title: A neuronal network model of associative memory and a brain theory.
abstract: There are facts suggesting that the changes of excitability of neurons and conductance of synapses are responsible for learning and memory. In accordance with the idea, the author proposed a neuronal network model of associative memory, which can learn conditioned reflexes repeatedly together with its adaptive properties, without much interference with the previously existing memories. Further, a modified model can memorize dynamic images and establish motor patterns. An analysis of the structure of the model is presented, and some conclusions about this sort of model are drawn. A theory of memory and learning suggesting that the brain works by means of a mechanism similar to that of the model is proposed, as well as the explanations for some behavioral and clinical findings from the viewpoint of the model.
mesh_terms: D000818:Animals; D001245:Association Learning / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D003214:Conditioning, Classical / Q000502:physiology; D003216:Conditioning, Operant / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology*; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009044:Motor Cortex / Q000502:physiology; D009415:Nerve Net; D051381:Rats; D013003:Somatosensory Cortex / Q000502:physiology; D014793:Visual Cortex / Q000502:physiology