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

M. Giulioni, Patrick Camilleri, Vittorio Dante, D. Badoni, Giacomo Indiveri, Jochen Braun, Paolo Del Giudice

2008 · 31 citations · 12 references

Concepts

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.

References

12