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December 2, 2025Scientific Reports2 citationsOpen Access

Cortical activation and functional connectivity during verbal fluency task in patients with chronic insomnia: a multi-channel fNIRS study

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YLYudiao LiangXWXiuli WangSZSha Zhang

Key Points

  • CID patients displayed reduced bilateral prefrontal activation during verbal fluency tasks, indicating impaired cognitive function and functional connectivity.
  • Specifically, activation in the left inferior frontal gyrus showed correlations with sleep latency and sleep duration, highlighting its role as a potential biomarker for CID.
  • Analysis employed multichannel fNIRS, revealing significant differences in hemodynamic responses when comparing patients with healthy controls.
  • The study demonstrates that integrated data from multiple prefrontal regions improves diagnostic accuracy, emphasizing the importance of a multi-modal approach for CID.

Abstract

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 (SFGL) 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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Cite This Study

Liang et al. (2025) studied this question.

synapsesocial.com/papers/692e3da16c9b3ab28c187ba4https://doi.org/10.1038/s41598-025-29365-9
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Also Consider

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