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Spontaneous Brain Activity Emerges from Pairwise Interactions in the Larval Zebrafish Brain
Richard E Rosch1,2,3, Dominic R W Burrows4, Christopher W Lynn5
1Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Physical Review. X
|February 10, 2025
Summary
Researchers used a statistical mechanics model to understand how brain activity emerges from neural interactions. They found that pairwise neural connections explain whole-brain dynamics and can predict physiological and pathological brain states.
Area of Science:
- Neuroscience
- Statistical Mechanics
- Computational Biology
Background:
- Brain activity arises from complex interactions between individual neurons.
- Understanding large-scale brain dynamics requires analyzing whole-brain activity at single-neuron resolution.
- Calcium imaging offers in vivo whole-brain activity recordings crucial for studying emergent dynamics.
Purpose of the Study:
- To infer microscopic network features from collective brain activity patterns using a statistical mechanics approach.
- To relate inferred network features to the emergence of observed whole-brain dynamics in larval zebrafish.
- To identify key brain structures essential for maintaining physiological brain dynamics.
Main Methods:
- Application of the pairwise maximum entropy model to analyze neural activity data.
- Utilizing in vivo calcium imaging for whole-brain activity recordings in larval zebrafish.
- Performing virtual resection experiments to identify critical brain structures.
Main Results:
- Pairwise interactions between neural populations and their intrinsic activity states sufficiently explain observed whole-brain dynamics.
- Maximum entropy model-estimated pairwise relationships between neuronal populations strongly correlate with observed structural connectivity.
- Model simulations show that tuning pairwise neuronal interactions drives transitions between physiological and hyperexcitable brain states.
Conclusions:
- Whole-brain activity emerges from a complex dynamical system governed by connectivity between brain areas.
- The strength and topology of basins of attraction in brain dynamics are dependent on inter-areal connectivity.
- The pairwise maximum entropy model effectively infers network features and predicts brain dynamics.
