EEG

Рurpose of this work is to study the effect of previous sensory information on the brain’s processing of current visual stimuli. Bistable images (Necker cubes) with a high degree of ambiguity (HA) and a low degree of ambiguity (LA) were used as visual stimuli. Methods. In this paper, we used wavelets to identify features of the brain activity signals. A multivariate analysis of variance was used to compare behavioral characteristics.

The goal of the present study is to investigate the effect of healthy aging on the neuronal mechanisms supporting human brain activity during motor task performance. Such biomarkers of the age-related changes can be detected using mathematical methods of time-series analysis and complexity analysis. Methods. In the present paper, recurrence quantification analysis (RQA) measures are employed to explore the complexity of the pre-movement EEG in young and elderly adult groups.

The purpose of the current study is to determine how the characteristic time (lag) responsible for keeping information about the previous dynamics in the brain local field potential signals evaluates in time. This time is necessary to know in order to construct forecasting models for coupling estimation and seizure prediction and detection. Methods. Mutual information function calculated between a signal with itself shifted in time is used. The shift varies from 0 to one half of characteristic oscillation period.

The EEG research technique on the basis of autoregressive models construction and Granger causality estimation by experimental data are described in this article. The EEG is written down from the brain of WAG/Rij rats, which are absence-epilepsy contaminated. The EEG episodes well enough described in terms of small order linear display along with the episodes with expressed nonlinearity are revealed during the analysis. The EEG episodes ordering is spent in accordance with the model parameters received and physiological condition of the animals.

The detailed wavelet analysis of sleep electric brain activity, obtained from rats with genetic predisposition to absence-epilepsy, has been performed. Characteristic features of time-and-frequency structure of sleep spindles (oscillatory pattern, that serve as electroencephalographic correlate for slow-wave sleep) have been discovered in long-term electroencephalographic data. Operation has been performed using continuous wavelet transform.