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

这个项目致力于推进已知的导航神经机制。我们的方法是 通过开发和实验测试神经回路如何编码的计算框架 并对信息进行解码，形成尺度不变的记忆。该框架称为SIPI，简称SIPI 规模不变的路径集成框架。将SIPI框架应用于导航提供了一个 神经元如何通过编码动物的运动来获得空间调谐以及如何获得空间调谐的机械模型 神经退行性变影响路径整合能力。该项目将生成新的工具，以促进更广泛的 SIPI的应用和检验，并通过实证研究检验SIPI框架的强预测性 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功能：1)使用可视输入进行指导 导航，2)位置编码如何与嘈杂的自动提示相互作用，以及3)执行记忆 导航仪。啮齿类动物的高密度单单位电生理学将检验SIPI的有力预测 关于头部方向和边界调谐神经元是否编码多尺度运动史 以及这些神经元编码的历史是否能解释健康和转基因患者的导航能力 阿尔茨海默病(AD)模型。人类的行为和超高分辨率功能成像将 来自SIPI的测试预测：1)路径集成性能具有诊断价值 临床前AD，2)老年患者速度编码和路径整合能力降低 通过批准的AD治疗，3)AD与对环境的依赖增加有关 定位的边界，以及4)在健康志愿者中，环境边界的接近程度是 在内嗅皮层以多尺度方式编码。也就是说，这个项目将对 SIPI框架，将促进我们对大脑中空间编码的理解，并测试 对伴随阿尔茨海默病的行为缺陷的洞察。 相关性(请参阅说明)： 导航是一项核心能力，它依赖于首先受到影响的电路的完整功能 阿尔茨海默氏症。这个项目的目的是确定神经生理学机制 人类临床前阿尔茨海默病患者的路径整合和边界编码障碍 为评估阿尔茨海默病的动物模型开发可翻译的结果指标。

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.