A NETWORK MODEL WITH AUTO-OSCILLATING OUTPUT AND DYNAMIC CONNECTIONS

A major problem that researchers attempting to elaborate mathematical models of neurophysiological and/or psychophysiological processes are confronted with is the identification of the mechanisms that give rise , in a neural network, to oscillatory behavior, either spontaneous or induced by external stimuli. The present work starts by considering a network model of a central pattern generator (CPG), introduced by Somp olinsky and co-authors. The present authors try to generalize this mod el to a wider range of biological situations, by introducing into it d ynamic adjustments of connections among the processing units. Although the study performed so far is quite preliminary, some analytical cons iderations can be presented, supported by the results of numerical sim ulations, which show always a relaxation of the network toward specifi c stable states.