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

Author(s): Meshulam, Leenoy; Gauthier, Jeffrey L; Brody, Carlos D; Tank, David W; Bialek, William

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Abstract: 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.
Publication Date: 1-Jan-2019
Citation: Meshulam, Leenoy, et al. "Coarse--Graining and Hints of Scaling in a Population of 1000+ Neurons.", 2018.
Pages: 1-21
Type of Material: Journal Article
Journal/Proceeding Title: BioRxiv
Version: Author's manuscript

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