Advanced Methods of Physiological System Modeling -

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Résumé :
This volume is the second in a series of publications sponsored by the Biomedical Simulations Resource (BMSR) at the University of Southern California that report on recent research developments in the area of physiological systems modeling and anal? ysis of physiological signals. As in the first volume of this series, the work reported herein is concerned with the development of advanced 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 used by most investigators in this area, which is confined primarily in the linear domain. As the im? portance of nonlinearities in understanding the complex mechanisms of physiological function is increasingly recognized, the need for effective and practical methodolo? gies that address the issue of nonlinear dynamics in life sciences becomes more and more pressing. The publication of these volumes and the workshops, organized by the BMSR on the same subject, are two key activities in our efforts to promote and intensify research in this area, foster interaction and collaboration among interested investigators, and disseminate recent results throughout the biomedical community.

Sommaire:
Volterra-Wiener Analysis of a Class of Nonlinear Feedback Systems and Application to Sensory Biosystems.- Parameter Estimation for Nongaussian Processes via Second and Third Order Spectra with an Application to some Endocrine Data.- Analysis of the Whole-Nerve Responses from the Exposed Auditory Nerve in Man to Pseudorandom Noise.- Nonlinear Models of Transduction and Adaptation in Locust Photoreceptors.- Identification of Intensive Nonlinearities in Cascade Models of Visual Cortex and its Relation to Cell Classification.- Modeling of Neuronal Networks Through Experimental Decomposition.- Theoretical Decomposition of Neuronal Networks.- The Geometry of System Identification: Fractal Dimension and Integration Formulae.- Fast Orthogonal Algorithms for Nonlinear System Identification and Time-Series Analysis.- New Algorithm for Korenberg-Billings Model of Nonlinear System Identification.- Nonlinear Filters for Tracking Chaos in Neurobiological Time Series.- Chaotic Heart Rate Dynamics in Isolated Perfused Rat Hearts.- to the Properties and Analysis of Fractal Objects, Processes, and Data.- Towards a Physics of Neocortex.- The Use of Wiener-Volterra Methods in the Analysis and Synthesis of Simulated Neural Networks.- Wiener Analysis of the Hodgkin-Huxley Equations.- Contributors.