Training-related motor plasticity and the representation of skill

运动技能是我们与世界互动的重要组成部分，但我们关于大脑结构和功能如何支持运动技能习得的模型却严重不足--几乎完全缺乏支持神经可塑性的生理机制的任何证据。大多数运动神经可塑性研究只使用一组在短时间内（主要是一天内或两天内）接受单一任务训练的参与者，因此很难识别与学习本身相关的过程或得出有关自然主义学习的结论，这通常需要数天、数周或数月的训练。此外，成像研究绝大多数只调查了一个或两个既不是定量的也不是与大脑生理学密切相关的成像指标;这使得既难以进行纵向比较，也无法推断可塑性的生理标志物。如果没有一个更完整的模型来解释生理过程（如髓鞘形成、树突状分支和血管增殖）如何支持可塑性，我们的理解将局限于“变化”发生的地点和时间，而没有迹象表明发生了什么变化。因此，我们必须开发一个更生理信息的框架，以产生更具体的机制模型的时间过程中的人类神经可塑性。 我的总体研究目标是更深入地了解大脑如何通过神经可塑性过程支持运动技能的获得。这里提出的短期目标将开发一个生理上知情的人类运动神经可塑性模型：确定大脑的区域，支持序列特异性可塑性本身（以上的性能的影响），表征其变化的时间过程，并确定假定的神经生理机制，支持神经可塑性。拟议的工作是基于一个独特的和丰富的超高场（7 T）多模态定量磁共振成像（MRI）数据集，以前收集的我和colloborators。两组20名参与者（主动，控制）进行了培训的视觉运动序列学习任务的精细运动控制（顺序捏力任务），连续5天。每天采集多模式定量MRI，包括对髓鞘、细胞密度、组织显微结构、静息血流量、血容量和铁敏感的序列。这个独特的数据集将由HQP使用，包括2名博士和3名硕士，以开发结构，功能和多模态训练相关神经可塑性的生理学模型，关键是利用我们对收集的多模态定量MRI指标的生理起源的了解，以确定训练相关神经可塑性的机械时程。总之，拟议中的研究是对我们的大脑如何学习运动技能的机械理解的关键的第一步。

Motor skills are a crucial component of our interaction with the world, yet our models for how the structure and function of the brain support their acquisition are severely underspecified - almost completely lacking any evidence for the physiological mechanisms that support neuroplasticity. Most motor neuroplasticity studies use only a single group of participants trained on a single task over a short period of time (predominantly within a single day or across two), making it difficult to identify processes linked to learning per-se or draw conclusions about naturalistic learning that often requires days, weeks, or months of training. In addition, imaging studies overwhelmingly investigate only one or two imaging metrics that are neither quantitative nor strongly linked to brain physiology; making it both difficult to perform longitudinal comparisons and impossible to make inferences about the physiological markers of plasticity. Without a more complete model for how physiological processes (such as myelination, dendritic arborization, and vascular proliferation) support plasticity, our understanding will be limited to where and when "change" occurred, with no indication of what changed. Thus, we must develop a more physiologically-informed framework to generate more specific mechanistic models of the timecourse of human neuroplasticity. My overall research goal is to develop a deeper understanding of how the brain supports the acquisition of motor skills through the process of neuroplasticity. The short-term objectives porposed here will develop a physiologically-informed model of human motor neuroplasticity by: determining the regions of the brain that support sequence-specific plasticity per-se (over and above the effect of performance), characterizing their timecourses of change, and identifying the putative neurophysiological mechanisms that support neuroplasticity. The proposed work is based on a unique and rich Ultra-high field (7T) multimodal quantitative magnetic resonance imaging (MRI) dataset that was previously collected by myself and colloborators. Two groups of 20 participants (active, control) were trained on a visuo-motor sequence learning task of fine motor control (sequential pinch force task) over 5 consecutive days. Multimodal quantitative MRI was acquired on each day, and included sequences sensitive to myelin, cell density, tissue microstructure, resting blood flow, blood volume, and iron. This unique dataset will used by HQP including 2 PhDs and 3 Masters to develop a physiologically-informed model of structural, functional and multimodal training-related neuroplasticity, crucially leveraging our knowledge of the physiological origins of the collected multimodal quantitative MRI metrics to identify the mechanistic timecourse of training-related neuroplasticity. Together, the proposed research is a critical first step towards a mechanistic understanding of how our brains learn motor skills.