Detecting causality in Plant electrical signal by a hybrid causal analysis approach

TL;DR

This paper introduces a hybrid causal analysis method combining Granger causality and transfer entropy to analyze plant electrical signals, revealing complex directional information flow in plant bioelectrical activity.

Contribution

It presents a novel combined approach for causal analysis that improves understanding of dynamic information flow in plant electrical signaling systems.

Findings

Direction of information flow is both longitudinal and transverse.

The hybrid method effectively reveals complex causal connectivities.

Plant electrical activity exhibits dynamic and multi-directional causal interactions.

Abstract

At present, multi-electrode array (MEA) approach and optical recording allow us to acquire plant electrical activity with higher spatio-temporal resolution. To understand the dynamic information flow of the electrical signaling system and estimate the effective connectivity, we proposed a solution to combine the two casualty analysis approaches, i.e. Granger causality and transfer entropy, which they complement each other to measure dynamics effective connectivity of the complex system. Our findings in three qualitatively different levels of plant bioelectrical activities revealed direction of information flow and dynamic complex causal connectives by using the two causal analysis approaches, especially indicated that the direction of information flow is not only along the longitudinal section but also spreading in transection.