Motor learning in real-world pool billiards

Abstract

24The neurobehavioral mechanisms of human motor-control and learning evolved in free 25 behaving, real-life settings, yet to date is studied in simplified lab-based settings. We demonstrate 26 the feasibility of real-world neuroscience, using wearables for naturalistic full-body motion-27 tracking and mobile brain-imaging, to study motor-learning in billiards. We highlight the 28 similarities between motor-learning in-the-wild and classic toy-tasks in well-known features, such 29 as multiple learning rates, and the relationship between task-related variability and motor learning. 30Studying in-the-wild learning enable looking at global observables of motor learning, as well as 31 relating learning to mechanisms deduced from reductionist models. The analysis of the velocity 32 profiles of all joints enabled in depth understanding of the structure of learning across the body. 33First, while most of the movement was done by the right arm, the entire body learned the task, as 34 evident by the decrease in both inter-and intra-trial variabilities of various joints across the body 35 over learning. Second, while over learning all subjects decreased their movement variability and 36 the variability in the outcome (ball direction), subjects who were initially more variable were also 37 more variable after learning, supporting the notion that movement variability is an individual trait. 38Lastly, when exploring the link between variability and learning over joints we found that only the 39 variability in the right elbow supination shows significant correlation to learning. This demonstrates 40 the relation between learning and variability: while learning leads to overall reduction in movement 41 variability, only initial variability in specific task relevant dimensions can facilitate faster learning. 42 43 Author Summary 44This study addresses a foundational problem in the neuroscience: studying the mechanisms 45 of motor control and learning in free behaving, real-life tasks, where our brains and bodies operate 46 in on a daily basis and which contains the richness of stimuli and responses for what our nervous 47 system evolved. We used the competitive sports of pool billiard to frame an unconstrained real-48 world skill learning experiment which is amenable to predictive modelling and understanding. Our 49 data-driven approach unfolds the structure and complexity of movement, variability, and motor-50 learning, highlighting that real-world motor-learning affects the whole body, changing motor-51 control from head to toe. Crucially, we are enabling novel hypothesis driven experimental 52 approaches to study behavior where it matters most -in real life settings. 53

Practicing one thing at a time: the secret to reward-based learning?

“…The second difference is related to the noise in the task-relevant factors. Noise hampers learning 5 and an additional factor may hamper learning by adding noise to the signal that the reward is based on. In van der Kooij & Smeets (2019) we studied the addition of depth and elevation to a lateral task.…”

“…Therefore we analyze exploration from trial-by-trial changes. Trial-by-trial changes (D) were calculated as the amplitude of each change in the normalized error from trial t-1 to trial t. Several studies have found that trial-by-trial changes are larger following non-rewarded trials than following rewarded trials 4,5,10,12,14,15 . To test whether this effect existed in the current study, we calculated the median trial-by-trial change in the combined error (D Combined ) following non-rewarded trials and following rewarded trials within the three learning phases.…”

“…For instance, Katy may directly form associations between actions and success which would result in action-specific learning 1,3 . Another possibility is that she may learn from successful exploration [4][5][6] , which could potentially transfer across actions. The type of mechanism that we focus on in this study is a learning mechanism that relies on the exploitation of successful exploration.…”

“…The task in which reward-based learning has been typically tested is a far cry from the complexity of 'real-life' tasks such as Katy's dance training 7 . In the commonly used 'visuomotor rotation' paradigm 1,[4][5][6]8,9 movements are in a horizontal plane in which the relation between visual and motor direction is rotated. In this paradigm, participants make center-out reaching movements in which reward feedback is based on a single factor: the angular error.…”

Neurobehavioural signatures in race car driving

“…This is probably why we are so fascinated by individual musicians, artists, athletes, and craftsmen who take these expertise to levels that most of us can only imagine. Novel technology for mobile brain and body imaging is now enabling to study neurobehavior in real-world settings 3 . When carried out in natural environments, these measures can enable a meaningful understanding of human behaviour while performing real-life tasks.…”