Analytical and empirical fluctuation functions of the EEG microstate random walk - Short-range vs. long-range correlations

von Wegner, F.; Tagliazucchi, E.; Brodbeck, V.; Laufs, H.

Abstract

We analyze temporal autocorrelations and the scaling behaviour of EEG microstate sequences during wakeful rest. We use the recently introduced random walk approach and compute its fluctuation function analytically under the null hypothesis of a short-range correlated, first-order Markov process. The empirical fluctuation function and the Hurst parameter H as a surrogate parameter of long-range correlations are computed from 32 resting state EEG recordings and for a set of first-order Markov surrogate data sets with equilibrium distribution and transition matrices identical to the empirical data. In order to distinguish short-range correlations (H approximate to 0.5) from previously reported long-range correlations (H > 0.5) statistically, confidence intervals for H and the fluctuation functions are constructed under the null hypothesis. Comparing three different estimation methods for H, we find that only one data set consistently shows H > 0.5, compatible with long-range correlations, whereas the majority of experimental data sets cannot be consistently distinguished from Markovian scaling behaviour. Our analysis suggests that the scaling behaviour of resting state EEG microstate sequences, though markedly different from uncorrelated, zero-order Markov processes, can often not be distinguished from a short-range correlated, first-order Markov process. Our results do not prove the microstate process to be Markovian, but challenge the approach to parametrize resting state EEG by single parameter models. (C) 2016 Elsevier Inc. All rights reserved.

Más información

Título según WOS: ID WOS:000384074500039 Not found in local WOS DB
Título de la Revista: NEUROIMAGE
Volumen: 141
Editorial: ACADEMIC PRESS INC ELSEVIER SCIENCE
Fecha de publicación: 2016
Página de inicio: 442
Página final: 451
DOI:

10.1016/j.neuroimage.2016.07.050

Notas: ISI