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International Conference on Artificial Neural Networks

ICANN 2008: Artificial Neural Networks - ICANN 2008 pp 238–247Cite as

Encoding and Retrieval in a CA1 Microcircuit Model of the Hippocampus

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5164))

Abstract

Recent years have witnessed a dramatic accumulation of knowledge about the morphological, physiological and molecular characteristics, as well as connectivity and synaptic properties of neurons in the mammalian hippocampus. Despite these advances, very little insight has been gained into the computational function of the different neuronal classes; in particular, the role of the various inhibitory interneurons in encoding and retrieval of information remains elusive. Mathematical and computational models of microcircuits play an instrumental role in exploring microcircuit functions and facilitate the dissection of operations performed by diverse inhibitory interneurons. A model of the CA1 microcircuitry is presented using biophysical representations of its major cell types: pyramidal, basket, axo-axonic, bistratified and oriens lacunosum-moleculare cells. Computer simulations explore the biophysical mechanisms by which encoding and retrieval of spatio-temporal input patterns are achieved by the CA1 microcircuitry. The model proposes functional roles for the different classes of inhibitory interneurons in the encoding and retrieval cycles.

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Author information

Authors and Affiliations

  1. Department of Computing Science and Mathematics, University of Stirling, Stirling, FK9 4LA, U.K.

    Vassilis Cutsuridis & Bruce P. Graham

  2. Division of Neuroscience and Biomedical Systems, University of Glasgow, Glasgow, G12 8QQ, U.K.

    Stuart Cobb

Authors
  1. Vassilis Cutsuridis
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  2. Stuart Cobb
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  3. Bruce P. Graham
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Véra Kůrková Roman Neruda Jan Koutník

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© 2008 Springer-Verlag Berlin Heidelberg

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Cutsuridis, V., Cobb, S., Graham, B.P. (2008). Encoding and Retrieval in a CA1 Microcircuit Model of the Hippocampus. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_25

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  • DOI: https://doi.org/10.1007/978-3-540-87559-8_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87558-1

  • Online ISBN: 978-3-540-87559-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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