Scale-invariance of human EEG signals in sleep

Abstract

We investigate the dynamical properties of electroencephalogram (EEG) signals of human in sleep. By using a modified random walk method, We demonstrate that the scale-invariance is embedded in EEG signals after a detrending procedure. Further more, we study the dynamical evolution of probability density function (PDF) of the detrended EEG signals by nonextensive statistical modeling. It displays scale-independent property, which is markedly different from the turbulent-like scale-dependent PDF evolution.

4 pages and 6 figures

References in corpus (3)

• Self-Organized Criticality model for Brain Plasticity
• Non-extensive Behavior of a Stock Market Index at Microscopic Time Scales
• Power-law random walks