Impaired spatial decoding and neural population code rescaling in AD mice

AD 小鼠的空间解码和神经群体代码重新调整受损

• 批准号: 10237353
• 负责人: Gustavo A Rodriguez
• 金额: $ 10.64万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10237353
• 关键词: 4-Hydroxy-Tamoxifen; Address; Affect; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease pathology; Amyloid beta-42; Amyloid beta-Protein; Attenuated; Behavior; Behavioral; Cells; Chronic; Code; Complex; Coupled; Data; Development; Development Plans; Electrophysiology (science); Ensure; Exhibits; Functional disorder; Goals; Hippocampus (Brain); Hyperactivity; Impaired cognition; Impairment; Individual; Intervention; J20 mouse; Knowledge; Label; Learning; Ligands; Location; Machine Learning; Maps; Measures; Memory; Mentored Research Scientist Development Award; Mentors; Mentorship; Motion; Mus; Muscarinic Acetylcholine Receptor; Neuronal Dysfunction; Neurons; Pathologic; Pathology; Pattern; Peptides; Performance; Play; Population; Process; Research; Role; Scientist; Signal Transduction; Specificity; Speed; Stimulus; Talents; Testing; Training; Transgenic Mice; Universities; abeta accumulation; attenuation; awake; career; career development; cognitive performance; combat; design; designer receptors exclusively activated by designer drugs; entorhinal cortex; excitatory neuron; experience; experimental study; improved; in vivo; information processing; learning strategy; memory encoding; mouse model; network dysfunction; neuron loss; neuronal circuitry; neuronal patterning; neuroregulation; neurotransmission; novel; recruit; relating to nervous system; response; spatial memory; tau Proteins; tau aggregation

Impaired spatial decoding and neural population code rescaling in AD mice Project Summary: Considerable evidence exists to support the notion that amyloid beta (Aβ) and tau pathology impair neuronal circuit integrity and function in Alzheimer’s disease (AD). Unfortunately, few studies have tested the direct influence of AD pathology on spatial computation within affected neuronal populations, resulting in an information gap at the neuronal network level. Moreover, in vivo experiments that examine large scale, neuronal network activity in mouse models of Aβ and tau pathology are lacking. In this proposal, I test the overarching hypothesis that Aβ and tau associated neuronal network dysfunction impairs task-relevant, spatial information encoding in large populations of neurons within the EC-HIPP circuit, and that combating this aberrant activity can restore order and improve spatial information processing in AD mice. In Aim 1, I will test the hypothesis that oligomeric forms of Aβ and tau disturb spatial information content encoded within large populations of neurons in the entorhinal cortex – hippocampal (EC-HIPP) circuit. I will also test if these oligomeric peptides alter the number of neurons recruited into the population code responsible for memory encoding in a spatial learning and memory task. In Aims 2 & 3, I will leverage the predictive power of machine learning to decipher the neural code for spatial information processing in EC-HIPP population activity. Specifically, my goals in Aim 2 will be to examine the individual and combined impact of Aβ and tau pathologies on features of spatial information encoding in the EC-Tau/hAPP mouse line. In Aim 3, I will employ chemogenetics using a novel DREADDs ligand to combat aberrant neuronal activity in AD mouse models, with the ultimate goal of improving spatial information processing in neuronal networks burdened with pathology. Excitatory neurons will be specifically targeted in an effort to better understand their contribution to impaired spatial information processing in AD mouse models. The proposed research aims are designed to bridge an information gap between AD-related cognitive impairment and the underlying circuit pathology. This Mentored Research Scientist Development (K01) Award will afford me the opportunity to accomplish this major goal while enriching my technical skillset and expanding my knowledge of AD pathophysiology. In addition, the integrated training and mentorship that I will receive will help me develop additional expertise in machine learning for spatial decoding analyses. Together, the proposed studies and career development plan will ensure that I achieve my long-term career goal of launching a competitive, independent research career at a major research university.

AD 小鼠的空间解码和神经群体代码重新调整受损 项目摘要：存在大量证据支持β淀粉样蛋白 (Aβ) 和 tau 病理学这一观点 损害阿尔茨海默病 (AD) 中神经元回路的完整性和功能。不幸的是，很少有研究测试过 AD 病理学对受影响神经元群内空间计算的直接影响，导致 神经元网络层面的信息差距。此外，检查大规模神经元的体内实验 Aβ 和 tau 病理学小鼠模型中缺乏网络活动。在这个提案中，我测试了总体 假设 Aβ 和 tau 相关神经元网络功能障碍会损害任务相关性、空间性 EC-HIPP 回路内大量神经元的信息编码，以及对抗 这种异常活动可以恢复 AD 小鼠的秩序并改善空间信息处理。在目标 1 中， 我将检验以下假设：Aβ 和 tau 的寡聚形式会干扰编码在其中的空间信息内容 内嗅皮层-海马（EC-HIPP）回路中存在大量神经元。我也会测试这些是否 寡聚肽改变了负责记忆的群体代码中招募的神经元数量 空间学习和记忆任务中的编码。在目标 2 和 3 中，我将利用机器的预测能力 学习破译 EC-HIPP 群体活动中空间信息处理的神经代码。 具体来说，我的目标 2 的目标是检查 Aβ 和 tau 病理学的单独影响和综合影响 EC-Tau/hAPP 小鼠系空间信息编码特征的研究。在目标 3 中，我将采用 化学遗传学使用新型 DREADDs 配体来对抗 AD 小鼠模型中的异常神经元活动， 最终目标是改善承载病理学的神经网络的空间信息处理。 将专门针对兴奋性神经元，以更好地了解它们对受损神经元的贡献 AD 小鼠模型中的空间信息处理。 拟议的研究目标旨在弥合 AD 相关认知之间的信息差距 损伤和潜在的电路病理学。指导研究科学家发展 (K01) 奖 将为我提供实现这一主要目标的机会，同时丰富我的技术技能并扩展 我对 AD 病理生理学的了解。此外，我将接受的综合培训和指导将 帮助我发展用于空间解码分析的机器学习方面的额外专业知识。共同提出的 学习和职业发展计划将确保我实现我的长期职业目标 在一所主要研究型大学从事有竞争力的、独立的研究生涯。