Sensitivity analysis enlightens effects of connectivity in a Neural Mass Model under Control-Target mode

PLOS Computational Biology

Dear Dr. Gautrais,

Thank you for submitting your manuscript to PLOS Computational Biology. After careful consideration, we feel that it has merit but does not fully meet PLOS Computational Biology's publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Arvind Kumar, Ph.D.

Academic Editor

PLOS Computational Biology

Hugues Berry

Section Editor

PLOS Computational Biology

Additional Editor Comments:

Your paper was reviewed by two experts. They both liked the paper but they have made several suggestions. So I would like to invite you consider those and revise your manuscript accordingly.

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At this stage, the following Authors/Authors require contributions: Jacques Gautrais. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Thank you of this paper. It discusses a technical but important aspect of understanding the excitatory inhibitory balance of the brain. The analysis is sound and correct. The derivations are easy to follow. There a few comments on the paper.

Major comments:

The paper studied how the stationary points of a dynamic system with single and collections of neuronal pools change depending on the internal connectivity and external forcing. The stability of a stationary point was partly explained for the single state system (excitation or inhibition only) but I did not see a stability analysis for the interconnected neural pools. This paper would gain considerably with an analytical section on the stability of the stationary points for each different connectivity set-up.

Minor comments:

1) The notation is not useful for a reader not accustomed to the specific references noted in the paper. The use of e.g. sn and sg for the state of the NMDA or GABA looks more like a product between s and n or g. It would be useful to use a specific notation for the terms (greek letters or other specific math symbols).

2) In equation 1 is $\sigma v_i$ a random noise? and if so how was it dealt with in deriving equation 5. Are there underlying assumptions of stability of the system? Again a stability analysis would be useful.

3) Line 185: What is canonical with equation 10. It is a useful expression, and used repeatedly in the manuscript but I do not see why it is called canonical.

4) Line 188: What does this mean: ...non linearity is the self-amplification of the excitatory pool by the recurrent connectivity, which is expressed in the function wn through the parameter W+.

5) line 207: The idea of connection gains having values above and below 0 is a new interesting constraint on the dynamics. This was partly discussed where the connection gain was treated as a gauge field in Cooray GK, Cooray V, Friston KJ. Cortical dynamics of neural-connectivity fields. Journal of Computational Neuroscience. 2025 Apr 10:1-9.

Reviewer #2: The paper presents an interesting approach to include and study the effects of inhibitory connectivity in phenomemological models such as neural field/mass models. The authors use the framework of sensitivity analysis to see how perturbation in one area (control) affects the activvation in another area (target), where the perturbed parameter is related to external input currents. The equations are modified to allow for both long-range excitatory and inhibitory connections (eq.4), which esssentially includes modulating the fraction of long range excitatory connections and rest is projected to the inhibitory population. Overall, a mathematically thorough and well-written paper.

While the idead is interesting and probably also has much need to be explored for development of modeling work in neuroscience, there are few major concerns that need to be addressed before I am convinced.

1. I am not very convinced with the idea of using just two-regions to demonstrate the concept. In such scenarios, the simplest case that should be tested is a three region model. May some examples of a structured sub-network involving three regions could be used (for ex. something from frontostriatal circuit ?)

2. Relating the change in sign of the derivative to iup or down-regulation is straightforward and trivial in a two region scenario. Again, the iossue is that when it is scaled to three or more regions is this interpretation valid ? As the effect could pass through many (intermediate) areas ? This should be discussed and the validity beyond two-region scenario should be throroughly discussed.

3. The nested sensitivity approach taken by the authors assume separability (if I am not mistaken). What would be the author's view on using Jacobian matrix instead ? Probably, a comparison with Jacobian-based sensitivityy would clarify the validity or limits of nestd sensitivity?

4. Regarding the structure of the paper, it would help to have a brief into to sensitivity analysis and its applications to neural mass models as part of lit review (ex. see https://doi.org/10.1103/PhysRevE.110.044208 ) as well as other approaches to understand parameter importance (PLoS Comput. Biol. 14, e1006009 (2018), PLoS Comput. Biol. 15, e1006694 (2019)).

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Reviewer #1: Yes

Reviewer #2: No: i could not find any git repo linked in the paper

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Reviewer #1: Yes: Gerald Cooray

Reviewer #2: No

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Reproducibility:

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PCOMPBIOL-D-25-00851R1

Sensitivity analysis enlightens effects of connectivity in a Neural Mass Model under Control-Target mode

PLOS Computational Biology

Dear Dr. Gautrais,

Thank you for submitting your manuscript to PLOS Computational Biology. After careful consideration, we feel that it has merit but does not fully meet PLOS Computational Biology's publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Feb 22 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at ploscompbiol@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pcompbiol/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

* A letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. This file does not need to include responses to formatting updates and technical items listed in the 'Journal Requirements' section below.

* A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

* An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, competing interests statement, or data availability statement, please make these updates within the submission form at the time of resubmission. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Arvind Kumar, Ph.D.

Academic Editor

PLOS Computational Biology

Hugues Berry

Section Editor

PLOS Computational Biology

Additional Editor Comments:

The two reviewers are now happy with the revision of the manuscript. There is one outstanding issue: the reviewers would like to have a look at the code. I read your note in the rebuttal letter. Until the reviewers are fully satisfied I cannot promise a positive outcome but since you have addressed all the concerns raised the only remaining issue is the code. As you may have seen by now it has become a norm and not just PloS Comp most journals would require you to submit the code to reproduce key results.

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

1) We have noticed that you have uploaded Supporting Information files, but you have not included a list of legends. Please add a full list of legends for your Supporting Information files after the references list.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: No further comments, thanks you.

Reviewer #2: I am satisfied with the responses. However, I cannot find any code/Data that is made available as per journal policies. Kindly make this available and then I happy to accept.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: No:

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Reviewer #1: Yes: Gerald K. Cooray

Reviewer #2: No

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Dear Dr. Gautrais,

We are pleased to inform you that your manuscript 'Sensitivity analysis enlightens effects of connectivity in a Neural Mass Model under Control-Target mode' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology.

Best regards,

Arvind Kumar, Ph.D.

Academic Editor

PLOS Computational Biology

Hugues Berry

Section Editor

PLOS Computational Biology

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Thank you for your patience with the review process. I am pleased to inform that now we can accept your paper in its current form. Congratulations for a very fine contribution.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #2: Thanks for providing the codes.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

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Reviewer #2: Yes: Narayan Puthanmadam Subramaniyam