Back

Dopamine Agonists in Parkinson's Disease Decouple Risk-Taking from Reward-Paired Cues by Enhancing Risky Choice in Their Absence

Muksuris, K.; Flynn, E.; Feng, T. L.; Surathi, P.; Yeung, S. C.; Mortazavi, L.; Isberg, A.; McKeown, M.; Appel-Cresswell, S.; Winstanley, C. A.; Stoessl, A. J.; Barton, J.; Cherkasova, M. V.

2026-09-12 neuroscience
10.64898/2026.09.05.748022 bioRxiv
Show abstract

Background: Common side effects of dopamine replacement therapy (DRT) for Parkinson's Disease (PD) are addiction-like impulse control disorders, including compulsive gambling. Gambling products such as slot machines prominently feature reward-paired audiovisual stimuli, which can promote riskier choices on laboratory gambling tasks in both humans and rodents. In rats, risky decision making in the presence of reward-paired cues is dependent on dopamine D3 receptor activity and is increased by ropinirole, a D2/3 receptor agonist with a higher affinity for D3 receptors. In humans, it remains uncertain whether cue-induced risky choice is amplified by dopamine agonism. Methods: We tested effects of DRT on cue-induced risky choice in 62 patients with PD (34 on levodopa monotherapy, 27 on levodopa and dopamine agonists). Patients performed two versions of a risky decision-making task: one with and one without reward-paired sensory cues, both ON and OFF DRT. A group of 36 age-matched controls completed the same task versions without DRT. Results: Across all groups, participants made riskier choices when the task included reward-paired sensory cues. Levodopa monotherapy did not affect risky decision-making. However, a combination of levodopa and dopamine agonists increased risky choices specifically in the uncued version of the task, making performance indistinguishable from that on the cued task. Conclusions: Dopamine agonists combined with levodopa promote risk-taking even in the absence of reward-paired cues. This could translate into risky reward-seeking behaviors that are decoupled from contextual factors.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.