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

动物被认为是在15亿年前从植物中分化出来的。这种分裂的基础是获得生命所需能量的不同策略：对于植物来说，它是“呆在原地并吸收”，而对于动物来说，它是“四处移动并抓取”。一旦运动进入场景，两种完全不同的运动状态也会发生：第一种是“粘性”状态，动物一旦停止产生运动力，就会停止运动;第二种是“动态”状态，动物即使停止产生这种力，也会继续运动。对于我们的流体束缚祖先来说，这种转变发生在大约6亿年前的多细胞动物的黎明。在动态状态下，运动的控制要困难得多，这是机器人系统工程中众所周知的事实。这就为神经系统提出了一个需要解决的基本问题：如何将感觉信号转换为运动信号，以解释动物的动态约束。 MacIver博士将领导一个由神经科学、机器人技术和流体动力学专业人员组成的多学科研究小组，以了解弱电鱼Apteronotus albifrons的大脑如何将感觉信号转化为运动信号，并特别关注鱼的动态约束如何影响这种转化。研究人员假设，支持这种转变的神经结构被简化为与任务动态相协调的感觉和运动能力。该团队的研究目标是：1）重建捕获猎物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，用于将重建的大脑输入转换为估计的肌肉激活信号。真实的鱼和虚拟鱼与现实的传感和力学实验将结合起来，以测试几个关键的假设，包括声称，一个轨迹的猎物，最大限度地减少动物的努力将是相同的，最大限度地减少不确定性的行为有关的属性的猎物，如它的位置。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技术等领域进行跨学科的努力。这项研究将具有广泛的适用性，以了解动物的感觉运动转换的原则。该小组还预计，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，并将开发一个机器鱼装置，向公众介绍这种多学科研究。

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.