A study on dynamics and multiscale complexity of a neuro system

TL;DR

This paper investigates the chaotic behavior and multiscale complexity of a neuro-system under various conditions, revealing how noise and music influence its dynamics through bifurcation analysis and a novel complexity measure.

Contribution

It introduces a multiscale complexity measure based on recurrence plot density entropy and analyzes the effects of noise and music on neuro-system dynamics.

Findings

White noise increases system complexity.

Music maintains dynamics similar to the original system.

Proposed complexity measure effectively captures multiscale changes.

Abstract

We explore the chaotic dynamics and complexity of a neuro-system with respect to variable synaptic weights in both noise free and noisy conditions. The chaotic dynamics of the system is investigated by bifurcation analysis and 0-1 test. A multiscale complexity of the system is proposed based on the notion of recurrence plot density entropy. Numerical results support the proposed analysis. Impact of music on the aforesaid neuro-system has also been studied. The analysis shows that inclusion of white noise even with a minimal strength makes the neuro dynamics more complex, where as music signal keeps the dynamics almost similar to that of the original system. This is properly interpreted by the proposed multiscale complexity measure.