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.

项目总结 因为大多数高级认知依赖于工作记忆(WM)，其功能障碍导致大量 认知障碍，研究人员花了几十年的时间试图了解 支持WM。最近，研究人员使用复杂的计算神经成像方法 反复从广泛分布的大脑中神经活动的模式中解码WM的内容 区域。例如，早期视觉皮质中WM表征的形式可能具有相同的“感觉-- 就像“作为视觉刺激的属性。尽管在高级大脑中，类似感觉的表征不太可能发生 在这些地区，这些替代代表的性质仍然令人费解。我们知识中的这一鸿沟 是一个严重的问题，因为许多精神和神经障碍源于原发的WM 功能障碍。我们的长期目标是了解大脑中的神经细胞群体 对WM表示进行编码，以及我们如何制定策略来缓解影响 认知质量。我们的总体假设是，一个人在WM中看到的和存储的可以是截然不同的 这种区别在大脑皮层的不同层次上是不同的。该项目的中心目标是开发精辟的数据 将揭示神经种群中实际编码的内容的性质的分析方法 WM存储的基础动态。建议进行研究的理由是，随着我们更好地了解 WM的神经机制，将出现一个强大的理论框架，在其中将策略理解 治疗认知功能障碍将会出现。我们通过追求两个具体目标来检验我们的中心假设。1) 我们将对不同格式的WM表示进行编码的神经种群动态进行建模。2)我们会 识别神经群体何时何地编码WM表示，这些表示是感觉的抽象 功能。强劲的初步数据证明了拟议工作的可行性，以及对 假设。在目标1下，使用新的降维技术表明，神经种群编码 对于记忆的刺激的表示和特定刺激特征的表示， 与任务相关。在目标2下，使用新的方法对工作记忆表征进行建模和可视化显示，神经 传统上被认为在WM中编码视觉刺激特征的群体也存储着 与最初的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 需要揭开大脑皮质层次中WM的表征格式的面纱。这种方法是创新的 因为它使用直接和无偏见的计算方法来建模和可视化代表性的 WM的格式以尚未在神经成像中应用的方式。这项拟议的研究具有重要意义，因为 它将提供对人类大脑中WM表示的性质的关键洞察，除了提供新的 精神病学、神经病学和老年人群认知矫正的目标。