ArticleNeurology2024
Energy Associated With Dynamic Network Changes in Patients With Multiple Sclerosis and Cognitive Impairment.
Article in Neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Graded hypergravity is associated with large-scale reorganization of resting-state cortical networks: EEG evidence from a neurological inactivity phenotype.IBRO neuroscience reports · 2026Article
- Neurochemically informed network control theory reveals energetic dysregulation of altered brain state dynamics in obsessive-compulsive disorder.Psychiatry and clinical neurosciences · 2026Article
- Optimizing brain functional-structural architecture with cTBS to reduce relapse in alcohol use disorder: a randomized controlled trial.Molecular psychiatry · 2026Article
- Mapping the Disrupted Connectome in Spinocerebellar Ataxia Type 3: A Network-Based Statistics Study Identifying Novel Therapeutic Targets for Neuromodulation.CNS neuroscience & therapeutics · 2026Article
- Functional connectivity dynamics of monoaminergic circuits related to fatigue in multiple sclerosis.Journal of neurology · 2026Article
- Childhood absence epilepsy and distinct dynamic functional network connectivity patterns in self-limited epilepsy with centrotemporal spikes: a resting-state fMRI study.Pediatric research · 2026Article
- Time-Varying Brain Functional Reconfiguration Patterns Associated With Fatigue in Multiple Sclerosis.Human brain mapping · 2026Observational
- Optical coherence tomography angiography reveals insights into complementary vascular and neurodegenerative mechanisms in multiple sclerosis.Brain communications · 2026Article
- Disrupted Energetic and Entropic Landscape in Individuals With Mild Cognitive Impairment: Insights From Network Control Theory.Human brain mapping · 2025Article
- Investigating the Associated Factors of Mood Disorders and Fatigue in Multiple Sclerosis Patients With Cognitive Impairment: A Cross-Sectional Study.Health science reports · 2025Article
- Network control theory uncovers aberrant connectome controllability in trigeminal neuralgia.The journal of headache and pain · 2025Article
- Exploratory GABAa-informed control network modulates hyperarousal brain dynamics in chronic insomnia.Communications biology · 2025Article
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Authors and funding
10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesPatients with multiple sclerosis (MS) often experience cognitive impairment, and this is related to structural disconnection and subsequent functional reorganization. It is unclear how specific patterns of functional reorganization might make it harder for cognitively impaired (CI) patients with MS to dynamically adapt how brain regions communicate, which is crucial for normal cognition. We aimed to identify dynamic functional network patterns that are relevant to cognitive impairment in MS and investigate whether these patterns can be explained by altered energy costs.
methodsResting-state functional and diffusion MRI was acquired in a cross-sectional design, as part of the Amsterdam MS cohort. Patients with clinically definitive MS (relapse-free) were classified as CI (≥2/7 domains
resultsImaging and cognitive data were available for 95 controls and 330 patients (disease duration: 15 years; 179 CP, 65 MCI, and 86 CI). We identified a "visual network state," "sensorimotor network state," "ventral attention network state," and "default mode network state." CI patients transitioned less frequently between connectivity states compared with CP (β = -5.78; DISCUSSION: This study showed that it costs more energy for MS patients with cognitive impairment to dynamically change the functional network, possibly explaining why these transitions occur less frequently. In particular, transitions from a default mode network state to a visual network state were relevant for cognition in these patients. To further study the order of events leading to these network disturbances, future work should include longitudinal data across different disease stages.
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