人际互动中社会学习的计算神经机制

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黎穗卿, 陈新玲, 翟瑜竹, 张怡洁, 章植鑫, 封春亮(

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教育部脑认知与教育科学重点实验室(华南师范大学); 华南师范大学心理学院; 华南师范大学心理应用研究中心; 华南师范大学广东省心理健康与认知科学重点实验室, 广州 510631

收稿日期:2020-08-10出版日期:2021-04-15发布日期:2021-02-22

基金资助:国家自然科学基金(31900757);国家自然科学基金(32020103008)

The computational and neural substrates underlying social learning

LI Suiqing, CHEN Xinling, ZHAI Yuzhu, ZHANG Yijie, ZHANG Zhixing, FENG Chunliang(

)

Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology, South China Normal University; Center for Studies of Psychological Application, South China Normal University; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China

Received:2020-08-10Online:2021-04-15Published:2021-02-22

摘要/Abstract

摘要： 人类在社会互动中通过他人的行为对他人特质、意图及特定情境下的社会规范进行学习, 是优化决策、维护积极社会互动的重要条件。近年来, 越来越多的研究通过结合计算模型与神经影像技术对社会学习的认知计算机制及其神经基础进行了深入考察。已有研究发现, 人类的社会学习过程能够较好地被强化学习模型与贝叶斯模型刻画, 主要涉及的认知计算过程包括主观期望、预期误差和不确定性的表征以及信息整合的过程。大脑对这些计算过程的执行主要涉及奖惩加工相关脑区(如腹侧纹状体与腹内侧前额叶)、社会认知加工相关脑区(如背内侧前额叶和颞顶联合区)及认知控制相关脑区(如背外侧前额叶)。需要指出的是, 计算过程与大脑区域之间并不是一一映射的关系, 提示未来研究可借助多变量分析与脑网络分析等技术从系统神经科学的角度来考察大尺度脑网络如何执行不同计算过程。此外, 将来研究应注重生态效度, 利用超扫描技术考察真实互动下的社会学习过程, 并更多地关注内隐社会学习的计算与神经机制。

图/表 1

图1社会学习的计算神经机制 A：社会学习的计算模型及神经基础。强化学习模型下社会学习的认知过程主要包括主观期望和预期误差的计算, 贝叶斯模型下社会学习的认知过程包括主观期望、预期误差的计算、不确定性的表征以及信息整合。主观期望的计算涉及奖赏系统与社会认知系统; 预期误差的计算涉及奖赏系统、情感系统与社会认知系统; 不确定性的表征及信息整合涉及奖赏系统、情感系统、社会认知系统与认知控制系统。B：社会学习涉及的大脑系统：奖赏系统主要包括VS、vmPFC; 情感系统主要包括ACC、AI、amygdala ; 社会认知系统主要包括dmPFC、TPJ、STS、PCC; 认知控制系统主要包括dlPFC、IPL。 VS：ventral striatum, 腹侧纹状体; vmPFC：ventromedial prefrontal cortex, 腹内侧前额叶皮层; ACC：anterior cingulate cortex, 前扣带皮层; AI：anterior insula, 前侧脑岛; amygdala：杏仁核; dmPFC：dorsalmedial prefrontal cortex, 背内侧前额叶皮层; TPJ：temporo-parietal junction, 颞顶联合区; STS, superior temporal sulcus, 颞上沟; PCC：posterior cingulate cortex, 后扣带皮层; dlPFC：dorsolateral prefrontal cortex, 背外侧前额叶皮层; IPL：inferior parietal lobule, 顶下小叶。

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