NDLI: Stochastic Model for Real and Simulated Neurophysiological Behavior

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Stochastic Model for Real and Simulated Neurophysiological Behavior

Content Provider	IEEE Xplore Digital Library
Author	Gersch, W.
Copyright Year	1965
Abstract	Meaningful factor analysis and algebraic operations during stimulation, learning, and discrimination experiments have been performed on averaged evoked potential responses, suggesting that, at least under some circumstances, the signal space of average evoked potentials is linear. Alternatively, the "behavior" of simulated neural nets is defined as the observation of an average over an ensemble of the trajectories of solutions of interconnected nonlinear dynamical systems. This behavior is a mathematical counterpart of the physiological macropotential observations. In this paper, a mathematical model corresponding to the ensemble average over an unconnected set of statistically distributed linear elements suggests duplication of both the simulated neural net and the neurophysiological findings. In contrast with the simulated neural network, the statistical properties of this model are amenable to analysis. The model suggests experiments of the prediction and control of multidiscrimination experiments in cats and provokes questions on the significance of the specification of detail in different levels on the structural hierarchy of the brain.
Starting Page	86
Ending Page	92
Page Count	7
File Size	2266370
File Format	PDF
ISSN	05361567
Volume Number	3
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1967-11-01
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Biological neural networks Brain modeling Signal analysis Performance analysis Nonlinear dynamical systems Mathematical model Analytical models Predictive models Cats
Content Type	Text
Resource Type	Article
Subject	Engineering

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