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Hippocampal formation as unitary coherent particle filter

Fox, C. and Prescott, T. (2009) Hippocampal formation as unitary coherent particle filter. In: Eighteenth Annual Computational Neuroscience Meeting: CNS 2009, 18–23 July 2009, Berlin, Germany.

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Abstract

A standard approach to localization, recall and prediction from sensors is the Hidden Markov Model (HMM, [1]), with location as hidden state and sense data as observations. Assuming that hippocampus performs a similar task, we present a new top-down mapping of this function onto its anatomy. In localization models of CA3 [2], firing rates of individual place cells encode probabilities over current location and recurrent connections may represent transitions probabilities between them. In auto-associative models [3], recurrent connections bring the network into a vector-coded memorized state. The existence of cells encoding rewards and locations of external objects supports this view [3].

Item Type: Conference or Workshop Item (Poster)
Copyright, Publisher and Additional Information: © 2009 Fox and Prescott; licensee BioMed Central Ltd.
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield)
Depositing User: Sheffield Import
Date Deposited: 05 Oct 2009 10:30
Last Modified: 08 Oct 2009 09:43
Published Version: http://www.biomedcentral.com/1471-2202/10/S1/P275
Status: Published
URI: http://eprints.whiterose.ac.uk/id/eprint/9649

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