Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke
Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke
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DOI：
10.1073/pnas.1521083113
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发表时间：
2016-07-26
影响因子：
11.1
通讯作者：
Corbetta, Maurizio
中科院分区：
文献类型：
--
作者：
Siegel, Joshua Sarfaty;Ramsey, Lenny E.;Corbetta, Maurizio
中风后的缺陷通常归因于局灶性损伤，但最近的证据表明分布式脑网络中断的关键作用。我们测量了132名中风患者的静息功能连接（FC），病变地形图和多个领域（注意力，视觉记忆，言语记忆，语言，运动和视觉）的行为，并使用机器学习模型来预测个体受试者的神经功能缺损。我们发现FC能更好地预测视觉记忆和言语记忆，而病灶地形图能更好地预测视觉和运动障碍。注意力和语言缺陷都得到了很好的预测。接下来，我们确定了生理网络功能障碍的一般模式，包括半球间整合和半球内分离的减少，这与多个领域的行为障碍密切相关。网络功能障碍的特定模式预测特定的行为缺陷，一组区域的大脑半球间沟通的丧失与多个行为领域的损伤相关。这些结果将脑网络的关键组织特征与中风中的脑行为关系联系起来。
Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke.