The multiple components of motor memory

运动记忆的多个组成部分

• 批准号: 8543777
• 负责人: REZA SHADMEHR
• 金额: $ 36.29万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8543777
• 关键词: Affect; Area; Basic Science; Brain; Cerebellar Diseases; Cerebellum; Cerebral cortex; Chemosensitization; Feedback; Learning; Maps; Memory; Modeling; Motor; Motor Cortex; Motor Evoked Potentials; Motor output; Movement; Neural Pathways; Outcome; Output; Patients; Performance; Phase; Procedures; Process; Rehabilitation therapy; Research; Response Latencies; Rewards; Schedule; Sensory; Series; Staging; Structure; Techniques; Testing; Training; Translating; Work; base; biceps brachii muscle; expectation; field study; improved; motor control; motor learning; novel; prevent; public health relevance; rehabilitation strategy; relating to nervous system; research study; response; sensory feedback

DESCRIPTION (provided by applicant): Our ability to adapt to systematic perturbations makes it possible to maintain a lifetime of calibrated movements. Our focus here is on the neural basis of this motor memory. The current view is that adaptation depends critically on the cerebellum. However, over the last two years we, and others, have made a series of observations that challenge this view of adaptation. Here we suggest a different view of the problem of motor adaptation based on the core hypothesis that the cerebellum is embedded in a larger network that includes motor cortical areas, and that more than one mechanism is involved in forming a motor memory. Specifically, we suggest that motor memory is a result of interaction of distinct components: one component associates motor commands with sensory consequences, resulting in a forward model; one component searches the motor space for output that can produce a rewarding outcome, resulting in exploration; a third component relies on repetition to associate the sensory feedback with the motor commands, resulting in a feedback- dependent controller. In Aim 1, we will test that idea that the function of M1 during adaptation is to encode a component of motor memory that depends on reinforced repetition of motor commands. In Aim 2, we will test the hypothesis that damage to the cerebellum affects only one component of motor memory, the ability to form memories that depend on sensory prediction errors (forward models), but spares the ability to learn from repetition of motor commands. Our projects are clinically important because if we are right in that there are multiple neural pathways to formation of motor memory, then damage to one component may benefit from rehabilitation procedures that focus on remaining healthy neural structures. Our projects are important from a basic science standpoint because: (1) our experiments can connect the cerebellar-centric field of adaptation which has focused on error-dependent learning, with cerebral cortex-centric field of motor learning which has focused on repetition-dependent processes; (2) our experiments have the power to explain what is being 'prepared' by the brain during the preparatory period before movement onset; and finally (3) our experiments have the potential to actually test computational ideas that are very much in fashion in the field of optima control, and ask whether they have any relevance to the neural basis of motor control.

描述（由申请人提供）：我们适应系统扰动的能力使我们能够在整个生命周期内维持校准运动。我们这里的重点是这种运动记忆的神经基础。目前的观点是，适应很大程度上取决于小脑。然而，在过去的两年里，我们和其他人进行了一系列观察，挑战了这种适应观点。在这里，我们基于核心假设提出了对运动适应问题的不同看法，即小脑嵌入到包括运动皮质区域的更大网络中，并且不止一种机制参与形成运动记忆。具体来说，我们认为运动记忆是不同组件相互作用的结果：一个组件将运动命令与感官结果相关联，从而产生正向模型；​​另一个组件将运动命令与感官结果相关联，从而产生正向模型；一个组件在运动空间中搜索可以产生有益结果的输出，从而产生探索；第三个组件依靠重复将感觉反馈与运动命令相关联，从而形成依赖于反馈的控制器。在目标 1 中，我们将测试这样的想法：M1 在适应过程中的功能是对运动记忆的一个组成部分进行编码，该组成部分依赖于运动命令的强化重复。在目标 2 中，我们将检验以下假设：小脑损伤仅影响运动记忆的一个组成部分，即形成依赖于感觉预测误差（前向模型）的记忆的能力，但不影响从重复运动命令中学习的能力。我们的项目在临床上很重要，因为如果我们的观点是正确的，运动记忆的形成有多种神经通路，那么针对某一部分的损伤可能会受益于专注于保持健康神经结构的康复程序。从基础科学的角度来看，我们的项目很重要，因为：（1）我们的实验可以将以小脑为中心的适应领域（专注于错误依赖学习）与以大脑皮层为中心的运动学习领域（专注于重复依赖过程）联系起来； （2）我们的实验能够解释大脑在运动开始前的准备阶段正在“准备”什么；最后（3）我们的实验有可能实际测试最优控制领域非常流行的计算思想，并询问它们是否与运动控制的神经基础有任何相关性。