Recurrence quantification analysis of dynamic brain networks

Marinho A. Lopes*, Jiaxiang Zhang, Dominik Krzemiński, Khalid Hamandi, Qi Chen, Lorenzo Livi, Naoki Masuda

*この研究の対応する著者

研究成果: Article査読

2 被引用数 (Scopus)

抄録

Evidence suggests that brain network dynamics are a key determinant of brain function and dysfunction. Here we propose a new framework to assess the dynamics of brain networks based on recurrence analysis. Our framework uses recurrence plots and recurrence quantification analysis to characterize dynamic networks. For resting-state magnetoencephalographic dynamic functional networks (dFNs), we have found that functional networks recur more quickly in people with epilepsy than in healthy controls. This suggests that recurrence of dFNs may be used as a biomarker of epilepsy. For stereo electroencephalography data, we have found that dFNs involved in epileptic seizures emerge before seizure onset, and recurrence analysis allows us to detect seizures. We further observe distinct dFNs before and after seizures, which may inform neurostimulation strategies to prevent seizures. Our framework can also be used for understanding dFNs in healthy brain function and in other neurological disorders besides epilepsy.

本文言語English
ページ(範囲)1040-1059
ページ数20
ジャーナルEuropean Journal of Neuroscience
53
4
DOI
出版ステータスPublished - 2021 2
外部発表はい

ASJC Scopus subject areas

  • 神経科学(全般)

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