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。变化 特定回路中的突触连接是经验依赖性回路修饰的基础， 学习对这一过程的详细了解是重要的，而不仅仅是了解 学习，而且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 老年痴呆症和帕金森病。我们的最终目标是了解精确的，精细的- 规模电路修改，支持学习。 学习的基本形式之一是运动学习，在这种学习中，动物调整它们的运动方式 以适应他们的行为目标。在参与运动学习的许多脑区中， 运动皮层（M1）是运动学习期间发生变化的主要部位。许多类型的变化， M1已经被描述为伴随运动学习，包括躯体位置图、神经元和神经元的变化。 群体活动变化和突触可塑性。然而，目前还不清楚M1是否总是参与 在整个学习和过度训练过程中的动作控制。此外，精确的功能重组 在运动学习过程中M1的突触输入才刚刚开始被理解。我们会解决这两个问题 使用尖端技术的问题。头部固定的小鼠将在基于前肢的训练中训练。 运动神经学习任务。在目标1中，我们将对M1神经群进行纵向记录 几个月的运动学习和过度训练。结合M1活性的光遗传学扰动， 不同阶段的训练，我们测试的假设，是依赖于M1的运动在学习早期 可以通过长期过度训练变得M1独立。这也将确定在此期间， 我们在提案中使用的特定运动任务关键取决于M1。在这一时期，当M1 对于运动表现至关重要，我们将研究M1中突触的精确功能重组。我们将尽 这使用突触分辨率的纵向功能成像。特别是，我们将测试假设， 运动学习诱导与所学习的运动相关的突触输入的功能聚集。等 功能聚类将允许学习相关信息鲁棒地驱动电路激活。这些 实验将有助于运动学习的基本神经回路机制。这种知识 最终可能有助于更好地诊断和治疗运动障碍，如帕金森氏病， 和中风

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.