Intraindividual time-varying dynamic network of affects: linear autoregressive mixed-effects models for ecological momentary assessment.

An interesting recent development in emotion research and clinical psychology is the discovery that affective states can be modeled as a network of temporally interacting moods or emotions. Additionally, external factors like stressors or treatments can influence the mood network by amplifying or dampening the activation of specific moods. Researchers have turned to multilevel autoregressive models to fit these affective networks using intensive longitudinal data gathered through ecological momentary assessment. Nonetheless, a more comprehensive examination of the performance of such models is warranted. In our study, we focus on simple directed intraindividual networks consisting of two interconnected mood nodes that mutually enhance or dampen each other. We also introduce a node representing external factors that affect both mood nodes unidirectionally. Importantly, we disregard the potential effects of a current mood/emotion on the perception of external factors. We then formalize the mathematical representation of such networks by exogenous linear autoregressive mixed-effects models. In this representation, the autoregressive coefficients signify the interactions between moods, while external factors are incorporated as exogenous covariates. We let the autoregressive and exogenous coefficients in the model have fixed and random components. Depending on the analysis, this leads to networks with variable structures over reasonable time units, such as days or weeks, which are captured by the variability of random effects. Furthermore, the fixed-effects parameters encapsulate a subject-specific network structure. Leveraging the well-established theoretical and computational foundation of linear mixed-effects models, we transform the autoregressive formulation to a classical one and utilize the existing methods and tools. To validate our approach, we perform simulations assuming our model as the true data-generating process. By manipulating a predefined set of parameters, we investigate the reliability and feasibility of our approach across varying numbers of observations, levels of noise intensity, compliance rates, and scalability to higher dimensions. Our findings underscore the challenges associated with estimating individualized parameters in the context of common longitudinal designs, where the required number of observations may often be unattainable. Moreover, our study highlights the sensitivity of autoregressive mixed-effect models to noise levels and the difficulty of scaling due to the substantial number of parameters.

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.

Psychological Resilience Factors and Their Association With Weekly Stressor Reactivity During the COVID-19 Outbreak in Europe: Prospective Longitudinal Study.

BACKGROUND: Cross-sectional relationships between psychosocial resilience factors (RFs) and resilience, operationalized as the outcome of low mental health reactivity to stressor exposure (low "stressor reactivity" [SR]), were reported during the first wave of the COVID-19 pandemic in 2020. OBJECTIVE: Extending these findings, we here examined prospective relationships and weekly dynamics between the same RFs and SR in a longitudinal sample during the aftermath of the first wave in several European countries. METHODS: Over 5 weeks of app-based assessments, participants reported weekly stressor exposure, mental health problems, RFs, and demographic data in 1 of 6 different languages. As (partly) preregistered, hypotheses were tested cross-sectionally at baseline (N=558), and longitudinally (n=200), using mixed effects models and mediation analyses. RESULTS: RFs at baseline, including positive appraisal style (PAS), optimism (OPT), general self-efficacy (GSE), perceived good stress recovery (REC), and perceived social support (PSS), were negatively associated with SR scores, not only cross-sectionally (baseline SR scores; all P<.001) but also prospectively (average SR scores across subsequent weeks; positive appraisal (PA), P=.008; OPT, P<.001; GSE, P=.01; REC, P<.001; and PSS, P=.002). In both associations, PAS mediated the effects of PSS on SR (cross-sectionally: 95% CI -0.064 to -0.013; prospectively: 95% CI -0.074 to -0.0008). In the analyses of weekly RF-SR dynamics, the RFs PA of stressors generally and specifically related to the COVID-19 pandemic, and GSE were negatively associated with SR in a contemporaneous fashion (PA, P<.001; PAC,P=.03; and GSE, P<.001), but not in a lagged fashion (PA, P=.36; PAC, P=.52; and GSE, P=.06). CONCLUSIONS: We identified psychological RFs that prospectively predict resilience and cofluctuate with weekly SR within individuals. These prospective results endorse that the previously reported RF-SR associations do not exclusively reflect mood congruency or other temporal bias effects. We further confirm the important role of PA in resilience.

Dynamic Modelling of Mental Resilience in Young Adults: Protocol for a Longitudinal Observational Study (DynaM-OBS).

BACKGROUND: Stress-related mental disorders are highly prevalent and pose a substantial burden on individuals and society. Improving strategies for the prevention and treatment of mental disorders requires a better understanding of their risk and resilience factors. This multicenter study aims to contribute to this endeavor by investigating psychological resilience in healthy but susceptible young adults over 9 months. Resilience is conceptualized in this study as the maintenance of mental health or quick recovery from mental health perturbations upon exposure to stressors, assessed longitudinally via frequent monitoring of stressors and mental health. OBJECTIVE: This study aims to investigate the factors predicting mental resilience and adaptive processes and mechanisms contributing to mental resilience and to provide a methodological and evidence-based framework for later intervention studies. METHODS: In a multicenter setting, across 5 research sites, a sample with a total target size of 250 young male and female adults was assessed longitudinally over 9 months. Participants were included if they reported at least 3 past stressful life events and an elevated level of (internalizing) mental health problems but were not presently affected by any mental disorder other than mild depression. At baseline, sociodemographic, psychological, neuropsychological, structural, and functional brain imaging; salivary cortisol and α-amylase levels; and cardiovascular data were acquired. In a 6-month longitudinal phase 1, stressor exposure, mental health problems, and perceived positive appraisal were monitored biweekly in a web-based environment, while ecological momentary assessments and ecological physiological assessments took place once per month for 1 week, using mobile phones and wristbands. In a subsequent 3-month longitudinal phase 2, web-based monitoring was reduced to once a month, and psychological resilience and risk factors were assessed again at the end of the 9-month period. In addition, samples for genetic, epigenetic, and microbiome analyses were collected at baseline and at months 3 and 6. As an approximation of resilience, an individual stressor reactivity score will be calculated. Using regularized regression methods, network modeling, ordinary differential equations, landmarking methods, and neural net-based methods for imputation and dimension reduction, we will identify the predictors and mechanisms of stressor reactivity and thus be able to identify resilience factors and mechanisms that facilitate adaptation to stressors. RESULTS: Participant inclusion began in October 2020, and data acquisition was completed in June 2022. A total of 249 participants were assessed at baseline, 209 finished longitudinal phase 1, and 153 finished longitudinal phase 2. CONCLUSIONS: The Dynamic Modelling of Resilience-Observational Study provides a methodological framework and data set to identify predictors and mechanisms of mental resilience, which are intended to serve as an empirical foundation for future intervention studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39817.

No Differences in Value-Based Decision-Making Due to Use of Oral Contraceptives.

Fluctuating ovarian hormones have been shown to affect decision-making processes in women. While emerging evidence suggests effects of endogenous ovarian hormones such as estradiol and progesterone on value-based decision-making in women, the impact of exogenous synthetic hormones, as in most oral contraceptives, is not clear. In a between-subjects design, we assessed measures of value-based decision-making in three groups of women aged 18 to 29 years, during (1) active oral contraceptive intake (N = 22), (2) the early follicular phase of the natural menstrual cycle (N = 20), and (3) the periovulatory phase of the natural menstrual cycle (N = 20). Estradiol, progesterone, testosterone, and sex-hormone binding globulin levels were assessed in all groups via blood samples. We used a test battery which measured different facets of value-based decision-making: delay discounting, risk-aversion, risk-seeking, and loss aversion. While hormonal levels did show the expected patterns for the three groups, there were no differences in value-based decision-making parameters. Consequently, Bayes factors showed conclusive evidence in support of the null hypothesis. We conclude that women on oral contraceptives show no differences in value-based decision-making compared to the early follicular and periovulatory natural menstrual cycle phases.

Individualizing deep dynamic models for psychological resilience data.

Deep learning approaches can uncover complex patterns in data. In particular, variational autoencoders achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project, which features intermittent longitudinal measurements of stressors and mental health, we propose an approach for individualized, dynamic modeling in this latent space. Specifically, we utilize ordinary differential equations (ODEs) and develop a novel technique for obtaining person-specific ODE parameters even in settings with a rather small number of individuals and observations, incomplete data, and a differing number of observations per individual. This technique allows us to subsequently investigate individual reactions to stimuli, such as the mental health impact of stressors. A potentially large number of baseline characteristics can then be linked to this individual response by regularized regression, e.g., for identifying resilience factors. Thus, our new method provides a way of connecting different kinds of complex longitudinal and baseline measures via individualized, dynamic models. The promising results obtained in the exemplary resilience application indicate that our proposal for dynamic deep learning might also be more generally useful for other application domains.

Temporal discounting and smoking cessation: choice consistency predicts nicotine abstinence in treatment-seeking smokers.

INTRODUCTION: Smokers discount delayed rewards steeper than non-smokers or ex-smokers, possibly due to neuropharmacological effects of tobacco on brain circuitry, or lower abstinence rates in smokers with steep discounting. To delineate both theories from each other, we tested if temporal discounting, choice inconsistency, and related brain activity in treatment-seeking smokers (1) are higher compared to non-smokers, (2) decrease after smoking cessation, and (3) predict relapse. METHODS: At T1, 44 dependent smokers, 29 non-smokers, and 30 occasional smokers underwent fMRI while performing an intertemporal choice task. Smokers were measured before and 21 days after cessation if abstinent from nicotine. In total, 27 smokers, 28 non-smokers, and 29 occasional smokers were scanned again at T2. Discounting rate k and inconsistency var(k) were estimated with Bayesian analysis. RESULTS: First, k and var(k) in smokers in treatment were not higher than in non-smokers or occasional smokers. Second, neither k nor var(k) changed after smoking cessation. Third, k did not predict relapse, but high var(k) was associated with relapse during treatment and over 6 months. Brain activity in valuation and decision networks did not significantly differ between groups and conditions. CONCLUSION: Our data from treatment-seeking smokers do not support the pharmacological hypothesis of pronounced reversible changes in discounting behavior and brain activity, possibly due to limited power. Behavioral data rather suggest that differences between current and ex-smokers might be due to selection. The association of choice consistency and treatment outcome possibly links consistent intertemporal decisions to remaining abstinent.

Probabilistic Reversal Learning Deficits in Patients With Methamphetamine Use Disorder-A Longitudinal Pilot Study.

Methamphetamine use disorder (MUD) is increasing worldwide and commonly associated with learning deficits. Little is known the about underlying trajectories, i.e., how the affected higher-order cognitive functions develop over time and with respect to abstinence and relapse. A probabilistic reversal learning (PRL) paradigm was implemented to uncover the microstructure of impulsive choice and maladaptive learning strategies in 23 patients with MUD in comparison with 24 controls. Baseline data revealed fewer optimal choices and a pattern of altered learning behavior from negative and positive feedback in patients suggesting impairments in flexibly-adapting behavior to changes of reward contingencies. Integrating longitudinal data from a follow-up assessment after 3 months of specific treatment revealed a group-by-time interaction indicating a normalization of these cognitive impairments in patients with MUD. In summary, our study demonstrates behavioral correlates of maladaptive decision-making processes in patients with MUD, which may recover after 3 months of MUD-specific therapy paving the way for further learning-based interventions. Limited by a small sample size, the results of this pilot study warrant replication in larger populations.

Reward modulates the association between sensory noise and brain activity during perceptual decision-making.

Perceptual decisions entail the accumulation of evidence until a decision criterion is reached. The amount of noise in this process is inversely related to the behavioral performance of the decision-maker. Hence, reducing the amount of perceived noise could improve performance in perceptual decisions. In this study, we investigated whether providing monetary reward for correct responses in a perceptual decision-making task would enhance performance based on prior research linking noise reduction to the administration of reward. To this end, thirty-one healthy young adults carried out an incentivized dot tracking task (iDT) during recording of functional magnetic resonance imaging (fMRI). Behavioral responses were fitted to a Bayesian version of the drift-diffusion model that, among other parameters, also includes an estimate of sensory noise. Fifty percent of the trials were incentivized to compare rewarded with unrewarded trials regarding behavior, brain responses and estimates of model parameters. In order to establish a link between the noise parameter and fMRI activity, we correlated percent signal change (PSC) values from nucleus accumbens and caudate nucleus with noise levels in rewarded and unrewarded trials respectively. Although reward did not affect behavioral performance and model parameters, the fMRI analyses showed notable differences in nucleus accumbens, caudate nucleus and rostral anterior cingulate cortex in rewarded relative to unrewarded trials. Furthermore, higher PSC within nucleus accumbens was significantly associated with lower sensory noise levels, which was specific to rewarded trials. This work is consistent with previous findings on reward modulation of brain responses and marks a first step towards elucidating the effects of reward-induced noise suppression during perceptual decision-making.

Neurocognitive Dysfunctions and Their Therapeutic Modulation in Patients With Methamphetamine Dependence: A Pilot Study.

AIM: Methamphetamine (MA) abuse and dependence are increasing worldwide and are commonly associated with cognitive deficits. Some studies indicate that such impairments can improve if users become abstinent, but overall results remain inconclusive. Hence, we have performed a longitudinal case-control study investigating key surrogates for attention and impulsive decision-making before and after treatment. METHODS: Thirty patients with MA dependence and 24 non-substance-abusing control participants were recruited. Groups were matched on age, sex and education. All subjects performed a baseline assessment to obtain neurocognitive measures of sustained attention and delay discounting. Patients subsequently participated in an MA-specific relapse prevention program including repeated monitoring of relapse status. After 3 months, participants of both groups were reevaluated for neurocognitive performance. RESULTS: At baseline, MA patients showed a significantly higher number of omissions compared to controls, indicative of lower sustained attention. Interestingly, we observed a steep decrease of omissions in MA patients to control-group level post treatment. On the other hand, MA patients discounted delayed rewards significantly stronger than controls, indicating a more impulsive choice behavior both before and after treatment. LIMITATION: The results should be interpreted with care because of the small sample and short follow-up period. CONCLUSION: Our data support earlier findings on partial recovery of cognitive deficits in MA patients. They also strengthen the indication for recently recommended psychotherapeutic interventions and may provide a behavioral monitoring tool to inform treatment progress.

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

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.

Metabolic state and value-based decision-making in acute and recovered female patients with anorexia nervosa

Background: Patients with anorexia nervosa forgo eating despite emaciation and severe health consequences. Such dysfunctional decision-making might be explained by an excessive level of self-control, alterations in homeostatic and hedonic regulation, or an interplay between these processes. We aimed to understand value-based decision-making in anorexia nervosa and its association with the gut hormone ghrelin. Besides its homeostatic function, ghrelin has been implicated in the hedonic regulation of appetite and reward via the modulation of phasic dopamine signalling. Methods: In a cross-sectional design, we studied acutely underweight (n = 94) and recovered (n = 37) patients with anorexia nervosa of the restrictive subtype, as well as healthy control participants (n = 119). We assessed plasma concentrations of desacyl ghrelin and parameters of delay discounting, probability discounting for gains and losses, and loss aversion. Results: Recovered patients displayed higher risk aversion for gains, but we observed no group differences for the remaining decision-making parameters. Desacyl ghrelin was higher in acutely underweight and recovered participants with anorexia nervosa relative to healthy controls. Moreover, we found a significant group × desacyl ghrelin interaction in delay discounting, indicating that in contrast to healthy controls, acutely underweight patients with anorexia nervosa who had high desacyl ghrelin concentrations preferably chose the delayed reward option. Limitations: We probed decision-making using monetary rewards, but patients with anorexia nervosa may react differently to disorder-relevant stimuli. Furthermore, in contrast to acyl ghrelin, the functions of desacyl ghrelin are unclear. Therefore, the interpretation of the results is preliminary. Conclusion: The propensity for risk aversion as found in recovered patients with anorexia nervosa could help them successfully complete therapy, or it could reflect sequelae of the disorder. Conversely, ghrelin findings might be related to a mechanism contributing to disease maintenance; that is, in acutely underweight anorexia nervosa, a hungry state may facilitate the ability to forgo an immediate reward to achieve a (dysfunctional) long-term goal.

Presynaptic dopamine function measured with [18F]fluorodopa and L-DOPA effects on impulsive choice.

We previously reported that L-DOPA effects on reward-based decision-making in a randomized, placebo-controlled, double-blind, crossover study were consistent with an inverted U-shaped function whereby both low and high extremes of dopamine signaling are associated with high-impulsive choice. To test this hypothesis, we performed [18F]DOPA positron emission tomography in 60 of the 87 participants in that study, and measured the effective distribution volume ratio (EDVR) of [18F]DOPA influx rate to [18F]dopamine washout rate, an index of presynaptic dopaminergic function. Participants with higher baseline EDVR self-reported lower impulsivity, and discounted rewards as a function of delay more strongly after receiving L-DOPA, whereas the opposite was detected for those with lower baseline EDVR. Our findings support a relationship of striatal dopaminergic activity to trait impulsivity, and the view that there is a non-linear, possibly inverted U-shaped relationship of striatal dopaminergic function with delay discounting. Individuals with optimal dopamine signaling would become more impulsive when receiving dopamine-enhancing drugs, whereas those with suboptimal dopaminergic signaling would benefit and exhibit less impulsive choice. Consideration of differences in endogenous dopamine signaling and possibly also other neurotransmitter activity may be crucial to advance understanding of the neurobiochemical mechanisms of impulsive decision-making and related mental disorders.

No evidence for the involvement of serotonin or the 5-HTTLPR genotype in intertemporal choice in a larger community sample.

BACKGROUND: Serotonin has been implicated in impulsive behaviours such as temporal discounting. While animal studies and theoretical approaches suggest that reduced tonic serotonin levels increase temporal discounting rates and vice versa, evidence from human studies is scarce and inconclusive. Furthermore, an important modulator of serotonin signalling, a genetic variation in the promoter region of the serotonin transporter gene (5-HTTLPR), has not been investigated for temporal discounting so far. OBJECTIVE: First, the purpose of this study was to test for a significant association between 5-HTTLPR and temporal discounting. Second, we wished to investigate the effect of high/low tonic serotonin levels on intertemporal choice and blood oxygen-level-dependent response, controlling for 5-HTTLPR. METHODS: We tested the association of 5-HTTLPR with temporal discounting rates using an intertemporal choice task in 611 individuals. We then manipulated tonic serotonin levels with acute tryptophan interventions (depletion, loading, balanced) in a subsample of 45 short (S)-allele and 45 long (L)/L-allele carriers in a randomised double-blind crossover design using functional magnetic resonance imaging and an intertemporal choice task. RESULTS: Overall, we did not find any effect of serotonin and 5-HTTLPR on temporal discounting rates or the brain networks associated with valuation and cognitive control. CONCLUSION: Our findings indicate that serotonin may not be directly involved in choices including delays on longer timescales such as days, weeks or months. We speculate that serotonin plays a stronger role in dynamic intertemporal choice tasks where the delays are on a timescale of seconds and hence are therefore directly experienced during the experiment.

Baseline impulsivity may moderate L-DOPA effects on value-based decision-making.

Research has indicated a major role of dopamine in decision-making processes, but the underlying mechanisms remain largely unknown due to inconsistency in effects of dopaminergic drugs. To clarify the impact of dopamine on impulsive choice, we administered 150 mg L-DOPA to 87 healthy adults in a randomized, placebo-controlled, double-blind, crossover study, evaluating performance in four value-based decision-making tasks. We predicted that baseline impulsivity would moderate L-DOPA effects. In support of our hypothesis, L-DOPA had no main effect on impulsive choice, but reduced risk-seeking for gains in more-impulsive subjects. Because L-DOPA effects may be influenced by body weight, we repeated our analyses on data from half of the sample (n = 44) with lower weight, anticipating a stronger effect. In addition to the effect on risk-seeking for gains, low-weight participants also exhibited baseline-dependent effects of L-DOPA on loss aversion and delay discounting. Our results are consistent with the hypothesis of an inverted U-shaped dopamine function in which both low and high extremes of dopamine signaling are associated with high-impulsive choice. Consideration of differential baseline impulsivity and body weight may resolve previous seemingly paradoxical pharmacological results and might deepen our understanding of dopaminergic mechanisms underlying impulsivity.

Acute alcohol effects on impulsive choice in adolescents.

BACKGROUND: Neurodevelopmental and alcohol-induced changes in decision-making have been proposed to critically influence impulsive behaviour in adolescents. OBJECTIVE: This study tested the influence of acute alcohol administration on impulsive choice in adolescents. METHODS: Fifty-four males aged 18-19 years were tested in a single-blind placebo-controlled cross-over design. During alcohol administration (infusion resulting in an arterial blood alcohol concentration of 80 mg%) and placebo condition (saline infusion), participants performed a task battery providing estimates of delay discounting, probability discounting for gains, for losses and loss aversion, and also rated subjectively experienced alcohol effects. Additionally, baseline alcohol consumption (Alcohol Use Disorders Identification Test, blood phosphatidylethanol levels), motives (Drinking Motive Questionnaire, Alcohol Expectancy Questionnaire and Obsessive Compulsive Drinking Scale), family history and self-report measures of impulsivity (Barratt Impulsiveness Scale, Substance Use Risk Profile Scale) were provided. RESULTS: No overall effects of treatment on choice behaviour were found. However, individual differences were observed. In the alcohol condition, more impulsive choice tendencies for delay discounting were associated with higher subjectively experienced alcohol effects. Further, higher risk aversion for probabilistic gains and higher loss aversion during alcohol condition were related to higher levels of real-life alcohol consumption and a family history of alcohol problems, respectively. Finally, the time to make a decision was substantially shortened for choices involving negative prospects. CONCLUSIONS: Contrary to common beliefs, acute alcohol intoxication did not generally incite impulsive decision-making. It rather appears that alcohol-induced behavioural changes in adolescents vary considerably depending on prior experiences and subjective effects of alcohol.

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

Dopamine is a key neurotransmitter in action control. However, influential theories of dopamine function make conflicting predictions about the effect of boosting dopamine neurotransmission. Here, we tested if increases in dopamine tone by administration of L-DOPA upregulate reward learning as predicted by reinforcement learning theories, and if increases are specific for deliberative "model-based" control or reflexive "model-free" control. Alternatively, L-DOPA may impair learning as suggested by "value" or "thrift" theories of dopamine. To this end, we employed a two-stage Markov decision-task to investigate the effect of L-DOPA (randomized cross-over) on behavioral control while brain activation was measured using fMRI. L-DOPA led to attenuated model-free control of behavior as indicated by the reduced impact of reward on choice. Increased model-based control was only observed in participants with high working memory capacity. Furthermore, L-DOPA facilitated exploratory behavior, particularly after a stream of wins in the task. Correspondingly, in the brain, L-DOPA decreased the effect of reward at the outcome stage and when the next decision had to be made. Critically, reward-learning rates and prediction error signals were unaffected by L-DOPA, indicating that differences in behavior and brain response to reward were not driven by differences in learning. Taken together, our results suggest that L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action. These findings provide support for the value and thrift accounts of dopamine and call for a refined integration of valuation and action signals in reinforcement learning models.

Risk-seeking for losses is associated with 5-HTTLPR, but not with transient changes in 5-HT levels.

RATIONALE: Serotonin (5-HT) plays a key role in different aspects of value-based decision-making. A recent framework proposed that tonic 5-HT (together with dopamine, DA) codes future average reward expectations, providing a baseline against which possible choice outcomes are compared to guide decision-making. OBJECTIVES: To test whether high 5-HT levels decrease loss aversion, risk-seeking for gains, and risk-seeking for losses. METHODS: In a first session, 611 participants were genotyped for 5-HTTLPR and performed a mixed gambles (MGA) task and two probability discounting tasks for gains and losses, respectively (PDG/PDL). Afterwards, a subsample of 105 participants (44 with S/S, 6 with S/L, 55 with L/L genotype) completed the pharmacological study using a crossover design with tryptophan depletion (ATD), loading (ATL), and balanced (BAL) conditions. The same decision constructs were assessed. RESULTS: We found increased risk-seeking for losses in S/S compared to L/L individuals at the first visit (p = 0.002). Neither tryptophan depletion nor loading affected decision-making, nor did we observe an interaction between intervention and 5-HTTLPR genotype. CONCLUSION: Our data do not support the idea that transient changes of tonic 5-HT affect value-based decision-making. We provide evidence for an association of 5-HTTLPR with risk-seeking for losses, independent of acute 5-HT levels. This indicates that the association of 5-HTTLPR and risk-seeking for losses is mediated via other mechanisms, possibly by differences in the structural development of neural circuits of the 5-HT system during early life phases.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

Value-based decision-making battery: A Bayesian adaptive approach to assess impulsive and risky behavior.

Using simple mathematical models of choice behavior, we present a Bayesian adaptive algorithm to assess measures of impulsive and risky decision making. Practically, these measures are characterized by discounting rates and are used to classify individuals or population groups, to distinguish unhealthy behavior, and to predict developmental courses. However, a constant demand for improved tools to assess these constructs remains unanswered. The algorithm is based on trial-by-trial observations. At each step, a choice is made between immediate (certain) and delayed (risky) options. Then the current parameter estimates are updated by the likelihood of observing the choice, and the next offers are provided from the indifference point, so that they will acquire the most informative data based on the current parameter estimates. The procedure continues for a certain number of trials in order to reach a stable estimation. The algorithm is discussed in detail for the delay discounting case, and results from decision making under risk for gains, losses, and mixed prospects are also provided. Simulated experiments using prescribed parameter values were performed to justify the algorithm in terms of the reproducibility of its parameters for individual assessments, and to test the reliability of the estimation procedure in a group-level analysis. The algorithm was implemented as an experimental battery to measure temporal and probability discounting rates together with loss aversion, and was tested on a healthy participant sample.