Meng Kun, Eloyan Ani
Division of Applied Mathematics, Brown University, Providence, RI, USA.
Department of Biostatistics, Brown University School of Public Health, Providence, RI, USA.
J R Stat Soc Ser C Appl Stat. 2024 Mar 14;73(4):857-879. doi: 10.1093/jrsssc/qlae015. eCollection 2024 Aug.
Functional magnetic resonance imaging (fMRI) is a noninvasive and in-vivo imaging technique essential for measuring brain activity. Functional connectivity is used to study associations between brain regions, either while study subjects perform tasks or during periods of rest. In this paper, we propose a rigorous definition of task-evoked functional connectivity at the population level (ptFC). Importantly, our proposed ptFC is interpretable in the context of task-fMRI studies. An algorithm for estimating the ptFC is provided. We present the performance of the proposed algorithm compared to existing functional connectivity frameworks using simulations. Lastly, we apply the proposed algorithm to estimate the ptFC in a motor-task study from the Human Connectome Project.
功能磁共振成像（fMRI）是一种用于测量大脑活动的非侵入性体内成像技术。功能连接用于研究大脑区域之间的关联，无论是在研究对象执行任务时还是在休息期间。在本文中，我们提出了群体水平任务诱发功能连接（ptFC）的严格定义。重要的是，我们提出的ptFC在任务功能磁共振成像研究的背景下是可解释的。提供了一种估计ptFC的算法。我们通过模拟展示了与现有功能连接框架相比，所提出算法的性能。最后，我们将所提出的算法应用于人类连接体项目的一项运动任务研究中，以估计ptFC。
