ArticleNetwork neuroscience (Cambridge, Mass.)2020
Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy.
Article in Network neuroscience (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 25 citations in OpenAlex.
- A generalized scaling law reveals synchrony-driven reorganization of brain dynamics across human lifespan.PLoS computational biology · 2026Article
- Energy-Based Phase-Locking State Analysis in Brain State Identification.Human brain mapping · 2026Article
- Spatiotemporal asymmetries on brain energy landscape uncover system entrapment related to depression severity.Nature communications · 2026Article
- Computational Pipeline to Infer Micro-, Meso-, and Macro-Scale Brain-State Transitions.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Comparison of Large Language Model with Aphasia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Energy landscape analysis based on the Ising model: Tutorial review.PLOS complex systems · 2025Article
- FNIRS-Based Energy Landscape Analysis to Signify Brain Activity Dynamics of Individuals With Depression.CNS neuroscience & therapeutics · 2024Article
- Article
- Aberrant brain dynamics in individuals with clinical high risk of psychosis.Schizophrenia bulletin open · 2024Article
- Functional and structural networks decoupling in generalized tonic-clonic seizures and its reorganization by drugs.Epilepsia open · 2023Article
- Control energy assessment of spatial interactions among macro-scale brain networks.Human brain mapping · 2022Article
- Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies?Frontiers in neurology · 2022Review
- It's about time: Linking dynamical systems with human neuroimaging to understand the brain.Network neuroscience (Cambridge, Mass.) · 2022Article
- The ascending arousal system shapes neural dynamics to mediate awareness of cognitive states.Nature communications · 2021Article
- Alterations of the intrinsic amygdala-hippocampal network in juvenile myoclonic epilepsy.Brain and behavior · 2021Article
- A computational biomarker of juvenile myoclonic epilepsy from resting-state MEG.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2021Article
- Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states.Communications biology · 2021Article
- Emotion Recognition Based on Dynamic Energy Features Using a Bi-LSTM Network.Frontiers in computational neuroscience · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy. It is yet unclear to what extent JME leads to abnormal network activation patterns. Here, we characterized statistical regularities in magnetoencephalograph (MEG) resting-state networks and their differences between JME patients and controls by combining a pairwise maximum entropy model (pMEM) and novel energy landscape analyses for MEG. First, we fitted the pMEM to the MEG oscillatory power in the front-oparietal network (FPN) and other resting-state networks, which provided a good estimation of the occurrence probability of network states. Then, we used energy values derived from the pMEM to depict an energy landscape, with a higher energy state corresponding to a lower occurrence probability. JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta, and gamma bands. Furthermore, simulations of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of energy minima was shortened in JME patients. These network alterations were highlighted by significant classification of individual participants employing energy values as multivariate features. Our findings suggested that JME patients had altered multistability in selective functional networks and frequency bands in the fronto-parietal cortices.
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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.