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Neurosci Bull. 2018 Aug;34(4):592-604. doi: 10.1007/s12264-018-0243-5. Epub 2018 Jun 18.

Brain Network Studies in Chronic Disorders of Consciousness: Advances and Perspectives.

Song M1,2, Zhang Y1,2, Cui Y1,2,3, Yang Y4, Jiang T5,6,7,8,9,10.

Author information

1
National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
2
Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
3
University of Chinese Academy of Sciences, Beijing, 100190, China.
4
Department of Neurosurgery, PLA Army General Hospital, Beijing, 100700, China.
5
National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China. jiangtz@nlpr.ia.ac.cn.
6
Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China. jiangtz@nlpr.ia.ac.cn.
7
University of Chinese Academy of Sciences, Beijing, 100190, China. jiangtz@nlpr.ia.ac.cn.
8
CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, 100190, China. jiangtz@nlpr.ia.ac.cn.
9
Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China. jiangtz@nlpr.ia.ac.cn.
10
The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia. jiangtz@nlpr.ia.ac.cn.

Abstract

Neuroimaging has opened new opportunities to study the neural correlates of consciousness, and provided additional information concerning diagnosis, prognosis, and therapeutic interventions in patients with disorders of consciousness. Here, we aim to review neuroimaging studies in chronic disorders of consciousness from the viewpoint of the brain network, focusing on positron emission tomography, functional MRI, functional near-infrared spectroscopy, electrophysiology, and diffusion MRI. To accelerate basic research on disorders of consciousness and provide a panoramic view of unconsciousness, we propose that it is urgent to integrate different techniques at various spatiotemporal scales, and to merge fragmented findings into a uniform "Brainnetome" (Brain-net-ome) research framework.

KEYWORDS:

Brain network; Brainnetome; Disorders of consciousness; Neuroimaging

PMID:
29916113
PMCID:
PMC6060221
DOI:
10.1007/s12264-018-0243-5
[Indexed for MEDLINE]
Free PMC Article

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