Post-traumatic stress disorder (PTSD) is characterized by altered emotional and behavioral responding following a traumatic event. In this article, we review the concepts of latent-state and model-based learning (i.e., learning and inferring abstract task representations) and discuss their relevance for clinical and neuroscience models of PTSD. Recent data demonstrate evidence for brain and behavioral biases in these learning processes in PTSD. These new data potentially recast excessive fear towards trauma cues as a problem in learning and updating abstract task representations, as opposed to traditional conceptualizations focused on stimulus-specific learning. Biases in latent-state and model-based learning may also be a common mechanism targeted in common therapies for PTSD. We highlight key knowledge gaps that need to be addressed to further elaborate how latent-state learning and its associated neurocircuitry mechanisms function in PTSD and how to optimize treatments to target these processes.

创伤后应激障碍（PTSD）的特点是创伤事件后情绪和行为反应的改变。在本文中，我们回顾了潜在状态和基于模型的学习（即学习和推断抽象任务表示）的概念，并讨论了它们与 PTSD 临床和神经科学模型的相关性。最近的数据证明了 PTSD 学习过程中大脑和行为偏差的证据。这些新数据可能会将对创伤线索的过度恐惧重新定义为学习和更新抽象任务表征的问题，而不是专注于特定刺激学习的传统概念化。潜在状态和基于模型的学习的偏差也可能是 PTSD 常见疗法的常见机制。我们强调了需要解决的关键知识差距，以进一步阐述潜态学习及其相关的神经回路机制如何在 PTSD 中发挥作用，以及如何优化治疗以针对这些过程。