Collaborative Research: Neural and mechanical bases of motor primitives in voluntary frog behavior

运动的组织是一个复杂而困难的问题，部分原因在于运动控制中的“自由度问题”。动物运动的丰富性使其运动控制的选择变得复杂。然而，与目前的机器人不同，动物可以有效地应对它们的自由度。一头刚出生的牛羚幼崽在出生后的几个小时内就和鹿群一起行走。一只青蛙或一只乌龟，仅仅用它的脊髓，就能控制复杂的目标导向轨迹。如果这些动作受到干扰，脊髓也能迅速纠正。有人认为，这些非凡的能力是模块化的，由小组基本元素或运动构建块构建而成。如何产生和使用这些原语是本项目的重点。模块化和运动原语的概念为脊髓运动系统的组织提供了有用的描述。模块化组织已被证明支持脊柱行为，并可能有助于“引导”运动学习。尽管如此，模块化在很多层面上都存在争议。为了完成复杂的、自愿的行为，脊椎原语可能需要被取代或增强。这个项目解决了青蛙捕食行为中的这个问题，这是一个对动物至关重要的系统中的自愿和适应行为，并且在以前的模块化研究中也得到了很好的表征。从多学科的角度研究了猎物攻击的神经力学。模块化组织在神经科学和行为学中的重要性远远超出了生物运动控制，在进化和认知心理学中也有分支。生物策略和解决方案也与未来的技术和机器人技术高度相关。利用一种基于科塞拉特链元的新方法，将开发一个猎物攻击的计算机模型。该模型将由四名研究人员组成的团队开发：德雷克塞尔大学的Simon Giszter（神经生理学）和Jonathan Nissanov（解剖学，成像），不列颠哥伦比亚大学的Dinesh Pai（计算机科学，生物力学建模）和北亚利桑那大学的Kiisa Nishikawa（神经力学）。冰冻平面显微镜将用于重建牛蛙的感觉运动解剖细节。这些结构将使用基于链的方法来建模，以纳入这些细节。利用这些数据对猎物攻击进行实验和模型分析，将有助于建立固定或自适应模块化机制的优点和局限性，以及在青蛙中使用的生物实施。

The organization of movement is a complex and difficult problem, in part because of a "degrees of freedom problem" in motor control. The richness of an animal's movement possibilities makes its choice of movement controls complex. However, unlike current robots, animals cope efficiently with their degrees of freedom. A newborn wildebeest calf walks with the herd within a few hours of birth. A frog or a turtle, using just its spinal cord, can control complex goal-directed trajectories. The spinal cord can also rapidly correct such movements if they are perturbed. It has been argued that these remarkable capacities are modular, constructed with small sets of primitives or motor building blocks. How such primitives arise and are used is the focus of this project.The concepts of modularity and motor primitives have provided useful descriptions of the organization of spinal motor systems. Modular organization has been shown to support spinal behaviors, and may help to "bootstrap" motor learning. Nonetheless, modularity is controversial at many levels. Spinal primitives might need to be supplanted or augmented in order to perform complex, voluntary behaviors. This project attacks this problem in frog prey strike behaviors, a voluntary and adapted behavior in a system that is fundamentally important to the animal, and has also been well characterized in previous studies of modularity. The neuromechanics of prey strike is examined from a multi-disciplinary perspective. The importance of modular organization in neuroscience and behavior extends well beyond biological motor control, with ramifications in evolutionary and cognitive psychology. Biological strategies and solutions are also highly relevant to future technologies and robotics.A computer model of prey strike will be developed using a novel approach based on Cosserat strand-elements. The model will be developed by a team of four investigators: Simon Giszter (neurophysiology) and Jonathan Nissanov (anatomy, imaging) at Drexel University, Dinesh Pai (computer science, biomechanical modeling) at the University of British Columbia, and Kiisa Nishikawa (neuromechanics) at Northern Arizona University. Cryoplane microscopy will be used to reconstruct bullfrog sensorimotor anatomy in detail. These structures will be modeled using a strand-based approach to incorporate this detail. Experimental and model analyses of prey strike using these data will inform one another to establish the benefits and limits of fixed or adaptive modular mechanisms, and the biological implementation used in frogs.