Complex Perceptual-Motor Learning in Virtual Reality: Investigating the Generalization of Complex Motor Sequences

<p><strong>Abstract Learning motor skills that involve repetitive action sequences, such as driving, is essential. An important question is whether these skills are generalizable, or in other words, whether learning one sequence transfers to new sequences or environments, or whether they are sequence-specific and do not transfer. Many of these skills rely heavily on perception to guide effective movements and are defined as perceptual-motor skills in this study. Much of the existing research focuses on simple motor skills, which do not reflect the complexity of real-world motor tasks. This thesis developed a new paradigm to test complex perceptual- motor learning and generalizability using the off-the-shelf Virtual Reality (VR) game Beat Saber.</strong></p><p>Beat Saber requires players to slice coloured blocks using two lightsabres controlled by VR hand controllers. Participants played a particular song on a specific difficulty (a particular perceptual-motor sequence) for four consecutive days. On the fifth day, participants played the same song once more, followed by a new song of equal difficulty, representing a new perceptual-motor sequence. This paradigm enabled significant learning across three performance metrics: the proportion of blocks hit, and left- and right-hand accuracy scores, which measured the precision of slicing. As expected, participants’ performance dropped when transitioning to the new song on the fifth day. From this performance drop, we calculated that 65.7% of the learning from the first song was general skill learning, meaning the remaining 34.3% of the learning was tied to the initial sequence and did not transfer to the new song. This paradigm offers a valuable tool for further exploring complex perceptual motor learning and generalizability.</p>