EEG Microstate Sequences From Different Clustering Algorithms Are Information-Theoretically Invariant

EEG Microstate Sequences From Different Clustering Algorithms Are Information-Theoretically Invariant

We analyse statistical and information-theoretical properties of EEG microstate sequences, as seen through the lens of five different clustering algorithms. Microstate sequences are computed for n = 20 resting state EEG recordings during wakeful rest. The input for all clustering algorithms is the s...

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Bibliographic Details
Main Authors: Frederic von Wegner, Paul Knaut, Helmut Laufs
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-08-01
Series:Frontiers in Computational Neuroscience
Subjects:
EEG microstates
information theory
entropy
mutual information
markovianity
stationarity
Online Access:https://www.frontiersin.org/article/10.3389/fncom.2018.00070/full

Internet

https://www.frontiersin.org/article/10.3389/fncom.2018.00070/full

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