CDI-Type II: Cyber-Enabled Discovery in Neuromechanical Systems

CDI-Type II：神经机械系统中的网络驱动发现

• 批准号: 0941674
• 负责人: Malcolm MacIver
• 金额: $ 140万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0941674&HistoricalAwards=false
• 关键词: CDI; Type; II; Cyber; Enabled

In the traditional view, the nervous system performs the computational "heavy lifting" in an organism. This view neglects, however, the critical role of biomaterials, passive mechanical physics, and other pre-neuronal or non-neuronal systems. Given that neurons consume forty times more energy per unit mass than structural materials such as bone, it is better, when possible, that biological systems employ relatively inexpensive structural materials rather than relying on more costly neuronal control. In this "bone-brain continuum" view, animal intelligence and behavioral control systems can only be understood using integrative modeling approaches that expose the computational roles of both neural and non-neural substrates and their close coupling in behavioral output. To this end, a group of researchers from Northwestern University, The Johns Hopkins University, and Harvard University propose to create a unique high fidelity neuromechanical model of a vertebrate. The effort is divided between the development of a general purpose computational tool set for neuromechanics research and application of these tools to an ideally suited model system, weakly electric knifefish. The research will lead to breakthroughs in fundamental problems of how nervous systems work together with biomechanics to generate adaptive behavior. The final goal of the research is to construct an integrated neuromechanical model of a unique biological system - weakly electric knifefish - that places biomechanics and neural control on equal footing. Prior such neuromechanical models have used highly simplified models of mechanics and highly abstracted neuronal control approaches. This research advances the state of the art by incorporating high-fidelity mechanics with neuronal mechanisms motivated by direct neurophysiological evidence. Ultimately, this computational approach will help elucidate how animals distribute computations between brain and bone.

在传统观点中，神经系统在生物体中执行计算“繁重的工作”。然而，这种观点忽略了生物材料、被动机械物理和其他前神经元或非神经元系统的关键作用。考虑到神经元每单位质量消耗的能量是骨骼等结构材料的40倍，在可能的情况下，生物系统最好使用相对便宜的结构材料，而不是依赖更昂贵的神经元控制。在这种“骨-脑连续体”的观点中，动物智力和行为控制系统只能通过综合建模方法来理解，这种方法揭示了神经和非神经基质的计算作用以及它们在行为输出中的密切耦合。为此，来自美国西北大学、约翰霍普金斯大学和哈佛大学的一组研究人员提议创建一种独特的高保真脊椎动物神经力学模型。这项工作分为开发用于神经力学研究的通用计算工具集和将这些工具应用于理想的模型系统弱电刀鱼。这项研究将在神经系统如何与生物力学一起产生适应性行为的基本问题上取得突破。这项研究的最终目标是为一个独特的生物系统——弱电刀鱼——构建一个集成的神经力学模型，将生物力学和神经控制置于同等地位。先前的神经力学模型使用了高度简化的力学模型和高度抽象的神经元控制方法。这项研究通过将高保真力学与直接神经生理学证据驱动的神经元机制结合起来，推进了目前的技术水平。最终，这种计算方法将有助于阐明动物如何在大脑和骨骼之间分配计算。