ReviewNeuroImage. Clinical2022
The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics.
Review in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
48 citing papers in PubMed, 87 citations in OpenAlex.
- Increased functional network connectivity following cognitive rehabilitation in progressive multiple sclerosis with moderate to severe disabilty: findings from the CogEx study.Journal of neurology · 2026Trial
- Treatment effects of cladribine tablets on data-driven patterns of regional grey matter atrophy in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Trial
- Neurophysiological brain function predicts response to cognitive rehabilitation and mindfulness in multiple sclerosis: a randomized trial.Journal of neurology · 2024Trial
- Functional and Structural Imaging Features of Cognitive Profiles in Multiple Sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2026Observational
- Rethinking prognosis in multiple sclerosis: a multiaxial perspective.Nature reviews. Neurology · 2026Review
- Feasibility of a 12-month, remotely delivered and supported aerobic walking exercise training program for brain and cognition in adults with multiple sclerosis.Journal of neurology · 2026Article
- TMS-EEG signatures of motor network dysfunction in multiple sclerosis.Brain communications · 2026Article
- Cognitive outcomes in multiple sclerosis are shaped by divergent functional connectivity trajectories.Brain communications · 2026Article
- Functional connectivity is linked to symbolic BOLD patterns: Replication, extension, and clinical application of the human "Complexome".Network neuroscience (Cambridge, Mass.) · 2026Article
- Resting-state functional connectivity correlates of gait and turning performance in multiple sclerosis: a multivariate pattern analysis.Scientific reports · 2025Article
- Clinically Relevant Patterns of Co-Fluctuating Structure and Function in Multiple Sclerosis.European journal of neurology · 2025Article
- Navigating a Misty Road: Novel Ways to Study the Impact of Cognition on Driving Performance in Multiple Sclerosis.Brain sciences · 2025Review
- Brain Atrophy and Cognitive Impairment in Primary and Secondary Progressive Multiple Sclerosis Cohort-Similar Progressive MS Phenotype.International journal of molecular sciences · 2025Article
- Krakencoder: a unified brain connectome translation and fusion tool.Nature methods · 2025Article
- Thalamic Network Controllability Predicts Cognitive Impairment in Multiple Sclerosis.Human brain mapping · 2025Article
- Thalamic atrophy in multiple sclerosis is associated with tract disconnection and altered microglia.Acta neuropathologica · 2025Article
- Changes in brain functional connectivity and clinical correlations in neuromyelitis optica spectrum disorder: a longitudinal resting-state fMRI study.European journal of medical research · 2025Article
- Conventional MRI-Based Structural Disconnection and Morphometric Similarity Networks and Their Clinical Correlates in Multiple Sclerosis.Neurology · 2025Article
- Associations between connectivity in functional brain networks and gait speed in older adults with and without multiple sclerosis.Journal of neurology · 2025Article
- Explaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis.Journal of neurology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a "network collapse". After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.