Modeling Cellular Determinants of Cognitive Decline in Aging

衰老过程中认知能力下降的细胞决定因素建模

• 批准号: 8042213
• 负责人: PATRICK R HOF
• 金额: $ 42.38万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8042213
• 关键词: Modeling; Cellular; Determinants; Cognitive; Decline

DESCRIPTION (provided by applicant): Cognitive decline in normal aging is accompanied by morphologic changes on many scales, and in rhesus monkeys, by single cell electrophysiological changes such as altered firing rates and synaptic responses. A subset of 'successful agers' can maintain both normal cognitive function and normal single-cell electrophysiology, suggesting some form of adaptive compensation for morphologic dystrophy at the cellular level. To date, no mechanistic understanding of these cellular changes, nor the inferred compensatory mechanisms, exists. The goal of this unique multidisciplinary project is to develop innovative computational technologies for identifying causal mechanisms underlying the cognitive decline that accompanies aging and neurodegeneration. Based upon these mechanisms, this project will design quantitatively precise strategies for compensating or reversing these changes, to restore a given cellular-level function to normal levels. Three Specific Aims will address this broad objective: (1) To reconstruct the morphology, including dendritic spines, of electrophysiologically characterized young and aged layer 3 (L3) pyramidal cells from the prefrontal cortex of rhesus monkeys that have underwent behavioral testing; (2) To develop morphologically accurate compartment models of young and aged L3 pyramidal cells while developing novel parameter optimization tools; and (3) To predict compensatory mechanisms for restoring normal function in aged or dystrophic neurons using newly-designed sensitivity-analysis techniques. Public dissemination of the 3D morphology and physiology of young and aged neurons from behaviorally characterized primates will provide a unique database for the general neuroscience community to begin to address important cellular and system-level questions. Dissemination of all modeling and analysis software will provide the computational community with efficient tools to apply and extend these techniques. Such studies will generate crucial insight into the cellular bases of aging- and neurodegenerative disease-related changes in cognitive function. The development of novel technologies to predict mechanisms that can compensate for specific morphologic changes to restore a given cellular level function, has far-reaching implications for designing therapeutic interventions for many human diseases. PUBLIC HEALTH RELEVANCE: This project develops and validates novel computational methods for predicting compensatory strategies to reverse the effects of pathologic changes accompanying normal aging and neurodegenerative disorders. Such technologies have far-reaching implications for designing therapeutic interventions in brain diseases. Public distribution of the software that implements these technologies and of the reconstructed neuron morphologies and electrophysiological data from cognitively characterized animals is an invaluable resource to the general neuroscience community.

描述（由申请人提供）：正常衰老中的认知衰退伴随着许多尺度上的形态学变化，在恒河猴中，伴随着单细胞电生理学变化，如放电率和突触反应的改变。 “成功老年人”的一个子集可以保持正常的认知功能和正常的单细胞电生理，这表明在细胞水平上对形态学营养不良进行了某种形式的适应性补偿。 到目前为止，这些细胞的变化，也没有机制的理解，也不存在推断的补偿机制。 这个独特的多学科项目的目标是开发创新的计算技术，用于识别伴随衰老和神经退行性变的认知下降的因果机制。 基于这些机制，该项目将设计定量精确的策略来补偿或逆转这些变化，以将给定的细胞水平功能恢复到正常水平。 三个具体的目标将解决这个广泛的目标：（1）重建的形态，包括树突棘，电生理学特征的年轻和老年层3（L3）锥体细胞从恒河猴的前额叶皮质，已经经历了行为测试;（2）开发形态学上准确的房室模型的年轻和老年L3锥体细胞，同时开发新的参数优化工具;（3）利用新设计的敏感性分析技术预测老年或营养不良神经元恢复正常功能的代偿机制。 从行为特征的灵长类动物的年轻和老年神经元的3D形态和生理学的公开传播将提供一个独特的数据库，一般神经科学界开始，以解决重要的细胞和系统水平的问题。 所有建模和分析软件的传播将为计算界提供应用和扩展这些技术的有效工具。 这些研究将对认知功能中与衰老和神经退行性疾病相关的变化的细胞基础产生至关重要的见解。 开发新技术来预测可以补偿特定形态学变化以恢复给定细胞水平功能的机制，对于设计许多人类疾病的治疗干预措施具有深远的影响。 公共卫生关系：该项目开发并验证了新的计算方法，用于预测补偿策略，以逆转伴随正常衰老和神经退行性疾病的病理变化的影响。 这些技术对设计脑部疾病的治疗干预措施具有深远的影响。 公开分发实现这些技术的软件以及从具有认知特征的动物中重建的神经元形态和电生理数据对一般神经科学界来说是一种宝贵的资源。