Latent-cause inference is the process of identifying features of the environment that have caused an outcome. This problem is especially important in social settings where individuals may not make equal contributions to the outcomes they achieve together. Here, we designed a novel task in which participants inferred which of two characters was more likely to have been responsible for outcomes achieved by working together. Using computational modeling, univariate and multivariate analysis of human fMRI, and continuous theta-burst stimulation, we identified two brain regions that solved the task. Notably, as each outcome occurred, it was possible to decode the inference of its cause (the responsible character) from hippocampal activity. Activity in dorsomedial prefrontal cortex (dmPFC) updated estimates of association between cause—responsible character—and the outcome. Disruption of dmPFC activity impaired participants’ ability to update their estimate as a function of inferred responsibility but spared their ability to infer responsibility.

中文翻译：

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人类海马体和背内侧前额叶皮层在社交互动中推断和更新潜在原因


潜在原因推理是识别导致结果的环境特征的过程。这个问题在社会环境中尤为重要，因为个人可能无法对他们共同实现的结果做出同等贡献。在这里，我们设计了一项新颖的任务，参与者推断两个角色中的哪一个更有可能对合作取得的结果负责。使用计算建模、人类 fMRI 的单变量和多变量分析以及连续 θ 爆发刺激，我们确定了解决该任务的两个大脑区域。值得注意的是，当每个结果发生时，可以从海马活动中解码其原因（负责特征）的推断。背内侧前额叶皮层 （dmPFC） 的活动更新了对原因 - 负责特征 - 与结果之间关联的估计。dmPFC 活动的中断损害了参与者根据推断责任更新其估计的能力，但保留了他们推断责任的能力。