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- W2912863431 abstract "Difference exists widely in cognition, behavior and psychopathology between males and females, while the underlying neurobiology is still unclear. As brain structure is the fundament of its function, getting insight into structural brain may help us to better understand the functional mechanism of gender differences. Previous structural studies of gender difference in Magnetic Resonance Imaging (MRI) usually focused on Grey Matter (GM) density and Structural Connectivity (SC), while cortical morphology was not well characterized. In this study a large dataset is used to explore whether cortical 3-dimensional (3-D) morphology can afford enough discriminative morphological features to effectively identify gender. Data of all available healthy controls (N=1113) from the Human Connectome Project (HCP) were utilized. We suggested a multivariate pattern analysis method called Hierarchical Sparse Representation Classifier (HSRC) and got an accuracy of 96.77% for gender identification. Permutation tests were used to testify the reliability of gender discrimination (p<.001). Cortical 3-D morphological features within the Frontal Lobe were found the most important contributors to gender difference of human brain morphology. Moreover, we investigated gender discriminative ability of cortical 3-D morphology in predefined Anatomical Automatic Labeling (AAL) and Resting-State Networks (RSN) templates, and found the superior frontal gyrus the most discriminative in AAL and the default network the most discriminative in RSN. Gender difference of surface-based morphology was also discussed. The Frontal Lobe, as well as the Default network, was widely reported of gender difference in previous structural and functional MRI studies, which suggest that morphology indeed affect human brain function. The outcome of our study indicates that gender can be identified on individual level using cortical 3-D morphology and affords a new approach for structural MRI research, as well as highlights the importance of gender balance in brain imaging studies." @default.
- W2912863431 created "2019-02-21" @default.
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- W2912863431 date "2019-02-07" @default.
- W2912863431 modified "2023-10-12" @default.
- W2912863431 title "Gender Identification of Human Cortical 3-D Morphology Using Hierarchical Sparsity" @default.
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- W2912863431 doi "https://doi.org/10.3389/fnhum.2019.00029" @default.
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