Deciphering aging-driven cognitive decline in C. elegans spatial memory and learning through an interdisciplinary approach

通过跨学科方法破译线虫空间记忆和学习中衰老驱动的认知衰退

• 批准号: 9905326
• 负责人: Eleni Gourgou
• 金额: $ 12.25万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-15 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9905326
• 关键词: Affect; Age; Age-associated memory impairment; Aging; Alzheimer' s Disease; Animal Model; Animals; Behavior; Behavioral; Behavioral Assay; Biological; Biological Models; Biology of Aging; Caenorhabditis elegans; Calcium; Chemicals; Cognition; Cognitive; Cognitive aging; Communities; Complement; Computational Technique; Computer Models; Conflict (Psychology); Cues; Custom; Data; Decision Making; Dementia; Engineering; Ensure; Exposure to; Failure; Genes; Genetic; Goals; Human; Image; Imaging Techniques; Impaired cognition; Invertebrates; Knowledge; Learning; Literature; Maps; Mathematics; Measures; Mechanics; Memory; Memory Loss; Mentorship; Methods; Michigan; Modeling; Molecular; Monitor; Motor Activity; Motor Neurons; Nematoda; Nerve Degeneration; Nervous system structure; Neurobiology; Neurons; Organism; Outcome; Pathway interactions; Performance; Positioning Attribute; Process; Proprioception; Research; Research Activity; Research Personnel; Risk; Sensory; Smell Perception; Stimulus; Structure; Synaptic plasticity; System; Targeted Research; Testing; Training; Universities; Weight; Work; age effect; aged; base; behavioral outcome; behavioral study; career; career development; cognitive function; computational neuroscience; design; experience; experimental study; functional decline; gene therapy; genetic analysis; information processing; interdisciplinary approach; interest; mathematical model; medical schools; mild cognitive impairment; molecular imaging; multidisciplinary; mutant; neuronal circuitry; normal aging; skills; spatial memory; way finding

Project Summary Cognitive decline is a central issue in neurobiology of aging, not only due to its profound scientific interest, but also because people with mild cognitive impairment are at increased risk of developing Alzheimer's or another dementia. Even though human cognition may differ from animal cognition, cognitive behaviors like memory, learning, decision making and environmental information processing are widely observed even in invertebrate animals. C. elegans nematode is an exemplary model organism in both biology of aging and neurobiology. Cognitive behaviors (memory, learning and decision making) are being steadily clarified using C. elegans worms, mainly however in the context of chemical stimuli; hence little is known about their cognitive aging in relation to spatial navigation. Still, the need for elucidating the cellular and molecular details of these processes remains pressing. The emerging potential of C. elegans as model system for behavioral and cognitive studies could significantly help the scientific community understand aging-driven cognitive decline and its mechanisms in higher organisms, including humans. The proposed research focuses on characterizing aging-driven cognitive decline. We hypothesize that normal aging differentially affects multiple cognitive functions, and that specific neurons and neuronal circuits are more susceptible to aging effects, functioning as "aging hubs" that determine the performance of entire networks. To test this, we have planned two research thrusts, one experimental and one computational. We will use a custom-made cognitive aging studying platform for worms, i.e. the Worm-Maze. To characterize aging-driven cognitive decline, we will investigate the impact of aging on spatial memory and on decision making under conflicting environmental cues. Next, we will genetically inactivate selected neurons by silencing target genes, to identify genes and neurons that govern these behaviors and we will detect how each of them is affected by aging. Live calcium imaging will be used to track firing neurons. For the computational part, we will build mathematical models to describe learning, spatial memory and decision making, and predict the performance of neuronal networks undergoing aging. Thus, by combining experimental and computational efforts, we will identify "aging hubs" in the cognition-related neuronal networks. Successful outcome of the proposed work will significantly contribute to understanding aging of neuronal circuits involved in cognition. The proposed research plan is based on the applicant's strong background in neurobiology and her engineering experience. Together with the career plan, they aim to strengthen and expand the applicant's knowledge in genetics, behavioral studies and computational neuroscience in order for her to grow into a uniquely positioned independent investigator in contemporary neurobiology of aging. Well rounded career development through targeted research activities, mentorship from a multi-disciplinary team of acclaimed experts and selected coursework will take place in the University of Michigan Medical School, Mechanical Engineering Department and Department of Mathematics.

项目摘要 认知能力下降是衰老神经生物学的一个中心问题，这不仅是因为它具有深刻的科学意义， 还因为轻度认知障碍的人患阿尔茨海默氏症或其他疾病的风险增加， 痴呆尽管人类的认知可能不同于动物的认知，但像记忆这样的认知行为， 学习、决策和环境信息处理在无脊椎动物中也广泛存在 动物C.线虫是衰老生物学和神经生物学中的典型模式生物。 认知行为（记忆、学习和决策）正在使用C语言逐步得到澄清。elegans 蠕虫，但主要是在化学刺激的背景下，因此很少有人知道他们的认知老化， 与空间导航有关。尽管如此，需要阐明这些过程的细胞和分子细节， 仍然紧迫。C.线虫作为行为和认知研究的模型系统 可以显著帮助科学界了解衰老驱动的认知衰退及其机制 包括人类在内的高等生物。拟议的研究重点是表征老化驱动的 认知能力下降我们假设正常的衰老对多种认知功能的影响不同， 特定的神经元和神经元回路更容易受到衰老的影响，作为“衰老中枢”， 决定整个网络的性能。为了验证这一点，我们计划了两个研究方向， 一个是实验的，一个是计算的。我们将使用定制的蠕虫认知老化研究平台， 即蠕虫迷宫为了描述衰老驱动的认知衰退，我们将研究衰老对 空间记忆和在冲突环境线索下的决策。接下来，我们将从基因上 通过沉默靶基因来筛选选定的神经元，以确定控制这些基因和神经元的基因。 行为，我们将检测它们中的每一个是如何受到衰老的影响的。实时钙成像将用于跟踪 发射神经元对于计算部分，我们将建立数学模型来描述学习，空间 记忆和决策，并预测神经网络的性能经历老化。因此，由 结合实验和计算的努力，我们将确定“老化枢纽”在认知相关的 神经网络拟议工作的成功结果将大大有助于了解 参与认知的神经元回路的老化。拟议的研究计划是基于申请人的强大 神经生物学背景和工程经验与职业规划一起，他们的目标是 加强和扩大申请人在遗传学，行为研究和计算方面的知识 神经科学，以使她成长为一个独特的定位独立调查员，在当代 衰老的神经生物学通过有针对性的研究活动， 一个由著名专家和选定课程组成的多学科团队将在大学举行， 密歇根医学院，机械工程系和数学系。