The ABCD stop signal data: Response to Bissett et al. (October 2022)

• Record Type: Journal Article
• Authors: Garavan, H.; Chaarani, B.; Hahn, S.; Allgaier, N.; Juliano, A.; Yuan, D.K.; Orr, C.; Watts, R.; Wager, T.D.; Ruiz de Leon, O.; Hagler, D.J.; Potter, A.
• Is Part Of: Developmental cognitive neuroscience. Volume 57(2022)
• Publication Date: 2022-10
• Subjects: ABCD -- STOP task -- Race model -- Adolescence -- Neuroimaging; Cognitive neuroscience -- Periodicals; Developmental neurobiology -- Periodicals; Neuropsychology -- Periodicals; Neuropsychiatry -- Periodicals; 612.8233
• DOI: 10.1016/j.dcn.2022.101144
• Languages: English
• ISSNs: 1878-9293

Abstract

Abstract: 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.