High-resolution multimodal imaging of episodic memory networks in aging.

衰老过程中情景记忆网络的高分辨率多模态成像。

基本信息

项目摘要

DESCRIPTION (provided by applicant): The training and research plan proposed in this Pathway to Independence Award will propel the candidate to become an independent scientist in a tenure-track position at a research university. This award will support her investigation of novel questions regarding structural connectivity of neural networks that subserve episodic memory across the lifespan. She will be introduced to high-resolution multimodal neuroimaging and will receive training in corresponding advanced MRI and multivariate analysis techniques. The candidate's expertise in neurocognitive aging research will also be strengthened by the proposal's focus on component processes of episodic memory (i.e., pattern separation), the neural networks that support these processes, and how they are affected in both healthy aging and in individuals at increased risk for dementia. Importantly, this award will prepare the candidate to submit a major research proposal (e.g., R01) at an earlier stage in her career that would be possible otherwise. Environment. The University of California, Irvine (UCI) offers a unique array of training and development resources to facilitate the candidate advancing to an independent scientist position. These include a collaborative group of distinguished researchers at the Center for the Neurobiology of Learning and Memory (CNLM) dedicated to understanding neural mechanisms that support memory, an exceptional mentor (Dr. Craig Stark, Director of the CNLM) and co-mentor (Dr. Claudia Kawas, Clinical Core director of the UCI Institute for Memory Impairments and Neurological Disorders) whose pioneering research programs laid the foundation for the current proposal, access to state-of-the-art research and neuroimaging facilities, and a variety of courses and workshops that will accelerate both educational and career development throughout the duration of this award. Research. The central aim of the current proposal is to investigate neural networks of pattern separation, a component process of episodic memory, across the life span using behavioral and high- resolution multimodal neuroimaging techniques. Episodic memory decline is a hallmark feature of healthy aging and age-related cognitive disorders such as amnestic mild cognitive impairment and Alzheimer's disease. Further detailing the neural mechanisms that support component processes of episodic memory may facilitate identification of neural markers associated with cognitive aging, and inform cognitive and neural interventions aimed at promoting successful aging. Episodic memory is a complex mnemonic ability that involves encoding and retrieval of discrete events, including details such as what, where, and when an event occurred. Successful encoding of new information requires that similar events get separated into distinct memory representations. This process, termed pattern separation, is known to rely on medial temporal lobe (MTL) subregions. However, neuroimaging studies have shown that prefrontal cortex (PFC) and striatum are also engaged during episodic memory performance. Whereas these distributed brain regions are frequently studied in isolation, a comprehensive understanding of the neural substrates of episodic memory in general, and pattern separation in particular, will require knowledge of how they interact as interconnected neural networks. In the mentored phase of this award, high-resolution diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) will be used to identify more accurate models of MTL (Specific Aim 1) and striatal (Specific Aim 2) connectivity across the human lifespan than has been previously acquired in vivo. Expanding on our earlier work with the perforate path, the proposed study will assess the contribution of local tracts connecting MTL subregions (e.g., perforate path, mossy fibers, and schaffer collaterals) and large-scale tracts connecting MTL to PFC (e.g., fornix, cingulum) to pattern separation performance in healthy adults. It will also be the first to examine integrity of tracts connecting striatum to PFC (e.g., caudate-PFC, putamen-motor) in relation to these mnemonic processes. The independent phase of this award will assess interactions and dissociations between MTL and striatal memory systems, which are frequently regarded as being differentially affected by healthy and pathological aging. We will test the hypotheses that degradation of striatal versus MTL tract integrity accounts for pattern separation declines in healthy older versus younger adults (Specific Aim 2) and that degradation of MTL versus striatal tract connectivity accounts for pattern separation declines in oldest- old versus younger-old adults (Specific Aim 3). These data will directly test cortical disconnection theories, which propose that diminished white matter connectivity accounts for cognitive declines associated with aging.
描述(由申请人提供):独立之路奖提出的培训和研究计划将推动候选人成为研究型大学终身职位的独立科学家。该奖项将支持她对神经网络结构连通性的新问题的研究,这些神经网络在整个生命周期中为情景记忆提供服务。她将被介绍高分辨率多模态神经成像,并将接受相应的高级MRI和多变量分析技术的培训。候选人在神经认知衰老研究方面的专业知识也将得到加强,该提案将重点关注情景记忆的组成过程(即模式分离),支持这些过程的神经网络,以及它们如何在健康老龄化和痴呆症风险增加的个体中受到影响。重要的是,该奖项将使候选人在其职业生涯的早期阶段提交一项重大研究计划(例如R01),否则可能会这样做。环境。加州大学欧文分校(UCI)提供一系列独特的培训和发展资源,以促进候选人晋升为独立的科学家职位。其中包括学习与记忆神经生物学中心(CNLM)的杰出研究人员组成的合作小组,他们致力于理解支持记忆的神经机制,一位杰出的导师(CNLM主任Craig Stark博士)和共同导师(UCI记忆障碍和神经疾病研究所临床核心主任Claudia Kawas博士),他们的开创性研究项目为当前的提案奠定了基础。获得最先进的研究和神经成像设施,以及各种课程和研讨会,这些课程和研讨会将在整个奖项期间加速教育和职业发展。研究。当前建议的中心目标是研究模式分离的神经网络,情景记忆的一个组成过程,在整个生命周期中使用行为和高分辨率多模态神经成像技术。情景记忆衰退是健康老龄化和与年龄相关的认知障碍(如遗忘性轻度认知障碍和阿尔茨海默病)的标志性特征。进一步阐明支持情景记忆组成过程的神经机制可能有助于识别与认知衰老相关的神经标记,并为旨在促进成功衰老的认知和神经干预提供信息。情景记忆是一种复杂的助记能力,涉及对离散事件的编码和检索,包括事件发生的内容、地点和时间等细节。新信息的成功编码需要将相似的事件分离到不同的记忆表征中。这个过程被称为模式分离,已知依赖于内侧颞叶(MTL)亚区。然而,神经影像学研究表明,前额叶皮层(PFC)和纹状体也参与情景记忆的表现。尽管这些分布的大脑区域经常被孤立地研究,但要全面了解情景记忆的神经基质,特别是模式分离,将需要了解它们如何作为相互关联的神经网络相互作用。在该合同的指导阶段,高分辨率弥散张量成像(DTI)和功能性磁共振成像(fMRI)将用于识别更准确的MTL (Specific Aim 1)和纹状体(Specific Aim 2)贯穿人类生命周期的连接模型,而不是之前在体内获得的模型。在我们早期穿孔路径研究的基础上,本研究将评估连接MTL亚区(如穿孔路径、苔藓纤维和schaffer侧枝)的局部束和连接MTL到PFC的大尺度束(如穹窿、扣带)对健康成人模式分离性能的贡献。它也将是第一个被检验的

项目成果

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Ilana Jacqueline Bennett其他文献

Ilana Jacqueline Bennett的其他文献

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{{ truncateString('Ilana Jacqueline Bennett', 18)}}的其他基金

MRI biomarkers of glial-specific metabolites and microstructure in aging
衰老过程中神经胶质特异性代谢物和微观结构的 MRI 生物标志物
  • 批准号:
    10742593
  • 财政年份:
    2023
  • 资助金额:
    $ 25.55万
  • 项目类别:
High-resolution multimodal imaging of episodic memory networks in aging.
衰老过程中情景记忆网络的高分辨率多模态成像。
  • 批准号:
    9352898
  • 财政年份:
    2016
  • 资助金额:
    $ 25.55万
  • 项目类别:
High-resolution multimodal imaging of episodic memory networks in aging.
衰老过程中情景记忆网络的高分辨率多模态成像。
  • 批准号:
    8826006
  • 财政年份:
    2014
  • 资助金额:
    $ 25.55万
  • 项目类别:
The role of white matter integrity in the neural efficiency hypothesis of cogniti
白质完整性在认知神经效率假说中的作用
  • 批准号:
    8060228
  • 财政年份:
    2010
  • 资助金额:
    $ 25.55万
  • 项目类别:
The role of white matter integrity in neural efficiency and cognitive aging
白质完整性在神经效率和认知衰老中的作用
  • 批准号:
    8210353
  • 财政年份:
    2010
  • 资助金额:
    $ 25.55万
  • 项目类别:
Aging, implicit learning, and white matter integrity
衰老、内隐学习和白质完整性
  • 批准号:
    7637355
  • 财政年份:
    2007
  • 资助金额:
    $ 25.55万
  • 项目类别:
Aging, implicit learning, and white matter integrity
衰老、内隐学习和白质完整性
  • 批准号:
    7330885
  • 财政年份:
    2007
  • 资助金额:
    $ 25.55万
  • 项目类别:

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