# Time‐Varying Brain Functional Reconfiguration Patterns Associated With Fatigue in Multiple Sclerosis

**Authors:** Stefanie Hechenberger, Tommy A. A. Broeders, Marloes D. A. Bet, Birgit Helmlinger, Christian Tinauer, Stefan Ropele, Bettina Heschl, Sebastian Wurth, Anna Damulina, Michael Khalil, Menno M. Schoonheim, Christian Enzinger, Daniela Pinter

PMC · DOI: 10.1002/hbm.70480 · Human Brain Mapping · 2026-03-08

## TL;DR

The study found that fatigue in multiple sclerosis is linked to unstable brain network communication, especially in the limbic network, which may increase energy demands and worsen fatigue.

## Contribution

The study introduces novel insights into how time-varying brain network reconfigurations are associated with fatigue in multiple sclerosis.

## Key findings

- Higher fatigue in pwMS correlates with increased global promiscuity and disjointedness in brain network reconfigurations.
- Motor fatigue is strongly linked to unstable limbic network reconfigurations, even after controlling for structural brain damage.
- Cognitive fatigue showed no significant associations with brain network reconfigurations in pwMS.

## Abstract

Fatigue affects between 36.5% and 78% of people with multiple sclerosis (pwMS) and significantly impairs daily life. The neurobiological mechanisms underlying fatigue remain poorly understood and information about the time‐varying communication between brain regions and the networks they form may offer new insights into the complex pathology of MS‐related fatigue. Brain regions continuously reconfigure how they communicate within distinct networks (i.e., time‐varying reconfigurations) and aberrant time‐varying reconfigurations may contribute to the perception of fatigue in pwMS. This study aimed to explore if and how time‐varying reconfigurations are associated with fatigue in pwMS. In this cross‐sectional study, 155 pwMS (62% female; age = 39 ± 10 years; disease duration = 10 ± 8 years; median EDSS = 1.0 ± 2.0) and 48 healthy controls (HC) (71% female; age = 33 ± 10 years) underwent clinical, neuropsychological, and (resting‐state functional) MRI assessments. Fatigue was evaluated with the “Fatigue Scale for Motor and Cognitive Function”, comprising total, motor, and cognitive fatigue scores. Time‐varying connectivity was derived using a sliding‐window approach, with data‐driven assignment of brain regions to one of eight resting‐state networks for each window. Promiscuity (dispersion of reconfigurations), flexibility (frequency of reconfigurations), cohesion (joint reconfigurations), and disjointedness (independent reconfigurations) described the time‐varying reconfigurations of the whole brain and its networks. Among pwMS, 57% reported experiencing at least mild total fatigue (motor: 60%, cognitive: 57%). Higher total fatigue was correlated with greater global promiscuity (r = 0.21, p = 0.032) and disjointedness (r = 0.24, p = 0.008). Similarly, higher motor fatigue was associated with greater global promiscuity (r = 0.25, p = 0.008), flexibility (r = 0.21, p = 0.032), and disjointedness (r = 0.28, p < 0.001). The associations with disjointedness remained significant even after controlling for demographics, clinical measures, and structural brain damage, such as lesion load and atrophy (total fatigue: adj.R
2 = 0.23, β = 0.17, p = 0.033; motor fatigue: adj.R
2 = 0.38, β = 0.16, p = 0.026). Network‐level analyses in pwMS revealed that higher total (r = 0.25, p = 0.016) and motor (r = 0.25, p = 0.016) fatigue were associated with greater limbic network promiscuity. No significant correlations were found for cognitive fatigue in pwMS, or for total, motor, and cognitive fatigue in HC (all p > 0.05). Elevated levels of fatigue, particularly motor fatigue, in pwMS were linked to more unstable network reconfigurations, particularly of regions in the limbic network, possibly reflecting dysfunctional reward processing. More frequent dispersion requires more energy and may therefore contribute to increased fatigue.

This project was pre‐registered at ClinicalTrials.gov (registration number: NCT04892134)

Fatigue in people with multiple sclerosis has been associated with more unstable and dispersed patterns of brain network reconfiguration, particularly within the limbic network. These findings suggest that inefficient and energetically demanding time‐varying communication among brain regions may contribute to the subjective experience of fatigue.

## Linked entities

- **Diseases:** multiple sclerosis (MONDO:0005301)

## Full-text entities

- **Genes:** SLC6A2 (solute carrier family 6 member 2) [NCBI Gene 6530] {aka NAT1, NET, NET1, SLC6A5}, SYNM (synemin) [NCBI Gene 23336] {aka DMN, SYN}
- **Diseases:** pwMS (MESH:C000719191), Depression (MESH:D003866), mental exhaustion (MESH:D006359), MS (MESH:D009103), impaired cognition (MESH:D003072), clinical disability (MESH:D009069), DMT (OMIM:603855), impaired concentration, attention, or memory (MESH:D008569), CIS (MESH:D059466), brain damage (MESH:D001925), relapse remitting multiple sclerosis (MESH:D020529), white matter lesion (MESH:D056784), Lesion (MESH:D009059), Fatigue (MESH:D005221), chronic fatigue (MESH:D015673), damage (MESH:D020263), isolated syndrome (MESH:C565377), inflammation (MESH:D007249), primary progressive multiple sclerosis (MESH:D020528), HC (MESH:D000067329), psychiatric and/or neurological disease (MESH:D001523), atrophy (MESH:D001284), Anxiety (MESH:D001007)
- **Chemicals:** dimethyl fumarate (MESH:D000069462), steroid (MESH:D013256), natalizumab (MESH:D000069442), DMT (-), ocrelizumab (MESH:C533411), siponimod (MESH:C578989), fingolimod (MESH:D000068876), glatiramer (MESH:D000068717)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

63 references — full list in the complete paper: https://tomesphere.com/paper/PMC12968462/full.md

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Source: https://tomesphere.com/paper/PMC12968462