Coarse Graining, Fixed Points, and Scaling in a Large Population of Neurons

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

doi:10.1103/PhysRevLett.123.178103

Coarse Graining, Fixed Points, and Scaling in a Large Population of Neurons

Phys Rev Lett. 2019 Oct 25;123(17):178103. doi: 10.1103/PhysRevLett.123.178103.

Authors

Leenoy Meshulam^{1

2

3}, Jeffrey L Gauthier¹, Carlos D Brody^{1

4

5}, David W Tank^{1

2

4}, William Bialek^{2

3

6}

Affiliations

¹ Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA.
² Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA.
³ Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.
⁴ Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.
⁵ Howard Hughes Medical Institute, Princeton University, Princeton, New Jersey 08544, USA.
⁶ Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, 365 Fifth Ave., New York, New York 10016, USA.

Abstract

We develop a phenomenological coarse-graining procedure for activity in a large network of neurons, and apply this to recordings from a population of 1000+ cells in the hippocampus. Distributions of coarse-grained variables seem to approach a fixed non-Gaussian form, and we see evidence of scaling in both static and dynamic quantities. These results suggest that the collective behavior of the network is described by a nontrivial fixed point.

MeSH terms

Animals
Hippocampus / cytology
Hippocampus / physiology*
Humans
Mice
Models, Neurological*
Nerve Net / cytology
Nerve Net / physiology
Neurons / cytology
Neurons / physiology*

Grants and funding

R01 EB026943/EB/NIBIB NIH HHS/United States