Background. Transient ischemic attack (TIA) is a known risk factor for stroke. Abnormal alterations in the low-frequency range of the gray matter (GM) of the brain have been studied in patients with TIA. However, whether there are abnormal neural activities in the low-frequency range of the white matter (WM) in patients with TIA remains unknown. The current study applied two resting-state metrics to explore functional abnormalities in the low-frequency range of WM in patients with TIA. Furthermore, a reinforcement learning method was used to investigate whether altered WM function could be a diagnostic indicator of TIA. Methods. We enrolled 48 patients with TIA and 41 age- and sex-matched healthy controls (HCs). Resting-state functional magnetic resonance imaging (rs-fMRI) and clinical/physiological/biochemical data were collected from each participant. We compared the group differences between patients with TIA and HCs in the low-frequency range of WM using two resting-state metrics: amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The altered ALFF and fALFF values were defined as features of the reinforcement learning method involving a -learning algorithm. Results. Compared with HCs, patients with TIA showed decreased ALFF in the right cingulate gyrus/right superior longitudinal fasciculus/left superior corona radiata and decreased fALFF in the right cerebral peduncle/right cingulate gyrus/middle cerebellar peduncle. Based on these two rs-fMRI metrics, an optimal -learning model was obtained with an accuracy of 82.02%, sensitivity of 85.42%, specificity of 78.05%, precision of 82.00%, and area under the curve (AUC) of 0.87. Conclusion. The present study revealed abnormal WM functional alterations in the low-frequency range in patients with TIA. These results support the role of WM functional neural activity as a potential neuromarker in classifying patients with TIA and offer novel insights into the underlying mechanisms in patients with TIA from the perspective of WM function.

中文翻译：

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短暂性脑缺血发作患者的白质功能异常：强化学习方法

背景。短暂性脑缺血发作 (TIA) 是已知的中风危险因素。已经在 TIA 患者中研究了大脑灰质 (GM) 低频范围的异常变化。然而，TIA患者白质（WM）低频范围内是否存在异常神经活动尚不清楚。目前的研究应用了两个静息状态指标来探索 TIA 患者 WM 低频范围内的功能异常。此外，使用强化学习方法来研究改变的 WM 功能是否可以作为 TIA 的诊断指标。方法。我们招募了 48 名 TIA 患者和 41 名年龄和性别匹配的健康对照 (HC)。从每位参与者那里收集静息状态功能磁共振成像 (rs-fMRI) 和临床/生理/生化数据。我们使用两种静息状态指标比较了 TIA 和 HC 在 WM 低频范围内的组间差异：低频波动幅度 (ALFF) 和分数 ALFF (fALFF)。改变的 ALFF 和 fALFF 值被定义为涉及学习算法的强化学习方法的特征。结果。与HCs相比，TIA患者右扣带回/右上纵束/左上放射冠的ALFF降低，右大脑脚/右扣带回/小脑中脚的fALFF降低。基于这两个rs-fMRI指标，得到了一个最优的学习模型，其准确度为82.02%，敏感性为85.42%，特异性为78.05%，精密度为82.00%，曲线下面积（AUC）为0.87。结论。本研究揭示了 TIA 患者低频范围内的异常 WM 功能改变。这些结果支持 WM 功能性神经活动作为潜在神经标志物在 TIA 患者分类中的作用，并从 WM 功能的角度对 TIA 患者的潜在机制提供新的见解。