4.6 Article

Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study

期刊

CLINICAL NEUROPHYSIOLOGY
卷 131, 期 2, 页码 377-384

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.clinph.2019.11.021

关键词

Insular epilepsy; Magnetoencephalography; Ripples; Effective connectivity; Graph theory

资金

  1. Natural Science Foundation of China [81771398]
  2. Beijing Municipal Science & Technology Commission [Z161100002616001]

向作者/读者索取更多资源

Objective: The project aimed to determine the alterations in the effective connectivity (EC) neural network in patients with insular epilepsy based on interictal high-frequency oscillations (HFOs) from magnetoencephalography (MEG) data. Methods: We studied MEG data from 22 insular epilepsy patients and 20 normal subjects. Alterations in spatial pattern and connection properties of the patients with insular epilepsy were investigated in the entire brain network and insula-based network. Results: Analyses of the parameters of graph theory revealed the over-connectivity and small-world configuration of the global connectivity patterns observed in the patients. In the insula-based network, the insular cortex ipsilateral to the seizure onset displayed increased efferent and afferent EC. Left insular epilepsy featured strong connectivity with the bilateral hemispheres, whereas right insular epilepsy featured increased connectivity with only the ipsilateral hemisphere. Conclusions: Patients with insular epilepsy display alterations in the EC network in terms of both whole-brain connectivity and the insula-based network during interictal HFOs. Significance: Alterations of interictal HFO-based networks provide evidence that epilepsy networks, instead of epileptic foci, play a key role in the complex pathophysiological mechanisms of insular epilepsy. The dysfunction of HFO networks may prove to be a novel promising biomarker and the cause of interictal brain dysfunctions in insular epilepsy. (C) 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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