2023
DOI: 10.1038/s41467-023-41130-y
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Dopamine regulates decision thresholds in human reinforcement learning in males

Karima Chakroun,
Antonius Wiehler,
Ben Wagner
et al.

Abstract: 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 credi… Show more

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Cited by 8 publications
(16 citation statements)
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“…Following completion of our previously reported restless four-armed bandit task ( Wiehler et al, 2021 ), participants had a short break inside the scanner. Then they performed 60 trials in total of a stationary reinforcement learning task ( Chakroun et al, 2023 ; Pessiglione et al, 2006 ) using two pairs of stimuli (n = 30 trials per pair). Per pair, one stimulus was associated with a reinforcement rate of 80% (optimal stimulus) whereas the other was associated with a reinforcement rate of 20% (suboptimal stimulus).…”
Section: Methodsmentioning
confidence: 99%
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“…Following completion of our previously reported restless four-armed bandit task ( Wiehler et al, 2021 ), participants had a short break inside the scanner. Then they performed 60 trials in total of a stationary reinforcement learning task ( Chakroun et al, 2023 ; Pessiglione et al, 2006 ) using two pairs of stimuli (n = 30 trials per pair). Per pair, one stimulus was associated with a reinforcement rate of 80% (optimal stimulus) whereas the other was associated with a reinforcement rate of 20% (suboptimal stimulus).…”
Section: Methodsmentioning
confidence: 99%
“…We next set out to more comprehensively analyze choice dynamics underlying learning performance. To this end, we examined a set a reinforcement learning drift diffusion models ( Chakroun et al, 2023 ; Fontanesi, Gluth, et al, 2019 ; Pedersen et al, 2017 ) (RLDDMs) in which the DDM replaces softmax action selection as the choice rule ( Miletić et al, 2020 ). These models can account for the full response time (RT) distributions associated with decisions, and thus provide additional information regarding the dynamics of the choice process.…”
Section: Methodsmentioning
confidence: 99%
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