Stroke data from: Robust dynamic brain coactivation states estimated in individuals

A confluence of evidence indicates that brain functional connectivity (FC) is not static but rather dynamic. Capturing transient network interactions in the individual brain requires a technology that offers sufficient within-subject reliability. Here, we introduce an individualized network-based dynamics analysis technique and demonstrate that it is reliable in detecting subject-specific brain states during both resting state and a cognitively challenging language task. Moreover, we evaluated the extent to which brain states showed hemispheric asymmetries and how various phenotypic factors such as handedness and gender might influence network dynamics. We discovered a right-lateralized brain state that occurred more frequently in men than in women, and more frequently in right-handed versus left-handed individuals. Lastly, we demonstrated longitudinal brain state changes in 42 patients with subcortical stroke over 6 months. Taken together, this approach could quantify subject-specific ..., This is supplemental material for \"X. Peng, Robust dynamic brain coactivation states estimated in individuals, Science Advances, 2022\".,

多项汇聚的证据表明，大脑功能连接（functional connectivity, FC）并非静态不变，而是处于动态变化之中。若要捕捉个体大脑中的瞬时网络交互活动，需要一种能在被试内部具备足够可靠性的技术手段。本研究提出了一种基于个体的网络动态分析技术，并证实该技术可在静息态与认知负荷较高的语言任务中，可靠地检测出被试特异性的大脑状态。此外，本研究评估了大脑状态在多大程度上呈现半球不对称性，以及利手性、性别等多种表型因素如何影响网络动态特性。本研究发现了一种右侧偏侧化的大脑状态，该状态在男性群体中的出现频率高于女性，且在右利手个体中的出现频率高于左利手个体。最后，本研究对42名皮质下卒中患者进行了为期6个月的纵向追踪，证实了其大脑状态的动态变化。综上，该方法可量化被试特异性的[原文此处存在省略内容]。本文为《X. Peng, Robust dynamic brain coactivation states estimated in individuals, Science Advances, 2022》的补充材料。