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Identifying endophenotypes of autism: a multivariate approach

机译:识别自闭症的内表型:多变量方法

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摘要

The existence of an endophenotype of autism spectrum condition (ASC) has been recently suggested by several commentators. It can be estimated by finding differences between controls and people with ASC that are also present when comparing controls and the unaffected siblings of ASC individuals. In this work, we used a multivariate methodology applied on magnetic resonance images to look for such differences. The proposed procedure consists of combining a searchlight approach and a support vector machine classifier to identify the differences between three groups of participants in pairwise comparisons: controls, people with ASC and their unaffected siblings. Then we compared those differences selecting spatially collocated as candidate endophenotypes of ASC.
机译:几位评论者最近提出了自闭症谱系条件(ASC)的内表型的存在。可以通过比较对照组和ASC个人未受影响的兄弟姐妹时发现对照组与ASC人之间的差异来进行估算。在这项工作中,我们使用了应用于磁共振图像的多元方法来寻找这种差异。拟议的程序包括将探照灯方法和支持向量机分类器相结合,以识别成对比较的三组参与者之间的差异:对照组,患有ASC的人及其未受影响的兄弟姐妹。然后,我们比较了那些选择在空间上并列为ASC候选表型的差异。

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