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I Can't Hear You Both at the Same Time: A Temporal Dilemma During Inter-Regional Communication.

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Paper

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The authors' code

MATLAB · 73 lines · 1.7 KB · no license

  1. clear all
  3. %%% Parameters
  4. beta_X = 4;
  5. beta_Y = 4;
  6. k = 1;
  7. epsilon = 1;
  8. r_I = 1.0;
  9. omega_I = 4; % Fixed omega_I
  10. tau_2 =0.1 ;
  11. r_X = 1; % Constant radius for X
  12. r_Y = 1; % Constant radius for Y
  14. % Initial conditions
  15. theta_X0 = 0.897117;
  16. theta_Y0 = 4.88914;
  17. initial_conditions = [theta_X0; theta_Y0];
  19. % Time span
  20. t_start = 0;
  21. t_end = 4;
  22. dt = 0.001;
  23. tspan = t_start:dt:t_end;
  25. % Convert delays to number of time steps
  26. tau_2_steps = round(tau_2 / dt);
  28. % Initialize solution arrays
  29. theta_X = zeros(size(tspan));
  30. theta_Y = zeros(size(tspan));
  31. theta_I = omega_I * tspan;
  33. % Set initial conditions
  34. theta_X(1) = theta_X0;
  35. theta_Y(1) = theta_Y0;
  36. vec1 = [];
  37. vec2=[];
  39. % Euler's method
  40. for i = 2:length(tspan)
  41. t = tspan(i);
  42. % k = mod(floor(t / 0.5), 2);
  43. % epsilon = 5*mod(floor(t / 0.5), 2);
  44. % Indices for delayed terms
  45. %idx_tau2 = max(1, i - tau_2_steps);
  46. if i <= tau_2_steps
  47. idx_tau2 = i-1;
  48. else
  49. idx_tau2 = i - tau_2_steps;
  50. end
  51. theta_Y_tau2 = theta_Y(idx_tau2);
  53. % Phase reduced model equations
  54. dtheta_X = beta_X + k * sin(theta_I(i-1) - theta_X(i-1));
  55. vec1(i-1) = theta_X(i-1) - theta_Y(i-1);
  56. vec2(i-1) = theta_Y_tau2 - theta_Y(i-1);
  57. dtheta_Y = beta_Y + epsilon * sin((theta_X(i-1) - theta_Y(i-1))) - sin((theta_Y_tau2 - theta_Y(i-1)));
  59. % Update phase angles using Euler's method
  60. theta_X(i) = theta_X(i-1) + dtheta_X * dt;
  61. theta_Y(i) = theta_Y(i-1) + dtheta_Y * dt;
  62. end
  64. % Plot results
  65. %clf;
  66. %plot(tspan, sin(theta_X), 'b', tspan, sin(theta_Y), 'r', tspan, sin(theta_I), 'g');
  67. %title('Phase Angles \theta_X, \theta_Y and \theta_I');
  68. %xlabel('Time');
  69. %ylabel('Phase Angles');
  70. %legend('\theta_X', '\theta_Y', '\theta_I');
  71. %plot_waves
  72. % Parameters
  73. create_fig

AS.m at commit eae00b3, no license · at the source

Overview

Authors: Salil Bhat1, Sanne Ten Oever1
ORCID iDs: Salil Bhat, Sanne Ten Oever
  1. Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229EV, The Netherlands
Institutions: Maastricht University (Netherlands)
Journal: eNeuro, volume 13, issue 8, pages ENEURO.0012-26.2026
Dates: received 14 January 2026; accepted 29 May 2026; published online 4 August 2026; in print August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1523/eneuro.0012-26.2026 · PMID 42552110 · PMCID PMC13555238 · OpenAlex W7172429511
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), systems (subfield)
Methods: Connectivity
Keywords: inter-area communication, neural oscillations, optimal coupling, synchronization
MeSH: Brain*, Models, Neurological*, Neurons*, Animals, Feedback, Physiological, Humans, Neural Pathways, Time Factors (* major topic)
Topic: Neural dynamics and brain function (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: European Research Council (101116685)
Citations: not cited yet (Europe PMC); 112 references in the paper

Abstract

Cognitive functioning depends on the brain’s ability to process sensory information and simultaneously integrate contextual feedback from higher-order regions like the prefrontal cortex (PFC). This requires the sensory cortex (SC) to handle both processes simultaneously. Some phase-coupled oscillator models propose that the scaffolding of neuronal communication occurs via oscillatory coupling of low-frequency oscillations. However, it is often neglected that processing this bidirectional input poses serious temporal constraints on the system. Specifically, is it possible for SC to be coupled to PFC, while at the same time being coupled to the sensory input? In this article, we describe the temporal constraints required to simultaneously process feedforward and feedback information through oscillatory coupling. We adopt a dynamical systems perspective to suggest mechanisms by which phase-coupled oscillator models can achieve optimal temporal dynamics for neural communication while accounting for these temporal constraints. Although initially counterintuitive, our proposed framework indicates that any viable solution of bidirectional phase-based coupling inherently relies on the feedforward scaffolding of neuronal communication. The mechanisms proposed here may generalize to other situations in which brain areas need to cope with bidirectional feedforward and feedback interactions while maintaining phase coupling.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

tedyUM/CommunicationDilemma_models

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: eae00b3ba7af87a482ec7f2baf38358df24edab7, 21 July 2025
Languages: MATLAB (7)
Size: 9 files, 7 scripts
Software Heritage: not archived
Found in: the text, “So, What’s the Catch?”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Signal Processing Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
8 files
At the source: github.com/tedyUM/CommunicationDilemma_models

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 7 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 4 keywords, 8 MeSH terms, 1 funder, 109 references.

Cite

This paper

Bhat, S., & Ten Oever, S. (2026). I Can't Hear You Both at the Same Time: A Temporal Dilemma During Inter-Regional Communication. eNeuro, 13(8), ENEURO.0012-26.2026. https://doi.org/10.1523/eneuro.0012-26.2026

BibTeX

@article{bhat2026i,
author = {Bhat, Salil and Ten Oever, Sanne},
title = {{I Can't Hear You Both at the Same Time: A Temporal Dilemma During Inter-Regional Communication}},
journal = {eNeuro},
year = {2026},
month = aug,
volume = {13},
number = {8},
pages = {ENEURO.0012--26.2026},
publisher = {Society for Neuroscience},
issn = {2373-2822},
doi = {10.1523/eneuro.0012-26.2026},
url = {https://doi.org/10.1523/eneuro.0012-26.2026},
pmid = {42552110},
pmcid = {PMC13555238}
}

RIS

TY - JOUR
AU - Bhat, Salil
AU - Ten Oever, Sanne
TI - I Can't Hear You Both at the Same Time: A Temporal Dilemma During Inter-Regional Communication
T2 - eNeuro
J2 - eNeuro
PY - 2026
DA - 2026/08/04
VL - 13
IS - 8
SP - ENEURO.0012
EP - 26.2026
SN - 2373-2822
PB - Society for Neuroscience
DO - 10.1523/eneuro.0012-26.2026
UR - https://doi.org/10.1523/eneuro.0012-26.2026
LA - en
ER -

CSL-JSON

{
"id": "10.1523/eneuro.0012-26.2026",
"type": "article-journal",
"title": "I Can't Hear You Both at the Same Time: A Temporal Dilemma During Inter-Regional Communication",
"container-title": "eNeuro",
"author": [
{
"family": "Bhat",
"given": "Salil"
},
{
"family": "Ten Oever",
"given": "Sanne"
}
],
"container-title-short": "eNeuro",
"volume": "13",
"issue": "8",
"page": "ENEURO.0012-26.2026",
"DOI": "10.1523/eneuro.0012-26.2026",
"PMID": "42552110",
"PMCID": "PMC13555238",
"ISSN": "2373-2822",
"publisher": "Society for Neuroscience",
"URL": "https://doi.org/10.1523/eneuro.0012-26.2026",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
4
]
]
}
}

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