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Related Experiment Video

Updated: Nov 4, 2025

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

Optimal resilience of modular interacting networks.

Gaogao Dong^1,2,3, Fan Wang^4,1, Louis M Shekhtman⁵

¹School of Mathematical Sciences, Jiangsu University, 212013 Zhenjiang, Jiangsu, People's Republic of China.

Proceedings of the National Academy of Sciences of the United States of America

|May 26, 2021

Summary

Real-world networks have diverse coupling patterns, not just uniform ones. This study reveals an optimal fraction of interconnected nodes exists, enhancing network resilience against damage.

Keywords:

interacting network optimal phenomenon percolation resilience

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Area of Science:

Network science
Complex systems analysis
Systems resilience

Background:

Coupling in real-world systems significantly impacts network resilience and function.
Existing theoretical models often oversimplify coupling as homogeneous, neglecting diverse real-world patterns.

Purpose of the Study:

To develop frameworks for analyzing the resilience of modular networks with heterogeneous coupling patterns.
To investigate the impact of deterministic and random coupling patterns on network resilience.

Main Methods:

Developed two analytical and numerical frameworks to model modular networks.
Investigated varying fractions of interconnected nodes while keeping the total number of links constant.

Main Results:

Network resilience exhibits a non-monotonic transition point dependent on the fraction of interconnected nodes.
An optimal fraction of interconnected nodes was identified, maximizing system resilience and damage tolerance.

Conclusions:

The existence of an optimal interconnection fraction for maximizing network resilience is demonstrated across various coupling patterns.
Findings offer insights into optimizing network design based on specific coupling characteristics for enhanced robustness.