scholarly journals Comparison of conventional and rapid-acting antidepressants in a rodent probabilistic reversal learning task

2020 ◽  
Vol 4 ◽  
pp. 239821282090717 ◽  
Author(s):  
Matthew P. Wilkinson ◽  
John P. Grogan ◽  
Jack R. Mellor ◽  
Emma S. J. Robinson
Keyword(s):  
Reinforcement Learning ◽  
Reversal Learning ◽  
Antidepressant Treatment ◽  
Learning Task ◽  
Reward Processing ◽  
Reward Learning ◽  
Feedback Sensitivity ◽  
Rule Changes ◽  
Reinforcement Learning Model ◽  
Probabilistic Reversal Learning

Deficits in reward processing are a central feature of major depressive disorder with patients exhibiting decreased reward learning and altered feedback sensitivity in probabilistic reversal learning tasks. Methods to quantify probabilistic learning in both rodents and humans have been developed, providing translational paradigms for depression research. We have utilised a probabilistic reversal learning task to investigate potential differences between conventional and rapid-acting antidepressants on reward learning and feedback sensitivity. We trained 12 rats in a touchscreen probabilistic reversal learning task before investigating the effect of acute administration of citalopram, venlafaxine, reboxetine, ketamine or scopolamine. Data were also analysed using a Q-learning reinforcement learning model to understand the effects of antidepressant treatment on underlying reward processing parameters. Citalopram administration decreased trials taken to learn the first rule and increased win-stay probability. Reboxetine decreased win-stay behaviour while also decreasing the number of rule changes animals performed in a session. Venlafaxine had no effect. Ketamine and scopolamine both decreased win-stay probability, number of rule changes performed and motivation in the task. Insights from the reinforcement learning model suggested that reboxetine led animals to choose a less optimal strategy, while ketamine decreased the model-free learning rate. These results suggest that reward learning and feedback sensitivity are not differentially modulated by conventional and rapid-acting antidepressant treatment in the probabilistic reversal learning task.

scholarly journals Investigation of reward learning and feedback sensitivity in non-clinical participants with a history of early life stress

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260444
Author(s):  
Matthew Paul Wilkinson ◽  
Chloe Louise Slaney ◽  
Jack Robert Mellor ◽  
Emma Susan Jane Robinson
Keyword(s):  
Reversal Learning ◽  
Life Stress ◽  
Early Life ◽  
Early Life Stress ◽  
Learning Task ◽  
Reward Learning ◽  
Feedback Sensitivity ◽  
History Of ◽  
A Current ◽  
Probabilistic Reversal Learning

Early life stress (ELS) is an important risk factor for the development of depression. Impairments in reward learning and feedback sensitivity are suggested to be an intermediate phenotype in depression aetiology therefore we hypothesised that healthy adults with a history of ELS would exhibit reward processing deficits independent of any current depressive symptoms. We recruited 64 adults with high levels of ELS and no diagnosis of a current mental health disorder and 65 controls. Participants completed the probabilistic reversal learning task and probabilistic reward task followed by depression, anhedonia, social status, and stress scales. Participants with high levels of ELS showed decreased positive feedback sensitivity in the probabilistic reversal learning task compared to controls. High ELS participants also trended towards possessing a decreased model-free learning rate. This was coupled with a decreased learning ability in the acquisition phase of block 1 following the practice session. Neither group showed a reward induced response bias in the probabilistic reward task however high ELS participants exhibited decreased stimuli discrimination. Overall, these data suggest that healthy participants without a current mental health diagnosis but with high levels of ELS show deficits in positive feedback sensitivity and reward learning in the probabilistic reversal learning task that are distinct from depressed patients. These deficits may be relevant to increased depression vulnerability.

scholarly journals Acute stress impairs reward learning in men

2020 ◽  
Author(s):  
Joana Carvalheiro ◽  
Vasco A. Conceição ◽  
Ana Mesquita ◽  
Ana Seara-Cardoso
Keyword(s):  
Reinforcement Learning ◽  
Acute Stress ◽  
Learning Task ◽  
Reward Learning ◽  
Prediction Errors ◽  
How People Learn ◽  
And Control ◽  
The Impact ◽  
Reinforcement Learning Model ◽  
Better Than

AbstractAcute stress is ubiquitous in everyday life, but the extent to which acute stress affects how people learn from the outcomes of their choices is still poorly understood. Here, we investigate how acute stress impacts reward and punishment learning in men using a reinforcement-learning task. Sixty-two male participants performed the task whilst under stress and control conditions. We observed that acute stress impaired participants’ choice performance towards monetary gains, but not losses. To unravel the mechanism(s) underlying such impairment, we fitted a reinforcement-learning model to participants’ trial-by-trial choices. Computational modeling indicated that under acute stress participants learned more slowly from positive prediction errors — when the outcomes were better than expected — consistent with stress-induced dopamine disruptions. Such mechanistic understanding of how acute stress impairs reward learning is particularly important given the pervasiveness of stress in our daily life and the impact that stress can have on our wellbeing and mental health.

Probabilistic Reversal Learning Task

2013 ◽  
Author(s):  
Anna-Maria D'Cruz ◽  
Michael E. Ragozzino ◽  
Matthew W. Mosconi ◽  
Sunil Shrestha ◽  
Edwin H. Cook ◽  
...  
Keyword(s):  
Reversal Learning ◽  
Learning Task ◽  
Probabilistic Reversal Learning

scholarly journals Deficits in reinforcement learning but no link to apathy in patients with schizophrenia

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Matthias N. Hartmann-Riemer ◽  
Steffen Aschenbrenner ◽  
Magdalena Bossert ◽  
Celina Westermann ◽  
Erich Seifritz ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Negative Symptoms ◽  
Learning Task ◽  
Reward Learning ◽  
Positive Outcomes ◽  
Learning Deficits ◽  
Loss Avoidance ◽  
Healthy Control ◽  
Precise Representation ◽  
The Stability

Abstract Negative symptoms in schizophrenia have been linked to selective reinforcement learning deficits in the context of gains combined with intact loss-avoidance learning. Fundamental mechanisms of reinforcement learning and choice are prediction error signaling and the precise representation of reward value for future decisions. It is unclear which of these mechanisms contribute to the impairments in learning from positive outcomes observed in schizophrenia. A recent study suggested that patients with severe apathy symptoms show deficits in the representation of expected value. Considering the fundamental relevance for the understanding of these symptoms, we aimed to assess the stability of these findings across studies. Sixty-four patients with schizophrenia and 19 healthy control participants performed a probabilistic reward learning task. They had to associate stimuli with gain or loss-avoidance. In a transfer phase participants indicated valuation of the previously learned stimuli by choosing among them. Patients demonstrated an overall impairment in learning compared to healthy controls. No effects of apathy symptoms on task indices were observed. However, patients with schizophrenia learned better in the context of loss-avoidance than in the context of gain. Earlier findings were thus partially replicated. Further studies are needed to clarify the mechanistic link between negative symptoms and reinforcement learning.

scholarly journals Trading off the cost of conflict against expected rewards

2018 ◽  
Author(s):  
Nura Sidarus ◽  
Stefano Palminteri ◽  
Valérian Chambon
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Cognitive Control ◽  
Reversal Learning ◽  
Computational Models ◽  
Learning Task ◽  
Learning Rates ◽  
Different Types ◽  
Irrelevant Distractors ◽  
The Cost

AbstractValue-based decision-making involves trading off the cost associated with an action against its expected reward. Research has shown that both physical and mental effort constitute such subjective costs, biasing choices away from effortful actions, and discounting the value of obtained rewards. Facing conflicts between competing action alternatives is considered aversive, as recruiting cognitive control to overcome conflict is effortful. Yet, it remains unclear whether conflict is also perceived as a cost in value-based decisions. The present study investigated this question by embedding irrelevant distractors (flanker arrows) within a reversal-learning task, with intermixed free and instructed trials. Results showed that participants learned to adapt their choices to maximize rewards, but were nevertheless biased to follow the suggestions of irrelevant distractors. Thus, the perceived cost of being in conflict with an external suggestion could sometimes trump internal value representations. By adapting computational models of reinforcement learning, we assessed the influence of conflict at both the decision and learning stages. Modelling the decision showed that conflict was avoided when evidence for either action alternative was weak, demonstrating that the cost of conflict was traded off against expected rewards. During the learning phase, we found that learning rates were reduced in instructed, relative to free, choices. Learning rates were further reduced by conflict between an instruction and subjective action values, whereas learning was not robustly influenced by conflict between one’s actions and external distractors. Our results show that the subjective cost of conflict factors into value-based decision-making, and highlights that different types of conflict may have different effects on learning about action outcomes.

scholarly journals Brief Report: Feasibility of the Probabilistic Reversal Learning Task as an Outcome Measure in an Intervention Trial for Individuals with Autism Spectrum Disorder

2021 ◽  
Author(s):  
Lauren M. Schmitt ◽  
John A. Sweeney ◽  
Craig A. Erickson ◽  
Rebecca Shaffer
Keyword(s):  
Autism Spectrum Disorder ◽  
Cognitive Flexibility ◽  
Reversal Learning ◽  
Behavioral Interventions ◽  
Outcome Measure ◽  
Outcome Measurement ◽  
Learning Task ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Probabilistic Reversal Learning

AbstractCognitive flexibility deficits are a hallmark feature of autism spectrum disorder (ASD), but few evidence-based behavioral interventions have successfully addressed this treatment target. Outcome measurement selection may help account for previous findings. The probabilistic reversal learning task (PRL) is a measure of cognitive flexibility previously validated for use in ASD, but its use as an outcome measure has not yet been assessed. The current study examined the feasibility, reproducibility, and sensitivity of PRL in a within-subjects trial of Regulating Together, a group-based intervention targeting emotion regulation. We demonstrated the PRL is highly feasible, showed test–retest reproducibility, and is sensitive to detect change following the intervention. Our findings demonstrate the PRL task may be a useful outcome measure of cognitive flexibility in future intervention trials in ASD.

Compulsivity and probabilistic reversal learning in OCD and cocaine addiction

2015 ◽  
Vol 30 (S2) ◽  
pp. S110-S111 ◽  
Author(s):  
P. Smith ◽  
N. Benzina ◽  
F. Vorspan ◽  
L. Mallet ◽  
K. N’Diaye
Keyword(s):  
Reversal Learning ◽  
A Priori ◽  
Behavioral Flexibility ◽  
Learning Task ◽  
Repetitive Behaviors ◽  
Cocaine Addiction ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Cocaine Users ◽  
Probabilistic Reversal Learning

Compulsive behavior is a core symptom of both obsessive compulsive disorder (OCD) and cocaine addiction (CA). Across both pathologies, one can identify a priori goal-directed actions (purportedly anxiolytic checking or washing in OCD and pleasure-seeking drug use in addiction) that turn into rigid, ritualized and repetitive behaviors over which the patient loose control. One possible psychopathological mechanism underlying compulsivity is behavioral inflexibility, namely a deficit in the aptitude to dynamically adapt to novel contexts and changing reward rules. The probabilistic reversal learning paradigm allows to objectively assess behavioral flexibility by challenging participants with a task where they have to learn through trials-and-errors which of two stimuli is the most-often rewarded one, while adjusting to sudden inconspicuous contingency reversals. We therefore hypothesized that both OCD and CA would be associated with impaired cognitive flexibility, as measured through perseverative response rate following contingency reversals in this task. Interestingly, impulsivity may also be assessed within this task via the tendency of participants to switch from one stimulus to the other following probabilistic errors. To investigate cognitive inflexibility in relation to CA and OCD respectively, we first compared the performance in a probabilistic reversal learning task of cocaine users, ex cocaine users (abstinent for 2 months or more), and controls, as well as that of participants from the general population whose obsessive-compulsive traits were assessed using the OCI-R, a well-validated self-questionnaire. Our task yielded results similar to those found in the literature: cocaine addicts changed their responses more often, and learned less effectively. Ex-cocaine addicts performed better than addicts but worse than controls, suggesting that addicts’ poor results may be in part explained by reversible cognitive consequences of addiction. Addicts with less cognitive impairments may also be less likely to relapse. Regarding the relationship of flexibility to subclinical OCD traits, we found no link between OCI-R score and perseveration, or between impulsiveness and excessive switching.

scholarly journals Individual differences in behavioral flexibility in a probabilistic reversal learning task: An fMRI study.

2014 ◽  
Vol 7 (4) ◽  
pp. 203-218 ◽  
Author(s):  
Anja Waegeman ◽  
Carolyn H. Declerck ◽  
Christophe Boone ◽  
Ruth Seurinck ◽  
Paul M. Parizel
Keyword(s):  
Individual Differences ◽  
Reversal Learning ◽  
Behavioral Flexibility ◽  
Learning Task ◽  
Fmri Study ◽  
Probabilistic Reversal Learning
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