Advanced Methods of Physiological System Modeling, Volume 3
Springer US, Oct 31, 1994 - Technology & Engineering - 272 pages
This volume is the third in a series entitled" Advanced Methods of Physiological System Modeling" and the fifth in a series of research volumes published by Plenum under the sponsorship of the Biomedical Simulations Resource (BMSR) at the Uni versity of Southern California in the context of dissemination activities supported by the Biomedical Research Technology Program of the National Center for Research Resources at the National Institutes of Health under Grant No. P41 RR-OI861. These volumes are edited by BMSR principal scientists and report on recent research de velopments in the area of physiological systems modeling, as well as on advanced methods for analysis of physiological signals and data. As in the previous two volumes of this series, the work reported herein is con cerned with the development of advanced modeling methodologies and their novel application to problems of biomedical interest, with emphasis on nonlinear aspects of physiological function. The term "advanced methodologies" is used to indicate that the scope of this work extends beyond the ordinary type of analysis, which is confined traditionally to the linear domain. As the importance of nonlinearities in understanding the complex mechanisms of physiological function is increasingly recognized, the need for effective and practical modeling methodologies that address the issue of nonlinear dynamics in life sciences becomes more and more pressing.
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Advanced Methods of Physiological System Modeling
Experimental Basis for an InputOutput Model of
Computational Methods of Neuronal Network Decomposition
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1st—order 2nd-order kernel estimate 3rd-order action potential Advanced Methods algorithm alphaxalone analysis approach approximation average Berger bicuculline binary Biomed component computed cross-correlation CSRS decomposition dentate granule cells dentate gyrus diagonal discrete-time domain dynamic eigenvector equivalent experimental feedforward Figure first-order frequency cycles/sec functional expansion GABAA GABAA receptor GABAergic Gaussian granule cells hidden units hippocampal formation I-V scatter impulse input signal input/output inter-impulse intervals interneurons kernel values Korenberg Laguerre expansion linear m—sequences mapping Methods of Physiological multi-input NARMA NARMAX model neural neurons NMA model noise nonlinear systems orthogonal output parallel cascade parameters partial coherence PDM's perforant path Physiological System Modeling Plenum polynomial population spike properties representation response Schetzen Sclabassi second order kernel second-order kernel sequence shown in Fig sigmoid sigmoid functions slices static nonlinearity stimulus subsystems system identification technique V.Z. Marmarelis voltage Volterra kernels Volterra model Volterra series white—noise Wiener kernels York