Coordinating movements using optimal control: A neuro-computational perspective

使用最佳控制协调运动：神经计算视角

• 批准号: BB/E009174/1
• 负责人: Jörn Diedrichsen
• 金额: $ 36.8万
• 依托单位: Bangor University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE009174%2F1
• 关键词: Coordinating; movements; using; optimal; control

Much of the research on human motor control has examined how humans move a single body part, such as the arm or the eyes. Our everyday actions, however, consist of movements of multiple body parts at the same time. For example, we use both hands to tie our shoes. Even the simple act of raising one arm is accompanied by changes in leg muscles to stabilize stance. For many patients with neurological strokes or disorders, these complex movement skills often cause problems even after simple movements of isolated limbs have recovered. Compared to single limb movements, however, we know very little about how the nervous system achieves coordination between movements of different body parts. We have gained some insights into how the brain coordinates complex movements through experiments in which human volunteers are instructed to produce two different movements at the same time. These experiments have identified fundamental limitations in our ability to move two limbs independently. For example it is quite difficult to rub one's belly and to simultaneously pat one's head. Further experimentation however, has made clear that these limitations are generally not hard-wired into the motor system. Rather they depend crucially on what the goals of the movements are. For example, movements of the two hands can depend strongly upon one another when we manipulate a single object with two hands, and they can be controlled quite independently when we reach out for two separate objects. To understand how the brain coordinates movements in these different situations, we will study how human volunteers learn motor tasks in which the hands must be coordinated to achieve different goals. We will apply approaches from engineering and control theory to predict how, given a specific task goal, an organism should optimally coordinate movements, and will then test these predictions. We will also investigate how specifically the brain achieves optimal control in coordination. For example, what signals are exchanged between regions of the brain that control different movement components? Does coordination depend on 'muscle memory' / a memorized set of activation patterns in particular muscles? Or do different body parts 'talk' to each other by exchanging information about their current position and velocity? How do the ways in which these areas communicate change as coordination skills become more automatic through training? Functional magnetic resonance imaging (fMRI) will be used to measure brain activity in human volunteers while they perform coordination tasks. By changing the goals and requirements of the task, we will be able to identify neural areas that are involved in coordinating movements and specify their function. For example, when we grasp an object we have to coordinate the arm movement and the opening of the hand for grasping. Which neural areas are involved in estimating how far the arm has moved already towards the target, an important signal for deciding when to start the grasp? Which neural areas take these estimates and initiate the opening of the hand? Understanding how the brain coordinates movements and which areas of the brain are involved in this task is essential for understanding the coordination problems faced by patients affected by strokes or brain disorders. This work will provide a theoretical foundation that can lead to new treatments and rehabilitation programs designed to facilitate the ability of these individuals to produce complex motor skills, those that go beyond the control requirements for producing simple movements.

许多关于人类运动控制的研究都是研究人类如何移动身体的一个部位，比如手臂或眼睛。然而，我们的日常活动是由多个身体部位同时运动组成的。例如，我们用双手系鞋带。即使是举起一只手臂的简单动作，也伴随着腿部肌肉的变化，以稳定立场。对于许多患有神经性中风或疾病的患者来说，即使在孤立肢体的简单运动已经恢复之后，这些复杂的运动技能也常常会引起问题。然而，与单肢运动相比，我们对神经系统如何实现不同身体部位运动之间的协调知之甚少。我们已经通过实验对大脑如何协调复杂的动作有了一些了解，在这些实验中，人类志愿者被指示同时产生两个不同的动作。这些实验已经确定了我们独立移动两个肢体的能力的基本限制。例如，揉肚子的同时拍头是相当困难的。然而，进一步的实验已经清楚地表明，这些限制通常不会硬连线到电机系统中。相反，它们主要取决于运动的目标是什么。例如，当我们用两只手操纵一个物体时，两只手的运动可能强烈地依赖于彼此，而当我们伸手去拿两个单独的物体时，它们可以被完全独立地控制。为了了解大脑如何在这些不同的情况下协调运动，我们将研究人类志愿者如何学习运动任务，其中双手必须协调以实现不同的目标。我们将应用工程和控制理论的方法来预测，给定一个特定的任务目标，生物体应该如何最佳地协调运动，然后将测试这些预测。我们还将研究大脑如何具体实现协调的最佳控制。例如，控制不同运动成分的大脑区域之间交换了什么信号？协调是否依赖于“肌肉记忆”/特定肌肉的一组记忆激活模式？还是不同的身体部位通过交换当前位置和速度的信息来相互“交谈”？随着协调技能通过培训变得更加自动化，这些领域的沟通方式如何改变？功能性磁共振成像（fMRI）将用于测量人类志愿者在执行协调任务时的大脑活动。通过改变任务的目标和要求，我们将能够识别参与协调运动的神经区域，并指定它们的功能。例如，当我们抓住一个物体时，我们必须协调手臂的运动和手的张开。哪些神经区域参与估计手臂已经向目标移动了多远，这是决定何时开始抓握的重要信号？哪些神经区域接受这些估计并开始张开手？了解大脑如何协调运动，以及大脑的哪些区域参与了这项任务，对于理解中风或大脑疾病患者所面临的协调问题至关重要。这项工作将提供一个理论基础，可以导致新的治疗和康复计划，旨在促进这些人产生复杂的运动技能的能力，那些超越了产生简单运动的控制要求。

项目成果

Dissociating timing and coordination as functions of the cerebellum.

• DOI: 10.1523/jneurosci.0061-07.2007
• 发表时间: 2007-06-06
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Diedrichsen J;Criscimagna-Hemminger SE;Shadmehr R
• 通讯作者: Shadmehr R

Use-Dependent and Error-Based Learning of Motor Behaviors

• DOI: 10.1523/jneurosci.5406-09.2010
• 发表时间: 2010-04-14
• 期刊: JOURNAL OF NEUROSCIENCE
• 影响因子: 5.3
• 作者: Diedrichsen, Joern;White, Olivier;Lally, Niall
• 通讯作者: Lally, Niall

Optimal task-dependent changes of bimanual feedback control and adaptation.

• DOI: 10.1016/j.cub.2007.08.051
• 发表时间: 2007-10-09
• 期刊: CURRENT BIOLOGY
• 影响因子: 9.2
• 作者: Diedrichsen, Jorn

Bimanual coordination as task-dependent linear control policies

• DOI: 10.1016/j.humov.2008.10.003
• 发表时间: 2009-06-01
• 期刊: HUMAN MOVEMENT SCIENCE
• 影响因子: 2.1
• 作者: Diedrichsen, Joern;Dowling, Noreen
• 通讯作者: Dowling, Noreen

Dissociating variability and effort as determinants of coordination.

• DOI: 10.1371/journal.pcbi.1000345
• 发表时间: 2009-04
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: O'Sullivan I;Burdet E;Diedrichsen J
• 通讯作者: Diedrichsen J