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Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning

机译:遗传三重解离揭示了多巴胺在强化学习中的多种作用

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摘要

What are the genetic and neural components that support adaptive learning from positive and negative outcomes? Here, we show with genetic analyses that three independent dopaminergic mechanisms contribute to reward and avoidance learning in humans. A polymorphism in the DARPP-32 gene, associated with striatal dopamine function, predicted relatively better probabilistic reward learning. Conversely, the C957T polymorphism of the DRD2 gene, associated with striatal D2 receptor function, predicted the degree to which participants learned to avoid choices that had been probabilistically associated with negative outcomes. The Val/Met polymorphism of the COMT gene, associated with prefrontal cortical dopamine function, predicted participants' ability to rapidly adapt behavior on a trial-to-trial basis. These findings support a neurocomputational dissociation between striatal and prefrontal dopaminergic mechanisms in reinforcement learning. Computational maximum likelihood analyses reveal independent gene effects on three reinforcement learning parameters that can explain the observed dissociations.
机译:支持正面和负面结果的自适应学习的遗传和神经成分是什么?在这里,我们通过遗传分析表明,三种独立的多巴胺能机制有助于人类的奖励和避免学习。 DARPP-32基因的多态性与纹状体多巴胺功能有关,预示着相对较好的概率奖励学习。相反,DRD2基因的C957T多态性与纹状体D2受体功能相关,可预测参与者学会避免可能与阴性结果相关的选择的程度。 COMT基因的Val / Met多态性与额叶前皮质多巴胺功能相关,可预测参与者在试验间快速适应行为的能力。这些发现支持加强学习中纹状体和前额叶多巴胺能机制之间的神经计算分离。计算最大似然分析揭示了对三个强化学习参数的独立基因效应,这些参数可以解释观察到的解离。

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