Individualized event structure drives individual differences in whole-brain functional connectivity
Individualized event structure drives individual differences in whole-brain functional connectivity
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DOI：
10.1016/j.neuroimage.2022.118993
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发表时间：
2022-03-08
期刊：
影响因子：
5.7
通讯作者：
Sporns, Olaf
中科院分区：
文献类型：
--
作者：
Betzel, Richard F.;Cutts, Sarah A.;Sporns, Olaf
静息状态功能连接通常被建模为全脑区域活动的相关结构。它被广泛研究，不仅是为了深入了解大脑的内在组织，也是为了开发对个体认知、临床和发育状态变化敏感的标记物。尽管如此，功能连接的起源和驱动因素，特别是在密集采样的个体水平上，仍然难以捉摸。在这里，我们利用新颖的方法将功能连接分解为其精确的框架贡献。使用两个密集的采样数据集，我们研究了个性化功能连接的起源，特别关注大脑网络“事件”的作用-高振幅共波动的短暂和峰值模式。在这里，我们开发了一个统计测试来识别经验记录中的事件。我们表明，在事件中表达的共波动模式在同一个体的多次扫描中重复出现，并代表了在群体水平上表达的模板模式的特殊变体。最后，我们提出了一个简单的基于事件共波动的功能连通性模型，表明群体平均共波动对于解释参与者特定的连通性是次优的。我们的工作补充了最近的研究，这些研究表明，短暂的高振幅共波动是静态的全脑功能连接的主要驱动因素。我们的工作也扩展了这些研究，证明事件中的共波动是个性化的，为功能连接提供了动态基础。
Resting-state functional connectivity is typically modeled as the correlation structure of whole-brain regional activity. It is studied widely, both to gain insight into the brain's intrinsic organization but also to develop markers sensitive to changes in an individual's cognitive, clinical, and developmental state. Despite this, the origins and drivers of functional connectivity, especially at the level of densely sampled individuals, remain elusive. Here, we leverage novel methodology to decompose functional connectivity into its precise framewise contributions. Using two dense sampling datasets, we investigate the origins of individualized functional connectivity, focusing specifically on the role of brain network "events"- short-lived and peaked patterns of high-amplitude cofluctuations. Here, we develop a statistical test to identify events in empirical recordings. We show that the patterns of cofluctuation expressed during events are repeated across multiple scans of the same individual and represent idiosyncratic variants of template patterns that are expressed at the group level. Lastly, we propose a simple model of functional connectivity based on event cofluctuations, demonstrating that group-averaged cofluctuations are suboptimal for explaining participant-specific connectivity. Our work complements recent studies implicating brief instants of high-amplitude cofluctuations as the primary drivers of static, whole-brain functional connectivity. Our work also extends those studies, demonstrating that cofluctuations during events are individualized, positing a dynamic basis for functional connectivity.