Exploring Folding Patterns of Infant Cerebral Cortex Based on Multi-view Curvature Features: Methods and Applications

Dingna Duan, Shunren Xia, Islem Rekik, Yu Meng, Zhengwang Wu, Li Wang, Weili Lin, John H. Gilmore, Dinggang Shen (Lead / Corresponding author), Gang Li (Lead / Corresponding author)

Research output: Contribution to journalArticle

Abstract

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 2retaining 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 neonatesand 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 sexdifference 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.,theHuman Connectome Project (HCP), and revealed that certainmajor cortical folding patterns of adults are largely established at term birth.
LanguageEnglish
JournalNeuroImage
Early online date18 Aug 2018
DOIs
Publication statusE-pub ahead of print - 18 Aug 2018

Fingerprint

Temporal Lobe
Cerebral Cortex
Gyrus Cinguli
Term Birth
Frontal Lobe
Prefrontal Cortex
Connectome
Parietal Lobe
Brain
Neuroimaging
Cluster Analysis
Newborn Infant
Datasets

Keywords

  • Cortical folding pattern
  • infant brain
  • spherical wavelets
  • sex difference
  • emispheric asymmetry

Cite this

Duan, Dingna ; Xia, Shunren ; Rekik, Islem ; Meng, Yu ; Wu, Zhengwang ; Wang, Li ; Lin, Weili ; Gilmore, John H. ; Shen, Dinggang ; Li, Gang. / Exploring Folding Patterns of Infant Cerebral Cortex Based on Multi-view Curvature Features : Methods and Applications. In: NeuroImage. 2018.
@article{85d10f0a9e7e4b4db294dbb8aed0a3a7,
title = "Exploring Folding Patterns of Infant Cerebral Cortex Based on Multi-view Curvature Features: Methods and Applications",
abstract = "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 2retaining 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 neonatesand 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 sexdifference 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.,theHuman Connectome Project (HCP), and revealed that certainmajor cortical folding patterns of adults are largely established at term birth.",
keywords = "Cortical folding pattern, infant brain, spherical wavelets, sex difference, emispheric asymmetry",
author = "Dingna Duan and Shunren Xia and Islem Rekik and Yu Meng and Zhengwang Wu and Li Wang and Weili Lin and Gilmore, {John H.} and Dinggang Shen and Gang Li",
note = "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)",
year = "2018",
month = "8",
day = "18",
doi = "10.1016/j.neuroimage.2018.08.041",
language = "English",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Elsevier",

}

Exploring Folding Patterns of Infant Cerebral Cortex Based on Multi-view Curvature Features : Methods and Applications. / Duan, Dingna; Xia, Shunren; Rekik, Islem; Meng, Yu ; Wu, Zhengwang ; Wang, Li ; Lin, Weili; Gilmore, John H.; Shen, Dinggang (Lead / Corresponding author); Li, Gang (Lead / Corresponding author).

In: NeuroImage, 18.08.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Exploring Folding Patterns of Infant Cerebral Cortex Based on Multi-view Curvature Features

T2 - NeuroImage

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 - 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)

PY - 2018/8/18

Y1 - 2018/8/18

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 2retaining 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 neonatesand 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 sexdifference 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.,theHuman Connectome Project (HCP), and revealed that certainmajor 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 2retaining 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 neonatesand 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 sexdifference 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.,theHuman Connectome Project (HCP), and revealed that certainmajor cortical folding patterns of adults are largely established at term birth.

KW - Cortical folding pattern

KW - infant brain

KW - spherical wavelets

KW - sex difference

KW - emispheric asymmetry

U2 - 10.1016/j.neuroimage.2018.08.041

DO - 10.1016/j.neuroimage.2018.08.041

M3 - Article

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

ER -