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Functional connectivity and hemodynamic responses during verbal fluency tasks reveal chronic insomnia biomarkers, suggesting a multivariate model enhances diagnostic capacity.
Chronic insomnia disorder (CID) is associated with verbal fluency deficits linked to abnormal prefrontal activation. This multichannel functional near-infrared spectroscopy (fNIRS) study compared prefrontal hemodynamic responses and functional connectivity during verbal fluency tasks (VFT) in 81 CID patients versus 100 healthy controls (HC). Cortical activation patterns and interregional connectivity were analyzed using general linear modeling and correlation matrices. CID patients exhibited significantly reduced bilateral prefrontal activation (p < 0.01), particularly in the left inferior frontal gyrus (IFG), middle frontal gyrus (MFG), and superior frontal gyrus (SFG), alongside 32-45% weaker functional connectivity compared to HC. Activation in left IFG correlated negatively with sleep latency (r=-0.32) and positively with sleep duration (r = 0.28), while right SFG activation positively associated with sleep efficiency (r = 0.31) in CID patients. Receiver operating characteristic analysis demonstrated that activation in the left superior frontal gyrus (SFG_L) alone provided fair to good discriminative capacity (AUC = 0.79). Crucially, following constructive reviewer feedback, we found that a multivariate model integrating all six prefrontal ROIs achieved a higher AUC of 0.84. Most impressively, a combined model that further incorporated behavioral performance and clinical scale scores yielded excellent discrimination (AUC = 0.91). This underscores a critical finding: while fNIRS-derived prefrontal activation is a powerful biomarker in its own right, its true clinical potential is unlocked when integrated into a multi-modal framework that captures the cognitive and affective dimensions of the disorder. These results strongly suggest that such an integrated approach, rather than relying on any single metric, is the most promising path for developing objective diagnostic aids for CID.
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Liang et al. (2025) studied this question.
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