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International Conference on Artificial Neural Networks

ICANN 2006: Artificial Neural Networks – ICANN 2006 pp 750–759Cite as

Temporal Processing in a Spiking Model of the Visual System

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4131))

Abstract

Increasing amount of evidence suggests that the brain has the necessary mechanisms to and indeed does generate and process temporal information from the very early stages of sensory pathways. This paper presents a novel biologically motivated model of the visual system based on temporal encoding of the visual stimuli and temporally precise lateral geniculate nucleus (LGN) spikes. The work investigates whether such a network could be developed using an extended type of integrate-and-fire neurons (ADDS) and trained to recognise objects of different shapes using STDP learning. The experimental results contribute further support to the argument that temporal encoding can provide a mechanism for representing information in the visual system and has the potential to complement firing-rate-based architectures toward building more realistic and powerful models.

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Author information

Authors and Affiliations

  1. School of Computing and Technology, University of Sunderland, St. Peter’s Campus, Sunderland, SR6 0DD, United Kingdom

    Christo Panchev

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  1. Christo Panchev
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Editor information

Editors and Affiliations

  1. School of Electrical and Computer Engineering, Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, GR-157 80, Zographou, Greece

    Stefanos D. Kollias

  2. Department of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zographou, Greece

    Andreas Stafylopatis

  3. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  4. Adaptive Informatics Research Centre, Helsinki University of Technology, HUT, P.O. Box 5400, 02015, Finland

    Erkki Oja

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© 2006 Springer-Verlag Berlin Heidelberg

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Panchev, C. (2006). Temporal Processing in a Spiking Model of the Visual System. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_78

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  • DOI: https://doi.org/10.1007/11840817_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38625-4

  • Online ISBN: 978-3-540-38627-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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