Social anxiety disorder (SAD) is a prevalent disabling psychiatric condition, for which the underlying neurobiological mechanisms remain poorly understood. Herein, we used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra- and inter-network functional network connectivity (FNC), as well as their associations with clinical characteristics and their potential diagnostic value. As a result, we observed widespread intra-/inter-network FNC abnormalities among high-order and primary perceptual RSNs in SAD, which were correlated to the symptom severity and illness duration, and allowed individual classification of SAD versus healthy controls with significant accuracy.
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Zhang et al. (2024) studied this question.
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