Title :
Segmental structure of EEG more likely reveals the dynamic multistability of the brain tissue than the continual plasticity one
Author_Institution :
Dept. of Human Physiol., Moscow State Univ., Russia
Abstract :
A critical review of the principal strategies of the EEG description as a piecewise stationary process is given and new methodology of EEG segmentation, based on nonparametric statistical analysis, is proposed. Our methodology provides the detection of moments of quasi-stationary segments´ boundaries in almost any EEG characteristic for a given level of false alarm probability. Relatively high temporal resolution of the method makes it possible to formulate a new approach to investigation of the functional synchrony between different brain areas. We discuss also the achievements, problems, and prospects of EEG signal segmentation
Keywords :
electroencephalography; medical signal processing; statistical analysis; EEG description; EEG segmentation; brain areas; brain tissue; continual plasticity; dynamic multistability; electroencephalography; false alarm probability; functional synchrony; nonparametric statistical analysis; piecewise stationary process; quasi-stationary segment boundaries; segmental structure; signal segmentation; temporal resolution; Brain; Electroencephalography; Large Hadron Collider; Light rail systems; Physiology; Sampling methods; Signal resolution; Statistical distributions; Stochastic processes; Tin;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.845668