Grant: Discovery Grants Program - Individual

When someone learns to make a movement in a new situation, various cognitive processes occur. Imagine playing basketball outside on a windy day. Some people might adopt a strategy to aim so the wind carries the ball into the basket. Others might rely more on subconscious wrist and arm adjustments guided by past shot accuracy. While these processes are well-documented in controlled lab settings, understanding how they function in the real world, like on a basketball court, remains a mystery. Additionally, how individuals perceive their own bodies can vary widely, which can directly impact how they learn to make movements. This self-perceptual phenomenon, known as embodiment, is seen, for instance, in how professional hockey players consider their sticks extensions of their bodies, a perception that evolves over time. My long-term research goal is to explain the intricate interactions between motor learning processes and cognitive functions like perception, attention, and memory. During the next five years, I will run a series of experiments in virtual reality (VR) environments to study how different motor learning mechanisms operate together during unconstrained movements, and how this learning is affected by the body connectedness of the moved object. We use VR representations of realistic motor tasks because making controlled changes in the real world is challenging (e.g. turning on and off wind during a basketball game). We will first determine if the interplay between strategic and subconscious motor learning is maintained outside of controlled lab settings. Then we will change the level of embodiment, or body connectedness, of a person's virtual representation and see how that affects motor learning. Additional studies will probe how motor learning affects our perception of our own limbs across the lifespan. This research has wide-ranging implications. First, it will deepen our understanding of fundamental motor learning processes. Second, this knowledge will be harnessed to drive advances in various domains including athletics, robotics, and workplace safety. An understanding of unconstrained motor learning will enable tailored training programs to optimize athlete performance. Understanding the interaction between motor learning and object perception will transform the design of human-controlled robots, including surgical tools. Knowledge of how movements deteriorate in tandem with changes in embodiment, such as with fatigue or drug use, will allow us to assess and mitigate the impact of such factors on worker performance and safety. Furthermore, our research will produce innovative tools to measure embodiment in VR, empowering software developers to create more immersive gaming, training, and rehabilitation experiences. By encompassing these diverse domains, our research aims to bridge the gap between fundamental cognitive science and practical, real-world applications, potentially transforming how we interact with the world around us.