TY - JOUR
T1 - Exploring folding patterns of infant cerebral cortex based on multi-view curvature features
T2 - Methods and applications
AU - Duan, Dingna
AU - Xia, Shunren
AU - Rekik, Islem
AU - Meng, Yu
AU - Wu, Zhengwang
AU - Wang, Li
AU - Lin, Weili
AU - Gilmore, John H.
AU - Shen, Dinggang
AU - Li, Gang
N1 - Funding Information:
This work was supported in part by NIH grants ( MH100217 , MH107815 , MH108914 , MH109773 , MH110274 , MH116225 , MH117943 , MH070890 , MH064065 , and HD053000 ), as well as National Key Research and Development Program of China (No. 2016YFC1306600 ) and Zhejiang Provincial Natural Science Foundation of China (No. LQ18A010003 ).
Funding Information:
Adult data were provided in part by the Human Connectome Project, WU-Minn Consortium (principal investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657 ) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research ; and by the McDonnell Center for Systems Neuroscience at Washington University .
Funding Information:
Adult data were provided in part by the Human Connectome Project, WU-Minn Consortium (principal investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.
Publisher Copyright:
© 2018 Elsevier Inc.
PY - 2019/1/15
Y1 - 2019/1/15
N2 - The highly convoluted cortical folding of the human brain is intriguingly complex and variable across individuals. Exploring the underlying representative patterns of cortical folding is of great importance for many neuroimaging studies. At term birth, all major cortical folds are established and are minimally affected by the complicated postnatal environments; hence, neonates are the ideal candidates for exploring early postnatal cortical folding patterns, which yet remain largely unexplored. In this paper, we propose a novel method for exploring the representative regional folding patterns of infant brains. Specifically, first, multi-view curvature features are constructed to comprehensively characterize the complex characteristics of cortical folding. Second, for each view of curvature features, a similarity matrix is computed to measure the similarity of cortical folding in a specific region between any pair of subjects. Next, a similarity network fusion method is adopted to nonlinearly and adaptively fuse all the similarity matrices into a single one for retaining both shared and complementary similarity information of the multiple characteristics of cortical folding. Finally, based on the fused similarity matrix and a hierarchical affinity propagation clustering approach, all subjects are automatically grouped into several clusters to obtain the representative folding patterns. To show the applications, we have applied the proposed method to a large-scale dataset with 595 normal neonates and discovered representative folding patterns in several cortical regions, i.e., the superior temporal gyrus (STG), inferior frontal gyrus (IFG), precuneus, and cingulate cortex. Meanwhile, we have revealed sex difference in STG, IFG, and cingulate cortex, as well as hemispheric asymmetries in STG and cingulate cortex in terms of cortical folding patterns. Moreover, we have also validated the proposed method on a public adult dataset, i.e., the Human Connectome Project (HCP), and revealed that certain major cortical folding patterns of adults are largely established at term birth.
AB - The highly convoluted cortical folding of the human brain is intriguingly complex and variable across individuals. Exploring the underlying representative patterns of cortical folding is of great importance for many neuroimaging studies. At term birth, all major cortical folds are established and are minimally affected by the complicated postnatal environments; hence, neonates are the ideal candidates for exploring early postnatal cortical folding patterns, which yet remain largely unexplored. In this paper, we propose a novel method for exploring the representative regional folding patterns of infant brains. Specifically, first, multi-view curvature features are constructed to comprehensively characterize the complex characteristics of cortical folding. Second, for each view of curvature features, a similarity matrix is computed to measure the similarity of cortical folding in a specific region between any pair of subjects. Next, a similarity network fusion method is adopted to nonlinearly and adaptively fuse all the similarity matrices into a single one for retaining both shared and complementary similarity information of the multiple characteristics of cortical folding. Finally, based on the fused similarity matrix and a hierarchical affinity propagation clustering approach, all subjects are automatically grouped into several clusters to obtain the representative folding patterns. To show the applications, we have applied the proposed method to a large-scale dataset with 595 normal neonates and discovered representative folding patterns in several cortical regions, i.e., the superior temporal gyrus (STG), inferior frontal gyrus (IFG), precuneus, and cingulate cortex. Meanwhile, we have revealed sex difference in STG, IFG, and cingulate cortex, as well as hemispheric asymmetries in STG and cingulate cortex in terms of cortical folding patterns. Moreover, we have also validated the proposed method on a public adult dataset, i.e., the Human Connectome Project (HCP), and revealed that certain major cortical folding patterns of adults are largely established at term birth.
KW - Cortical folding pattern
KW - Hemispheric asymmetry
KW - Infant brain
KW - Sex difference
KW - Spherical wavelets
UR - http://www.scopus.com/inward/record.url?scp=85052198170&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2018.08.041
DO - 10.1016/j.neuroimage.2018.08.041
M3 - Review article
C2 - 30130646
AN - SCOPUS:85052198170
SN - 1053-8119
VL - 185
SP - 575
EP - 592
JO - NeuroImage
JF - NeuroImage
ER -