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: 8731287
• 负责人: Ronald L Calabrese
• 金额: $ 33.42万
• 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/8731287
• 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

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：许多日常节奏活动，如呼吸，咀嚼和咀嚼，部分由称为中央模式发生器（CPG）的神经元网络编程。CPGs的机制分析在无脊椎动物的CPGs中尤其富有成效，无脊椎动物的CPGs具有相对较少的神经元，因此可以根据识别的神经元和特定的突触连接来精确地定义。无脊椎动物的CPG网络已经成为大脑网络如何可靠而灵活地处理感觉信息或程序运动输出的实验和理论分析的代理。我们对水蛭心跳CPG的详细分析继续为我们现在理解网络功能的组织原则做出重大贡献。不同网络和物种的理论研究和实验分析表明，神经元的内在膜特性及其突触连接的强度显示出2-5倍的动物间变异性，但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--表明突触和内在特性的个体差异确实会产生功能性后果，表现在网络性能或对扰动的敏感性上。这些研究意味着，要从根本上理解神经元网络，我们必须努力从个体中收集完整的数据，因为来自个体的网络虽然功能定型，但在膜电流和突触连接水平上可能具有不同的机制基础，并具有可辨别的功能后果。鉴于这种变化，集成建模方法是必要的，以生成和测试有关生活网络的假设。在这种方法中，使用由进化算法或蛮力参数变化生成的多个模型实例（具有不同的参数）。这种方法的先决条件是实验研究，确定各种网络中生命系统的参数变化。我们的实验将整合计算和神经生理学方法，以阐明网络功能的基本机制和网络参数的个体差异的影响。此外，我们将使用个体变异作为一种创新的工具来探测网络功能。水蛭心跳CPG类似于在运动神经元中产生协调的节律活动的脊髓CPG，并且其相对简单和极好的可访问性允许目前在脊髓中不可能的细胞分析水平。我们将分析CPG输入和运动神经元内在特性的个体间差异对运动输出的影响，以及运动如何反映这种变化。这些研究将提供对个体网络功能的基本机制见解，这将有助于脊髓和大脑网络的研究，并可能导致脊髓和大脑损伤以及影响运动表现的疾病的治疗。