Constancy and Variability in a Motor Program: CPG to Motor Performance

运动程序的恒定性和可变性：CPG 到运动性能

• 批准号: 8609260
• 负责人: Ronald L Calabrese
• 金额: $ 33.76万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8609260
• 关键词: Address; Affect; Algorithms; Animals; Behavior; Biological Models; Brain; Brain Diseases; Breathing; Clinical; Data; Disease; Ensure; Future; Goals; Heart; Image; Individual; Injury; Invertebrates; Ion Channel; Lead; Leeches; Life; Light; Mastication; Measures; Membrane; Modeling; Motor; Motor Neurons; Motor output; Movement; Muscle; Myocardial Contraction; Neurons; Organism; Outcome; Output; Pattern; Performance; Predisposition; Property; Proxy; Relative (related person); Role; Sensory Process; Spinal; Spinal Cord; Stereotyping; Synapses; Testing; Theoretical Studies; Variant; Work; brain pathway; central pattern generator; experimental analysis; innovation; insight; neurophysiology; programs; public health relevance; research study; spinal cord and brain injury; tool; voltage clamp

Project Summary Many everyday rhythmic activities such as breathing, chewing, and locomoting, are programed in part by neuronal networks called central pattern generators (CPGs). Mechanistic analysis of CPGs has been especially fruitful in the CPGs of invertebrates, which have relatively few neurons and can therefore be precisely defined in terms of identified neurons and specific synaptic connections. CPG networks of invertebrates have become proxies for experimental and theoretical analyses of how brain networks reliably yet flexibly process sensory information or program motor output. Our detailed analyses of the leech heartbeat CPG continue to contribute substantially to the organizing principles by which we now understand network function. Theoretical studies and experimental analysis in different networks and species have shown that the intrinsic membrane properties of the neurons and the strengths of their synaptic connections show 2-5 fold animal-to-animal variability, yet networks still produce functional output. Nevertheless, there are clear examples - including from our own work - showing that individual variation in synaptic and intrinsic properties do have functional consequences that manifest in network performance or susceptibility to perturbation. These studies imply that to understand fundamentally a neuronal network, we must strive to gather complete data from individuals because networks from individuals, while functionally stereotyped, may have different mechanistic underpinnings at the level of membrane currents and synaptic connections with discernible functional consequences. In light of this variation, an ensemble modeling approach is necessary to generate and test hypotheses about living networks. In this approach, multiple model instances (with different parameters) generated by evolutionary algorithms or brute force parameter variation are used. A prerequisite for this approach is experimental studies that determine parameter variation in the living system across a variety of networks. Our experiments will integrate computational and neurophysiological approaches to elucidate basic mechanisms of network function and the impact of individual variation in network parameters. Moreover, we will use individual variation as an innovative tool to probe network function. The leech heartbeat CPG is analogous to spinal CPGs that produce coordinated rhythmic activity in motor neurons, and its relative simplicity and superb accessibility allow a level of cellular analysis not currently possible in spinal cord. We will analyze the impact of inter-individual variation in CPG input and motor neuron intrinsic properties on motor output and how movements reflect this variation. These studies will provide basic mechanistic insights into network function in individuals, which will be useful in the study of spinal and brain networks and can lead to therapies for spinal cord and brain injury and disorders affecting motor performance.

项目摘要 许多日常有节奏的活动，如呼吸、咀嚼和运动，部分是由 神经网络被称为中枢模式生成器(CPG)。对CPG的力学性能进行了分析。 尤其是在无脊椎动物的CPG中成果丰硕，无脊椎动物的神经元相对较少，因此可以 根据已识别的神经元和特定的突触连接进行精确定义。CPG网络 无脊椎动物已经成为大脑网络如何可靠地进行实验和理论分析的替代品 还可以灵活地处理感官信息或编程运动输出。我们对水蛭心跳的详细分析 中央人民政府继续为我们现在了解网络的组织原则做出重大贡献 功能。不同网络和物种的理论研究和实验分析表明， 神经元的固有膜特性及其突触连接的强度显示2-5倍 动物之间的可变性，然而网络仍然产生功能输出。尽管如此，有明确的 例子-包括我们自己的工作-表明突触和内在属性的个体差异 确实会产生功能后果，表现为网络性能或易受干扰影响。这些 研究表明，为了从根本上理解神经网络，我们必须努力收集完整的数据。 来自个人的，因为来自个人的网络，虽然在功能上刻板，但可能有不同的 在膜电流和突触连接水平上的机械性基础 功能后果。考虑到这种变化，需要一种集成建模方法来生成 并测试关于生活网络的假设。在这种方法中，多个模型实例(具有不同的 参数)由进化算法或强力参数变化产生。一个先决条件 因为这种方法是通过实验研究来确定生命系统中的参数变化 各种各样的网络。我们的实验将结合计算和神经生理学方法 阐明网络功能的基本机制以及网络参数中个体差异的影响。 此外，我们还将利用个体差异作为探索网络功能的创新工具。 水蛭心跳CPG类似于在运动中产生协调节律活动的脊椎CPG 神经元，以及它的相对简单和卓越的可及性，使得细胞分析达到了目前无法达到的水平 可能是在脊髓。我们将分析CPG输入和运动神经元的个体间差异的影响 电机输出的内在属性以及运动如何反映这种变化。这些研究将提供基本的 对个体网络功能的机械性洞察，这将有助于脊椎和大脑的研究 它是一种神经网络，可用于治疗脊髓和脑损伤以及影响运动能力的疾病。