Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation

Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase syn...

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Veröffentlicht in:	Computational intelligence and neuroscience Jg. 2018; H. 2018; S. 1 - 15
Hauptverfasser:	Porta-Garcia, M. A., Yáñez-Suárez, Oscar, Valdés-Cristerna, Raquel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cairo, Egypt Hindawi Publishing Corporation 01.01.2018 Hindawi John Wiley & Sons, Inc
Schlagworte:	Algorithms Analysis Bivariate analysis Cluster analysis Clustering Clustering (Computers) Clusters Cognitive ability Decomposition EEG Eigenvalues Electrodes Electroencephalography Event-related potentials Fourier transforms Fuzzy algorithms Fuzzy logic Fuzzy systems Methods Neurosciences Phase transitions Representations Synchronism Synchronization Time series Topography
ISSN:	1687-5265, 1687-5273, 1687-5273
Online-Zugang:	Volltext
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