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 nonsubstance-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 decisionmaking 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 cueinduced 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 abuse KEYWORDS

In everyday life we are constantly updating our moral judgements of people and actions as we learn new information. We developed a novel paradigm to investigate how people update their moral judgements of fairness-related actions upon receiving contextual information regarding the deservingness of the action recipient. Participants (N = 313) observed a variant of the dictator game, whereby a ‘Decision-maker’ was given 10 dollars and decided how much of this amount to share with another person termed the ‘Receiver’. Participants first made an initial, context-absent judgement of the Decision-maker’s offer to the Receiver, and then a subsequent judgement of the same offer after learning contextual information regarding the Receiver’s previous offer to another person (context-present judgement). This sequence was repeated for varying combinations of Decision-maker and Receiver offers. Functional Principle Component Analyses revealed that participants showed patterns of judgements across offers that were interpretable in relation to moral norms, but that these patterns varied across individuals. Participants who endorsed equal-split (5 dollar) offers in their context-absent judgements also endorsed offers made by Decision-makers that were similar to the previous offer made by the Receiver (i.e. indirectly reciprocal offers). Participants who endorsed high (>5 dollar) offers in context-absent judgements also endorsed Decision-maker offers that were more generous than those made by the Receiver. Our findings show that most participants flexibly switched from relying on commonly studied context-independent norms (generosity, equality), to relying on related, context-dependent norms (relative generosity, indirect reciprocity), as they successfully integrate contextual information. The paradigm we have developed also provides a novel framework for investigating how moral judgements evolve in real time as people learn more information about a given situation.

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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.

In everyday life we are constantly updating our moral judgements as we learn new information. However, this judgement updating process has not been systematically studied. We investigated how people update their moral judgements of fairness-related actions of others after receiving contextual information regarding the deservingness of the action recipient. Participants (N = 313) observed a virtual ‘Decision-maker’ share a portion of $10 with a virtual ‘Receiver’. Participants were aware that the Decision-maker made these choices knowing the Receiver’s previous offer to another person. Participants first made a context-absent judgement of the Decision-maker’s offer to the Receiver, and then a subsequent context-present judgement of the same offer after learning the Receiver’s previous offer. This sequence was repeated for varying dollar values of Decision-makers’ and Receivers’ offers. Patterns of judgements varied across individuals and were interpretable in relation to moral norms. Most participants flexibly switched from relying on context-independent norms (generosity, equality) to related, context-dependent norms (relative generosity, indirect reciprocity) as they integrated contextual information. Judgement of low offers varied across individuals, with a substantial minority of participants withholding their context-absent judgements of selfishness, and another minority that was lenient towards selfishness across both judgements. Our paradigm provides a novel framework for investigating how moral judgements evolve in real time as people learn more information about a given situation.

Humans tend to present themselves in a positive light to gain social approval. This behavioral trait, termed social desirability, is important for various types of social success. Surprisingly, investigation into the neural underpinnings of social desirability has been limited and focused only on interindividual differences in dopamine receptor binding. These studies revealed reduced dopamine receptor binding in the striatum of individuals who are high in trait social desirability. Interestingly, high dopamine signaling has been associated with low white-matter integrity, irrespective of social desirability. Based on these findings, we hypothesized that a positive association exists between trait social desirability and the white-matter microstructure of the external capsule, which carries fibers to the striatum from the prefrontal cortex. To test this hypothesis, we collected diffusion tensor imaging data and examined the relationship between fractional anisotropy of the external capsule and participants' social desirability-our analysis revealed a positive association. As a second exploratory step, we examined the association between social desirability and white-matter microstructure throughout the whole brain. Our whole-brain analysis revealed associations within multiple major white-matter tracts, demonstrating that socially desirable behavior relies on connectivity between distributed brain regions.

How we exert control over our decision making has been investigated using conflict tasks, which involve stimuli containing elements that are either congruent or incongruent. In these tasks, participants adapt their decision making strategies following exposure to incongruent stimuli. According to conflict monitoring accounts, conflicting stimulus features are detected in medial frontal cortex, and the extent of experienced conflict scales with response time (RT) and frontal theta--band activity in the electroencephalogram (EEG). However, the consequent adjustments to decision processes following response conflict are not well--specified. To characterise these adjustments and their neural implementation we recorded EEG during a Flanker task. We traced the time--courses of performance monitoring processes (frontal theta) and multiple processes related to perceptual decision making. In each trial participants judged which of two overlaid gratings forming a plaid stimulus (termed the S1 target) was of higher contrast. The stimulus was divided into two sections, which each contained higher contrast gratings in either congruent or incongruent directions. Shortly after responding to the S1 target, an additional S2 target was presented, which was always congruent. Our EEG results suggest enhanced sensory evidence representations in visual cortex and reduced evidence accumulation rates for S2 targets following incongruent S1 stimuli. Frontal theta amplitudes positively correlated with RT following S1 targets (in line with conflict monitoring accounts). Following S2 targets there was no such correlation, and theta amplitude profiles instead resembled decision evidence accumulation trajectories. Based on these differing amplitude profiles across S1 and S2 we formulated a novel theory of frontal theta and performance monitoring, which accounts for differing theta amplitude profiles previously observed across tasks that do and do not involve conflict. We propose that frontal theta does not actually index conflict detection but instead reflects a more general performance monitoring process related to decision confidence and rapid error detection.

Background:Just as substance use disorders (SUD), gambling disorder (GD) is characterized by an increase in cue-dependent decision-making (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). However, these neural differences are 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 healthy control (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 Alexander Genauck 5 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 nucleus accumbens (NAcc) and amygdala elicited by gambling background cues, as well as between amygdala and orbitofrontal cortex (OFC) elicited by negative and positive cues. Conclusion:We propose that GD and HC 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.Alexander Genauck 6