Cue‐induced effects on decision‐making distinguish subjects with gambling disorder from healthy controls

While an increased impact of cues on decision‐making has been associated with substance dependence, it is yet unclear whether this is also a phenotype of non‐substance‐related addictive disorders, such as gambling disorder (GD). To better understand the basic mechanisms of impaired decision‐making in addiction, we investigated whether cue‐induced changes in decision‐making could distinguish GD from healthy control (HC) subjects. We expected that cue‐induced changes in gamble acceptance and specifically in loss aversion would distinguish GD from HC subjects. Thirty GD subjects and 30 matched HC subjects completed a mixed gambles task where gambling and other emotional cues were shown in the background. We used machine learning to carve out the importance of cue dependency of decision‐making and of loss aversion for distinguishing GD from HC subjects. Cross‐validated classification yielded an area under the receiver operating curve (AUC‐ROC) of 68.9% (p = .002). Applying the classifier to an independent sample yielded an AUC‐ROC of 65.0% (p = .047). As expected, the classifier used cue‐induced changes in gamble acceptance to distinguish GD from HC. Especially, increased gambling during the presentation of gambling cues characterized GD subjects. However, cue‐induced changes in loss aversion were irrelevant for distinguishing GD from HC subjects. To our knowledge, this is the first study to investigate the classificatory power of addiction‐relevant behavioral task parameters when distinguishing GD from HC subjects. The results indicate that cue‐induced changes in decision‐making are a characteristic feature of addictive disorders, independent of a substance of abuseDFG, 103586207, GRK 1589: Sensory Computation in Neural System