Abstract
Double-layer neural networks with mutually inhibiting interconnections are analyzed using a continuous-variable model of the neuron. The first layer consists of excitatory neurons while the second layer consists of inhibitory neurons. Both feedforward and feedback interconnections exist between the two layers. An autonomous system of nonlinear differential equations is introduced to describe the network dynamics, and the stability conditions for some classes of equilibria are investigated in detail. Several simulation results are also presented. It is shown that even those networks which are formed with rather powerless synapses are capable of carrying out input pattern sharpening, temporary information storage, and periodic signal generation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Hadeler, K.P.: On the theory of lateral inhibition. Kybernetik 14, 161–165 (1974)
Morishita, I., Yajima, A.: Analysis and simulation of networks of mutually inhibiting neurons. Kybernetik 11, 154–165 (1972)
Reichardt, W. von, Ginitie, G.M.: Zur Theorie der lateralen Inhibition. Kybernetik 1, 155–165 (1962)
Szentágothai, J.: Architecture of the cerebral cortex. In: Basic mechanisms of the epilepsies. Eds.: Jasper, H.H., Ward, A.A., Pope, A. Boston: Little Brown and Company 1969
Varjú, D.: Vergleich zweier Modelle für laterale Inhibition. Kybernetik 1, 200–208 (1962)
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Tokura, T., Morishita, I. Analysis and simulation of double-layer neural networks with mutually inhibiting interconnections. Biol. Cybernetics 25, 83–92 (1977). https://doi.org/10.1007/BF00337266
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF00337266