Cognitive control and decision-making rely on the interplay of medial and lateral prefrontal cortex (mPFC/lPFC), particularly for circumstances in which correct behavior requires integrating and selecting among multiple sources of interrelated information. While the interaction between mPFC and lPFC is generally acknowledged as a crucial circuit in adaptive behavior, the nature of this interaction remains open to debate, with various proposals suggesting complementary roles in (i) signaling the need for and implementing control, (ii) identifying and selecting appropriate behavioral policies from a candidate set, and (iii) constructing behavioral schemata for performance of structured tasks. Although these proposed roles capture salient aspects of conjoint mPFC/lPFC function, none are sufficiently well-specified to provide a detailed account of the continuous interaction of the two regions during ongoing behavior. A recent computational model of mPFC and lPFC, the Hierarchical Error Representation (HER) model, places the regions within the framework of hierarchical predictive coding, and suggests how they interact during behavioral periods preceding and following salient events. In this manuscript, we extend the HER model to incorporate real-time temporal dynamics and demonstrate how the extended model is able to capture single-unit neurophysiological, behavioral, and network effects previously reported in the literature. Our results add to the wide range of results that can be accounted for by the HER model, and provide further evidence for predictive coding as a unifying framework for understanding PFC function and organization.

认知控制和决策依赖于内侧和外侧前额叶皮层 (mPFC/lPFC) 的相互作用，特别是在正确行为需要在多个相关信息源之间进行整合和选择的情况下。虽然 mPFC 和 lPFC 之间的相互作用被普遍认为是适应性行为中的关键回路，但这种相互作用的性质仍然存在争议，各种建议表明在以下方面具有互补作用：(i) 发出控制的需要并实施控制，(ii) 识别从候选集中选择适当的行为策略，以及（iii）构建用于执行结构化任务的行为模式。尽管这些提出的角色抓住了 mPFC/lPFC 联合功能的显着方面，但没有一个足够明确地详细说明两个区域在持续行为过程中的持续相互作用。最近的 mPFC 和 lPFC 计算模型，即分层错误表示 (HER) 模型，将这些区域置于分层预测编码的框架内，并建议它们在显着事件之前和之后的行为期间如何相互作用。在这篇手稿中，我们扩展了 HER 模型以纳入实时时间动态，并演示了扩展模型如何能够捕获先前文献中报道的单个单元神经生理学、行为和网络效应。我们的结果增加了 HER 模型可以解释的广泛结果，并为预测编码作为理解 PFC 功能和组织的统一框架提供了进一步的证据。