Dear Ms Duecker,

Thank you very much for submitting your manuscript "Oscillations in an Artificial Neural Network Convert Competing Inputs into a Temporal Code" 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. In light of the reviews (below this email), we would like to invite the resubmission of a revised version that takes into account the reviewers' comments.

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[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).

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Sincerely,

Stefano Panzeri

Academic Editor

PLOS Computational Biology

Lyle Graham

Section Editor

PLOS Computational Biology

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Dear Authors, thanks for submitting this work to PLoS Computational Biology. As you will see below, the Reviewers found your paper of interest. However, they recommend that several improvements are made. We look forward to receiving the revised version. Yours truly, Stefano Panzeri (Academic Editor of this submission)

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: There is a broad range of temporal dynamics in the neural system, and these temporal dynamics are thought to have an important function in the representation of information, especially multiple competing information. In this manuscript, the authors trained the ANN to recognize letters, and with adding of temporal dynamics in the hidden layer, the ANN was able to read out sequentially for two letters presented at the same time. Moreover, the sequence of readout is along the phase of inhibitory oscillations. The results of the study proved that the inhibitory oscillations help to segregate the information in time. Overall, this study is a timely and insight-providing study that demonstrates the positive effects of oscillations on information readout. It was a pleasure to read such a well-designed and well-written study, and I think that both the neuroscience and machine learning fields will have interest in the results of this study, and I would like to see it published.

I have 3 small suggestions that the author might consider.

1. I would like the authors to discuss how the findings of this study contribute to our understanding of how the neural system works.

2. I would like to know if adding other frequencies of oscillations to the hidden layer by changing the time parameter would produce similar results to this study? In other words, could the authors discuss the similarities and differences between brain information processing and ANN information processing, especially in the time scales.

3. There is a small typo, the second line of 2.1 on page 3. Should it be Figure 2a?

Reviewer #2: My comments are in the attached document.

Reviewer #3: The review is uploaded as attachment.

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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 #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes: Jianrong Jia

Reviewer #2: Yes: Lou Zonca

Reviewer #3: Yes: Simone Blanco Malerba

Figure Files:

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Attachments

Attachment

Submitted filename: review Plos CB PCOMPBIOL-D-24-00669.pdf

Attachment

Submitted filename: Deucker_etal_PLOSReview.pdf

Dear Ms Duecker,

We are pleased to inform you that your manuscript 'Oscillations in an Artificial Neural Network Convert Competing Inputs into a Temporal Code' 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,

Stefano Panzeri

Academic Editor

PLOS Computational Biology

Lyle Graham

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Thanks to the author's efforts to revise the article, the current version is much better than the previous one. I have no further questions.

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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 #1: Yes

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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: Yes: Jianrong Jia