The Heart and the Mind: An Integrative Approach to Brain-Body Interactions in the Zebrafish

心与心：对脑-体相互作用的综合方法 斑马鱼 我们目前的U19主要集中在外感，这可以被定义为积累的感官体验 源自外部世界的事件。然而，所有的神经计算都发生在身体的环境中， 其受饥饿、疲劳、动力和昼夜周期的动态影响。到达大脑的信息 从器官和感受器内的身体，总结下的总括术语内感受，因此， 叠加在外感受计算上这增加了任何动物任务的行为变异性，从改变活力到 改变奖励的效价来完全否决反应。 为了更好地理解这种具体的计算，我们将首先纳入心脏和呼吸变量， 动态报告基本的内部状态，我们的标准行为分类方法，我们将包括详细的 在我们的功能成像研究中，自主神经和心内神经系统的表征和建模。 最后，作为描述和验证生成的神经电路模型的关键资源，我们将创建一个 完整的斑马鱼幼鱼体脑连接体。 这项研究计划与三十多年前大卫马尔阐述的三个层次的理解是一致的， 他强调了考虑进化原理、数学表示和硬件的重要性 实现作为理解大脑的统一和相互关联的方法。根据这一框架，我们首先 试图分离出鱼类行为的各个方面，以适应它们的原生环境和背景。我们接下来使用各种 受控行为分析，以提取控制模块化感觉运动动力学的算法规则， 转换，并且通过关于内部状态变化的知识来增强，如通过观察到的调制所反映的， 心脏和呼吸活动。为了表征这些显式和潜在行为的硬件实现， 算法，我们建议首先测量细胞活动使用全脑功能光成像的中央， 自主神经系统和心内神经系统（CNS、ANS和ICNS）。接下来，我们将使用这些全面的数据集， 生成所观察到的动态的真实电路模型。这些模型将指导一系列的电路解剖 实验，如特定细胞类型的光遗传学扰动，靶向膜片钳生理学和稀疏 connectomics跟踪，允许我们验证，扩展和约束我们的模型。我们注意到，这一办法还使我们能够 发现新的电路元件和电路图案的机会，以及实现计算的新方法， 大脑的算法。 我们当前U19的另一个扩展是为这些行为添加了动态建模框架，其中 动物可以灵活地与环境互动，我们考虑多个时间尺度的互动。我们认为 这构成了一种不同的，也许在行为学上更相关的方法， 我们以前使用的受限的、简化的和重复的挑战。此外，该框架非常适合于表征 心脏控制的连续过程及其与行为调节的相互作用。

The heart and the mind: an integrative approach to brain-body interactions in the zebrafish Our current U19 has focused primarily on Exteroception, which can be defined as the accumulated sensory experience originating from events in the outside world. However, all neural computation takes place in the context of the body, which is subject to the dynamics of hunger, fatigue, motivation and diurnal cycles. The information that reaches the brain from the organs and receptors inside of the body, summarized under the umbrella term of Interoception, is therefore overlaid onto exteroceptive computations. This adds behavioral variability to any animal task, from changing vigor to altering valence of rewards to vetoing responses altogether. To better understand such embodied computation, we will first incorporate cardiac and respiratory variables that dynamically report basic internal states to our standard behavioral classification methods, and we will include detailed characterization and modeling of the autonomic and intracardiac nervous system in our functional imaging studies. Finally, as a critical resource for the description and validation of the generated neural circuit models, we will create a complete body-and-brain connectome of the larval zebrafish. This research plan is aligned with the three levels of understanding articulated by David Marr more than thirty years ago, who emphasized the importance of considering Evolutionary Principles, Algorithmic Representation and Hardware Implementation as a unified and interconnected approach for understanding the brain. Following this framework, we first try to isolate aspects of fish behavior that are adapted to their native environment and context. We next use a variety of controlled behavioral assays to extract the algorithmic rules that govern the dynamics of modular sensorimotor transformations, and that are augmented by knowledge about internal state changes as reflected by observed modulation of cardiac and respiratory activity. To characterize the hardware implementation of these explicit and latent behavioral algorithms, we propose to first measure cellular activity using brain-wide functional light imaging of the central, the autonomic and the intracardiac nervous systems (CNS, ANS and ICNS). We next will use these comprehensive datasets to generate realistic circuit models of the observed dynamics. These models will then guide a series of circuit dissection experiments, such as optogenetic perturbations of specific cell types, targeted patch-clamp physiology and sparse connectomics tracing, allowing us to validate, extend, and constrain our models. We note that this approach also affords us the opportunity to discover new circuit elements and circuit motifs, and novel ways to implement computational algorithms by the brain. Another extension of our current U19 is the addition of a dynamical modeling framework for these behaviors, where animals can interact flexibly with the environment, and where we consider multiple time scales of interaction. We believe that this constitutes a different and perhaps ethologically more relevant approach when compared to the highly constrained, simplified and repetitive challenges we used before. Further, this framework is well suited in characterizing the continuous process of cardiac control and its interaction with behavioral modulation.