Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

NeuroImage(2022)

引用 12|浏览17
暂无评分
摘要
•Exclusion of high-motion subjects reduces rs-fMRI artifacts but may bias the study sample.•Autistic children with usable data had less severe symptoms and were older than the original sample.•Among children with usable data, symptom severity and age were related to functional connectivity.•Using doubly robust targeted minimum loss based estimation (DRTMLE) to address these biases, we observe more extensive group differences.•If quality control changes the distribution of a variable related to the outcome, we recommend using DRTMLE.
更多
查看译文
关键词
Causal inference,Confounding,Functional connectivity,Missing data,Sampling bias,Super learner,Targeted minimum loss based estimation,Motion quality control,Autism spectrum disorder
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要