聚类分析
计算机科学
人工智能
光谱聚类
模式识别(心理学)
作者
Ying Huang,Zhengwang Wu,Ya Wang,Tengfei Li,Xifeng Wang,Hongtu Zhu,Weili Lin,Li Wang,Jun Feng,John H. Gilmore,Gang Li
标识
DOI:10.1109/embc53108.2024.10782296
摘要
Genetic factors have been proven to be one of the major determinants in shaping the neonatal cerebral cortex. Previous research has demonstrated distinct genetic influences on the spatial patterns of cortical thickness (CT) and surface area (SA) in neonates, leading to their unique genetically informed parcellation maps. However, these parcellation maps were derived at coarse scales and only reliant on single cortical properties, making them unable to comprehensively characterize the fine-grained genetically regulated patterns of the neonatal cerebral cortex. To fill this knowledge gap, by combining genetic correlations of multiple cortical properties (CT and SA) based on 202 twin neonates' brain magnetic resonance (MR) images, we performed multi-view spectral clustering and revealed the first joint, fine-grained, genetically informed parcellation map of the neonatal cerebral cortex. The discovered parcellation maps comprehensively reflect genetically regulated detailed patterns of the neonatal brain.
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