Model-Free and Model-Based Influences in Addiction-Related Behaviors
Model-Free and Model-Based Influences in Addiction-Related Behaviors
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DOI：
10.1016/j.biopsych.2018.12.017
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发表时间：
2019-06-01
影响因子：
10.6
通讯作者：
Taylor, Jane R.
中科院分区：
文献类型：
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作者：
Groman, Stephanie M.;Massi, Bart;Taylor, Jane R.
背景技术背景：指导行为选择的决策过程中断是许多精神疾病的核心特征，包括成瘾。决策受到目标导向和习惯系统的影响，这些系统可以分别使用基于模型和无模型的强化学习算法进行计算表征。最近的证据表明，这些强化学习系统对物质依赖个体行为的影响不平衡，但尚不清楚这些干扰是否是慢性药物使用的表现和/或成瘾的预先存在的风险因素。方法：我们对成年雄性大鼠进行了多阶段决策任务的训练，以量化自我决策前后的无模型和基于模型的过程。结果：在任何药物使用之前，无模型但非基于模型的学习的个体差异预测随后的甲基苯丙胺自我管理;具有较低无模型行为的大鼠比具有较高无模型行为的大鼠服用更多的甲基苯丙胺。这种关系是有选择性的无模型更新后的奖励，但不是无奖励的，选择。无模型和基于模型的学习减少大鼠甲基苯丙胺自我管理后，这是由于在大鼠适当地使用未奖励的结果的能力递减。此外，药物诱导的无模型学习中断的程度与基于模型的行为中断无关，表明药物自我给药独立地改变了两种强化学习策略。这些发现提供了直接证据，表明无模型和基于模型的学习机制参与了成瘾脆弱性和病理学的选择方面，它们提供了一个独特的行为平台，用于对精神疾病的临床前模型中的决策进行系统级分析。
BACKGROUND: Disruptions in the decision-making processes that guide action selection are a core feature of many psychiatric disorders, including addiction. Decision making is influenced by the goal-directed and habitual systems that can be computationally characterized using model-based and model-free reinforcement learning algorithms, respectively. Recent evidence suggests an imbalance in the influence of these reinforcement learning systems on behavior in individuals with substance dependence, but it is unknown whether these disruptions are a manifestation of chronic drug use and/or are a preexisting risk factor for addiction.METHODS: We trained adult male rats on a multistage decision-making task to quantify model-free and model-based processes before and after self-administration of methamphetamine or saline.RESULTS: Individual differences in model-free, but not model-based, learning prior to any drug use predicted subsequent methamphetamine self-administration; rats with lower model-free behavior took more methamphetamine than rats with higher model-free behavior. This relationship was selective to model-free updating following a rewarded, but not unrewarded, choice. Both model-free and model-based learning were reduced in rats following methamphetamine self-administration, which was due to a decrement in the ability of rats to use unrewarded outcomes appropriately. Moreover, the magnitude of drug-induced disruptions in model-free learning was not correlated with disruptions in model-based behavior, indicating that drug self-administration independently altered both reinforcement learning strategies.CONCLUSIONS: These findings provide direct evidence that model-free and model-based learning mechanisms are involved in select aspects of addiction vulnerability and pathology, and they provide a unique behavioral platform for conducting systems-level analyses of decision making in preclinical models of mental illness.