L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action

A dopaminergic basis of behavioral control

Both goal-directed and automatic processes shape human behavior, but these processes often conflict. Behavioral control is the decision about which process guides behavior. Despite the importance of behavioral control for adaptive decision-making, its neural mechanisms remain unclear. Critically, it is unknown if there are mechanisms for behavioral control that are distinct from those supporting the formation of goal-relevant knowledge. We performed deep phenotyping of individual dopamine system function by combining multiple PET scans, fMRI, and dopaminergic drug administration in a within-subject, double-blind, placebo-controlled design. Subjects performed a rule-based response time task, with goal-directed and automatic decision-making operationalized as model-based and model-free influences on behavior. We found a double dissociation between two aspects of ventral striatal dopamine physiology: D2/3 receptor availability and dopamine synthesis capacity. Convergent and causal evidence indicated that D2/3 receptors regulate behavioral control by enhancing model-based and blunting model-free influences on behavior but do not affect model-based knowledge formation. In contrast, dopamine synthesis capacity was linked to the formation of model-based knowledge but not behavioral control. D2/3 receptors also modulated frontostriatal functional connectivity, suggesting they regulate behavioral control by gating prefrontal inputs to the striatum. These results identify central mechanisms underlying individual and state differences in behavioral control and point to striatal D2/3 receptors as targets for interventions for improving goal-directed behavior.

Assessing the influence of dopamine and mindfulness on the formation of routines in visual search

Given experience in cluttered but stable visual environments, our eye-movements form stereotyped routines that sample task-relevant locations, while not mixing-up routines between similar task-settings. Both dopamine signaling and mindfulness have been posited as factors that influence the formation of such routines, yet quantification of their impact remains to be tested in healthy humans. Over two sessions, participants searched through grids of doors to find hidden targets, using a gaze-contingent display. Within each session, door scenes appeared in either one of two colors, with each color signaling a differing set of likely target locations. We derived measures for how well target locations were learned (target-accuracy), how routine were sets of eye-movements (stereotypy), and the extent of interference between the two scenes (setting-accuracy). Participants completed two sessions, where they were administered either levodopa (dopamine precursor) or placebo (vitamin C), under double-blind counterbalanced conditions. Dopamine and trait mindfulness (assessed by questionnaire) interacted to influence both target-accuracy and stereotypy. Increasing dopamine improved accuracy and reduced stereotypy for high mindfulness scorers, but induced the opposite pattern for low mindfulness scorers. Dopamine also disrupted setting-accuracy invariant to mindfulness. Our findings show that mindfulness modulates the impact of dopamine on the target-accuracy and stereotypy of eye-movement routines, whereas increasing dopamine promotes interference between task-settings, regardless of mindfulness. These findings provide a link between non-human and human models regarding the influence of dopamine on the formation of task-relevant eye-movement routines and provide novel insights into behavior-trait factors that modulate the use of experience when building adaptive repertoires.

Uncertainty of treatment efficacy moderates placebo effects on reinforcement learning

The placebo-reward hypothesis postulates that positive effects of treatment expectations on health (i.e., placebo effects) and reward processing share common neural underpinnings. Moreover, experiments in humans and animals indicate that reward uncertainty increases striatal dopamine, which is presumably involved in placebo responses and reward learning. Therefore, treatment uncertainty analogously to reward uncertainty may affect updating from rewards after placebo treatment. Here, we address whether different degrees of uncertainty regarding the efficacy of a sham treatment affect reward sensitivity. In an online between-subjects experiment with N = 141 participants, we systematically varied the provided efficacy instructions before participants first received a sham treatment that consisted of listening to binaural beats and then performed a probabilistic reinforcement learning task. We fitted a Q-learning model including two different learning rates for positive (gain) and negative (loss) reward prediction errors and an inverse gain parameter to behavioral decision data in the reinforcement learning task. Our results yielded an inverted-U-relationship between provided treatment efficacy probability and learning rates for gain, such that higher levels of treatment uncertainty, rather than of expected net efficacy, affect presumably dopamine-related reward learning. These findings support the placebo-reward hypothesis and suggest harnessing uncertainty in placebo treatment for recovering reward learning capabilities.

Connection Failure: Differences in White Matter Microstructure Are Associated with 5-HTTLPR but Not with Risk Seeking for Losses

S/S carriers of 5-HTTLPR have been found to be more risk seeking for losses compared to L/L carriers. This finding may be the result of reduced top-down control from the frontal cortex due to altered signal pathways involving the amygdala and ventral striatum. The serotonergic system is known to be involved in neurodevelopment and neuroplasticity. Therefore, the aim of this study was to investigate whether structural differences in white matter can explain the differences in risk-seeking behaviour. Lower structural connectivity in S/S compared to L/L carriers and a negative relationship between risk seeking for losses and connectivity were assumed. Diffusion-weighted imaging was used to compute diffusion parameters for the frontostriatal and uncinate tract in 175 genotyped individuals. The results showed no significant relationship between diffusion parameters and risk seeking for losses. Furthermore, we did not find significant differences in diffusion parameters of the S/S vs. L/L group. There were only group differences in the frontostriatal tract showing stronger structural connectivity in the S/L group, which is also reflected in the whole brain approach. Therefore, the data do not support the hypothesis that the association between 5-HTTLPR and risk seeking for losses is related to differences in white matter pathways implicated in decision-making.

L-DOPA and oxytocin influence the neural correlates of performance monitoring for self and others

RATIONALE

The ability to monitor the consequences of our actions for others is imperative for flexible and adaptive behavior, and allows us to act in a (pro)social manner. Yet, little is known about the neurochemical mechanisms underlying alterations in (pro)social performance monitoring.

OBJECTIVE

The aim of this functional magnetic resonance imaging (fMRI) study was to improve our understanding of the role of dopamine and oxytocin and their potential overlap in the neural mechanisms underlying performance monitoring for own versus others' outcomes.

METHOD

Using a double-blind placebo-controlled cross-over design, 30 healthy male volunteers were administered oxytocin (24 international units), the dopamine precursor L-DOPA (100 mg + 25 mg carbidopa), or placebo in three sessions. Participants performed a computerized cannon shooting game in two recipient conditions where mistakes resulted in negative monetary consequences for (1) oneself or (2) an anonymous other participant.

RESULTS

Results indicated reduced error-correct differentiation in the ventral striatum after L-DOPA compared to placebo, independent of recipient. Hence, pharmacological manipulation of dopamine via L-DOPA modulated performance-monitoring activity in a brain region associated with reward prediction and processing in a domain-general manner. In contrast, oxytocin modulated the BOLD response in a recipient-specific manner, such that it specifically enhanced activity for errors that affected the other in the pregenual anterior cingulate cortex (pgACC), a region previously implicated in the processing of social rewards and prediction errors. Behaviorally, we also found reduced target sizes-indicative of better performance-after oxytocin, regardless of recipient. Moreover, after oxytocin lower target sizes specifically predicted higher pgACC activity when performing for others.

CONCLUSIONS

These different behavioral and neural patterns after oxytocin compared to L-DOPA administration highlight a divergent role of each neurochemical in modulating the neural mechanisms underlying social performance monitoring.

Arbitration between model-free and model-based control is not affected by transient changes in tonic serotonin levels

BACKGROUND

Serotonin has been suggested to modulate decision-making by influencing the arbitration between model-based and model-free control. Disruptions in these control mechanisms are involved in mental disorders such as drug dependence or obsessive-compulsive disorder. While previous reports indicate that lower brain serotonin levels reduce model-based control, it remains unknown whether increases in serotonergic availability might thus increase model-based control. Moreover, the mediating neural mechanisms have not been studied yet.

AIM

The first aim of this study was to investigate whether increased/decreased tonic serotonin levels affect the arbitration between model-free and model-based control. Second, we aimed to identify the underlying neural processes.

METHODS

We employed a sequential two-stage Markov decision-task and measured brain responses during functional magnetic resonance imaging in 98 participants in a randomized, double-blind cross-over within-subject design. To investigate the influence of serotonin on the balance between model-free and model-based control, we used a tryptophan intervention with three intervention levels (loading, balanced, depletion). We hypothesized that model-based behaviour would increase with higher serotonin levels.

RESULTS

We found evidence that neither model-free nor model-based control were affected by changes in tonic serotonin levels. Furthermore, our tryptophan intervention did not elicit relevant changes in Blood-Oxygenation-Level Dependent activity.

The effects of paranoia and dopamine on perception of cohesion and conspiracy: a pre-registered, double-blind, placebo-controlled experiment

Paranoia is a common symptom of psychotic disorders but is also present on a spectrum of severity in the general population. Although paranoia is associated with an increased tendency to perceive cohesion and conspiracy within groups, the mechanistic basis of this variation remains unclear. One potential avenue involves the brain's dopaminergic system, which is known to be altered in psychosis. In this study, we used large-N online samples to establish the association between trait paranoia and perceptions of cohesion and conspiracy. We further evaluated the role of dopamine on perceptions of cohesion and conspiracy using a double-blind, placebo-controlled laboratory experiment where participants received levodopa or a placebo control. Our results were mixed: group perceptions and perceptions of cohesion were higher among more paranoid individuals but were not altered under dopamine administration. We outline the potential reasons for these discrepancies and the broader implications for understanding paranoia in terms of dopamine dysregulation.

Dopamine Increases Accuracy and Lengthens Deliberation Time in Explicit Motor Skill Learning

Although animal research implicates a central role for dopamine in motor skill learning, a direct causal link has yet to be established in neurotypical humans. Here, we tested if a pharmacological manipulation of dopamine alters motor learning, using a paradigm which engaged explicit, goal-directed strategies. Participants (27 females; 11 males; aged 18-29 years) first consumed either 100 mg of levodopa (n = 19), a dopamine precursor that increases dopamine availability, or placebo (n = 19). Then, during training, participants learnt the explicit strategy of aiming away from presented targets by instructed angles of varying sizes. Targets jumped mid-movement by the instructed aiming angle. Task success was thus contingent upon aiming accuracy and not speed. The effect of the dopamine manipulations on skill learning was assessed during training and after an overnight follow-up. Increasing dopamine availability at training improved aiming accuracy and lengthened reaction times, particularly for larger, more difficult aiming angles, both at training and, importantly, at follow-up, despite prominent session-by-session performance improvements in both accuracy and speed. Exogenous dopamine thus seems to result in a learnt, persistent propensity to better adhere to task goals. Results support the proposal that dopamine is important in engagement of instrumental motivation to optimize adherence to task goals, particularly when learning to execute goal-directed strategies in motor skill learning.

Erotic cue exposure increases physiological arousal, biases choices toward immediate rewards, and attenuates model-based reinforcement learning

Computational psychiatry focuses on identifying core cognitive processes that appear altered across distinct psychiatric disorders. Temporal discounting of future rewards and model-based control during reinforcement learning have proven as two promising candidates. Despite its trait-like stability, temporal discounting may be at least partly under contextual control. Highly arousing cues were shown to increase discounting, although evidence to date remains somewhat mixed. Whether model-based reinforcement learning is similarly affected by arousing cues remains unclear. Here, we tested cue-reactivity effects (erotic pictures) on subsequent temporal discounting and model-based reinforcement learning in a within-subjects design in n = 39 healthy heterosexual male participants. Self-reported and physiological arousal (cardiac activity and pupil dilation) were assessed before and during cue exposure. Arousal was increased during exposure of erotic versus neutral cues both on the subjective and autonomic level. Erotic cue exposure increased discounting as reflected by more impatient choices. Hierarchical drift diffusion modeling (DDM) linked increased discounting to a shift in the starting point bias of evidence accumulation toward immediate options. Model-based control during reinforcement learning was reduced following erotic cues according to model-agnostic analysis. Notably, DDM linked this effect to attenuated forgetting rates of unchosen options, leaving the model-based control parameter unchanged. Our findings replicate previous work on cue-reactivity effects in temporal discounting and for the first time show similar effects in model-based reinforcement learning in a heterosexual male sample. This highlights how environmental cues can impact core human decision processes and reveal that comprehensive modeling approaches can yield novel insights in reward-based decision processes.

Levodopa suppresses grid-like activity and impairs spatial learning in novel environments in healthy young adults

Accumulated evidence from animal studies suggests a role for the neuromodulator dopamine in memory processes, particularly under conditions of novelty or reward. Our understanding of how dopaminergic modulation impacts spatial representations and spatial memory in humans remains limited. Recent evidence suggests age-specific regulation effects of dopamine pharmacology on activity in the medial temporal lobe, a key region for spatial memory. To which degree this modulation affects spatially patterned medial temporal representations remains unclear. We reanalyzed recent data from a pharmacological dopamine challenge during functional brain imaging combined with a virtual object-location memory paradigm to assess the effect of Levodopa, a dopamine precursor, on grid-like activity in the entorhinal cortex. We found that Levodopa impaired grid cell-like representations in a sample of young adults (n = 55, age = 26-35 years) in a novel environment, accompanied by reduced spatial memory performance. We observed no such impairment when Levodopa was delivered to participants who had prior experience with the task. These results are consistent with a role of dopamine in modulating the encoding of novel spatial experiences. Our results suggest that dopamine signaling may play a larger role in shaping ongoing spatial representations than previously thought.

Dopamine regulates decision thresholds in human reinforcement learning in males

Dopamine fundamentally contributes to reinforcement learning, but recent accounts also suggest a contribution to specific action selection mechanisms and the regulation of response vigour. Here, we examine dopaminergic mechanisms underlying human reinforcement learning and action selection via a combined pharmacological neuroimaging approach in male human volunteers (n = 31, within-subjects; Placebo, 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist Haloperidol). We found little credible evidence for previously reported beneficial effects of L-dopa vs. Haloperidol on learning from gains and altered neural prediction error signals, which may be partly due to differences experimental design and/or drug dosages. Reinforcement learning drift diffusion models account for learning-related changes in accuracy and response times, and reveal consistent decision threshold reductions under both drugs, in line with the idea that lower dosages of D2 receptor antagonists increase striatal DA release via an autoreceptor-mediated feedback mechanism. These results are in line with the idea that dopamine regulates decision thresholds during reinforcement learning, and may help to bridge action selection and response vigor accounts of dopamine.

Dopamine differentially modulates medial temporal lobe activity and behavior during spatial navigation in young and older adults

Aging is associated with changes in spatial navigation behavior. In addition to an overall performance decline, older adults tend to rely more on proximal location cue information than on environmental boundary information during spatial navigation compared to young adults. The fact that older adults are more susceptible to errors during spatial navigation might be partly attributed to deficient dopaminergic modulation of hippocampal and striatal functioning. Hence, elevating dopamine levels might differentially modulate spatial navigation and memory performance in young and older adults. In this work, we administered levodopa (L-DOPA) in a double-blind within-subject, placebo-controlled design and recorded functional neuroimaging while young and older adults performed a 3D spatial navigation task in which boundary geometry or the position of a location cue were systematically manipulated. An age by intervention interaction on the neural level revealed an upregulation of brain responses in older adults and a downregulation of responses in young adults within the medial temporal lobe (including hippocampus and parahippocampus) and brainstem, during memory retrieval. Behaviorally, L-DOPA had no effect on older adults' overall memory performance; however, older adults whose spatial memory improved under L-DOPA also showed a shift towards more boundary processing under L-DOPA. In young adults, L-DOPA induced a decline in spatial memory performance in task-naïve participants. These results are consistent with the inverted-U-shaped hypothesis of dopamine signaling and cognitive function and suggest that increasing dopamine availability improves hippocampus-dependent place learning in some older adults.

Negative symptoms, striatal dopamine and model-free reward decision-making in schizophrenia

Negative symptoms, such as lack of motivation or social withdrawal, are highly prevalent and debilitating in patients with schizophrenia. Underlying mechanisms of negative symptoms are incompletely understood, thereby preventing the development of targeted treatments. We hypothesized that in patients with schizophrenia during psychotic remission, impaired influences of both model-based and model-free reward predictions on decision-making ('reward prediction influence', RPI) underlie negative symptoms. We focused on psychotic remission, because psychotic symptoms might confound reward-based decision-making. Moreover, we hypothesized that impaired model-based/model-free RPIs depend on alterations of both associative striatum dopamine synthesis and storage (DSS) and executive functioning. Both factors influence RPI in healthy subjects and are typically impaired in schizophrenia. Twenty-five patients with schizophrenia with pronounced negative symptoms during psychotic remission and 24 healthy controls were included in the study. Negative symptom severity was measured by the Positive and Negative Syndrome Scale negative subscale, model-based/model-free RPI by the two-stage decision task, associative striatum DSS by 18F-DOPA positron emission tomography and executive functioning by the symbol coding task. Model-free RPI was selectively reduced in patients and associated with negative symptom severity as well as with reduced associative striatum DSS (in patients only) and executive functions (both in patients and controls). In contrast, model-based RPI was not altered in patients. Results provide evidence for impaired model-free reward prediction influence as a mechanism for negative symptoms in schizophrenia as well as for reduced associative striatum dopamine and executive dysfunction as relevant factors. Data suggest potential treatment targets for patients with schizophrenia and pronounced negative symptoms.

Evidence for dopaminergic involvement in endogenous modulation of pain relief

Relief of ongoing pain is a potent motivator of behavior, directing actions to escape from or reduce potentially harmful stimuli. Whereas endogenous modulation of pain events is well characterized, relatively little is known about the modulation of pain relief and its corresponding neurochemical basis. Here, we studied pain modulation during a probabilistic relief-seeking task (a 'wheel of fortune' gambling task), in which people actively or passively received reduction of a tonic thermal pain stimulus. We found that relief perception was enhanced by active decisions and unpredictability, and greater in high novelty-seeking trait individuals, consistent with a model in which relief is tuned by its informational content. We then probed the roles of dopaminergic and opioidergic signaling, both of which are implicated in relief processing, by embedding the task in a double-blinded cross-over design with administration of the dopamine precursor levodopa and the opioid receptor antagonist naltrexone. We found that levodopa enhanced each of these information-specific aspects of relief modulation but no significant effects of the opioidergic manipulation. These results show that dopaminergic signaling has a key role in modulating the perception of pain relief to optimize motivation and behavior.

Effects of dopamine D2/3 and opioid receptor antagonism on the trade-off between model-based and model-free behaviour in healthy volunteers

Human behaviour requires flexible arbitration between actions we do out of habit and actions that are directed towards a specific goal. Drugs that target opioid and dopamine receptors are notorious for inducing maladaptive habitual drug consumption; yet, how the opioidergic and dopaminergic neurotransmitter systems contribute to the arbitration between habitual and goal-directed behaviour is poorly understood. By combining pharmacological challenges with a well-established decision-making task and a novel computational model, we show that the administration of the dopamine D2/3 receptor antagonist amisulpride led to an increase in goal-directed or 'model-based' relative to habitual or 'model-free' behaviour, whereas the non-selective opioid receptor antagonist naltrexone had no appreciable effect. The effect of amisulpride on model-based/model-free behaviour did not scale with drug serum levels in the blood. Furthermore, participants with higher amisulpride serum levels showed higher explorative behaviour. These findings highlight the distinct functional contributions of dopamine and opioid receptors to goal-directed and habitual behaviour and support the notion that even small doses of amisulpride promote flexible application of cognitive control.

The catecholamine precursor Tyrosine reduces autonomic arousal and decreases decision thresholds in reinforcement learning and temporal discounting

Supplementation with the catecholamine precursor L-Tyrosine might enhance cognitive performance, but overall findings are mixed. Here, we investigate the effect of a single dose of tyrosine (2g) vs. placebo on two catecholamine-dependent trans-diagnostic traits: model-based control during reinforcement learning (2-step task) and temporal discounting, using a double-blind, placebo-controlled, within-subject design (n = 28 healthy male participants). We leveraged drift diffusion models in a hierarchical Bayesian framework to jointly model participants' choices and response times (RTS) in both tasks. Furthermore, comprehensive autonomic monitoring (heart rate, heart rate variability, pupillometry, spontaneous eye blink rate) was performed both pre- and post-supplementation, to explore potential physiological effects of supplementation. Across tasks, tyrosine consistently reduced participants' RTs without deteriorating task-performance. Diffusion modeling linked this effect to attenuated decision-thresholds in both tasks and further revealed increased model-based control (2-step task) and (if anything) attenuated temporal discounting. On the physiological level, participants' pupil dilation was predictive of the individual degree of temporal discounting. Tyrosine supplementation reduced physiological arousal as revealed by increases in pupil dilation variability and reductions in heart rate. Supplementation-related changes in physiological arousal predicted individual changes in temporal discounting. Our findings provide first evidence that tyrosine supplementation might impact psychophysiological parameters, and suggest that modeling approaches based on sequential sampling models can yield novel insights into latent cognitive processes modulated by amino-acid supplementation.

L-DOPA enhances neural direction signals in younger and older adults

Previous studies indicate a role of dopamine in spatial navigation. Although neural representations of direction are an important aspect of spatial cognition, it is not well understood whether dopamine directly affects these representations, or only impacts other aspects of spatial brain function. Moreover, both dopamine and spatial cognition decline sharply during age, raising the question which effect dopamine has on directional signals in the brain of older adults. To investigate these questions, we used a double-blind cross-over L-DOPA/Placebo intervention design in which 43 younger and 37 older adults navigated in a virtual spatial environment while undergoing functional magnetic resonance imaging (fMRI). We studied the effect of L-DOPA, a dopamine precursor, on fMRI activation patterns that encode spatial walking directions that have previously been shown to lose specificity with age. This was done in predefined regions of interest, including the early visual cortex, retrosplenial cortex, and hippocampus. Classification of brain activation patterns associated with different walking directions was improved across all regions following L-DOPA administration, suggesting that dopamine broadly enhances neural representations of direction. No evidence for differences between regions was found. In the hippocampus these results were found in both age groups, while in the retrosplenial cortex they were only observed in younger adults. Taken together, our study provides evidence for a link between dopamine and the specificity of neural responses during spatial navigation. SIGNIFICANCE STATEMENT: The sense of direction is an important aspect of spatial navigation, and neural representations of direction can be found throughout a large network of space-related brain regions. But what influences how well these representations track someone's true direction? Using a double-blind cross-over L-DOPA/Placebo intervention design, we find causal evidence that the neurotransmitter dopamine impacts the fidelity of direction selective neural representations in the human hippocampus and retrosplenial cortex. Interestingly, the effect of L-DOPA was either equally present or even smaller in older adults, despite the well-known age related decline of dopamine. These results provide novel insights into how dopamine shapes the neural representations that underlie spatial navigation.

Gambling Environment Exposure Increases Temporal Discounting but Improves Model-Based Control in Regular Slot-Machine Gamblers

Gambling disorder is a behavioral addiction that negatively impacts personal finances, work, relationships and mental health. In this pre-registered study (https://osf.io/5ptz9/) we investigated the impact of real-life gambling environments on two computational markers of addiction, temporal discounting and model-based reinforcement learning. Gambling disorder is associated with increased temporal discounting and reduced model-based learning. Regular gamblers (n = 30, DSM-5 score range 3-9) performed both tasks in a neutral (café) and a gambling-related environment (slot-machine venue) in counterbalanced order. Data were modeled using drift diffusion models for temporal discounting and reinforcement learning via hierarchical Bayesian estimation. Replicating previous findings, gamblers discounted rewards more steeply in the gambling-related context. This effect was positively correlated with gambling related cognitive distortions (pre-registered analysis). In contrast to our pre-registered hypothesis, model-based reinforcement learning was improved in the gambling context. Here we show that temporal discounting and model-based reinforcement learning are modulated in opposite ways by real-life gambling cue exposure. Results challenge aspects of habit theories of addiction, and reveal that laboratory-based computational markers of psychopathology are under substantial contextual control.

Different brain systems support learning from received and avoided pain during human pain-avoidance learning

Both unexpected pain and unexpected pain absence can drive avoidance learning, but whether they do so via shared or separate neural and neurochemical systems is largely unknown. To address this issue, we combined an instrumental pain-avoidance learning task with computational modeling, functional magnetic resonance imaging (fMRI), and pharmacological manipulations of the dopaminergic (100 mg levodopa) and opioidergic (50 mg naltrexone) systems (N = 83). Computational modeling provided evidence that untreated participants learned more from received than avoided pain. Our dopamine and opioid manipulations negated this learning asymmetry by selectively increasing learning rates for avoided pain. Furthermore, our fMRI analyses revealed that pain prediction errors were encoded in subcortical and limbic brain regions, whereas no-pain prediction errors were encoded in frontal and parietal cortical regions. However, we found no effects of our pharmacological manipulations on the neural encoding of prediction errors. Together, our results suggest that human pain-avoidance learning is supported by separate threat- and safety-learning systems, and that dopamine and endogenous opioids specifically regulate learning from successfully avoided pain.

A Neuroeconomics Approach to Obesity

Obesity is a heterogeneous condition that is affected by physiological, behavioral, and environmental factors. Value-based decision making is a useful framework for integrating these factors at the individual level. The disciplines of behavioral economics and reinforcement learning provide tools for identifying specific cognitive and motivational processes that may contribute to the development and maintenance of obesity. Neuroeconomics complements these disciplines by studying the neural mechanisms underlying these processes. We surveyed recent literature on individual decision characteristics that are most frequently implicated in obesity: discounting the value of future outcomes, attitudes toward uncertainty, and learning from rewards and punishments. Our survey highlighted both consistent and inconsistent behavioral findings. These findings underscore the need to examine multiple processes within individuals to identify unique behavioral profiles associated with obesity. Such individual characterization will inform future studies on the neurobiology of obesity as well as the design of effective interventions that are individually tailored.

Stronger Prejudices Are Associated With Decreased Model-Based Control

Background: Prejudices against minorities can be understood as habitually negative evaluations that are kept in spite of evidence to the contrary. Therefore, individuals with strong prejudices might be dominated by habitual or "automatic" reactions at the expense of more controlled reactions. Computational theories suggest individual differences in the balance between habitual/model-free and deliberative/model-based decision-making. Methods: 127 subjects performed the two Step task and completed the blatant and subtle prejudice scale. Results: By using analyses of choices and reaction times in combination with computational modeling, subjects with stronger blatant prejudices showed a shift away from model-based control. There was no association between these decision-making processes and subtle prejudices. Conclusion: These results support the idea that blatant prejudices toward minorities are related to a relative dominance of habitual decision-making. This finding has important implications for developing interventions that target to change prejudices across societies.

Computational analysis of probabilistic reversal learning deficits in male subjects with alcohol use disorder

BACKGROUND

Alcohol use disorder is characterized by perseverative alcohol use despite negative consequences. This hallmark feature of addiction potentially relates to impairments in behavioral flexibility, which can be measured by probabilistic reversal learning (PRL) paradigms. We here aimed to examine the cognitive mechanisms underlying impaired PRL task performance in patients with alcohol use disorder (AUDP) using computational models of reinforcement learning.

METHODS

Twenty-eight early abstinent AUDP and 27 healthy controls (HC) performed an extensive PRL paradigm. We compared conventional behavioral variables of choices (perseveration; correct responses) between groups. Moreover, we fitted Bayesian computational models to the task data to compare differences in latent cognitive variables including reward and punishment learning and choice consistency between groups.

RESULTS

AUDP and HC did not significantly differ with regard to direct perseveration rates after reversals. However, AUDP made overall less correct responses and specifically showed decreased win-stay behavior compared to HC. Interestingly, AUDP showed premature switching after no or little negative feedback but elevated proneness to stay when accumulation of negative feedback would make switching a more optimal option. Computational modeling revealed that AUDP compared to HC showed enhanced learning from punishment, a tendency to learn less from positive feedback and lower choice consistency.

CONCLUSION

Our data do not support the assumption that AUDP are characterized by increased perseveration behavior. Instead our findings provide evidence that enhanced negative reinforcement and decreased non-drug-related reward learning as well as diminished choice consistency underlie dysfunctional choice behavior in AUDP.

L-DOPA administration shifts the stability-flexibility balance towards attentional capture by distractors during a visual search task

RATIONALE

The cognitive control dilemma describes the necessity to balance two antagonistic modes of attention: stability and flexibility. Stability refers to goal-directed thought, feeling, or action and flexibility refers to the complementary ability to adapt to an ever-changing environment. Their balance is thought to be maintained by neurotransmitters such as dopamine, most likely in a U-shaped rather than linear manner. However, in humans, studies on the stability-flexibility balance using a dopaminergic agent and/or measurement of brain dopamine are scarce.

OBJECTIVE

The study aimed to investigate the causal involvement of dopamine in the stability-flexibility balance and the nature of this relationship in humans.

METHODS

Distractibility was assessed as the difference in reaction time (RT) between distractor and non-distractor trials in a visual search task. In a randomized, placebo-controlled, double-blind, crossover study, 65 healthy participants performed the task under placebo and a dopamine precursor (L-DOPA). Using ¹⁸F-DOPA-PET, dopamine availability in the striatum was examined at baseline to investigate its relationship to the RT distractor effect and to the L-DOPA-induced change of the RT distractor effect.

RESULTS

There was a pronounced RT distractor effect in the placebo session that increased under L-DOPA. Neither the RT distractor effect in the placebo session nor the magnitude of its L-DOPA-induced increase were related to baseline striatal dopamine.

CONCLUSIONS

L-DOPA administration shifted the stability-flexibility balance towards attentional capture by distractors, suggesting causal involvement of dopamine. This finding is consistent with current theories of prefrontal cortex dopamine function. Current data can neither confirm nor falsify the inverted U-shaped function hypothesis with regard to cognitive control.

Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference

Dopamine is implicated in representing model-free (MF) reward prediction errors a as well as influencing model-based (MB) credit assignment and choice. Putative cooperative interactions between MB and MF systems include a guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test an hypothesis that enhancing dopamine levels boosts the guidance of MF credit assignment by MB inference. In line with this, we found that levodopa enhanced guidance of MF credit assignment by MB inference, without impacting MF and MB influences directly. This drug effect correlated negatively with a dopamine-dependent change in purely MB credit assignment, possibly reflecting a trade-off between these two MB components of behavioural control. Our findings of a dopamine boost in MB inference guidance of MF learning highlight a novel DA influence on MB-MF cooperative interactions.

Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making

Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) entanglement of brain signals of different learning modules, and (iii) a limited number of computational models considered as candidates for explaining behavior. Here, we address these three limitations and (i) introduce a complex sequential decision making task with surprising events that allows us to (ii) dissociate correlates of reward prediction errors from those of surprise in functional magnetic resonance imaging (fMRI); and (iii) we test behavior against a large repertoire of model-free, model-based, and hybrid reinforcement learning algorithms, including a novel surprise-modulated actor-critic algorithm. Surprise, derived from an approximate Bayesian approach for learning the world-model, is extracted in our algorithm from a state prediction error. Surprise is then used to modulate the learning rate of a model-free actor, which itself learns via the reward prediction error from model-free value estimation by the critic. We find that action choices are well explained by pure model-free policy gradient, but reaction times and neural data are not. We identify signatures of both model-free and surprise-based learning signals in blood oxygen level dependent (BOLD) responses, supporting the existence of multiple parallel learning modules in the brain. Our results extend previous fMRI findings to a multi-step setting and emphasize the role of policy gradient and surprise signalling in human learning.

Dopaminergic and noradrenergic modulation of stress-induced alterations in brain activation associated with goal-directed behaviour

BACKGROUND

Acute stress is thought to reduce goal-directed behaviour, an effect purportedly associated with stress-induced release of catecholamines. In contrast, experimentally increased systemic catecholamine levels have been shown to increase goal-directed behaviour. Whether experimentally increased catecholamine function can modulate stress-induced reductions in goal-directed behaviour and its neural substrates, is currently unknown.

AIM

To assess whether and how experimentally induced increases in dopamine and noradrenaline contribute to the acute stress effects on goal-directed behaviour and associated brain activation.

METHODS

One hundred participants underwent a stress induction protocol (Maastricht acute stress test; MAST) or a control procedure and received methylphenidate (MPH) (40 mg, oral) or placebo according to a 2 × 2 between-subjects design. In a well-established instrumental learning paradigm, participants learnt stimulus-response-outcome associations, after which rewards were selectively devalued. Participants' brain activation and associated goal-directed behaviour were assessed in a magnetic resonance imaging scanner at peak cortisol/MPH concentrations.

RESULTS

The MAST and MPH increased physiological measures of stress (salivary cortisol and blood pressure), but only MAST increased subjective measures of stress. MPH modulated stress effects on activation of brain areas associated with goal-directed behaviour, including insula, putamen, amygdala, medial prefrontal cortex, frontal pole and orbitofrontal cortex. However, MPH did not modulate the tendency of stress to induce a reduction in goal-directed behaviour.

CONCLUSION

Our neuroimaging data suggest that MPH-induced increases in dopamine and noradrenaline reverse stress-induced changes in key brain regions associated with goal-directed behaviour, while behavioural effects were absent. These effects may be relevant for preventing stress-induced maladaptive behaviour like in addiction or binge eating disorder.

Differential prioritization of intramaze cue and boundary information during spatial navigation across the human lifespan

Spatial learning can be based on intramaze cues and environmental boundaries. These processes are predominantly subserved by striatal- and hippocampal-dependent circuitries, respectively. Maturation and aging processes in these brain regions may affect lifespan differences in their contributions to spatial learning. We independently manipulated an intramaze cue or the environment's boundary in a navigation task in 27 younger children (6-8 years), 30 older children (10-13 years), 29 adolescents (15-17 years), 29 younger adults (20-35 years) and 26 older adults (65-80 years) to investigate lifespan age differences in the relative prioritization of either information. Whereas learning based on an intramaze cue showed earlier maturation during the progression from younger to later childhood and remained relatively stable across adulthood, maturation of boundary-based learning was more protracted towards peri-adolescence and showed strong aging-related decline. Furthermore, individual differences in prioritizing intramaze cue- over computationally more demanding boundary-based learning was positively associated with cognitive processing fluctuations and this association was partially mediated by spatial working memory capacity during adult, but not during child development. This evidence reveals different age gradients of two modes of spatial learning across the lifespan, which seem further influenced by individual differences in cognitive processing fluctuations and working memory, particularly during aging.

The Straw That Broke the Camel's Back: Natural Variations in 17β-Estradiol and COMT-Val158Met Genotype Interact in the Modulation of Model-Free and Model-Based Control

The sex hormone estradiol has recently gained attention in human decision-making research. Animal studies have already shown that estradiol promotes dopaminergic transmission and thus supports reward-seeking behavior and aspects of addiction. In humans, natural variations of estradiol across the menstrual cycle modulate the ability to learn from direct performance feedback ("model-free" learning). However, it remains unclear whether estradiol also influences more complex "model-based" contributions to reinforcement learning. Here, 41 women were tested twice - in the low and high estradiol state of the follicular phase of their menstrual cycle - with a Two-Step decision task designed to separate model-free from model-based learning. The results showed that in the high estradiol state women relied more heavily on model-free learning, and accomplished reduced performance gains, particularly during the more volatile periods of the task that demanded increased learning effort. In contrast, model-based control remained unaltered by the influence of hormonal state across the group. Yet, when accounting for individual differences in the genetic proxy of the COMT-Val158Met polymorphism (rs4680), we observed that only the participants homozygote for the methionine allele (n = 12; with putatively higher prefrontal dopamine) experienced a decline in model-based control when facing volatile reward probabilities. This group also showed the increase in suboptimal model-free control, while the carriers of the valine allele remained unaffected by the rise in endogenous estradiol. Taken together, these preliminary findings suggest that endogenous estradiol may affect the balance between model-based and model-free control, and particularly so in women with a high prefrontal baseline dopamine capacity and in situations of increased environmental volatility.

A mosaic of cost-benefit control over cortico-striatal circuitry

Dopamine contributes to cognitive control through well-established effects in both the striatum and cortex. Although earlier work suggests that dopamine affects cognitive control capacity, more recent work suggests that striatal dopamine may also impact on cognitive motivation. We consider the emerging perspective that striatal dopamine boosts control by making people more sensitive to the benefits versus the costs of cognitive effort, and we discuss how this sensitivity shapes competition between controlled and prepotent actions. We propose that dopamine signaling in distinct cortico-striatal subregions mediates different types of cost-benefit tradeoffs, and also discuss mechanisms for the local control of dopamine release, enabling selectivity among cortico-striatal circuits. In so doing, we show how this cost-benefit mosaic can reconcile seemingly conflicting findings about the impact of dopamine signaling on cognitive control.

Fronto-striatal structures related with model-based control as an endophenotype for obsessive-compulsive disorder

Recent theories suggest a shift from model-based goal-directed to model-free habitual decision-making in obsessive–compulsive disorder (OCD). However, it is yet unclear, whether this shift in the decision process is heritable. We investigated 32 patients with OCD, 27 unaffected siblings (SIBs) and 31 healthy controls (HCs) using the two-step task. We computed behavioral and reaction time analyses and fitted a computational model to assess the balance between model-based and model-free control. 80 subjects also underwent structural imaging. We observed a significant ordered effect for the shift towards model-free control in the direction OCD > SIB > HC in our computational parameter of interest. However less directed analyses revealed no shift towards model-free control in OCDs. Nonetheless, we found evidence for reduced model-based control in OCDs compared to HCs and SIBs via 2nd stage reaction time analyses. In this measure SIBs also showed higher levels of model-based control than HCs. Across all subjects these effects were associated with the surface area of the left medial/right dorsolateral prefrontal cortex. Moreover, correlations between bilateral putamen/right caudate volumes and these effects varied as a function of group: they were negative in SIBs and OCDs, but positive in HCs. Associations between fronto-striatal regions and model-based reaction time effects point to a potential endophenotype for OCD.

Reliance on model-based and model-free control in obesity

Consuming more energy than is expended may reflect a failure of control over eating behaviour in obesity. Behavioural control arises from a balance between two dissociable strategies of reinforcement learning: model-free and model-based. We hypothesized that weight status relates to an imbalance in reliance on model-based and model-free control, and that it may do so in a linear or quadratic manner. To test this, 90 healthy participants in a wide BMI range [normal-weight (n = 31), overweight (n = 29), obese (n = 30)] performed a sequential decision-making task. The primary analysis indicated that obese participants relied less on model-based control than overweight and normal-weight participants, with no difference between overweight and normal-weight participants. In line, secondary continuous analyses revealed a negative linear, but not quadratic, relationship between BMI and model-based control. Computational modelling of choice behaviour suggested that a mixture of both strategies was shifted towards less model-based control in obese participants. Our findings suggest that obesity may indeed be related to an imbalance in behavioural control as expressed in a phenotype of less model-based control potentially resulting from enhanced reliance on model-free computations.

Dopaminergic Modulation of Human Intertemporal Choice: A Diffusion Model Analysis Using the D2-Receptor Antagonist Haloperidol

The neurotransmitter dopamine is implicated in diverse functions, including reward processing, reinforcement learning, and cognitive control. The tendency to discount future rewards over time has long been discussed in the context of potential dopaminergic modulation. Here we examined the effect of a single dose of the D2 receptor antagonist haloperidol (2 mg) on temporal discounting in healthy female and male human participants. Our approach extends previous pharmacological studies in two ways. First, we applied combined temporal discounting drift diffusion models to examine choice dynamics. Second, we examined dopaminergic modulation of reward magnitude effects on temporal discounting. Hierarchical Bayesian parameter estimation revealed that the data were best accounted for by a temporal discounting drift diffusion model with nonlinear trialwise drift rate scaling. This model showed good parameter recovery, and posterior predictive checks revealed that it accurately reproduced the relationship between decision conflict and response times in individual participants. We observed reduced temporal discounting and substantially faster nondecision times under haloperidol compared with placebo. Discounting was steeper for low versus high reward magnitudes, but this effect was largely unaffected by haloperidol. Results were corroborated by model-free analyses and modeling via more standard approaches. We previously reported elevated caudate activation under haloperidol in this sample of participants, supporting the idea that haloperidol elevated dopamine neurotransmission (e.g., by blocking inhibitory feedback via presynaptic D2 auto-receptors). The present results reveal that this is associated with an augmentation of both lower-level (nondecision time) and higher-level (temporal discounting) components of the decision process.SIGNIFICANCE STATEMENT Dopamine is implicated in reward processing, reinforcement learning, and cognitive control. Here we examined the effects of a single dose of the D2 receptor antagonist haloperidol on temporal discounting and choice dynamics during the decision process. We extend previous studies by applying computational modeling using the drift diffusion model, which revealed that haloperidol reduced the nondecision time and reduced impulsive choice compared with placebo. These findings are compatible with a haloperidol-induced increase in striatal dopamine (e.g., because of a presynaptic mechanism). Our data provide novel insights into the contributions of dopamine to value-based decision-making and highlight how comprehensive model-based analyses using sequential sampling models can inform the effects of pharmacological modulation on choice processes.

Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making

Involvement of dopamine in regulating exploration during decision-making has long been hypothesized, but direct causal evidence in humans is still lacking. Here, we use a combination of computational modeling, pharmacological intervention and functional magnetic resonance imaging to address this issue. Thirty-one healthy male participants performed a restless four-armed bandit task in a within-subjects design under three drug conditions: 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist haloperidol, and placebo. Choices were best explained by an extension of an established Bayesian learning model accounting for perseveration, directed exploration and random exploration. Modeling revealed attenuated directed exploration under L-dopa, while neural signatures of exploration, exploitation and prediction error were unaffected. Instead, L-dopa attenuated neural representations of overall uncertainty in insula and dorsal anterior cingulate cortex. Our results highlight the computational role of these regions in exploration and suggest that dopamine modulates how this circuit tracks accumulating uncertainty during decision-making.

Stimulation of the vagus nerve reduces learning in a go/no-go reinforcement learning task

When facing decisions to approach rewards or to avoid punishments, we often figuratively go with our gut, and the impact of metabolic states such as hunger on motivation are well documented. However, whether and how vagal feedback signals from the gut influence instrumental actions is unknown. Here, we investigated the effect of non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) vs. sham (randomized cross-over design) on approach and avoidance behavior using an established go/no-go reinforcement learning paradigm in 39 healthy human participants (23 female) after an overnight fast. First, mixed-effects logistic regression analysis of choice accuracy showed that taVNS acutely impaired decision-making, p = .041. Computational reinforcement learning models identified the cause of this as a reduction in the learning rate through taVNS (∆α = -0.092, p_boot = .002), particularly after punishment (∆α_Pun = -0.081, p_boot = .012 vs. ∆α_Rew =-0.031, p_boot = .22). However, taVNS had no effect on go biases, Pavlovian response biases or response time. Hence, taVNS appeared to influence learning rather than action execution. These results highlight a novel role of vagal afferent input in modulating reinforcement learning by tuning the learning rate according to homeostatic needs.

Goal-oriented and habitual decisions: Neural signatures of model-based and model-free learning

Human decision-making is mainly driven by two fundamental learning processes: a slow, deliberative, goal-directed model-based process that maps out the potential outcomes of all options and a rapid habitual model-free process that enables reflexive repetition of previously successful choices. Although many model-informed neuroimaging studies have examined the neural correlates of model-based and model-free learning, the concordant activity among these two processes remains unclear. We used quantitative meta-analyses of functional magnetic resonance imaging experiments to identify the concordant activity pertaining to model-based and model-free learning over a range of reward-related paradigms. We found that: 1) both processes yielded concordant ventral striatum activity, 2) model-based learning activated the medial prefrontal cortex and orbital frontal cortex, and 3) model-free learning specifically activated the left globus pallidus and right caudate head. Our findings suggest that model-free and model-based decision making engage overlapping yet distinct neural regions. These stereotaxic maps improve our understanding of how deliberative goal-directed and reflexive habitual learning are implemented in the brain.

The neurochemical substrates of habitual and goal-directed control

Our daily decisions are governed by the arbitration between goal-directed and habitual strategies. However, the neurochemical basis of this arbitration is unclear. We assessed the contribution of dopaminergic, serotonergic, and opioidergic systems to this balance across reward and loss domains. Thirty-nine participants (17 healthy controls, 15 patients with pathological gambling, and 7 with binge eating disorder) underwent positron emission tomography (PET) imaging with [¹⁸F]FDOPA, [¹¹C]MADAM and [¹¹C]carfentanil to assess presynaptic dopamine, and serotonin transporter and mu-opioid receptor binding potential. Separately, participants completed a modified two-step task, which quantifies the degree to which decision-making is influenced by goal-directed or habitual strategies. All participants completed a version with reward outcomes; healthy controls additionally completed a version with loss outcomes. In the context of rewarding outcomes, we found that greater serotonin transporter binding potential in prefrontal regions was associated with habitual control, while greater serotonin transporter binding potential in the putamen was marginally associated with goal-directed control; however, the findings were no longer significant when controlling for the opposing valence (loss). In blocks with loss outcomes, we found that the opioidergic system, specifically greater [¹¹C]carfentanil binding potential, was positively associated with goal-directed control and negatively associated with habit-directed control. Our findings illuminate the complex neurochemical basis of goal-directed and habitual behavior, implicating differential roles for prefrontal and subcortical serotonin in decision-making across healthy and pathological populations.

Dopamine and Gambling Disorder: Prospects for Personalized Treatment

Purpose of Review

To address variation in the severity of gambling disorder, this review evaluates the contribution of mesocorticolimbic dopamine neurons to potential behavioral endophenotypes, the influence of individual differences in the dopamine system on gambling and related behaviors, and the possible role for dopaminergic medications in the treatment of gambling disorder.

Recent Findings

Newer work has suggested that dopaminergic dysfunction can lead to increased reward anticipation and a greater sensitivity to uncertainty, which in turn may drive addictive gambling behaviors. In addition, increased impulsivity, a well-recognized risk factor for gambling disorder, has been linked to dopaminergic dysfunction. More recently, emerging evidence has suggested that dopaminergic medications can influence the discounting of delayed rewards.

Summary

Dopaminergic drugs that increase the salience of long-term over short-term goals may ameliorate symptoms of impulsive individuals with gambling disorder. More broadly, improved understanding of intermediate behavioral and other phenotypes with a defined neurobiological substrate may allow for personalized treatment of gambling disorder and other psychiatric conditions.

Reward and avoidance learning in the context of aversive environments and possible implications for depressive symptoms

BACKGROUND

Aversive stimuli in the environment influence human actions. This includes valence-dependent influences on action selection, e.g., increased avoidance but decreased approach behavior. However, it is yet unclear how aversive stimuli interact with complex learning and decision-making in the reward and avoidance domain. Moreover, the underlying computational mechanisms of these decision-making biases are unknown.

METHODS

To elucidate these mechanisms, 54 healthy young male subjects performed a two-step sequential decision-making task, which allows to computationally model different aspects of learning, e.g., model-free, habitual, and model-based, goal-directed learning. We used a within-subject design, crossing task valence (reward vs. punishment learning) with emotional context (aversive vs. neutral background stimuli). We analyzed choice data, applied a computational model, and performed simulations.

RESULTS

Whereas model-based learning was not affected, aversive stimuli interacted with model-free learning in a way that depended on task valence. Thus, aversive stimuli increased model-free avoidance learning but decreased model-free reward learning. The computational model confirmed this effect: the parameter lambda that indicates the influence of reward prediction errors on decision values was increased in the punishment condition but decreased in the reward condition when aversive stimuli were present. Further, by using the inferred computational parameters to simulate choice data, our effects were captured. Exploratory analyses revealed that the observed biases were associated with subclinical depressive symptoms.

CONCLUSION

Our data show that aversive environmental stimuli affect complex learning and decision-making, which depends on task valence. Further, we provide a model of the underlying computations of this affective modulation. Finally, our finding of increased decision-making biases in subjects reporting subclinical depressive symptoms matches recent reports of amplified Pavlovian influences on action selection in depression and suggests a potential vulnerability factor for mood disorders. We discuss our findings in the light of the involvement of the neuromodulators serotonin and dopamine.