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The temporal noisy-leaky integrator neuron with additional inhibitory inputs

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New Trends in Neural Computation (IWANN 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 686))

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Abstract

The Temporal Noisy-Leaky Integrator (TNLI) neuron model with additional inhibitory inputs is presented together with its theoretical mathematical basis. The TNLI is a biologically inspired hardware neuron which models temporal features of real neurons like the temporal summation of the dendritic postsynaptic response currents of controlled delay and duration and the decay of the somatic potential due to its membrane leak. In addition, it models the stochastic neurotransmiller release by the synapses of real neurons, as pRAMs are used at each input. Using the TNLI, we investigated the effect of synoptic integration between excitatory and inhibitory inputs on the transfer function of the neuron. We observed that inhibitory inputs increase the fluctuations of the input current and reduce the slope of the sigmoidal transfer function of the neuron, which highlights one of the differences between biological neurons and formal neurons.

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Author information

Authors and Affiliations

  1. Department of Electronic and Electrical Engineering, King's College London, WC2R 2LS, Strand, London, UK

    Chris Christodoulou & Trevor G Clarkson

  2. Department of Mathematics, King's College London, WC2R 2LS, Strand, London, UK

    Guido Bugmann & John G Taylor

Authors
  1. Chris Christodoulou
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  2. Guido Bugmann
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  3. Trevor G Clarkson
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  4. John G Taylor
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Editor information

José Mira Joan Cabestany Alberto Prieto

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© 1993 Springer-Verlag Berlin Heidelberg

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Christodoulou, C., Bugmann, G., Clarkson, T.G., Taylor, J.G. (1993). The temporal noisy-leaky integrator neuron with additional inhibitory inputs. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_189

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  • DOI: https://doi.org/10.1007/3-540-56798-4_189

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56798-1

  • Online ISBN: 978-3-540-47741-9

  • eBook Packages: Springer Book Archive

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