Simulation studies of a temporal sequence memory model

Abstract

Models of circuit action in the mammalian hippocampus have led us to a study of habituation circuits. In order to help model the process of habituation we consider here a memory network designed to learn sequences of inputs separated by various time intervals and to repeat these sequences when cued by their initial portions. The structure of the memory is based on the anatomy of the dentate gyrus region of the mammalian hippocampus. The model consists of a number of arrays of cells called lamellae. Each array consists of four lines of model cells coupled uniformly to neighbors within the array and with some randomness to cells in other lamellae. All model cells operate according to first-order differential equations. Two of the lines of cells in each lamella are coupled such that sufficient excitation by a system input generates a wave of activity that travels down the lamella. Such waves effect dynamic storage of the representation of each input, allowing association connections to form that code both the set of cells stimulated by each input and the time interval between successive inputs. Results of simulation of two networks are presented illustrating the model's operating characteristics and memory capacity.