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

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

In addiction, there are few human studies on the neural basis of cue-induced changes in value-based decision making (Pavlovian-to-instrumental transfer, PIT). It is especially unclear whether neural alterations related to PIT are due to the physiological effects of substance abuse or rather related to learning processes and/or other etiological factors related to addiction. We have thus investigated whether neural activation patterns during a PIT task help to distinguish subjects with gambling disorder (GD), a nonsubstance-based addiction, from healthy controls (HCs). Thirty 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. Data collection and feature modeling focused on a network of nucleus accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC) (derived from PIT and substance use disorder [SUD] studies). We built and tested a linear classifier based on these multivariate neural PIT signatures. GD subjects showed stronger PIT than HC subjects. Classification based on neural PIT signatures yielded a significant area under the receiver operating curve (AUC-ROC) (0.70,p= 0.013). GD subjects showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling cues, as well as between amygdala and OFC elicited by negative and positive cues. HC and GD subjects were thus distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. 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

Addiction Research Consortium: Losing and regaining control over drug intake (ReCoDe)—From trajectories to mechanisms and interventions

One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Decision-making and its modulation by cues in addictive disorders

Diese Dissertation fasst drei wissenschaftliche Arbeiten (Artikel) zusammen, welche sich mit veränderten Entscheidungsprozessen bei substanzgebundenen- und substanzungebundenen Abhängigkeitserkrankungen beschäftigen. In Artikel I wurde beobachtet, dass Probanden mit Alkoholkonsumstörung (AD) und Probanden mit Glücksspielstörung (GD) eine ähnlich reduzierte Verlustaversion gegenüber gesunden Kontrollen (HC) aufweisen. Beide Gruppen zeigten jedoch unterschiedliche neuronale Korrelate dieser reduzierten Verlustaversion: Während AD-Probanden eine unterschiedliche funktionelle Aktivität im dorsal-lateralen-präfrontalen Kortex im Vergleich zu HC aufwiesen, zeigten GD-Probanden eine veränderte funktionelle Konnektivität zwischen Amygdala und orbito-frontalem Kortex (OFC) bzw. medial-präfrontalem Kortex. In den Artikeln II und III wurde untersucht, ob das Verhalten und die neuronale Aktivität bei einer Verlustaversionsaufgabe bei GD-Probanden moduliert wird, wie dies in ähnlichen Studien bei AD-Probanden beobachtet wurde. Tatsächlich konnten GD-Probanden von HC-Probanden auf Grundlage ihrer veränderten Glücksspielannahme während der Präsentation spielbezogener Hinweisreize unterschieden werden. Auf neuronaler Ebene (Artikel III) konnten GD-Probanden von HC-Probanden durch die neuronalen Korrelate der reizinduzierten Veränderungen im Spielverhalten in einem Netzwerk aus Amygdala, Nucleus Accumbens und OFC unterschieden werden. Da in den Studien der Fokus auf Glücksspielabhängigkeit lag, also auf einer Abhängigkeit, welche unabhängig von Substanzmissbrauch existiert, deuten die hier diskutierten Ergebnisse darauf hin, dass verminderte Verlustaversion, sowie erhöhte reizinduzierte Veränderungen im Entscheidungsverhalten – welches beides bekannte Phänomene von Substanzabhängigkeiten sind – nicht durch Substanzmissbrauch zustande kommen. Beide Phänomene scheinen vielmehr erlernte Merkmale oder sogar prädisponierende Faktoren von Abhängigkeitserkrankungen zu sein.This dissertation summarizes three papers concerned with decision-making impairments in a substance-based and a non-substance-based addictive disorder. In Paper I, it was observed that subjects with alcohol use disorder (AD) and subjects with gambling disorder (GD) show similarly reduced loss aversion. Both groups, however, showed different neural correlates of this reduced loss aversion: While AD subjects showed different functional activity in dorsal-lateral-prefrontal cortex compared to healthy controls (HC), GD subjects showed different amygdala-orbital-frontal and amygdala-medial-prefrontal connectivity. Paper II and III investigated whether behavior and neural activity in a loss aversion task is modulated in GD subjects, as has been observed in similar studies in AD subjects. The data showed that GD subjects can be distinguished from HC subjects using a behavioral pattern of increased cue-induced gamble increase when gambling-related cues are presented in the background. On neural level (Paper III), GD subjects could be distinguished from HC subjects by neural correlates of cue-induced changes in gambling behavior in a network of amygdala, nucleus accumbens and orbital-frontal cortex. Since the focus of the studies was GD, an addiction that is independent of substance abuse, the results suggest that reduced loss aversion and increased cue-induced changes in gambling behaviors, two phenomena related to substance-based addictions, are not dependent on a substance of abuse but rather on learned characteristics or even on predisposing traits of addictive disorders