Cortical network characteristics in post-stroke anxiety: an fNIRS-based study

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Authors: Xue Qian, Qinglei Wang, Jie Wang, Ling Yang, Ayan Geng, Wenjie Xu, Gengjuan Dong, Tianqi Lu, Chuan Guo
Cited by: 0
References: 43

Abstract

Objective: To examine prefrontal hemodynamic changes in patients with post-stroke anxiety (PSA), both at rest and during cognitive task engagement, with the aim of elucidating the underlying neural mechanisms of PSA and identifying potential neural correlates for clinical application. Methods: Fifty patients with PSA and 45 post-stroke patients without anxiety symptoms were recruited. PSA was diagnosed using the Hamilton Anxiety Rating Scale (HAMA ≥ 7), and comorbid depression was screened using the 17-item Hamilton Depression Rating Scale (HAMD-17 ≥ 8). Patients with significant cognitive impairment were excluded. Functional near-infrared spectroscopy (fNIRS) was used to measure resting-state functional connectivity in the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC), as well as task-evoked activation during the verbal fluency task (VFT). Demographic and clinical characteristics showed no significant differences between groups except for stroke type. Between-group comparisons were conducted to identify PSA-related differences in prefrontal network characteristics. Subgroup analyses were performed to explore the influence of comorbid depression on neural alterations. Results: > 0.05). Conclusion: Reduced activation in the bilateral FPC may represent a key neural substrate associated with post-stroke anxiety. In addition, altered activation patterns in the bilateral FPC and left DLPFC may reflect neural correlates related to depressive symptoms in patients with PSA, providing candidate targets for future mechanistic and clinical studies.

Fields of Study & Subjects

Stroke Rehabilitation and Recovery Functional Brain Connectivity Studies Optical Imaging and Spectroscopy Techniques

Publication details

Journal / source
Frontiers in Neuroscience
Volume
19
Pages
1708752–1708752
Publication date
16 January 2026
Language
EN