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Related Experiment Video

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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Energy constraints on brain network formation.

Kosuke Takagi1

  • 1Unaffiliated, Saitama, Japan. coutakagi@gmail.com.

Scientific Reports
|June 4, 2021
PubMed
Summary

Brain network structures emerge from minimizing energy costs. This study shows that reducing wiring and activity costs strengthens connections, forming clusters similar to real brain networks.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Network Science

Background:

  • The brain's complex functionality arises from neuronal connections, but these processes incur significant energy costs.
  • Understanding how energy constraints shape neuronal network organization and formation is crucial but remains unclear.

Purpose of the Study:

  • To investigate the mechanism by which energy constraints influence the organization and formation of neuronal networks.
  • To demonstrate that cost minimization can reproduce characteristic brain network structures.

Main Methods:

  • Developed a simple computational model incorporating an activity-dependent cost function, balancing neuronal activity and wiring costs.
  • Simulated cost reduction within the model to observe emergent network properties.

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  • Compared model-generated network features with connectome datasets from real brains.

    • Main Results:

    • Cost minimization led to strengthened connections, particularly at highly active neuronal nodes.
    • The model reproduced the formation of large clusters, a characteristic feature of brain networks.
    • Statistical analysis confirmed similarities between the model's network features and real brain connectomes.

    Conclusions:

    • Energy constraints play a critical role in regulating brain network activity and structure.
    • The brain exhibits an efficient structure optimized for low energy expenditure in both activity and wiring.
    • Cost minimization principles provide a parsimonious explanation for observed brain network organization.