Anja Euser Erasmus University Rotterdam FADO 2011

1. Deficient feedback processing during risky decision-making in adolescents with a parental history of Substance Use Disorders Anja Euser Erasmus University Rotterdam FADO 2011

2. INTRODUCTION • Impairments in decision-making processes: a principal target in addiction research Employing gambling and decision-making tasks, numerous studies have demonstrated decision-making impairments in SUD patients, with a bias towards riskier choices This has been found in: - Chronic alcoholics(e.g., Cantrell et al., 2008) - Illicit substance users(e.g., Bechara et al., 2001; 2004) - Long-term abstinent SUD patients(e.g., Fein et al., 2004) Deficient feedback processing?

3. INTRODUCTION Two ERP components particularly sensitive for Feedback: FRN  negative deflection 200 – 300 ms following feedback An early, rapid evaluation; its amplitude is related to the simple bad versus good appraisal of feedback 2. Feedback-related P300  positive peak 300 – 600 ms following feedback A later, attention-sensitive, appraisal of outcome evaluation; P300 amplitude probably reflect the evaluation of the functional significance of feedback stimuli. P300 FRN Accumulating evidence support the idea that SUD patients display abnormal feedback processing (e.g., Kamarajan et al. 2010; Ramsey & Finn, 1997).

4. SUD ? Risky decision-making Impaired feedback processing INTRODUCTION In summary: • Risky decision-making = a hallmark phenotype of SUD • Is thought to be associated with deficient feedback processing HOWEVER: whether these deficits are present prior to SUD onset or reflect a consequence of chronic substance use remains unclear. The present study investigated whether blunted feedback processing during risky decision-making reflects a biological predisposition to SUD, by using a young high risk population

5. METHOD • High Risk adolescents (HR; n = 65; 31 males) • Parental history of SUD (DSM-IV diagnosis of substance abuse/ dependency) • Parent in treatment at Bouman GGZ • 50.8% SUD diagnosed father; 44.6% SUD diagnosed mother; 4.6% both parents • Most common diagnosis was alcohol (66.2%), followed by polydrug (24.6%), cannabis (4.6%), sedatives (3.1%) and cocaine (1.5%). • Mean age = 15.69 (SD = 2.53) • Normal risk adolescents (NR; n = 110; 59 males) • No parental history of SUD • Mean age = 15.26 (SD = 2.17) • We assessed ERPs elicited by positive and negative feedback during performance of a modified version of the Balloon Analogue Risk Task (BART)

6. METHOD • Automatic response mode BART • Dependent variables: • Mean number of pumps • FRN • P300 • Total of 60 balloons • Maximum number of 128 pumps • Optimal balance of 64 pumps

7. RESULTS • Sample characteristics: • Both groups comparable in age and gender • HR adolescents: > Impulsiveness (p = .04) and Externalizing behavior (p = .01) • Self-reported substance use: no significant group differences in age of onset alcohol, nicotine or cannabis use; HR adolescents used significant more cannabis than NR controls (p = .04). • Behavioral data: * * No significant Gender or Gender x Group interaction-effects

8. RESULTS HR – Negative Feedback HR – Positive Feedback NR – Negative Feedback NR – Positive Feedback [µV] Feedback Related Negativity (FRN) FCz -10 -5 0 5 10 [ms] -200 0 200 400 600 No significant Feedback valence, Group, Gender or Gender x Group interaction-effects.

9. RESULTS HR – Negative Feedback HR – Positive Feedback NR – Negative Feedback NR – Positive Feedback [µV] Pz Feedback-related P300 amplitude -10 0 10 20 30 -200 0 200 400 600 [ms] Main effect Feedback valence (P300 > for negative feedback than for positive feedback) Main effect Group (HR group significantly < P300 in response to both positive and negative feedback) No significant Gender or interaction-effects. Additional analysis to control for pre-existing differences: results not influenced by Impulsiveness, Externalizing behavior or frequency of cannabis use!

10. CONCLUSION • Adolescents at presumed high risk for developing a SUD are characterized by decision-making impairments, with a bias towards riskier choices • Blunted P300 in response to both positive and negative feedback may reflect poor integration of feedback across trials: reduced sensitivity for feedback  Hyposensitivity for future consequences. • Our ERP findings: it is not the ability to rapidly evaluate feedback valence that is influenced by a parental history of SUD, but rather the ability to subsequently assign sufficient attention to further process motivationally salient events. • Hence, HR adolescents may be unable to use ongoing feedback to guide current as well as future behavior and therefore, their behavior is guided by immediate contingency. This could contribute to the onset of SUD and an increased propensity toward substance abuse.

11. DISCUSSION • Absence of an FRN effect? • P300 a general deficit? • Studies of young relatives of SUD offer a valuable opportunity to characterize premorbid traits in SUD The ability to identify vulnerability markers among High Risk adolescents would: • facilitate prospective studies that could clarify trajectories of developing disorders, • delineate etiological mechnisms, and • facilitate the development of preventive interventions

12. Thanks for your attention! ?