Granger causality for circular variables
Leonardo Angelini, Mario Pellicoro, and Sebastiano Stramaglia
TL;DR
This paper extends Granger causality analysis to systems of coupled circular variables, demonstrating its application on Kuramoto models and anesthetic state transitions to understand information flow.
Contribution
It introduces a modified Granger causality method tailored for circular variables and applies it to complex systems, highlighting its utility.
Findings
Effective detection of causality in circular variable systems
Application to Kuramoto oscillators on complex networks
Insights into information flow during anesthetic state transitions
Abstract
In this letter we discuss use of Granger causality to the analyze systems of coupled circular variables, by modifying a recently proposed method for multivariate analysis of causality. We show the application of the proposed approach on several Kuramoto systems, in particular one living on networks built by preferential attachment and a model for the transition from deeply to lightly anaesthetized states. Granger causalities describe the flow of information among variables.
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