计算机科学
人工智能
计算机视觉
功能连接
神经科学
模式识别(心理学)
心理学
作者
Yue Cui,Chengyi Li,Yuheng Lu,Liang Ma,Luqi Cheng,Long Cao,Shan Yu,Tianzi Jiang
出处
期刊:IEEE Transactions on Medical Imaging
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-1
被引量:2
标识
DOI:10.1109/tmi.2024.3392946
摘要
Individual brains vary greatly in morphology, connectivity and organization. Individualized brain parcellation is capable of precisely localizing subject-specific functional regions. However, most individualization approaches examined single modality of data and have not generalized to nonhuman primates. The present study proposed a novel multimodal connectivity-based individual parcellation (MCIP) method, which optimizes within-region homogeneity, spatial continuity and similarity to a reference atlas with the fusion of personal functional and anatomical connectivity. Comprehensive evaluation demonstrated that MCIP outperformed state-of-the-art multimodal individualization methods in terms of functional and anatomical homogeneity, predictability of cognitive measures, heritability, reproducibility and generalizability across species. Comparative investigation showed a higher topographic variability in humans than that in macaques. Therefore, MCIP provides improved accurate and reliable mapping of brain functional regions over existing methods at an individual level across species, and could facilitate comparative and translational neuroscience research.
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