论文标题
大脑形状和连通性的功能随机效应建模
Functional random effects modeling of brain shape and connectivity
论文作者
论文摘要
我们提出了一个统计框架，该框架共同模拟了大脑形状和功能连接性，这是大脑的两个复杂方面，它们已经独立研究。我们采用Riemannian建模方法来说明形状空间的非欧几里得几何形状以及连接空间的限制，从而限制了共差异的轨迹为有效的统计估计。为了将可变性的遗传源与由独特环境因素驱动的遗传来源解散，我们将功能随机效应模型嵌入了Riemannian框架中。我们将提出的模型应用于人类Connectome项目数据集，以探索年轻健康个体的大脑形状和连通性之间的自发共同变化。
We present a statistical framework that jointly models brain shape and functional connectivity, which are two complex aspects of the brain that have been classically studied independently. We adopt a Riemannian modeling approach to account for the non-Euclidean geometry of the space of shapes and the space of connectivity that constrains trajectories of co-variation to be valid statistical estimates. In order to disentangle genetic sources of variability from those driven by unique environmental factors, we embed a functional random effects model in the Riemannian framework. We apply the proposed model to the Human Connectome Project dataset to explore spontaneous co-variation between brain shape and connectivity in young healthy individuals.
