Neural Control of Grasping

抓取的神经控制

• 批准号: 7494478
• 负责人: MARCO SANTELLO
• 金额: $ 24.96万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7494478
• 关键词: Address; Behavior; Behavioral; Clinical; Complex; Condition; Control Groups; Coupling; Data; Digit structure; Electromyography; Exhibits; Fingers; Flexor; Freedom; Frequencies; Funding; Hand; Hand functions; Human; Individual; Joints; Kinetics; Knowledge; Literature; Measures; Mechanics; Mediating; Motion; Motor; Muscle; Nervous System Trauma; Neuraxis; Numbers; Operative Surgical Procedures; Outcome; Pattern; Population; Production; Public Health; Range; Rehabilitation therapy; Relative (related person); Statistically Significant; Stroke; Testing; Thumb structure; Time; Work; base; design; desire; grasp; improved; indexing; insight; kinematics; multitask; neuromechanism; neuroregulation; relating to nervous system; research study; restoration; tool; vector

DESCRIPTION (provided by applicant): Important features of the kinetics and kinematics of human object grasping and manipulation have been characterized, providing significant insight into how the Central Nervous System controls the hand. However, the underlying neural mechanisms that regulate the activity of multiple hand muscles are not yet well understood. This gap in our understanding of hand control has significant clinical implications for rehabilitation of hand function following neurological injury such as stroke. In our previous work we focused on correlated neural input to hand muscles to quantify the neural bases of force coordination during object grasping. We found that correlated neural input is distributed in a muscle-pair specific fashion, i.e., the neural coupling between certain muscle pairs is stronger than that between other muscle pairs. However, within this distribution, the strength of neural coupling of given muscle pairs could be modulated to task conditions. Yet, these results were obtained from a relatively small number of muscles and limited range of task conditions (grip type and object center of mass). The aim of the present study is to determine the neural mechanisms underlying a crucial aspect of hand control: the modulation of digit force direction. To attain this objective we will quantify the modulation of (a) EMG amplitude and (b) correlated neural input (coherence) of all muscles of the thumb, index and middle fingers as a function of digit force direction. Our working hypotheses are that (1) a force-direction dependent modulation of coherence between two muscles will occur as the relative force contribution of a given muscle to the modulation of fingertip force direction changes and (2) coherence modulation will occur within an invariant distribution of correlated neural input among hand muscle pairs. These hypotheses will be tested through one-digit force production tasks and multi-digit grasping tasks (Aim#1 and #2, respectively). The outcomes of our experiments will establish how motor commands controlling groups of hand muscles are modulated as a function of force direction and task constraints. Our data are expected to improve our understanding of the control of prehension, specifically the principles underlying fundamental mechanisms of synergistic control of hand muscles for object grasping and manipulation. Relevance to public health: We believe that this knowledge will be beneficial to rehabilitation and restoration of hand function as well as to the field of neuroprosthetics.

描述（由申请人提供）：已经表征了动力学的重要特征和人类物体抓握和操纵的运动学特征，从而对中枢神经系统如何控制手提供了重要的见解。但是，调节多手肌肉活性的潜在神经机制尚未得到充分了解。在我们对手控制的理解中，这种差距对神经系统损伤（例如中风）的手部功能的康复具有重要的临床意义。在以前的工作中，我们专注于将肌肉手动的神经输入相关联，以量化物体抓紧过程中力协调的神经底座。我们发现，相关的神经输入是以肌肉对特定方式分布的，即，某些肌肉对之间的神经耦合比其他肌肉对之间的神经耦合要强。但是，在这种分布中，可以调节给定肌肉对的神经偶联的强度。然而，这些结果是从相对少量的肌肉和有限的任务条件（grip类型和质量中心）获得的。本研究的目的是确定手部控制关键方面的神经机制：数字力方向的调节。为了实现这一目标，我们将量化（a）EMG振幅的调制，以及（b）与数字力方向的关系，拇指，索引和中指的所有肌肉的神经输入（相干）相关。我们的工作假设是（1）由于给定肌肉对指尖力方向的调节调节的相对力贡献，两种肌肉之间的相干性的依赖性调节将发生，并且（2）连贯性调节将发生在手肌肉对中相关神经输入的不变分布中。这些假设将通过一位数的力量生产任务和多位数的掌握任务进行检验（AIM＃1和＃2）。我们实验的结果将确定如何根据力方向和任务约束来调制手机命令。期望我们的数据能够提高我们对预性控制的理解，特别是对手动肌肉进行对象抓握和操纵的协同控制的基本机制的基本原理。与公共卫生相关：我们认为，这种知识将有助于康复和恢复手部功能以及神经假想领域。