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Neuronal Avalanches Differ from Wakefulness to Deep Sleep – Evidence from Intracranial Depth Recordings in Humans

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Neuronal Avalanches Differ from Wakefulness to Deep Sleep – Evidence from Intracranial Depth Recordings in Humans
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002985
Pubmed ID
Authors

Viola Priesemann, Mario Valderrama, Michael Wibral, Michel Le Van Quyen

Abstract

Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches--spatiotemporal waves of enhanced activity--from dense intracranial depth recordings in humans. We showed that avalanche distributions closely follow a power law--the hallmark feature of SOC--for each vigilance state. However, avalanches clearly differ with vigilance states: slow wave sleep (SWS) shows large avalanches, wakefulness intermediate, and rapid eye movement (REM) sleep small ones. Our SOC model, together with the data, suggested first that the differences are mediated by global but tiny changes in synaptic strength, and second, that the changes with vigilance states reflect small deviations from criticality to the subcritical regime, implying that the human brain does not operate at criticality proper but close to SOC. Independent of criticality, the analysis confirms that SWS shows increased correlations between cortical areas, and reveals that REM sleep shows more fragmented cortical dynamics.

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Geographical breakdown

Country Count As %
Germany 3 2%
United Kingdom 2 1%
Brazil 1 <1%
France 1 <1%
Canada 1 <1%
Spain 1 <1%
Unknown 167 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 30%
Researcher 32 18%
Student > Master 22 13%
Student > Bachelor 11 6%
Professor > Associate Professor 9 5%
Other 23 13%
Unknown 26 15%
Readers by discipline Count As %
Neuroscience 43 24%
Agricultural and Biological Sciences 29 16%
Physics and Astronomy 28 16%
Psychology 11 6%
Medicine and Dentistry 8 5%
Other 21 12%
Unknown 36 20%