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A VLSI network of spiking neurons with plastic fully configurable "stop-learning" synapses


Giulioni, M; Camilleri, P; Dante, V; Badoni, D; Indiveri, G; Braun, J; Del Giudice, P (2008). A VLSI network of spiking neurons with plastic fully configurable "stop-learning" synapses. In: IEEE. 15th IEEE International Conference on Electronics, Circuits and Systems, 2008 (ICECS 2008), Malta, St. Julians, 31 August - 3 September 2008. Piscataway, NJ, US: IEEE Service Center, 678-681.

Abstract

We describe and demonstrate a neuromorphic, analog VLSI chip (termed F-LANN) hosting 128 integrate-and-fire (IF) neurons with spike-frequency adaptation, and 16,384 plastic bistable synapses implementing a self-regulated form of Hebbian, spike-driven, stochastic plasticity. The chip is designed to offer a high degree of reconfigurability: each synapse may be individually configured at any time to be either excitatory or inhibitory and to receive either recurrent input from an on-chip neuron or AER-based input from an off-chip neuron. The initial state of each synapse can be set as potentiated or depressed, and the state of each synapse can be read and stored on a computer.

We describe and demonstrate a neuromorphic, analog VLSI chip (termed F-LANN) hosting 128 integrate-and-fire (IF) neurons with spike-frequency adaptation, and 16,384 plastic bistable synapses implementing a self-regulated form of Hebbian, spike-driven, stochastic plasticity. The chip is designed to offer a high degree of reconfigurability: each synapse may be individually configured at any time to be either excitatory or inhibitory and to receive either recurrent input from an on-chip neuron or AER-based input from an off-chip neuron. The initial state of each synapse can be set as potentiated or depressed, and the state of each synapse can be read and stored on a computer.

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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Uncontrolled Keywords:neuromorphic
Language:English
Date:2008
Deposited On:06 Mar 2009 17:17
Last Modified:05 Apr 2016 13:10
Publisher:IEEE Service Center
ISBN:978-1-4244-2181-7
Additional Information:© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Publisher DOI:10.1109/ICECS.2008.4674944
Related URLs:http://www.icecs2008.org/ (Organisation)
Permanent URL: http://doi.org/10.5167/uzh-17603

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