Sub-threshold CMOS Spiking Neuron Circuit Design for Navigation Inspired by C. elegans Chemotaxis

TL;DR

This paper presents a sub-threshold CMOS spiking neuron circuit inspired by C. elegans chemotaxis, enabling navigation and target tracking in noisy environments through biologically inspired gradient detection.

Contribution

It introduces a novel CMOS circuit for gradient detection based on C. elegans mechanisms, integrated into a neural network for navigation tasks.

Findings

Successful navigation and target tracking in noisy environments

VLSI implementation of gradient detector neurons

Robust circuit design for chemotaxis-inspired navigation

Abstract

We demonstrate a spiking neural network for navigation motivated by the chemotaxis network of Caenorhabditis elegans. Our network uses information regarding temporal gradients in the tracking variable's concentration to make navigational decisions. The gradient information is determined by mimicking the underlying mechanisms of the ASE neurons of C. elegans. Simulations show that our model is able to forage and track a target set-point in extremely noisy environments. We develop a VLSI implementation for the main gradient detector neurons, which could be integrated with standard comparator circuitry to develop a robust circuit for navigation and contour tracking.