Analog CMOS synaptic learning circuits adapted from invertebrate biology

Analog CMOS circuits implementing abstractions of certain biological synaptic processes are presented. In particular, the circuits extract features of synaptic learning observed in the marine mollusk Aplysia. Two types of nonassociative learning, habituation and sensitization, as well as associative learning (classical conditioning), are modeled. The synaptic learning rules used by Aplysia are considerably more complex than those typically used in artificial neural networks (ANNs), leading to the speculation that additional biological detail may be beneficial in ANN models. The synaptic circuitry described is expected to be useful as a basic primitive in ANNs with higher order synapses and learning rules that perform temporal association of multiple inputs. >