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2017 | OriginalPaper | Chapter

5. A New Approach to the Identification of Sensory Processing Circuits Based on Spiking Neuron Data

Author : Dorian Florescu

Published in: Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Publisher: Springer International Publishing

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Abstract

The cascade model, comprising a filter in series with a spiking neuron, have been widely used as representation for spiking neural circuits. Although the state-of-the-art identification methods for cascade models can accommodate a wide range of filters and spiking neurons, the assumptions proposed can in some cases be considered restrictive. Specifically, for [Filter]-[IF] circuits, it is assumed that the IF model is known, or that the filter output is available for measurement. In this chapter, two new identification methodologies are proposed for neural circuits comprising a linear or nonlinear filter in cascade with a spiking neuron. A [Nonlinear Filter]-[Ideal IF] circuit is reformulated as a scaled nonlinear filter in series with a modified ideal IF neuron. The identification is subsequently carried out by employing the NARMAX nonlinear system identification methodology to infer the structure and parameters of a discrete-time representation for the scaled nonlinear filter. An equivalent [Linear Filter]-[Leaky IF] circuit is identified, assuming that input-output measurements of the spiking neuron are not available and that all parameters are unknown. The leaky IF model is identified by solving an equation whose solution is proven to be unique. An algorithm is provided that computes the solution with arbitrary precision. Subsequently, the structure and parameters of the filter are inferred using the NARMAX identification methodology. Numerical simulations are given to test the performance of the new methods.

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previous chapter A Novel Reconstruction Framework in Shift-Invariant Spaces for Signals Encoded with Integrate-and-Fire Neurons
next chapter A New Method for Implementing Linear Filters in the Spike Domain
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Metadata
Title
A New Approach to the Identification of Sensory Processing Circuits Based on Spiking Neuron Data
Author
Dorian Florescu
Copyright Year
2017
Book
Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Print ISBN: 978-3-319-57080-8

Electronic ISBN: 978-3-319-57081-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-57081-5_5