MUSCLE PROPERTIES DURING NORMAL MOVEMENT CONDITIONS

正常运动条件下的肌肉特性

• 批准号: 2080786
• 负责人: Charles Heckman
• 金额: $ 6.99万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-01-01 至 1996-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2080786
• 关键词: biological signal transduction; cats; computer simulation; isomer; mechanical pressure; muscle contraction; single cell analysis; striated muscles

Muscles transduce neural signals into the forces needed for movement. Every muscle is composed of a large population of motor units, each of which generates only a very small force. Virtually all previous work on motor unit properties has relied upon isometric conditions (constant muscle length) to facilitate measurement of these small forces. However, isometric conditions constitute only a small portion of normal motor behavior. Furthermore, data from whole muscles and single muscle fibers have shown that muscle tissue has a wide range of dynamic behaviors. The goal of this proposal is to obtain the first systematic measurements of dynamic motor unit properties. While there are many dynamic properties that could be studied in single units, Specific aim 1 proposes to determine which motor unit properties are actually important in normal movement conditions. For example, most muscle models rely only on the steady-state properties of muscle and thus assume dynamic properties play a minor role in force generation. A new decomposition technique has been developed to test this hypothesis. It has 2 phases: (1) techniques for accurately measuring single motor unit forces in dynamic conditions resembling those in normal movements; and (2) measurements in more controlled conditions that are designed to identify the effect of each mechanical property on the unit force output in those normal movement conditions. Specific aims 2&3 focus upon the behavior of motor units as a population of parallel mechanical elements. Since motor units form a heterogeneous population that is activated in order of increasing unit force, the population behavior cannot be predicted from that of any single unit. The hypothesis to be tested is that the population behavior increases the stability of muscle (i.e. its resistance to perturbations). The technique for testing this hypothesis also has 2 phases: (1) measurement of 2 basic motor unit properties that greatly influence stability, the force-velocity and force-length relations; and (20 prediction of population force-velocity-length behavior by use of realistic computer simulations based on these single unit data. These data should provide a foundation for understanding the underlying mechanisms of the functional deficits in diseases affecting both motor units and the control of motor units by the CNS.

肌肉将神经信号转换为运动所需的力。 每块肌肉都由大量的运动单位组成， 它只产生很小的力。 几乎所有以前的工作 运动单位特性依赖于等长条件（恒定 肌肉长度）以便于测量这些小的力。 然而，在这方面， 等长条件仅构成正常运动的一小部分 行为 此外，来自整个肌肉和单个肌纤维的数据 已经表明肌肉组织具有广泛的动态行为。 的 该提案的目标是获得第一个系统的测量， 动态运动单位特性。 虽然有许多动力学性质可以在单个 单位，具体目标1建议确定哪些运动单位属性 在正常的运动条件下是很重要的 比如多数 肌肉模型仅依赖于肌肉的稳态特性， 假设动态特性在力的产生中起次要作用。 一个新 分解技术已被开发来测试这一假设。 它 有两个阶段：（1）精确测量单个电机单元的技术 类似于正常运动的动态条件下的力;以及 (2)在更受控的条件下进行测量， 确定每种机械性能对单位力输出的影响 在正常的运动条件下。 具体目标2和3关注运动单位作为群体的行为 平行的机械元件。 由于运动单位形成了一个异质的 按照单位兵力增加的顺序激活的人口， 种群行为不能从任何单个个体的行为来预测。 要检验的假设是，人口行为增加了 肌肉的稳定性（即对扰动的抵抗力）。 的 检验这一假设的技术也有两个阶段：（1）测量 2个基本的运动单元属性，极大地影响稳定性， 力-速度和力-长度关系;以及（20个预测 种群力-速度-长度行为的计算机模拟 基于这些单个单元数据的模拟。 这些数据应该为理解潜在的 影响运动神经和运动神经的疾病中的功能缺陷的机制 单位和中枢神经系统对运动单位的控制。