title: Pattern separation, completion, and categorisation in the hippocampus and neocortex.
abstract: The mechanisms for pattern completion and pattern separation are described in the context of a theory of hippocampal function in which the hippocampal CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The factors important in the pattern completion in CA3 and also a large number of independent memories stored in CA3 include: a sparse distributed representation, representations that are independent due to the randomizing effect of the mossy fibres, heterosynaptic long-term depression as well as long-term potentiation in the recurrent collateral synapses, and diluted connectivity to minimize the number of multiple synapses between any pair of CA3 neurons which otherwise distort the basins of attraction. Recall of information from CA3 is implemented by the entorhinal cortex perforant path synapses to CA3 cells, which in acting as a pattern associator allow some pattern generalization. Pattern separation is performed in the dentate granule cells using competitive learning to convert grid-like entorhinal cortex firing to place-like fields, and in the dentate to CA3 connections that have diluted connectivity. Recall to the neocortex is achieved by a reverse hierarchical series of pattern association networks implemented by the hippocampo-cortical backprojections, each one of which performs some pattern generalization, to retrieve a complete pattern of cortical firing in higher-order cortical areas. New results on competitive networks show which factors contribute to their ability to perform pattern separation, pattern clustering, and pattern categorisation, and how these apply in different hippocampal and neocortical systems.
authors.affiliation: Oxford Centre for Computational Neuroscience, Oxford, England, United Kingdom; University of Warwick, Department of Computer Science, Coventry CV4 7AL, England, United Kingdom. Electronic address: Edmund.Rolls@oxcns.org.
authors.forename: Edmund T
authors.initials: ET
authors.lastname: Rolls
mesh_terms: D000818:Animals; D001245:Association Learning / Q000502:physiology*; D056654:CA3 Region, Hippocampal / Q000502:physiology*; D006801:Humans; D011939:Mental Recall / Q000502:physiology*; D008959:Models, Neurological; D019579:Neocortex / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D046709:Pattern Recognition, Physiological / Q000502:physiology*; D013569:Synapses / Q000502:physiology
keywords: Attractor network; Categorisation; Competitive network; Completion; Episodic memory; Hippocampus; Pattern association network; Pattern separation