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Competitive Interactions Shape Mammalian Brain Network Dynamics And Computation.

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Competitive Interactions Shape Mammalian Brain Network Dynamics And Computation.

Related Experiment Video

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains

Published on: January 16, 2026

Competitive interactions shape mammalian brain network dynamics and computation.

Andrea I Luppi^{1,2,3,4,5,6,7}, Yonatan Sanz Perl^8,9,10,11, Jakub Vohryzek^8,9,10,11

¹Department of Psychiatry and Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK. andrea.luppi@psych.ox.ac.uk.

Nature Neuroscience

|March 12, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

Brain network architecture balances cooperation and competition, with competitive interactions enhancing subject specificity and computational performance across species. This reveals key principles of mammalian brain organization.

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Area of Science:

Neuroscience
Computational Biology
Systems Neuroscience

Background:

The brain's ability to integrate information relies on complex network architectures.
Understanding how distributed circuits balance cooperative and competitive interactions is crucial for deciphering brain function.

Purpose of the Study:

To investigate the dynamical and computational relevance of cooperative and competitive interactions within the mammalian connectome using whole-brain modeling.
To determine how network architecture influences brain activity and computational performance.

Main Methods:

Computational whole-brain modeling applied to human, macaque, and mouse connectomes.
Analysis of emergent dynamical properties and subject-specific brain activity reproduction.

Main Results:

Mammalian brain activity is best reproduced by models combining modular cooperation with diffuse, long-range competition.
Competitive interactions preferentially link regions with opposing molecular and structural profiles.
Models incorporating competition demonstrate superior subject specificity and fit to brain activity dynamics, with these properties emerging spontaneously.

Conclusions:

A balance of cooperative and competitive interactions is fundamental to mammalian brain network architecture and function.
Competitive interactions are key to achieving subject-specific brain dynamics and enhanced computational performance.
This study establishes a generative link between network structure, dynamics, and computational capabilities in the brain.