substituer une motivation externe à une motivation autonome.

Le succès d'un système d'émulation repose sur des conditions strictes : le choix d'un renforçateur perçu comme agréable par l'élève, l'application immédiate du renforçateur après le comportement (contiguïté), et un lien de cause à effet clair pour l'élève (contingence).

Il est crucial de planifier le retrait progressif du système dès sa mise en place, en parallèle d'un enseignement explicite des compétences visées.

Le système en lui-même n'enseigne rien ; il ne fait que motiver.

Il existe trois types de systèmes : indépendant (individuel), dépendant (la récompense du groupe dépend d'un individu) et interdépendant (défi collectif).

Le système interdépendant est le plus recommandé pour une classe ordinaire afin de relever un défi de groupe précis.

Finalement, il est essentiel de distinguer le système d'émulation, qui est un contrat "si... alors...", de la récompense spontanée, qui est bien plus efficace pour reconnaître la bonne conduite de la majorité des élèves et demande moins d'énergie à l'enseignant.

Définition et Objectifs du Système d'Émulation

Un système d'émulation, aussi appelé système de renforcement, est une intervention structurée mise en place pour encourager un comportement désiré. Son objectif est double :

1. Faire apparaître un comportement qui est actuellement absent chez un élève.

2. Augmenter la fréquence ou la pertinence d'un comportement déjà présent mais manifesté de façon insuffisante ou dans des contextes inappropriés.

Le mécanisme repose sur l'utilisation d'une motivation extrinsèque (externe) pour amener l'élève à adopter le comportement.

Un "renforçateur" est présenté à l'élève immédiatement après la manifestation du comportement attendu.

Il existe deux types de renforcement :

• Renforcement positif : L'ajout d'un stimulus agréable suite au comportement (ex: obtenir un autocollant, un privilège).

• Renforcement négatif : Le retrait d'un stimulus désagréable suite au comportement (ex: être exempté d'une corvée).

Il est important de noter que le terme "négatif" se réfère au retrait et non à une connotation péjorative.

Principes Fondamentaux et Conditions d'Efficacité

L'efficacité d'un système d'émulation n'est pas automatique.

Elle dépend du respect rigoureux de plusieurs principes fondamentaux et de l'évitement de certaines erreurs courantes.

Quand Utiliser un Système d'Émulation ?

Le recours à un système d'émulation devrait être réservé à des contextes précis :

• Lorsqu'un comportement attendu est totalement absent et qu'il faut initier son apparition.

• Avec des élèves présentant des difficultés de comportement importantes, pour qui la motivation à adopter les conduites attendues est très faible.

• Pour contrecarrer des renforçateurs sociaux qui maintiennent des comportements indésirables (ex: un élève qui fait rire la classe).

Le système vise alors à offrir une réponse positive plus forte, associée au comportement attendu.

Les Erreurs à Éviter

L'utilisation inadéquate des systèmes d'émulation peut être contre-productive. Les erreurs les plus fréquentes sont :

1. Utiliser le système avec des élèves déjà motivés : Appliquer un renforçateur externe à un élève qui agit déjà pour les "bonnes raisons" (motivation autonome) risque de déplacer sa motivation.

L'élève commencera à adopter le comportement non plus par plaisir ou par conviction, mais pour obtenir la récompense.

2. Appliquer un système à toute la classe de manière indifférenciée : Souvent, seuls un ou deux élèves ont réellement besoin d'un tel système.

L'appliquer à tous est une source de gestion lourde pour un bénéfice faible, et il est souvent inefficace pour les élèves qui en ont le plus besoin.

3. Omettre de planifier le retrait du système : Un système d'émulation est une mesure temporaire.

S'il n'y a pas de plan pour le retirer progressivement, l'enseignant et les élèves deviennent "pris dans le système", ce qui mène à un cycle où il faut constamment trouver de nouveaux systèmes pour maintenir la motivation.

Les Clés du Succès

Pour qu'un système soit efficace, plusieurs conditions doivent être réunies :

• Choix du Renforçateur : Le renforçateur doit être perçu comme agréable et motivant du point de vue de l'élève.

Un renforçateur choisi par l'adulte sans consultation peut même avoir un effet punitif (ex: un dîner avec l'enseignante pour un adolescent).

Il est donc primordial de consulter les élèves.

• Principe de Contiguïté : Le délai entre le comportement et l'obtention du renforçateur doit être le plus court possible, surtout avec les jeunes enfants.

Un renforçateur reçu le vendredi pour un comportement du mardi n'a aucun effet, car l'association ne se fait pas.

• Principe de Contingence : L'élève doit clairement et systématiquement associer le comportement spécifique avec la conséquence agréable.

• Enseignement Explicite de la Compétence : C'est un point crucial souvent négligé.

"Ça n'enseigne rien ce système-là".

Le système motive, mais il n'enseigne pas comment gérer sa colère, résoudre un conflit ou composer avec la défaite. Il doit impérativement être accompagné d'un enseignement explicite et d'un accompagnement dans le développement de la compétence visée.

• Planification du Retrait : L'objectif ultime est de développer la motivation autonome de l'élève.

L'adulte doit donc activement l'aider à prendre conscience des avantages et du plaisir associés au nouveau comportement pour que celui-ci se maintienne sans renforçateur externe.

La durée d'utilisation doit être "le plus court possible".

Typologie des Renforçateurs et des Systèmes

Les Types de Renforçateurs

• Renforçateurs Sociaux : Ce sont les renforçateurs les plus puissants pour maintenir durablement les comportements.

Ils incluent les rétroactions positives, les félicitations chaleureuses et sincères, les encouragements, etc.

Ils devraient être utilisés constamment, avec ou sans système formel.

Un système purement "comptable", sans chaleur humaine, est peu efficace.

• Renforçateurs Tangibles : Ils incluent les points, autocollants, privilèges, etc.

Ils sont utiles pour amorcer un changement, mais la transition vers les renforçateurs sociaux puis vers la motivation intrinsèque doit être planifiée.

L'apprentissage de la propreté est une analogie parfaite : on commence avec des renforçateurs tangibles (ex: un bonbon) car l'enfant n'a aucune motivation autonome, puis on transitionne rapidement vers des renforçateurs sociaux (bravos, fierté, appel aux grands-parents) jusqu'à ce que l'enfant devienne autonome.

Les Trois Groupes de Contingence

Il existe trois manières d'organiser un système d'émulation en fonction du groupe.

| Type de Système | Description | Usage Recommandé | Avantages et Inconvénients | | --- | --- | --- | --- | | Groupe Indépendant | Chaque élève travaille pour sa propre récompense ("chacun pour soi"). | Pour un ou deux élèves ayant des difficultés spécifiques, dans le cadre d'un plan d'intervention. | Avantage: Entièrement personnalisé.<br>Inconvénient: "Le moins bon choix" lorsqu'appliqué à toute une classe. Lourd à gérer, inefficace pour les élèves en difficulté et démobilisateur. | | Groupe Dépendant | La récompense de toute la classe dépend de la réussite d'un ou de quelques élèves. | Très efficace pour les élèves avec des troubles du comportement, pour mobiliser le soutien des pairs. | Avantage: Le soutien social des pairs devient un puissant levier d'aide.<br>Inconvénient: Nécessite une bonne préparation de la classe pour éviter de blâmer l'élève en cas d'échec. | | Groupe Interdépendant | La classe travaille collectivement à l'atteinte d'un objectif commun pour une récompense collective ("tous pour un, un pour tous"). | La meilleure approche pour une classe ordinaire afin de relever un défi de groupe ponctuel et précis. | Avantage: Facile à gérer, soutient un climat de coopération, inclut tous les élèves.<br>Inconvénient: Doit cibler un seul comportement précis pour être efficace. |

Conclusions et Recommandations Pratiques

Faut-il les Utiliser au Primaire ?

La réponse est nuancée : uniquement si c'est vraiment nécessaire. La plupart des classes fonctionnent bien sans système d'émulation formel.

• Pour un élève avec des besoins importants, un système indépendant sur mesure et intégré à son plan d'intervention est justifié et peut être efficace.

• Pour un défi de groupe ponctuel (ex: un relâchement dans le calme des déplacements), un système interdépendant peut être une solution efficace et temporaire.

Il doit cibler un seul comportement, et non devenir un "melting pot" de toutes les règles de la classe.

• L'utilisation d'un système indépendant pour tous les élèves d'une classe représente "énormément de temps et d'énergie pour peu de résultats".

La Distinction Cruciale : Système d'Émulation vs. Récompense

Il est fondamental de différencier ces deux concepts :

• Système d'Émulation : Un contrat préétabli. L'élève sait à l'avance que s'il produit le comportement X, il obtiendra la récompense Y. (Ex: "Si vous travaillez bien, je vous donnerai 15 minutes de plus dehors.")

• Récompense : Une reconnaissance spontanée et non annoncée d'un bon comportement. (Ex: "Vous avez tellement fait une belle journée que j'ai envie de vous récompenser, on va aller profiter du soleil 15 minutes.")

Pour la grande majorité des élèves, qui ont déjà une motivation autonome, la récompense spontanée est beaucoup plus efficace pour reconnaître leur bonne conduite, tout en étant infiniment moins énergivore pour l'enseignant que la gestion d'un système formel.

Ces élèves ont avant tout besoin "d'encouragement, de félicitations, de tapes dans le dos".

Document d'Information : Les Fonctions Exécutives chez l'Enfant

Résumé Exécutif

Ce document synthétise les perspectives de Julie Beaulieu, docteure en psychopédagogie, sur les fonctions exécutives chez l'enfant.

Considérées comme le « chef d'orchestre » ou la « tour de contrôle » du cerveau, ces habiletés cognitives de haut niveau, situées dans le lobe frontal, sont fondamentales pour la régulation des pensées, des émotions et des comportements.

Elles permettent à l'individu de s'adapter à son environnement et d'atteindre des objectifs.

Leur développement s'étend sur une longue période, débutant dès les premiers mois de la vie pour atteindre leur plein potentiel vers l'âge de 25 ans, avec des phases de progression accélérée durant la période préscolaire (3-7 ans) et au début de l'adolescence.

Si la maturation cérébrale est un facteur essentiel, l'environnement et la diversité des expériences vécues par l'enfant jouent un rôle crucial pour « aiguiser » ces fonctions.

Quatre composantes principales sont identifiées : la mémoire de travail, l'inhibition, la flexibilité cognitive et la planification.

Ces fonctions, bien que distinctes, sont interdépendantes et fonctionnent en synergie, à l'image d'une « toile d'araignée ».

Elles sont la fondation de nombreuses aptitudes et ont un impact direct sur la réussite éducative et le développement global de l'enfant (social, langagier, moteur).

Le soutien parental est déterminant et s'intègre dans les activités quotidiennes.

Les stratégies efficaces incluent le jeu, les interactions sociales, le questionnement (notamment le « pourquoi »), l'offre de choix, la stimulation de l'autonomie et de la créativité, ainsi que la mise en place d'un environnement sécurisant et positif.

L'objectif n'est pas d'entraîner ces fonctions comme un muscle, mais de les mobiliser à travers des expériences ludiques et variées.

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1. Définition et Nature des Fonctions Exécutives

Les fonctions exécutives sont définies comme un ensemble de processus cognitifs de haut niveau localisés dans le lobe frontal du cerveau.

Elles sont essentielles pour la réalisation de tâches complexes et pour l'adaptation de l'individu à son environnement.

Leur rôle principal est de réguler trois aspects fondamentaux du comportement humain :

• Les pensées : Organiser ses idées, raisonner, réfléchir.

• Les comportements : Contrôler ses actions, initier des tâches, s'ajuster.

• Les émotions : Gérer ses réactions émotionnelles.

Ces fonctions sont mobilisées en continu dans la vie quotidienne, dès qu'une tâche n'est pas automatique ou routinière et demande de réfléchir, raisonner, anticiper, planifier ou diriger son attention.

La Métaphore du Chef d'Orchestre

Pour illustrer leur rôle, Julie Beaulieu utilise deux analogies principales :

• La tour de contrôle : Elles permettent de se contrôler et de diriger ses actions.

• Le chef d'orchestre : C'est la métaphore la plus développée.

Les fonctions exécutives agissent comme le chef d'orchestre du cerveau, coordonnant l'ensemble des autres habiletés cognitives (les "instruments") pour produire un comportement harmonieux et adapté à un objectif précis.

Elles dirigent les pensées, les émotions et les comportements pour permettre à l'individu de s'adapter et de répondre efficacement aux exigences de son environnement.

2. Le Développement des Fonctions Exécutives

Le développement des fonctions exécutives est un processus long et progressif, influencé par la maturation biologique et les expériences environnementales.

Chronologie du Développement

• Début : Les composantes des fonctions exécutives commencent à se développer dès les premiers mois de la vie.

• Maturité : Elles atteignent leur plein potentiel au début de l'âge adulte, vers 25 ans.

• Périodes Clés : Deux périodes sont identifiées comme particulièrement propices à une progression importante :

1. L'âge préscolaire (3 à 6-7 ans).    2. Le début de l'adolescence.

Il est crucial de noter que le rythme de développement varie d'un enfant à l'autre, en fonction de facteurs individuels comme la maturation de leur propre cerveau.

Le Rôle Crucial de l'Environnement

La maturation du cerveau est une composante essentielle, mais l'environnement dans lequel l'enfant évolue est un moteur fondamental du développement.

• L'expérience : C'est principalement à travers les expériences vécues que les enfants mobilisent et développent leurs fonctions exécutives.

• L'aiguisage : Plus les fonctions sont mobilisées, plus elles s'« aiguisent », devenant « sophistiquées et spécialistes ».

• La variété : Proposer des contextes et des expériences variés permet de mobiliser un plus large éventail de fonctions exécutives et de favoriser un développement plus complet.

Le soutien offert par l'entourage (parents, éducateurs) est donc primordial.

3. Contextes Favorables au Développement

Certains contextes et situations sont particulièrement efficaces pour mobiliser et renforcer les fonctions exécutives, car ils empêchent l'enfant de recourir à des automatismes.

• Situations nouvelles : Toute situation où l'enfant n'a pas de routine établie l'oblige à s'adapter et donc à mobiliser ses fonctions exécutives.

• Tâches complexes : Les activités qui demandent plusieurs étapes, actions ou une réflexion soutenue.

• Situations inattendues : Les imprévus qui forcent une réévaluation et une adaptation.

• Résolution de problèmes : Chercher des solutions à un conflit ou à une difficulté pratique.

• Le jeu : Un contexte extrêmement favorable, en particulier :

◦ Le jeu symbolique (« faire semblant ») : Se mettre dans la peau d'un personnage.  

◦ Les jeux de société : Qui demandent de la stratégie, de la mémoire et de l'anticipation.

• Interactions sociales : Les discussions, les échanges et les conversations demandent une réflexion constante, une anticipation des réponses et une adaptation à l'interlocuteur.

• Découvertes et nature : Explorer de nouveaux environnements.

• Projets à long terme : Les projets qui s'étalent sur plusieurs jours ou semaines et nécessitent de la planification.

• Environnement stimulant et sécurisant : Un climat familial positif, où l'enfant se sent en sécurité, est plus propice à la mobilisation des fonctions exécutives.

Un stress élevé ou des émotions négatives intenses peuvent entraver leur fonctionnement.

4. Les Quatre Composantes Principales des Fonctions Exécutives

L'exposé se concentre sur quatre composantes fondamentales, qui sont interdépendantes et fonctionnent comme une « toile d'araignée ».

| Composante | Description | Exemple Clé | | --- | --- | --- | | Mémoire de travail | Capacité à retenir temporairement et à manipuler l'information pour l'utiliser dans une tâche. Elle fait le pont entre la mémoire sensorielle et la mémoire à long terme, et filtre les informations pertinentes. C'est l'aspect "actif" ou "dynamique" de la mémoire. | Le calcul mental (ex: 52 + 48). Il faut retenir les chiffres et activement les additionner pour trouver le résultat. | | Inhibition | Capacité à résister aux impulsions, aux distractions et aux habitudes pour adopter un comportement plus approprié. C'est le « frein » du cerveau qui permet de prendre un temps de recul avant d'agir et de diriger son attention. | Un jeune enfant à l'épicerie qui s'empêche de faire un commentaire à voix haute sur l'apparence physique d'une personne. | | Flexibilité cognitive | Capacité à se désengager d'une tâche ou d'une perspective pour s'adapter à une nouvelle situation, un nouveau point de vue ou de nouvelles règles. Elle permet de changer de stratégie quand la première ne fonctionne pas. | Un enfant qui accepte d'arrêter son jeu vidéo pour venir souper en famille, se désengageant cognitivement de la première activité pour se réengager dans la seconde. | | Planification | Capacité à anticiper des événements futurs, à se fixer un but et à organiser une séquence d'actions pour l'atteindre. Son développement est plus tardif, car il dépend de l'acquisition de la notion du temps. | Prévoir le trajet pour aller au parc, ou suivre les étapes d'une recette de cuisine. |

5. L'Importance Fondamentale des Fonctions Exécutives

Les fonctions exécutives sont décrites comme des compétences de base, constituant la fondation de multiples aptitudes et habiletés. Leur importance est capitale car :

• Elles soutiennent la réussite éducative à tous les niveaux (primaire, secondaire, et même post-secondaire).

• Elles ont un impact sur l'ensemble des sphères de développement de l'enfant : langagier, social, cognitif et même moteur.

• Elles sont essentielles pour fonctionner efficacement dans la vie de tous les jours et pour le bien-être futur de l'individu.

6. Stratégies de Soutien Parental pour le Développement

Les parents peuvent jouer un rôle actif dans le développement des fonctions exécutives de leur enfant à travers des actions intégrées au quotidien, sans nécessiter de matériel sophistiqué.

Approches Générales

• Développer le langage intérieur : Verbaliser à voix haute ses propres pensées pour modéliser, puis encourager l'enfant à se parler dans sa tête pour retenir des consignes ou se réguler.

• Soutenir les habiletés sociales : Favoriser les interactions sociales positives et variées.

• Offrir un soutien émotionnel : Accueillir les émotions de l'enfant avec empathie pour créer un climat de sécurité.

• Pratiquer des activités sportives et artistiques : Ces activités mobilisent l'ensemble des fonctions exécutives.

• Utiliser l'étayage et le questionnement : Accompagner l'enfant et le questionner sur ce qu'il pense, et surtout pourquoi il le pense, pour l'amener à verbaliser son raisonnement.

• Offrir des choix : Faire un choix implique de prioriser et de renoncer, ce qui mobilise la réflexion.

• Favoriser l'autonomie : Encourager l'enfant à faire les choses par lui-même.

• Tenir compte de ses intérêts : Un contexte agréable et motivant est plus propice à la mobilisation cognitive.

• Proposer des défis : Offrir des défis légèrement supérieurs à ses capacités actuelles, tout en l'accompagnant.

Stratégies Ciblées par Composante

Pour la Mémoire de Travail

• Stratégies de mémorisation : Utiliser des images mentales, la répétition (avec le langage intérieur), le regroupement d'informations (ex: retenir trois légumes), des associations ou des moyens mnémotechniques (chansons, rythmes).

• Repères visuels : Utiliser des listes, des pictogrammes pour les routines afin de se souvenir des étapes.

• Résumer et reformuler : Demander à l'enfant de redire avec ses propres mots ce qu'il a entendu ou lu.

• Réduire la charge cognitive : Éviter de surcharger l'enfant d'informations, surtout dans les moments de transition (ex: le matin avant de partir à l'école).

Pour l'Inhibition

• Prendre un temps de recul : Apprendre à l'enfant à compter jusqu'à trois avant de réagir.

• Communiquer les attentes : Avoir des attentes réalistes et les expliquer clairement à l'enfant.

• Gestion des émotions : Mettre en place des stratégies pour gérer la colère ou la tristesse (respiration, visualisation, relaxation).

• Jeux d'adresse et d'équilibre : Ces jeux demandent de contrôler ses gestes et d'éviter les mouvements impulsifs.

• Jeux de vitesse et de réflexes : Jouer à des jeux où il faut réagir rapidement mais au bon moment (ex: le jeu Dobble).

Pour la Flexibilité Cognitive

• Laisser prendre des décisions : Permettre à l'enfant de prendre des décisions par lui-même.

• Déroger aux routines : Modifier occasionnellement une routine pour l'amener à s'adapter.

• Préparer les transitions : Aviser l'enfant à l'avance d'un changement d'activité pour lui permettre de s'y préparer cognitivement.

• Stimuler la créativité : Encourager les activités créatives, les jeux de rôle et l'improvisation.

• Changer la fin des histoires : Avant de lire la fin d'un livre, demander à l'enfant d'inventer sa propre conclusion.

Pour la Planification

• Utiliser des repères de temps visuels : Calendriers, horaires de la journée ou de la fin de semaine.

• Amener à anticiper : Poser des questions comme : «

• Qu'est-ce que tu penses qu'il va se passer après ? »,
• « De quoi auras-tu besoin pour cette activité ? ».

• Créer des plans : Avant une construction en blocs LEGO, suggérer de dessiner un petit plan.

• Remettre en séquence : Après avoir lu une histoire ou vu un film, demander à l'enfant de raconter ce qui s'est passé au début, au milieu et à la fin.

Synthèse sur la Gestion de la Colère et de la Frustration chez l'Enfant

Résumé Exécutif

Ce document de synthèse présente les stratégies et les concepts clés pour aider les enfants à gérer leur colère et leur frustration, basés sur l'expertise de Madame Ly Massy, docteure en psychologie de l'éducation.

L'approche fondamentale est de considérer la colère non pas comme une émotion négative à supprimer, mais comme une émotion normale, un signal d'alarme indiquant une injustice ou un préjudice.

Elle devient problématique uniquement lorsqu'elle est mal exprimée, trop intense ou injustifiée.

La gestion de ces émotions repose sur le développement de la régulation émotionnelle, une compétence qui s'articule autour de trois habiletés fondamentales :

1. L'identification des émotions et de leurs sources.

2. La modulation de l'intensité émotionnelle pour prévenir l'escalade et retrouver le calme.

3. L'expression adéquate des émotions pour résoudre les situations conflictuelles.

Le rôle des parents est central et s'articule autour de la prévention et de l'enseignement de stratégies concrètes.

La prévention consiste à instaurer un environnement sécurisant par le biais de routines prévisibles et de saines habitudes de vie, notamment une activité physique suffisante et un sommeil adéquat.

Pour l'enseignement, il est crucial d'aider l'enfant à développer un vocabulaire émotionnel, à reconnaître ses propres signaux (physiques, cognitifs, comportementaux) et à maîtriser un éventail de stratégies d'apaisement (techniques physiques, diversion de l'attention).

Le modelage parental — la manière dont les parents gèrent et expriment leurs propres émotions — est l'outil le plus puissant pour guider l'enfant.

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1. Comprendre la Colère : Une Émotion Normale

Selon Madame Ly Massy, la perception de la colère comme une émotion purement négative est une erreur. Elle doit être comprise comme un mécanisme de signalisation fondamental.

• Une Fonction d'Alarme : La colère est décrite comme "un petit bouton d'alarme" qui signale qu'une situation est perçue comme injuste, moqueuse, ou qu'elle nuit au développement personnel.

• Quand la Colère Devient Problématique : L'enjeu n'est pas de supprimer la colère, mais de gérer son expression. Elle devient problématique dans trois cas de figure :

1. Expression Inadéquate : L'enfant "explose au lieu de dire tranquillement qu'est-ce qui nous fait vivre l'émotion négative".   

2. Intensité Excessive : L'émotion est trop intense et l'enfant ne parvient pas à la contrôler.  

3. Justification Inappropriée : La colère est déclenchée par une mauvaise interprétation de la situation (par exemple, percevoir un accident comme un acte intentionnel).

2. La Régulation Émotionnelle : Un Apprentissage en Trois Temps

La régulation émotionnelle est une habileté qui se développe tout au long de la vie, mais dont les bases devraient être acquises au début du primaire. Elle se compose de trois compétences interdépendantes.

| Habileté | Description | | --- | --- | | 1\. Identification des Émotions | Comprendre l'émotion ressentie et ses sources. C'est le prérequis à toute gestion. | | 2\. Modulation des Émotions | Être capable de gérer l'intensité de l'émotion pour éviter une escalade ou pour s'apaiser après une crise et retrouver son calme. | | 3\. Expression des Émotions | Communiquer de manière adéquate ce que l'on ressent et ce qui a causé l'émotion, dans le but de résoudre la situation. |

3. Facteurs de Difficulté dans la Régulation Émotionnelle

Plusieurs caractéristiques individuelles peuvent expliquer pourquoi certains enfants ont plus de difficultés à gérer leurs émotions.

• Hypersensibilité ou Hyperréactivité : Une réaction plus intense aux émotions, aux situations et à l'environnement. Le "moindre petit élément va susciter une réaction négative".

• Seuil de Frustration Bas : L'image d'une "mèche courte" est utilisée. Il en faut très peu pour que l'enfant se sente frustré ou en colère.

• Faible Tolérance au Délai de Gratification : Une difficulté à attendre. Le besoin doit être satisfait immédiatement, sinon une réaction négative s'ensuit.

• Rigidité Mentale : Un besoin que les choses soient faites d'une manière précise ou selon leurs goûts.

Un changement dans la routine peut susciter des émotions négatives.

C'est un trait commun chez les enfants avec un trouble du spectre de l'autisme.

• Perceptions Faussées : Une tendance à interpréter les situations neutres comme hostiles.

L'enfant est en état de vigilance constant, "comme s'il était toujours en vigilance d'avoir peur d'être attaqué".

Cela peut mener à généraliser ou dramatiser les événements.

• Trauma : Un traumatisme peut accentuer tous les facteurs précédents et mener à un "surétiquetage" des émotions négatives comme de la colère, l'enfant cherchant inconsciemment à se sentir moins victime et plus combatif.

4. Stratégies Parentales : Prévention et Anticipation

La première étape pour un parent est de mettre en place des conditions pour "prévenir les pertes de contrôle" plutôt que de simplement réagir aux crises.

4.1. Un Environnement Sécurisant

• Instauration de Routines : Mettre en place des routines prévisibles, surtout pour les moments de la journée identifiés comme difficiles (le matin avant l'école, la période des devoirs, le coucher, la fin de l'effet de la médication).

La prévisibilité rend la gestion des frustrations plus facile pour l'enfant.

4.2. Saines Habitudes de Vie

• Activité Physique : Essentielle pour évacuer les tensions accumulées.

Un enfant qui ne bouge pas assez (par exemple, en s'installant directement pour les devoirs après l'école) aura plus de mal à gérer un événement frustrant.

• Sommeil : Le manque de sommeil est un des "premiers facteurs qui va nuire à la régulation émotionnelle". Les besoins varient selon l'âge :

◦ Début du primaire : Entre 11 et 13 heures.    ◦ Début du secondaire : Environ 9 heures.

4.3. Identification des Déclencheurs de Crises

Il est crucial de distinguer deux types de facteurs :

• Facteurs Précipitants (Déclencheurs) : Ce qui initie la crise. Exemples : l'envahissement de l'espace personnel, une blessure d'estime de soi, l'accumulation de stress, la faim.

En identifiant la source, on peut agir en amont (par exemple, prévoir une collation dans la voiture au retour de l'école).

• Facteurs Aggravants : Ce qui intensifie la crise. Exemples : la fatigue de fin de journée, la fin de l'effet d'une médication pour un TDAH.

5. Développer les Compétences de Régulation Émotionnelle

Le parent doit activement enseigner les trois habiletés fondamentales de la régulation, en choisissant un moment où l'enfant est calme.

5.1. Habileté 1 : Identifier les Émotions

• Enrichir le Vocabulaire : Aider l'enfant à nommer ses émotions avec précision (irrité, frustré, furieux) et à décrire ses sensations physiques ("vidé", "submergé").

• Reconnaître les Signaux : L'aider à identifier les signaux précurseurs de la colère :

◦ Signaux Corporels : Externes (tension, rougeur, froncement des sourcils) et internes (cœur qui bat vite, souffle court).   

◦ Comportements : Tendance à frapper, à se replier sur soi.  

◦ Pensées : Identifier les pensées qui nourrissent la colère ("il l'a fait exprès").

• Outils et Approches :

◦ Refléter : "Tu as l'air déçu, est-ce qu'il s'est passé quelque chose ?".  

◦ Utiliser des supports ludiques : Livres, histoires, jeux de mimes, affiches, collages, création d'un "dictionnaire des émotions".

5.2. Habileté 2 : Moduler les Émotions

• Évaluer l'Intensité : Utiliser une échelle simple comme un thermomètre des émotions (vert, jaune, orange, rouge) pour aider l'enfant à prendre conscience de son état et à choisir la bonne stratégie.

• Enseigner Deux Grandes Catégories de Stratégies :

1. Stratégies Physiques : Très efficaces pour réduire la tension physique lors d'émotions intenses.    

▪ Respiration profonde : "La plus simple et la plus efficace".     

▪ Relaxation : Relaxation musculaire, méditation de pleine conscience.    

▪ Stimulation Sensorielle : Objets lourds (couverture, toutou), se bercer, se retirer dans un endroit calme et peu stimulant (tente, garde-robe), manipuler des objets (balles de tension, "putty").  

2. Stratégies de Diversion de l'Attention : Idéales pour interrompre les pensées négatives en boucle qui nourrissent la colère.     

▪ Activités exigeant de la concentration : Compter à l'envers (de 20 à 1, ou de 200 à 0 par bonds de 4), dessiner des mandalas, jouer aux LEGO, faire une activité artistique.    

▪ Objets Visuels : Regarder des objets calmants (spirales liquides, lumières douces).

• Stratégie Cognitive : Les "Pensées Froides"

◦ Aider l'enfant à remplacer les "pensées chaudes" qui attisent la colère par des "pensées froides" qui apaisent.

Exemples : "Il ne l'a pas fait exprès", "Ça va me couler sur le dos comme sur un canard".

5.3. Habileté 3 : Exprimer les Émotions

• Le Bon Moment et le Bon Endroit : Cette étape ne peut se faire que lorsque l'enfant s'est calmé, dans un lieu propice à la discussion.

• Le "Message au Je" : Enseigner à l'enfant à structurer son expression :

1. Je me sens... (nommer l'émotion).   

2. Parce que... (expliquer la cause).  

3. J'aimerais que... (proposer une solution pour que cela ne se répète pas).

• Le Modelage Parental : "Ici encore plus, le modelage est important".

Les parents doivent eux-mêmes utiliser le "message au je" et parler de leurs propres émotions. C'est en voyant ses parents le faire que l'enfant apprendra le mieux.

6. Messages Clés et Conclusion

Madame Ly Massy conclut avec plusieurs messages fondamentaux pour les parents et les éducateurs :

• La Normalité de la Colère : Il faut cesser de diaboliser cette émotion.

• La Primauté de l'Identification : "Si on n'a pas identifié comment on se sent, on ne sera pas capable de prendre les bons moyens pour se contrôler".

• La Diversité des Stratégies : Il faut enseigner un large éventail de stratégies, car aucune n'est universellement efficace.

• Les Exutoires Sains : Proposer des moyens sains de se défouler quand l'expression verbale directe n'est pas possible (écriture, art, sport intense).

• Le Rôle du Parent : Être un modèle de calme, éviter de "mettre de l'huile sur le feu" et savoir prendre soi-même une grande respiration pour garder son calme face à l'enfant.

Soutenir la Participation Parentale à l'École : Synthèse et Stratégies Clés

Résumé Exécutif

Ce document de synthèse analyse les stratégies et les concepts fondamentaux pour favoriser une participation parentale efficace et constructive dans le milieu scolaire, en se basant sur l'expertise d'Elodie Marion, docteure en administration publique et professeure à l'Université de Montréal.

L'implication parentale est définie comme un ensemble de pratiques à la maison, à l'école et dans la communauté, qui soutiennent le développement de l'enfant.

Son efficacité dépend moins des attentes de l'école envers les parents que des pratiques mises en place par l'école elle-même pour la soutenir.

Trois facteurs principaux influencent l'implication des parents : leur contexte de vie, leur perception d'être invités à participer et leur sentiment de compétence.

Pour surmonter les obstacles et catalyser l'engagement, une approche proactive fondée sur les "Cinq R" est proposée :

• Reconnaissance,
• Respect,
• Rôle,
• Résultats et
• Relation.

Cette approche transforme la dynamique de simple diffusion d'information en une véritable collaboration.

Enfin, la mise en place d'un plan de communication stratégique par les enseignants est essentielle.

Ce plan doit être structuré autour de quatre axes : la fréquence, la bidirectionnalité, les moyens adaptés et la diversité des thèmes abordés.

L'objectif ultime est d'instaurer une coéducation, une responsabilité partagée qui non seulement bénéficie à l'élève, mais brise également l'isolement de l'enseignant et augmente l'efficacité collective.

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1. Définition et Modalités de l'Implication Parentale

L'implication parentale englobe toutes les pratiques que les parents mettent en œuvre en lien avec l'éducation de leur enfant.

La recherche la catégorise généralement en trois sphères distinctes, chacune avec des actions concrètes.

1.1. Implication à la Maison

• Rôle Parental : Création d'un environnement familial propice à l'apprentissage et au développement.

Cela inclut la gestion des habitudes de vie (sommeil, alimentation), du stress et le soutien général au bien-être de l'enfant.

• Soutien Scolaire : Actions directement liées à la scolarité de l'enfant, telles que les communications sur l'école, les encouragements, et la transmission d'attentes claires concernant la réussite scolaire.

1.2. Implication à l'École

• Communications : Échanges formels et informels avec le personnel de l'école.

◦ Communications en personne : Rencontres parents-enseignants, réunions avec la direction.   

◦ Communications écrites : Messages quotidiens, signatures sur les évaluations (noté comme étant souvent une diffusion d'information plutôt qu'une communication bilatérale).

• Participation à la Prise de Décision : Engagement actif dans les instances de gouvernance de l'école, comme les comités d'école, les comités au centre de services scolaires ou la participation aux rencontres pour l'élaboration de plans d'intervention.

• Volontariat : Implication bénévole dans les activités de l'école.

1.3. Implication dans la Communauté

Bien que mentionnée comme une troisième catégorie par les chercheurs, cette dimension n'est pas détaillée dans la source.

2. Facteurs d'Influence sur l'Implication Parentale

L'engagement des parents n'est pas inné ; il est influencé par un ensemble de facteurs personnels et contextuels. L'école doit les comprendre pour adapter ses propres pratiques.

• Le Contexte de Vie des Familles : Les conditions de vie des parents (statut d'emploi, stress, monoparentalité, statut socio-économique) déterminent leur capacité à s'impliquer.

Par exemple, un parent d'un enfant autiste peut trouver le soutien scolaire à la maison extrêmement difficile, non par manque de volonté, mais en raison du contexte familial.

• La Perception d'Être Invité : L'implication dépend de la manière dont le parent perçoit et reçoit l'invitation de l'école à participer.

Une invitation envoyée n'est pas nécessairement une invitation ressentie comme telle.

• Le Sentiment de Compétence Parentale : Les parents, particulièrement ceux d'enfants en difficulté, peuvent se sentir démunis ou incompétents pour aider leur enfant.

Ce manque de confiance peut être interprété à tort comme un désengagement.

De plus, un sentiment de ne pas être à la hauteur des attentes de l'école peut paralyser leur implication.

• La Reconnaissance de l'Expertise Parentale : Les parents possèdent une connaissance fine et continue de leur enfant. Ils sont "le filon du parcours de son enfant".

Ils souhaitent que cette expertise, acquise au quotidien et souvent documentée, soit reconnue et valorisée par l'école, plutôt que de se sentir dans une relation hiérarchique face à "l'expert" scolaire.

3. Une Approche Stratégique : Le Cadre des "Cinq R" pour Favoriser l'Engagement

Pour passer d'une posture d'attente à une posture de soutien actif, Elodie Marion propose un cadre mnémonique basé sur "cinq R".

Cette approche vise à regarder ses propres pratiques ("se regarder dans le miroir") plutôt que de juger celles des parents ("regarder par la fenêtre").

| Le "R" | Définition | Actions Concrètes | | --- | --- | --- | | Reconnaissance | Valider et reconnaître les efforts et contributions des parents, passés et présents. | \- Mentionner les progrès accomplis les années précédentes.<br>\- Souligner les efforts actuels, même s'ils sont modestes.<br>\- Éviter de se concentrer uniquement sur les nouveaux défis sans reconnaître le travail déjà fait. | | Respect | Tenir compte de l'opinion, de l'expertise, de la culture et du contexte de vie des parents. | \- Pratiquer l'écoute active lors des rencontres.<br>\- Arriver en mode discussion plutôt qu'avec un ordre du jour rigide.<br>\- Adapter les attentes de l'école à la réalité des familles (ex: trouver des alternatives au soutien scolaire à la maison si nécessaire). | | Rôle | Clarifier et définir explicitement le rôle attendu du parent pour éviter les malentendus. | \- Expliciter ce que l'école attend (ex: encourager, questionner) et ce qu'elle n'attend pas (ex: ré-enseigner la matière).<br>\- Co-construire un rôle clair et accepté par le parent.<br>\- Donner des pistes concrètes sur comment le parent peut questionner son enfant sur les apprentissages. | | Résultats | Mettre en évidence les progrès et les objectifs pour que l'engagement soit perçu comme utile. | \- Définir des objectifs clairs pour chaque rencontre.<br>\- Communiquer fréquemment les améliorations observées chez l'enfant suite à l'implication du parent.<br>\- Célébrer les succès pour motiver la poursuite des efforts, au lieu d'attendre les bilans officiels. | | Relation | Bâtir une véritable relation de confiance et un sentiment d'appartenance. | \- Organiser des moments de rencontre informels (ex: fête de la rentrée).<br>\- Concevoir les rencontres pour permettre un réel échange et pas seulement une transmission d'information.<br>\- Intégrer un temps pour la "présentation des parents" lors des réunions de début d'année. |

4. Mettre en Place un Plan de Communication Efficace à l'École

Un plan de communication réfléchi est un outil puissant pour structurer et améliorer les interactions avec les parents tout au long de l'année.

Il doit s'articuler autour de quatre axes.

4.1. Fréquence

• Planification : Établir dès le début de l'année un rythme de communication réaliste pour l'enseignant et pertinent pour les parents.

• Routine : Créer des habitudes de communication (ex: un courriel hebdomadaire) pour éviter les contacts sporadiques ou uniquement déclenchés par des problèmes.

4.2. Bidirectionnalité

• Passer de la diffusion à l'échange : Concevoir les communications pour solliciter l'avis et les informations des parents.

• Poser des questions ouvertes : Utiliser des questions commençant par "comment" ou "pourquoi" pour inviter à des réponses développées, plutôt que des questions fermées (oui/non).

• Expliciter les besoins : Indiquer clairement aux parents les types d'informations que l'enseignant souhaite recevoir (ex: un changement à la maison, une inquiétude de l'enfant).

4.3. Moyens de Communication

• Adaptation : Choisir des moyens de communication adaptés au contexte des parents (ex: langue, niveau de littératie).

• Simplification : Alléger les communications écrites pour en faciliter la compréhension. Éviter les lettres de plusieurs pages.

• Le Piège Technologique : La multiplication des plateformes de communication (portails, applications) augmente souvent la quantité d'informations diffusées sans pour autant améliorer la relation.

Il est recommandé de réduire le nombre de canaux pour se concentrer sur la qualité des échanges.

4.4. Diversité des Thèmes

• Prévoir à l'avance : Planifier la diversité des sujets à aborder durant l'année pour éviter de ne communiquer que sur les difficultés.

• Inciter à l'action : Pour chaque information transmise, se poser la question : "Qu'est-ce que je veux que le parent fasse de cette information ?".

Cela permet de formuler des suggestions concrètes (ex: "Vous pourriez l'encourager en...", "N'hésitez pas à lui demander comment...").

5. Vers la Coéducation : Bénéfices d'une Responsabilité Partagée

L'instauration d'une collaboration solide et d'une relation de confiance entre l'école et la famille mène à une véritable coéducation.

Cette responsabilité partagée génère des bénéfices significatifs pour toutes les parties prenantes.

• Pour l'enseignant :

◦ Briser l'isolement : Le parent devient un allié dans la résolution de problèmes.  

◦ Stimuler la créativité : L'échange avec le parent apporte de nouvelles perspectives et idées d'intervention.  

◦ Gagner en efficacité : Bien que la collaboration demande du temps initialement, elle permet de comprendre plus vite les situations et de trouver des solutions plus durables, rendant le travail plus efficace à long terme.

• Pour le parent :

◦ Se sent valorisé, compétent et partie prenante de la réussite de son enfant.

• Pour l'élève :

◦ Bénéficie d'un soutien cohérent et aligné entre la maison et l'école, favorisant sa réussite scolaire et éducative.

Soutenir l'Enfant face au Stress Toxique : Synthèse des Idées d'Alexandra Mathurin-Landry

Résumé Exécutif

Ce document de synthèse présente les perspectives d'Alexandra Mathurin-Landry, psychologue, neuropsychologue et professeure spécialisée dans le trauma infantile.

L'analyse distingue trois types de stress — positif, tolérable et toxique — en se concentrant sur les effets dévastateurs du stress toxique, étroitement lié au concept de "trauma complexe".

Le trauma complexe découle d'une exposition répétée et prolongée à des expériences d'adversité (abus, négligence) durant des périodes de développement critiques, souvent perpétrées par les figures de soin, ce qui prive l'enfant de tout effet protecteur.

Les données scientifiques, notamment une méta-analyse récente, révèlent l'ampleur du problème : 60 % des adultes rapportent avoir vécu au moins une expérience d'adversité dans l'enfance, et 16 % en ont vécu quatre ou plus, un seuil qui augmente substantiellement les risques développementaux.

Face à ce constat, les "approches sensibles au trauma" offrent une voie d'intervention prometteuse.

Le modèle "Attachement, Régulation et Compétences" (ARC) est présenté comme un cadre d'intervention concret, de plus en plus utilisé au Québec.

La mise en œuvre de ces approches repose sur une posture adulte de "syntonie" (ajustement empathique), qui consiste à devenir un "détective des émotions" pour comprendre les besoins non comblés derrière les comportements.

Trois stratégies concrètes sont proposées :

1) établir des routines prévisibles et sécurisantes ;

2) répondre aux besoins sous-jacents plutôt que de se focaliser sur les comportements visibles (l'analogie de l'iceberg) ; et

3) soutenir activement la régulation des émotions de l'enfant par la "corégulation", où le calme de l'adulte aide l'enfant à retrouver le sien.

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Introduction de l'Experte et du Sujet

L'intervenante, Alexandra Mathurin-Landry, est une experte reconnue dans le domaine du développement de l'enfant.

En tant que professeure agrégée à l'École de travail social et de criminologie, titulaire de la Chaire Richelieu de recherche sur la jeunesse, l'enfance et la famille, psychologue et neuropsychologue, ses travaux se concentrent sur l'amélioration des connaissances sur le trauma et le développement de pratiques innovantes et sensibles aux traumas.

L'objectif de la discussion est d'explorer les différentes formes de stress et d'identifier les moyens de soutenir le développement et la réussite des enfants qui y sont confrontés.

Les Trois Formes de Stress : Un Modèle de Compréhension

Contrairement à une perception monolithique, le stress n'est pas uniforme.

Un modèle distinguant trois formes de stress permet de mieux comprendre leurs impacts respectifs sur le développement de l'enfant.

1. Le Stress Positif

◦ Description : Une forme de stress bénéfique associée à des événements normatifs qui mobilisent la préparation et les apprentissages.   

◦ Exemples : Un examen scolaire, une présentation orale.  

◦ Impact : N'a pas d'effets négatifs à long terme sur le développement. Il contribue à l'adaptation et à la survie.

2. Le Stress Tolérable

◦ Description : Résulte d'un événement plus exceptionnel, unique et intense. Il a un début et une fin clairs.  

◦ Exemple : Un enfant se faisant frapper par une automobile.  

◦ Facteur Clé : La présence d'un adulte ou d'une figure de soutien qui offre un "effet protecteur" est cruciale.

Cet adulte croit, soutient et accompagne l'enfant, ce qui permet de mitiger les effets du stress et de le rendre "tolérable".

Le message clé est de ne "pas négliger le rôle qu'on peut avoir protecteur auprès des enfants".

3. Le Stress Toxique

◦ Description : Cette forme de stress est la plus dommageable.

Elle survient dans un contexte où un enfant est exposé de manière répétée et prolongée à des expériences de vie très difficiles.  

◦ Exemples : Abus, négligence.  

◦ Facteurs Aggravants :    

▪ Absence de Protection : L'effet protecteur de l'adulte est absent. Pire, les parents ou figures de soin peuvent être la source du trauma.  

▪ Nature du Trauma : Les événements menacent l'intégrité physique et psychologique de l'enfant, affectent son identité et peuvent être associés à un sentiment de trahison.  

◦ Impact : A des effets substantiels et à long terme sur tous les domaines du développement de l'enfant, y compris le développement du cerveau.

Du Stress Toxique au Trauma Complexe

Les travaux d'Alexandra Mathurin-Landry portent spécifiquement sur le "trauma complexe", un concept étroitement lié au stress toxique.

• Définition du Trauma Complexe : La situation d'un enfant exposé de façon répétée et prolongée à des expériences d'abus, de négligence ou d'autres problématiques familiales lors de périodes vulnérables du développement (petite enfance, adolescence).

• Chevauchement : Le trauma complexe peut être directement associé au stress toxique en raison de la nature chronique de l'adversité et de l'implication des figures de soin.

• Statut Diagnostique : Il est important de noter que ni le stress toxique ni le trauma complexe ne sont des diagnostics officiels, ce qui complique leur étude et leur quantification précise.

Prévalence de l'Adversité Infantile : Les Données Probantes

En l'absence de diagnostic formel, l'étude de la fréquence des expériences d'adversité (abus, négligence, problématiques familiales) permet d'estimer l'ampleur du phénomène.

Une méta-analyse récente (2023 ou 2024), combinant plus de 200 études et un demi-million d'individus, fournit des données robustes :

| Indicateur | Pourcentage | Interprétation | | --- | --- | --- | | Adultes ayant vécu au moins une forme d'adversité infantile | 60 % | Un chiffre qualifié d'"énorme" et de "trop élevé". | | Adultes ayant vécu quatre formes ou plus d'adversité infantile | 16 % | Un cumul qui augmente "substantiellement les risques" pour le développement. |

Pour rendre ce chiffre concret, 16 % équivaut à quatre enfants dans une classe de 25, dont le parcours de vie est marqué par une adversité significative.

Les Approches Sensibles au Trauma : Une Voie vers la Guérison

Malgré la gravité du problème, il existe des solutions efficaces.

Les "approches sensibles au trauma" sont des interventions qui ont montré des effets positifs significatifs.

• Définition : Des approches systémiques qui modifient la "manière de voir les choses, notre manière de penser, nos manières de faire".

Elles visent à ce que les pratiques, politiques et procédures tiennent compte de la réalité du trauma.

• Objectif : Créer des environnements sécurisants, accueillants et engageants pour les jeunes.

• Portée Universelle : Bien que conçues pour les enfants ayant un vécu traumatique, ces approches sont bénéfiques pour tous les enfants et ne présentent "pas de contre-indication".

Elles sont particulièrement importantes pour ceux qui vivent un stress toxique ou un trauma complexe.

Le Modèle ARC : Attachement, Régulation et Compétences

Le modèle ARC est un cadre d'intervention concret et tangible qui incarne les principes des approches sensibles au trauma.

Il connaît un essor important au Québec, notamment dans les services de protection de la jeunesse et dans les écoles.

• Cible : Il vise à outiller les intervenants, mais aussi les parents (biologiques, d'accueil) et autres "piliers de résilience".

• Objectifs Fondamentaux :

1. Attachement : Aider l'enfant à développer une base relationnelle sécurisante.  

2. Régulation : Soutenir l'acquisition de compétences et de stratégies de régulation des émotions.

Un point crucial est que cette acquisition doit être soutenue par l'adulte ; l'enfant ne doit pas être laissé seul.  

3. Compétences : Développer diverses compétences chez l'enfant.

La Syntonie : La Clé de Voûte de l'Intervention

Au cœur du modèle ARC se trouve le concept de "syntonie", aussi appelé "ajustement empathique". C'est un élément clé de la posture de l'adulte.

• Description : Une posture axée sur l'accueil, la sensibilité aux besoins et aux émotions de l'enfant, et la capacité à détecter ses signaux verbaux et non verbaux.

• La Métaphore du Détective : L'adulte doit agir comme un "détective des émotions", cherchant à comprendre ce qui se cache derrière un comportement.

Les comportements souvent jugés "perturbateurs" ou "oppositionnels" peuvent en réalité être la manifestation de besoins non comblés (affection, écoute, affirmation de soi) ou d'émotions non régulées.

Trois Stratégies Concrètes Issues du Modèle ARC

Pour traduire ces principes en actions, trois stratégies fondamentales sont proposées :

1. Établir des Routines

◦ Objectif : Sécuriser l'enfant par la prévisibilité. Les enfants ayant un vécu traumatique ont particulièrement besoin de prévisibilité, car leur vie passée en a souvent manqué.   

◦ Application : Les routines doivent être individualisées pour répondre aux besoins spécifiques de chaque enfant (ex: besoin de s'activer ou de se reposer le matin).

2. Répondre aux Besoins Sous-Jacents (L'Analogie de l'Iceberg)

◦ Concept : Les comportements visibles ne sont que la pointe de l'iceberg.

La majeure partie, sous la surface de l'eau, est constituée des besoins non comblés, des émotions non régulées et du vécu traumatique.  

◦ Intervention : Pour être efficace, l'intervention doit "plonger sous l'eau" et s'adresser aux causes profondes (besoins, émotions) plutôt que de se limiter à la gestion du comportement en surface.

En répondant aux besoins, les comportements problématiques sont susceptibles de diminuer.

3. Soutenir la Régulation des Émotions (La Corégulation)

◦ Principe : Ne pas laisser l'enfant seul face à ses émotions.

La "corégulation" est le processus par lequel "l'état calme de l'adulte va aider l'enfant à retrouver un état calme".  

◦ Action : L'adulte doit aider l'enfant à remplir sa "boîte à outils" de stratégies de régulation saines (car il n'en a peut-être pas appris ou en a développé de dangereuses comme l'automutilation).

Plus important encore, l'adulte doit être présent pour "ouvrir sa boîte à outils avec lui" et lui montrer comment utiliser les outils.

Document de Synthèse : Contrer l'Absentéisme au Secondaire

Résumé Exécutif

Ce document synthétise une approche innovante pour la gestion de l'absentéisme dans une école secondaire, développée et présentée par Véronique Sir, directrice d'établissement et candidate au doctorat.

Le projet marque une transition fondamentale d'un modèle punitif, jugé lourd et inefficace, vers un modèle relationnel qui responsabilise et outille les enseignants.

Cette nouvelle stratégie a permis de réduire de 50 % le nombre d'élèves présentant plus de 15 absences non motivées en une seule année scolaire.

Au-delà des chiffres, la retombée la plus significative est l'amélioration notable de la relation entre les enseignants et les élèves, les premiers n'étant plus perçus comme des "polices de la retenue" mais comme des adultes bienveillants et soucieux de la présence de chaque jeune.

La mise en œuvre s'est articulée en cinq étapes clés, incluant une analyse rigoureuse, la création d'un sous-comité stratégique, une approche pilote par "petits pas", une intégration systémique et un partage des connaissances.

Le projet met en lumière l'importance du temps, de l'adhésion des équipes et de la focalisation sur le pouvoir d'agir collectif de l'école plutôt que sur des facteurs externes.

Contexte et Problématique Initiale

À l'arrivée de la nouvelle direction il y a trois ans, deux irritants majeurs étaient palpables et verbalisés par le personnel de l'école :

1. Un manque de cohérence dans l'application du code de vie.

2. Une gestion des absences perçue comme excessivement lourde et inefficace.

Cette dernière tâche était si pesante que la majorité des enseignants souhaitaient s'en dégager.

L'analyse initiale des données a permis de "neutraliser l'effet négatif" des perceptions en démontrant que le problème, bien que réel, ne concernait que deux ou trois élèves par groupe, et non une majorité comme il était parfois ressenti.

Le Projet de Gestion des Absences : Une Approche Relationnelle

Philosophie et Changement de Paradigme

Le cœur du projet est un changement radical de philosophie, passant d'un système répressif à une approche humaine et proactive.

• D'un modèle punitif à un modèle relationnel : L'ancienne méthode, qui consistait à sanctionner l'absence (par exemple, par une retenue), est abandonnée au profit d'une démarche qui cherche à comprendre les causes de l'absence et à outiller l'élève.

Comme le résume Mme Sir : "On est passé d'un modèle punitif à un modèle relationnel et outillé soutenu par des facilitateurs à l'école."

• Le rôle central de l'enseignant : Le projet repose sur l'implication directe des enseignants, qui deviennent les premiers intervenants.

Ils sont responsables des sept premières interventions auprès de leurs élèves tuteurs, incluant deux appels aux parents pour les sensibiliser.

Cette approche s'oppose au réflexe de déléguer cette responsabilité à l'équipe de soutien, reconnaissant qu'une poignée d'intervenants ne peut gérer efficacement les absences de plus de 900 élèves.

La présence des enseignants est donc jugée "essentielle".

Résultats Quantitatifs

Le projet, axé sur une gestion par les résultats, a démontré un impact mesurable et significatif sur la réduction de l'absentéisme chronique non motivé.

| Période | Contexte | Nombre d'élèves avec >15 absences non motivées | | --- | --- | --- | | Juin 2024 | Fin de la phase pilote (3 mois, 3 groupes sur 35) | Environ 120 élèves | | Juin 2025 | Fin de la première année complète (tous les groupes) | Environ 60 élèves | | 31 octobre 2025 | Début de l'année scolaire en cours | 6 élèves |

Ces chiffres représentent une diminution d'environ 50 % des cas d'absentéisme chronique en un an.

Il est noté que le mois de juin tend à augmenter le nombre d'absences, ce qui rend la comparaison encore plus probante.

Le principal fait saillant est que tous les élèves de l'école (clientèle d'environ 950 jeunes) sont désormais connus et suivis, ne permettant à personne de "passer sous la craque".

Les Cinq Étapes de la Mise en Œuvre

Le cheminement réflexif du projet a été structuré en cinq phases distinctes, menées en collaboration avec des chercheurs universitaires.

1. Analyse de la situation : La première étape a consisté à faire émerger des données factuelles pour objectiver les deux irritants majeurs (code de vie et gestion des absences).

2. Création du sous-comité : Considérée comme le "cœur de la démarche", cette étape a impliqué la sélection stratégique de ses membres.

Le comité inclut non seulement des personnes ouvertes au changement, mais aussi des enseignants plus critiques et des membres du personnel encore attachés au modèle punitif.

L'objectif était de créer un espace de réflexion pour confirmer la fin du statu quo et construire une vision commune.

3. Culture des "petits pas" : Pour gérer le changement, le projet a débuté par un pilote limité : trois groupes, trois enseignants volontaires, pendant trois mois.

Ce n'est que la deuxième année que l'approche a été étendue à toute l'école.

Cette phase a été marquée par des "allers-retours constants" et un "droit à l'erreur", permettant d'ajuster les moyens tout en gardant le cap sur la finalité (le modèle relationnel).

4. Veilles et intégration systémique : Cette étape, imbriquée dans les autres, a consisté à ancrer le projet dans toutes les instances de l'école :

◦ Comité projet éducatif : Intégration d'indicateurs sur l'assiduité.   

◦ Plan de lutte contre la violence et l'intimidation : Favoriser un climat scolaire sécuritaire.  

◦ Assemblées générales : Véhiculer l'importance du projet, en faisant témoigner les "agents facilitateurs".  

◦ Rencontres de niveaux : Instaurer un point statutaire toutes les deux semaines pour suivre les élèves absentéistes.

5. Partage à la communauté : La dernière étape consiste à diffuser le projet pour "faire gagner du temps" à d'autres équipes-écoles, évitant ainsi de réinventer des solutions existantes.

Défis, Facteurs de Succès et Recommandations

Défis Rencontrés

• La gestion du temps et des attentes : Les résultats ne sont pas immédiats.

Comprendre les causes profondes de l'absentéisme prend du temps, ce qui peut être un défi dans une culture axée sur les résultats rapides.

• L'adhésion de l'équipe : La deuxième année, lorsque tout le personnel est impliqué, est cruciale et peut voir émerger plus de résistance.

Le sous-comité joue un rôle fondamental pour accueillir ces résistances sans reculer.

• La gestion des cas chroniques : Certains élèves, aux prises avec des enjeux de santé mentale ou de démotivation scolaire importants, résistent aux interventions.

L'implication des professionnels (psychoéducateurs, conseillers d'orientation) est ici fondamentale.

• Le roulement du personnel : L'arrivée de personnel non formé en pédagogie peut rendre la création de liens plus difficile, nécessitant un soutien accru de la part des "agents facilitateurs" internes.

Principale Réussite : L'Amélioration de la Relation Enseignant-Élève

Le gain le plus "magnifique" et le plus positif du projet est l'amélioration de la qualité des relations.

Les enseignants ne sont plus vus comme des agents de sanction. Un enseignant a partagé une anecdote révélatrice :

"Les élèves m'ont dit à plusieurs reprises cette année : 'Cou'donc, avez-vous une vie à part nous regarder à l'école ?'".

Pour l'équipe, cette remarque est une "victoire", car elle signifie que chaque élève sait qu'au moins un adulte se soucie de sa présence.

Erreurs à Éviter

1. Aller trop vite : Le changement culturel et la compréhension des causes profondes de l'absence exigent du temps.

2. Remettre le sort aux parents : Plutôt que de se concentrer sur les motifs d'absence (sur lesquels l'école a peu de contrôle), la discussion doit être réorientée vers le "pouvoir d'agir collectif" à l'interne.

3. Utiliser les données à mauvais escient : Un outil de suivi (Power BI) a été développé pour fournir des données quotidiennes.

La vigilance est de mise pour que ces données servent à comprendre et agir, et non à "masquer artificiellement" les problèmes ou à créer une compétition entre les écoles.

Retombées Stratégiques et Pérennité du Projet

Outre la baisse de l'absentéisme et l'amélioration des relations, le projet a généré plusieurs impacts positifs durables :

• Approche personnalisée : L'école est passée d'une généralisation ("tous les élèves de 4e secondaire s'absentent") à une analyse fine et personnalisée des besoins de chaque élève.

• Standardisation des interventions : Un protocole écrit garantit la qualité et la pérennité des interventions, indépendamment du personnel en place.

• Autonomisation et résilience des équipes : Les enseignants ont développé une autonomie ("empowerment") et une résilience face à la problématique, conscients de leur pouvoir d'agir collectif.

• Préparation à la croissance : La structure mise en place est comparée aux "fondations d'une maison", rendant l'école prête à accueillir une hausse de sa clientèle.

• Pérennité du modèle : Le projet est conçu pour être durable. L'objectif final est de développer une autonomie telle que le projet puisse survivre au départ de la direction actuelle.

Comme le conclut Mme Sir : "demain matin si je pars comme direction d'établissement, le projet va survivre grâce à nos agents facilitateurs qui vont assurer la pérennité du projet."

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

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Reply to the reviewers

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

*Using genetics and microscopy approaches, Cabral et al. investigate how fission yeast regulates its length and width in response to osmotic, oxidative, or low glucose stress. Miller et al. have recently found that the cell cycle regulators Cdc25, Cdc13 and Cdr2 integrate information about cell volume, time and cell surface area into the cellular decision when to divide. Cabral now build on this work and test how disruption of these regulators affects cell size adaptation. They find that each stress condition shows a distinct dependence on the individual regulators, suggesting that the complex size control network enables optimized size adaptation for each condition. Overall, the manuscript is clear and the detailed methods ensure that the experiments can be replicated.

Major comments:

1.) It would be much easier to follow the authors' conclusions, if in addition to surface area to volume ratio, length and width, they would also plot cell volume at division in Figs. 1-4.*

AUTHOR RESPONSE: Due to space constraints in the main (and supplemental) figures, we focused on SA:Vol ratio together with cell length and width, which directly define cell geometry in rod-shaped fission yeast. Surface area and volume are derived from these measurements and can be misleading when considered alone, as similar surface area or volume values can arise from distinct combinations of length and width. The SA:Vol ratio therefore serves as a robust integrative metric for capturing coordinated changes in length and width that reshape cell geometry. We would be happy to include individual surface area and volume plots if requested.

2.) To me, it seems that maybe even more than upon osmotic stress, the cdc13-2x strain differs qualitatively from WT in low glucose conditions, where the increased SA-V ratio is almost completely abolished.

AUTHOR RESPONSE: We agree with the reviewer and have revised the manuscript text to point out this difference. The newly added text states: “Under low glucose, cdc13-2x cells also showed a WT-like response, decreasing length and increasing in SA:Vol ratio (Figures 3B-D). However, this SA:Vol increase was reduced compared to WT (1% vs 8.5%; Figures 1D and 3B), suggesting impaired geometric remodeling under glucose limitation.”

3.) It is not entirely clear to me why two copies of Cdc13 would qualitatively affect the responses. Shouldn't the extra copy behave similarly to the endogenous one and therefore only lead to quantitative changes? Maybe the authors can discuss this more clearly or even test a strain in which Cdc13 function is qualitatively disrupted.

AUTHOR RESPONSE: Increased Cdc13 protein concentration in cdc13-2x cells disrupts the typical time-scaling of Cdc13 protein. Consistent with this, cdc13-2x cells enter mitosis at a smaller cell size. We have modified the text to clarify this point. The new text states: “To access the role of the Cdc13 time-sensing pathway, we disrupted Cdc13 protein abundance by creating a cdc13-2x strain carrying an additional copy of cdc13 integrated at an exogenous locus. cdc13-2x cells divided at a smaller size than WT, reflecting accelerated mitotic entry upon disruption of typical time-scaling of Cdc13 protein (Figure S1A).”

4.) I don't see why the authors come to the conclusion that under osmotic stress cells would maximize cell volume. It leads to a decreased cell length, doesn't it?

AUTHOR RESPONSE: WT cells under osmotic stress do decrease in length, but this is accompanied by an increase in cell width. Because width contributes disproportionately to cell volume in rod-shaped cells, this change results in a modest but reproducible reduction in the SA:Vol ratio relative to WT cells in control medium (Figure 1D). We note that the degree of this change under osmotic stress is small (-0.4%), although statistically significant (p * Likewise, in Figure 2B, they interpret tiny changes in the SA/V. By my estimation, the difference between control and osmotic stress is only 2% (1.195/1.17), less that the wild-type case, which appears to be twice that (which is still pretty modest). The small amplitude of these changes is obscured by the fact that the graphs do not have a baseline at zero, which, as a matter of good data-presentation practice, they should.

*

AUTHOR RESPONSE: We appreciate the reviewer’s distinction between statistical and biological significance and agree that this is an important point to clarify. We now note in the revised text that changes in SA:Vol ratio under osmotic stress are numerically small and should not be overinterpreted. Our revised text now states: “Under oxidative and osmotic stress, the SA:Vol ratio decreased, indicating greater cell volume expansion relative to surface area (Figure 1D). However, we note that the reduction in SA:Vol under osmotic stress, while statistically significant, was modest in magnitude (−0.4%).”

Although small in absolute terms, even subtle geometric changes can be biologically meaningful in fission yeast due to the small size of these cells, where minor shifts in length or width translate into measurable differences in membrane area relative to cytoplasmic volume. Importantly, in Figure 2B, the key observation is not the magnitude of the change but its direction: cdc25-degron-DaMP cells exhibit a ~2% increase in SA:Vol ratio under osmotic stress, in contrast to the decrease observed in WT cells under the same condition. This opposite response reflects altered cell geometry and is supported by corresponding changes in cell length and width. We have revised the Results text to emphasize both the modest magnitude and the directional nature of these effects: “Under osmotic stress, cdc25-degron-DaMP cells exhibited a ~2% increase in SA:Vol ratio, opposite to the modest decrease observed in WT cells. This increase arose from increased cell length and reduced width (Figures 2B-D).”

Regarding data presentation, because SA:Vol ratios vary over a narrow numerical range, setting the y-axis minimum to zero would compress the data and obscure all detectable differences. Instead, we have modifed our SA:Vol ratio graphs in Fig. 1-4 to have consistent axis scaling across panels to accurately convey relative changes while maintaining visual clarity. We are happy to provide full data tables and statistical outputs upon request.

* I am also concerned about the use of manual measurement of width at a single point along the cell. This approach is very sensitive to the choice of width point and to non-cylindrical geometries, several of which are evident in the images presented. MATLAB will return the ??? as well as the length from a mask, but even better, one can more accurately calculate the surface area and volume by assuming rotational symmetry of the mask. Given that surface area and volume calculation need to be redone anyway, as discussed below, I encourage the authors to calculate them directly from the mask, instead of using the cylindrical assumption.*

AUTHOR RESPONSE: In initial experiments to calculate surface area and volume of fission yeast cells for prior work (Miller et al., 2023, Current Biology) we found that automated width measurements by MATLAB or ImageJ were inaccurate for a subset of cells leading to noisy cell surface area and volume values. Measuring cell width by hand and assuming that each cell in a given strain had the same cell radius (average of population) for calculation of cell surface area and volume gave more consistent results and recapitulated established conclusions regarding size control mechanisms.

In this previous work and the current study, abnormally skinny or wide regions of a cell were avoided when drawing a line to measure the cell width by hand. For each strain and condition, an average cell width was determined per independent experiment and used for surface area and volume calculations. Additionally, previous analysis demonstrated that this approach yields results consistent with a rotation method derived directly from cell masks, which does not assume a cylindrical cell shape (Facchetti et al., 2019, Current Biology; Miller et al., 2023, Current Biology).

To test the validity of our size measurements and confirm the robustness of our results in this study we compared the surface area and volume of cells by this rotation method. We have added this additional information to our revised methods section and also added SA:Vol ratio graphs generated from the rotation size measurement to our revised Figure S1 E-J. Importantly, both approaches used to measure cell size gave consistent results and supported the same conclusions.*

The authors also need to be more careful about their claims about size-dependent scaling. The concentration of both Cdc13 and Cdc25 scale with size (perhaps indirectly, in the case of Cdc13), but Cdr2 does not. Cdr2 activity has been proposed to scale with size, and its density at cortical nodes has been reported to scale with size, although that claim has been challenged .*

AUTHOR RESPONSE: We have modified text in the Introduction and Results to address this point. Our revised text in the introduction states: “Recent work has shown that Cdk1 activation integrates size- and time-dependent inputs: the Wee1-inhibitory kinase Cdr2 cortical node density scales with cell surface area (Pan et al., 2014; Facchetti et al., 2019); Cdc25 nuclear accumulation scales with cell volume; and cyclin Cdc13 accumulates over time in the nucleus (Miller et al., 2023) (Figure 1B).” Our revised text in the results section states: “Cdr2 functions as a cortical scaffold that regulates Wee1 activity in relation to cell size, with Cdr2 nodal density reported to scale with cell surface area, enforcing a surface area threshold for mitotic entry (Pan et al., 2014; Allard et al., 2018; Facchetti et al., 2019; Sayyad and Pollard, 2022).”*

Even taking the authors approach at face value, there are observations that do not seem to make sense, which led me to realize that the wrong formulae were used to calculate surface area and volume.

In Figure 1E,F, the KCl-treated cells get shorter and wider; surely, that should result in a lower SA/V ratio. However, as noted above, in Figure 1D, they are shown to have a similar ratio. As a sanity check, I eye-balled the numbers off of the figure (control: 14 µm x 3.6 µm and KCl: 11 µm x 3.8 µm) and calculated their surface area and volume using the formula for a capsule (i.e., a cylinder with hemispheric ends).

SA = the surface area of the two hemispheres + the surface are of the cylinder in between = 4*pi*(width/2)^2 + pi*width*(length-width), the length-width term calculates the side length of the capsule (length without the hemispheres) from the full length of the capsule (length including the hemispheres)

V = the volume of the two hemispheres + the volume of the cylinder in between = 4/3*pi*(width/2)^3 + pi*(width/2)^2*(length-width).

I got SA/V ratios of around 2, which are way off from what is presented in Figure 1D, but my calculated ratio goes down in KCl, as expected, but not as reported.

To make sure I was not doing something wrong, I was going to repeat my calculations with the formulae in Table 1, which made me realize both are incorrect. The stated formula for the cell surface area-2*pi*RL-only represents to surface area of the cylindrical side of the cells, not its hemispherical ends. And it is not even the correct formula for the surface area of the side, because that calls for L to be the length of the side (without the hemispherical ends) not the length of the cell (which includes the hemispherical ends). L here is stated to be cell length (which is what is normally measured in the field, and which is consistent with the reported length of control cells in Figure 1E being 14 µm). The formula for the volume of a capsule in the form use in Table 1 (volume of a cylinder of length L - the volume excluded from the hemispherical ends) is pi*R^2*L - (8-(4/3*pi))*R^3.

Given these problems, I think I spent too much time thinking about the rest of the paper, because all of the calculations, and perhaps their interpretations, need to be redone.*

AUTHOR RESPONSE: The surface area and volume equations for a cylinder with hemispherical ends used in our study and listed in our table are correct and widely used in other work with fission yeast cells (Navarro and Nurse, 2012; Pan et al., 2014; Facchetti et al., 2019; BayBay et al., 2020; and Miller et al., 2023). We write our equations with variables for cell length and radius because these are biologically relevant and measured parameters for fission yeast cells. Cell length (L) refers to the total tip-to-tip length of the cell, including the hemispherical ends, and radius (R) refers to half the measured cell width. We have revised the Methods section to clarify this definition and avoid ambiguity (Please see methods section “Cell geometry measurements”)

Additionally, SA or Vol calculations were performed using the length of each individual cell and the average cell radius of the population. We did not use mean cell length of the population for our calculations like the reviewer assumed in their “sanity check” above. Please see methods section “Cell geometry measurements”. We hope that these clarifications and text revisions improve transparency and reproducibility.

* Minor Points:

Strains should be identified by strain number is the text and figure legends.*

AUTHOR RESPONSE: For clarity and readability, we refer to strains by genotype in the main text and figure legends, which we believe is more informative for readers than strain numbers. All strain numbers corresponding to each genotype are provided in Table S1, ensuring traceability and reproducibility without compromising clarity in data presentation.*

In the Introduction, "Most cell control their size" should be "Most eukaryotic cell control their size".*

• *

AUTHOR RESPONSE: The text has been corrected as suggested.*

Reviewer #2 (Significance (Required)):

Nothing to add.*

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

Summary This manuscript reports that fission yeast cells exhibit distinct cell size and geometry when exposed to osmotic, oxidative, or low-glucose stress. Based on quantitative measurements of cell length and width, the authors propose that different stress conditions trigger specific 'geometric adaptation' patterns, suggesting that cell size homeostasis is flexibly modulated depending on environmental cues. The study provides phenotypic evidence that multiple environmental stresses lead to distinct outcomes in the balance between cell surface area and volume, which the authors interpret as stress-specific modes of size control.

Major comments 1) The authors define the 48-hour time point as the 'long-term response', but no justification is provided for why 48 hours represents a physiologically relevant adaptation phase. It is unclear whether the size-control mode has stabilized by that time, or whether it may continue to change afterward. At minimum, the authors should provide a rationale (e.g., growth recovery dynamics, transcriptional adaptation plateau, or pilot time-course observations) to demonstrate that 48 hours corresponds to the steady-state adaptive phase rather than an arbitrarily selected time point.*

AUTHOR RESPONSE: We thank the reviewer for this important point and agree that the definition of the long-term response should be clarified. We have addressed this with new experiments and revised text. We now incorporate growth curve data and doubling time analyses for all yeast strains grown under control and stress conditions (See new Figure S3). These analyses show that following an initial transient stress-induced cell cycle delay, growth rates stabilize well before 48 hours. Notably, the slowest growth rate observed was in 1M KCl, with a doubling time of ~4 hours across all yeast strains tested. Thus, by 48 hours, cells in this condition have undergone more than 12 generations of growth, while cells in all other conditions with shorter doubling times have undergone even more divisions. So by allowing cells to grow for 48 hours prior to imaging, we are capturing cells that have resumed sustained cell cycle progression following transient stress-induced cell cycle delays. Because cell size control is tightly linked to the cell cycle, we define 48 hours as a physiologically relevant time point where cells have adapted to stress conditions.

Our revised methods now states: “Cultures were incubated at 25°C while shaking at 180 rpm for 48 h prior to imaging. This time point was chosen to ensure that cells had progressed beyond the initial transient stress response and reached a stable, condition-specific growth state, as confirmed by growth curve and doubling time analyses showing stabilization well before 48 h (Figure S3), including in the slowest growing condition (1 M KCl; doubling time ~4 h).”

* 2*）Related to the above comment, the authors propose that different stresses lead to distinct cell size adaptations, yet the rationale for the chosen stress intensities and exposure times is insufficiently described. It remains unclear whether the osmotic, oxidative, and low-glucose conditions used here induce comparable levels of cellular stress. Dose-response and time-course analyses would greatly strengthen the conclusions. Without such analyses, it is difficult to support the interpretation that geometry modulation represents a direct adaptive response.

AUTHOR RESPONSE: * *We selected the specific stress conditions based on previously published work showing that these doses elicit robust responses while preserving overall cell viability and the capacity for recovery. We note that osmotic, oxidative, and low glucose conditions perturb fundamentally different cellular systems (turgor pressure and cell wall mechanics, redox balance, and metabolism etc.) and therefore do not generate directly comparable levels of cellular stress in a quantitative sense. Our goal was not to equalize stress intensity across conditions, but to examine how cells change their geometry in response to distinct classes of stressors.

We have clarified the rationale for specific stress conditions in the revised methods: “These stress intensities were selected based on prior studies demonstrating robust cellular responses while preserving cell viability and the capacity for recovery (Fantes and Nurse, 1977, Shiozaki and Russell, 1995, Degols, et al., 1996; López-Avilés et al., 2008; Sansó et al., 2008; Satioh et al., 2015, Salat-Canela et al., 2021, Bertaux et al., 2023).”

* 3) The authors describe stress-induced size changes as an 'adaptive' response. While this is an appealing hypothesis, the presented data do not demonstrate that the change in cell size itself confers a fitness advantage. Evidence showing that blocking the size change reduces stress survival-or that the altered size improves growth recovery- would be required to support this claim. Without such data, the use of the term 'geometric adaptation' seems overstated.*

AUTHOR RESPONSE: We have revised the text to remove the term “adaptive” and now describe stress-induced size changes in descriptive terms. As discussed further in response to Comment 4, new growth curve and doubling time analyses show that defects in surface area or volume expansion do not uniformly impair growth or survival over the stress exposure examined here, reinforcing the decision to avoid fitness-based language.*

4) The authors conclude that mutants exhibit no major defects in growth or viability during 48-hour stress exposure based on comparable septation index values (Fig. S2). However, septation index alone does not fully capture growth performance or cell-cycle progression and is not sufficient to support claims regarding fitness or robustness of proliferation. If the authors intend to make statements about 'growth', 'viability', or 'cell-cycle progression', additional quantitative measures (e.g., growth curves, doubling time, colony-forming units, or microcolony growth measurements) would be necessary. Alternatively, the claims should be toned down to align with the measurements currently provided.*

AUTHOR RESPONSE: We have addressed this concern with new experiments and revised text. In addition to septation index measurements (now analyzed using chi-square tests of proportions; Figure S2), we performed growth curve experiments and doubling time analyses for all genotypes under control and stress conditions (new Figure S3). These additional data show that growth rates are largely comparable across genotypes in control, oxidative, and low-glucose conditions, with more pronounced genotype-dependent differences emerging under osmotic stress. Defects in surface area or volume expansion did not uniformly correspond to impaired population growth, indicating that geometric remodeling is not strictly required for proliferation over the 48-hour stress exposure examined here. We have refined our conclusion to emphasize that defects in surface area or volume expansion do not uniformly impair growth or survival. See revised Results text under the heading “Defects in surface area or volume expansion do not uniformly compromise growth or survival”.*

5) Related to the above comment, the manuscript does not adequately rule out the possibility that the decreased division size simply results from slower growth or delayed cell-cycle progression rather than a shift in the size-control mechanism. Measurements and normalizations of growth rate are required; without them, the interpretation remains speculative.*

AUTHOR RESPONSE: We agree that changes in growth rate or altered cell cycle timing are important to consider. We have revised our text: “Changes in growth rate or cell cycle progression under stress may influence division size by altering mitotic regulator accumulation. Future studies measuring mitotic regulator dynamics alongside growth rates will be needed to distinguish direct changes in size control mechanisms from growth- or timing-dependent effects.”

* 6) Regarding the phenotypes of wee1-2x cells, it is interesting that they increase the SA:Vol ratio under all stress conditions and show phenotypes distinct from cdr2Δ cells. From these observations, the authors claims that Cdr2 and Wee1 function as a surface-area-sensing module that complements the volume-sensing and time-sensing pathways to maintain geometric homeostasis. To support this interpretation, the authors could consider additional experiments, such as analyzing cdr2Δ + wee1-2x cells under the same stress conditions. Such data would test whether increased Wee1 can rescue or modify the cdr2Δ phenotype, providing functional evidence for the proposed Cdr2-Wee1-Cdk1 regulatory relationship. Measurements of cell length, width, SA:Vol ratio, and, if feasible, Cdk1 activity markers in the strain would greatly strengthen the mechanistic claims.*

AUTHOR RESPONSE: We thank the reviewer for this insightful suggestion. While analysis of a cdr2Δ wee1-2x strain could provide additional mechanistic detail, such experiments address a distinct question beyond the scope of our current study, which focuses on how cell geometry changes under different stress conditions in cells with perturbed surface area-, volume-, or time-sensing pathways. Our conclusions regarding a surface area-sensing role for Cdr2-Wee1 signaling are based on previous studies (Pan et al., 2014; Facchetti et al., 2019; Miller et al., 2023) and the cell geometry phenotypes we observe of cdr2Δ and wee1-2x cells under stress conditions. *

Minor comments 1) The manuscript focuses on adaptation through changes in the surface-to-volume ratio; however, only the ratio is shown. Presenting the underlying values of surface area and volume would clarify which geometric parameter primary contributes to the observed changes.*

AUTHOR RESPONSE: Please see our response to Reviewer 1 major comment 1.*

*2) Statistical analysis for Fig.S2 should be provided.

AUTHOR RESPONSE: We have completed this. See revised Figure S2 and methods.*

3) The paper by Kellog and Levin 2022 is missing from the reference list.*

AUTHOR RESPONSE: Thank you for catching this. This reference has now been added. *

**Referees cross-commenting**

After reading the other reviewer's reports, I recognize that focal points differ, but they appear sequential rather than contradictory.

Reviewer 2 raises concerns regarding the surface area/volume calculations, which-if incorrect-would influence many of the quantitative conclusions. I agree that confirming the validity of these calculations (and recalculating if necessary) should be the top priority before evaluating the biological interpretations.

Reviewer 1 raises more mechanistic biological questions. These are certainly important, but in my view they depend on the robustness of the quantitative analysis highlighted by Reviewer 2.

Therefore, I regard the reports as complementary rather than conflicting. Once the analytical issue pointed out by Reviewer 2 is resolved, the field will be in a better position to assess the significance of the mechanistic points raised by Reviewer 1 (as well as those in my own report).

Reviewer #3 (Significance (Required)):

General assessment One of the major strengths of this manuscript is its quantitative, side-by-side comparison of multiple environmental stresses under a unified experimental and analytical framework. The authors provide well-controlled morphometric measurements, allowing direct comparison of geometry changes that would otherwise be difficult to evaluate across studies. The observation that different stress types generate distinct geometric outcomes is particularly intriguing and has the potential to stimulate new conceptual thinking in the field of size control. However, the strength of the conceptual conclusion is currently limited by several aspects of the experimental design and interpretation. In particular, it remains unclear whether the observed geometry changes represent active adaptive responses rather than non-specific consequences of prolonged or string stress exposure. Demonstrating whether geometry remodeling provides a fitness advantage, clarifying whether the changes reach a steady-state rather than reflecting slow drift over time, or identifying upstream stress pathways that govern the response would substantially strengthen the conceptual advance. Even if additional mechanistic or fitness-related data cannot be added, refining the interpretation so that it remains aligned with the present evidence will enhance the clarity, and impact of the study.

Advance Previous study - including the 2023 publication by the James B. Moseley group - established that fission yeast integrates distinct size-control pathways related to surface area, volume, and time under normal growth conditions. The present manuscript extends this line of work to stressed environments and argues that each stress condition elicits a distinct size-control pattern. To our knowledge, a systematic comparison of cell geometry across multiple stress types in the context of size-control pathways has not been reported, and this represents a potentially valuable conceptual advance. The advance is primarily phenomenological and conceptual rather than mechanistic: the work presents new correlation between stress types and geometry but does not yet elucidate the pathways governing these responses or demonstrate a functional advantage. With additional evidence - or with qualifiers ensuring that claims match the current data - the study could make an important contribution to understanding how cells integrate environmental cues into size-control strategies.

Audience Although the primary audience consists of researchers in the fields of cell growth, cell-cycle control, and stress responses in yeast, the conceptual contribution may interest broader fields such as growth homeostasis, metabolic adaptation, and pathological cell size changes in higher eukaryotes. Beyond yeast biology, the modular view of size regulation proposed here may inspire new investigations in stem cell biology, cancer research, and biotechnology where environmental adaptation and cell size are closely linked.

Expertise: nuclear morphology; cell morphology; cell growth; cell cycle; cytoskeleton*

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #3

Evidence, reproducibility and clarity

Summary

This manuscript reports that fission yeast cells exhibit distinct cell size and geometry when exposed to osmotic, oxidative, or low-glucose stress. Based on quantitative measurements of cell length and width, the authors propose that different stress conditions trigger specific 'geometric adaptation' patterns, suggesting that cell size homeostasis is flexibly modulated depending on environmental cues. The study provides phenotypic evidence that multiple environmental stresses lead to distinct outcomes in the balance between cell surface area and volume, which the authors interpret as stress-specific modes of size control.

Major comments

1) The authors define the 48-hour time point as the 'long-term response', but no justification is provided for why 48 hours represents a physiologically relevant adaptation phase. It is unclear whether the size-control mode has stabilized by that time, or whether it may continue to change afterward. At minimum, the authors should provide a rationale (e.g., growth recovery dynamics, transcriptional adaptation plateau, or pilot time-course observations) to demonstrate that 48 hours corresponds to the steady-state adaptive phase rather than an arbitrarily selected time point.

2）Related to the above comment, the authors propose that different stresses lead to distinct cell size adaptations, yet the rationale for the chosen stress intensities and exposure times is insufficiently described. It remains unclear whether the osmotic, oxidative, and low-glucose conditions used here induce comparable levels of cellular stress. Dose-response and time-course analyses would greatly strengthen the conclusions. Without such analyses, it is difficult to support the interpretation that geometry modulation represents a direct adaptive response.

3) The authors describe stress-induced size changes as an 'adaptive' response. While this is an appealing hypothesis, the presented data do not demonstrate that the change in cell size itself confers a fitness advantage. Evidence showing that blocking the size change reduces stress survival-or that the altered size improves growth recovery- would be required to support this claim. Without such data, the use of the term 'geometric adaptation' seems overstated.

4) The authors conclude that mutants exhibit no major defects in growth or viability during 48-hour stress exposure based on comparable septation index values (Fig. S2). However, septation index alone does not fully capture growth performance or cell-cycle progression and is not sufficient to support claims regarding fitness or robustness of proliferation. If the authors intend to make statements about 'growth', 'viability', or 'cell-cycle progression', additional quantitative measures (e.g., growth curves, doubling time, colony-forming units, or microcolony growth measurements) would be necessary. Alternatively, the claims should be toned down to align with the measurements currently provided.

5) Related to the above comment, the manuscript does not adequately rule out the possibility that the decreased division size simply results from slower growth or delayed cell-cycle progression rather than a shift in the size-control mechanism. Measurements and normalizations of growth rate are required; without them, the interpretation remains speculative.

6) Regarding the phenotypes of wee1-2x cells, it is interesting that they increase the SA:Vol ratio under all stress conditions and show phenotypes distinct from cdr2Δ cells. From these observations, the authors claims that Cdr2 and Wee1 function as a surface-area-sensing module that complements the volume-sensing and time-sensing pathways to maintain geometric homeostasis. To support this interpretation, the authors could consider additional experiments, such as analyzing cdr2Δ + wee1-2x cells under the same stress conditions. Such data would test whether increased Wee1 can rescue or modify the cdr2Δ phenotype, providing functional evidence for the proposed Cdr2-Wee1-Cdk1 regulatory relationship. Measurements of cell length, width, SA:Vol ratio, and, if feasible, Cdk1 activity markers in the strain would greatly strengthen the mechanistic claims.

Minor comments

1) The manuscript focuses on adaptation through changes in the surface-to-volume ratio; however, only the ratio is shown. Presenting the underlying values of surface area and volume would clarify which geometric parameter primary contributes to the observed changes.

2) Statistical analysis for Fig.S2 should be provided.

3) The paper by Kellog and Levin 2022 is missing from the reference list.

Referees cross-commenting

After reading the other reviewer's reports, I recognize that focal points differ, but they appear sequential rather than contradictory.

Reviewer 2 raises concerns regarding the surface area/volume calculations, which-if incorrect-would influence many of the quantitative conclusions. I agree that confirming the validity of these calculations (and recalculating if necessary) should be the top priority before evaluating the biological interpretations.

Reviewer 1 raises more mechanistic biological questions. These are certainly important, but in my view they depend on the robustness of the quantitative analysis highlighted by Reviewer 2.

Therefore, I regard the reports as complementary rather than conflicting. Once the analytical issue pointed out by Reviewer 2 is resolved, the field will be in a better position to assess the significance of the mechanistic points raised by Reviewer 1 (as well as those in my own report).

Significance

General assessment

One of the major strengths of this manuscript is its quantitative, side-by-side comparison of multiple environmental stresses under a unified experimental and analytical framework. The authors provide well-controlled morphometric measurements, allowing direct comparison of geometry changes that would otherwise be difficult to evaluate across studies. The observation that different stress types generate distinct geometric outcomes is particularly intriguing and has the potential to stimulate new conceptual thinking in the field of size control. However, the strength of the conceptual conclusion is currently limited by several aspects of the experimental design and interpretation. In particular, it remains unclear whether the observed geometry changes represent active adaptive responses rather than non-specific consequences of prolonged or string stress exposure. Demonstrating whether geometry remodeling provides a fitness advantage, clarifying whether the changes reach a steady-state rather than reflecting slow drift over time, or identifying upstream stress pathways that govern the response would substantially strengthen the conceptual advance. Even if additional mechanistic or fitness-related data cannot be added, refining the interpretation so that it remains aligned with the present evidence will enhance the clarity, and impact of the study.

Advance

Previous study - including the 2023 publication by the James B. Moseley group - established that fission yeast integrates distinct size-control pathways related to surface area, volume, and time under normal growth conditions. The present manuscript extends this line of work to stressed environments and argues that each stress condition elicits a distinct size-control pattern. To our knowledge, a systematic comparison of cell geometry across multiple stress types in the context of size-control pathways has not been reported, and this represents a potentially valuable conceptual advance. The advance is primarily phenomenological and conceptual rather than mechanistic: the work presents new correlation between stress types and geometry but does not yet elucidate the pathways governing these responses or demonstrate a functional advantage. With additional evidence - or with qualifiers ensuring that claims match the current data - the study could make an important contribution to understanding how cells integrate environmental cues into size-control strategies.

Audience

Although the primary audience consists of researchers in the fields of cell growth, cell-cycle control, and stress responses in yeast, the conceptual contribution may interest broader fields such as growth homeostasis, metabolic adaptation, and pathological cell size changes in higher eukaryotes. Beyond yeast biology, the modular view of size regulation proposed here may inspire new investigations in stem cell biology, cancer research, and biotechnology where environmental adaptation and cell size are closely linked.

Expertise: nuclear morphology; cell morphology; cell growth; cell cycle; cytoskeleton.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

Cabral et al. present a analysis of the effects of environmental stress of cellular geometry in the fission yeast S. pombe. The stresses they study-oxidative, osmotic and nutritional-have previously been shown to affect cell size in fission yeast. Here, the authors do a more sophisticated analysis, measuring surface area as well as volume (for which length had previously been used as a proxy, assuming fission yeast cells are cylinders of constant width). In addition, they investigate the effect of mutations in three cell-cycle control proteins that have been proposed to regulate cell geometry: Cdc13, Cdc25 and Cdr2. It is an interesting study that could provide insight into cell-size control and environmental-stress response in fission yeast. However, I have serious concerns about the analysis of the data. In fact, as I was writing up my concerns, I noticed that the formulae in Table 1 for surface area and volume are incorrect, so the whole paper appears to require reanalysis.

One general problem is that the authors seem to confuse statistical significance with biological significance. They claim that both oxidative and osmotic stress cause a reduction in SA/V ratio. For oxidative stress, the difference is evident, but the control and KCl-treated cells look to have indistinguishable distributions. Perhaps there is a significant statistical difference between the, but I am skeptical. (I would ask for the data table to try out the stats myself, but given the revelation below that the number will all need to be recalculated, that point is moot). In any case, the difference is certainly not biologically significant.

Likewise, in Figure 2B, they interpret tiny changes in the SA/V. By my estimation, the difference between control and osmotic stress is only 2% (1.195/1.17), less that the wild-type case, which appears to be twice that (which is still pretty modest). The small amplitude of these changes is obscured by the fact that the graphs do not have a baseline at zero, which, as a matter of good data-presentation practice, they should.

I am also concerned about the use of manual measurement of width at a single point along the cell. This approach is very sensitive to the choice of width point and to non-cylindrical geometries, several of which are evident in the images presented. MATLAB will return the ??? as well as the length from a mask, but even better, one can more accurately calculate the surface area and volume by assuming rotational symmetry of the mask. Given that surface area and volume calculation need to be redone anyway, as discussed below, I encourage the authors to calculate them directly from the mask, instead of using the cylindrical assumption.

The authors also need to be more careful about their claims about size-dependent scaling. The concentration of both Cdc13 and Cdc25 scale with size (perhaps indirectly, in the case of Cdc13), but Cdr2 does not. Cdr2 activity has been proposed to scale with size, and its density at cortical nodes has been reported to scale with size, although that claim has been challenged <https://pubmed.ncbi.nlm.nih.gov/36093997>.

Even taking the authors approach at face value, there are observations that do not seem to make sense, which led me to realize that the wrong formulae were used to calculate surface area and volume.

In Figure 1E,F, the KCl-treated cells get shorter and wider; surely, that should result in a lower SA/V ratio. However, as noted above, in Figure 1D, they are shown to have a similar ratio. As a sanity check, I eye-balled the numbers off of the figure (control: 14 µm x 3.6 µm and KCl: 11 µm x 3.8 µm) and calculated their surface area and volume using the formula for a capsule (i.e., a cylinder with hemispheric ends).

SA = the surface area of the two hemispheres + the surface are of the cylinder in between = 4pi(width/2)^2 + piwidth(length-width), the length-width term calculates the side length of the capsule (length without the hemispheres) from the full length of the capsule (length including the hemispheres)

V = the volume of the two hemispheres + the volume of the cylinder in between = 4/3pi(width/2)^3 + pi(width/2)^2(length-width).

I got SA/V ratios of around 2, which are way off from what is presented in Figure 1D, but my calculated ratio goes down in KCl, as expected, but not as reported.

To make sure I was not doing something wrong, I was going to repeat my calculations with the formulae in Table 1, which made me realize both are incorrect. The stated formula for the cell surface area-2piRL-only represents to surface area of the cylindrical side of the cells, not its hemispherical ends. And it is not even the correct formula for the surface area of the side, because that calls for L to be the length of the side (without the hemispherical ends) not the length of the cell (which includes the hemispherical ends). L here is stated to be cell length (which is what is normally measured in the field, and which is consistent with the reported length of control cells in Figure 1E being 14 µm). The formula for the volume of a capsule in the form use in Table 1 (volume of a cylinder of length L - the volume excluded from the hemispherical ends) is piR^2L - (8-(4/3pi))R^3.

Given these problems, I think I spent too much time thinking about the rest of the paper, because all of the calculations, and perhaps their interpretations, need to be redone.

Minor Points:

Strains should be identified by strain number is the text and figure legends.

In the Introduction, "Most cell control their size" should be "Most eukaryotic cell control their size".

Significance

Nothing to add.

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Referee #1

Evidence, reproducibility and clarity

Using genetics and microscopy approaches, Cabral et al. investigate how fission yeast regulates its length and width in response to osmotic, oxidative, or low glucose stress. Miller et al. have recently found that the cell cycle regulators Cdc25, Cdc13 and Cdr2 integrate information about cell volume, time and cell surface area into the cellular decision when to divide. Cabral now build on this work and test how disruption of these regulators affects cell size adaptation. They find that each stress condition shows a distinct dependence on the individual regulators, suggesting that the complex size control network enables optimized size adaptation for each condition. Overall, the manuscript is clear and the detailed methods ensure that the experiments can be replicated.

Major comments:

1. It would be much easier to follow the authors' conclusions, if in addition to surface area to volume ratio, length and width, they would also plot cell volume at division in Figs. 1-4.
2. To me, it seems that maybe even more than upon osmotic stress, the cdc13-2x strain differs qualitatively from WT in low glucose conditions, where the increased SA-V ratio is almost completely abolished.
3. It is not entirely clear to me why two copies of Cdc13 would qualitatively affect the responses. Shouldn't the extra copy behave similarly to the endogenous one and therefore only lead to quantitative changes? Maybe the authors can discuss this more clearly or even test a strain in which Cdc13 function is qualitatively disrupted.
4. I don't see why the authors come to the conclusion that under osmotic stress cells would maximize cell volume. It leads to a decreased cell length, doesn't it?

Significance

Fission yeast has long been used as a model for eukaryotic cell size regulation. So far, this research has been mostly focused on steady state size regulation. While it has long been clear that cells across organisms adapt their size in response to environmental changes, little is known about how these external inputs are processed through the size control network. Dissecting how disruption of the various branches of the size control network affects size adaptation is an important step towards a mechanistic understanding of this process. Future studies will have to build on these observations and investigate how each stress mechanistically affects the respective regulator(s). While the details of the molecular players and their contribution to size adaptation are likely specific to fission yeast, the concept of stress type-specific size adaptation that is mediated through different regulators is likely conserved and thus of broader relevance.

В конце автор приходит к следующим мыслям: 1. Мусульманские страны сильно отличаются по религиозным традициям. 2. На индивидуальном уровне люди в мусульманских странах поддерживают демократию независимо от теологических различий. 3. Показатели религиозности мало объясняют, кто поддерживает демократию

Новизна работы заключается в комплексном подходе к исследованию. Автор использовал сразу несколько теорий (модернизация, социальный капитал и исламские ценности). Он также детально сосредоточился на личностных факторах и использовал широкую выборку данных. В целом, его подход "снизу вверх" показал свою эффективность в анализе формирования демократических установок в мусульманских странах.

Возможные вопросы на будущее: 1. Почему влияние образования отрицательно в некоторых странах (например, Бангладеш и Пакистан)?

1. Какие факторы, не включенные в исследование, могли бы влиять на поддержку демократии?

2. Можно ли использовать эти методы для других регионов мира?

Автор соглашается с этими исследователями и использует их работы и эмпирические наблюдения в качестве своих аргументов. При этом критически относится к Липсету, т.к. на индивидуальном уровне ислам не препятствует поддержке демократических режимов.

Абмрозия. Челы покупют лечение-омоложение. при этом вся эта схема на формальном уровне выглядит как эксперемент.

во первых, это сделано для того, чтоб данную операцию по переливанию молодой крови не считать лечением - уменьшение бюрократии.

во-вторых, правах эксперемента они могут брать кровь у фонда (сугубо для эксперемента).

по итогу, разные миллиардены учавстовали в этом эксперементе. 2016 год.

один из первых людей решивших стать бессмертным был китайский император, который шатался по всему китаю в поисках трав, шаманов, учёных и т.д, чтоб продлить свою жизнь. так, кстати, китай нашел Японию. а сам император умер от своих пилулю - ртути было много.

благодаря мылу люди стали жить до 40 лет к концу 19 века.

сейчас есть два типа трансгуманистов.

1. зожники - чистые прагматики - их цель прожить как можно больше времени в здоровом состоянии

2. техно гумансты - используют все технологии 21 века, чтоб прожить как можно больше.

пропаганда бессмертия - это часть плана стравохранния, чтоб люди больше платили за "полис"(у них эта штука стоит денег много денег).

логика проста. если богатые живут чаще и не пользуются им, то + деньги.

calico - одна из дочерних компании google, которая занимается борьбой со старением. полность засикреченно, но нанимает к себе ведущих учёных в областях старения.

хотя уже 12 лет живёт, но ничего интересного пока нету.

нынешнии гуманисты верят, что могут создать таблетку бессмертия, потому что уже много раз меняли эту реальность. Соц сети, ракеты, AI и т.д.

они очень самоуверены в этом плане уже.

в целом есть три виды гуманиста 1. теоритеки - футуролаги, придумывают. разные возможности рецепты. 2. практики - пробуют разную бады, питание, спорт 3. милиоенры - спонсируют все подряд, что связано с бессмпертием.

seria o KPI 23, de acordo com o PCA 100-3, sim