Related Experiment Video

Updated: Feb 12, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
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Disrupted and reorganized connectivity of brain networks in multiple sclerosis: a systematic review and meta-analysis

Bingyi Qu1,2,3, Siyi Li1,2,3, Hongxi Chen4

  • 1Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, West China Hospital of Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China.

Journal of Neurology
|February 11, 2026
PubMed
Abstract

Insights

Multiple sclerosis (MS) shows widespread brain functional network abnormalities, particularly in the default mode (DMN) and sensorimotor (SMN) networks. These resting-state functional connectivity (rsFC) changes may reflect underlying neuropathology, but were not linked to clinical variables in this meta-analysis.

Area of Science:

  • Neuroimaging
  • Systems Neuroscience
  • Clinical Neurology

Background:

  • Large-scale brain functional network abnormalities are linked to multiple sclerosis (MS) and its clinical impairments.
  • Existing findings on these abnormalities are heterogeneous due to variations in methodology and sample size.

Purpose of the Study:

  • To meta-analyze resting-state functional connectivity (rsFC) changes in major brain networks in MS patients compared to healthy controls (HCs).
  • To assess heterogeneity and explore correlations between rsFC alterations and clinical variables in MS.

Main Methods:

  • A meta-analysis of 25 resting-state functional magnetic resonance imaging (rsfMRI) studies involving 1,524 MS patients and 886 HCs.
  • Independent component analysis (ICA) was used to evaluate rsFC in default mode (DMN), sensorimotor (SMN), salience (SN), and visual (VN) networks.
  • Anisotropic effect size seed mapping (AES-SDM) software and meta-regression were employed.

Main Results:

  • MS patients exhibited increased rsFC in parts of the DMN, SMN, and SN compared to HCs.
  • Hypoconnectivity was observed in core regions of the DMN, SMN, VN, and SN in MS patients.
  • Meta-regression analysis found no significant correlation between altered rsFC and clinical variables like age or disease duration.

Conclusions:

  • This meta-analysis reveals widespread and complex rsFC abnormalities across multiple neural networks in MS.
  • These disruptions and reorganizations in functional connectivity likely represent intrinsic neuropathological alterations in MS.
  • The findings enhance understanding of the pathophysiological mechanisms underlying functional abnormalities in MS.
Keywords:
Functional connectivityIndependent component analysisMeta-analysisMultiple sclerosisResting-state fMRI

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