An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks.

An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks.
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DOI:
10.1016/j.neuroimage.2017.08.068
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发表时间:
2018-04-15
期刊:
影响因子:
5.7
通讯作者:
Constable RT
Constable RT
中科院分区:
医学1区
文献类型:
--
作者:
Salehi M;Karbasi A;Shen X;Scheinost D;Constable RT

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最近的工作与功能连接数据导致了重大进展,了解大脑的功能组织。虽然大多数文献都集中在群体水平的分组方法,但有充分的证据表明,大脑在结构和功能上都因个体而异。在这项工作中,我们介绍了一个包裹技术,结合了在个人和群体水平的功能网络的划定。所提出的技术部署的概念,“子模块”共同包裹大脑皮层,同时建立一个包容性的个性化功能网络之间的对应关系。使用这种包裹技术,我们成功地建立了一个交叉验证的预测模型,预测个人的性别,完全基于包裹方案(即节点到网络的分配向量)。性别预测的结果表明,个性化的功能网络的包裹可以揭示在人口中的亚组,并建议使用全球网络包裹可能会忽略网络组织的根本差异。在比较患者与对照组甚至患者亚组的研究中,这一点尤其重要。网络组织可能因个人而异,不应假设全球配置。这种对大脑功能组织进行个体化研究的方法对神经科学和临床应用都有许多意义。
Recent work with functional connectivity data has led to significant progress in understanding the functional organization of the brain. While the majority of the literature has focused on group-level parcellation approaches, there is ample evidence that the brain varies in both structure and function across individuals. In this work, we introduce a parcellation technique that incorporates delineation of functional networks both at the individual- and group-level. The proposed technique deploys the notion of “submodularity” to jointly parcellate the cerebral cortex while establishing an inclusive correspondence between the individualized functional networks. Using this parcellation technique, we successfully established a cross-validated predictive model that predicts individuals’ sex, solely based on the parcellation schemes (i.e. the node-to-network assignment vectors). The sex prediction finding illustrates that individualized parcellation of functional networks can reveal subgroups in a population and suggests that the use of a global network parcellation may overlook fundamental differences in network organization. This is a particularly important point to consider in studies comparing patients versus controls or even patient subgroups. Network organization may differ between individuals and global configurations should not be assumed. This approach to the individualized study of functional organization in the brain has many implications for both neuroscience and clinical applications.
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