Biology subjects

Wiehler, A.

Publications and source records attributed to Wiehler, A..

7 recordsLinked to original sources

bioRxiv2022

Dopamine regulates decision thresholds in human reinforcement learning.

Dopamine fundamentally contributes to reinforcement learning by encoding prediction errors, deviations of an outcome from expectation. Prediction error coding in dopaminergic regions in human functional neuroimaging studies is well replicated. In contrast, replications of behavioral and neural effects of pharmacological modulations of the dopamine system in human reinforcement learning are scarce. Additionally, dopamine contributes to action selection, but direct evidence and process-specific accounts in human reinforcement learning are lacking. Here we examined dopaminergic mechanisms underlying human reinforcement learning in a within-subjects pharmacological approach in male human volunteers (n=31, within-subjects design; Placebo, 150mg L-dopa, 2mg Haloperidol) in combination with functional magnetic resonance imaging and a stationary reinforcement learning task. We had two aims. First, we aimed to replicate previously reported beneficial effects of L-dopa vs. Haloperidol on reinforcement learning from gains. This replication was not successful. We observed no performance benefit of L-Dopa vs. Haloperidol, and no evidence for alterations in neural prediction error signaling. In contrast, Bayesian analyses provided moderate evidence in favor of the null hypothesis. This unsuccessful replication is likely at least partly due to a number of differences in experimental design. Second, using combined reinforcement learning drift diffusion models, we tested the recent proposal that dopamine contributes to action selection by regulating decision thresholds. Model comparison revealed that the data were best accounted for by a reinforcement learning drift diffusion model with separate learning rates for positive and negative prediction errors. The model accounted for both reductions in RTs and increases in accuracy over the course of learning. The only parameter showing robust drug effects was the boundary separation parameter, which revealed reduced decision thresholds under both L-Dopa and Haloperidol, compared to Placebo, and the degree of threshold reduction accounted for individual differences in RTs between conditions. Results are in line with the idea that striatal dopamine regulates decision thresholds during action selection, and that lower dosages of D2 receptor antagonists increase striatal DA release via an inhibition of autoreceptor-mediated feedback mechanisms.

neuroscience↗

bioRxiv2021

Contractile force of transplanted cardiomyocytes contributes to heart function after injury

Transplantation of pluripotent stem cell-derived cardiomyocytes represents an innovative therapeutic strategy for heart failure. Studies in small and large animals have demonstrated functional recovery of left ventricular function after cardiomyocyte transplantation1-4, and first clinical studies are currently underway5. Yet, the mechanism of action underlying graft-induced benefit is unknown6. Here we demonstrate that transplanted cardiomyocytes actively contribute to heart function. We transplanted cardiomyocytes with an optogenetic off-on switch in a guinea pig cardiac injury model. Light-induced inhibition of engrafted cardiomyocyte contractility resulted in a rapid decrease of left ventricular function that was fully reversible with the offset of photostimulation. Hence, our optogenetic approach demonstrated that transplanted cardiomyocytes actively participate in heart function, supporting the hypothesis that the delivery of new force-generating myocardium can serve as a regenerative therapeutic strategy.

pharmacology and toxicology↗

bioRxiv2020

Diffusion modeling reveals reinforcement learning impairments in gambling disorder that are linked to attenuated ventromedial prefrontal cortex value representations.

Gambling disorder is associated with deficits in feedback-based learning tasks, but the computational mechanisms underlying these learning impairments are still poorly understood. Here, we examined this question using a combination of computational modeling and functional resonance imaging (fMRI) in individuals that regular participate in gambling (n=23, seven fulfilled 1-3 DSM 5 criteria, sixteen fulfilled 4 or more) and matched controls (n=23). Participants performed a stationary reinforcement learning task with two pairs of stimuli (80% vs. 20% reinforcement rates per pair). As predicted, the gambling group made significantly fewer selections of the optimal stimulus, while overall response times (RTs) were not significantly different between groups. We then used comprehensive modeling using reinforcement learning drift diffusion models (RLDDMs) in combination with hierarchical Bayesian parameter estimation to shed light on the computational underpinnings of this performance impairment. In both groups, an RLDDM in which both non-decision time and response threshold (boundary separation) changed over the course of the experiment accounted for the data best. The model showed good parameter and model recovery, and posterior predictive checks revealed that in both groups, the model reproduced the evolution of both accuracy and RTs over time. The learning impairment in the gambling group was attributable to a more rapid reduction in boundary separation over time, and a reduced effect of value-differences on the drift rate, compared to controls. The gambling group also exhibted substantially shorter non-decision times. Imaging analyses replicated earlier effects of prediction error coding in the ventral striatum and value coding in the ventro-medial prefrontal cortex, but there was no credible evidence for group differences in these regions. Taken together, our findings highlight the computational mechanisms underlying reinforcement learning impairments in gambling disorder.

neuroscience↗

bioRxiv2020

Effects of episodic future thinking on temporal discounting: a re-analysis of six data sets using hierarchical Bayesian parameter estimation and compilation of effect sizes

Temporal discounting refers to the tendency of humans and many animals to devalue rewards as a function of time. Steep discounting of value over time is associated with a range of psychiatric disorders, including substance use disorders and behavioral addictions, and therefore of potentially high clinical relevance. One cognitive factor that has repeatedly been shown to reduce temporal discounting in humans is episodic future thinking, the process of vividly imagining future outcomes, which has been linked to hippocampal mechanisms in a number of studies. However, the analytical approaches used to quantify the behavioral effects have varied between studies, which complicates a direct comparison of the obtained effect sizes. Here we re-analyzed temporal discounting data from previously published functional magnetic resonance imaging (fMRI) and behavioral studies (six data sets from five papers, n=204 participants in total) using an identical model structure and hierarchical Bayesian parameter estimation procedure. Analyses confirmed that engagement in episodic future thinking leads to robust and and consistent reductions in temporal discounting with on average medium effect sizes. In contrast, effects on choice consistency (decision noise) where small and with inconsistent directionality. We provide standardized and unstandardized effect size estimates for each data set and discuss clinical implications as well as issues of hierarchical Bayesian parameter estimation.

neuroscience↗

bioRxiv2019

Attenuated directed exploration during reinforcement learning in gambling disorder

Gambling disorder is a behavioral addiction associated with impairments in value-based decision-making and behavioral flexibility and might be linked to changes in the dopamine system. Maximizing long-term rewards requires a flexible trade-off between the exploitation of known options and the exploration of novel options for information gain. This exploration-exploitation trade-off is thought to depend on dopamine neurotransmission. We hypothesized that human gamblers would show a reduction in directed (uncertainty-based) exploration, accompanied by changes in brain activity in a fronto-parietal exploration-related network. Twenty-three frequent, non-treatment seeking gamblers and twenty-three healthy matched controls (all male) performed a four-armed bandit task during functional magnetic resonance-imaging. Computational modeling using hierarchical Bayesian parameter estimation revealed signatures of directed exploration, random exploration, and perseveration in both groups. Gamblers showed a reduction in directed exploration, whereas random exploration and perseveration were similar between groups. Neuroimaging revealed no evidence for group differences in neural representations of basic task variables (expected value, prediction errors). Our hypothesis of reduced frontal pole recruitment in gamblers was not supported. Exploratory analyses revealed that during directed exploration, gamblers showed reduced parietal cortex and substantia-nigra / ventral-tegmental-area activity. Cross-validated classification analyses revealed that connectivity in an exploration-related network was predictive of group status, suggesting that connectivity patterns might be more predictive of problem gambling than univariate effects. Findings reveal specific reductions in strategic exploration gamblers that might be linked to altered processing in a fronto-parietal network and/or changes in dopamine neurotransmission implicated in gambling disorder. Significance statementWiehler et al. report that gamblers rely less on the strategic exploration of unknown, but potentially better rewards during reward learning. This is reflected in a related network of brain activity. Parameters of this network can be used to predict the presence of problem gambling behavior in participants.

neuroscience↗

bioRxiv2019

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

A central issue in reinforcement learning and decision-making is whether to exploit knowledge of reward values, or to explore novel options. Although it is widely hypothesized that dopamine neurotransmission plays a key role in regulating this balance, causal evidence for a role of dopamine in human exploration is still lacking. Here, we use a combination of computational modeling, pharmacological intervention and functional magnetic resonance imaging (fMRI) to test for a causal effect of dopamine transmission on the exploration-exploitation trade-off in humans. 31 healthy male subjects performed a restless four-armed bandit task in a within-subjects design under three drug conditions: 150mg of the dopamine precursor L-dopa, 2mg of the D2 receptor antagonist haloperidol, and placebo. In all conditions, choice behavior was best explained by an extension of an established Bayesian learning model accounting for perseveration, uncertainty-based exploration and random exploration. Uncertainty-based exploration was attenuated under L-dopa compared to placebo and haloperidol. There was no evidence for a modulation of prediction error signaling or categorical effects of exploration/exploitation under L-dopa, whereas model-based fMRI revealed that 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 exploration by modulating how this circuit tracks accumulating uncertainty during decision-making.

neuroscience↗

bioRxiv2017

A potential link between gambling addiction severity and central dopamine levels -- evidence from spontaneous eye blink rates in gamblers and controls

Accumulating evidence points at similarities between substance use disorders and pathological gambling on the behavioral and neural level. In substance addiction, dysregulation of striatal dopamine transmission has been consistently revealed. Due to the neurotoxicity of stimulating substances, it is still debated if this constitutes mainly a consequence of recurrent substance abuse or a vulnerability marker for addiction disorders. For gambling addiction, no clear association with striatal dopamine levels has been unveiled so far. With its presumably negligible dopaminergic toxicity, possible differences in striatal dopamine transmission in gambling addiction might therefore constitute a vulnerability marker. Spontaneous eye blink rate (sEBR) is controversially discussed as a potential proxy measure for striatal dopamine levels. Here we examined sEBR in 21 male problem gamblers and 20 healthy control participants. In addition, participants completed a screening questionnaire for overall psychopathology and self-reported measures of alcohol and nicotine consumption. We found no significant difference in sEBR between gamblers and controls. However, in gamblers, sEBR was negatively associated with addiction severity and positively associated with psychopathology. A final exploratory analysis revealed that healthy controls with low sEBR displayed higher alcohol and nicotine consumption than healthy participants with high sEBR. Although the association between dopamine transmission and sEBR is still debated, our findings reveal that sEBR is sensitive to inter-individual differences in addiction severity in problem gamblers.

neuroscience↗