What is going on in the fish's brain? Characterization and Modeling of Neural Dynamics (CNS and ANS and ICNS)

项目2 正是行为算法决定了任何神经实现模型的问题和框架。因此，要 了解行为算法是如何实现的，并为幼虫生成一个逼真的大脑-身体电路模型 斑马鱼，我们除了需要关于电路解剖结构的知识外，还需要关于 行为过程中的神经活动模式。此外，行为算法必须在 具体化动物，它受制于生理需求、波动和约束。为了适应这两种情况 在这些需求中，我们将估计这些生理状态变量并将其纳入我们的建模框架。 为了获得必要的数据集，我们建议添加心脏和鳃以及身体宽度的详细测量 从自主神经系统(ANS)和心脏固有神经系统(ICNS)到我们的 实验曲目。这样的录音将与成熟的全脑成像技术相结合，在那里我们 将重点放在关键区域，如下丘脑和其他各种已经被确定为发挥作用的区域 在行为和内部状态的调节中起着重要作用。以便于量化和控制 状态依赖的可变性，我们还设计了一套行为分析，其中环境背景被调制到 诱导动物体内和自主神经状态的特定变化。 然后，在这些实验中收集的综合数据集允许生成一系列真实的电路 原则上可以实现行为算法的模型，并且可以重现和模拟记录的 神经和心脏活动模式。这些现实的模型允许产生特定的预测和假设 关于底层电路中的许多不受约束的参数。这些参数包括特定的连通性 模式、突触重量、膜的兴奋性等等。为了限制这么多种类的 变量我们需要应用各种独立的方法。为此，我们将利用广泛的 已经在当前U19赠款的背景下开发了实验工具包，其中包括光遗传学的使用 基于电路询问、有针对性的电生理学和覆盖的EM体积中的稀疏连接追踪。许多. 这些实验方法需要捆绑的行为准备，而我们的实验室已经建立了这些准备。 这种准备为全脑成像和靶向干扰提供了理想的环境，因此它们将 促进为我们的各种行为分析生成一套进一步完善的验证电路模型。 总而言之，我们的目标是首先验证和约束我们已经在 当前U19的背景下，将这些经过验证的模型与我们将为 动物的自主神经状态，并最终将它们组合成一个复合的逼真的多尺度电路模型 斑马鱼的大脑和身体。这个多尺度电路模型将描述所有来自外部世界的感觉刺激是如何 以及来自身体内部的，被编码并转换为产生运动的分布式神经活动 构成系统最终输出的序列。

Project 2 It is the behavioral algorithms that dictate the questions and framework for any model of neural implementation. Thus, to discover how behavioral algorithms are implemented and to generate a realistic brain-body circuit model for larval zebrafish, we need, in addition to knowledge about the anatomical structure of the circuits, detailed information about neural activity patterns during behavior. Further, behavioral algorithms must be implemented in the context of the embodied animal, which is subject to physiological demands, fluctuations and constraints. In order to accommodate both of these requirements, we will estimate and incorporate these physiological state variables into our modeling framework. In order to obtain the necessary datasets, we propose to add detailed measurements of heart and gills, as well as body wide recordings from the autonomic nervous system (ANS) and the intrinsic cardiac nervous system (ICNS) to our experimental repertoire. Such recordings will be combined with established brain wide imaging technologies, where we will focus on critical regions, such as the hypothalamus and various other areas that were already identified to play an important role in the modulation of behaviors and internal states. To facilitate the quantification and control of state-dependent variability, we have also designed a set of behavioral assays where environmental context is modulated to induce specific changes in the animal's internal and autonomic state. The comprehensive data sets collected in these experiments then allow for the generation of a family of realistic circuit models that could, in principle, implement the behavioral algorithms and that can reproduce and emulate the recorded neural and cardiac activity patterns. These realistic models allow for the generation of specific predictions and hypotheses about many of the unconstrained parameters in the underlying circuits. Such parameters include specific connectivity patterns, the synaptic weights, the excitability of membranes and many more. In order to constrain this large variety of variables one needs to apply a variety of independent approaches. To that end we will take advantage of the extensive experimental toolset already developed in the context of the current U19 grant, which includes the use of optogenetics based circuit interrogation, targeted electrophysiology and sparse connectomics tracing in overlaid EM volumes. Many of these experimental approaches require tethered behavioral preparations which are already established in our laboratories. Such preparations provide the ideal setting for brain wide imaging and targeted perturbation, and they will therefore facilitate the generation of a further refined set of validated circuit models for our various behavioral assays. To summarize, our goal is to first validate and constrain a set of realistic circuit models that we have already generated in the context of the current U19, to integrate these validated models with a novel framework we will generate for the animal's autonomic state, and ultimately to combine all of them into a composite realistic multiscale circuit model of the zebrafish brain and body. This multiscale circuit model will describe how all sensory stimuli, from the outside world as well as from inside the body, are encoded and transformed into distributed neural activity that generates the motor sequences that constitute the final output of the system.