Advanced methods of physiological system modeling

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書誌事項

Advanced methods of physiological system modeling

edited by Vasilis Z. Marmarelis

Plenum Press, 1987-c1994

  • v. 1
  • v. 2
  • v. 3

タイトル別名

Physiological system modeling

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注記

"Published in cooperation with Biomedical Simulations Resource, University of Southern California, Los Angeles"

Publisher of Vol.1 : Biomedical simulations resource

内容説明・目次

巻冊次

v. 2 ISBN 9780306432590

内容説明

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.

目次

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.
巻冊次

v. 3 ISBN 9780306448195

内容説明

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.

目次

Nonlinear Modeling of Physiological Systems Using Principal Dynamic Modes (V.Z. Marmarelis). Experimental Basis for an Input/Output Model of the Hippocampal Formation (T.W. Berger et al.). Computational Methods of Neuronal Network Decomposition (R.J. Sclabassi et al.). An Extension of the Msequence Technique for the Analysis of Multiinput Nonlinear Systems (E.A. Benardete, J.D. Victor). Examples of the Investigation of Neural Information Processing by Point Process Analysis (D.R. Brillinger, A.E.P. Villa). Testing a Nonlinear Model of Sensory Adaptation with a Range of Step Input Functions (A.S. French, S.K. Patrick). Identification of Nonlinear System with Feedback Structure (J. Shi, H.H. Sun). Identification of Multipleinput Nonlinear Systems Using Nonwhite Test Signals (D.T. Westwick, R.E. Kearney). Nonlinear System Identification of Hippocampal Neurons (B.L. Bardakjian et al.). Parametric and Nonparametric Nonlinear Modeling of Renal Autoregulation Dynamics (K.H. Chon et al.). 5 additional articles. Index.

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