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2015, Nature Neuroscience. DOI: 10.1038/nn.4164
Parcellating cortical functional networks in individuals
Danhong Wang , Randy L Buckner , Michael D Fox , Daphne J Holt , Avram J Holmes , Sophia Stoecklein , Georg Langs , Ruiqi Pan , Tianyi Qian , Kuncheng Li , Justin T Baker , Steven M Stufflebeam , Kai Wang , Xiaomin Wang , Bo Hong , Hesheng Liu
Abstract:
The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.
2023-02-28 21:02:00
#paper doi:https://doi.org/10.1038/nn.4164 Parcellating cortical functional networks in individuals 大脑网络的位置、大小等属性具有个体差异。之前的研究忽略了这些差异,运用组水平的分区模板计算功能连接矩阵,导致功能连接个体间差异的混淆。本研究是第一个提出个体化功能网络的研究,基于组水平网络分区模板迭代的思路,获得了具有可重复性、可以捕捉个体间差异、可通过电刺激验证的功能网络个体化分区,为我们进行个体化功能网络的研究提供了新思路。
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