CRCNS: Scale-invariant navigation and its degradation in Alzheimer's disease

该项目旨在推进已知的导航神经机制。我们的做法是 通过开发和实证测试一个计算框架， 并解码信息以形成比例不变存储器。这个框架被称为SIPI，简称 Scale Invariant Path Integration框架。将SIPI框架应用于导航提供了 神经元如何通过编码动物的运动获得空间调谐的机制模型，以及神经元如何通过编码动物的运动获得空间调谐的机制模型。 神经元退化影响路径整合能力。该项目将产生新的工具，以促进更广泛的 SIPI的应用和测试，并通过实证研究测试SIPI框架的强有力预测 啮齿动物和人类的行为和大脑活动。新工具包括一个模拟环境， 跨SIPI的参数化和变体分析SIPI函数，其1）使用视觉输入来引导 导航，2）解决位置编码如何与嘈杂的自我运动线索相互作用，以及3）执行记忆 导航。啮齿动物中的高密度单单位电生理学将测试SIPI的强预测 关于头部方向和边界调谐神经元是否编码运动的多尺度历史， 以及这些神经元编码的历史是否解释了健康和转基因动物的导航能力， 阿尔茨海默病（AD）的模型。人类的行为和超高分辨率功能成像将 测试SIPI预测：1）路径集成性能具有诊断价值， 临床前AD，2）老年患者的速度编码和路径整合能力降低 通过批准的AD治疗，3）AD与对环境的依赖性增加有关 定向的边界，以及4）在健康志愿者中，环境边界的接近度是 在内嗅皮层中以多尺度方式编码。也就是说，该项目将对 SIPI框架，将促进我们对大脑空间编码的理解，并测试新的途径， 深入了解伴随阿尔茨海默病的行为缺陷。 相关性（参见说明）： 导航是一种核心能力，它取决于在第一次碰撞中受到影响的电路的完整功能。 老年痴呆症该项目旨在确定神经生理学机制，有助于 人类临床前阿尔茨海默病个体中的路径整合和边界编码损伤， 开发可翻译的结果评估阿尔茨海默病的动物模型的措施。

This project seeks to advance what is known about the neural mechanisms of navigation. Our approach is through the development and empirical testing of a computational framework for how neural circuits encode and decode information to form scale invariant memories. This framework is referred to as SIPI, short for Scale Invariant Path Integration framework. Applying the SIPI framework to navigation provides a mechanistic model for how neurons obtain spatial tuning by encoding an animals’ movements and for how neural degeneration affects path integration ability. This project will generate new tools to facilitate broader application and testing of SIPI and test strong predictions of the SIPI framework through empirical studies of rodent and human behavior and brain activity. The new tools include a simulation environment for analyzing SIPI function across parameterizations and variants of SIPI that 1) use visual input to guide navigation, 2) address how positional coding interacts with noisy self-motion cues, and 3) perform memory guided navigation. High-density single unit electrophysiology in rodents will test strong predictions of SIPI regarding whether head direction and boundary tuned neurons encode a multiscale history of movements and whether the history encoded by those neurons accounts for navigation ability in healthy and transgenic models of Alzheimer’s disease (AD). Behavioral and ultra-high resolution functional imaging in humans will test predictions from SIPI that 1) path-integration performance has diagnostic value for identifying preclinical AD, 2) that reduced velocity coding and path integration ability in elderly patients are addressed by approved AD treatments, 3) that AD is associated with increased dependence on environmental boundaries for orienting, and 4) that, in healthy volunteers, the proximity of environmental boundaries are encoded in a multiscale fashion in the entorhinal cortex. That is, this project will perform strong tests of the SIPI framework, will advance our understanding of spatial coding in the brain, and test new avenues for insight into the behavioral deficits that accompany Alzheimer’s disease. RELEVANCE (See instructions): Navigation is a core competency that depends upon intact functioning of circuits impacted first in Alzheimer’s disease. This project aims to determine the neurophysiological mechanisms that contribute to path integration and boundary coding impairments in human preclinical Alzheimer’s disease individuals and develop translatable outcome measures for assessing animal models of Alzheimer’s disease.