ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2021
Functional brain network organization measured with magnetoencephalography predicts cognitive decline in multiple sclerosis.
Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Neurophysiological brain function predicts response to cognitive rehabilitation and mindfulness in multiple sclerosis: a randomized trial.Journal of neurology · 2024Trial
- Functional Connectivity at Rest and During Cognitive Processing in Multiple Sclerosis: A Pilot Magnetoencephalography Study and Systematic Review.Brain sciences · 2026Article
- Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms.Journal of neural transmission (Vienna, Austria : 1996) · 2024Review
- Hub overload and failure as a final common pathway in neurological brain network disorders.Network neuroscience (Cambridge, Mass.) · 2024Review
- Neurophysiological MEG markers of cognitive impairment and performance validity in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023Article
- Changes in brain perfusion with training-related visuomotor improvement in MS.Frontiers in molecular neuroscience · 2023Article
- Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity.Network neuroscience (Cambridge, Mass.) · 2022Article
- Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis.Network neuroscience (Cambridge, Mass.) · 2022Article
- A Preliminary Report of Network Electroencephalographic Measures in Primary Progressive Apraxia of Speech and Aphasia.Brain sciences · 2022Article
- The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics.NeuroImage. Clinical · 2022Review
- Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis.Journal of personalized medicine · 2021Review
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients.
objectiveTo investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology.
methodsResting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage.
resultsA more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years (
conclusionsThe level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.
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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.