ASSOCIATIVE LEARNING IN A NETWORK MODEL OF HERMISSENDA-CRASSICORNIS .2. EXPERIMENTS

A companion paper in a previous issue of this journal presented a resi stance-capacitance circuit computer model of the four-neuron visual-ve stibular network of the invertebrate marine mollusk Hermissenda crassi cornis. In the present paper, we demonstrate that changes in the model 's output in response to simulated associative training is quantitativ ely similar to behavioral and electrophysiological changes in response to associative training of Hermissenda crassicornis. Specifically, th e model demonstrates many characteristics of conditioning: sensitivity to stimulus contingency, stimulus specificity, extinction, and saving s. The model's learning features also are shown to be devoid of non-as sociative components. Thus, this computational model is an excellent t ool for examining the information flow and dynamics of biological asso ciative learning and for uncovering insights concerning associative le arning, memory, and recall that can be applied to the development of a rtificial neural networks.