Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-17603
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: Institute of Electrical and Electronics Engineers, [et al.]. 15th IEEE International Conference on Electronics, Circuits and Systems, 2008 (ICECS 2008), Malta, St. Julians, 31 August - 3 September 2008. Piscataway, NJ, US, 678-681. ISBN 978-1-4244-2181-7.
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.
|Item Type:||Book Section, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Neuroinformatics|
|DDC:||570 Life sciences; biology|
|Deposited On:||06 Mar 2009 17:17|
|Last Modified:||09 Jul 2012 03:44|
|Publisher:||IEEE Service Center|
|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.|
|Related URLs:||http://www.icecs2008.org/ (Organisation)|
Scopus®. Citation Count: 8
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