Fear memory attenuation: testing reconsolidation-extinction boundaries

描述（由申请人提供）：夸大或持续的恐惧是精神疾病的常见现象。尽管通过巴甫洛夫条件反射的研究，在揭示恐惧学习的神经基础方面取得了很大进展，但如何在病理病例中减少或消除创伤记忆却知之甚少，这是临床非常关注的问题。我们最近设计了一种新的行为模式，可以减弱并防止恐惧记忆的回归。我们的研究结果表明，对一种常用的临床治疗方法（暴露疗法）进行细微的修改可以极大地改善结果，并减少创伤后应激障碍或特定恐惧症患者复发的可能性。与此同时，在我们的合作者实验室（普林斯顿大学的Yael Niv博士）开发的一个新的计算模型为我们的结果提供了一个原则性的解释，并将有助于生成可测试的预测，以完善我们的协议，并更好地理解持续更新恐惧记忆的机制。在拟议的研究中，我们将首先使用计算导出的预测来完善我们的协议。接下来，我们将测试这种优化方案的局限性，并检查它是否可以用于针对更强、更老、更复杂的恐惧记忆，希望它最终可以用于减轻临床人群的创伤记忆。

DESCRIPTION (provided by applicant): Exaggerated or persistent fear is a common occurrence in psychiatric disorders. Although much progress has been made in uncovering the neural basis of fear learning through studies of Pavlovian conditioning, little is known about how to reduce or eliminate traumatic memories in pathological cases, which is of great clinical concern. We have recently devised a novel behavioral paradigm that attenuates and prevents the return of fear memories. Our results indicate that subtle modifications to a commonly employed clinical treatment (exposure therapy) could greatly improve outcome, and reduce the potential for relapse in individuals suffering from post-traumatic stress disorder or specific phobias. In parallel, a new computational model developed in our collaborator's lab (Dr. Yael Niv, at Princeton University) provides a principled explanation for our results, and will help generate testable predictions to refine our protocol, and better understand the mechanisms that underlie the persistent updating of fear memories. In the proposed studies, we will first refine our protocol using computationally-derived predictions. Next, we will test the limits of this optimized protocol, and examine whether it may be used to target stronger, older, and more complex fear memories, with the hopes that it may eventually be employed to attenuate traumatic memories in clinical populations.