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A feature-based network analysis and fMRI meta-analysis reveal three distinct types of prosocial decisions
Social Cognitive and Affective Neuroscience ( IF 3.9 ) Pub Date : 2021-06-23 , DOI: 10.1093/scan/nsab079
Shawn A Rhoads 1 , Jo Cutler 2 , Abigail A Marsh 1
Affiliation  

Tasks that measure correlates of prosocial decision-making share one common feature: agents can make choices that increase the welfare of a beneficiary. However, prosocial decisions vary widely as a function of other task features. The diverse ways that prosociality is defined and the heterogeneity of prosocial decisions have created challenges for interpreting findings across studies and identifying their neural correlates. To overcome these challenges, we aimed to organize the prosocial decision-making task space of neuroimaging studies. We conducted a systematic search for studies in which participants made decisions to increase the welfare of others during functional magnetic resonance imaging. We identified shared and distinct features of these tasks and employed an unsupervised graph-based approach to assess how various forms of prosocial decision-making are related in terms of their low-level components (e.g. task features like potential cost to the agent or potential for reciprocity). Analyses uncovered three clusters of prosocial decisions, which we labeled as cooperation, equity and altruism. This feature-based representation of the task structure was supported by results of a neuroimaging meta-analysis that each type of prosocial decisions recruited diverging neural systems. Results clarify some of the existing heterogeneity in how prosociality is conceptualized and generate insight for future research and task paradigm development.

中文翻译:

基于特征的网络分析和 fMRI 元分析揭示了三种不同类型的亲社会决策

衡量亲社会决策相关性的任务有一个共同特征:代理人可以做出增加受益人福利的选择。然而,亲社会决策因其他任务特征而异。定义亲社会性的多种方式和亲社会决策的异质性为解释跨研究结果和确定其神经相关性带来了挑战。为了克服这些挑战,我们旨在组织神经影像学研究的亲社会决策任务空间。我们对参与者在功能性磁共振成像期间做出增加他人福利的决定的研究进行了系统搜索。我们确定了这些任务的共同和不同的特征,并采用了一种无监督的基于图的方法来评估各种形式的亲社会决策如何与其低级组件相关(例如任务特征,如代理的潜在成本或潜在的互惠)。分析揭示了三组亲社会决策,我们将其标记为合作、公平和利他主义。这种基于特征的任务结构表示得到了神经影像元分析结果的支持,每种类型的亲社会决策都招募了不同的神经系统。结果阐明了亲社会性如何被概念化的一些现有异质性,并为未来的研究和任务范式发展提供了洞察力。任务特征,例如代理的潜在成本或互惠的潜力)。分析揭示了三组亲社会决策,我们将其标记为合作、公平和利他主义。这种基于特征的任务结构表示得到了神经影像元分析结果的支持,每种类型的亲社会决策都招募了不同的神经系统。结果阐明了亲社会性如何被概念化的一些现有异质性,并为未来的研究和任务范式发展提供了洞察力。任务特征,例如代理的潜在成本或互惠的潜力)。分析揭示了三组亲社会决策,我们将其标记为合作、公平和利他主义。这种基于特征的任务结构表示得到了神经影像元分析结果的支持,每种类型的亲社会决策都招募了不同的神经系统。结果阐明了亲社会性如何被概念化的一些现有异质性,并为未来的研究和任务范式发展提供了洞察力。这种基于特征的任务结构表示得到了神经影像元分析结果的支持,每种类型的亲社会决策都招募了不同的神经系统。结果阐明了亲社会性如何被概念化的一些现有异质性,并为未来的研究和任务范式发展提供了洞察力。这种基于特征的任务结构表示得到了神经影像元分析结果的支持,每种类型的亲社会决策都招募了不同的神经系统。结果阐明了亲社会性如何被概念化的一些现有异质性,并为未来的研究和任务范式发展提供了洞察力。
更新日期:2021-06-23
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