Background: Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks associated with fatigue. Methods: 38 MS patients with and 21 without fatigue were included in the study. Association between fatigue and lesion locations was investigated using voxel-lesion symptom mapping and lesion connectivity using lesion network mapping. The findings were tested in two independent datasets, including (1) MS patients scanned using resting-state functional connectivity MRI (rs-fcMRI) (n = 199) and (2) individuals with stroke lesions (n = 85). Results: There were no specific anatomical MS lesion locations significantly associated with fatigue, but lesions associated with fatigue were connected to a common network with peak positive connectivity to the right premotor cortex and negative connectivity to the left temporal pole (pFWE < 0.05). Of the two identified network nodes, connectivity from the premotor cortex to multiple other brain regions was significantly associated with MS fatigue severity in the independent dataset of MS patients (p < 0.05). The MS fatigue network was also reproducible in poststroke fatigue (spatial correlation r = 0.57, permutation test p = 0.02), again showing that lesion connectivity to the premotor cortex, but not the temporal pole, was associated with fatigue (p = 0.04). Conclusions: Our results show that fatigue in MS localizes to a brain network, lending insight into the neural substrates of fatigue.

Network Localization of Fatigue in Multiple Sclerosis

Tommasin, Silvia;
2026-01-01

Abstract

Background: Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks associated with fatigue. Methods: 38 MS patients with and 21 without fatigue were included in the study. Association between fatigue and lesion locations was investigated using voxel-lesion symptom mapping and lesion connectivity using lesion network mapping. The findings were tested in two independent datasets, including (1) MS patients scanned using resting-state functional connectivity MRI (rs-fcMRI) (n = 199) and (2) individuals with stroke lesions (n = 85). Results: There were no specific anatomical MS lesion locations significantly associated with fatigue, but lesions associated with fatigue were connected to a common network with peak positive connectivity to the right premotor cortex and negative connectivity to the left temporal pole (pFWE < 0.05). Of the two identified network nodes, connectivity from the premotor cortex to multiple other brain regions was significantly associated with MS fatigue severity in the independent dataset of MS patients (p < 0.05). The MS fatigue network was also reproducible in poststroke fatigue (spatial correlation r = 0.57, permutation test p = 0.02), again showing that lesion connectivity to the premotor cortex, but not the temporal pole, was associated with fatigue (p = 0.04). Conclusions: Our results show that fatigue in MS localizes to a brain network, lending insight into the neural substrates of fatigue.
2026
fatigue
lesion network mapping
multiple sclerosis
stroke
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14245/18221
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