Learning-model action observation: An investigation in long-term motor learning outcomes
Motor learning can take place using a number of strategies other than physical practice, either independently or in conjunction with one another. One such strategy is action observation (AO), which involves observing a model perform a motor skill. In typical AO protocols, the model executes the skill without committing any errors, thereby offering the viewer a perfect demonstration of the skill and task outcome. However, for individuals in the early phases of learning a novel motor skill, this type of skilled performance may not be ideal given the absence of errors in the model’s performance. This is due to the critical role that error correction and sensory feedback have in driving early learning gains in physical practice and the evidence that this role is similarly conserved in AO. The goal of this project is to determine if AO of a learning model (who commits and corrects errors, improving over time) results in improved performance outcomes on a dart-throwing task when compared to AO of a skilled model for early-phase learners completing a 6-week training program. The results of this study can be used to optimise the use of AO in performance, occupational, and rehabilitation settings, and address questions surrounding the conservation of error-based learning mechanisms across different motor learning strategies.
Project member: David Bowman
Examining brain excitability during motor imagery
Motor imagery widely activates the sensorimotor network, leading to brain plasticity that underlies learning. One drawback to motor imagery is that it is considered to be mentally fatiguing. When we are mentally fatigued, our brains are less excitable, which means that the effectiveness of motor imagery for learning is hindered. In this study, we are looking at how brain excitability is reduced after different durations of imagery practice. Ultimately, this research contributes to our understanding of using motor imagery for learning.
Project members: JungWoo Lee (Honours project), Sarah Kraeutner, Devan Pancura
Investigating the effect of manipulating effector load on corticospinal excitability during motor imagery and motor execution of a grip force task
Performing motor imagery (MI), the mental rehearsal of a motor task, leads to an increase in cortical excitability and facilitates synaptic plasticity, which is required for motor skill learning to occur. As such, motor imagery is used as an adjunct to physical practice in motor skill training and rehabilitation. The Functional Equivalence and Cognitive Motor models are competing theories that explain the neural mechanisms underlying MI. Evidence about how cortical excitability changes during MI as a function of effort differs between the models; some research has found that cortical excitability during imagined tasks scales with effort in a linear fashion (similar to physical practice), supporting the functional equivalence model, while other studies have shown cortical excitability mirrors that of physical practice only during low effort tasks, but differs as the effort required to complete a task increases, supporting the cognitive motor model. This study will investigate how cortical excitability scales across varying levels of effort during imagined vs. executed tasks. We will also compare how this scaling differs when the imagined task is performed with high fidelity (familiar tasks) vs. low fidelity (unfamiliar tasks) imagery. The aim of this study is to provide an explanation for the divide in the current literature on how brain activity scales at varying efforts of MI tasks compared to motor execution, thereby generating further evidence to support the theoretical underpinnings of why MI is effective for motor skill acquisition.
Project members: Devan Pancura, Jack Solomon
Can you imagine? Comparing assessments of imagery ability
Motor imagery, the mental rehearsal of movement, can help us learn and improve skills. Because motor imagery is performed ‘in your head’, it is difficult to assess someone’s ability to perform motor imagery. Assessing imagery ability is important as one wants to make sure that their method of practice is effective before engaging in it. While there are many different tools to assess motor imagery ability, we still don’t know which tool is the best. This study seeks to determine which assessment tool is the best, by comparing the tools against how well we learn through motor imagery. Ultimately, this work will help us understand how we can assess motor imagery ability.
Project members: Sarah Kraeutner, Alexandra Stratus
Imagine that! Probing different brain regions in motor imagery-based learning
Motor imagery (MI) can help us improve skills by driving brain plasticity that underlies learning and relearning after brain injury. But we don’t know how damage to different parts of your brain (e.g., after brain injury) might prevent a person from being able to do motor imagery. To use motor imagery to help people with brain injury recover, we need to make sure that damage to brain areas does not impact on practicing skills using motor imagery. This study will look at the role of one particular brain area in using motor imagery to practice and learn a new skill. This study will also help us understand the roles of different brain regions in MI performance and learning.
Project members: Jack Solomon, Sarah Kraeutner
Don’t move! The timing and mechanism of movement inhibition in motor imagery
Motor imagery (MI) and motor execution (ME) are two methods one can use to learn motor skills. The primary behavioral difference between the two modalities is that ME results in overt movement whereas MI does not. Two theories exist two explain this difference. The first indicates that movement inhibition in MI is embedded in planning for the movement and the second suggests that the motor command is stopped after it is made. This study used neuroimaging to capture brain activity from a reach and grasp task to identify when movement inhibition occurs in MI to identify which theory is correct. Afterwards, a second analysis was performed to understand which parts of the brain are responsible for movement inhibition in MI
Project members: Jack Solomon, Sarah Kraeutner
Everyday experts: prior experience to optimize imagery
Repetitive practice, both imagined or physical, drives brain activity that ultimately underlies recovery post-stroke. However, this brain activity can vary across individuals and tasks when practiced using motor imagery. Because driving brain activation in the ‘right’ areas is what allows us to ultimately re-learn skills, it is important to understand what might influence brain activity driven by motor imagery. This project seeks to examine how someone’s physical expertise of a skill may impact brain activity driven via motor imagery, by comparing brain activity during motor imagery of highly familiar (performed regularly) vs. non-familiar tasks. The information gathered in this study will help us understand whether we can use someone’s skill expertise to optimize brain activity during motor imagery for recovery post-stroke.
MSc student Chris Friesen working on his BCI project for imagined imitation with lab members Tony Ingram and Karl Simon. Chris’s project uses EEG to provide real-time neurofeedback to help with imagery performance.
iImagine: Digital physiotherapy for survivors of stroke?
Following a stroke, the brain requires repetitive practice to change and recover. However, patients are often easily fatigued, and in some instances are not able to move the arm or hand affected by the stroke. Studies have now shown that both imagining and watching arm movements, in addition to regular therapy, can improve recovery. However these techniques are not often used. Enter neurofeedback—feeding information on brain function back to the patient in real time, while they imagine movements. We’re designing a novel neurofeedback system that strives to both increase effectiveness and be user-friendly, with a long-term vision of having this cost-effective therapy gain mass adoption.
The priming effect: aerobic exercise, fitness and brain excitability
Learning and rehabilitation are dependent on our brain’s ability to change. We can make our brain more susceptible to changes by increasing its excitability, or ‘priming’ the brain. Aerobic exercise is an exciting method of priming the brain: not only does it work the heart and lungs, but it has been shown to increase excitability in brain areas that weren’t involved in controlling the exercise — pedaling a bike can prime the brain areas that control the hands! Priming the brain before therapy may improve clinical outcomes, so understanding how aerobic exercise does this is important. In this study we are investigating whether or not aerobic fitness plays a role in the priming effect.
Imagine that! Motor imagery for skill acquisition
Motor imagery (MI), the mental rehearsal of movement, can help us learn and improve skills as an adjunct to physical practice. But what if you are unable to engage in physical practice, such as after stroke? To use MI in these domains, we need to establish whether MI on its own can produce learning. Further, brain damage that results from stroke may impact on the effectiveness of MI. This project characterizes MI-based skill acquisition with and without brain damage, using transcranial magnetic stimulation to temporarily ‘turn down’ brain activity. Ultimately, this work will inform on the use MI for skill acquisition in health and disease.
Exercise and the brain: a lowest common denominator?
Aerobic exercise has been shown to increase activity in parts of the brain that are responsible for movement. Activation of these brain areas can help with recovery of function in people who have lost the ability to move as a result of brain injury. But what are the best exercise parameters (like intensity and duration) that can turn on these brain areas without tiring the patient? This project aims to test how activity in the brain changes as a result of varying intensities of aerobic exercise. The main goal is to identify the lowest intensity of exercise needed to increase activity in the brain, and to evaluate the mechanisms underlying these changes in activity. The outcome of this work will aid in the development of protocols that use aerobic exercise to prime the brain before rehabilitation.
“I know kung-fu”: brain stimulation to enhance skilled movement
We remember how to ride a bike because the brain stores this information through complex networks of connected brain regions. Repetitive practice rewires the brain to make these networks more efficient. Our lab works to identify the most important connections for learning a skill, and is currently testing new methods of safe brain stimulation to enhance these connections more specifically. The goal is to develop the most effective procedures for enhancing learning, and to apply these techniques to rehabilitation.
Are you better than Shaq? Creating a motor plan using motor imagery
Can you shoot free throws better than Shaquille O’Neal? When a person learns a motor skill like shooting a free throw, the brain creates a motor plan, which is then updated each time they physically practice the skill. But what if you can’t physically practice? Can you still create and update a motor plan? This project seeks to answer this question by investigating whether a motor plan can be created using motor imagery (MI), the imagination of movement, without any physical practice. We’re going to teach novice basketball players a free throw with MI, recording changes in brain activity and performance. The goal is to learn more about how we can use MI to teach new skills.
‘Punch Drunk’: concussion, learning & memory
We know concussions impair learning and memory in the short-term. Recently, a conclusive link has been identified between repetitive concussions and the development of learning and memory-related pathologies later in life. Nevertheless, not all studies evaluating learning and memory in previously concussed individuals demonstrate definitive cognitive impairment in the long-term (i.e., years after the injury). Insufficiently sensitive methods used to assess learning and memory may account for this finding. To better understand the long-term implications of concussion, we are conducting a systematic review that synthesizes the current literature relating concussion history to long-term learning and memory impairments.
Tortoise or the hare? Examining the rate of skill acquisition using MI
Repetitive practice drives changes in the brain, which leads to learning new skills. While physical practice is the ‘gold standard’ of learning, we can also imagine ourselves performing the task without moving (called motor imagery) to learn new skills. However, we don’t know how fast we can learn a skill using motor imagery or how much training is required. Do we learn at the same rate as when we try to learn a skill using physical practice? And is the amount of training that we need equal? This project aims to investigate the rate of skill acquisition via motor imagery-based practice. The information gathered in this study will contribute to our understanding regarding the application of motor imagery as a form of practice in sport and rehabilitation.
Implicit learning of complex motor skills
We learn and improve our skills by practicing them. When we learn skills, part of the learning happens without our conscious awareness – this is called implicit learning. Most research studies that look at implicit learning have people practice simple movements. However, something we’re not sure about is how implicit learning occurs in more complex movements. The purpose of this study is to examine implicit learning a complex skill.