Optical spike-timing-dependent plasticity with weight-dependent learning window and reward modulation

Abstract

Optical spike-timing-dependent plasticity (STDP) synapses form the basis of learning in photonic neuromorphic system. In biological neural systems, STDP synapses generally have multiplicative boundary mechanisms, and can be modulated by a third factor such as dopamine. Analogously, we introduce a third factor into optical STDP: The current-injection of semiconductor optical amplifiers can be modified in an adaptive way according to local or global feedback signals. The local one is present synaptic weight, which elicits an optical weight-dependent STDP, while the global one is a reward signal. We demonstrate that the optical weight-dependent STDP can emulate the behavior of biological STDP synapses more closely, and can be seen as an intermediate configuration between additive and multiplicative STDP, which balances stability and competition among synapses. Simulation studies with scalable photonic neurons further show that optical STDP with reward modulation enables reward-based reinforcement learning.