IMAGING MECHANISMS OF ACTION IN MOTOR LEARNING

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 目的：本研究的重点是探索运动学习的作用机制。目前的神经成像研究通过探索任务绩效的区域神经活动和区域间活动的变化来研究学习的作用机制。很少有人致力于研究神经连接和突触权重的更根本的变化。本提案旨在开发神经成像的系统级建模策略，并将这些新策略应用于运动学习的作用机制。 研究计划和方法：将进行成像研究，以绘制任务执行策略(以任务执行的区域神经活动衡量)、信息流(以任务执行期间的区域间有效连通性衡量)、突触权重(以与任务无关的静息状态的有效区域连通性衡量)以及运动训练前后这些指标的变化。任务执行策略将使用功能磁共振成像(FMRI)来确定。与任务无关的连接性将通过同步经颅磁刺激/正电子发射断层扫描(TMS/PET)和静息状态fMRI进行测量。结构方程模型，使用由TMS/PET测量和静息状态fMRI测量单独定义的解剖学约束，将被执行以调查在任务执行期间有效的区域间连接。使用扫描电子显微镜对静息状态的fMRI数据进行突触权重测量。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. OBJECTIVE: The focus of this proposal is to explore the mechanisms of action underlying motor learning. Current neuroimaging studies investigate mechanisms of action of learning by exploring the changes in regional neural activity and inter-regional activity of task-performance. Little effort has been given to studying the more fundamental changes of neural connections and synaptic weighting. The present proposal seeks to develop system-level modeling strategies for neuroimaging and to apply these novel strategies to mechanisms of action of motor learning. RESEARCH PLAN AND METHODS: Imaging studies will be performed to map task-performance strategy (measured as regional neural activity of task performance), information flow (measured as effective inter-regional connectivity during task performance), synaptic weighting (measured as task-independent effective inter-regional connectivity during the resting state), and changes in these measures before and after motor training. Task-performance strategy will be determined using functional magnetic resonance imaging (fMRI). Task-independent connectivity will be measured with concurrent transcranial magnetic stimulation/positron emission tomography (TMS/PET) and with resting-state fMRI. Structural Equation Modeling, using anatomical constraints individually defined by the TMS/PET and resting-state fMRI measurements, will be performed to investigate the effective inter-regional connectivity during task performance. Synaptic weighting measurements will be performed on the resting-state fMRI data using SEM.