scholarly journals Cue-induced effects on decision-making distinguish subjects with gambling disorder from healthy controls

2019 ◽  
Author(s):  
Alexander Genauck ◽  
Milan Andrejevic ◽  
Katharina Brehm ◽  
Caroline Matthis ◽  
Andreas Heinz ◽  
...  
Keyword(s):  
Decision Making ◽  
Loss Aversion ◽  
Gambling Disorder ◽  
Substance Dependence ◽  
Receiver Operating Curve ◽  
Addictive Disorders ◽  
Emotional Cues ◽  
Healthy Control ◽  
Induced Changes ◽  
Task Parameters

ABSTRACTWhile 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. To better understand the basic mechanisms of impaired decision-making in addiction, we investigated whether cue-induced changes in decision-making could distinguish gambling disorder (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.30 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 and classification 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=0.002). Applying the classifier to an independent sample yielded an AUC-ROC of 65.0% (p=0.047). 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 was characteristic of GD subjects. However, unexpectedly, 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 abuse.

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

2018 ◽  
Author(s):  
Alexander Genauck ◽  
Caroline Matthis ◽  
Milan Andrejevic ◽  
Lukas Ballon ◽  
Francesca Chiarello ◽  
...  
Keyword(s):  
Decision Making ◽  
Substance Abuse ◽  
Functional Connectivity ◽  
Gambling Disorder ◽  
Physiological Effect ◽  
Learning Processes ◽  
Addictive Disorders ◽  
Emotional Cues ◽  
Network Activation ◽  
Neural Signatures

Background: Just as substance use disorders (SUDs), gambling disorder (GD) is characterized by an increase in cue-dependent decision-making (similar to Pavlovian-to-instrumental transfer, PIT). PIT, as studied in SUDs and healthy subjects, is associated with altered communication between Nucleus Accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC). These neural differences are, however, poorly understood. For example, it is unclear whether they are due to the physiological effects of substance abuse, or rather related to learning processes and/or other etiological factors like innate traits associated with addiction. We have thus investigated whether network activation patterns during a PIT task are also altered in GD, an addictive disorder not involving substance abuse. We have specifically studied which neural PIT patterns were best at distinguishing GD from HC subjects, all to improve our understanding of the neural signatures of GD and of addiction-related PIT in general. Methods: 30 GD and 30 HC subjects completed an affective decision-making task in a functional magnetic resonance imaging (fMRI) scanner. Gambling associated and other emotional cues were shown in the background during the task, allowing us to record multivariate neural PIT signatures focusing on a network of NAcc, amygdala and OFC. We built and tested a classifier based on these multivariate neural PIT signatures using cross-validated elastic net regression. Results and Discussion: As expected, GD subjects showed stronger PIT than HC subjects because they showed stronger increase in gamble acceptance when gambling cues were presented in the background. Classification based on neural PIT signatures yielded a significant AUC-ROC (0.70, p = 0.013). When inspecting the features of the classifier, we observed that GD showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling background cues, as well as between amygdala and OFC elicited by negative and positive cues. Conclusion: We propose that HC and GD subjects are distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. Our findings suggest that neural PIT alterations in addictive disorders might not depend on the physiological effect of a substance of abuse, but on related learning processes or even innate neural traits, also found in behavioral addictions.

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

2020 ◽  
Author(s):  
Alexander Genauck ◽  
Caroline Matthis ◽  
Milan Andrejevic ◽  
Lukas Ballon ◽  
Francesca Chiarello ◽  
...  
Keyword(s):  
Decision Making ◽  
Gambling Disorder ◽  
Neural Correlates ◽  
Healthy Controls ◽  
Induced Changes

scholarly journals Decision-making inflexibility in a reversal learning task is associated with severity of problem gambling symptoms but not with a diagnosis of substance use disorder

2019 ◽  
Author(s):  
Maria Fernanda Jara-Rizzo ◽  
Juan F. Navas ◽  
Jose A. Rodas ◽  
José C. Perales
Keyword(s):  
Decision Making ◽  
Substance Use ◽  
Substance Use Disorder ◽  
Reversal Learning ◽  
Gambling Disorder ◽  
Learning Task ◽  
Learning Curves ◽  
Gambling Problems ◽  
Mixed Effect ◽  
Addictive Disorders

Background: Decisions made by individuals with disordered gambling are markedly inflexible. However, whether anomalies in learning from feedback are gambling-specific, or extend beyond gambling contexts, remains an open question. More generally, addictive disorders –including gambling disorder– have been proposed to be facilitated by individual differences in feedback-driven decision-making inflexibility, which has been studied in the lab with the Probabilistic Reversal Learning Task (PRLT). In this task, participants are first asked to learn which of two choice options is more advantageous, on the basis of trial-by-trial feedback, but, once preferences are established, reward contingencies are reversed, so that the advantageous option becomes disadvantageous and vice versa. Inflexibility is revealed by a less effective reacquisition of preferences after reversal, which can be distinguished from more generalized learning deficits.Methods: In the present study, we compared PRLT performance across two groups of 25 treatment-seeking patients diagnosed with an addictive disorder and who reported gambling problems, and 25 matched controls [18 Males/7 Females in both groups, Mage(SDage) = 25.24 (8.42) and 24.96 (7.90), for patients and controls, respectively]. Beyond testing for differences in the shape of PRLT learning curves across groups, the specific effect of problematic gambling symptoms’ severity was also assessed independently of group assignment. In order to surpass previous methodological problems, full acquisition and reacquisition curves were fitted using generalized mixed-effect models. Results: Results showed that (1) controls did not significantly differ from patients in global PRLT performance nor showed specific signs of decision-making inflexibility; and (2) regardless of whether group affiliation was controlled for or not, gambling severity was specifically associated with more inefficient learning in phases with reversed contingencies. Conclusion: Decision-making inflexibility, as revealed by difficulty to reacquire decisional preferences based on feedback after contingency reversals, seems to be associated with gambling problems, but not necessarily with a substance-use disorder diagnosis. This result aligns with gambling disorder models in which domain-general compulsivity is linked to vulnerability to develop gambling-specific problems with exposure to gambling opportunities.

scholarly journals Impulsive decision-making predicts the course of substance-related and addictive disorders

2020 ◽  
Vol 237 (9) ◽  
pp. 2709-2724
Author(s):  
Anja Kräplin ◽  
Michael Höfler ◽  
Shakoor Pooseh ◽  
Max Wolff ◽  
Klaus-Martin Krönke ◽  
...  
Keyword(s):  
Decision Making ◽  
Delay Discounting ◽  
Loss Aversion ◽  
Probability Discounting ◽  
Lower Probability ◽  
Healthy Controls ◽  
Posterior Probabilities ◽  
Addictive Disorders ◽  
Prospective Longitudinal ◽  
Lower Loss

Abstract Background This study investigated whether patterns of impulsive decision-making (i) differ between individuals with DSM-5 substance use disorders (SUD) or non-substance-related addictive disorders (ND) and healthy controls, and (ii) predict the increase of SUD and ND severity after one year. Methods In a prospective-longitudinal community study, 338 individuals (19–27 years, 59% female) were included in one of three groups: SUD (n = 100), ND (n = 118), or healthy controls (n = 120). Group differences in four impulsive decision-making facets were analyzed with the Bayesian priors: delay discounting (mean = 0.37, variance = 0.02), probability discounting for gains and for losses (each − 0.16, 0.02), and loss aversion (− 0.44, 0.02). SUD and ND severity were assessed at baseline and after 1 year (n = 312, 92%). Predictive associations between decision-making and SUD/ND severity changes were analyzed with the Bayesian prior: mean = 0.25, variance = 0.016. Results Compared with controls, the SUD group displayed steeper delay discounting and lower probability discounting for losses; the ND group displayed lower probability discounting for losses (posterior probabilities > 98%). SUD symptom increase after 1 year was predicted by steeper delay discounting and lower loss aversion; ND symptom increase by lower probability discounting for losses and lower loss aversion (posterior probabilities > 98%). There was low evidence for predictive relations between decision-making and the quantity-frequency of addictive behaviours. Discussion Impulsive decision-making characterizes SUD and ND and predicts the course of SUD and ND symptoms but not the engagement in addictive behaviours. Strength of evidence differed between different facets of impulsive decision-making and was mostly weaker than a priori expected.

scholarly journals A Research Domain Criteria Approach to Gambling Disorder and Behavioral Addictions: Decision-Making, Response Inhibition, and the Role of Cannabidiol

2021 ◽  
Vol 12 ◽  
Author(s):  
Stefano Pallanti ◽  
Anna Marras ◽  
Nikolaos Makris
Keyword(s):  
Gambling Disorder ◽  
Substance Dependence ◽  
Endocannabinoid System ◽  
Behavioral Addictions ◽  
Psychoactive Substance ◽  
Research Domain Criteria ◽  
Addictive Disorders ◽  
Substance Addiction ◽  
Positive Valence ◽  
Research Domain

Gambling Disorder (GD) has been recently re-classified in the DSM-5 under the “substance-related and addictive disorders,” in light of its genetic, endophenotypic, and phenotypic resemblances to substance dependence. Diminished control is a core defining concept of psychoactive substance dependence or addiction and has given rise to the concept of “behavioral” addictions, which are syndromes analogous to substance addiction, but with a behavioral focus other than ingestion of a psychoactive substance. The main symptom clusters are represented by loss of control, craving/withdrawal, and neglect of other areas of life, whereas in a Research Domain Criteria (RDoC) perspective, GD patients exhibit deficits in the domain of “Positive valence systems,” particularly in the “Approach motivation” and “Reward learning” constructs, as well as in the “Cognitive systems,” primarily in the “Cognitive control” construct. In the Addictions Neuroclinical Assessment (ANA), three relevant domains for addictions emerge: “Incentive salience,” “Negative Emotionality,” and “Executive Function.” The endocannabinoid system (ECS) may largely modulate these circuits, presenting a promising pharmaceutical avenue for treating addictions. Up to now, research on cannabidiol has shown some efficacy in Attention Deficit/Hyperactivity Disorder (ADHD), whereas in behavioral addictions its role has not been fully elucidated, as well as its precise action on RDoC domains. Herein, we review available evidence on RDoC domains affected in GD and behavioral addictions and summarize insights on the use of cannabidiol in those disorders and its potential mechanisms of action on reward, decisional, and sensorimotor processes.

scholarly journals Decision-making inflexibility in a reversal learning task is associated with severity of problem gambling symptoms but not with a diagnosis of substance use disorder

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
María F. Jara-Rizzo ◽  
Juan F. Navas ◽  
Jose A. Rodas ◽  
José C. Perales
Keyword(s):  
Decision Making ◽  
Substance Use ◽  
Substance Use Disorder ◽  
Reversal Learning ◽  
Gambling Disorder ◽  
Learning Task ◽  
Learning Curves ◽  
Gambling Problems ◽  
Mixed Effect ◽  
Addictive Disorders

Abstract Background Decisions made by individuals with disordered gambling are markedly inflexible. However, whether anomalies in learning from feedback are gambling-specific, or extend beyond gambling contexts, remains an open question. More generally, addictive disorders—including gambling disorder—have been proposed to be facilitated by individual differences in feedback-driven decision-making inflexibility, which has been studied in the lab with the Probabilistic Reversal Learning Task (PRLT). In this task, participants are first asked to learn which of two choice options is more advantageous, on the basis of trial-by-trial feedback, but, once preferences are established, reward contingencies are reversed, so that the advantageous option becomes disadvantageous and vice versa. Inflexibility is revealed by a less effective reacquisition of preferences after reversal, which can be distinguished from more generalized learning deficits. Methods In the present study, we compared PRLT performance across two groups of 25 treatment-seeking patients diagnosed with an addictive disorder and who reported gambling problems, and 25 matched controls [18 Males/7 Females in both groups, Mage(SDage) = 25.24 (8.42) and 24.96 (7.90), for patients and controls, respectively]. Beyond testing for differences in the shape of PRLT learning curves across groups, the specific effect of problematic gambling symptoms’ severity was also assessed independently of group assignment. In order to surpass previous methodological problems, full acquisition and reacquisition curves were fitted using generalized mixed-effect models. Results Results showed that (1) controls did not significantly differ from patients in global PRLT performance nor showed specific signs of decision-making inflexibility; and (2) regardless of whether group affiliation was controlled for or not, gambling severity was specifically associated with more inefficient learning in phases with reversed contingencies. Conclusion Decision-making inflexibility, as revealed by difficulty to reacquire decisional preferences based on feedback after contingency reversals, seems to be associated with gambling problems, but not necessarily with a substance-use disorder diagnosis. This result aligns with gambling disorder models in which domain-general compulsivity is linked to vulnerability to develop gambling-specific problems with exposure to gambling opportunities.

Emotional stress & decision-making: an emotional stressor significantly reduces loss aversion

Stress ◽  
2021 ◽  
pp. 1-7
Author(s):  
Francisco Molins ◽  
Carla Ayuso ◽  
Miguel Ángel Serrano
Keyword(s):  
Decision Making ◽  
Emotional Stress ◽  
Loss Aversion
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