OSCR

Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity.

Code ↔ Paper

5 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 5 matches · all tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Miniscope Ca imaging with optogenetic manipulation ↔ findResponsiveNeuron/ROCanalysis.m, the whole file · a weak match · score 0.64 · auROC, behavioral event, variable, inhibited, neuron, window
  2. [2] § Methods › Fiber photometry Ca recording ↔ convergence/periEventSigArray.m, the whole file · a weak match · score 0.61 · frame rate, behavioral events, field, duration, window, dig
  3. [3] § Results › The aIC → mPFC neurons carry outcome information ↔ findResponsiveNeuron/periEventSigArray.m, the whole file · a weak match · score 0.56 · peri event, Behavioral events, eat, calcium, reward, neurons
  4. [4] § Results › The aIC → mPFC neurons carry outcome information ↔ convergence/periEventSigArray.m, the whole file · a weak match · score 0.56 · peri event, Behavioral events, eat, calcium, reward, dig
  5. [5] § Methods › Fiber photometry Ca recording ↔ findResponsiveNeuron/periEventSigArray.m, the whole file · a weak match · score 0.54 · frame rate, behavioral events, duration, neurons, window, dig

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

MATLAB · 127 lines · 4.6 KB · MIT · 2 matches

  1. function sigArray = periEventSigArray(dn,behEvtTbls)
  2. % This functions organizes ca signals into an periEvent array
  3. % Inputs:
  4. % dn: ca signal structure
  5. % .ca: calcium signal matrix: nFrame x nCell
  6. % .time: timestamps of each frame
  7. % .sttFrameT: table for the start time of each session of interest
  8. % behEvtTbls: structure with session name as field
  9. % behavior event table: nEvent x nFeature
  11. % Outputs:
  12. % sigArray: a structure with subfields for signals and metadata
  13. % .caA: calcium signals arranged in a 4d array
  14. % .Events: structure for behavior variables and event times organized by trial
  15. % .dimension = {'neuron','framePerWindow','eventWindow','trial'};
  17. %% organize multi-session signals
  18. sessionNames = fieldnames(behEvtTbls);
  19. nSession = length(sessionNames);
  21. %% extract ca signals corresponding to sessions
  22. % find the row (frame) index for the start of each session
  23. sessionStartIdx = zeros(nSession,1);
  24. for k = 1:nSession
  25. rowIdx = strcmp(dn.sttFrameT.session,sessionNames{k});
  26. sessionStartIdx(k) = find(dn.time==dn.sttFrameT.sttT(rowIdx));
  27. end
  29. sig = dn.ca(sessionStartIdx(1):end,:);
  30. time = dn.time(sessionStartIdx(1):end); % in sec
  31. fps = 1./diff(time(1:2)); % calcium frame rate ~10 Hz
  33. %% excluding start transients
  34. [~,nNeuron] = size(sig);
  36. % mask recording start caused transients in ca signal
  37. maskWin = round(3*fps); % 3 sec mask
  38. sigM = mean(sig,2);
  39. movieStartIdx = find(sigM == 0); % movie starts have 0 intensity
  40. transientFrame = movieStartIdx + (0:maskWin); % nStart x nWin
  41. transientFrame = transientFrame(:); % linearize
  43. sigN = sig;
  44. sigN(transientFrame,:) = NaN;
  45. sigN(sigN<0) = 0; % negative numbers are small and related to start transient in CNMFe
  47. % fill NaN in sigN by interpolation
  48. nanId = isnan(sigN(:,1));
  49. sigN = interp1(time(~nanId),sigN(~nanId,:),time);
  51. %% peri-event time windows
  52. tau = 2; %2 sec
  53. tWin = round(tau*fps);
  55. %% behavior variables to decode by trials: current and prior reward
  56. % event markers in behEvtTbls
  57. markerName = {'TrialStart','Approach','Dig','Outcome'};
  58. nMarker = length(markerName);
  60. % structures for behavior event times and labels, organized by trial
  61. EvtFrame = struct;
  62. TrialLabel = struct;
  63. counter = 1;
  64. for k = 1:nSession
  65. % single session behavior event table
  66. behEvtTbl = behEvtTbls.(sessionNames{k});
  67. uniqueTrials = unique(behEvtTbl.Trial);
  68. nTrial = length(uniqueTrials);
  70. % event index
  71. evtIdx = [];
  72. evtIdx.TrialStart = contains(behEvtTbl.Behavior,'TrialStart');
  73. evtIdx.Approach = contains(behEvtTbl.Behavior,'Approach');
  74. evtIdx.Dig = contains(behEvtTbl.Behavior,'Dig') & contains(behEvtTbl.Status,'START');
  75. evtIdx.Outcome = contains(behEvtTbl.Behavior,'Dig') & contains(behEvtTbl.Status,'STOP');
  76. for i = 1:nTrial
  77. trialIdx = behEvtTbl.Trial == uniqueTrials(i);
  78. if any(trialIdx & evtIdx.Dig) % exclude no dig (decision) trial
  80. % calculate event frames in ca movies
  81. for j = 1:nMarker
  82. markerIdx = trialIdx & evtIdx.(markerName{j});
  83. markerIdx = find(markerIdx,1,'last'); % keep last approach
  84. markerFrame = behEvtTbl.caFrame(markerIdx);
  85. EvtFrame.(markerName{j})(counter,1) = markerFrame;
  86. end
  88. TrialLabel.CurrRwd(counter,1) = any(contains(behEvtTbl.Behavior(trialIdx),'Eat'));
  89. TrialLabel.Trial(counter,1) = i;
  90. TrialLabel.Session(counter,1) = sessionNames(k);
  91. counter = counter+1;
  92. end
  93. end
  94. end
  95. TrialLabel.PriorRwd = [true;TrialLabel.CurrRwd(1:end-1)]; % first trial, true for prior reward
  97. %% calcium activity organized by nNeuron x tWin x nWin x nTrial
  98. winName = {'preSta','posSta','preApp','posApp','preDec','posDec','preOut','posOut'};
  99. nWin = length(winName);
  100. totalTrial = length(TrialLabel.Trial);
  101. caA = zeros(nNeuron,tWin,nWin,totalTrial); % ca signal array
  103. for i = 1:totalTrial
  104. for j = 1:nMarker
  105. caFrame = EvtFrame.(markerName{j})(i);
  106. caA(:,:,2*j-1,i) = sigN(caFrame-tWin : caFrame-1,:)';
  107. caA(:,:,2*j,i) = sigN(caFrame : caFrame+tWin-1,:)';
  108. end
  109. end
  111. % interpolate caA to 10Hz
  112. xq = linspace(1,tWin,round(tau*10));
  113. tWinIn = length(xq);
  114. caL = reshape(permute(caA,[2 1 3 4]),tWin,nNeuron*nWin*totalTrial);
  115. caL = interp1(1:tWin,caL,xq);
  116. caA = permute(reshape(caL,[tWinIn nNeuron nWin totalTrial]),[2 1 3 4]); % [nNeuron,tWin,nWin,nTrial]
  118. %% output structure
  119. sigArray.caA = caA;
  120. sigArray.dimension = {'neuron','framePerWindow','eventWindow','trial'};
  121. sigArray.TrialLabel = TrialLabel;
  122. sigArray.winName = winName;
  123. sigArray.winDurationSec = tau;
  124. sigArray.fpsOrigin = fps;
  125. sigArray.fps = 10;
  127. end

periEventSigArray.m at commit 843e8d0, under MIT · at the source

Overview

Authors: Shaorong Ma1, Kuan Hong Wang2, Yi Zuo1
ORCID iDs: Shaorong Ma, Kuan Hong Wang, Yi Zuo
  1. Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz,Santa Cruz, CA USA
  2. Department of Neuroscience, University of Rochester Medical Center,Rochester, NY USA
Institutions: University of California, Santa Cruz (United States); University of Rochester Medicine (United States)
Journal: Nature communications, volume 17, issue 1, article 5791
Dates: received 9 March 2026; accepted 7 April 2026; published online 27 April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41467-026-72221-1 · PMID 42045196 · PMCID PMC13332065 · OpenAlex W7155882386
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: mouse (organism)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Evoked potentials, Connectivity, Machine learning, fMRI & imaging
Keywords: Neural circuits, Stress and resilience
MeSH: Cerebral Cortex*, Cognition*, Prefrontal Cortex*, Stress, Psychological*, Animals, Attention, Cognitive Enhancement, Cognitive Flexibility, Decision Making, Male, Mice, Mice, Inbred C57BL, Neural Pathways, Neurons, Optogenetics (* major topic)
Topic: Stress Responses and Cortisol (Behavioral Neuroscience, Neuroscience), according to OpenAlex
Funding: National Institute of Mental Health (R01MH127737, R01MH136381); National Institute on Aging (R01AG071787, U24AG072701); Max Planck Society (fellowship)
Citations: not cited yet (Europe PMC); 59 references in the paper

Abstract

Cognitive rigidity often follows chronic stress and is prevalent in stress-related psychiatric disorders, yet the underlying neural circuit mechanisms remain unclear. Using attentional set-shifting tasks (AST) in mice, we identified projection from the anterior insular cortex to the medial prefrontal cortex (aIC→mPFC) as key regulators of adaptive decision-making. The aIC→mPFC neurons show heightened activity following incorrect, but not correct, trials. This elevated activity persists into subsequent trials, providing a salience signal that enhances mPFC outcome-dependent updating and promotes convergence of neural activity patterns across trials. Optogenetic manipulation of aIC→mPFC projections during the pre-decision phase disrupts mPFC updating and impairs AST performance. Moreover, chronic stress disrupts the outcome-dependence of aIC activity and impairs cognitive flexibility. Crucially, selectively reinforcing aIC→mPFC activity after incorrect trials via optogenetics enhances mPFC updating, improves neural activity convergence across trials, and restores cognitive flexibility in stressed mice. These findings revealed a previously unrecognized role of the aIC→mPFC circuit in linking trial outcomes to adaptive decision-making and identified this pathway as a promising target for treating stress-induced cognitive rigidity.

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

Repository

Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.

ZuoLabUCSC/Targeting-insulo-frontal-pathway-to-reduce-stress-evoked-cognitive-rigidity

License: MIT
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 843e8d01c2273bb10213a8f45a2b51aa6adf58da, 19 March 2026
Languages: MATLAB (8)
Size: 20 files, 8 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (3 files)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
10 files
At the source: github.com/ZuoLabUCSC/Targeting-insulo-frontal-pathway-to-reduce-stress-evoked-cognitive-rigidity

Code availability

All custom code used in this study is available at https://github.com/ZuoLabUCSC/Targeting-insulo-frontal-pathway-to-reduce-stress-evoked-cognitive-rigidity.

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

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;
  • 8 scripts, each with its path and the digest of its content;
  • 5 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • 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

Datasets cited

Data availability

Source Data includes all plotted data in individual Excel sheets and is provided with this paper. Source data are provided with this paper.

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

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 2 keywords, 15 MeSH terms, 3 funders, 58 references.

Cite

This paper

Ma, S., Wang, K. H., & Zuo, Y. (2026). Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity. Nature communications, 17(1), 5791. https://doi.org/10.1038/s41467-026-72221-1

BibTeX

@article{ma2026targeting,
author = {Ma, Shaorong and Wang, Kuan Hong and Zuo, Yi},
title = {{Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity}},
journal = {Nature communications},
year = {2026},
month = apr,
volume = {17},
number = {1},
pages = {5791},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-72221-1},
url = {https://doi.org/10.1038/s41467-026-72221-1},
pmid = {42045196},
pmcid = {PMC13332065}
}

RIS

TY - JOUR
AU - Ma, Shaorong
AU - Wang, Kuan Hong
AU - Zuo, Yi
TI - Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/04/27
VL - 17
IS - 1
SP - 5791
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-72221-1
UR - https://doi.org/10.1038/s41467-026-72221-1
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s41467-026-72221-1",
"type": "article-journal",
"title": "Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity",
"container-title": "Nature communications",
"author": [
{
"family": "Ma",
"given": "Shaorong"
},
{
"family": "Wang",
"given": "Kuan Hong"
},
{
"family": "Zuo",
"given": "Yi"
}
],
"container-title-short": "Nat Commun",
"volume": "17",
"issue": "1",
"page": "5791",
"DOI": "10.1038/s41467-026-72221-1",
"PMID": "42045196",
"PMCID": "PMC13332065",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s41467-026-72221-1",
"language": "en",
"issued": {
"date-parts": [
[
2026,
4,
27
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1371/journal.pbio.3003738 [code]
Altered salience network structure-function integration underlies the decline in cognitive flexibility during aging.
Journal: PLoS biology
In common: Statistics and Machine Learning Toolbox, 5 references
[2] doi:10.1162/imag.a.1149
An implanted lennula approach to measure neural Ca&lt;sup&gt;2+&lt;/sup&gt; responses in the awake marmoset visual cortex.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: 1 reference, author Kuan Hong Wang
[3] doi:10.1523/eneuro.0441-25.2026
Adolescent Social Isolation Induces Persistent Impairments in Emotional Discrimination and Helping Behavior.
Journal: eNeuro
In common: mouse, author Yi Zuo
[4] doi:10.1038/s41386-026-02483-2 [code]
Long-term effects of adolescent risperidone treatment on the mouse cortex.
Journal: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
In common: mouse, author Kuan Hong Wang
[5] doi:10.1038/s41398-026-04091-6 [code]
The development of FEDUPP: feeding experimentation device users processing package to assess learning and cognitive flexibility.
Journal: Translational psychiatry
In common: mouse, 3 references
[6] doi:10.1016/j.celrep.2026.117067 [code]
A brain stem circuit integrating reflexive and anticipatory salivation.
Journal: Cell reports
In common: Statistics and Machine Learning Toolbox, mouse, 2 references
[7] doi:10.1038/s41592-026-03154-2 [code]
Simultaneous single-cell calcium imaging of neuronal population activity and brain-wide BOLD fMRI.
Journal: Nature methods
In common: Statistics and Machine Learning Toolbox, mouse, 2 references
[8] doi:10.1016/j.neuron.2026.07.016 [code]
Inferring brain-wide interactions using data-constrained recurrent neural network models.
Journal: Neuron
In common: Statistics and Machine Learning Toolbox, mouse, 2 references
[9] doi:10.1016/j.celrep.2026.117456 [code]
Anterior lateral motor cortex enables contextual decision-making via dynamic reconfiguration of local circuits.
Journal: Cell reports
In common: Statistics and Machine Learning Toolbox, mouse, 2 references
[10] doi:10.1038/s42003-026-10156-5 [code]
Brain-heart interactions in late-onset major depressive disorder revealed by multimodal HRV-driven fMRI.
Journal: Communications biology
In common: 3 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.