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- Title
Intrinsic Organization of the Anesthetized Brain.
- Authors
Zhifeng Liang; King, Jean; Nanyin Zhang
- Abstract
The neural mechanism of unconsciousness has been a major unsolved question in neuroscience despite its vital role in brain states like coma and anesthesia. The existing literature suggests that neural connections, information integration, and conscious states are closely related. Indeed, alterations in several important neural circuitries and networks during unconscious conditions have been reported. However, how the whole-brain network is topologically reorganized to support different patterns of information transfer during unconscious states remains unknown. Here we directly compared whole-brain neural networks in awake and anesthetized states in rodents. Consistent with our previous report, the awake rat brain was organized in a nontrivial manner and conserved fundamental topological properties in a way similar to thehumanbrain. Strikingly, these topological features were well maintained in the anesthetized brain. Local neural networks in the anesthetized brain were reorganized with altered local network properties. The connectional strength between brain regions was also considerably different between the awake and anesthetized conditions. Interestingly, we found that long-distance connections were not preferentially reduced in the anesthetized condition, arguing against the hypothesis that loss of long-distance connections is characteristic to unconsciousness. These findings collectively show that the integrity of the whole-brain network can be conserved between widely dissimilar physiologic states while local neural networks can flexibly adapt to new conditions. They also illustrate that the governing principles of intrinsic brain organization might represent fundamental characteristics of the healthy brain. With the unique spatial and temporal scales of resting-state fMRI, this study has opened a new avenue for understanding the neural mechanism of (un)consciousness.
- Subjects
LOSS of consciousness; BIOLOGICAL neural networks; KNOWLEDGE transfer; TOPOLOGICAL property; ANESTHESIA in neurology
- Publication
Journal of Neuroscience, 2012, Vol 32, Issue 30, p10183
- ISSN
0270-6474
- Publication type
Article
- DOI
10.1523/JNEUROSCI.1020-12.2012