Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital memristor networks

Muhammad Yousuf; Uzma Ahmad; Ghulam Muhammad; Hamed Alsulami

doi:10.1371/journal.pone.0339866

Peer Review History

Original SubmissionMay 24, 2025
25 Aug 2025 Decision Letter - Muntazir Hussain, Editor PONE-D-25-28173Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital Memristor networksPLOS ONE Dear Dr. Ghulam, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’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 Oct 09 2025 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 plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. 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, please include your updated statement in your cover letter. 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, Muntazir Hussain Academic Editor PLOS ONE Journal requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. When completing the data availability statement of the submission form, you indicated that you will make your data available on acceptance. We strongly recommend all authors decide on a data sharing plan before acceptance, as the process can be lengthy and hold up publication timelines. Please note that, though access restrictions are acceptable now, your entire data will need to be made freely accessible if your manuscript is accepted for publication. This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If you are unable to adhere to our open data policy, please kindly revise your statement to explain your reasoning and we will seek the editor's input on an exemption. Please be assured that, once you have provided your new statement, the assessment of your exemption will not hold up the peer review process. 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. Additional Editor Comments: Suggestions for Improvement Explicitly explain the significance of applying this model to digital memristor networks—how does the fuzzy fractional modeling enhance control of such systems? Provide a systematic schematic or flowchart to summarize the mathematical solution approach. Include a clearer explanation of how the results relate to real-world digital memristors. Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes Reviewer #4: Yes Reviewer #5: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: No Reviewer #3: N/A Reviewer #4: No Reviewer #5: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data 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 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—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: No Reviewer #3: Yes Reviewer #4: Yes Reviewer #5: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: No Reviewer #3: No Reviewer #4: Yes Reviewer #5: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: 1. Explain clearly fuzzy fractional generalized FitzHugh-Nagumo differential equations ? 2. How do fuzzy fractional generalized FitzHugh-Nagumo differential equations enhance the modeling of neurodynamical systems by incorporating uncertainty, memory effects, and nonlinear behavior? Reviewer #2: Dear Authors, thank you for submitting manuscript with interesting topic and with mathematical derivations appear very good. However, I have few comments that need to be addressed for improvement of this manuscript. (1) This manuscript lacks the validation of analytical solutions. Author must provide the evidence that solution are accurate and relevant to real-world memristor network. I suggest (a) Compare your a analytical solutions with numerial solutions. (b) Provide a more detailed discussion of the parameters used in your memristor network application. (2) Figures could be improved. Add axis labels and legends to make more easier to understand. (3) The English language needs significant improvement. There are numerous grammatical errors, inconsistencies in notation. (4) Improve the flow of the manuscript by adding more introductory and concluding sentences to each section. I hope addressing these concerns will improve the quality of manuscript for publication. Reviewer #3: This manuscript presents a fuzzy fractional modeling approach to generalized FitzHugh–Nagumo (FHN) equations incorporating Caputo gH-differentiability, with application to digital memristor networks. The study integrates nonlinear neuroscience modeling with fractional fuzzy calculus and emerging electronic devices, which is an interesting and multidisciplinary topic. The mathematical formulation is solid, but some aspects require clarification or refinement for technical completeness. 1. The physical motivation for applying the Caputo gH-differentiable fractional framework to the FHN model should be explained more clearly, especially its specific advantage over other fractional definitions in the context of memristor network dynamics. 2. The description of the generalized FHN system would benefit from explicitly listing all assumptions, including parameter constraints, initial conditions, and boundary conditions. 3. The derivation of the fuzzy fractional model lacks intermediate mathematical steps in some areas—adding these would improve transparency and reproducibility. 4. The link between the fuzzy fractional formulation and the memristor network model should be strengthened by explaining the mapping of FHN variables to memristor parameters. 5. Numerical implementation details (e.g., discretization method, time step size, stability considerations) are too brief—these should be expanded for clarity. 6. Figures showing simulation results should include axis labels with units where applicable, and legends should clearly identify different parameter cases. 7. A brief comparative discussion with other fractional-order modeling techniques (e.g., Atangana–Baleanu, Caputo–Fabrizio derivatives) could help highlight the novelty of the chosen method. 8. The conclusion should elaborate more on the potential practical implications in neuromorphic computing and whether the proposed approach is computationally feasible for large-scale memristor arrays. 9. For enhancing the introduction section with the new publications, old references may be replaced with new ones such as: Artificial neural network validation of MHD natural bioconvection in a square enclosure: entropic analysis and optimization Reviewer #4: The manuscript demonstrates significant potential and originality but requires substantial improvements in: 1. Clearer articulation of novelty. 2. Comparative and statistical validation of results. 3. Stronger discussion and conclusion. 4. Updated and more consistent references. Reviewer #5: Review Report The paper addresses the fuzzy fractional generalized FitzHugh-Nagumo differential equations (FFGFH-NDEs), which are crucial in biological systems, neuroscience, cardiac dynamics, and digital circuit theory. The study is well-aligned with the interdisciplinary scope of applied mathematics, fuzzy analysis, and computational neuroscience. • Provide numerical simulations alongside the analytical solutions to validate results. • Discuss biological interpretations in more depth, linking mathematics to real-world brain or cardiac systems. • Add a comparative analysis with existing solution techniques (e.g., Adomian decomposition, homotopy perturbation, or PINNs). • Enhance figures and graphical results with clearer visual representation. ****** 6. 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 Reviewer #3: No Reviewer #4: No Reviewer #5: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment 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. Registration is free. 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 PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0339866.r001
Revision 1
22 Sep 2025 Author Response \noindent August 25, 2025\\ Journal: PLOS One\\ Manuscript ID: Ms. Ref. No.: PONE-D-25-28173\\ Title: Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital Memristor networks\\\\ Dear Emily Chenette,\\\\ We sincerely appreciate the opportunity to revise our manuscript for possible publication in PLOS One and would like to thank you and the reviewers for their guidance and comments in your letter dated August 25, 2025. We have carefully incorporated their suggestions and made the necessary changes, including fixing grammatical and typing errors and improving the writing in certain areas. We are grateful for the valuable input provided by the reviewers and agree with all the comments made. We hope that the revised version of our paper meets their expectations and is suitable for publication in your esteemed journal.\\\\ Thank you for your time and consideration.\\\\ Best Regards,\\ Dr. G. Muhammad\\ (Corresponding Author) \newpage \begin{center} {\bf\large Response to the Comments of Reviewer 1} \end{center} 1. Explain clearly fuzzy fractional generalized FitzHugh-Nagumo differential equations ? \textcolor{blue} {\bf Our Response.} We appreciate this constructive comment. We have revised and clearly explained the fuzzy fractional generalized FitzHugh-Nagumo differential equations in section 3 according to your suggestions.\\\\ 2. How do fuzzy FFHNDEs enhance the modeling of neurodynamical systems by incorporating uncertainty, memory effects, and nonlinear behavior? \textcolor{blue} {\bf Our Response.} We appreciate this constructive comment. We have explained that how fuzzy fractional generalized FitzHugh-Nagumo differential equations enhance the modeling of neurodynamical systems by incorporating uncertainty, memory effects, and nonlinear behavior in introduction and section 5.\\ \begin{center} {\bf\large Response to the Comments of Reviewer 2} \end{center} 1. This manuscript lacks the validation of analytical solutions. Author must provide the evidence that solution are accurate and relevant to real-world memristor network. I suggest (a)..., (b)... \textcolor{blue} {\bf Our Response.} We appreciate your constructive comment. We have provided the detailed comparison of the proposed generalized fuzzy solutions and provided the detailed discussion in order to validate our results in section 4.\\ 2. Figures could be improved. Add axis labels and legends to make more easier to understand. \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have improved the figures by showing the axes clearly.\\ 3. The English language needs significant improvement. There are numerous grammatical errors, inconsistencies in notation. \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have corrected the grammatical errors and improved the manuscript by adding concluding sentences to each section. \begin{center} {\bf\large Response to the Comments of Reviewer 3} \end{center} 1. The physical motivation for applying the Caputo gH-differentiable fractional framework to the FHN model should be explained more clearly, especially its specific advantage over other fractional definitions in the context of memristor network dynamics.\\ \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have provided the physical motivation for applying the Caputo gH-differentiable in the introduction section and explained the proposed model in section 3 and the real-world benefits of the propsed model as memristors networks in section 5.\\ 2,3. The derivation of the fuzzy fractional model lacks intermediate mathematical steps in some areasâ€”adding these would improve transparency and reproducibility.\\ \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have revised the derivation of the fuzzy fractional model and organized the fuzzy solutions in a arranged way in section 3.\\ 4. The link between the fuzzy fractional formulation and the memristor network model should be strengthened by explaining the mapping of FHN variables to memristor parameters.\\ \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have provided the one-one correspondence of proposed model as an application of fuzzy memristor networks in in section 5.\\ 5,6,7. Numerical implementation details (e.g., discretization method, time step size, stability considerations) are too brief these should be expanded for clarity. A brief comparative discussion with other fractional-order modeling techniques (e.g., Atangana-Baleanu, Caputo-Fabrizio derivatives) could help highlight the novelty of the chosen method. \textcolor{blue} {\bf Our Response.} Thank you so much for your valuable comment. We have provided the numerical solutions at fixed fuzzy parameters and variables in order to determine the novelty and accuracy of the solutions of proposed model. We have provided the comparative discussion of fuzzy solutions with the other existing techniques to show the novelty of the fuzzy solutions.\\ 8. The conclusion should elaborate more on the potential practical implications in neuromorphic computing and whether the proposed approach is computationally feasible for large-scale memristor arrays.\\ \textcolor{blue} {\bf Our Response.} We have revised the conclusion section and explained the results in a broader way. \\ 9. For enhancing the introduction section with the new publications, old references may be replaced with new ones such as: Artificial neural network validation of MHD natural bioconvection in a square enclosure: entropic analysis and optimization\\ \textcolor{blue} {\bf Our Response.} We have revised the introduction section and added the new pubilcations related to the concerned work according to your suggestions. \begin{center} {\bf\large Response to the Comments of Reviewer 4} \end{center} The manuscript demonstrates significant potential and originality but requires substantial improvements in:1. Clearer articulation of novelty.2. Comparative and statistical validation of results..... \textcolor{blue} {\bf Our Response.} Thank you very much for your constructive commets on this manuscript. We have revised the article and provided clear understanding of novelty, comparative analysis, stronger discussion, and updated references related to proposed model. \begin{center} {\bf\large Response to the Comments of Reviewer 5} \end{center} The paper addresses the fuzzy fractional generalized FitzHugh-Nagumo differential equations (FFGFH-NDEs), which are crucial in biological systems... \textcolor{blue} {\bf Our Response.} Thank you very much for your constructive comments on this manuscript. We have provided the real-world application of the proposed model in memristors networks, added the numerical results of fuzzy solutions for fixed fuzzy parameters and variables, comparative analysis of fuzzy solutions with the exixting solutions and the graphical representations in the clear way according to the valuable suggestions.\\ Thank you very much!! Attachments Attachment Submitted filename: Reviewer response of PONE-D-25-28173.pdf https://doi.org/10.1371/journal.pone.0339866.r002
19 Nov 2025 Decision Letter - Muntazir Hussain, Editor PONE-D-25-28173R1Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital Memristor networksPLOS ONE Dear Dr. Muhammad, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the minor points raised during the review process. Please submit your revised manuscript by Jan 03 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 plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. 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, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Muntazir Hussain Academic Editor PLOS ONE 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. Please 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. Additional Editor Comments: The manuscript presents a study with good theoretical and applied contributions. All major concerns have been addressed. Please consider minor refinements. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed Reviewer #3: (No Response) Reviewer #5: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes Reviewer #3: (No Response) Reviewer #5: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes Reviewer #3: (No Response) Reviewer #5: I Don't Know ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data 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 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—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes Reviewer #3: (No Response) Reviewer #5: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes Reviewer #3: (No Response) Reviewer #5: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: The manuscript presents a novel and well-executed study with strong theoretical and applied contributions. The suggested improvements are minor but aimed at enhancing clarity and usability. 1) Summary Table of Differentiability Cases:Include a concise table summarizing all differentiability types and corresponding solution forms. 2) Schematic Diagram:Add a visual diagram illustrating the mapping between FFGFH-NDEs components and memristor network elements. 3) Notation Table:Include a table of symbols and notations used throughout the manuscript for clarity. 4) Broader Implications:Expand the discussion on how the proposed model could be extended to other domains such as fuzzy control systems or biological signal processing. Reviewer #3: Authors have done the required amendments and article is ready for publication. Reviewer #5: Accepted in the current form. All comments are addressed with full Concentration and care. paper can be accepted now ****** 7. 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 #2: No Reviewer #3: No Reviewer #5: Yes: Assad Ayub ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation. NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications. https://doi.org/10.1371/journal.pone.0339866.r003
Revision 2
26 Nov 2025 Author Response \noindent November 19, 2025\\ Journal: PLOS One\\ Manuscript ID: Ms. Ref. No.: PONE-D-25-28173\\ Title: Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital Memristor networks\\\\ Dear Emily Chenette,\\\\ We sincerely appreciate the opportunity to revise our manuscript for possible publication in PLOS One and would like to thank you and the reviewers for their guidance and comments in your letter dated November 19, 2025. We have carefully incorporated their suggestions and made the necessary changes, including fixing grammatical and typing errors and improving the writing in certain areas. We are grateful for the valuable input provided by the reviewers and agree with all the comments made. We hope that the revised version of our paper meets their expectations and is suitable for publication in your esteemed journal.\\\\ Thank you for your time and consideration.\\\\ Best Regards,\\ Dr. G. Muhammad\\ (Corresponding Author) \newpage \begin{center} {\bf\large Response to the Comments of Reviewer 2} \end{center} \begin{enumerate} \item Summary Table of Differentiability Cases: Include a concise table summarizing all differentiability types and corresponding solution forms.\\ \textcolor{blue} {\bf Our Response.} We appreciate this valuable comment. We have presented the summary table summarizing all differentiability types and corresponding solution forms.\\ \item Schematic Diagram: Add a visual diagram illustrating the mapping between FFGFH-NDEs components and memristor network elements.\\ \textcolor{blue} {\bf Our Response.} We appreciate this worthy comment. We have presented the schematic diagrams illustrating the mapping between FFGFH-NDEs components and memristor network.\\ \item Notation Table: Include a table of symbols and notations used throughout the manuscript for clarity.\\ \textcolor{blue} {\bf Our Response.} We appreciate your comment. We have presented the notation table of symbols and notation used throughout the manuscript.\\ \item Broader Implications: Expand the discussion on how the proposed model could be extended to other domains such as fuzzy control systems or biological signal processing.\\\\ \textcolor{blue} {\bf Our Response.} Thank you so much for your constructive comment. We have presented the discussion on the extension of proposed model for suggested domains. We have also revised and checked the correctness of all the references.\\ \end{enumerate} Attachments Attachment Submitted filename: Reviewer response of PONE-D-25-28173R2.pdf https://doi.org/10.1371/journal.pone.0339866.r004
15 Dec 2025 Decision Letter - Muntazir Hussain, Editor Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability:~ A novel fuzzy fractional approach to digital Memristor networks PONE-D-25-28173R2 Dear Dr. Ghulam, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Kind regards, Muntazir Hussain Academic Editor PLOS One Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0339866.r005
Formally Accepted
Acceptance Letter - Muntazir Hussain, Editor PONE-D-25-28173R2 PLOS One Dear Dr. Muhammad, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Muntazir Hussain Academic Editor PLOS One https://doi.org/10.1371/journal.pone.0339866.r006

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .