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Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in attention deficit/hyperactivity disorder

Weigard, A, Heathcote, A ORCID: 0000-0003-4324-5537, Matzke, D and Huang-Pollock, C 2019 , 'Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in attention deficit/hyperactivity disorder' , Clinical Psychological Science, vol. 7, no. 4 , pp. 856-872 , doi: 10.1177/2167702619838466.

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Abstract

Mean stop-signal reaction time (SSRT) is frequently employed as a measure of response inhibition in cognitive neuroscience research on attention deficit/hyperactivity disorder (ADHD). However, this measurement model is limited by two factors that may bias SSRT estimation in this population: (a) excessive skew in “go” RT distributions and (b) trigger failures, or instances in which individuals fail to trigger an inhibition process in response to the stop signal. We used a Bayesian parametric approach that allows unbiased estimation of the shape of entire SSRT distributions and the probability of trigger failures to clarify mechanisms of stop-signal task deficits in ADHD. Children with ADHD displayed greater positive skew than their peers in both go RT and SSRT distributions. However, they also displayed more frequent trigger failures, which appeared to drive ADHD-related stopping difficulties. Results suggest that performance on the stop-signal task among children with ADHD reflects impairments in early attentional processes, rather than inefficiency in the stop process.

Item Type: Article
Authors/Creators:Weigard, A and Heathcote, A and Matzke, D and Huang-Pollock, C
Keywords: computational psychiatry, ADHD, attention, response inhibition, Bayesian cognitive modeling
Journal or Publication Title: Clinical Psychological Science
Publisher: Sage Publications, Inc.
ISSN: 2167-7026
DOI / ID Number: 10.1177/2167702619838466
Copyright Information:

© The Author(s) 2019

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