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Related Experiment Video

Updated: Jan 4, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Toward optimizing control signal paths in functional brain networks.

Peng Yao1, Xiang Li1

  • 1Adaptive Networks & Control Lab, and Research Center of Smart Networks & Systems, School of Information Science & Engineering, Fudan University, Shanghai 200433, China.

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Summary
This summary is machine-generated.

This study introduces optimal control signal paths in human brain networks to understand brain function and structure. Algorithms using control centrality identify efficient pathways, aiding in discovering neural pathways for cognitive progress.

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Area of Science:

  • Neuroscience
  • Network Science
  • Control Theory

Background:

  • Controlling human brain networks is crucial for understanding brain structure-function relationships.
  • Structural controllability offers tools to analyze these networks.
  • Identifying optimal control signal paths is key to understanding information flow and energy efficiency.

Purpose of the Study:

  • To define and identify optimal control signal paths in human brain networks.
  • To understand how control signals traverse networks with minimum energy.
  • To develop algorithms for finding the most effective control signal paths.

Main Methods:

  • Defining optimal control signal paths based on network nodes and connections.
  • Developing algorithms using control centrality to identify efficient paths.
  • Utilizing local control centrality for subnetworks and specific cognitive tasks.

Main Results:

  • Proposed algorithms effectively identify optimal control signal paths.
  • Control centrality quantifies path efficiency based on control energy.
  • Local control centrality aids in selecting efficient paths within functional subnetworks.

Conclusions:

  • Optimal control signal paths provide insights into brain network control and function.
  • Control centrality is a valuable metric for evaluating path efficiency.
  • This approach can help unveil neural pathways underlying cognitive processes.