Inferring multi-scale dynamics underlying behavior in aging C. elegans

项目摘要 生理过程，如老化，必须产生于活动和事件跨越多个时间 鳞片这些过程的动态虽然重要，但很难测量和研究。在多细胞 衰老的模式生物，自由生活的线虫C.线虫是研究得最好的，然而，大多数 衰老研究仅限于简单的结果，如寿命，完全忽略了过程， 老化的发生。这种限制部分是由于缺乏经济和可扩展的技术来获取 在老化过程中的详细数据（记录行为和神经动力学的个人基础上，使用 传统的方法是非常昂贵的）;此外，还没有一个完善的理论（和 计算）方法来模拟老化行为，并在短期和长期之间建立联系 动力学由于缺乏这些工具，人们对这些机制的描述和理解非常有限。 healthspan，即使在优秀的遗传模型系统，如C.优雅此应用程序的目标是定义 行为状态和动力学在老化过程中，并检查行为的神经起源 动力学首先，将设计高通量实验系统和强大的计算管道。 然后，这些工具将用于描述衰老过程中的短期和长期行为动力学，特别是在 对食物供应的反应，导致寿命和健康的调节。模型将建立连接 神经动力学到行为动力学，模型将解决它是否是神经系统中的调制， 导致行为状态变化和不同的长期生理结果的动力学。的 提出的项目是创新的，因为它是第一次多尺度行为动力学记录在大 数量的个人和充分的特点，使用随机动力系统模型在老化过程中，它是 这也是第一次将行为动力学模型与神经动力学模型联系起来，并用神经动力学模型来解释。 拟议的工作是重要的，因为它产生的工具和见解。科学家， 定义内部状态和理解衰老轨迹，特别是对神经起源的洞察， 在各种长寿诱导条件下观察到的动态，将指向潜在的策略， 健康老龄化从技术上讲，我们设想高通量行为记录平台和 神经成像管道将是有用的超越C.理论和计算管道 可以潜在地推广到许多其他实验系统，包括小鼠、非人灵长类动物和 人类丰富的衰老行为数据集也将使其他衰老研究人员受益。

Project Summary Physiological processes such as aging must arise from activities and events spanning multiple time scales. Although important, the dynamics of these processes are difficult to measure and study. In multicellular model organisms for aging, the freely living nematode C. elegans is among the best studied, and yet, most of the aging studies are limited to simple outcomes such as lifespan and completely ignore the process through which aging occurs. This limitation is in part due to the lack of economical and scalable technologies to acquire detailed data during the aging process (recording behavior and neural dynamics on individual basis using conventional approaches are very expensive); further, there has not been a well-established theoretical (and computational) approach to model the aging behavior and make connections between short- and long-term dynamics. The lack of these tools result in the very limited description and understanding of the mechanisms of healthspan, even in excellent genetic model systems as C. elegans. The goal of this application is to define behavioral states and dynamics in the aging process and examine the neural origins of the behavioral dynamics. First, high-throughput experimental systems and robust computational pipelines will be engineered. The tools will then be used to characterize short- and long-term behavior dynamics in aging, especially in response to food availability that results in modulations of longevity and health. Models will be built to connect the neural dynamics to behavioral dynamics, and the models will address whether it is modulations in neural dynamics that lead to changes in behavioral states and different long-term physiological outcomes. The proposed project is innovative, because it is the first time multi-scale behavioral dynamics is recorded in large number of individuals and fully characterized using stochastic dynamical system models in aging process; it is also the first time that behavioral dynamical models are connected to and explained by neural dynamical models. The proposed work is significant, because of both the tools and insights it generates. Scientifically, the ability to define internal states and understand the aging trajectory, especially with insights to the neural origin of the observed dynamics under a variety of longevity-inducing conditions, will point to potential strategies to influence healthy aging. Technologically, we envision that both the high-throughput behavioral recording platform and the neural imaging pipeline will be useful beyond C. elegans, and that the theoretical and computational pipelines can potentially be generalized to many other experimental systems, including mice, non-human primates, and humans. The rich data set for aging behavior will also benefit other aging researchers.