Journal article

Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study

Lian Duan, Nicholas T Van Dam, Hui Ai, Pengfei 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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Grants

Awarded by National Natural Science Foundation of China


Awarded by Young Elite Scientists Sponsorship Program by China Association for Science and Technology


Awarded by Guangdong International Scientific Collaboration Project


Awarded by Guangdong Key Basic Research Grant


Awarded by Guangdong young Innovative Talent Project


Awarded by Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team grant


Awarded by Guangdong University Innovation Team Project


Awarded by Guangdong Basic and Applied Research Major Project


Awarded by Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions


Awarded by Shenzhen Science and Technology Research Funding Program


Awarded by Shenzhen Peacock Program


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).