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Journal ArticleDOI

The criticality hypothesis: how local cortical networks might optimize information processing

John M. Beggs
- 13 Feb 2008 - 
- Vol. 366, Iss: 1864, pp 329-343
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TLDR
In this paper, the authors review recent experiments on networks of cortical neurons, showing that they appear to be operating near the critical point in a phase transition between total randomness and boring order, and suggest that criticality may allow cortical networks to optimize information processing.
Abstract
Early theoretical and simulation work independently undertaken by Packard, Langton and Kauffman suggested that adaptability and computational power would be optimized in systems at the ‘edge of chaos’, at a critical point in a phase transition between total randomness and boring order. This provocative hypothesis has received much attention, but biological experiments supporting it have been relatively few. Here, we review recent experiments on networks of cortical neurons, showing that they appear to be operating near the critical point. Simulation studies capture the main features of these data and suggest that criticality may allow cortical networks to optimize information processing. These simulations lead to predictions that could be tested in the near future, possibly providing further experimental evidence for the criticality hypothesis.

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The economy of brain network organization

TL;DR: It is proposed that brain organization is shaped by an economic trade-off between minimizing costs and allowing the emergence of adaptively valuable topological patterns of anatomical or functional connectivity between multiple neuronal populations.
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Spike avalanches in vivo suggest a driven, slightly subcritical brain state

TL;DR: The results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step.
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Are biological systems poised at criticality

TL;DR: This work reviews the surprising successes of this “inverse” approach to statistical mechanics models of biological systems directly from real data, using examples from families of proteins, networks of neurons, and flocks of birds.
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Broadband criticality of human brain network synchronization.

TL;DR: It is suggested that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal “avalanches” previously described in cellular systems.
Journal ArticleDOI

Are biological systems poised at criticality

TL;DR: In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data as discussed by the authors, and the surprising successes of this "inverse" approach, using examples from families of proteins, networks of neurons, and flocks of birds.
References
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TL;DR: It is shown that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point, and flicker noise, or 1/f noise, can be identified with the dynamics of the critical state.
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