Spatio-temporal analysis of monofractal and multifractal properties of the human sleep EEG

• Published in: Journal of neuroscience methods Vol. 185; no. 1; pp. 116 - 124
• Main Authors: Weiss, Béla, Clemens, Zsófia, Bódizs, Róbert, Vágó, Zsuzsanna, Halász, Péter
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.12.2009
• Subjects: Adolescent; Adult; Algorithms; Cerebral Cortex - anatomy & histology; Cerebral Cortex - physiology; EEG; Electrodes; Electroencephalography - methods; Evoked Potentials - physiology; Female; Fractal spectrum; Fractals; Generalized dimensions; Humans; Hurst exponent; Male; Middle Aged; Monofractal analysis; Multifractal analysis; Polysomnography - methods; Reaction Time - physiology; Self-similarity; Signal Processing, Computer-Assisted; Sleep - physiology; Sleep stages; Stochastic Processes; Time Factors; Young Adult; Fractal spectrum; Monofractal analysis; EEG; Sleep stages; Hurst exponent; Generalized dimensions; Multifractal analysis; Self-similarity
• ISSN: 0165-0270; 1872-678X; 1872-678X
• DOI: 10.1016/j.jneumeth.2009.07.027

Fractality is a common property in nature. It can also be observed in time series representing dynamics of complex processes. Therefore fractal analysis could be a useful tool to describe the dynamics of brain electrical activities in physiological and pathological conditions. In this study, we carried out a spatio-temporal analysis of monofractal and multifractal properties of whole-night sleep EEG recordings. We estimated the Hurst exponent (H) and the range of fractal spectra (dD) in 10 healthy subjects. We found higher H values during NREM4 compared to NREM2 and REM in all electrodes. Measure dD showed an opposite trend. Differences of H and dD between NREM2 and REM reached significancy at circumscribed regions only. Our results contribute to a deeper understanding of the fractal nature of brain electrical activities and may have implications for automatic classification of sleep stages.