Journal article
Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study
L Duan, NT Van Dam, H Ai, P Xu
Translational Psychiatry | SPRINGERNATURE | Published : 2020
Abstract
Although state anxiety has been characterized by hyper-responsive subcortical activity and its bottom-up connectivity with cortical regions, the role of cortical networks in state anxiety is not yet well understood. To this end, we decoded individual state anxiety by using a machine-learning approach based on resting-state functional connectivity (RSFC) with functional near-infrared spectroscopy (fNIRS). Our results showed that the RSFC among a set of cortical networks were highly predictive of state anxiety, rather than trait anxiety. Specifically, these networks included connectivity between cortical areas in the default mode network (DMN) and dorsal attention network (DAN), and connectivi..
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Awarded by China Association for Science and Technology
Funding Acknowledgements
This work was supported by the National Natural Science Foundation of China (31530031, 61503030, 31871137, 31700959, 31920103009, and 31671133), Young Elite Scientists Sponsorship Program by China Association for Science and Technology (YESS2018), Guangdong International Scientific Collaboration Project (2019A050510048), Guangdong Key Basic Research Grant (2018B030332001), Guangdong young Innovative Talent Project (2016KQNCX149), Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team grant (2016ZT06S220), Guangdong University Innovation Team Project (2015KCXTD009), Guangdong Basic and Applied Research Major Project (2016KZDXM009), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2019SHIBS0003), Shenzhen Science and Technology Research Funding Program (JCYJ20180305124819889, JCYJ20180507183500566, JCYJ20150729104249783, and CYJ20170412164413575) and Shenzhen Peacock Program (827-000235, KQTD2015033016104926).