Hippocampal Network Profiles of Memory Aging

记忆老化的海马网络概况

• 批准号: 7731631
• 负责人: Joe Z Tsien
• 金额: $ 49.18万
• 依托单位: AUGUSTA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7731631
• 关键词: Address; Affect; Age; Aging; Aging-Related Process; Algorithms; Animals; Attention; Behavioral; Biological Neural Networks; Brain; Characteristics; Computational algorithm; Data Set; Deterioration; Elderly; Exhibits; Fright; Genetic; Goals; Hippocampus (Brain); Imagery; Individual; Knowledge; Laboratories; Lead; Learning; Mathematics; Measures; Memory; Methods; Molecular; Monitor; Mus; Network-based; Neurons; Pattern; Performance; Population; Process; Regulation; Retrieval; Role; Series; Sleep; Staging; Techniques; Testing; Therapeutic Intervention; Time; Transgenic Mice; aged; aging brain; base; cell assembly; cognitive function; conditioning; in vivo; insight; memory acquisition; memory encoding; memory process; memory recall; public health relevance; relating to nervous system; research study; success; tool; young adult

DESCRIPTION (provided by applicant): One of the major obstacles in our understanding of memory ageing is lack of an effective tool to address the fundamental questions such as: what are memory traces? What are the major alterations in the network-level dynamics and memory-encoding patterns during aging? How can we identify network characteristics that give rise to superior memory function in the aged brain? In this application, we propose to apply large-scale ensemble recording method to identify, visualize, and characterize memory traces in CA1 region throughout all major stage of the memory process, namely, acquisition, consolidation, and retrieval in both young adult and aging brains. In our application, we hypothesize that unique activation and reactivation patterns by CA1 cell assemblies form the network-level basis for predicting behavioral performances in memory tests. We will test this key hypothesis by examining four specific questions: 1) what are the ensemble patterns of CA1 activity during memory acquisition, consolidation, and retrieval? 2) What are the fundamental network-level characteristics that are correlated with behavioral memory performances? 3) How does the aging process affect those characteristics? 4) What is the role of the NR2B in the regulation of network-level features underling the enhanced memory during ageing? It is conceivable that identification and visualization of CA1 memory traces should enable us to manipulate and discover the neural processes underlying memory decline in the old brain. Such a new capacity and knowledge should lead to new strategies for potential therapeutic interventions for memory ageing. PUBLIC HEALTH RELEVANCE: Both people and animals exhibit deterioration of cognitive function as they age. The neural bases for the gradual decline in attention and memory are poorly understood. Based on our recent success in applying large-scale in vivo recording techniques and computational algorithms for monitoring and analyzing activity patterns of over hundreds of individual neurons in the CA1 region of freely behaving mice, we propose to identify and characterize network-level memory traces in both young and old animals. Moreover, we will investigate the neural network basis underlying enhanced memory function in young and aged NR2B transgenic mice. We will compare the similarity and differences between wild-type aged mice and transgenic aged mice. It is conceivable that the identification and biophysical description of network-level memory traces should provide crucial insights into the question of what memory is, and how memory is altered by ageing.

描述（由申请人提供）：我们对记忆衰老的理解的主要障碍之一是缺乏解决基本问题的有效工具，例如：什么是记忆痕迹？衰老过程中网络级动力学和内存编码模式的主要变化是什么？我们如何确定在老年大脑中产生出色记忆功能的网络特征？在此应用程序中，我们建议在整个内存过程的所有主要阶段中应用大规模的集合记录方法，以识别，可视化和表征CA1区域中的记忆痕迹，即，在年轻人和衰老的大脑中，获得，获取，巩固和检索。在我们的应用程序中，我们假设CA1单元组件的独特激活和重新激活模式构成了预测记忆测试中行为性能的网络级别基础。我们将通过检查四个特定问题来检验这一关键假设：1）在记忆获取，合并和检索过程中，CA1活动的合奏模式是什么？ 2）与行为记忆性能相关的基本网络级特征是什么？ 3）衰老过程如何影响这些特征？ 4）NR2B在衰老期间增强内存的网络级特征调节中的作用是什么？可以想象，CA1记忆痕迹的识别和可视化应该使我们能够操纵和发现旧大脑记忆下降的神经过程。这种新的能力和知识应为记忆衰老的潜在治疗干预措施带来新的策略。 公共卫生相关性：随着年龄的增长，人和动物都表现出认知功能的恶化。人们对注意力和记忆的逐渐下降的神经基础知之甚少。基于我们最近在应用大规模的体内记录技术和计算算法方面的成功，以监测和分析自由行为的CA1区域中数百个单个神经元的活动模式，我们建议在年轻动物和旧动物中识别和表征网络水平的记忆痕迹。此外，我们将研究年轻和老化的NR2B转基因小鼠的神经网络基础增强的记忆功能。我们将比较野生型老鼠和转基因老年小鼠之间的相似性和差异。可以想象，网络级内存痕迹的识别和生物物理描述应为什么是内存以及如何通过衰老改变记忆的问题提供重要的见解。