Reduced loss aversion in pathological gambling and alcohol dependence is associated with differential alterations in amygdala and prefrontal functioning

Abstract

Diagnostic criteria for pathological gambling and alcohol dependence (AD) include repeated addictive behavior despite severe negative consequences. However, the concept of loss aversion (LA) as a facet of value-based decision making has not yet been used to directly compare these disorders. We hypothesized reduced LA in pathological gamblers (PG) and AD patients, correlation of LA with disorder severity, and reduced loss-related modulation of brain activity. 19 PG subjects, 15 AD patients and 17 healthy controls (HC) engaged in a LA task in a functional magnetic resonance imaging setting. Imaging analyses focused on neural gain and loss sensitivity in the meso-cortico-limbic network of the brain. Both PG and AD subjects showed reduced LA. AD subjects showed altered loss-related modulation of activity in lateral prefrontal regions. PG subjects showed indication of altered amygdala-prefrontal functional connectivity. Although we observed reduced LA in both a behavioral addiction and a substance-related disorder our neural findings might challenge the notion of complete neuro-behavioral congruence of substance-use disorders and behavioral addictions.

Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls

“…HC subjects may not show this effect because of stronger signal transmission related to negative cues from Alexander Genauck 33 amygdala to OFC. Similarly, it has been found that reduced loss aversion in GD subjects was associated with reduced loss-related functional connectivity from amygdala to ventral medial prefrontal cortex in a pure mixed-gambles task (Genauck et al, 2017). This highlights that impaired decision-making in GD during a pure mixed-gambles task, as well as during an affective mixed-gambles task, may draw from the same functional neural substrate.…”

“…We were inspired by established mixed-gambles decision-making tasks (Genauck et al, 2017;Tom, Fox, Trepel, & Poldrack, 2007) and mixed-gambles decision-making tasks with the influence of affective cues (Charpentier et al, 2015;Genauck et al, under review). As affective cues, four sets of images were assembled: 1) 67 gambling images, showing a variety of gambling scenes, and paraphernalia (gambling cues); 2) 31 images showing negative consequences of gambling (negative cues); 3) 31 images showing positive effects of abstinence from gambling (positive cues); 4) 24 neutral IAPS images (neutral cues).…”

“…Gambles were created by randomly drawing with replacement from a matrix with possible gambles consisting of 12 levels of gains (14, 16, …, 36) and 12 levels of losses (-7, -8, …, -18) ( Fig. 1) (Genauck et al, 2017;Tom et al, 2007;Tversky & Kahneman, 1992). In every subject, we stratified gambles according to mean and variance of gain, loss, gamble variance, and…”

“…Predictors were centralized values of gain, centralized absolute values of Alexander Genauck 18 loss, euclidean distance (ed) from gamble matrix as indicator of gamble difficulty (Tom et al, 2007) (all down-sampled from twelve to four steps) (Genauck et al, under review, 2017;Tom et al, 2007), and cue category (c). We defined the gamble value ( ), according to a modeling of the affective mixed-gambles task that has been observed to be successful in distinguishing GD from HC subjects (Genauck et al, under review) and which is also useful for modeling the fMRI data (Genauck et al, 2017;Tom et al, 2007). According to these findings we focus on an additive change in gamble acceptance depending on the cues presented in the background.…”

“…Besides cue reactivity, and just like in SUDs, GD subjects display impaired value-based decision-making. For example, GD subjects show increased risk taking, higher discounting of delayed rewards (delay discounting) and reduced loss aversion (Clark et al, 2013;Dixon, Marley, & Jacobs, 2003;Genauck et al, 2017;Glimcher & Rustichini, 2004;Lorains et al, Alexander Genauck 7 2014;MacKillop et al, 2011;Madden, Petry, & Johnson, 2009;N. M. Petry, 2012;Platt & Huettel, 2008;Romanczuk-Seiferth et al, 2014;Wiehler & Peters, 2015).…”