Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning

Part of Advances in Neural Information Processing Systems 14 (NIPS 2001)

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A. Bofill, D. Thompson, Alan Murray


Experimental data has shown that synaptic strength modification in some types of biological neurons depends upon precise spike tim(cid:173) ing differences between presynaptic and postsynaptic spikes. Sev(cid:173) eral temporally-asymmetric Hebbian learning rules motivated by this data have been proposed. We argue that such learning rules are suitable to analog VLSI implementation. We describe an eas(cid:173) ily tunable circuit to modify the weight of a silicon spiking neuron according to those learning rules. Test results from the fabrication of the circuit using a O.6J.lm CMOS process are given.