Long-term consequences of visual working memory

项目摘要 记忆信息的能力，无论是在短时间还是长时间延迟之后，都是人类的一项基本能力。的确有 对孤立地理解工作记忆和长期记忆的大量研究，但也是一个 关于工作记忆和长期记忆之间相互作用的争论由来已久。这项研究 提案将通过调查和剖析门户假说来解决关键的知识缺口，以 描述工作记忆延迟活动如何预测以后记住什么信息，以及如何建立大脑- 计算机界面利用对工作记忆的实时洞察延迟活动来改变后来的记忆。一个 更好地了解工作记忆和长期记忆是如何相互作用的，将对众多 以这些系统的缺陷为特征的精神障碍。最近的实证研究表明 揭示了工作记忆容量和长期记忆之间的联系，但有多个子过程 在工作记忆中保持多个项目是基础。例如，有相应的神经信号 工作记忆中的项目数，以及与空间位置相对应的不同神经特征 工作记忆中的项目。这两个子过程中的一个或两个，数量和位置，可以预测长期 记忆。我将使用多变量解码和时间分辨神经科学技术，EEG(AIM 1)和颅内脑电(AIM 2)来描述这些工作记忆的子过程及其与 长期记忆。然后，作为一名独立调查员，我将构建能够实时跟踪延误活动的工具 根据工作记忆项目的数量和位置，适时地设计实验。这 将对工作记忆和长期记忆之间的关系进行详细而具体的概念化测试 记忆。这项研究计划的研究和培训目标将由一个顾问团队 芝加哥大学和加州大学伯克利分校的认知、系统和临床神经学家。这项研究 建议包括通常孤立的认知过程(工作记忆和长期记忆)， 互补的时间分辨方法(EEG和iEEG)和计算复杂的多变量 能够敏感地解码工作记忆中的信息的分析。最后，这项研究建议将 开发创新的实时工具来跟踪记住的信息并预测未来的长期记忆 性能。这项研究提案的短期目标是开发一个复合模型，说明如何区分 工作记忆延迟活动的每时每刻的子过程可以预测长期记忆的结果。这 将为工作记忆和长期记忆之间的关系提供新的见解。长期的 我的研究计划的目标是全面描述影响我们 记住，为了构建能够增强记忆力的工具。

Project Summary The ability to remember information, whether after short or long delays, is a fundamental human ability. There is enormous research into understanding working memory and long-term memory in isolation, but also a longstanding debate about the interactions between working memory and long-term memory. This research proposal would address a critical knowledge gap by investigating and dissecting the gateway hypothesis, to characterize how working memory delay activity predicts what information is later remembered and to build brain- computer interfaces that leverage real-time insight into working memory delay activity to alter later memory. A better understanding how working memory and long-term memory interact would be beneficial for the numerous psychiatric disorders which are characterized by deficits in these systems. Recent empirical research has revealed links between working memory capacity and long-term memory, however multiple sub-processes underlie maintaining multiple items in working memory. For example, there are neural signatures that correspond to the number of items in working memory, and distinct neural signatures that correspond to the spatial locations of items in working memory. Either or both of those sub-processes, number and location, could predict long-term memory. I will use multivariate decoding in conjunction with time resolved neuroscience techniques, EEG (Aim 1) and intracranial EEG (Aim 2) to characterize these working memory sub-processes and their relationship to long-term memory. Then, as an independent investigator, I will build tools that can track delay activity in real time and adaptively design experiments contingent to the number and location of items of working memory. This will test a detailed and specific conceptualization of the relationship between working memory and long-term memory. The research and training goals of this research proposal will be furthered by an advising team of cognitive, systems, and clinical neuroscientists at the University of Chicago and UC Berkeley. This research proposal encompasses cognitive processes that are often siloed (working memory and long-term memory), complementary temporally resolved methods (EEG and iEEG), and computationally sophisticated multivariate analyses capable of sensitively decoding information in working memory. Finally, this research proposal will develop innovative real-time tools to track information held in mind and forecast future long-term memory performance. The short-term goal of this research proposal is to develop a composite model of how distinct moment-by-moment subprocesses of working memory delay activity predict long-term memory outcome. This will provide new insights into the relationship between working memory and long-term memory. The long-term goal for my research program is to comprehensively characterize the diverse factors that influence what we remember, in order to build tools that can enhance memory.