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Can we use neuroimaging data to differentiate between subgroups of children with ADHD symptoms: A proof of concept study using latent class analysis of brain activity

机译:我们是否可以使用神经影像学数据区分患有ADHD症状的儿童的亚组:使用脑活动潜伏类分析的概念研究

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摘要

BackgroundMultiple pathway models of ADHD suggest that multiple, separable biological pathways may lead to symptoms of the disorder. If this is the case, it should be possible to identify subgroups of children with ADHD based on distinct patterns of brain activity. Previous studies have used latent class analysis (LCA) to define subgroups at the behavioral and cognitive level and to then test whether they differ at the neurobiological level. In this proof of concept study, we took a reverse approach. We applied LCA to functional imaging data from two previously published studies to explore whether we could identify subgroups of children with ADHD symptoms at the neurobiological level with a meaningful relation to behavior or neuropsychology.
机译:背景多动症的多种途径模型表明,多种可分离的生物学途径可能导致该疾病的症状。在这种情况下,应该有可能根据脑活动的不同模式来识别多动症儿童的亚组。先前的研究已经使用潜在类别分析(LCA)在行为和认知水平上定义了亚组,然后在神经生物学水平上测试了它们是否有所不同。在本概念验证研究中,我们采用了相反的方法。我们将LCA应用于两项先前发表的研究的功能成像数据,以探讨我们是否可以在神经生物学水平上识别出与行为或神经心理学有有意义关系的ADHD症状儿童亚组。

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