The Influence of Mental Representations of Social Agents on Social Decision Preferences

社会主体心理表征对社会决策偏好的影响

• 批准号: 2104629
• 负责人: Joao Moreira
• 金额: $ 13.8万
• 依托单位: Moreira, Joao F
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2104629&HistoricalAwards=false
• 关键词: Influence; Mental; Representations; Social; Agents

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Carolyn Parkinson at the University of California, Los Angeles, this postdoctoral fellowship award supports an early career scientist investigating how mental representation of social agents affect decision processes involving these others. Defined as decisions that have direct or indirect social consequences, social decision-making has received much scientific attention over the past two decades. However, existing social decision-making research is impoverished insofar that very little is known about how the features of social targets implicated in social decision-making influence decision processes. Humans represent a wealth of information about others that profoundly shapes thought and behavior, yet it is unknown how these representations—dynamic mental models of others—impact decision preferences. Indeed, classic work from social cognitive psychology and neuroscience indicates that representations guide behavior in context, suggesting that mental representations likely play an important role in shaping social decision preferences. The current study aims to use computational methods to analyze functional magnetic resonance images and text data to (i) probe mental representations of common social decision-making targets (parents, friends) and (ii) relate structural features of these representations to social decision behavior. This project stands to make important theoretical contributions towards social decision-making research and contribute to ongoing efforts to build unifying and generalizable models of social decision-making. Notably, because social decision-making behavior has widespread impacts—ranging from individual well-being to aggregate societal phenomena—this project could inform future efforts to promote individually and societally adaptive social decision behavior.This project will employ eminent computational methodologies to test how mental representations of real-life social partners shape social decision preferences as a function of the motivational goals and needs fulfilled by said agents. By combining multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data with natural language processing (NLP) and computational models of behavior, this project will comprehensively measure mental representations of everyday social partners and identify their relationship to social decision-making preferences. Concretely, this will involving (i) probing the neural representations of different kinds of social agents using fMRI, (ii) determining how neural representational overlap shapes social decision preferences, and (iii) use NLP tools on written content of social agents to help identify the representational content that drives differences in social decision preferences across social partners. This research will hopefully help lay the groundwork for the gradual establishment and refinement of unifying quantitative models of social decision-making, aiding both basic and applied scientific endeavors in the future.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.

该奖项是作为NSF的社会，行为和经济科学博士后研究奖学金（SPRF）计划的一部分提供的。SPRF计划的目标是为学术界，工业或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF的奖励包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在加州大学洛杉矶分校的卡罗琳·帕金森博士的赞助下，这个博士后奖学金支持一个早期的职业科学家调查社会代理人的心理表征如何影响涉及这些人的决策过程。社会决策被定义为具有直接或间接社会后果的决策，在过去二十年中受到了科学界的广泛关注。然而，现有的社会决策研究是贫困的，很少有人知道的社会目标的特点，在社会决策影响决策过程。人类代表了关于他人的大量信息，这些信息深刻地塑造了思想和行为，但我们不知道这些代表他人的动态心理模型如何影响决策偏好。事实上，社会认知心理学和神经科学的经典研究表明，表征在情境中指导行为，这表明心理表征可能在塑造社会决策偏好方面发挥重要作用。本研究旨在利用计算方法分析功能磁共振图像和文本数据，以（i）探测常见的社会决策目标（父母，朋友）的心理表征和（ii）将这些表征的结构特征与社会决策行为联系起来。该项目将为社会决策研究做出重要的理论贡献，并为建立统一和可推广的社会决策模型做出贡献。值得注意的是，因为社会决策行为具有广泛的影响--从个人的幸福到集体的社会现象--这个项目可以为未来促进个人和社会适应性社会决策行为的努力提供信息。这个项目将采用著名的计算方法来测试真实的-生活社交伙伴根据所述代理所实现的动机目标和需求来形成社交决策偏好。通过将功能性磁共振成像（fMRI）数据的多变量模式分析与自然语言处理（NLP）和行为的计算模型相结合，该项目将全面测量日常社交伙伴的心理表征，并确定其与社交决策偏好的关系。具体地说，这将涉及（i）使用功能磁共振成像探测不同类型的社会代理的神经表征，（ii）确定神经表征重叠如何塑造社会决策偏好，以及（iii）使用NLP工具对社会代理的书面内容，以帮助识别驱动社会决策偏好差异的表征内容。这项研究有望为逐步建立和完善社会决策的统一量化模型奠定基础，为未来的基础和应用科学努力提供帮助。该奖项反映了NSF的法定使命，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。