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The role of white matter myelin in structural-functional network coupling.

Code ↔ Paper

3 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 3 matches · 1 of them tie a paragraph to a whole file without given lines: a weak match, whose lines are not tinted
  1. [1] § Data processing › Structural connectivity network reconstruction ↔ matlab/mk_edgescsv_from_mat.m, the whole file · a weak match · score 0.64 · edge length, edge caliber, edge myelin, COMMIT, MTsat, Schaefer · Report a mismatch
  2. [2] § Data processing › Multi-linear modeling ↔ matlab/+models/dominance_interaction.m, lines 2 to 33 · score 0.61 · handle interaction terms, response variable, R2, regression, dominance, models · Report a mismatch
  3. [3] § Data processing › Multi-linear modeling ↔ python/myelinfccoupling/model.py, lines 44 to 167 · score 0.50 · handle interaction terms, incremental, R2, variable, dominance, caliber · Report a mismatch

Paper

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The authors' code

MATLAB · 81 lines · 3.2 KB · GPL-3.0 · 1 match

  1. function mk_edgescsv_from_mat()
  2. % MK_EDGESCSV_FROM_MAT
  3. % Converts NxN connectivity matrices into required .csv file by FC modality
  4. %
  5. % addpath(genpath('matlab'))
  6. % mk_edgescsv_from_mat()
  9. % Setup
  10. ROOTDIR = fileparts(fileparts(mfilename('fullpath')));
  11. DATADIR = [ROOTDIR '/data'];
  12. PARCDIR = [ROOTDIR '/parcellations'];
  13. addpath(genpath(ROOTDIR))
  15. % ----- USER EDIT SECTION ----------------------------------------------
  16. fc_fn = 'fc_BOLDin'; % *** TOGGLE FC NETWORK HERE ***
  18. myelin_fn = 'mtsat'; % edge myelin
  19. caliber_fn = 'commit'; % edge caliber;
  20. length_fn = 'edgelength'; % edge length
  21. parc = 'schaefer-400'; % {'schaefer-200' 'schaefer-400'}
  22. % ----------------------------------------------------------------------
  24. % Load data
  25. loaddir = [DATADIR '/' parc '_group/'];
  26. load([loaddir caliber_fn '.mat'],'Dtg'); caliber_mat=Dtg;
  27. load([loaddir myelin_fn '.mat'],'Dtg'); myelin_mat=Dtg;
  28. load([loaddir length_fn '.mat'],'Dtg'); length_mat=Dtg; % Edge Length
  29. load([loaddir fc_fn '.mat'],'Dtg'); FC_mat=Dtg; % FC
  30. clear Dtg
  32. % Load SAaxis (not actually used here)
  33. % SA_map = readNPY([loaddir 'sa_axis.npy']);
  35. % Set missing values to nan for removal (do for all in case they are different)
  36. caliber_mat(caliber_mat==0)=nan;
  37. myelin_mat(myelin_mat==0)=nan;
  38. length_mat(length_mat==0)=nan;
  40. % load parc info
  41. pinfo = conn_getParcInfo({parc},PARCDIR,'cor'); % structure with parcellation info
  42. Nstx = pinfo.nsub;
  43. Nctx = pinfo.ncor;
  44. Nnode = Nctx + Nstx;
  45. Nntwk = length(pinfo.clabels);
  47. % Yeo RSNs
  48. rsn_idx = nan(Nnode,1);
  49. rsn_labels = cell(Nnode,1); % Nx1 string/cellstr of RSN per node (optional)
  50. for ii=1:Nntwk
  51. rsn_idx(pinfo.cis{ii},1) = ii;
  52. rsn_labels(pinfo.cis{ii}) = pinfo.clabels(ii);
  53. end
  55. % --- Build CSV ---
  56. % lower-triangle edge list (exclude self-edges)
  57. % N = size(FC_mat,1);
  58. N = Nnode;
  59. [i,j] = find(tril(true(N), -1));
  61. edges = table();
  62. edges.i = i;
  63. edges.j = j;
  64. edges.FC = FC_mat(sub2ind([N N], i, j)); % NxN functional connectivity
  65. edges.caliber = caliber_mat(sub2ind([N N], i, j)); % NxN edge caliber
  66. edges.myelin = myelin_mat(sub2ind([N N], i, j)); % NxN edge myelin
  67. edges.length = length_mat(sub2ind([N N], i, j)); % NxN edge length
  69. % Optional RSN columns (recommended if you’ll run RSN-pairs)
  70. if exist('rsn_labels','var') && ~isempty(rsn_labels)
  71. edges.rsn_i = string(rsn_labels(i));
  72. edges.rsn_j = string(rsn_labels(j));
  73. end
  75. % remove rows with any missing values
  76. mask = all(~isnan(edges{:, {'FC','caliber','myelin','length'}}),2);
  77. edges = edges(mask,:);
  79. % Save
  80. writetable(edges, fullfile(DATADIR,['edges_' fc_fn '.csv']));
  81. end

mk_edgescsv_from_mat.m at commit 5af996d, under GPL-3.0 · at the source

Overview

Authors: Mark C Nelson1,2, Wen Da Lu2,3, Ilana R Leppert2, Heather A Hansen1, Christopher D Rowley4, Bratislav Misic1,2, Christine L Tardif1,2,3
ORCID iDs: Mark C Nelson, Christopher D Rowley, Bratislav Misic, Christine L Tardif
  1. Department of Neurology and Neurosurgery, McGill University, Montreal, QC Canada
  2. McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC Canada
  3. Department of Biomedical Engineering, McGill University, Montreal, QC Canada
  4. Department of Physics and Astronomy, McMaster University, Hamilton, ON Canada
Institutions: Montreal Neurological Institute and Hospital (Canada); McGill University (Canada); McMaster University (Canada)
Journal: Communications biology, volume 9, issue 1, article 488
Dates: received 28 August 2025; accepted 24 February 2026; published online 27 March 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s42003-026-09813-6 · PMID 41896361 · PMCID PMC13050329 · OpenAlex W7141733455
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: structural MRI / diffusion (modality), human (organism), cellular / molecular (subfield)
Keywords: Network models, Brain, Myelin biology and repair
MeSH: Brain*, Myelin Sheath*, Nerve Net*, White Matter*, Humans, Magnetic Resonance Imaging, Models, Neurological (* major topic)
Topic: Neurogenesis and neuroplasticity mechanisms (Developmental Neuroscience, Neuroscience), according to OpenAlex
Funding: Killam Trusts; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Gouvernement du Canada | Instituts de Recherche en Santé du Canada | CIHR Skin Research Training Centre
Citations: cited by 4 papers (Europe PMC); 180 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

TardifLab/Modeling-Myelin-FC

License: GPL-3.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 5af996d1ee9ce4190f7d9dbca343c6aa57515dab, 16 June 2026
Languages: MATLAB (16), Python (8)
Size: 77 files, 24 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file, CITATION.cff, environment (python/setup.cfg, python/setup.py)
Not found: tests, continuous integration, documentation
Tools: pandas (4 files), Statistics and Machine Learning Toolbox (2 files), NumPy (2 files), BrainSpace (1 file), statsmodels (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
26 files
At the source: github.com/TardifLab/Modeling-Myelin-FC

Code availability statement

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Read it in the paper: doi.org/10.1038/s42003-026-09813-6.

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 3 keywords, 7 MeSH terms, 4 funders, 165 references.

Cite

This paper

Nelson, M. C., Da Lu, W., Leppert, I. R., Hansen, H. A., Rowley, C. D., Misic, B., & Tardif, C. L. (2026). The role of white matter myelin in structural-functional network coupling. Communications biology, 9(1), 488. https://doi.org/10.1038/s42003-026-09813-6

BibTeX

@article{nelson2026role,
author = {Nelson, Mark C and Da Lu, Wen and Leppert, Ilana R and Hansen, Heather A and Rowley, Christopher D and Misic, Bratislav and Tardif, Christine L},
title = {{The role of white matter myelin in structural-functional network coupling}},
journal = {Communications biology},
year = {2026},
month = mar,
volume = {9},
number = {1},
pages = {488},
publisher = {Nature Publishing Group},
issn = {2399-3642},
doi = {10.1038/s42003-026-09813-6},
url = {https://doi.org/10.1038/s42003-026-09813-6},
pmid = {41896361},
pmcid = {PMC13050329}
}

RIS

TY - JOUR
AU - Nelson, Mark C
AU - Da Lu, Wen
AU - Leppert, Ilana R
AU - Hansen, Heather A
AU - Rowley, Christopher D
AU - Misic, Bratislav
AU - Tardif, Christine L
TI - The role of white matter myelin in structural-functional network coupling
T2 - Communications biology
J2 - Commun Biol
PY - 2026
DA - 2026/03/27
VL - 9
IS - 1
SP - 488
SN - 2399-3642
PB - Nature Publishing Group
DO - 10.1038/s42003-026-09813-6
UR - https://doi.org/10.1038/s42003-026-09813-6
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s42003-026-09813-6",
"type": "article-journal",
"title": "The role of white matter myelin in structural-functional network coupling",
"container-title": "Communications biology",
"author": [
{
"family": "Nelson",
"given": "Mark C"
},
{
"family": "Da Lu",
"given": "Wen"
},
{
"family": "Leppert",
"given": "Ilana R"
},
{
"family": "Hansen",
"given": "Heather A"
},
{
"family": "Rowley",
"given": "Christopher D"
},
{
"family": "Misic",
"given": "Bratislav"
},
{
"family": "Tardif",
"given": "Christine L"
}
],
"container-title-short": "Commun Biol",
"volume": "9",
"issue": "1",
"page": "488",
"DOI": "10.1038/s42003-026-09813-6",
"PMID": "41896361",
"PMCID": "PMC13050329",
"ISSN": "2399-3642",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s42003-026-09813-6",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
27
]
]
}
}

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