Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06511, USA.
Department of Psychology , Stanford University, Jordan Hall Building 01-420, 450 Serra Mall, Stanford, CA 94305, USA.
Cereb Cortex. 2017 Dec 1;27(12):5539-5546. doi: 10.1093/cercor/bhw321.
Head movements are typically viewed as a nuisance to functional magnetic resonance imaging (fMRI) analysis, and are particularly problematic for resting state fMRI. However, there is growing evidence that head motion is a behavioral trait with neural and genetic underpinnings. Using data from a large randomly ascertained extended pedigree sample of Mexican Americans (n = 689), we modeled the genetic structure of head motion during resting state fMRI and its relation to 48 other demographic and behavioral phenotypes. A replication analysis was performed using data from the Human Connectome Project, which uses an extended twin design (n = 864). In both samples, head motion was significantly heritable (h2 = 0.313 and 0.427, respectively), and phenotypically correlated with numerous traits. The most strongly replicated relationship was between head motion and body mass index, which showed evidence of shared genetic influences in both data sets. These results highlight the need to view head motion in fMRI as a complex neurobehavioral trait correlated with a number of other demographic and behavioral phenotypes. Given this, when examining individual differences in functional connectivity, the confounding of head motion with other traits of interest needs to be taken into consideration alongside the critical important of addressing head motion artifacts.
头部运动通常被视为功能磁共振成像(fMRI)分析的干扰因素,特别是对静息态 fMRI 而言。然而,越来越多的证据表明,头部运动是一种具有神经和遗传基础的行为特征。本研究使用来自墨西哥裔美国人大型随机确定的扩展家系样本(n = 689)的数据,对静息态 fMRI 期间头部运动的遗传结构及其与其他 48 个人口统计学和行为表型的关系进行建模。使用人类连接组计划的数据(n = 864)进行了重复分析,该计划采用了扩展的双胞胎设计。在两个样本中,头部运动均具有显著的遗传性(h2 = 0.313 和 0.427),并且与许多表型相关。相关性最强的是头部运动与体重指数之间的关系,这表明在两个数据集之间存在共享遗传影响的证据。这些结果强调需要将 fMRI 中的头部运动视为与许多其他人口统计学和行为表型相关的复杂神经行为特征。考虑到这一点,在检查功能连接的个体差异时,需要考虑头部运动与其他感兴趣的特征的混杂因素,同时还需要解决头部运动伪影的重要问题。