Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study
AuthorDuan, L; Van Dam, NT; Ai, H; Xu, P
Source TitleTranslational Psychiatry
University of Melbourne Author/sVan Dam, Nicholas
AffiliationMelbourne School of Psychological Sciences
Document TypeJournal Article
CitationsDuan, L., Van Dam, N. T., Ai, H. & Xu, P. (2020). Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study. TRANSLATIONAL PSYCHIATRY, 10 (1), https://doi.org/10.1038/s41398-020-01088-7.
Access StatusOpen Access
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 connectivity within the DMN, which were negatively correlated with state anxiety; connectivity between cortical areas in the DMN and frontoparietal network (FPN), FPN and salience network (SN), FPN and DAN, DMN and SN, which were positively correlated with state anxiety. These findings suggest a predictive role of intrinsic cortical organization in the assessment of state anxiety. The work provides new insights into potential neural mechanisms of emotion states and implications for prognosis, diagnosis, and treatment of affective disorders.
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