Biological networks exhibit complex, coordinated patterns of activity. Can these patterns be captured precisely in simple models? Here we use measurements of simultaneous activity in 1000+ neurons in the mouse brain to test the validity of models grounded in statistical physics. When cells are dense samples from a small region, we find extremely detailed quantitative agreement between theory and experiment; sparse samples from larger regions lead to model failures. These results show we can aspire to more than qualitative agreement between simplifying theoretical ideas and the detailed behavior of a complex biological system.
@article{arxiv.2112.14735,
title = {Successes and failures of simple statistical physics models for a network of real neurons},
author = {Leenoy Meshulam and Jeffrey L. Gauthier and Carlos D. Brody and David W. Tank and William Bialek},
journal= {arXiv preprint arXiv:2112.14735},
year = {2023}
}