Establishing the nature and processes of error-based learning via motor imagery

想象表演一个动作有助于学习如何用身体做这个动作。这个过程被称为运动想象（MI），被认为有助于学习，因为当你想象运动时，大脑中发生的事情和你实际执行运动时是一样的。我们的研究表明，MI不同于体能表现。了解它的不同之处很重要。如果我们知道MI的不同之处，我们就可以更有效地使用MI来帮助人们学习新的动作。此外，我们获得的新知识告诉我们很多关于学习在大脑中发生的方式。我们认为MI和体能表现之间有两个主要区别。当你在身体上练习一个动作时，你会非常擅长你所练习的特定的事情——如果你用右手练习，你的右手真的很好，但用左手做同样的动作会导致表现不佳。当你通过MI练习时，动作的表现不是很好，但你可以转移你学到的东西-那就是你可以使用你的左手和右手。这种转移所学知识的能力使我们认为，通过人工智能学到的东西不同于物理练习。另一个区别在于你如何学习。当你做一个动作时，关于你如何做这个动作的信息会被与它应该怎么做进行比较，从而允许错误被检测和修复。因为你实际上从来没有在人工智能中移动过，所以不清楚错误是否被制造、检测和修复——这就导致了人工智能如何帮助学习的问题。所提议的项目希望更多地了解从人工智能中获得的学习类型，以及检测错误和修复错误的机制。在第一组项目中，人们将通过MI或身体练习来学习一个动作。在整个学习过程中，我们将测试他们的表现，看看他们正在学习的东西是否有所不同。我们还将记录人们的大脑活动，以找出大脑的哪些区域是活跃的，以及这在心肌梗死和体育锻炼之间有何不同。我们还将测试MI和物理练习的不同组合，看看MI帮助的学习方式是否能提高我们从物理练习中学到的东西。在第二组项目中，我们将探索人们在通过人工智能学习时是否会出现错误。我们还将记录人们的大脑活动，以找出在人工智能中哪些区域参与了错误检测。最后，使用特殊设备，我们将在短时间内抑制大脑部分区域的活动，以了解更多关于MI中学习发生的方式。这项研究将使我们能够确认我们关于MI帮助学习的类型以及通过MI学习如何实际发生的想法。我们需要这样的基础知识，这样我们才能找出使用人工智能来帮助学习运动的最佳方法。这将使在广泛领域的学习变得更好，最终将对加拿大人的健康和表现产生积极影响。

Imagining performing a movement helps with learning how to physically do the movement. This process, called motor imagery (MI), is thought to help with learning because the same things happen in the brain when you imagine movement as when you physically perform it. Our research suggests that MI is different from physical performance. Knowing how it is different is important. If we know how MI is different, we can use MI more effectively to help people learn new movements. Also, the new knowledge we gain tells us a lot about the ways learning can occur in the brain. We think there are two main differences between MI and physical performance. When you physically practice a movement you get very good at the specific things you practice - if you practice with your right hand, your right hand is really good, but doing the same movement with your left hand results in bad performance. When you practice through MI, performance of the movement is not as good, but you can transfer what you learned - that is you could use your left hand as well as your right. This ability to transfer what you learned makes us think that what you learn through MI is different from physical practice. The other difference is about how you learn. When you physically do a movement, information about how you did the movement is compared to how it was supposed to be done, allowing for errors to be detected and fixed. Because you actually never move in MI, it is not clear if errors are made, detected, and fixed - leading to the question of how MI can help with learning. The proposed projects look to find out more about the kind of learning that results from MI, and what the mechanism is for detecting errors and fixing them. In the first set of projects people will learn a movement through MI or physical practice. Throughout the learning we will test their performance to see if what they are learning is different. We will also record people's brain activity to find out which areas of the brain were active, and how this differs between MI and physical practice. We will also test different combinations of MI and physical practice to see if the kind of learning that MI helps with improves what we learn from physical practice. In the second set of projects we will explore if people make errors when they learn through MI. We will also record people's brain activity to find out what areas are involved in error detection in MI. Finally, using special equipment, we will turn down activity in parts of the brain for a short period of time to find out more about the way that learning occurs in MI. This research will allow us to confirm our ideas about the kind of learning that MI helps with and how learning through MI actually occurs. We need this kind of basic knowledge so we can figure out the best way to use MI to help with learning movement. This will make learning better in a wide range of areas that will ultimately have a positive impact on the health and performance of Canadians.