Department of Psychiatry, University of Vermont, Burlington, VT, USA.
Department of Psychiatry, University of Vermont, Burlington, VT, USA.
Dev Cogn Neurosci. 2022 Oct;57:101144. doi: 10.1016/j.dcn.2022.101144. Epub 2022 Aug 11.
This paper responds to a recent critique by Bissett et al. of the fMRI Stop task used in the Adolescent Brain Cognitive Development Study (ABCD Study®). The critique focuses primarily on a task design feature related to race model assumptions (i.e., that the Go and Stop processes are fully independent). In response, we note that the race model is quite robust against violations of its assumptions. Most importantly, while Bissett raises conceptual concerns with the task we focus here on analyzes of the task data and conclude that the concerns appear to have minimal impact on the neuroimaging data (the validity of which do not rely on race model assumptions) and have far less of an impact on the performance data than the critique suggests. We note that Bissett did not apply any performance-based exclusions to the data they analyzed, a number of the trial coding errors they flagged were already identified and corrected in ABCD annual data releases, a number of their secondary concerns reflect sensible design decisions and, indeed, their own computational modeling of the ABCD Stop task suggests the problems they identify have just a modest impact on the rank ordering of individual differences in subject performance.
本文回应了 Bissett 等人最近对用于青少年大脑认知发展研究(ABCD 研究)的 fMRI 停止任务的批评。批评主要集中在与种族模型假设相关的任务设计特征上(即,Go 和 Stop 过程完全独立)。作为回应,我们注意到种族模型对违反其假设具有很强的稳健性。最重要的是,虽然 Bissett 对任务提出了概念性的担忧,但我们在这里重点分析了任务数据,并得出结论,这些担忧似乎对神经影像学数据的影响很小(其有效性不依赖于种族模型假设),并且对性能数据的影响远小于批评所表明的。我们注意到,Bissett 没有对他们分析的数据进行任何基于性能的排除,他们标记的许多试验编码错误已经在 ABCD 年度数据发布中被识别和纠正,他们的一些次要关注点反映了合理的设计决策,事实上,他们自己对 ABCD 停止任务的计算建模表明,他们所确定的问题对个体差异在个体表现上的排序影响不大。