Table_1_Ability of an altered functional coupling between resting-state networks to predict behavioral outcomes in subcortical ischemic stroke: A longitudinal study.DOC

Stroke can be viewed as an acute disruption of an individual’s connectome caused by a focal or widespread loss of blood flow. Although individuals exhibit connectivity changes in multiple functional networks after stroke, the neural mechanisms that underlie the longitudinal reorganization of the connectivity patterns are still unclear. The study aimed to determine whether brain network connectivity patterns after stroke can predict longitudinal behavioral outcomes. Nineteen patients with stroke with subcortical lesions underwent two sessions of resting-state functional magnetic resonance imaging scanning at a 1-month interval. By independent component analysis, the functional connectivity within and between multiple brain networks (including the default mode network, the dorsal attention network, the limbic network, the visual network, and the frontoparietal network) was disrupted after stroke and partial recovery at the second time point. Additionally, regression analyses revealed that the connectivity between the limbic and dorsal attention networks at the first time point showed sufficient reliability in predicting the clinical scores (Fugl-Meyer Assessment and Neurological Deficit Scores) at the second time point. The overall findings suggest that functional coupling between the dorsal attention and limbic networks after stroke can be regarded as a biomarker to predict longitudinal clinical outcomes in motor function and the degree of neurological functional deficit. Overall, the present study provided a novel opportunity to improve prognostic ability after subcortical strokes.

脑卒中可被视为局灶性或广泛性脑血流灌注缺失所引发的个体连接组（connectome）急性紊乱。尽管脑卒中患者发病后多个功能网络均会出现连接模式改变，但连接模式纵向重塑的神经机制仍未明确。本研究旨在探讨脑卒中后大脑网络连接模式能否预测纵向行为结局。研究纳入19例伴皮质下病灶的脑卒中患者，在间隔1个月的两个时间点分别完成静息态功能磁共振成像（resting-state functional magnetic resonance imaging）扫描。通过独立成分分析（independent component analysis）发现，脑卒中后多个脑网络（包括默认模式网络（default mode network）、背侧注意网络（dorsal attention network）、边缘网络（limbic network）、视觉网络（visual network）及额顶网络（frontoparietal network））的内部及跨网络功能连接均遭到破坏，并在第二个时间点出现部分恢复。此外，回归分析（regression analyses）结果显示，首个时间点的边缘网络与背侧注意网络之间的连接强度，可稳定预测第二个时间点的临床评分（弗格勒-迈耶评估量表（Fugl-Meyer Assessment）与神经功能缺损评分（Neurological Deficit Scores））。整体研究结果表明，脑卒中后背侧注意网络与边缘网络之间的功能耦合可作为生物标志物（biomarker），用于预测运动功能及神经功能缺损程度的纵向临床结局。本研究为提升皮质下卒中患者的预后预测能力提供了全新思路。