Reliability of Event Timing in Silicon Neurons

TL;DR

This paper demonstrates that silicon neurons can reliably transmit spikes despite inherent noise and variability, drawing parallels with biological neurons, and showcases this with a neuromorphic bursting neuron model.

Contribution

It reveals that analog silicon neurons can achieve reliable spike transmission amidst PVT variations and noise, inspired by biological neuron behavior.

Findings

Reliable spike transmission is possible despite high noise levels.

Silicon neurons can transmit single spikes and bursts reliably.

The approach enables robust neuromorphic circuit design.

Abstract

Analog, low-voltage electronics show great promise in producing silicon neurons (SiNs) with unprecedented levels of energy efficiency. Yet, their inherently high susceptibility to process, voltage and temperature (PVT) variations, and noise has long been recognised as a major bottleneck in developing effective neuromorphic solutions. Inspired by spike transmission studies in biophysical, neocortical neurons, we demonstrate that the inherent noise and variability can coexist with reliable spike transmission in analog SiNs, similarly to biological neurons. We illustrate this property on a recent neuromorphic model of a bursting neuron by showcasing three different relevant types of reliable event transmission: single spike transmission, burst transmission, and the on-off control of a half-centre oscillator (HCO) network.