Imagining to learn: quantifying network activation patterns to understand the brain mechanisms underlying motor imagery-based skill acquisition

想象学习：量化网络激活模式以了解基于运动想象的技能习得背后的大脑机制

• 批准号: RGPIN-2015-04900
• 负责人: Boe, Shaun
• 金额: $ 1.75万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=645695
• 关键词: Imagining; learn; quantifying; network; activation

Our ability to learn highly skilled sequences of movements is key to many aspects of human performance. From the flawless triple jump of a figure skater to life-saving surgeries, skilled movements are honed through a process called motor learning. Motor learning happens because our brain changes as we repetitively practice new movements. We usually practice a movement by actually doing it. This is called physical practice. However, it's not always possible to physically practice a movement; athletes get injured, surgeons get tired, and some people re-learning movement after a brain injury can't move at all. It turns out that it's possible to practice a movement without moving at all; you just need to think about moving. This is called motor imagery. We think that using motor imagery along with physical practice can make learning motor skills faster and more efficient. ******The problem with motor imagery is that we don't know a lot about it. In fact, we know very little about what brain areas work during motor imagery, and how they change with learning. This lack of knowledge is a problem. Not knowing how the brain works during motor imagery prevents us from figuring out the best ways to use it to help with motor learning. In physical practice we know a lot about brain activity and how the brain changes with learning. As a result we have been able to figure out the best ways to learn, like how much practice to do and for how long. We need to figure out these same details for motor imagery. This is the long-term goal of this research - to establish how motor imagery best drives motor learning. The short-term goal that makes up the proposed research is to find out about how areas of the brain work together during motor imagery, and how they change when we learn new motor skills. This information tells us about the network of brain areas at work during motor imagery. We then want to identify the brain areas critical to performing motor imagery, and those critical to learning using motor imagery. Enhancing our ability to learn new skills or strengthen skills we already have by using motor imagery can impact on all Canadians. Imagine our high performance athletes having an edge on the competition, members of our workforce having a higher level of skill, and our healthcare professionals having a new tool to help with recovery of movement. This research will impact on a wide range of areas, ultimately having a positive effect on the performance and health of Canadians.

我们学习高度熟练的动作序列的能力是人类表现的许多方面的关键。从花样滑冰运动员完美的三级跳远到挽救生命的手术，熟练的动作都是通过一个叫做运动学习的过程来磨练的。动作学习的发生是因为我们的大脑在重复练习新动作时发生了变化。我们通常通过实际做动作来练习动作，这叫做身体练习。然而，并不总是可以通过身体练习运动;运动员受伤，外科医生累了，有些人在脑损伤后重新学习运动，根本不能移动。事实证明，完全不动也可以练习一个动作;你只需要想着移动。这就是所谓的运动想象。我们认为，运动想象沿着身体练习可以使运动技能的学习更快、更有效。** 运动想象的问题在于我们对它知之甚少。事实上，我们对运动想象过程中大脑的哪些区域工作以及它们如何随着学习而变化知之甚少。这种知识的缺乏是一个问题。不知道大脑在运动想象过程中是如何工作的，这阻止了我们找出最好的方法来使用它来帮助运动学习。在体育锻炼中，我们知道很多关于大脑活动以及大脑如何随着学习而变化的知识。因此，我们已经能够找出最好的学习方法，比如做多少练习和多长时间。我们需要在运动想象中找出同样的细节。这是这项研究的长期目标-确定运动想象如何最好地驱动运动学习。构成拟议研究的短期目标是找出在运动想象过程中大脑区域如何协同工作，以及当我们学习新的运动技能时它们如何变化。这些信息告诉我们，在运动想象过程中，大脑区域的网络在起作用。然后，我们想确定对执行运动想象至关重要的大脑区域，以及那些对使用运动想象进行学习至关重要的大脑区域。通过使用运动想象来提高我们学习新技能或加强我们现有技能的能力可以影响所有加拿大人。想象一下，我们的高性能运动员在竞争中具有优势，我们的劳动力成员具有更高的技能水平，我们的医疗保健专业人员拥有一种新的工具来帮助恢复运动。这项研究将对广泛的领域产生影响，最终对加拿大人的表现和健康产生积极影响。