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

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

Research output: Contribution to journal › Article › peer-review

62 Scopus citations

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.

Original language	English (US)
Article number	178103
Journal	Physical review letters
Volume	123
Issue number	17
DOIs	https://doi.org/10.1103/PhysRevLett.123.178103
State	Published - Oct 23 2019

All Science Journal Classification (ASJC) codes

General Physics and Astronomy

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10.1103/PhysRevLett.123.178103

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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.",

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AU - Tank, David W.

AU - Bialek, William

PY - 2019/10/23

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AB - 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.

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Coarse graining, fixed points, and scaling in a large population of neurons

Abstract

All Science Journal Classification (ASJC) codes

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