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Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy

Dominik Krzemiński Orcid Logo, Naoki Masuda Orcid Logo, Khalid Hamandi Orcid Logo, Krish D. Singh Orcid Logo, Bethany Routley, Jiaxiang Zhang Orcid Logo

Network Neuroscience, Volume: 4, Issue: 2, Pages: 374 - 396

Swansea University Author: Jiaxiang Zhang Orcid Logo

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DOI (Published version): 10.1162/netn_a_00125

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...

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Published in: Network Neuroscience
ISSN: 2472-1751
Published: MIT Press - Journals 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa61206
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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.
Keywords: Maximum entropy model, MEG, Energy landscape, Resting-state networks, Juvenile myoclonic epilepsy
College: Faculty of Science and Engineering
Funders: Krish D. Singh, Medical Research Council (http://dx.doi.org/10.13039/501100000265), Award ID: MR/K005464/1. Dominik Krzeminski, Engineering and Physical Sciences Research Coun- ´ cil (http://dx.doi.org/10.13039/501100000266), Award ID: EP/N509449/1. Jiaxiang Zhang, European Research Council, Award ID: 716321. Bethany Routley, Medical Research Council (http://dx.doi.org/10.13039/501100000265), Award ID: MR/K501086/1. Khalid Hamandi, Health Care Research Wales.
Issue: 2
Start Page: 374
End Page: 396