functional and topological conditions for explosive synchronization develop in human brain networks with the onset of anesthetic-induced unconsciousness
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2016
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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 state 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 conditions that were previously reported as conditions for 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 for ES 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.
| Reference Key |
ekim2016frontiersfunctional
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| Authors | ;MinKyung eKim;MinKyung eKim;George A. Mashour;George A. Mashour;Stefanie eBlain-Moraes;Giancarlo eVanini;Vijay eTarnal;Ellen eJanke;Anthony G. Hudetz;Anthony G. Hudetz;Uncheol eLee;Uncheol eLee |
| Journal | population health management |
| Year | 2016 |
| DOI |
10.3389/fncom.2016.00001
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| URL | |
| Keywords |
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