Paper

Coarse--graining and hints of scaling in a population of 1000+ neurons

Brody, Carlos D, Bialek, William, Tank, David W, Meshulam, Leenoy, Gauthier, Jeffrey L

2018

Overview

In many systems we can describe emergent macroscopic behaviors, quantitatively, using models that are much simpler than the underlying microscopic interactions; we understand the success of this simplification through the renormalization group. Could similar simplifications succeed in complex biological systems? We develop explicit coarse-graining procedures that we apply to experimental data on the electrical activity in large populations of neurons in the mouse hippocampus. Probability distributions of coarse-grained variables seem to approach a fixed non-Gaussian form, and we see evidence of power-law dependencies in both static and dynamic quantities as we vary the coarse-graining scale over two decades. Taken together, these results suggest that the collective behavior of the network is described by a non-trivial fixed point.

• Publisher: Cornell University Library, arXiv.org
• Subject: Coarsening / Granulation / Neurons