Li Xiao, Chen Hanbo, Zhang Tuo, Yu Xiang, Jiang Xi, Li Kaiming, Li Longchuan, Razavi Mir Jalil, Wang Xianqiao, Hu Xintao, Han Junwei, Guo Lei, Hu Xiaoping, 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 Struct Funct. 2017 Jul;222(5):2127-2141. doi: 10.1007/s00429-016-1329-3. Epub 2016 Oct 31.
Cortical folding pattern analysis is very important to understand brain organization and development. Since previous studies mostly focus on human brain cortex, the regularity and variability of cortical folding patterns across primate brains (macaques, chimpanzees and human) remain largely unknown. This paper presents a novel computational framework to identify common or unique gyral folding patterns in macaque, chimpanzee and human brains using magnetic resonance imaging (MRI) data. We quantitatively characterize gyral folding patterns via hinge numbers with cortical surfaces constructed from MRI data, and identify 6 common three-hinge gyral folds that exhibit consistent anatomical locations across these three species as well as 2 unique three hinges in macaque, 6 ones in chimpanzee and 14 ones in human. A novel morphology descriptor is then applied to classify three-hinge gyral folds, and the increasing complexity is identified among the species analyzed. This study may provide novel insights into the regularity and variability of the cerebral cortex from developmental perspective and may potentially facilitate novel neuroimage analyses such as cortical parcellation with correspondences across species in the future.
皮质折叠模式分析对于理解大脑组织和发育非常重要。由于先前的研究大多集中在人类大脑皮层,灵长类动物大脑(猕猴、黑猩猩和人类)皮质折叠模式的规律性和变异性在很大程度上仍然未知。本文提出了一种新颖的计算框架,用于使用磁共振成像(MRI)数据识别猕猴、黑猩猩和人类大脑中常见或独特的脑回折叠模式。我们通过从MRI数据构建的皮质表面的铰链数来定量表征脑回折叠模式,并识别出6种常见的三铰链脑回褶皱,这些褶皱在这三个物种中表现出一致的解剖位置,以及猕猴中的2种独特的三铰链、黑猩猩中的6种和人类中的14种。然后应用一种新颖的形态学描述符对三铰链脑回褶皱进行分类,并在所分析的物种中识别出不断增加的复杂性。这项研究可能从发育角度为大脑皮层的规律性和变异性提供新的见解,并可能在未来促进新的神经影像分析,如跨物种对应关系的皮质分割。