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Functional connectivity dynamics of monoaminergic circuits related to fatigue in multiple sclerosis.

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Paper

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The authors' code

Shell · 4 lines · 116 B · GPL-3.0

  1. #!/bin/bash
  2. for filename in crash-*.pklz; do
  3. nipypecli crash "$filename" > "$(basename "$filename" .txt).txt"
  4. done

crashes_to_text.sh at commit f83700a, under GPL-3.0 · at the source

Overview

Authors: Marloes D A Bet1, Birgit Helmlinger2, Tommy A A Broeders1, Stefanie M C Hechenberger2,3, Christian G Tinauer2, Stefan Ropele2, Frederik Barkhof4,5, Michael Khalil2, Christian Enzinger2, Linda Douw6,7, Menno M Schoonheim1, Daniela T Pinter2
ORCID iDs: Marloes D A Bet, Frederik Barkhof
  1. MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
  2. Department of Neurology, Medical University of Graz, Graz, Austria
  3. Department of Oncology, Medical University of Graz, Graz, Austria
  4. MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
  5. Queen Square Institute of Neurology and UCL Hawkes Institute, University College London, London, UK
  6. Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Cancer Center Amsterdam, Amsterdam University Medical Centers Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  7. Amsterdam Neuroscience, Systems & Network Neuroscience, Amsterdam, The Netherlands
Institutions: Amsterdam Neuroscience (Netherlands); Vrije Universiteit Amsterdam (Netherlands); Amsterdam UMC Location Vrije Universiteit Amsterdam (Netherlands); Medical University of Graz (Austria); UCL Queen Square Institute of Neurology (United Kingdom); University College London (United Kingdom); Amsterdam University Medical Centers (Netherlands); Cancer Center Amsterdam (Netherlands)
Journal: Journal of neurology, volume 273, issue 6, article 354
Dates: received 29 January 2026; accepted 13 May 2026; published online 2 June 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1007/s00415-026-13876-0 · PMID 42228097 · PMCID PMC13230267 · OpenAlex W7163132707
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: fMRI (modality), PET / SPECT (modality), human (organism), multiple sclerosis (population), systems (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Connectivity, fMRI & imaging
Keywords: Fatigue, Multiple sclerosis, Functional MRI, Networks, Monoamines
MeSH: Biogenic Monoamines*, Brain*, Connectome*, Fatigue*, Multiple Sclerosis*, Nerve Net*, Adult, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Positron-Emission Tomography (* major topic)
Topic: Multiple Sclerosis Research Studies (Pathology and Forensic Medicine, Medicine), according to OpenAlex
Citations: not cited yet (Europe PMC); 40 references in the paper

Abstract

Introduction: Monoaminergic neurotransmitters help regulate the interplay between the central nervous system and the immune system. Aberrant monoaminergic functional connectivity is presumably involved in MS-related fatigue, but mechanisms remain unclear.

Aim: To investigate how static and dynamic functional connectivity of monoaminergic circuits relate to fatigue in MS.

Methods: 60 healthy controls (HC) and 217 people with MS (pwMS) completed the Fatigue Scale for Motor and Cognitive Functions (FSMC) and underwent functional brain MRI. Brain regions were assigned to resting-state networks. Additionally, PET-derived receptor/transporter density atlases determined assignment to monoaminergic circuits (5-HT1a/5-HT2a/5-HTT/ D1/D2/DAT/NAT). Per monoaminergic circuit, we compared the frequency of switching between networks (flexibility) and the total number of networks switched to (promiscuity), between HC and pwMS with no fatigue (FSMC < 43), mild/moderate fatigue (43 ≤ FSMC < 63), or severe fatigue (FSMC ≥ 63). For circuits showing flexibility differences, we also compared rates of synchronous (cohesion) and independent switches (disjointedness).

Results: Global flexibility was higher in severely fatigued pwMS compared to non-fatigued pwMS (p = 0.025) and HC (p = 0.016). In line, global cohesion was higher in severely fatigued pwMS compared to non-fatigued pwMS (p = 0.022) and HC (p = 0.017). Compared to HC, 5-HT1a circuit flexibility (p = 0.048) and cohesion (p = 0.031) were higher in severely fatigued pwMS. Static FC showed significant group differences for the 5-HTT, D1, and D2/DAT circuits, but no significant pairwise contrasts.

Conclusion: Fatigued pwMS show more dynamic functional connectivity, both globally and in the inhibitory serotonergic receptor circuit. Unstable global and serotonergic dynamics likely raise energy expenditure in pwMS and therefore may underlie MS-related fatigue.

Supplementary Information: The online version contains supplementary material available at 10.1007/s00415-026-13876-0.

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

Repositories

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

neuroimaging-mug/ms-volest

License: GPL-3.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: f83700a55888e3da3c5409a384f31cb9b29bcbd8, 9 November 2023
Languages: Python (9), Shell (2)
Size: 19 files, 11 scripts
Software Heritage: archived
Found in: the text, “Preprocessing”
Holds: README, license file, environment (requirements.txt)
Not found: CITATION.cff, tests, continuous integration, documentation
Tools: FSL (2 files), Nipype (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
13 files
At the source: github.com/neuroimaging-mug/ms-volest

taabroeders/Recon_Dyn_MS

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 1ec1cc113823e7f27ea8ba87a1c72171031c6ea2, 7 September 2021
Languages: MATLAB (2)
Size: 2 files, 2 scripts
Software Heritage: not archived
Found in: the text, “Reconfiguration dynamics”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
2 files, not copied: shown from their source

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At the source: github.com/taabroeders/Recon_Dyn_MS

marloesbet/fatigue_dynamics

License: none: the authors keep all their rights
State: the link is dead, verified on 27 September 2026
Evidence: found in the paper
Software Heritage: not archived
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link is dead
  • 27 September 2026: the link is dead
At the source: github.com/marloesbet/fatigue_dynamics

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:

  • 3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 13 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

Data collected as part of this study are available only upon reasonable request. Scripts for pre- and post-processing of MR images are openly available through https://github.com/marloesbet/fatigue_dynamics.

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 2, 28 September 2026

  • Publisher: — → Springer Science+Business Media

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 12 authors, 5 keywords, 14 MeSH terms, 37 references.

Cite

This paper

Bet, M. D. A., Helmlinger, B., Broeders, T. A. A., Hechenberger, S. M. C., Tinauer, C. G., Ropele, S., Barkhof, F., Khalil, M., Enzinger, C., Douw, L., Schoonheim, M. M., & Pinter, D. T. (2026). Functional connectivity dynamics of monoaminergic circuits related to fatigue in multiple sclerosis. Journal of neurology, 273(6), 354. https://doi.org/10.1007/s00415-026-13876-0

BibTeX

@article{bet2026functional,
author = {Bet, Marloes D A and Helmlinger, Birgit and Broeders, Tommy A A and Hechenberger, Stefanie M C and Tinauer, Christian G and Ropele, Stefan and Barkhof, Frederik and Khalil, Michael and Enzinger, Christian and Douw, Linda and Schoonheim, Menno M and Pinter, Daniela T},
title = {{Functional connectivity dynamics of monoaminergic circuits related to fatigue in multiple sclerosis}},
journal = {Journal of neurology},
year = {2026},
month = jun,
volume = {273},
number = {6},
pages = {354},
publisher = {Springer Science+Business Media},
issn = {0340-5354},
doi = {10.1007/s00415-026-13876-0},
url = {https://doi.org/10.1007/s00415-026-13876-0},
pmid = {42228097},
pmcid = {PMC13230267}
}

RIS

TY - JOUR
AU - Bet, Marloes D A
AU - Helmlinger, Birgit
AU - Broeders, Tommy A A
AU - Hechenberger, Stefanie M C
AU - Tinauer, Christian G
AU - Ropele, Stefan
AU - Barkhof, Frederik
AU - Khalil, Michael
AU - Enzinger, Christian
AU - Douw, Linda
AU - Schoonheim, Menno M
AU - Pinter, Daniela T
TI - Functional connectivity dynamics of monoaminergic circuits related to fatigue in multiple sclerosis
T2 - Journal of neurology
J2 - J Neurol
PY - 2026
DA - 2026/06/02
VL - 273
IS - 6
SP - 354
SN - 0340-5354
PB - Springer Science+Business Media
DO - 10.1007/s00415-026-13876-0
UR - https://doi.org/10.1007/s00415-026-13876-0
LA - en
ER -

CSL-JSON

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