Testing for significance of phase synchronisation dynamics in the EEG.

Abstract:

:A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

journal_name

J Comput Neurosci

authors

Daly I,Sweeney-Reed CM,Nasuto SJ

doi

10.1007/s10827-012-0428-2

subject

Has Abstract

pub_date

2013-06-01 00:00:00

pages

411-32

issue

3

eissn

0929-5313

issn

1573-6873

journal_volume

34

pub_type

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