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Updated: Jan 14, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Using multimodal cortical parcellations to identify novel regions of the human cerebral cortex associated with
Shizheng Qiu1, Zhishuai Zhang1, Haozheng Liang1
1Faculty of Computing, Harbin Institute of Technology, Harbin, China.
Abstract:
Cognitive performance has been found to be associated with the complex structure of human cerebral cortex. However, due to the limitations of previous cortical parcellation atlases, the cortical genetic patterns determining cognitive performance remain unknown. Here, we utilized the latest Human Connectome Project Multi-Modal Parcellation (HCP-MMP) atlas to divide the cerebral cortex into 180 regions per hemisphere. We investigated the shared genetic architecture between four types of magnetic resonance imaging (MRI)-derived cortical phenotypes and cognitive performance using large-scale genome-wide association studies (N for cortical phenotypes = 36,843; N for cognitive performance = 257,828). We observed extensive genetic overlap between cortical surface area, volume, and local gyrification index (LGI) with cognitive performance, particularly the subregions in the insula, cingulate cortex, and ventromedial prefrontal cortex, many of which were novel findings. However, the thickness of some prefrontal regions was negatively correlated with cognitive performance. We identified 18 and 312 shared genetic loci for global and regional cortical phenotypes with cognitive performance, respectively. These genetic loci were involved in a substantial number of biological processes related to neuronal development, cell growth, and neuronal death or apoptosis. The cortical patterns defined by these shared loci were established entirely along the sensorimotor-association (S-A) axis. These findings provide new insights into the genetic relationship between cognitive performance and the human cerebral cortex under a more refined multimodal cortical parcellation scheme.
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