Reward-Mediated, Model-Free Reinforcement-Learning Mechanisms in Pavlovian and Instrumental Tasks Are Related

强化学习 激励显著性 显著性(神经科学) 联想学习 任务(项目管理) 人工智能 心理学 认知心理学 机器学习 上瘾 神经科学 经济 管理 计算机科学
作者
Neema Moin Afshar,François Cinotti,David C. Martin,Mehdi Khamassi,Donna J. Calu,Jane R. Taylor,Stephanie M. Groman
出处
期刊:The Journal of Neuroscience [Society for Neuroscience]
卷期号:43 (3): 458-471
标识
DOI:10.1523/jneurosci.1113-22.2022
摘要

Model-free and model-based computations are argued to distinctly update action values that guide decision-making processes. It is not known, however, if these model-free and model-based reinforcement learning mechanisms recruited in operationally based instrumental tasks parallel those engaged by pavlovian-based behavioral procedures. Recently, computational work has suggested that individual differences in the attribution of incentive salience to reward predictive cues, that is, sign- and goal-tracking behaviors, are also governed by variations in model-free and model-based value representations that guide behavior. Moreover, it is not appreciated if these systems that are characterized computationally using model-free and model-based algorithms are conserved across tasks for individual animals. In the current study, we used a within-subject design to assess sign-tracking and goal-tracking behaviors using a pavlovian conditioned approach task and then characterized behavior using an instrumental multistage decision-making (MSDM) task in male rats. We hypothesized that both pavlovian and instrumental learning processes may be driven by common reinforcement-learning mechanisms. Our data confirm that sign-tracking behavior was associated with greater reward-mediated, model-free reinforcement learning and that it was also linked to model-free reinforcement learning in the MSDM task. Computational analyses revealed that pavlovian model-free updating was correlated with model-free reinforcement learning in the MSDM task. These data provide key insights into the computational mechanisms mediating associative learning that could have important implications for normal and abnormal states.SIGNIFICANCE STATEMENT Model-free and model-based computations that guide instrumental decision-making processes may also be recruited in pavlovian-based behavioral procedures. Here, we used a within-subject design to test the hypothesis that both pavlovian and instrumental learning processes were driven by common reinforcement-learning mechanisms. Sign-tracking and goal-tracking behaviors were assessed in rats using a pavlovian conditioned approach task, and then instrumental behavior was characterized using an MSDM task. We report that sign-tracking behavior was associated with greater model-free, but not model-based, learning in the MSDM task. These data suggest that pavlovian and instrumental behaviors may be driven by conserved reinforcement-learning mechanisms.

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