DocumentCode :
3383887
Title :
A VLSI network of spiking neurons with plastic fully configurable “stop-learning” synapses
Author :
Giulioni, M. ; Camilleri, P. ; Dante, V. ; Badoni, D. ; Indiveri, G. ; Braun, J. ; Giudice, P. Del
fYear :
2008
fDate :
Aug. 31 2008-Sept. 3 2008
Firstpage :
678
Lastpage :
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.
Keywords :
VLSI; networks (circuits); VLSI network; integrate-and-fire neurons; plastic stop-learning synapses; spike-frequency adaptation; spiking neurons; Biological system modeling; Biology computing; Computational modeling; Dynamic range; Neuromorphics; Neurons; Plastics; Stochastic processes; Uniform resource locators; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Circuits and Systems, 2008. ICECS 2008. 15th IEEE International Conference on
Conference_Location :
St. Julien´s
Print_ISBN :
978-1-4244-2181-7
Electronic_ISBN :
978-1-4244-2182-4
Type :
conf
DOI :
10.1109/ICECS.2008.4674944
Filename :
4674944
Link To Document :
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