Abstract
Risk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift–diffusion model to extract parameters such as threshold (‘a’—amount of evidence accumulated before making a decision), drift rate (‘v’—information processing speed) and response bias (‘z’ apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.
Highlights
Evaluation of risk is one of the core constructs critical to decision making
Reinforcement learning parameters Repeated measures ANOVA on the reinforcement learning (RL) parameters (beta (β1, β2), learning rate (η1 and η2), and perseveration, model free-model based weight (w)) of attention-deficit hyperactivity disorder (ADHD) and Healthy volunteers (HV) subjects during placebo and MPH condition showed no main effect of drug or group or drug by group interaction
Repeated measures ANOVA with covariates on the behavioural outcomes that form the primary inputs to the hierarchical drift–diffusion modelling (HDDM) model showed no main effect of drug or group or risk or effect when adjusted for depression and anxiety covariates
Summary
Evaluation of risk is one of the core constructs critical to decision making. Risk-taking can involve the evaluation of explicit risk where the likelihoods of benefit (reward) or harm (loss) are known; or ambiguity, where the likelihoods are unknown[1]. Higher risk-taking behaviours are a common feature of ADHD, which include substance abuse[3] and gambling behaviours[4]. A meta-regression analysis comparing multiple studies on risk-taking behaviour including multiple implicit (Iowa Gambling Task (IGT), Balloon Analogue risk task (BART)) and explicit forms (Game of dice, Card Playing Task, Cambridge Gambling Task (CGT) & Probabilistic discounting task)) showed greater risk-taking in ADHD5. Methylphenidate (MPH), a commonly prescribed medication has a differential influence on ADHD patients relative to healthy controls based on the sub-type of impulsivity (Table 1). These mixed differential effects call out for novel approaches to understand mechanistic differences and identify behavioural markers associated with the pathophysiology
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