16 Effect of methylphenidate on risk preference in attention deficit hyperactivity disorder. (28th May 2019)

• Record Type: Journal Article
• Authors: Mandali, Alekhya; Sethi, Arjun; Harrison, Neil A; Voon, Valerie
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 90(2019)Supplement 2
• Page Start: A7
• Page End: A8
• Publication Date: 2019-05-28
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2019-BNPA.16
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Introduction: Methylphenidate (MPH) is one of most commonly prescribed drug to patients with Attention Deficit Hyperactivity Disorder (ADHD). While MPH has been known to improve executive functions, its effect on impulsivity, one of the cardinal symptoms in ADHD has mixed findings in part depending on baseline. Data driven computational models such as drift diffusion model utilize behavioural measures to explain subtle changes that are not sensitive to traditional analysis. Here, we aim to analyse risk preference in ADHD and healthy controls and the effects of MPH. Methods: Twenty-four healthy volunteers and 25 ADHD patients were tested on the 2 step sequential learning task in both MPH-ON and MPH-OFF conditions. We calculated the risk associated with each choice (variance of reward probability) and defined the choice with maximum variance as the risky one, for all 134 trials. With behavioural measures (selected choice- risky vs non-risky and response time) as inputs and risk as an independent factor, we extracted threshold ( a ), drift rate ( v ) and response bias ( z ) parameters using a hierarchical drift diffusion model (HDDM) for both groups during ON and OFF drug condition. Statistical analysis on the parameters was analysed using Bayesian factors. Results: Bayesian repeated measures ANOVA showed evidence for changes in response bias ( z ) but not in threshold and drift rate. A strong evidence for main effect of drug(BF10 =6.03×10 11 ), group(BF10 =86344) and group by drug interaction(BF10 =3.65×10 6 ) was observed. Post-hoc Bayesian independent sample t-tests showed strong evidence that the patient group had a higher preference towards the risky choice during both the ON (BF10 =8.94×10 14 ) and OFF (BF10 =20.9) conditions. Post-hoc Bayesian paired sample t-tests showed strong evidence for the drug to induce a preference towards the risky choice in both the HV(BF10 =397.1) and ADHD(BF10 =1.16×10 10 ) population. Behavioural results show a drug by group interaction ( F (1, 0.01)=11.80, p=0.001) on number of risky choices. Post-hoc analysis using paired sample t-test showed a significant increase in risky behaviour due to drug in the ADHD( t (24)= −3.5, p<0.005) but not healthy subjects. No differences were found in the traditional reinforcement learning parameters between the groups. Conclusions: Using a novel analysis, we showed that ADHD subjects had a greater bias towards risk preference and further that MPH increases risk preference in both ADHD and HV with a comparatively greater effect on the patient population. Critically we observe an effect on response bias highlighting the role of apriori information in influencing risky decision making.