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Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2016
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Title
Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness
Published in
Frontiers in Computational Neuroscience, January 2016
DOI 10.3389/fncom.2016.00001
Pubmed ID
Authors

Minkyung Kim, George A. Mashour, Stefanie-Blain Moraes, Giancarlo Vanini, Vijay Tarnal, Ellen Janke, Anthony G. Hudetz, Uncheol Lee

Abstract

Sleep, anesthesia, and coma share a number of neural features but the recovery profiles are radically different. To understand the mechanisms of reversibility of unconsciousness at the network level, we studied the conditions for gradual and abrupt transitions in conscious and anesthetized states. We hypothesized that the conditions for explosive synchronization (ES) in human brain networks would be present in the anesthetized brain just over the threshold of unconsciousness. To test this hypothesis, functional brain networks were constructed from multi-channel electroencephalogram (EEG) recordings in seven healthy subjects across conscious, unconscious, and recovery states. We analyzed four variables that are involved in facilitating ES in generic, non-biological networks: (1) correlation between node degree and frequency, (2) disassortativity (i.e., the tendency of highly-connected nodes to link with less-connected nodes, or vice versa), (3) frequency difference of coupled nodes, and (4) an inequality relationship between local and global network properties, which is referred to as the suppressive rule. We observed that the four network conditions for ES were satisfied in the unconscious state. Conditions for ES in the human brain suggest a potential mechanism for rapid recovery from the lightly-anesthetized state. This study demonstrates for the first time that the network conditions for ES, formerly shown in generic networks only, are present in empirically-derived functional brain networks. Further investigations with deep anesthesia, sleep, and coma could provide insight into the underlying causes of variability in recovery profiles of these unconscious states.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
United States 1 1%
Unknown 80 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 18%
Researcher 11 13%
Student > Bachelor 9 11%
Professor 6 7%
Student > Master 5 6%
Other 17 21%
Unknown 19 23%
Readers by discipline Count As %
Neuroscience 20 24%
Physics and Astronomy 7 9%
Medicine and Dentistry 7 9%
Agricultural and Biological Sciences 6 7%
Engineering 5 6%
Other 12 15%
Unknown 25 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2016.
All research outputs
#15,332,207
of 23,577,761 outputs
Outputs from Frontiers in Computational Neuroscience
#778
of 1,380 outputs
Outputs of similar age
#223,751
of 398,192 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#16
of 30 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 398,192 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.