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Maximum Entropy Principle Underlies Wiring Length Distribution in Brain Networks
Yuru Song1, Douglas Zhou2,3,4, Songting Li2,3,4
1Neuroscience Graduate Program, University of California, San Diego, CA, USA.
Cerebral Cortex (New York, N.Y. : 1991)
|May 17, 2021
Summary
Brain networks maximize entropy to diversify connections, balancing short and long wiring lengths. This principle, constrained by space and resources, explains wiring patterns across species and guides network formation.
Area of Science:
- Neuroscience
- Computational Biology
- Network Science
Background:
- Brain networks feature a mix of short- and long-range connections.
- The proportion of long-range connections varies significantly across species.
- Underlying principles governing brain network wiring length distributions are not fully understood.
Purpose of the Study:
- To investigate the fundamental principles governing brain network wiring length distributions.
- To determine if brain connectivity follows a universal organizational principle.
- To develop a biologically plausible model for brain network formation.
Main Methods:
- Quantified structural diversity using Shannon's entropy.
- Analyzed wiring length distributions in five species: Drosophila, mouse, macaque, human, and C. elegans.
- Proposed a network formation process based on stochastic axonal growth and the maximum entropy principle (MAP).
- Developed a generative model incorporating MAP to simulate brain networks.
Main Results:
- Brain wiring length distributions across species adhere to the maximum entropy principle (MAP).
- MAP is constrained by limited wiring material and the spatial arrangement of neurons or brain areas.
- A proposed network formation process successfully reproduced observed wiring length distributions.
- A generative model based on MAP created networks highly similar to real brain networks.
Conclusions:
- Brain connectivity evolves towards structural diversity by maximizing entropy.
- This maximization supports efficient interareal communication.
- The maximum entropy principle offers a potential organizational framework for understanding brain network architecture.
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