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Temporal-pattern learning in neural models. (English) Zbl 0589.92005

Lecture Notes in Biomathematics, 63. Berlin etc.: Springer-Verlag. VII, 227 p. DM 36.00 (1985).
Models of a pacemaker plastic neuron and of a network consisting of such neurons and having the property of learning rhythms are presented. This monograph consists of an introduction, five parts and three appendices.
The first part (second chapter) is a concise review of some specific experimental data at the unineuronal and multineuronal levels concerning especially rhythmic spontaneous activity and periodic stimulation. Previous models of pacemaker neurons are considered: on the one hand, biophysical models of intracellular activity (Hodgkin-Huxley, Perkel’s model, etc.) and on the other, neuronal models of learning (Hebb’s neuron, the perceptron, etc.). The neuron and networks models proposed here establish a point of connection (in the author’s words) between these two areas.
In the third chapter a pacemaker neuron model is presented and simulation experiments are carried out. The neuron model is based on Perkel’s one [Science 145, 61-63 (1964)] with three main innovations, the most important of which equips it with the desired adaptation capacity.
The fourth chapter gives an analytic study of the entrainment patterns: phase transition analysis, analysis of periodic solutions, analysis of the effect of randomness and learning upon entrainment.
A network of 10\(\times 10\) pacemaker neurons situated on the nodes of a toroidal network with square lattice where the connectivity obeys the principle of feedback latteral inhibition is considered in the fifth chapter. Simulation shows that some factors such as the proportion of the excitatory connections over the total and the ratio between the ranges of the excitatory and the inhibitory connectivity most crucially influence the learning capacity of the network.

MSC:

92Cxx Physiological, cellular and medical topics
92-02 Research exposition (monographs, survey articles) pertaining to biology
91E30 Psychophysics and psychophysiology; perception