Testing a unified spectral temporal context model

记忆对人类生活至关重要，支持适应性行为和个人身份的核心方面。这个研究项目旨在更深入地了解情景记忆--或对我们生活中特定事件或情节的记忆--以及时间在其中扮演的核心角色。我们如何回忆起改变生活的重大事件，比如我们高中毕业，或者我们的婚礼，甚至是普通的日常事件，比如我们今天早上把车停在哪里？这项研究探讨了事件发生和我们回忆起该事件之间的时间长短如何影响我们记忆的各个方面。事件发生多久会影响记忆功能的多个方面，例如记忆的质量和可用性，或者其他记忆是否会干扰我们试图回忆的事件的记忆。另一个关键问题是，记忆是否可以通过额外的线索和信息来增强。本研究的目标是建立一个统一的记忆理论模型，解释时间对记忆的影响。为了建立最好的解释和预测记忆的模型，本项目旨在建立和测试一个生物现实的计算模型，结合最近的神经生理学研究结果。这些神经发现的一个重要方面是，记忆背后的表征--可以说形成了一个时间背景--在很宽的时间尺度上漂移，时间尺度是秒、分钟、小时，甚至是几天、几周、几个月和几年。计算模型模拟和复制这些行为的发现，揭示了时间背景如何影响情景记忆。另一个目标是使用来自异常长时间尺度的神经记录的经验数据来经验性地测试人类记忆表征的动态神经漂移的程度。该模型结合了神经和行为数据，这些数据揭示了这样一种现象，即我们通常可以记住一段情节的要点，但随着时间的推移，我们会忘记该情节的一些细节。最后，它已被证明，表示不仅漂移，但也突然转移事件和空间环境之间的边界。这个项目扩展了我们的努力，导致对这些行为和神经数据突然变化的后果有了更动态的理解。通过这种方式，可以更深入地了解记忆，以及它如何随着时间的推移在行为和神经水平上发生变化。更广泛地说，该项目还旨在大力增加STEM领域历史上服务不足群体的学生的参与。从这项研究中产生的知识被纳入PI大学的课程和研讨会中，并免费提供给更广泛的公众受众。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Memory is essential for human life, supporting adaptive behavior and core aspects of personal identity. This research project aims to understand more about episodic memory - or memory for specific events or episodes in our lives - and the central role that time plays in it. How do we recall significant life-changing events such as our graduation from high school, or our wedding day, or even ordinary, daily events such as where we parked our car this morning? This research probes how the amount of elapsed time between the occurrence of the event and our recollection of that event affects myriad aspects of our memory. How long ago the event occurred affects multiple aspects of memory function, such as the quality and availability of the memory or whether other memories interfere with the memory of the event we are trying to recall. Another key question is whether memory can be enhanced with additional cues and information. The goal of this research is to develop a unified theoretical model of memory, that accounts for the many effects of time in shaping our memories.In order to develop the best explanatory and predictive model of memory, this project aims to create and test such an account in the form of a biologically realistic computational model that incorporates recent findings on the neurophysiology of memory systems. An essential aspect to these neural findings is that representations underlying memory - which might be said to form a temporal context - drift over a wide spectrum of time scales, on the order of seconds, minutes, hours, or even days to weeks to months and years. The computational model simulates and replicates these behavioral findings that reveal how temporal context affects episodic memory. An additional goal is to use empirical data from neural recordings over unusually long-time scales to empirically test the extent of dynamic neural drift of memory representations in humans. The model incorporates neural and behavioral data that sheds light on the phenomena that we can often remember the gist of an episode, but over time will forget some of the details of that episode. Finally, it has been shown that representations not only drift, but also suddenly shift at boundaries between events and spatial environments. This project expands our efforts, leading to a more dynamic understanding of the consequences of these sudden shifts both behaviorally and in neural data. In this way, it is possible to achieve a deeper understanding of memory, and how it changes at a behavioral and neural level over time. More broadly, this project also aims to strongly increase the participation of students from historically underserved groups in STEM fields. Knowledge generated from this research is incorporated into courses and workshops at the PIs’ university and made freely available for a broader public audience.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.