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 2018-01, Vol.2018 (2018), p.1-15
Hauptverfasser:	Porta-Garcia, M. A., Yáñez-Suárez, Oscar, Valdés-Cristerna, Raquel
Format:	Artikel
Sprache:	eng
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
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