Universal Critical Dynamics in High Resolution Neuronal Avalanche Data
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Friedman-2012-Universal Critical Dynamics in High Resolution Neuronal Avalanche Data.pdf
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Author(s) • • • • • • •
Friedman, Nir
Ito, Shinya
Brinkman, Braden A. W.
Shimono, Masanori
DeVille, R. E. Lee
Dahmen, Karin A.
Beggs, John M.
Butler, Thomas Charles
Date Issued
May 2012
Journal
Physical Review Letters
Publisher
American Physical Society
Citation
Friedman, Nir et al. “Universal Critical Dynamics in High Resolution Neuronal Avalanche Data.” Physical Review Letters 108.20 (2012). © 2012 American Physical Society
Version
Final published version
Abstract
The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network data collected at the individual neuron level using the framework of nonequilibrium phase transitions. Among the most striking predictions confirmed is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Physics
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DOI of Published Version
https://doi.org/10.1103/PhysRevLett.108.208102