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Energy landscape of resting magnetoencephalography reveals frontoparietal network impairments in epilepsy

Krzeminski, Dominik, Masuda, Naoki, Hamandi, Khalid, Singh, Krish D. ORCID:, Routley, Bethany and Zhang, Jiaxiang ORCID: 2020. Energy landscape of resting magnetoencephalography reveals frontoparietal network impairments in epilepsy. Network Neuroscience 4 (2) , pp. 374-396. 10.1162/netn_a_00125

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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 characterised statistical regularities in 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 frontoparietal 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 multi-stability in selective functional networks and frequency bands in the frontoparietal cortices.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Cardiff University Brain Research Imaging Centre (CUBRIC)
Publisher: Massachusetts Institute of Technology Press (MIT Press)
ISSN: 2472-1751
Funders: EPSRC
Date of First Compliant Deposit: 14 January 2020
Date of Acceptance: 22 December 2019
Last Modified: 24 Aug 2023 17:30

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