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.

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.

Shorter planning depth and higher response noise during sequential decision-making in old age.

Forward planning is crucial to maximize outcome in complex sequential decision-making scenarios. In this cross-sectional study, we were particularly interested in age-related differences of forward planning. We presumed that especially older individuals would show a shorter planning depth to keep the costs of model-based decision-making within limits. To test this hypothesis, we developed a sequential decision-making task to assess forward planning in younger (age < 40 years; n = 25) and older (age > 60 years; n = 27) adults. By using reinforcement learning modelling, we inferred planning depths from participants' choices. Our results showed significantly shorter planning depths and higher response noise for older adults. Age differences in planning depth were only partially explained by well-known cognitive covariates such as working memory and processing speed. Consistent with previous findings, this indicates age-related shifts away from model-based behaviour in older adults. In addition to a shorter planning depth, our findings suggest that older adults also apply a variety of heuristical low-cost strategies.

A comparison of fMRI and behavioral models for predicting inter-temporal choices.

In an inter-temporal choice (IteCh) task, subjects are offered a smaller amount of money immediately or a larger amount at a later time point. Here, we are using trial-by-trial fMRI data from 363 recording sessions and machine learning in an attempt to build a classifier that would ideally outperform established behavioral model given that it has access to brain activity specific to a single trial. Such methods could allow for future investigations of state-like factors that influence IteCh choices. To investigate this, coefficients of a GLM with one regressor per trial were used as features for a support vector machine (SVM) in combination with a searchlight approach for feature selection and cross-validation. We then compare the results to the performance of four different behavioral models. We found that the behavioral models reached mean accuracies of 90% and above, while the fMRI model only reached 54.84% at the best location in the brain with a spatial distribution similar to the well-known value-tracking network. This low, though significant, accuracy is in line with simulations showing that classifying based on signals with realistic correlations with subjective value produces comparable, low accuracies. These results emphasize the limitations of fMRI recordings from single events to predict human choices, especially when compared to conventional behavioral models. Better performance may be obtained with paradigms that allow the construction of miniblocks to improve the available signal-to-noise ratio.

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.

Acute tryptophan loading decreases functional connectivity between the default mode network and emotion-related brain regions.

It has been shown that the functional architecture of the default mode network (DMN) can be affected by serotonergic challenges and these effects may provide insights on the neurobiological bases of depressive symptomatology. To deepen our understanding of this possible interplay, we used a double-blind, randomized, cross-over design, with a control condition and two interventions to decrease (tryptophan depletion) and increase (tryptophan loading) brain serotonin synthesis. Resting-state fMRI from 85 healthy subjects was acquired for all conditions 3 hr after the ingestion of an amino acid mixture containing different amounts of tryptophan, the dietary precursor of serotonin. The DMN was derived for each participant and session. Permutation testing was performed to detect connectivity changes within the DMN as well as between the DMN and other brain regions elicited by the interventions. We found that tryptophan loading increased tryptophan plasma levels and decreased DMN connectivity with visual cortices and several brain regions involved in emotion and affect regulation (i.e., putamen, subcallosal cortex, thalamus, and frontal cortex). Tryptophan depletion significantly reduced tryptophan levels but did not affect brain connectivity. Subjective ratings of mood, anxiety, sleepiness, and impulsive choice were not strongly affected by any intervention. Our data indicate that connectivity between the DMN and emotion-related brain regions might be modulated by changes in the serotonergic system. These results suggest that functional changes in the brain associated with different brain serotonin levels may be relevant to understand the neural bases of depressive symptoms.

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.