Collaborative Research: Sensory feedback loops in a swimming lamprey: Integrating fluid dynamics, body mechanics, and neurophysiology

该项目将开发多尺度数学模型，整合神经生理学、肌肉力学和流体动力学，以控制最基础的活脊椎动物七鳃鳗的游泳。这些模型将用于开发和测试动物如何在复杂和不断变化的环境中稳定有效地移动的一般原理。pi开发了第一个游泳生物的数学模型，将周围的流体与模拟动物完全耦合。在这个项目中，pi将添加模拟神经和感觉系统，以测试动物必须如何对稳定有效游泳的扰动作出反应的广泛假设。该项目的方法是考虑游泳的动态如何从所有这些元素的固有耦合中产生。pi假设，随着振荡频率的增加，感觉反馈对于支持运动模式是必要的，但是，在特定的振荡频率下，机械相互作用本身就足以稳定游泳者免受神经噪声和流体扰动。为了验证这些假设，pi结合了两类不同的数学模型：(1)基于不可压缩Navier-Stokes方程的高保真计算流体动力学（CFD）模型，用于估计物体的力和运动；(2)耦合振荡器模型来描述产生运动模式的神经回路，称为中枢模式发生器（CPG）及其感觉输入。CFD模型模拟了控制方程和参数已知的系统方面，而CPG模型允许我们检查关于感觉运动反馈的一般原理，以了解细节较少的方面。所有的动物都使用灵活的结构，如毛发、触角、鳍、四肢，甚至整个身体来与环境相互作用，所有这些结构都会在身体内力和外部环境力的作用下变形。所有会运动的动物都有神经系统，它们利用电信号激活肌肉，产生力量，并对环境相互作用产生的感觉输入做出反应。要了解动物如何在物理世界中有效地运动，我们必须了解许多不同的力的相互作用，包括被动组织特性的力、主动肌肉力和外部环境的力。这样的理解对于下一代假肢的发展至关重要，下一代假肢能够在复杂的环境中实现适应性和有效的运动，对于依赖于受损脊髓回路、腿部力学和与外部世界相互作用之间耦合的脊髓损伤治疗的进展至关重要。在这个项目中，pi将研究这些不同系统和力之间的耦合如何有助于模型游泳生物运动的动力学和稳定性。

This project will develop multiscale mathematical models that integrate neurophysiology, muscle mechanics, and fluid dynamics that govern the swimming of lamprey, the most basal living vertebrate. The models will be used to develop and test general principles for how animals manage to move stably and effectively through complex and changing environments. The PIs have developed the first mathematical model of a swimming organism to fully couple a surrounding fluid with a simulated animal. In this project, the PIs will add simulated nervous and sensory systems, in order to test broad hypotheses for how animals must respond to perturbations for stable and effective swimming. The approach of the project is to consider how the dynamics of swimming emerges from the inherent coupling of all of these elements. The PIs hypothesize that sensory feedback is necessary to support the locomotor pattern as oscillation frequency increases, but, at a particular oscillation frequency, mechanical interactions alone can be sufficient to stabilize the swimmer against both neural noise and fluid perturbations. To test these hypotheses, the PIs combine two different classes of mathematical models: (1) a high-fidelity computational fluid dynamic (CFD) model based upon the incompressible Navier-Stokes equations to estimate the forces and the motion of the body; (2) coupled oscillator models to describe the neural circuit that generates the locomotor pattern, called a central pattern generator (CPG) and its sensory inputs. The CFD model simulates aspects of the system where the governing equations and parameters are known, while the CPG models allow us to examine general principles about sensorimotor feedback for aspects where fewer details are known.All animals interact with their environment using flexible structures such as hairs, antennae, fins, limbs, and even their entire bodies, and all of these structures deform in response to both internal body forces and external environmental forces. And all animals that move have nervous systems that use electrical signals to activate muscles to produce force and to respond to sensory inputs that result from those environmental interactions. To understand how animals move effectively in the physical world, one must understand the interactions of many different forces, including forces from passive tissue properties, active muscular forces, and forces from the external environment. Such an understanding is critical to the development of next generation prosthetic limbs that enable adaptive and effective motion in complex environments, and to the progress of therapies for spinal cord injury that rely on the coupling between the damaged spinal circuits, the mechanics of legs, and the interaction with the external world. In this project, the PIs will investigate how the coupling among these different systems and forces contributes to the dynamics and stability of motion in a model swimming organism.