Spontaneous brain activity emerges from pairwise interactions in the larval zebrafish brain

TL;DR

This study demonstrates that pairwise neural interactions are sufficient to explain and predict large-scale brain activity patterns in larval zebrafish, linking microscopic interactions to global dynamics and critical states.

Contribution

The paper introduces a maximum entropy model to connect pairwise neural interactions with whole-brain activity and critical transitions in larval zebrafish.

Findings

Pairwise interactions explain observed brain dynamics.

Structural connectivity correlates with inferred interactions.

Tuning interactions induces transitions between critical and hyper-excitable states.

Abstract

Brain activity is characterized by brain-wide spatiotemporal patterns which emerge from synapse-mediated interactions between individual neurons. Calcium imaging provides access to in vivo recordings of whole-brain activity at single-neuron resolution and, therefore, allows the study of how large-scale brain dynamics emerge from local activity. In this study, we used a statistical mechanics approach - the pairwise maximum entropy model (MEM) - to infer microscopic network features from collective patterns of activity in the larval zebrafish brain, and relate these features to the emergence of observed whole-brain dynamics. Our findings indicate that the pairwise interactions between neural populations and their intrinsic activity states are sufficient to explain observed whole-brain dynamics. In fact, the pairwise relationships between neuronal populations estimated with the MEM strongly correspond to observed structural connectivity patterns. Model simulations also demonstrated how tuning pairwise neuronal interactions drives transitions between critical and pathologically hyper-excitable whole-brain regimes. Finally, we use virtual resection to identify the brain structures that are important for maintaining the brain in a critical regime. Together, our results indicate that whole-brain activity emerges out of a complex dynamical system that transitions between basins of attraction whose strength and topology depend on the connectivity between brain areas.