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
• 负责人: Ilana Jacqueline Bennett
• 金额: $ 10.56万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8826006
• 关键词: Accounting; Address; Adult; Affect; Aged, 80 and over; Aging; Alzheimer' s Disease; Amyloid; Award; Behavioral; Biological Markers; Biological Neural Networks; Brain; Brain region; California; Clinical; Cognition; Cognitive; Cognitive aging; Complex; Corpus striatum structure; Data; Data Set; Dementia; Diffusion Magnetic Resonance Imaging; Dissociation; Educational workshop; Elderly; Environment; Episodic memory; Event; Foundations; Functional Magnetic Resonance Imaging; Genotype; Goals; Health; Hippocampus (Brain); Human; Impaired cognition; Individual; Institutes; Intervention; Investigation; Knowledge; Learning; Longevity; Magnetic Resonance Imaging; Medial; Mediating; Memory; Memory Loss; Memory impairment; Mentors; Modeling; Motor; Multimodal Imaging; Multivariate Analysis; Neuroanatomy; Neurobiology; Neurocognitive; Pathway interactions; Pattern; Perforant Pathway; Performance; Pharmaceutical Preparations; Phase; Population; Positioning Attribute; Positron-Emission Tomography; Prefrontal Cortex; Process; Research; Research Personnel; Research Proposals; Research Training; Resolution; Resource Development; Retrieval; Risk; Sampling; Scientist; Staging; Structure; System; Techniques; Temporal Lobe; Testing; Training; Universities; Work; age effect; age group; age related; age related cognitive disorder; base; career; career development; healthy aging; in vivo; indexing; interest; memory encoding; mild cognitive impairment; mossy fiber; nervous system disorder; network architecture; neuroimaging; neuromechanism; novel; pathological aging; programs; putamen; relating to nervous system; theories; white matter; young adult

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）：在这个独立之路奖提出的培训和研究计划将推动候选人成为一个独立的科学家在研究型大学的终身职位。该奖项将支持她对有关神经网络结构连接的新问题的研究，这些问题有助于整个生命周期的情景记忆。她将被介绍给高分辨率多模态神经成像，并将接受相应的先进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通过该提案对情景记忆组成过程的关注而得到加强（即，模式分离），支持这些过程的神经网络，以及它们在健康老龄化和痴呆症风险增加的个体中如何受到影响。重要的是，这个奖项将准备候选人提交一个重大的研究计划（例如，R 01）在她职业生涯的早期阶段，否则是可能的。 环境加州大学欧文分校（UCI）提供了一系列独特的培训和发展资源，以促进候选人晋升为独立科学家。其中包括一个由学习和记忆神经生物学中心（CNLM）的杰出研究人员组成的合作小组，他们致力于了解支持记忆的神经机制，（克雷格斯塔克博士，CNLM主任）和共同导师（克劳迪娅·卡瓦斯博士，UCI记忆障碍和神经障碍研究所临床核心主任）其开创性的研究项目为当前的提案奠定了基础，获得了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。 Research.目前建议的中心目标是使用行为和高分辨率多模态神经成像技术在整个生命周期中研究模式分离的神经网络，这是情景记忆的一个组成过程。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。进一步详细说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老化相关的神经标志物，并为旨在促进成功老化的认知和神经干预提供信息。情节记忆是一种复杂的记忆能力，涉及离散事件的编码和检索，包括事件发生的细节，如什么，在哪里和什么时候。新信息的成功编码要求相似的事件被分离成不同的记忆表征。这个过程称为模式分离，已知依赖于内侧颞叶（MTL）子区域。然而，神经影像学研究表明，前额叶皮层（PFC）和纹状体也参与情节记忆的表现。虽然这些分散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础，特别是模式分离，就需要了解它们如何作为相互连接的神经网络相互作用。在该奖项的指导阶段，高分辨率弥散张量成像（DTI）和功能性磁共振成像（fMRI）将用于识别人类寿命期间MTL（特定目标1）和纹状体（特定目标2）连接的更准确模型，而不是以前在体内获得的模型。在我们早期的研究工作的基础上，拟议的研究将评估连接MTL次区域的地方区域的贡献（例如，纤维束、苔藓纤维和谢弗侧支）和连接MTL与PFC的大规模纤维束（例如，穹窿、扣带回）与正常成人的模式分离性能之间的关系。它也将是第一个检查 连接纹状体与PFC的束的完整性（例如，尾状核-PFC，壳核-运动）与这些记忆过程的关系。该奖项的独立阶段将评估MTL和纹状体记忆系统之间的相互作用和解离，这些系统通常被认为受到健康和病理性衰老的不同影响。我们将检验以下假设：纹状体与MTL束完整性的退化解释了健康老年人与年轻人的模式分离下降（具体目标2），MTL与纹状体束连接性的退化解释了最老老年人与更老老年人的模式分离下降（具体目标3）。这些数据将直接检验皮层断开理论，该理论提出，白色物质连接的减少是与衰老相关的认知能力下降的原因。