Reinforcing and motivating properties of social conformity

我们所属的社会群体——家庭、朋友、团队、公司、组织——对我们的决策有着无处不在的影响。事实上，人们经常放弃自己的个人判断和选择，而倾向于服从群体的多数。在某些情况下，这种与群体的结盟可能会防止社会排斥，并允许获得共享资源。然而，研究表明，即使没有社会或经济利益，人们也会随大流。对这一结果的一种解释是，与自己的群体达成共识的行为本身可能是有价值的——最近的神经科学研究支持了这一观点，该研究表明，大脑的奖励回路与社会从众有关。该项目将计算认知模型与功能磁共振成像（fMRI）和行为经济学程序相结合，以更好地理解符合和反对决策的主观价值。通过揭示多数结盟的激励和强化特性，本研究将揭示组织、专业和个人互动的基本方面。在更广泛的影响中，优先共享数据和代码，以促进认知和社会神经科学的研究，让女性、代表性不足的群体和高中生参与进来，并为开发能够提高受损个体社会能力的工具提供信息。本项目使用基于模型的认知神经科学来研究社会从众的激励和强化特性。主要的方法是使顺从的愿望与经济收益的前景相竞争，并评估以顺从为基础的价向环境的其他特征的转移。第二个目标是调查多数意见的相对大小和感知能力如何影响与共识和异议相关的价值。第三个目标是探索从众和传统奖励的共同神经表征。所有的研究都使用了经济决策研究中使用的标准任务的变体。强化学习模型用于对行为选择和神经活动进行定量预测。基于模型的fMRI分析与连通性和多体素模式分析相结合，研究社会和动机神经网络之间的相互作用，并探索社会和经济货币的分布式重叠神经代码。通过将寻求共识的行为形式化为强化学习，该项目在几个方面为社会从众的行为和神经科学文献做出了贡献。特别是，强化学习框架提供了一种机制，用于解释先前获得的效价如何激发明显无关紧要的共识决策，以及该效价如何随后转移到其他情境和人际特征。这种方法在神经和行为层面上，在复杂的社会认知表征和基于奖励的学习和决策的基本机制之间架起了一座重要的桥梁。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The social groups to which we belong -- families, friends, teams, companies, organizations -- have a pervasive influence on our decision making. Indeed, people often abandon their own personal judgments and choices in favor of conforming to a group majority. In some cases, such alignment with the group may protect against social rejection and grant access to shared resources. However, research has shown that people also conform even when there is no social or economic gain for them. One explanation for this result is that the act of reaching consensus with one's group might be valuable in itself -- an idea that is supported by recent neuroscientific research showing that the brain's reward circuit is involved in social conformity. This project combines computational cognitive modeling with functional magnetic resonance imaging (fMRI) and behavioral economic procedures to better understand the subjective value of conforming and dissenting decisions. By uncovering the motivating and reinforcing properties of majority alignment, this research will shed light on a fundamental aspect of organizational, professional and personal interactions. Among the broader impacts is a priority to share data and code to benefit research in cognitive and social neuroscience, to involve the participation of women, underrepresented groups and high school students, and to inform the development of tools that can improve the social competency of impaired individuals.This project uses model-based cognitive neuroscience to investigate the motivating and reinforcing properties of social conformity. The main approach is to make the desire to conform compete with the prospect of economic gain, and to assess the transfer of conformity-based valence to other features of the environment. A second objective is to investigate how the relative size and perceived competence of a majority opinion influences the value associated with consensus and dissent. A third objective is to explore a common neural representation for conformity and conventional reward. All of the studies use variations of standard tasks employed in research on economic decision-making. Reinforcement learning models are used to make quantitative predictions about behavioral choices and neural activity. Model-based fMRI analyses are combined with connectivity and multi-voxel pattern analyses to investigate interactions between social and motivational neural networks, and to explore a distributed overlapping neural code for social and economic currencies. By formalizing consensus-seeking behavior as reinforcement learning, the project contributes in several ways to the behavioral and neuroscientific literatures on social conformity. In particular, the reinforcement learning framework provides a mechanism for how apparently inconsequential consensus decisions may be motivated by previously acquired valence, and for how that valence may then be transferred to other contextual and interpersonal features. This approach bridges a critical gap, at both neural and behavioral levels, between complex socio-cognitive representations and basic mechanisms of reward-based learning and decision-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.