title: Vector coding and neuronal maps.
abstract: A model of vector coding is proposed. An excitation vector is generated in an ensemble of neurons, which has simultaneous actions on the map of selective detectors (selectors), creating a local excitation maximum which represents the input stimulus. Vector coding is also proposed as an explanation for associative learning and memory. Responses to the input in this model are determined by the excitation vectors triggered by command neurons in ensembles of premotor neurons.
authors.affiliation: M. V. Lomonosov Moscow State University.
authors.forename: E N
authors.initials: EN
authors.lastname: Sokolov
mesh_terms: D000818:Animals; D003214:Conditioning, Classical / Q000502:physiology; D003216:Conditioning, Operant / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity; D009474:Neurons / Q000502:physiology*; D013569:Synapses / Q000502:physiology