College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, China.
College of Science, National University of Defense Technology, Changsha, Hunan, China.
Cereb Cortex. 2020 Jan 10;30(1):269-282. doi: 10.1093/cercor/bhz086.
The human precuneus is involved in many high-level cognitive functions, which strongly suggests the existence of biologically meaningful subdivisions. However, the functional parcellation of the precuneus needs much to be investigated. In this study, we developed an eigen clustering (EIC) approach for the parcellation using precuneus-cortical functional connectivity from fMRI data of the Human Connectome Project. The EIC approach is robust to noise and can automatically determine the cluster number. It is consistently demonstrated that the human precuneus can be subdivided into six symmetrical and connected parcels. The anterior and posterior precuneus participate in sensorimotor and visual functions, respectively. The central precuneus with four subregions indicates a media role in the interaction of the default mode, dorsal attention, and frontoparietal control networks. The EIC-based functional parcellation is free of the spatial distance constraint and is more functionally coherent than parcellation using typical clustering algorithms. The precuneus subregions had high accordance with cortical morphology and revealed good functional segregation and integration characteristics in functional task-evoked activations. This study may shed new light on the human precuneus function at a delicate level and offer an alternative scheme for human brain parcellation.
人类楔前叶参与许多高级认知功能，这强烈表明其存在具有生物学意义的细分。然而，楔前叶的功能划分还有很多需要研究。在这项研究中，我们使用来自人类连接组计划的 fMRI 数据中的楔前叶-皮质功能连接，开发了一种特征聚类（EIC）方法进行分割。EIC 方法对噪声具有鲁棒性，可以自动确定聚类数量。一致表明，人类楔前叶可以细分为六个对称且相连的区域。前楔前叶和后楔前叶分别参与感觉运动和视觉功能。具有四个子区域的中央楔前叶表明其在默认模式、背侧注意和额顶控制网络的相互作用中起中介作用。基于 EIC 的功能划分不受空间距离限制，并且比使用典型聚类算法的划分更具有功能一致性。楔前叶子区域与皮质形态高度一致，并在功能任务诱发激活中表现出良好的功能分离和整合特征。这项研究可能为精细水平的人类楔前叶功能提供新的见解，并为人类大脑划分提供替代方案。
