背景
焦慮症是最常見的情緒性精神疾病之一，其盛行率隨著現代社會壓力增加與生活步調加快而持續上升。腦影像技術已廣泛應用於探討焦慮症的神經相關機制。其中，功能性近紅外光譜儀（functional near-infrared spectroscopy, fNIRS）為近年來新興的一種非侵入性、可攜式且具良好時間解析度的神經影像工具，在研究與情緒與認知相關的大腦活動中展現潛力，亦被視為具臨床應用前景的精神疾病診斷與療效監測技術。然而，目前針對廣泛性焦慮症（generalized anxiety disorder, GAD）於不同認知任務中的 fNIRS 反應進行系統性比較的研究仍相對有限。因此，本研究旨在探討 fNIRS 應用於評估 GAD 前額葉活化特徵的可行性，以建立一套結合認知任務與前額葉活化模式之分析框架。本研究亦初步探討此分析框架應用於 GAD 腦刺激治療療效監測之潛力。
方法
本研究設計旨在驗證 fNIRS 是否能有效區分 GAD 患者在執行認知任務時的前額葉活化模式。研究共招募 28 位 GAD 患者與 36 位健康對照者，參與四項認知任務：言語流暢性（verbal fluency task, VF）、序列減法（serial subtraction task, SS）、1-back 工作記憶（1-back working memory task, WM）與 Go/No-Go（GNG），並同步記錄臨床量表與前額葉的氧合血紅素濃度（HbO）變化。
實驗於台大醫院與台北醫學大學附設醫院進行，腦影像量測分別使用 NIRScout 與 NIRSport2 系統，取樣頻率分別為 7.81 Hz 與 10.14 Hz，並使用 23 個通道覆蓋整體前額葉區域，涵蓋腹內側前額葉皮質（ventromedial prefrontal cortex, vmPFC）至背外側前額葉皮質（dorsolateral prefrontal cortex, dlPFC）等區域。
資料分析包含血流動力反應函數（hemodynamic response function, HRF）分析與時域特徵指標的提取，並進行獨立樣本 t 檢定以比較組間差異。由於兩組資料皆符合常態與獨立假設，因此進一步採用高斯混合模型（Gaussian Mixture Model, GMM）進行聚類分析，以辨識潛在的焦慮程度子群體。
此外，有兩位 GAD 受試者於兩週內完成共十次的高精度經顱電刺激（high-definition transcranial electrical stimulation, HD-tES）治療，並於治療前、中、後及一週後進行 SS 與 GNG 任務，同步記錄 fNIRS 數據。
結果與結論
結果顯示，在四項任務中皆可觀察到 GAD 與健康組之間的顯著差異，其中以 GNG 任務在臨床量表與神經活化方面差異最為顯著。GAD 組在GNG任務中以vmPFC表現出異常活化，並伴隨明顯的半球偏側化現象；在 VF 與 SS 任務中，GAD 組於dlPFC等區域呈現較低的活化程度。
聚類分析結果顯示，所有任務皆能辨識出以健康者為主的群體，唯有 GNG 任務能有效區分出高與低焦慮程度的子群體。在高焦慮群中，亦觀察到顯著的偏側化現象，且此現象並非單純的左右對稱，而呈現出前後位置的微妙對應差異。研究同時發現，無論左側或右側主導的活化樣態皆存在，顯示焦慮相關的大腦活化模式具多樣性與方向性。
此外，腦刺激治療療效監測之初步結果顯示，fNIRS 衍生指標在治療期間呈現明顯變化，顯示其具作為治療反應監測生物標記的潛力。
總結而言，本研究確認 GNG 任務結合 fNIRS 指標，在辨識 GAD 前額葉活化變化上具有高度敏感性。研究結果支持 fNIRS 與適當認知任務結合之應用，未來有望作為焦慮症診斷與治療監測的有效輔助工具。

Background:
Anxiety disorders are among the most common emotional psychiatric conditions, with prevalence rates increasing due to modern societal pressures and accelerated lifestyles. Neuroimaging techniques have been widely used to investigate the neural mechanisms underlying anxiety disorders. Among these, functional near-infrared spectroscopy (fNIRS) has emerged as a non-invasive, portable, and temporally precise neuroimaging tool. fNIRS has shown great potential in studying brain activity related to emotion and cognition and is considered promising for clinical applications such as psychiatric diagnosis and treatment monitoring. However, systematic comparisons of fNIRS responses in individuals with generalized anxiety disorder (GAD) across different cognitive tasks remain limited. Therefore, this study aims to explore the feasibility of using fNIRS to assess prefrontal activation patterns in GAD and to establish an analytical framework that integrates cognitive tasks with prefrontal activation profiles. Additionally, the study preliminarily investigates the potential of this framework in monitoring treatment responses to brain stimulation in GAD.
Methods:
This study was designed to evaluate whether fNIRS can effectively distinguish prefrontal activation patterns in GAD patients during cognitive task performance. A total of 28 individuals with GAD and 36 healthy controls participated in four cognitive tasks: verbal fluency task (VF), serial subtraction task (SS), 1-back working memory task (WM), and Go/No-Go task (GNG). Concurrently, clinical scale scores and changes in oxyhemoglobin concentration (HbO) in the prefrontal cortex were recorded.
Experiments were conducted at National Taiwan University Hospital and Taipei Medical University Hospital. Brain imaging data were acquired using the NIRScout and NIRSport2 systems, with sampling rates of 7.81 Hz and 10.14 Hz, respectively. A total of 23 channels covering the entire prefrontal cortex—including the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC)—were employed.
Data analysis included hemodynamic response function (HRF) analysis and time-domain feature extraction, followed by independent sample t-tests to compare between groups. Since both datasets met normality and independence assumptions, Gaussian Mixture Model (GMM) clustering was further applied to identify potential anxiety-related subgroups.
Additionally, two GAD participants underwent ten sessions of high-definition transcranial electrical stimulation (HD-tES) within two weeks. fNIRS data were recorded during SS and GNG tasks before, during, after, and one week post-treatment.
Results and Conclusion:
Significant differences in prefrontal activation between the GAD and healthy control groups were observed across all four tasks, with the GNG task showing the most prominent group differences in both clinical and neural responses. During the GNG task, GAD participants exhibited abnormal activation in the vmPFC, accompanied by a distinct hemispheric lateralization pattern. In the VF and SS tasks, reduced activation in regions such as the dlPFC was noted in the GAD group. Clustering analysis revealed that all tasks could identify a subgroup primarily composed of healthy controls. Notably, only the GNG task effectively distinguished between high- and low-anxiety subgroups. In the high-anxiety group, a significant lateralization pattern was also observed, characterized not merely by left-right asymmetry but by subtle anterior-posterior spatial differences. Both left- and right-dominant activation patterns were identified, indicating that anxiety-related brain activation patterns are diverse and directionally specific. Furthermore, preliminary results from brain stimulation monitoring showed clear changes in fNIRS-derived indicators throughout the treatment process, suggesting their potential as biomarkers for treatment response.
In summary, this study confirms that the GNG task, when combined with fNIRS measures, demonstrates high sensitivity in detecting prefrontal activation changes in GAD. The findings support the application of fNIRS with task-based paradigms as a promising auxiliary tool for anxiety disorder diagnosis and treatment monitoring.

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