Characterizing the firing properties of an adaptive analog VLSI neuron

Ben Dayan Rubin D, Chicca E, Indiveri G (2004)
Biologically Inspired Approaches to Advanced Information Technology 3141: 189-200.

Download
OA
Journal Article | Published | English
Author
; ;
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.
Publishing Year
PUB-ID

Cite this

Ben Dayan Rubin D, Chicca E, Indiveri G. Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology. 2004;3141:189-200.
Ben Dayan Rubin, D., Chicca, E., & Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology, 3141, 189-200.
Ben Dayan Rubin, D., Chicca, E., and Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology 3141, 189-200.
Ben Dayan Rubin, D., Chicca, E., & Indiveri, G., 2004. Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology, 3141, p 189-200.
D. Ben Dayan Rubin, E. Chicca, and G. Indiveri, “Characterizing the firing properties of an adaptive analog VLSI neuron”, Biologically Inspired Approaches to Advanced Information Technology, vol. 3141, 2004, pp. 189-200.
Ben Dayan Rubin, D., Chicca, E., Indiveri, G.: Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology. 3141, 189-200 (2004).
Ben Dayan Rubin, D., Chicca, Elisabetta, and Indiveri, G. “Characterizing the firing properties of an adaptive analog VLSI neuron”. Biologically Inspired Approaches to Advanced Information Technology 3141 (2004): 189-200.
Main File(s)
Access Level
OA Open Access
Last Uploaded
2012-01-09 10:29:21

This data publication is cited in the following publications:
This publication cites the following data publications:

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Search this title in

Google Scholar