Liu Huan, Jiang Xi, Zhang Tuo, Ren Yudan, Hu Xintao, Guo Lei, Han Junwei, Liu Tianming
School of Automation, Northwestern Polytechnical University, Xi'an, China.
Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.
Brain Res. 2017 Oct 1;1672:81-90. doi: 10.1016/j.brainres.2017.07.018. Epub 2017 Jul 28.
The highly convoluted cerebral cortex is characterized by two different topographic structures: convex gyri and concave sulci. Increasing studies have demonstrated that cortical gyri and sulci exhibit different structural connectivity patterns. Inspired by the intrinsic structural differences between gyri and sulci, in this paper, we present a data-driven framework based on sparse representation of fMRI data for functional network inferences, then examine the interactions within and across gyral and sulcal functional networks and finally elucidate possible functional differences using graph theory based properties. We apply the proposed framework to the high-resolution Human Connectome Project (HCP) grayordinate fMRI data. Extensive experimental results on both resting state fMRI data and task-based fMRI data consistently suggested that gyri are more functionally integrated, while sulci are more functionally segregated in the organizational architecture of cerebral cortex, offering novel understanding of the byzantine cerebral cortex.
凸状的脑回和凹状的脑沟。越来越多的研究表明,脑回和脑沟呈现出不同的结构连接模式。受脑回和脑沟之间内在结构差异的启发,在本文中,我们提出了一个基于功能磁共振成像(fMRI)数据稀疏表示的框架,用于功能网络推理,然后检查脑回和脑沟功能网络内部以及它们之间的相互作用,最后使用基于图论的属性阐明可能的功能差异。我们将所提出的框架应用于高分辨率人类连接组计划(HCP)的灰质坐标fMRI数据。在静息态fMRI数据和基于任务的fMRI数据上进行的大量实验结果一致表明,在大脑皮层的组织结构中,脑回在功能上更具整合性,而脑沟在功能上更具分离性,这为复杂的大脑皮层提供了新的理解。