Modeling behavioral reactivity to losses and rewards on the Balloon Analogue Risk Task (BART): Moderation by alcohol problem severity.

Abstract

The relationship between risk-taking behavior and substance dependence has proven to be complex, particularly when examining across participants expressing a range of substance use problem severity. While main indices of risk-taking in the Balloon Analogue Risk Task (BART) positively associate with problematic alcohol use in adolescent populations (e.g., MacPherson, Magidson, Reynolds, Kahler, & Lejuez, 2010), several studies have observed a negative relationship when examining behavior within adult substance using populations (Ashenhurst, Jentsch, & Ray, 2011; Campbell, Samartgis, & Crowe, 2013). To examine potential mechanisms that underlie this negative relationship, we implemented multilevel regression models on trial-by-trial BART data gathered from 295 adult problem drinkers. These models accounted for participant behavior on trials following balloon bursts or cash outs as indices of loss and reward reactivity, respectively, and included control variables including age, IQ, and individual delay discounting rate. Results revealed that individual trial pumping was significantly predicted by trial number, and by whether or not the previous trial was a big burst or a big cash out (i.e., large magnitude of potential gains) in a manner consistent with a “near-miss” effect. Furthermore, severity of alcohol problems moderated the effect of a previous trial big burst, but not of a big cash out, on subsequent trial behavior such that those with greater severity demonstrated relative insensitivity to this “near-miss” effect. These results extend previous studies suggesting that alcohol abusers are less risky on the BART by specifying a mechanism underlying this pattern, namely, diminished reactivity to large magnitude losses.

Adaptive Adolescent Flexibility: Neurodevelopment of Decision-making and Learning in a Risky Context

“…We modeled whether the number of pumps on a given trial varied depending on the outcome of the previous trial. Consistent with prior studies (Ashenhurst, Bujarski, Jentsch, & Ray, 2014; Mata, Hau, Papassotiropoulos, & Hertwig, 2012), our Level 1 equation was $$\begin{array}{c}center\text{Number}\text{of}{\text{Pumps}}_{ij}=b_{0j}+b_{1j}\left({\text{Explosion}}_{\left(N-1\right)}\right)\\ +b_{2j}\left({\text{Explosion}}_{\left(N\right)}\right)\\ +b_{3j}\left(\text{Trial}\text{Number}\right)+{\epsilon }_{ij}\end{array}$$Total pumps on a particular trial ( i ) for a particular adolescent ( j ) was modeled as a function of the average number of pumps across the task ( b 0 j ) and whether the previous trial ( b 1 j ) was an explosion or cash-out (coded Explosion ( N − 1) = 0; Cash-Out ( N − 1) = 1). In addition, we included two controls, including whether the current trial resulted in an explosion or a cash-out ( b 2 j ; coded Explosion ( N ) = 1; Cash-Out ( N ) ) = 0) and the trial number ( b 3 j ).…”

Decision‐ and feedback‐related brain potentials reveal risk processing mechanisms in patients with alcohol use disorder

“…That AUD did not make riskier choices than HC is in contrast to reports of enhanced risk propensity in AUD or problem drinkers but in agreement with reports of normal choice behavior (Moallem & Ray, ) or even more risk‐averse decisions in the BART (Ashenhurst, Bujarski, Jentsch, & Ray, ; Ashenhurst, Jentsch, & Ray, ). Contrary to present expectation, impulsivity did not affect choice behavior.…”

Dopamine Gene Profiling to Predict Impulse Control and Effects of Dopamine Agonist Ropinirole

“…Mata and colleagues inferred risk taking from average total number of button presses on collected trials. This study quantified behavioral modification on a trial-by-trial basis as a result of rewards and losses to assess impulsive decision-making (Ashenhurst, Bujarski, Jentsch, & Ray, 2014) and extend the findings of Mata and colleagues to show how DAT polymorphism dictates impulsive decision-making.…”