An analytical framework for modeling evoked and event-related potentials

The present work reviews briefly a segmentation method and a modeling approach for multivariate quasi-stationary data. The combination of both parts allows the extraction of low-dimensional models from multidimensional data. The segmentation method is applied to event-related potentials and fields and early auditory evoked potentials and extracts ERP- and ERF-components and early auditory waves objectively and independent from the number of segments. Additionally, the early auditory wave P-a is modeled by a two-dimensional system of ordinary differential equations. We find a common topology of wave P-a, which lets us conjecture intrinsic low-dimensional underlying attractors in the corresponding neuronal dynamics.