研究人员在受试者执行涉及三种认知冲突的两项任务时，记录了人类内侧额叶皮层的单个神经元。编码冲突概率、冲突和一个或两个任务中的错误的神经元混合在一起，形成一个表征几何，同时允许任务的特化和通用化。编码冲突的神经元回顾性地用于更新冲突概率的内部估计。冲突的群体表征是组成性的。这些发现揭示了评价性信号的表征如何既抽象又具有任务特异性，并提出了一种估计控制需求的神经元机制。
据悉，控制行为以灵活地实现预期目标，取决于监测自身表现的能力。目前还不知道绩效监测如何既能灵活地支持不同的任务，又能特化地很好地完成每项任务。
附：英文原文
Title: The geometry of domain-general performance monitoring in the human medial frontal cortex
Author: Zhongzheng Fu, Danielle Beam, Jeffrey M. Chung, Chrystal M. Reed, Adam N. Mamelak, Ralph Adolphs, Ueli Rutishauser
Issue&Volume: 2022-05-06
Abstract: Controlling behavior to flexibly achieve desired goals depends on the ability to monitor one’s own performance. It is unknown how performance monitoring can be both flexible, to support different tasks, and specialized, to perform each task well. We recorded single neurons in the human medial frontal cortex while subjects performed two tasks that involve three types of cognitive conflict. Neurons encoding conflict probability, conflict, and error in one or both tasks were intermixed, forming a representational geometry that simultaneously allowed task specialization and generalization. Neurons encoding conflict retrospectively served to update internal estimates of conflict probability. Population representations of conflict were compositional. These findings reveal how representations of evaluative signals can be both abstract and task-specific and suggest a neuronal mechanism for estimating control demand.
DOI: abm9922
Source: https://www.science.org/doi/10.1126/science.abm9922