Genetic effects on fine-grained human cortical regionalization

Cui, Yue, Liu, Bing, Zhou, Yuan, Fan, Lingzhong, Li, Jin, Zhang, Yun, Wu, Huawang, Hou, Bing, Wang, Chao, Zheng, Fanfan, Qiu, Chengxiang, Rao, Li-Lin, Ning, Yuping, Li, Shu and Jiang, Tianzi (2015) Genetic effects on fine-grained human cortical regionalization. Cerebral Cortex, 26 9: 3732-3743. doi:10.1093/cercor/bhv176

Author Cui, Yue
Liu, Bing
Zhou, Yuan
Fan, Lingzhong
Li, Jin
Zhang, Yun
Wu, Huawang
Hou, Bing
Wang, Chao
Zheng, Fanfan
Qiu, Chengxiang
Rao, Li-Lin
Ning, Yuping
Li, Shu
Jiang, Tianzi
Title Genetic effects on fine-grained human cortical regionalization
Journal name Cerebral Cortex   Check publisher's open access policy
ISSN 1047-3211
Publication date 2015-06-08
Year available 2015
Sub-type Article (original research)
DOI 10.1093/cercor/bhv176
Open Access Status Not Open Access
Volume 26
Issue 9
Start page 3732
End page 3743
Total pages 12
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Subject 2805 Cognitive Neuroscience
2804 Cellular and Molecular Neuroscience
Abstract Various brain structural and functional features such as cytoarchitecture, topographic mapping, gyral/sulcal anatomy, and anatomical and functional connectivity have been used in human brain parcellation. However, the fine-grained intrinsic genetic architecture of the cortex remains unknown. In the present study, we parcellated specific regions of the cortex into subregions based on genetic correlations (i.e., shared genetic influences) between the surface area of each pair of cortical locations within the seed region. The genetic correlations were estimated by comparing the correlations of the surface area between monozygotic and dizygotic twins using bivariate twin models. Our genetic subdivisions of diverse brain regions were reproducible across 2 independent datasets and corresponded closely to fine-grained functional specializations. Furthermore, subregional genetic correlation profiles were generally consistent with functional connectivity patterns. Our findings indicate that the magnitude of the genetic covariance in brain anatomy could be used to delineate the boundaries of functional subregions of the brain and may be of value in the next generation human brain atlas.
Keyword Cortical Regionalization
Genetic Correlation
Surface Area
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2016 Collection
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Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
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Created: Fri, 11 Mar 2016, 23:52:03 EST by Susan Day on behalf of Queensland Brain Institute