The Nature of Working Memory Representations

工作记忆表征的本质

• 批准号: 10677812
• 负责人: CLAYTON E CURTIS
• 金额: $ 39.41万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10677812
• 关键词: Area; Behavior; Brain; Clinical; Code; Cognition; Cognitive remediation; Data; Data Analytics; Decision Making; Diagnosis; Dimensions; Elderly; Evolution; Functional disorder; Goals; Human; Impaired cognition; Knowledge; Learning; Left; Maps; Measures; Memory; Memory impairment; Mental disorders; Mission; Modeling; Motion; Nature; Neurologic; Neurosciences Research; Outcome; Pathologic; Pattern; Population; Population Dynamics; Property; Psychiatric therapeutic procedure; Public Health; Reading; Research; Research Personnel; Resistance; Sensory; Short-Term Memory; Stimulus; Symptoms; Techniques; Testing; Time; United States National Institutes of Health; Visual; Visual Cortex; Visualization; Work; cognitive function; distraction; experimental study; innovation; insight; memory retention; nervous system disorder; neural; neural model; neural patterning; neuroimaging; neuromechanism; novel; receptive field; retinal stimulation; retinotopic; stem; success; theories; visual stimulus

PROJECT SUMMARY Because most high-level cognition depends on working memory (WM) and its dysfunction causes a host of cognitive impairments, researchers have spent decades trying to understand the neural mechanisms that support WM. Recently, using sophisticated computational neuroimaging approaches researchers have repeatedly decoded the contents of WM from patterns of neural activity in a widely distributed number of brain areas. The format of the WM representation in early visual cortex, for instance, might have the same “sensory- like” properties as the visual stimulus. Although sensory-like representations are less likely in higher-order brain areas, the nature of these alternative representations has yet remained impenetrable. This gap in our knowledge is a critical problem because a host of psychiatric and neurologic disorders stems from a primary WM dysfunction. Our long-term goal is to understand the mechanisms by which neural populations across the brain encode WM representations, and how we might develop strategies to mitigate WM problems that impact the quality of cognition. Our overall hypothesis is that what one sees and what one stores in WM can be distinct and that distinction differs across the cortical hierarchy. The central aim of the project is to develop incisive data analytic approaches that will reveal the nature of what is actually being encoded in the neural population dynamics underlying WM storage. The rationale for the proposed research is that as we better understand the neural mechanisms of WM, a strong theoretical framework will emerge within which strategies for understanding and treating cognitive dysfunction will emerge. We test our central hypothesis by pursuing two specific aims. 1) We will model the neural population dynamics that code for distinct formats of WM representations. 2) We will identify when and where neural populations encode WM representations that are abstractions of sensory features. Strong preliminary data demonstrate the feasibility of proposed work as well as initial support for the hypotheses. Under Aim 1, using novel dimensionality reduction techniques suggest that neural populations code for both a representation of the memorized stimulus and a representation of the specific stimulus feature that is task relevant. Under Aim 2, using novel means to model and visualize WM representations revealed that neural populations that are traditionally thought to encode visual stimulus features in WM also store abstractions that can bear little resemblance to the original visual stimulus. Overall, the proposed work will generate the data needed to unmask the representational format of WM across the cortical hierarchy. The approach is innovative because it uses direct and unbiased computational approaches to model and visualize the representational format of WM in ways that have not been applied in neuroimaging. The proposed research is significant because it will provide key insights into the nature of WM representations in the human brain, in addition to providing new targets for cognitive remediation in psychiatric, neurologic, and geriatric populations.

项目摘要 因为大多数高级认知取决于工作记忆（WM）及其功能障碍会导致许多人 认知障碍，研究人员花了数十年的时间试图了解神经机制 支持Wm。最近，使用复杂的计算神经影像学方法研究人员 反复从神经活动的模式中反复解码了大脑数量的神经活动模式 区域。例如，早期视觉皮层中WM表示的格式可能具有相同的“感觉” 像“视觉刺激”的属性。尽管在高阶大脑中，类似感觉的表示的可能性较小 这些替代表示的区域，尚未无法穿透。根据我们的差距 是一个关键的问题，因为一系列精神病和神经系统疾病从主要WM逐步 功能障碍。我们的长期目标是了解神经跨大脑的机制 编码WM表示形式，以及我们如何制定策略来减轻影响影响的WM问题 认知质量。我们的总体假设是，WM中的一个人看到的以及一个人可能是不同的，并且 这种差异在整个皮质层次结构上有所不同。该项目的核心目的是开发敏锐的数据 分析方法将揭示神经种群实际上正在编码的内容的性质 WM存储的动力学。拟议研究的理由是，我们更好地了解 WM的神经机制，将出现一个强大的理论框架，以理解理解的策略 并且会出现治疗认知功能障碍。我们通过追求两个具体目标来检验中心假设。 1） 我们将建模为WM表示的不同格式编码的神经种群动态。 2）我们会的 确定神经群体在何时何地编码为感觉的抽象的WM表示 特征。强大的初步数据证明了提议的工作的可行性以及对 假设。在AIM 1下，使用新颖的维度降低技术表明神经种群代码 对于记忆刺激的表示和特定刺激特征的表示 任务相关。在AIM 2下，使用新颖的手段对WM表示建模和可视化表明中性 传统上被认为编码WM中的视觉刺激特征的人群也存储了抽象 与原始视觉刺激几乎没有相似之处。总体而言，拟议的工作将生成数据 需要揭示整个皮质层次结构的WM的代表性格式。这种方法是创新的 因为它使用直接和公正的计算方法来建模和可视化表示 WM的格式未应用于神经影像。拟议的研究很重要，因为 除了提供新的外，它还将为人脑中WM表示的性质提供关键的见解 在精神病，神经系统和老年群体中认知修复的靶标。