Spatiotemporal Pattern Recognition in Single Mixed-Signal VLSI Neurons with Heterogeneous Dynamic Synapses
This work addresses the problem of energy efficiency in neuromorphic processors for researchers and engineers in low-power computing, though it is incremental as it builds on prior hardware implementations.
The paper tackled the challenge of efficiently using heterogeneous analog neurosynaptic circuitry in neuromorphic hardware by implementing a thalamocortically inspired Spatiotemporal Correlator neural network with balanced excitatory-inhibitory disynaptic lateral connections, achieving a tenfold reduction in energy dissipation per lateral connection (0.65 nJ vs 9.6 nJ per spike) compared to previous delay-based implementations.
Mixed-signal neuromorphic processors with brain-like organization and device physics offer an ultra-low-power alternative to the unsustainable developments of conventional deep learning and computing. However, realizing the potential of such neuromorphic hardware requires efficient use of its heterogeneous, analog neurosynaptic circuitry with neurocomputational methods for sparse, spike-timing-based encoding and processing. Here, we investigate the use of balanced excitatory-inhibitory disynaptic lateral connections as a resource-efficient mechanism for implementing a thalamocortically inspired Spatiotemporal Correlator (STC) neural network without using dedicated delay mechanisms. We present hardware-in-the-loop experiments with a DYNAP-SE neuromorphic processor, in which receptive fields of heterogeneous coincidence-detection neurons in an STC network with four lateral afferent connections per column were mapped by random input-sampling. Furthermore, we demonstrate how such a neuron was tuned to detect a particular spatiotemporal feature by discrete address-reprogramming of the analog synaptic circuits. The energy dissipation of the disynaptic connections is one order of magnitude lower per lateral connection (0.65 nJ vs 9.6 nJ per spike) than in the former delay-based hardware implementation of the STC.