Motor learning and memory in health and disease

描述(申请人提供)：当一个人的手从一个点移动到另一个点时，大脑依靠神经结构来引导手臂，这些神经结构可以估计任务的物理动力学，并将所需的运动转换为运动命令。如果我们的手握着一个物体，这些神经结构会考虑到手臂动力学的细微变化，这反映在改变后的运动指令上。这些观察表明，在产生运动指令时，大脑强烈依赖于预测外部世界物理动态的内部模型。内部模型是通过实践学习的，似乎是自愿运动控制的基本部分。然而，我们对大脑中哪些神经结构参与了运动控制内部模型的形成以及它们如何学习表示这些模型知之甚少。我们在这里的目的是结合行为学和数学工具来推断人类是如何学习内部模型的，以及当大脑中特定的运动结构受损时，这一过程是如何受到影响的。我们通过考虑一项任务来解决这个问题，其中达到运动的物理动力学发生了变化。当人们练习这项任务时，我们会问，在给定动作中经历的错误如何影响随后的动作？我们得到了一个泛化函数，它在数学上描述了大脑如何改变内部模型以响应错误。泛化函数的形状预测了参与表示关于运动运动学的内部模型的元素的接受场。我们研究了手臂在位置、速度和加速度空间中的推广函数。初步结果表明，这些行为推断的碱基与初级运动皮质细胞的典型调谐特性有显著的相似之处。这表明，这些细胞的调节特性可能反映在人类行为中，就像我们学习和概括力的模式一样。我们将研究扩展到包括从一只手臂到另一只手臂的泛化。我们进一步将研究扩展到动力学不仅依赖于手臂运动学，而且还依赖于其他线索的运动：外部线索，其中动力学与任意空间或颜色线索相关联，内部线索，动力学依赖于运动在序列中的位置。我们比较了亨廷顿氏病和小脑疾病对大脑的损伤对学习的影响。然而，运动记忆并不是静态的。它们的功能属性在学习任务后的几个小时内发生变化。我们问这种变化如何影响泛化函数。大脑在记忆巩固后对错误的反应方式与在学习阶段早期的不同吗？

DESCRIPTION (provided by applicant): When one moves their hand from one point to another, the brain guides the arm by relying on neural structures that estimate physical dynamics of the task and transform the desired motion into motor commands. If our hand is holding an object, the subtle changes in the dynamics of the arm are taken into account by these neural structures and this is reflected in the altered motor commands. These observations have suggested that in generating motor commands, the brain strongly relies on internal models that predict physical dynamics of the external world. The internal models are learned with practice, and appear to be a fundamental part of voluntary motor control. However, we know very little about which neural structures in the brain are involved in formation of internal models for motor control and how they learn to represent these models. Our aim here is to combine behavioral and mathematical tools to infer how humans learn internal models, and how the process is affected when there is damage to specific motor structures in the brain. We approach the problem by considering a task where physical dynamics of reaching movements are altered. As people practice the task, we ask how did an error that was experienced in a given movement affect subsequent movements? We arrive at a generalization function that mathematically describes how the brain changes the internal model in response to an error. The shape of the generalization function predicts the receptive field of the elements that took part in representing the internal model with respect to movement kinematics. We study these generalization functions in position, velocity, and acceleration space of the arm. Preliminary results demonstrate a remarkable similarity between these behaviorally inferred bases and typical tuning properties of cells in the primary motor cortex. This suggests that tuning properties of these cells might be reflected in human behavior in the way that we learn and generalize patterns of force. We extend the studies to include generalization from one arm to the other. We further extend the studies to movements where dynamics are not dependent only on arm kinematics, but also on other cues: external cues where dynamics are linked to an arbitrary spatial or color cue, internal cues where dynamics depends on position of a movement with in a sequence. We compare how damage to the brain in Huntington's disease vs. cerebellar disease affects this learning. However, motor memories are not static. Their functional properties change within hours after a task is learned. We ask how this change affects the generalization function. Is the brain different in the way it responds to an error after a memory has consolidated vs. early in the learning phase?