Are methamphetamine users compulsive? Faulty reinforcement learning, not inflexibility, underlies decision making in people with methamphetamine use disorder.

Autor: Robinson AH; Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia., Perales JC; Department of Experimental Psychology, Mind, Brain, and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain., Volpe I; Clinical and Social Research Team, Turning Point, Eastern Health, Melbourne, Victoria, Australia.; Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia.; Monash Addiction Research Centre, Monash University, Melbourne, Victoria, Australia., Chong TT; Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia., Verdejo-Garcia A; Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia.
Jazyk: angličtina
Zdroj: Addiction biology [Addict Biol] 2021 Jul; Vol. 26 (4), pp. e12999. Date of Electronic Publication: 2021 Jan 03.
DOI: 10.1111/adb.12999
Abstrakt: Methamphetamine use disorder involves continued use of the drug despite negative consequences. Such 'compulsivity' can be measured by reversal learning tasks, which involve participants learning action-outcome task contingencies (acquisition-contingency) and then updating their behaviour when the contingencies change (reversal). Using these paradigms, animal models suggest that people with methamphetamine use disorder (PwMUD) may struggle to avoid repeating actions that were previously rewarded but are now punished (inflexibility). However, difficulties in learning task contingencies (reinforcement learning) may offer an alternative explanation, with meaningful treatment implications. We aimed to disentangle inflexibility and reinforcement learning deficits in 35 PwMUD and 32 controls with similar sociodemographic characteristics, using novel trial-by-trial analyses on a probabilistic reversal learning task. Inflexibility was defined as (a) weaker reversal phase performance, compared with the acquisition-contingency phases, and (b) persistence with the same choice despite repeated punishments. Conversely, reinforcement learning deficits were defined as (a) poor performance across both acquisition-contingency and reversal phases and (b) inconsistent postfeedback behaviour (i.e., switching after reward). Compared with controls, PwMUD exhibited weaker learning (odds ratio [OR] = 0.69, 95% confidence interval [CI] [0.63-0.77], p < .001), though no greater accuracy reduction during reversal. Furthermore, PwMUD were more likely to switch responses after one reward/punishment (OR = 0.83, 95% CI [0.77-0.89], p < .001; OR = 0.82, 95% CI [0.72-0.93], p = .002) but just as likely to switch after repeated punishments (OR = 1.03, 95% CI [0.73-1.45], p = .853). These results indicate that PwMUD's reversal learning deficits are driven by weaker reinforcement learning, not inflexibility.
(© 2021 Society for the Study of Addiction.)
Databáze: MEDLINE