Characterizing the firing properties of an adaptive analog VLSI neuron

Daniel Ben Rubin*, Elisabetta Chicca, Giacomo Indiveri

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)

Abstract

We describe the response properties of a compact, low power, analog circuit that implements a model of a leaky-Integrate & Fire (I&F) neuron, with spike-frequency adaptation, refractory period and voltage threshold modulation properties. We investigate the statistics of the circuit's output response by modulating its operating parameters, like refractory period and adaptation level and by changing the statistics of the input current. The results show a clear match with theoretical prediction and neurophysiological data in a given range of the parameter space. This analysis defines the chip's parameter working range and predicts its behavior in case of integration into large massively parallel very-large-scale-integration (VLSI) networks.

Original languageEnglish
Title of host publicationBiologically Inspired Approaches to Advanced Information Technology
EditorsAJ Ijspeert, M Murata, N Wakamiya
PublisherSpringer-Verlag Berlin Heidelberg
Pages189-200
Number of pages12
ISBN (Electronic)978-3-540-27835-1
ISBN (Print)978-3-540-23339-8
DOIs
Publication statusPublished - 2004
Externally publishedYes
Event1st International Workshop on Biologically Inspired Approaches to Advanced Information Technology - Lausanne, Switzerland
Duration: 29-Jan-200430-Jan-2004

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag Berlin Heidelberg
Volume3141
ISSN (Print)0302-9743

Conference

Conference1st International Workshop on Biologically Inspired Approaches to Advanced Information Technology
CountrySwitzerland
CityLausanne
Period29/01/200430/01/2004

Keywords

  • SPIKE-FREQUENCY ADAPTATION
  • FIRE NEURONS
  • NETWORKS

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