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Functional connectivity predictors and mechanisms of symptom change in functional neurological disorder.

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The authors' code

MATLAB · 103 lines · 2.8 KB · no license

  1. clear;clc;
  2. addpath( 'scripts_matlab');
  4. subjects_file_list='subjects.txt'; %txt file with subject IDs (1 per line)
  5. mask_file='GM_mask_3mm.nii.gz'; %grey matter mask in the resolution of your data
  6. atlas_file='Yeo7_3mm.nii.gz'; %network parcellation map
  7. data_path='data3mm'; % a folder with processed fmri files (one per individual)
  8. out_path='results/intgr_segr_3mm/'; %output folder
  9. apply_fisher=0;
  10. block_sz=10000;
  13. %%%%%%%%%%%%%%% Code starts here %%%%%%%%%%%%%%%%%%
  15. %Read subjects filenames from txt file
  16. fid = fopen(subjects_file_list);
  17. tline = fgetl(fid);
  18. subjects={}; num_subjects=0;
  19. while ischar(tline)
  20. num_subjects=num_subjects+1;
  21. subjects{num_subjects}=tline;
  22. tline = fgetl(fid);
  23. end
  24. fclose(fid);
  26. %Read mask
  27. [hdr mask]=read_nii(mask_file);
  29. %Read atlas
  30. [hdra atlas]=read_nii(atlas_file);
  31. atlas=atlas.*(mask>0); %apply mask to atlas
  32. atlas=reshape(atlas,[],1); %reshape to 1d
  33. indx_mask=find(atlas>0); %find gm voxels
  34. num_voxels=length(indx_mask);
  35. atlas=atlas(indx_mask);
  36. num_rois_atlas=max(atlas(:));
  38. %Create output directories
  39. if exist([out_path '/segregation'])==0
  40. mkdir([out_path '/segregation']);
  41. end
  43. if exist([out_path '/integration'])==0
  44. mkdir([out_path '/integration']);
  45. end
  47. %For each file
  48. files=strsplit(ls([data_path '/*.nii.gz'])); files(end)=[];
  49. seg_all = zeros(1,num_voxels,num_subjects);
  50. int_all = zeros(1,num_voxels,num_subjects);
  51. for i=1:num_subjects %length(files)
  53. %read fmri
  54. fprintf('[%.3d/%.3d] %s\n',i,num_subjects,subjects{i});
  55. [hdri fmri]=read_nii([ data_path '/' subjects{i} '.nii.gz']);
  56. fmri=reshape(fmri,[],size(fmri,4)); % convert fmri to 2d matrix
  57. fmri=fmri(indx_mask,:); %apply mask
  59. %Comptue integration, segregation
  60. segregation=zeros(1,num_voxels);
  61. integration=zeros(1,num_voxels);
  63. %for each roi
  64. for a=1:num_rois_atlas
  65. fprintf(' Network %d\n',a);
  66. sgr=find(atlas==a);
  67. intr=setdiff(1:num_voxels,sgr);
  68. num_blocks=ceil(length(sgr)./block_sz);
  69. for b=1:num_blocks
  70. sv=((b-1)*block_sz)+1;
  71. ev=sv+block_sz-1;
  72. if ev>length(sgr)
  73. ev=length(sgr);
  74. end
  76. fc=corr(fmri(sgr(sv:ev),:)',fmri');
  77. fc(find(fc<0))=0;
  78. if (apply_fisher==1)
  79. fc= 0.5 * log( ( 1 + fc)./( 1 - fc) ); %fisher
  80. end
  82. segregation(sgr(sv:ev))=nansum(fc(:,sgr)')-1;
  83. integration(sgr(sv:ev))=nansum(fc(:,intr)');
  84. clear fc;
  85. end
  86. clear sgr intr;
  87. end
  89. int_all(:,:,i) = integration;
  90. seg_all(:,:,i) = segregation;
  92. img=zeros(size(mask));
  93. img(indx_mask)=segregation;
  94. save_nii(hdr,img,[out_path '/segregation/' subjects{i} '.nii.gz']);
  96. img=zeros(size(mask));
  97. img(indx_mask)=integration;
  98. save_nii(hdr,img,[out_path '/integration/' subjects{i} '.nii.gz']);
  100. end
  102. save([out_path '/integration_voxelLevel.mat'],'int_all');
  103. save([out_path '/segregation_voxelLevel.mat'],'seg_all');

IntegrationSegregation.m at commit e78dbd4, no license · at the source

Overview

Authors: Christiana Westlin1,2,3, Cristina Bleier1,3, Andrew J Guthrie1,3, Sara A Finkelstein1, Julie Maggio4, Jessica Ranford5, Julie MacLean5, Ellen Godena1, Daniel Millstein1,2, Jennifer Freeburn6, Caitlin Adams1,2, Christopher D Stephen1, Ibai Diez7,8,9, David L Perez1,2,3,10
ORCID iDs: Christiana Westlin, Christopher D Stephen, David L Perez
  1. Mass General Brigham Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
  2. Mass General Brigham Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
  3. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
  4. Department of Physical Therapy, Massachusetts General Hospital, Boston, MA 02114, USA
  5. Department of Occupational Therapy, Massachusetts General Hospital, Boston, MA 02114, USA
  6. Department of Speech, Language, and Swallowing Disorders, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
  7. Computational Neuroimaging Lab, Biobizkaia Health Research Institute, Barakaldo 48903, Spain
  8. Ikerbasque Basque Foundation for Science, Bilbao 48903, Spain
  9. Center for Inflammation Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 20114, USA
  10. Mass General Brigham Departments of Neurology and Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 20115, USA
Institutions: Harvard University (United States); Massachusetts General Hospital (United States); Athinoula A. Martinos Center for Biomedical Imaging (United States); Mass General Brigham (United States); Ikerbasque (Spain); Brigham and Women's Hospital (United States)
Journal: Brain communications, volume 8, issue 4, article fcag290
Dates: received 13 February 2026; accepted 9 July 2026; published online 22 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag290 · PMID 42553752 · PMCID PMC13435623 · OpenAlex W7170063802
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: fMRI (modality), human (organism), epilepsy (population), clinical / translational (subfield)
Methods: Spectral & time-frequency, Statistics, Connectivity, fMRI & imaging
Keywords: functional movement disorder, functional seizures, fMRI, graph theory, outcomes
Topic: Psychosomatic Disorders and Their Treatments (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: National Institute of Mental Health (R01MH125802)
Citations: not cited yet (Europe PMC); 65 references in the paper

Abstract

Clinical trajectories in patients with functional neurological disorder (FND) are variable, and the neural mechanisms underlying this heterogeneity remain poorly understood. This longitudinal brain imaging study examined resting-state functional connectivity predictors and mechanisms of symptom change in FND. Thirty-two adults with FND (motor and/or seizure phenotypes) completed baseline questionnaires and functional MRI (fMRI), followed by naturalistic treatment for 6.8 ± 0.8 months. All participants completed follow-up questionnaires; 28 completed follow-up fMRI. At each timepoint, three graph-theory network metrics of resting-state functional connectivity were computed: whole-brain weighted-degree (centrality), cortical integration (between-network connectivity), and cortical segregation (within-network connectivity). All analyses adjusted for age, sex, antidepressants, head motion, time between sessions and baseline score of interest, with cluster-wise correction. Results were contextualized against 50 age-, sex-, and head motion-matched healthy controls (HCs). Based on patient-reported Clinical Global Impression of Improvement ratings, 59.4% improved, 31.3% were unchanged, and 9.3% worsened. Core FND symptom (i.e. Screening for Somatoform Symptoms-7 Subscale for Conversion Disorder) and non-core physical symptom (Patient Health Questionnaire-15) scores showed variable trajectories, with no group-level changes. For whole-brain weighted-degree analyses, baseline centrality in right middle frontal, precentral, and left cerebellar regions was positively associated with core FND symptom change; longitudinally, centrality decreases in right precentral, superior parietal, lateral occipital, and cerebellar regions were associated with symptom improvement. For cortical integration analyses, baseline between-network connectivity in ventral attention, frontoparietal, and default mode network regions was positively associated with core FND symptom change; longitudinally, decreases in between-network connectivity for regions of these same networks were associated with symptom improvement. For cortical segregation analyses, baseline within-network connectivity in frontoparietal network regions was positively associated with core FND symptom change; no regions showed longitudinal segregation changes associated with symptom change. The right anterior insula emerged as a convergent site across baseline and longitudinal integration analyses, with the most improved participants showing elevated baseline between-network connectivity relative to HCs that normalized at follow-up. More modest functional connectivity associations were observed with non-core physical symptom change, spanning baseline within-network connectivity in dorsal attention network regions and longitudinal between-network connectivity increases in visual network regions. Findings remained significant adjusting for FND phenotype, although several attenuated when accounting for baseline affective symptoms or trauma burden. In conclusion, this study identified baseline and longitudinal resting-state functional connectivity features linked to symptom change in FND, highlighting the potential of large-scale network interactions as prognostic markers and providing mechanistic insights that set the stage for novel, biologically informed interventions.

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

Repository

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

FND-RG-Lab/NetworkIntegrationSegregation

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: e78dbd4edb187de5f1cb5493f437c51846049c46, 28 March 2025
Languages: MATLAB (5)
Size: 5 files, 5 scripts
Software Heritage: not archived
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Tools for NIfTI and ANALYZE image (MATLAB) (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
5 files
At the source: github.com/FND-RG-Lab/NetworkIntegrationSegregation

The paper's code and data availability statement is in the Data section.

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;
  • 5 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.

Data availability

For qualified researchers, de-identified data pertaining only to study results can be made available following local IRB approval upon reasonable request. Analysis code can be found in the following GitHub repository: https://github.com/FND-RG-Lab/NetworkIntegrationSegregation.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 14 authors, 5 keywords, 1 funder, 65 references.

Cite

This paper

Westlin, C., Bleier, C., Guthrie, A. J., Finkelstein, S. A., Maggio, J., Ranford, J., MacLean, J., Godena, E., Millstein, D., Freeburn, J., Adams, C., Stephen, C. D., Diez, I., & Perez, D. L. (2026). Functional connectivity predictors and mechanisms of symptom change in functional neurological disorder. Brain communications, 8(4), fcag290. https://doi.org/10.1093/braincomms/fcag290

BibTeX

@article{westlin2026functional,
author = {Westlin, Christiana and Bleier, Cristina and Guthrie, Andrew J and Finkelstein, Sara A and Maggio, Julie and Ranford, Jessica and MacLean, Julie and Godena, Ellen and Millstein, Daniel and Freeburn, Jennifer and Adams, Caitlin and Stephen, Christopher D and Diez, Ibai and Perez, David L},
title = {{Functional connectivity predictors and mechanisms of symptom change in functional neurological disorder}},
journal = {Brain communications},
year = {2026},
month = jul,
volume = {8},
number = {4},
pages = {fcag290},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag290},
url = {https://doi.org/10.1093/braincomms/fcag290},
pmid = {42553752},
pmcid = {PMC13435623}
}

RIS

TY - JOUR
AU - Westlin, Christiana
AU - Bleier, Cristina
AU - Guthrie, Andrew J
AU - Finkelstein, Sara A
AU - Maggio, Julie
AU - Ranford, Jessica
AU - MacLean, Julie
AU - Godena, Ellen
AU - Millstein, Daniel
AU - Freeburn, Jennifer
AU - Adams, Caitlin
AU - Stephen, Christopher D
AU - Diez, Ibai
AU - Perez, David L
TI - Functional connectivity predictors and mechanisms of symptom change in functional neurological disorder
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/07/22
VL - 8
IS - 4
SP - fcag290
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag290
UR - https://doi.org/10.1093/braincomms/fcag290
LA - en
ER -

CSL-JSON

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"id": "10.1093/braincomms/fcag290",
"type": "article-journal",
"title": "Functional connectivity predictors and mechanisms of symptom change in functional neurological disorder",
"container-title": "Brain communications",
"author": [
{
"family": "Westlin",
"given": "Christiana"
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{
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{
"family": "Finkelstein",
"given": "Sara A"
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{
"family": "Maggio",
"given": "Julie"
},
{
"family": "Ranford",
"given": "Jessica"
},
{
"family": "MacLean",
"given": "Julie"
},
{
"family": "Godena",
"given": "Ellen"
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{
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"given": "Daniel"
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{
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"container-title-short": "Brain Commun",
"volume": "8",
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"page": "fcag290",
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"PMID": "42553752",
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"issued": {
"date-parts": [
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