Structural and functional brain changes associated with motor learning

 描述（由申请人提供）：运动学习导致多种神经学变化，包括相关任务的能量消耗减少（Picard等人，2013）、灰质体积增加（Draganski等人，2004）和白色物质（WM）组织变化（Scholz等人，2009; Sampaio-Baptista等人，2013）。WM可塑性特别令人感兴趣。髓鞘，轴突的脂肪绝缘体，允许神经冲动的快速和安全的传导。WM的结构变化，特别是髓鞘形成（通过各向异性分数量化）和平均扩散率（MD）的增加，与新运动技能的获得相关（Sampaio-Baptista et al 2013）。髓鞘参与学习、多发性硬化症等神经系统疾病以及抑郁症和精神分裂症等精神疾病（Fields 2008）。然而，两个关键问题仍然存在：1）髓鞘的变化是否是通过成像观察到的WM可塑性的基础？2）运动学习后功能性连接网络的增强程度如何？ 本研究的目的是结合联合收割机行为学、神经影像学和组织学对脑结构和功能的评估来探讨工作记忆的可塑性。具体来说，我们将调查WM的组织学变化，假设与FA和MD的变化相关，通过神经影像学获得。我们还将研究WM组织的变化和功能连接网络的重组作为运动学习的功能。 这项研究将为WM的动态性质提供基础知识，并与运动学习领域和脑损伤（如中风）后的运动康复领域相关。

 DESCRIPTION (provided by applicant): Motor learning leads to a multitude of neurological changes, including reduced energy consumption for the associated task (Picard et al. 2013), increased gray matter volume (Draganski et al. 2004) and changes in white matter (WM) organization (Scholz et al. 2009; Sampaio-Baptista et al. 2013). WM plasticity is of particular interest. Myelin, the fatty insulator of axons, allows for rapid and secure conduction of neural impulses. Structural changes in WM, particularly increases in myelination (as quantified by fractional anisotropy) and mean diffusivity (MD), are associated with the acquisition of new motor skills (Sampaio-Baptista et al 2013). Myelin is involved in learning, neurological disorders such as multiple sclerosis, and psychiatric disorders including depression and schizophrenia (Fields 2008). However, two key questions remain: 1) do changes in myelin underlie the WM plasticity observed with imaging? and 2) to what extent are functional connectivity networks strengthened after motor learning? The objective of the proposed research is to combine behavior, neuroimaging and histological assessments of brain structure and function to explore WM plasticity. Specifically, we will investigate the histological changes in WM hypothesized to be associated with changes in FA and MD as obtained via neuroimaging. We will also investigate changes in WM organization and reorganization of functional connectivity networks as a function of motor learning. The proposed research will provide fundamental knowledge concerning the dynamic nature of WM, and has relevancy to the field of motor learning and the field of motor rehabilitation after brain damage, such as stroke.