New Horizons for Associative Memory Broaden by Neurophysiological and Computational Findings of Graded Persistent Activity

Associative memory in neural-neural network systems has long been described by dynamical systems with discrete attractors. Recent neurophysiological findings of graded persistent activity, however, suggest that memory retrieval in the brain is more likely to be described by dynamical systems with continuous attractors. This paper briefly reviews experimental studies of graded persistent activity and computational studies for modelling its neural mechanisms by continuous attractor dynamics. Furthermore, their implications for associative memory are discussed.

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