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The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model

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Computational Systems Neurobiology

Abstract

The study of neuronal populations with regards to coding, computation and learning relies on its primary building bloc: the single neuron. Describing the activity of single neurons can be done by mathematical models of various complexity. In this chapter we start with the integrate-and-fire model, and then consider a set of enhancements so as to approach the behaviour of multiple types of real neurons.

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Authors and Affiliations

  1. Ecole Polytechnique Fédérale de Lausanne, Lausanne, 1015-EPFL, Switzerland

    Richard Naud & Wulfram Gerstner

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  1. Richard Naud
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  2. Wulfram Gerstner
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Correspondence to Richard Naud .

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  1. European Bioinformatics Institute, EMBL-Outstation-Hinxton, Wellcome Trust Genome Campus, Welcome-Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom

    N. Le Novère

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Naud, R., Gerstner, W. (2012). The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model. In: Le Novère, N. (eds) Computational Systems Neurobiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3858-4_6

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