Neural correlates of menopausal symptoms revealed by emotion-related fNIRS activity.

OBJECTIVE

Menopausal symptoms had a continuous impact on women's well-being, with mood disturbances representing a core manifestation. To further support treatment decisions, objective neurophysiological approaches are anticipated to facilitate routine assessments. This study utilized an emotional Free Association Semantic Task (FAST) alongside functional near-infrared spectroscopy (fNIRS) to identify neural correlates of menopausal symptoms, aiming to reveal potential biomarkers and underlying mechanisms.

METHODS

Sixty-four menopausal transitional women were recruited. A 48-channel fNIRS system was used to monitor frontal and bilateral temporal regions during the FAST, which required participants to generate word chains in response to emotional seed words of different valences (negative, positive, neutral). Spearman correlation analysis was employed to identify symptom-related spatiotemporal patterns in the fNIRS signals. Additional psychological scales were selected to validate the specificity of neural features correlated with menopausal symptoms, with the VFT and counting task as comparisons.

RESULTS

Neural correlates of menopausal symptoms, measured by the Kupperman Index (KMI), demonstrated significant valence-specific pattern during the FAST. Specifically, symptom severity was positively correlated with activation in the right dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) during the negative valence task, and with the left frontal eye fields (FEF) during the positive valence task. These neural correlates were distinct from those associated with depression, anxiety, and cognitive measures.

CONCLUSIONS

The fNIRS-based FAST shows promise as an objective tool for assessing menopausal symptoms. The valence-dependent lateralization effects provide novel insight into the neural mechanisms of menopause and may contribute to the development of symptom-specific neuromarkers.