The Nature of Working Memory Representations
The Nature of Working Memory Representations
批准号:
10677812
负责人:
CLAYTON E CURTIS
金额:
$39.41万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2026-08-31
关键词:
AreaBehaviorBrainClinicalCodeCognitionCognitive remediationDataData AnalyticsDecision MakingDiagnosisDimensionsElderlyEvolutionFunctional disorderGoalsHumanImpaired cognitionKnowledgeLearningLeftMapsMeasuresMemoryMemory impairmentMental disordersMissionModelingMotionNatureNeurologicNeurosciences ResearchOutcomePathologicPatternPopulationPopulation DynamicsPropertyPsychiatric therapeutic procedurePublic HealthReadingResearchResearch PersonnelResistanceSensoryShort-Term MemoryStimulusSymptomsTechniquesTestingTimeUnited States National Institutes of HealthVisualVisual CortexVisualizationWorkcognitive functiondistractionexperimental studyinnovationinsightmemory retentionnervous system disorderneuralneural modelneural patterningneuroimagingneuromechanismnovelreceptive fieldretinal stimulationretinotopicstemsuccesstheoriesvisual stimulus
中文摘要
项目摘要
由于大多数高级认知依赖于工作记忆(WM),而它的功能障碍导致了许多
认知障碍,研究人员花了几十年的时间试图了解神经机制,
支持WM。最近,研究人员使用复杂的计算神经成像方法,
在广泛分布的大脑中,
地区例如,在早期视觉皮层中,WM表征的格式可能具有相同的“感觉-
像”属性作为视觉刺激。虽然感觉类表征在高级大脑中不太可能
在这些领域,这些替代表示的性质仍然是不可渗透的。我们知识上的差距
是一个关键的问题,因为许多精神和神经系统疾病源于原发性WM
功能障碍我们的长期目标是了解大脑中的神经群
编码WM表征,以及我们如何制定策略来缓解影响WM表征的WM问题。
认知质量。我们的总体假设是,一个人在WM中看到的和储存的东西可以是不同的,
这种区别在不同的皮层层级中是不同的。该项目的中心目标是开发深刻的数据
分析方法将揭示神经群体中实际编码的性质
WM存储的潜在动力学。拟议研究的基本原理是,随着我们更好地了解
工作记忆的神经机制,一个强大的理论框架将出现,其中的理解策略
和治疗认知功能障碍的方法将会出现。我们通过追求两个具体目标来检验我们的中心假设。第一章
我们将对编码WM表征的不同格式的神经种群动力学进行建模。2)我们将
识别神经群体何时何地编码作为感觉抽象的WM表征
功能.强有力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,神经群体编码
对于所记忆的刺激的表示和
任务相关。在目标2下,使用新的方法来建模和可视化WM表征揭示了神经
传统上被认为在WM中编码视觉刺激特征的人群也存储抽象,
与原始视觉刺激几乎没有相似之处。总的来说,拟议的工作将产生数据,
需要揭开大脑皮层层级中工作记忆的表征形式。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的代表性
WM格式的方式尚未应用于神经影像学。这项拟议的研究意义重大,因为
它将提供关键的洞察到本质的WM表示在人类大脑中,除了提供新的
在精神病、神经病和老年人群中的认知补救目标。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
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依托单位:
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