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• W3205377589 abstract "The main challenge in the clinical assessment of Psychogenic Non-Epileptic Seizures (PNES) is the lack of an electroencephalographic marker in the electroencephalography (EEG) readout. Although decades of EEG studies have focused on detecting cortical brain function underlying PNES, the principle of PNES remains poorly understood. To address this problem, electric potentials generated by large populations of neurons were collected during the resting state to be processed after that by Power Spectrum Density (PSD) for possible analysis of PNES signatures. Additionally, the integration of distributed information of regular and synchronized multi-scale communication within and across inter-regional brain areas has been observed using functional connectivity tools like Phase Lag Index (PLI) and graph-derived metrics. A cohort study of 20 PNES and 19 Healthy Control subjects (HC) were enrolled. The major finding is that PNES patients exhibited significant differences in alpha-power spectrum in brain regions related to cognitive operations, attention, working memory, and movement regulation. Noticeably, we observed that there exists an altered oscillatory activity and a widespread inter-regional phase desynchronization. This indicates changes in global efficiency, node betweenness, shortest path length, and small worldness in the delta, theta, alpha, and beta frequency bands. Finally, our findings look into new evidence of the intrinsic organization of functional brain networks that reflects a dysfunctional level of integration of local activity across brain regions, which can provide new insights into the pathophysiological mechanisms of PNES." @default.
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• W3205377589 date "2021-10-21" @default.
• W3205377589 modified "2023-10-16" @default.
• W3205377589 title "Signatures of Brain Network Alteration in Psychogenic Non-Epileptic Seizures: A Rest-EEG Study Based on Power Spectral Density and Phase Lag Index" @default.
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• W3205377589 doi "https://doi.org/10.1101/2021.10.20.464353" @default.
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