Cyclic modes in artificial neural nets

Artificial neural nets constructed of dicrete populations of 200–1000 formal neurons have been studied through computer simulation. Among the basic assumptions of operation of these nets are the following: a) Each neuron fires at times which are integral multiples of the synaptic delay . b) It produces the appropriate PSP's after . c) All the neurons have the same refractory period and d) temporal summation occurs without decrement, for a period less than the synaptic delay. The nets were specified by a number of parameters: fraction of inhibitory neurons in the population, average number of connections to each cell, threshold for cell firing. These parameters did not determine the detailed microscopical structures of nets which was established separately on a random basis.For the range of the parameters considered in this study it was found that neural nets are capable of supporting self-maintaining activity in the form of cycling modes, characterized by a fixed period. The period of the cycles can be altered by a steady, non-cycling external input to the net. Evidence is presented that the cycling modes depend upon the statistical parameters of the net and the stimulus characteristics rather than on the detailed structure of the net. These results suggest that non-structured nerve nets may respond in specific manner to specific stimuli.

Glossary

Parameters of Neural Net Model Synaptic delay - A Total number of neurons in the netlet - h Fraction of inhibitory neurons in the netlet (in % of total number of neurons) - ⁺ Average number of axon branches emanating from anexcitatory neuron - ^– Average number of axon branches emanating from an inhibitory neuron - k⁺ Average EPSP produced by an excitatory neuron in arbitrary units of amplitude - k^– Average IPSP produced by an inhibitory neuron in arbitrary units of amplitude - Firing threshold of neurons in the netlet - The minimum number of ESPS's necessary to trigger a neuron in the absence of inhibitory inputs - The minimum number of ESPS's necessary to trigger a neuron in the presence of inhibitory inputs.Dynamic Parameters of the Model n An integer giving the number of elapsed synaptic delays (i.e. elapsed time) - _n The activity; i.e. the fraction of active neurons in the netlet at t=n (the actual number of active cells is given by _nA) - _n={ⁱ_n} State vector of single netlet at time nThis research has been supported by NIH grants NS-8012 and NS-8498, and NSF grant GB-30498. Computation assistance was provoded by the Health Sciences Computing Facility, UCLA, sponsored by NIH Special Research Resources grant RR-3.