Transforming Sensory Signals into Muscle Activations in a Behavior with Dynamic Constraints

动物被认为是在15亿多年前从植物中分化出来的。这种分裂的基础是获取生命所需能量的不同策略：对植物来说，它是“留在原地并吸收”，而对动物来说，它是“四处走动并抓取”。运动一进入场景，两种完全不同的运动模式也会发生：第一种是粘性模式，动物一旦停止产生运动力就会停在轨道上；第二种是动态模式，在这种模式下，动物即使停止产生这种力也会继续运动。对于我们的流体结合的祖先来说，这种转变发生在大约6亿年前多细胞动物的黎明。在动态状态下，运动控制要困难得多，这是机器人系统工程中众所周知的事实。这设定了神经系统要解决的根本问题：以一种解释动物动态约束的方式将感觉信号转换为运动信号。MacIver博士将带领一个拥有神经科学、机器人学和流体动力学专业知识的多学科研究小组，了解弱电动鱼类Apteronotus albirons的大脑如何将感觉信号转换为运动信号，并特别关注鱼类的动态约束如何影响这种转换。研究人员假设，支持这种转变的神经结构因感觉和运动能力而简化，这些能力与任务的动态很好地协调。该团队的研究目标是1)重建猎物捕获行为期间发生的肌肉激活；2)重建猎物在此行为期间到达大脑的感觉信息；3)开发一个计算框架，将重建的大脑输入转换为估计的肌肉激活信号。对真实鱼类和具有真实感知和机械性能的虚拟鱼类的实验将被结合起来，以检验几个关键假设，包括以下说法：最大限度地减少动物努力的猎物轨迹将与最大限度地减少猎物行为相关特性(如位置)的不确定性。这些研究需要在神经生物学、计算神经科学、流体动力学和机器人学方面进行雄心勃勃的跨学科努力。这项研究将对理解动物感觉运动转换的原理具有广泛的适用性。该小组进一步预计，他们在运动流体动力学方面的工作将应用于动物飞行和游泳，以及微型空气和水上交通工具的工程。该项目还将让本科生参与研究的各个方面，并将开发一种机器鱼装置，让公众了解这种类型的多学科研究。

Animals are thought to have diverged from plants more than 1.5 billion years ago. Basic to this split are different strategies for obtaining the energy needed for life: for a plant, it is "stay in place and absorb," and for an animal, it is "move around and grab." As soon as motion enters the scene, so do two quite different regimes under which motion can occur: the first is the "viscous" regime, in which an animal will stop in its tracks as soon as it ceases generating locomotory forces, and the second is the "dynamic" regime, in which an animal will keep moving even after it ceases generating such forces. For our fluid-bound ancestors, this transition occurred with the dawn of the multicellular animals around 0.6 billion years ago. Control of motion is much more difficult in the dynamic regime, a fact well known in the engineering of robotic systems. This sets the fundamental problem for nervous systems to solve: the transformation of sensory signals into motor signals in a manner that accounts for the animal's dynamic constraints. Dr. MacIver will lead a multidisciplinary group of researchers with expertise in neuroscience, robotics, and fluid dynamics to understand how sensory signals are transformed into motor signals by the brain of weakly electric fish, Apteronotus albifrons, with particular attention paid to how the dynamic constraints of the fish affect this transformation. The researchers hypothesize that neural structures supporting this transformation are simplified by sensory and motor capabilities that are well tuned to the dynamics of the task. The team's research objectives are to 1) reconstruct muscle activations occurring during prey-capture behavior; 2) reconstruct the sensory information about the prey reaching the brain during this behavior; and 3) develop a computational framework for transforming the reconstructed brain input into the estimated muscle activation signals. Experiments on real fish and on a virtual fish with realistic sensing and mechanics will be combined to test several key hypotheses, including the claim that a trajectory to the prey that minimizes the animal's effort will be identical to one that minimizes uncertainty about behaviorally relevant properties of the prey, such as its location. These studies require an ambitious interdisciplinary effort in neurobiology, computational neuroscience, fluid dynamics, and robotics. The research will have broad applicability to understanding the principles of sensorimotor transformations in animals. The group further expects that their work on the fluid dynamics of locomotion will have applications to animal flight and swimming, and the engineering of micro-air and aquatic vehicles. The project will also involve undergraduate students in aspects of the research and will develop a robotic fish installation to inform the public about this type of multidisciplinary research.