Self-Organization of Diverse Directional Hierarchical Networks in Simple Coupled Maps with Connection Changes

TL;DR

This paper investigates how simple coupled maps with adaptive connection changes self-organize into various complex directional hierarchical networks, revealing four distinct types based on different parameter conditions.

Contribution

It introduces a comprehensive analysis of the morphology of self-organized networks in coupled maps, identifying four novel types of hierarchical structures formed through synchronization-dependent connection changes.

Findings

Four types of directional hierarchical networks identified

Self-organization depends on parameter values

Insights applicable to neural, biological, and social networks

Abstract

We comprehensively studied the morphology of the self-organized effective network structures that form in simple coupled maps with interelement synchronization-dependent connection changes. Based on the parameter values, the spontaneous formation of four types of directional hierarchical networks, named pair-driven networks, loop-driven networks, hidden trio-driven networks, and hidden community-driven networks, was observed. This study provides novel insights into the self-organized complex networks that form in neural networks, various other biological networks, and social networks.