Computational models, in conjunction with (neuro)cognitive tests, are increasingly used to understand the cognitive characteristics of participants with attention-deficit/hyperactivity disorder (ADHD). We reviewed 50 studies from a broad range of cognitive tests for ADHD to synthesize findings and to summarize the new insights provided by three commonly applied computational models (i.e., diffusion decision models, absolute accumulator models, ex-Gaussian distribution models). Four areas are discussed to improve the utility of (neuro)cognitive testing for ADHD: (a) the requirements for appropriate application of the computational models; (b) the consideration of sample characteristics and neurophysiological measures; (c) the integration of findings from cognitive psychology into the literature of cognitive testing to reconcile mixed evidence; and (d) future directions for the study of ADHD endophenotypes. We illustrate how computational models refine our understanding of cognitive concepts (slow processing speed, inhibition failures) presumed to characterize ADHD. We also show that considering sample characteristics and integrating findings from computational models and neurophysiological measures provide evidence for ADHD endophenotype-specific cognitive characteristics. However, studying the cognitive characteristics of ADHD endophenotypes often lies beyond the scope of existing research for three reasons: some cognitive tests lack sensitivity to detect clinical characteristics; analysis methods do not allow the study of subtle cognitive differences; and the precategorization of participants restricts the study of symptom severity on a continuous spectrum. We provide recommendations for cognitive testing, computational modeling, and integrating electrophysiological measures to produce more valuable tools in research and clinical practice (above and beyond the research domain of ADHD).

Objective: To Explore whether subtypes and comorbidities of attention-deficit hyperactivity disorder (ADHD) induce distinct biases in cognitive components involved in information processing. Method: Performance on the Integrated Visual and Auditory Continuous Performance Test (IVA-CPT) was compared between 150 children (aged 7 to 10) with ADHD, grouped by DSM-5 presentation (ADHD-C, ADHD-I) or co-morbid diagnoses (anxiety, oppositional defiant disorder [ODD], both, neither), and 60 children without ADHD. Diffusion decision modeling decomposed performance into cognitive components. Results: Children with ADHD had poorer information integration than controls. Children with ADHD-C were more sensitive to changes in presentation modality (auditory/visual) than those with ADHD-I and controls. Above and beyond these results, children with ADHD+anxiety+ODD had larger increases in response biases when targets became frequent than children with ADHD-only or with ADHD and one comorbidity. Conclusion: ADHD presentations and comorbidities have distinct cognitive characteristics quantifiable using DDM and IVA-CPT. We discuss implications for tailored cognitive-behavioral therapy.

We investigated aging effects in a task-switch paradigm with degraded stimuli administered to college students, 61–74 year olds, and 75–89 year olds. We studied switch costs (the performance difference between task-repeat and task-switch trials) in terms of accuracy and mean reaction times (RTs). Previous aging research focused on switch costs in terms of mean RTs (with accuracy at ceiling). Our results emphasize the importance of distinguishing between switch costs indexed by accuracy and by RTs because these measures lead to different interpretations. We used the Diffusion Decision Model (DDM; Ratcliff, 1978) to study the cognitive components contributing to switch costs. The DDM decomposed the cognitive process of task switching into multiple components. Two parameters of the model, the quality of evidence on which decisions were based (drift rate) and the duration of processes outside the decision process (nondecision time component), indexed different sources of switch costs. We found that older participants had larger switch costs indexed by nondecision time component than younger participants. This result suggests age-related deficits in preparatory cognitive processes. We also found group differences in switch costs indexed by drift rate for switch trials with high stimulus interference (stimuli with features relevant for both tasks). This result suggests that older participants have less effective cognitive processes involved in resolving interference. Our findings show that age-related effects in separate components of switch costs can be studied with the DDM. Our results demonstrate the utility of using discrimination tasks with degraded stimuli in conjunction with model-based analyses.

We experimentally study settings where an individual may have an incentive to adopt negative beliefs about another's intentions in order to justify egoistic behavior. Our first study uses a game in which a player can take money from an opponent in order to prevent the opponent from subsequently causing harm. We hypothesize that players will justify taking by engaging in "strategic cynicism," convincing themselves of the opponent's ill intentions. We elicit incentivized beliefs both from players with such an incentive and from neutral third parties with no incentive to bias their beliefs. We find no difference between the two sets of beliefs, suggesting that people do not negatively bias their beliefs about a strategic opponent even when they have an incentive to do so. This result contrasts with Di Tella, et al. (2015), who argue that they provide evidence of strategic cynicism. We reconcile the discrepancy by using Di Tella, et al.'s, data, a simple model of strategic belief manipulation and a novel experiment in which we replicate Di Tella, et al.'s, experiment and also elicit the beliefs of neutral third parties. Across three experimental datasets, the results provide no evidence of negatively biased beliefs about others' intentions. However, Di Tella, et al.'s, results and our novel data indicate that those with a greater incentive to view others' intentions negatively exhibit relatively less positive beliefs than those without such incentives.

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