On electrical correlates of Physarum polycephalum spatial activity: Can we see Physarum Machine in the dark?

TL;DR

This study investigates the electrical activity of Physarum polycephalum, revealing complex oscillations linked to its behavior and demonstrating that computational models can replicate these signals for non-invasive analysis.

Contribution

The paper introduces a novel approach to analyze Physarum's electrical signals and validates a particle-based simulation that replicates its complex oscillatory behavior.

Findings

Electrical activity correlates with specific Physarum behaviors.

Simulation accurately reproduces oscillatory patterns and responses.

Potential for non-invasive health monitoring of living systems.

Abstract

Plasmodium of Physarum polycephalum is a single cell visible by unaided eye, which spans sources of nutrients with its protoplasmic network. In a very simple experimental setup we recorded electric potential of the propagating plasmodium. We discovered a complex interplay of short range oscillatory behaviour combined with long range, low frequency oscillations which serve to communicate information between different parts of the plasmodium. The plasmodium's response to changing environmental conditions forms basis patterns of electric activity, which are unique indicators of the following events: plasmodium occupies a site, plasmodium functions normally, plasmodium becomes `agitated' due to drying substrate, plasmodium departs a site, and plasmodium forms sclerotium. Using a collective particle approximation of Physarum polycephalum we found matching correlates of electrical potential in computational simulations by measuring local population flux at the node positions, generating trains of high and low frequency oscillatory behaviour. Motifs present in these measurements matched the response `grammar' of the plasmodium when encountering new nodes, simulated consumption of nutrients, exposure to simulated hazardous illumination and sclerotium formation. The distributed computation of the particle collective was able to calculate beneficial network structures and sclerotium position by shifting the active growth zone of the simulated plasmodium. The results show future promise for the non-invasive study of the complex dynamical behaviour within --- and health status of --- living systems.