Cortical Control of Motor Learning

项目摘要 从经验中学习的能力是神经回路最基本的特征之一。中的更改 特定电路中的突触连接是经验依赖的电路修改的基础，这些修改对于 学习。对这一过程的详细了解非常重要，而不仅仅是为了了解 学习，也是为了更好地诊断和治疗影响记忆能力的疾病，如阿尔茨海默氏症 疾病、与衰老相关的痴呆和帕金森氏症。我们的最终目标是了解精确的、精细的- 调整支持学习的电路修改。 学习的基本形式之一是运动学习，动物在运动学习中调整它们的移动方式 他们的身体，以符合他们的行为目标。在参与运动学习的许多大脑区域中，主要的 运动皮质(M1)是运动学习过程中发生变化的一个主要部位。中的许多类型更改 已经描述了伴随运动学习的M1，包括躯体定位图、神经 种群活动变化和突触可塑性。然而，目前尚不清楚M1是否总是参与 在学习和过度训练过程中控制动作。此外，精确的功能重组 运动学习过程中M1中突触输入的变化才刚刚开始被理解。我们将解决这两个问题 在老鼠身上使用尖端技术的问题。头部固定的小鼠将在前肢基础上进行训练 连续几周每天完成运动学习任务。在目标1中，我们将对M1神经元群进行纵向记录 在运动学习和过度训练的几个月里。与M1活动的光发生扰动相结合 在训练的不同阶段，我们检验了一种假设，即在早期学习时依赖于M1的运动 可以在长期过度训练的情况下独立于M1。这也将定义在什么时间段内 我们在提案中使用的特定运动任务在很大程度上取决于M1。关注这段时间，M1是 对运动性能至关重要的是，我们将研究M1中突触的精确功能重组。我们会做的 这使用了突触分辨率的纵向功能成像。具体地说，我们将测试假设 运动学习诱导与习得动作相关的突触输入的功能性聚集。是这样的 功能集群将允许与学习相关的信息有力地驱动电路激活。这些 实验将有助于运动学习的基本神经回路机制。这样的知识 可能最终有助于更好地诊断和治疗运动障碍，如帕金森氏病 还有中风。

Project Summary The ability to learn from experience is one of the most fundamental features of neural circuits. Changes in synaptic connections in specific circuits underlie experience-dependent circuit modifications essential for learning. A detailed understanding of this process is important, not just to understand the mechanisms of learning, but also to better diagnose and treat conditions that affect memory abilities, such as Alzheimer's disease, aging-related dementia, and Parkinson's disease. Our ultimate goal is to understand the precise, fine- scale circuit modifications that support learning. One of the fundamental forms of learning is motor learning in which animals adjust the way they move their bodies to fit their behavioral goals. Among a number of brain areas involved in motor learning, the primary motor cortex (M1) is a major locus where changes take place during motor learning. Many types of changes in M1 have been described that accompany motor learning, including changes of the somatotopic map, neural population activity changes, and synaptic plasticity. However, it is unclear whether M1 is always involved in the control of movements throughout learning and overtraining. Furthermore, the precise functional reorganization of synaptic inputs in M1 during motor learning is only beginning to be understood. We will address these two questions using cutting-edge technologies in mice. Mice under head-fixation will be trained in a forelimb-based motor learning task daily over weeks. In Aim 1, we will perform longitudinal recording of M1 neural populations during months of motor learning and overtraining. Combined with optogenetic perturbation of M1 activity at various phases of training, we test the hypothesis that a movement that is dependent on M1 early in learning can become M1-independent with long-term overtraining. This will also define the period during which the particular motor task we use in the proposal depends critically on M1. Focusing on this period when M1 is critical for motor performance, we will study precise functional reorganization of synapses in M1. We will do this using longitudinal functional imaging at synaptic resolution. In particular, we will test the hypothesis that motor learning induces functional clustering of synaptic inputs related to the learned movements. Such functional clustering would allow the learning-related information to robustly drive circuit activation. These experiments will contribute fundamental neural circuit mechanisms underlying motor learning. Such knowledge could ultimately contribute to a better diagnosis and treatment of motor disorders such as Parkinson's disease and stroke.