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.

项目概要 因为大多数高级认知依赖于工作记忆（WM），其功能障碍会导致许多 研究人员花了几十年的时间试图了解认知障碍的神经机制 最近，研究人员使用复杂的计算神经成像方法 根据广泛分布的大脑中的神经活动模式反复解码 WM 的内容 例如，早期视觉皮层中 WM 表示的格式可能具有相同的“感觉- 尽管在高阶大脑中不太可能出现类似感觉的表征。 领域中，这些替代表征的本质仍然是我们知识中难以理解的。 这是一个严重的问题，因为许多精神和神经系统疾病都源于原发性 WM 我们的长期目标是了解大脑神经群的机制。 对 WM 表示进行编码，以及我们如何制定策略来减轻影响 WM 的问题 我们的总体假设是，人们在 WM 中看到的内容和存储的内容可能是截然不同的。 这种区别在整个皮质层次中是不同的。该项目的中心目标是开发深入的数据。 分析方法将揭示神经群体中实际编码内容的本质 拟议研究的基本原理是，随着我们更好地理解 WM 存储的动态。 WM 的神经机制，一个强大的理论框架将出现，其中理解策略 我们将通过追求两个具体目标来检验我们的中心假设：1）。 我们将对编码不同格式的 WM 表示的神经群体动态进行建模 2) 我们将。 识别神经群体何时何地编码 WM 表征（感官抽象） 强有力的初步数据证明了拟议工作的可行性以及对项目的初步支持。 在目标 1 下，使用新颖的降维技术表明神经群体编码。 对于记忆刺激的表示和特定刺激特征的表示 在目标 2 下，使用新颖的方法来建模和可视化 WM 表示揭示了神经网络 传统上被认为在 WM 中编码视觉刺激特征的群体也存储了抽象 总体而言，拟议的工作将生成数据。 需要揭示大脑皮层层次结构中 WM 的表征格式，该方法是创新的。 因为它使用直接且无偏见的计算方法来建模和可视化代表性 WM 的格式尚未应用于神经影像学，因此这项研究意义重大。 除了提供新的知识之外，它还将提供对人脑中 WM 表征本质的重要见解。 精神病学、神经学和老年人群认知矫正的目标。