English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Since the discovery of electrical activity of the brain, electroencephalographic (EEG) recordings constitute one of the most popular techniques of brain research. However, EEG signals are highly nonstationary and one should expect that averages of the cross-correlation coefficient, which may take positive and negative values with equal probability, (almost) vanish when estimated over long data segments. Instead, we found that the average zero-lag cross-correlation matrix estimated with a running window over the whole night of sleep EEGs, or of resting state during eyes-open and eyes-closed conditions of healthy subjects shows a characteristic correlation pattern containing pronounced nonzero values. A similar correlation structure has already been encountered in scalp EEG signals containing focal onset seizures. Therefore, we conclude that this structure is independent of the physiological state. Because of its pronounced similarity across subjects, we believe that it depicts a generic feature of the brain dynamics. Namely, we interpret this pattern as a manifestation of a dynamical ground state of the brain activity, necessary to preserve an efficient operational mode, or, expressed in terms of dynamical system theory, we interpret it as a "shadow" of the evolution on (or close to) an attractor in phase space. Nonstationary dynamical aspects of higher cerebral processes should manifest in deviations from this stable pattern. We confirm this hypothesis through a correlation analysis of EEG recordings of 10 healthy subjects during night sleep, 20 recordings of 9 epilepsy patients, and 42 recordings of 21 healthy subjects in resting state during eyes-open and eyes-closed conditions. In particular, we show that the estimation of deviations from the stationary correlation structures provides a more significant differentiation of physiological states and more homogeneous results across subjects.

Characteristic Fluctuations Around Stable Attractor Dynamics Extracted from Highly Nonstationary Electroencephalographic Recordings