Dear Dr. Modenese,

Thank you very much for submitting your manuscript "Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific human musculoskeletal anatomy" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Please note in particular that, although both reviewers appreciated the thorough approach in the presented muscle model, they felt that there should be more discussion of how it fits into the context of existing models. Under what circumstances would this model (rather than a simpler one) be most applicable? How do the results compare to the classic single-input Hill-type model and what is the relative computational cost?

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Barbara Webb

Academic Editor

PLOS Computational Biology

Marieke van Vugt

Section Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The manuscript presents the detailed development and validation of a motoneuron driven, physiologically accurate, muscle model. Subject and muscle specific parameters were derived from medical imaging and literature data to generate an accurate representation of the individual neuromuscular anatomy and physiology. Motoneuron spike trains were experimentally derived from measurement of the tibialis anterior muscles during submaximal voluntary isometric contraction, and used to drive and validate the proposed model. Three different grid configurations, with varying density of HDEMG, were evaluated to assess the effect of experimental recording quality on the TA force prediction. The verification of the modelling pipeline was detailed and provided convincing results that supported the conclusions of the manuscript.

Overall, this paper is carefully written and a wonderful example of how a computational model should be developed and validated. Every modelling choice was planned, justified, and supported by literature. I could not fault any part of the modelling that was not already detailed in the limitations. The well organised equations also provide an excellent summary of much of the cited literature, which was needed. Finally, I truly appreciated that the authors provided the modelling code, which will surely boost future impact.

Generic comments

1. While the paper is technically excellent, I believe the parts of the discussions related to future applications were a bit vague and generic. The number of required parameters, the challenges of data acquisition, and the inability to function in dynamic conditions might limit the future use of the proposed model for most biomechanics applications. Overall, I would appreciate to see the discussion extended to highlight and detail how future applications or scientific investigations could truly leverage this model.

2. As the focus of the paper was on muscle force, one is left wondering how this modelling approach would compare to a classic single-fibre Hill-type bEMG-driven muscle model. An additional analysis of this type would be very useful.

Specific comments

P10 line 186. It is unclear whether duplicates of motor units were automatically or manually removed.

P13 line 260. Mus should be Mus

P15 line 323-324. The state variables have not been previously stated.

P38 line 837. “true neural to muscle” missing a word?

Reviewer #2: The authors have developed a complex computational model, supported by experimental work, that is controlled at the level of individual motor units (MUs) and accounts for the dynamics of MU recruitment.

The authors include some subject-specific metrics (muscle volumes, centroid lines of action) extracted from MRI. How big an effect do these subject-specific parameters have on the predicted results, as compared to generic values (i.e., how much value does this additional customization add to the model performance)?

Parameters of the model are derived from a combination of calibration of some parameters, and direct measurement and application of others. As such, a true model validation has not been performed. Please include discussion of this limitation in the manuscript.

Lines 621-622: What was the reason for these inaccurate description of discharge activity?

Why were experimental samples better approximated at lower MVCs (30% versus 50%)?

It would be informative if the authors discussed applications where they expect their model to perform better than current models, and why (e.g., phenomenological models).

The authors do not provide any benchmarking against more simplistic models, therefore it is difficult to assess if the additional complexity is warranted, or if the additional effort and complexity required has a negligible outcome on model performance.

Please include some numerical values to describe the computational costs associated with the model (i.e., simulation time for a specific set of hardware) as compared to the classic single-input Hill-type actuators.

**********

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 #1: Yes

Reviewer #2: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References:

Review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Dear Dr. Modenese,

We are pleased to inform you that your manuscript 'Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy' 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.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

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

Best regards,

Barbara Webb

Academic Editor

PLOS Computational Biology

Marieke van Vugt

Section Editor

PLOS Computational Biology

***********************************************************

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: I would like to thank the authors for their extensive replies to my comments.

Reviewer #2: The authors have provided a detailed and thorough response to the comments previously raised. I have no further comments.

**********

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 #1: Yes

Reviewer #2: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No