Algorithm For 3D-Chemotaxis Using Spiking Neural Network

TL;DR

This paper presents an end-to-end spiking neural network algorithm inspired by chemotaxis for 3D media, enabling contour tracking based on klinokinesis principles, suitable for neuromorphic hardware implementation.

Contribution

It introduces a novel klinokinesis-based algorithm for 3D chemotaxis using simple LIF neurons, expanding capabilities beyond existing planar media solutions.

Findings

Successful contour tracking in 3D media using the proposed algorithm

Feasibility demonstrated with simple LIF neuron implementation

Potential for neuromorphic hardware deployment

Abstract

In this work, we aim to devise an end-to-end spiking implementation for contour tracking in 3D media inspired by chemotaxis, where the worm reaches the region which has the given set concentration. For a planer medium, efficient contour tracking algorithms have already been devised, but a new degree of freedom has quite a few challenges. Here we devise an algorithm based on klinokinesis - where the motion of the worm is in response to the stimuli but not proportional to it. Thus the path followed is not the shortest, but we can track the set concentration successfully. We are using simple LIF neurons for the neural network implementation, considering the feasibility of its implementation in the neuromorphic computing hardware.