Resting state MEG oscillations show long-range temporal correlations of phase synchrony that break down during finger movement.

ABSTRACT: The capacity of the human brain to interpret and respond to multiple temporal scales in its surroundings suggests that its internal interactions must also be able to operate over a broad temporal range. In this paper, we utilize a recently introduced method for characterizing the rate of change of the phase difference between MEG signals and use it to study the temporal structure of the phase interactions between MEG recordings from the left and right motor cortices during rest and during a finger-tapping task. We use the Hilbert transform to estimate moment-to-moment fluctuations of the phase difference between signals. After confirming the presence of scale-invariance we estimate the Hurst exponent using detrended fluctuation analysis (DFA). An exponent of >0.5 is indicative of long-rang

SUBMITTER: Botcharova M 

PROVIDER: S-EPMC4469817 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature