title: A neuromorphic VLSI design for spike timing and rate based synaptic plasticity.
abstract: Triplet-based Spike Timing Dependent Plasticity (TSTDP) is a powerful synaptic plasticity rule that acts beyond conventional pair-based STDP (PSTDP). Here, the TSTDP is capable of reproducing the outcomes from a variety of biological experiments, while the PSTDP rule fails to reproduce them. Additionally, it has been shown that the behaviour inherent to the spike rate-based Bienenstock-Cooper-Munro (BCM) synaptic plasticity rule can also emerge from the TSTDP rule. This paper proposes an analogue implementation of the TSTDP rule. The proposed VLSI circuit has been designed using the AMS 0.35 μm CMOS process and has been simulated using design kits for Synopsys and Cadence tools. Simulation results demonstrate how well the proposed circuit can alter synaptic weights according to the timing difference amongst a set of different patterns of spikes. Furthermore, the circuit is shown to give rise to a BCM-like learning rule, which is a rate-based rule. To mimic an implementation environment, a 1000 run Monte Carlo (MC) analysis was conducted on the proposed circuit. The presented MC simulation analysis and the simulation result from fine-tuned circuits show that it is possible to mitigate the effect of process variations in the proof of concept circuit; however, a practical variation aware design technique is required to promise a high circuit performance in a large scale neural network. We believe that the proposed design can play a significant role in future VLSI implementations of both spike timing and rate based neuromorphic learning systems.
authors.affiliation: School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia. mostafa@eleceng.adelaide.edu.au
authors.forename: Mostafa
authors.initials: M
authors.lastname: Rahimi Azghadi
authors.forename: Said
authors.initials: S
authors.lastname: Al-Sarawi
authors.forename: Derek
authors.initials: D
authors.lastname: Abbott
authors.forename: Nicolangelo
authors.initials: N
authors.lastname: Iannella
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001185:Artificial Intelligence; D006801:Humans; D009473:Neuronal Plasticity; D009474:Neurons / Q000502:physiology*; D009716:Numerical Analysis, Computer-Assisted / Q000295:instrumentation*; D012666:Semiconductors; D013569:Synapses / Q000502:physiology*; D013997:Time Factors
keywords: BCM; Neuromorphic VLSI; Rate based plasticity; Spike timing dependent plasticity; Synaptic plasticity