Journal
PHYSICAL REVIEW LETTERS
Volume 108, Issue 20, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevLett.108.208102
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Funding
- Natural Sciences and Engineering Research Council of Canada
- National Science Foundation (NSF) Physics Frontier Center [0822613]
- NSF [POLS-1058291, CRCNS-0904912, DMR-1005209, CMG-0934491]
- JSPS
- Direct For Mathematical & Physical Scien
- Division Of Materials Research [1005209] Funding Source: National Science Foundation
- Directorate For Geosciences
- Div Atmospheric & Geospace Sciences [0934491] Funding Source: National Science Foundation
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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.
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