Jonathon R Howlett1, He Huang2, Cédric M Hysek3, Martin P Paulus2. 1. Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA. jhowlett@ucsd.edu. 2. Laureate Institute for Brain Research, Tulsa, OK, 74136, USA. 3. Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
Abstract
RATIONALE AND OBJECTIVES:Norepinephrine mediates the adjustment of error-driven learning to match the rate of change of the environment, while phasic dopamine signals prediction errors. We tested the hypothesis that pharmacologic manipulation may modulate this process. METHODS: We administered a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, or placebo in double-blind randomized fashion to 20 healthy human males, who then performed a probabilistic learning task. Each subject was tested in two sessions, receiving methylphenidate in one session and placebo in the other, in randomized order. Task performance was quantified by the percentage of trials on which subjects chose the most likely option, while learning rate was measured using a computational model-based parameter as well as with a behavioral analogue of this parameter. RESULTS: There was a substance-by-session interaction effect on behavioral learning rate and model-based learning rate, such that subjects receiving methylphenidate exhibited higher learning rates than those receiving placebo in session 1, with no difference observed in session 2, suggesting that subjects retained the increased learning rate across sessions. Higher behavioral learning rate was associated with both higher task performance and with the model-based learning rate. Higher learning rates were advantageous given the high rate of change on the task. Subjects receiving methylphenidate and placebo began the task in session 1 with a similar behavioral learning rate, but those receiving methylphenidate rapidly increased learning rate toward the optimal value, suggesting that methylphenidate accelerated the adaptation of learning rate based on the environment. CONCLUSIONS: The results suggest that methylphenidate may improve disrupted probabilistic learning in disorders involving noradrenergic or dopaminergic dysfunction.
RCT Entities:
RATIONALE AND OBJECTIVES:Norepinephrine mediates the adjustment of error-driven learning to match the rate of change of the environment, while phasic dopamine signals prediction errors. We tested the hypothesis that pharmacologic manipulation may modulate this process. METHODS: We administered a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, or placebo in double-blind randomized fashion to 20 healthy human males, who then performed a probabilistic learning task. Each subject was tested in two sessions, receiving methylphenidate in one session and placebo in the other, in randomized order. Task performance was quantified by the percentage of trials on which subjects chose the most likely option, while learning rate was measured using a computational model-based parameter as well as with a behavioral analogue of this parameter. RESULTS: There was a substance-by-session interaction effect on behavioral learning rate and model-based learning rate, such that subjects receiving methylphenidate exhibited higher learning rates than those receiving placebo in session 1, with no difference observed in session 2, suggesting that subjects retained the increased learning rate across sessions. Higher behavioral learning rate was associated with both higher task performance and with the model-based learning rate. Higher learning rates were advantageous given the high rate of change on the task. Subjects receiving methylphenidate and placebo began the task in session 1 with a similar behavioral learning rate, but those receiving methylphenidate rapidly increased learning rate toward the optimal value, suggesting that methylphenidate accelerated the adaptation of learning rate based on the environment. CONCLUSIONS: The results suggest that methylphenidate may improve disrupted probabilistic learning in disorders involving noradrenergic or dopaminergic dysfunction.
Authors: Nora D Volkow; Gene-Jack Wang; Lisa Smith; Joanna S Fowler; Frank Telang; Jean Logan; Dardo Tomasi Journal: Neuroimage Date: 2015-07-21 Impact factor: 6.556
Authors: Alexandre Y Dombrovski; Luke Clark; Greg J Siegle; Meryl A Butters; Naho Ichikawa; Barbara J Sahakian; Katalin Szanto Journal: Am J Psychiatry Date: 2010-03-15 Impact factor: 18.112
Authors: Rumana Chowdhury; Marc Guitart-Masip; Christian Lambert; Peter Dayan; Quentin Huys; Emrah Düzel; Raymond J Dolan Journal: Nat Neurosci Date: 2013-03-24 Impact factor: 24.884
Authors: Hanneke Em den Ouden; Roshan Cools; Jennifer L Cook; Jennifer C Swart; Monja I Froböse; Andreea O Diaconescu; Dirk Em Geurts Journal: Elife Date: 2019-12-18 Impact factor: 8.140
Authors: Sahib S Khalsa; Teresa A Victor; Rayus Kuplicki; Hung-Wen Yeh; Kimberly E Vanover; Martin P Paulus; Robert E Davis Journal: Neuropsychopharmacology Date: 2022-04-29 Impact factor: 8.294