Deficient feedback processing during risky decision-making in adolescents with a parental history of Substance Use Disorders

Anja EuserErasmus University Rotterdam FADO 2011

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?

INTRODUCTION

Two ERP components particularly sensitive for Feedback:

1. 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).

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

INTRODUCTION

SUD

Impaired feedback processin

g

Risky decision-making

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)

METHOD

Automatic response mode BART

Dependent variables:• Mean number of pumps• FRN• P300

Total of 60 balloonsMaximum number of 128 pumpsOptimal balance of 64 pumps

57

58

59

60

61

62

63

64

HR NR

Group

Mean # of pumps

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:

3800

3850

3900

3950

4000

4050

4100

4150

4200

4250

4300

HR NR

Group

Mean Deliberation Time (ms)

RESULTS

* *

No significant Gender or Gender x Group interaction-effects

RESULTS

HR – Negative Feedback

HR – Positive Feedback

NR – Negative Feedback

NR – Positive Feedback

[µV]

[ms]

FCz

-200 0 200 400 600

-10

-5

0

5

10

Feedback Related Negativity (FRN)

No significant Feedback valence, Group, Gender or Gender x Group interaction-effects.

RESULTS

HR – Negative Feedback

HR – Positive Feedback

NR – Negative Feedback

NR – Positive Feedback

-200 0 200 400 600 [ms]

-10

0

10

20

30

[µV] Pz

Feedback-related P300 amplitude

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!

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.

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 Riskadolescents would:

– facilitate prospective studies that could clarify trajectories of developing disorders, – delineate etiological mechnisms, and – facilitate the development of preventive interventions

Thanks for your attention!