竞技游戏中策略推理的神经关联

Neural correlates of strategic reasoning during competitive games.

作者信息

Seo Hyojung, Cai Xinying, Donahue Christopher H, Lee Daeyeol

机构信息

Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA.

Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA. Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA. Department of Psychology, Yale University, New Haven, CT 06510, USA.

出版信息

Science. 2014 Oct 17;346(6207):340-3. doi: 10.1126/science.1256254. Epub 2014 Sep 18.

Abstract

Although human and animal behaviors are largely shaped by reinforcement and punishment, choices in social settings are also influenced by information about the knowledge and experience of other decision-makers. During competitive games, monkeys increased their payoffs by systematically deviating from a simple heuristic learning algorithm and thereby countering the predictable exploitation by their computer opponent. Neurons in the dorsomedial prefrontal cortex (dmPFC) signaled the animal's recent choice and reward history that reflected the computer's exploitative strategy. The strength of switching signals in the dmPFC also correlated with the animal's tendency to deviate from the heuristic learning algorithm. Therefore, the dmPFC might provide control signals for overriding simple heuristic learning algorithms based on the inferred strategies of the opponent.

摘要

尽管人类和动物的行为很大程度上是由强化和惩罚塑造的,但社会环境中的选择也会受到其他决策者的知识和经验信息的影响。在竞争性游戏中,猴子通过系统地偏离简单的启发式学习算法来增加它们的收益,从而对抗来自计算机对手的可预测的剥削。背内侧前额叶皮层(dmPFC)中的神经元发出信号,表明动物最近的选择和奖励历史,这反映了计算机的剥削策略。dmPFC中切换信号的强度也与动物偏离启发式学习算法的倾向相关。因此,dmPFC可能会根据对手的推断策略提供控制信号,以超越简单的启发式学习算法。

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