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- Gu S, Satterthwaite TD, Medaglia JD, Yang M, Gur RE, Gur RC, Bassett DS. Emergence of system roles in normative neurodevelopment. Proc Natl Acad Sci U S A. 2015 Oct 19. pii: 201502829. [Epub ahead of print]
- Comment: Brain networks consist of different modules or subnetworks that are activated during various cognitive tasks. In this large study of 780 subjects between 8-22 years the authors show that modules display a characteristic pattern of development which is related to the function and topology of the modules. Individual variation of this pattern correlates with variation in cognitive performance.
- Barttfeld P, Bekinschtein TA, Salles A, Stamatakis EA, Adapa R, Menon DK, Sigman M. Factoring the brain signatures of anesthesia concentration and level of arousal across individuals.Neuroimage Clin. 2015 Sep 3;9:385-91.
- Comment: Resting-state functional brain networks were studied in subjects sedated with Propofol and their clinical level of consciousness was assessed. Factorial analysis showed that Propofol levels were associated with a frontal parietal loss of functional connectivity, while decreased responsiveness was associated with lower thalamic frontal, and higher thalamic temporal / occipital connectivity.
- Wu X, Zou Q, Hu J, Tang W, Mao Y, Gao L, Zhu J, Jin Y, Wu X, Lu L, Zhang Y, Zhang Y, Dai Z, Gao JH, Weng X, Zhou L, Northoff G, Giacino JT, He Y, Yang Y. Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury. J Neurosci. 2015 Sep 16;35(37):12932-46.
- Comment: Resting-state fMRI was used in 99 patients with acquired brain injury (ABI) with various levels of disturbed consciousness and healthy controls. Loss of functional connectivity of a subset of regions was correlated with loss of consciousness and outcome after three months. With support vector machine analysis recovery of consciousness could be predicted with an accuracy of 81.25%. The most predictive regions were the posterior cingulate gyrus and the precuneus. This study illustrates the importance of hub connectivity for consciousness, and the potential of machine learning applied to connectivity networks for clinical application.
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