An Analytical Framework For Modeling Evoked and Event-Related Potentials

Axel Hutt

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Submission date: 03. Jun. 2002
Pages: 21
published in: International journal of bifurcation and chaos in applied sciences and engineering, 14 (2004) 2, p. 653-666 
DOI number (of the published article): 10.1142/S0218127404009351
Bibtex
PACS-Numbers: 02.50.Sk, 95.10.Fh, 06.30.-k
Keywords and phrases: signal segmentation, multivariate modeling, brain signals
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Abstract:
The presented work introduces shortly a novel segmentation method and a modeling approach for multivariate quasi-stationary data. The combination of both parts allows the extraction of low-dimensional models from multivariate data. The segmentation method is applied both to event-related potentials and fields and early auditory evoked potentials. Additionally, the early auditory wave Pa is modeled by a two-dimensional dynamical system. The segmentation method detects ERP- and ERF-components and early auditory waves objectively, which illustrates the independence of the segmentation method from the number of segments. Additionally, we find a common topology of wave Pa, which indicates a common underlying attractor in the brain

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