ArticleJournal of abnormal psychology2018
Testing formal predictions of neuroscientific theories of ADHD with a cognitive model-based approach.
Article in Journal of abnormal psychology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Less systematic decision-making during delay discounting, but not discounting rate, is robustly linked to psychopathology.Journal of psychopathology and clinical science · 2026Article
- Article
- Joint Cognitive Models Reveal Sources of Robust Individual Differences in Conflict Processing.Computational brain & behavior · 2026Article
- The diffusion model's drift rate parameter primarily reflects efficiency, rather than speed, of evidence accumulation.Psychonomic bulletin & review · 2026Article
- Attentional bias toward emotional faces in cognitive disengagement syndrome.Frontiers in psychology · 2026Article
- Prefrontal and parieto-occipital neural signatures of evidence accumulation and response to computerised Cognitive Behavioural Therapy in depression.Npj mental health research · 2025Article
- Dissociable Contributions of Goal-Relevant Evidence and Goal-Irrelevant Familiarity to Individual and Developmental Differences in Conflict Recognition.Cognitive science · 2024Article
- Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation.Communications biology · 2024Article
- Preferential Choice to Exert Cognitive Effort in Children with ADHD: a Diffusion Modelling Account.Research on child and adolescent psychopathology · 2023Article
- Delineating early developmental pathways to ADHD: Setting an international research agenda.JCPP advances · 2023Article
- Ahead of the (ROC) Curve: A Statistical Approach to Utilizing Ex-Gaussian Parameters of Reaction Time in Diagnosing ADHD Across Three Developmental Periods.Journal of the International Neuropsychological Society : JINS · 2022Article
- Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience.Biological psychiatry global open science · 2021Article
- Behavioral and cognitive correlates of the aperiodic (1/f-like) exponent of the EEG power spectrum in adolescents with and without ADHD.Developmental cognitive neuroscience · 2021Article
- The Deficit of Early Selective Attention in Adults With Sluggish Cognitive Tempo: In Comparison With Those With Attention-Deficit/Hyperactivity Disorder.Frontiers in psychology · 2021Article
- A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder.Neuropsychology · 2020Article
- Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2020Article
- Gait control in children with attention-deficit/hyperactivity disorder.Human movement science · 2020Article
- Modeling the effects of methylphenidate on interference and evidence accumulation processes using the conflict linear ballistic accumulator.Psychopharmacology · 2019Article
- Exploring the Variability in Reaction Times of Preschoolers at Risk of Attention-Deficit/Hyperactivity Disorder: an ex-Gaussian Analysis.Journal of abnormal child psychology · 2019Article
- Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder.Clinical psychological science : a journal of the Association for Psychological Science · 2019Article
Corrections and comments
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4 authors.
Funding
Abstract
Neuroscientific theories of attention-deficit/hyperactivity disorder (ADHD) alternately posit that cognitive aberrations in the disorder are due to acute attentional lapses, slowed neural processing, or reduced signal-to-noise ratios. However, they make similar predictions about behavioral summary statistics (response times [RTs] and accuracy), hindering the field's ability to produce strong and specific tests of these theories. The current study uses the linear ballistic accumulator (LBA; Brown & Heathcote, 2008), a mathematical model of choice RT tasks, to distinguish between competing theory predictions. Children with ADHD (n = 80) and age-matched controls (n = 32) completed a numerosity discrimination paradigm at 2 levels of difficulty, and RT data were fit to the LBA model to test theoretical predictions. Individuals with ADHD displayed slowed processing of evidence for correct responses (signal) relative to their peers but comparable processing of evidence for error responses (noise) and between-trial variability in processing (performance lapses). The findings are inconsistent with accounts that posit an increased incidence of attentional lapses in the disorder and provide partial support for those that posit slowed neural processing and lower signal-to-noise ratios. Results also highlight the utility of well-developed cognitive models for distinguishing between the predictions of etiological theories of psychopathology. (PsycINFO Database Record
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