标题： 皮质的群组结构分区：基于逻辑模型的合理方法 显示英文标题

标题： Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models

摘要： 当前的理论认为大脑功能与通过轴突束的长程物理连接密切相关，即外在连通性。然而，基于外在连通性获得全脑皮层分区仍然具有挑战性。现有的分区方法计算成本高昂；需要调整多个参数或依赖人为设定的约束条件。此外，这些方法中没有一种提出了皮层外在连通性的模型。为了解决这些问题，我们提出了一种简洁的外在连通性模型和一种基于轨迹聚类的高效分区技术。我们的技术允许创建单个受试者和群体层面的全脑皮层分区。我们技术得到的分区与文献中的结构和功能分区一致。特别是，运动和感觉皮层的亚分区与Penfield的人体小人图一致。我们通过比较我们的分区结果与人类连接组计划数据中包含的运动条带映射来证明这一点。 显示英文摘要

摘要： Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectiv-ity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are compu-tationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity of the cortex. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parceling technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with structural and functional parcellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human ho-munculus of Penfield. We illustrate this by comparing our resulting parcels with the motor strip mapping included in the Human Connectome Project data.