漸次的持続活性の神経生理学的および計算論的知見が開く連想記憶の新しい地平

抄録

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.