Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Science

Program

Neuroscience

Supervisor

Diedrichsen, Jörn

2nd Supervisor

Pruszynski, J. Andrew

Co-Supervisor

Abstract

Learning novel patterns of muscle activity, such as when producing a new guitar chord, is an essential aspect of human motor skill learning. However, most existing motor skill learning paradigms do not focus on this aspect, but rather deal with modification or combination of previously well-practiced actions (e.g. learn sequence of single-finger presses, adaptation of reaching movements). The study presented in this thesis aims to develop and validate a new well-controlled lab task to study learning novel muscle activity patterns. Participants practiced on 242 unique multi-finger configurations, involving flexion and extension at the metacarpophalangeal joint. On the first day, some of the configurations were so difficult that participants could not produce them. Nonetheless, after 3 days of practice, they were able produce all 242 combinations. We then quantified the difficulty of each chord across participants, and compared different explanatory models, including the cognitive complexity of the chord, the force directions, and the patterns of muscle activity. The model based on patterns of muscle activity provided the best predictive accuracy, indicating that some characteristic of the specific muscle activity pattern makes chords difficult to produce. To investigate the nature of these characteristics, we quantified the naturalness of these muscle activity patterns by comparing them with the muscle activity patterns that occur during natural everyday actions. We found that the probability of a given pattern occurring during natural actions, as well as the absolute amount of muscle activity, determines the difficulty of producing novel muscle activity patterns.

Summary for Lay Audience

We marvel at athletes in the Olympics, or listen in awe to a musician who has mastered their instrument. These skills, highlight the ability of our brains to learn and perfect movements. Researchers have long studied motor skill learning to uncover how our brains learn and support these skilled movements. While simple motor skills has been extensively studied, less attention has been given to how we learn novel complex skills, like playing musical instruments.

In this thesis, I developed and validated a new experiment that enables us to study these novel skills. Participants in this experiment learned to independently flex and extend multiple fingers quickly and simultaneously - a skill proximal to forming chords on a guitar, where specific finger shapes must be achieved.

This study is a foundational step in a broader research series. My first goal was to quantitatively confirm that the flexion-extension combinations in the experiment are novel and far from everyday movements. I found that some combinations were initially very difficult and even impossible for participants to produce. However, with practice, all individuals mastered all 242 distinct finger combinations.

Furthermore, I found that participants consistently found similar finger combinations to be difficult to produce. This reminds that when individuals are learning to play guitar, there is common experience about which chords are more difficult. For example, beginner guitar players commonly find F major chord to be much more difficult than E minor. I asked why some finger combinations are more difficult than others?

To explore this question, I studied multiple factors that could possibly cause dif- ficulty. For one, naturally we tend to move our fingers together in everyday tasks. I statistically quantified the naturalness of finger combinations and showed that the more unnatural ones were generally more difficult. Alternatively, the way tendons and muscles are connected together and to the finger joints, might make some finger combinations more challenging. I found that while the anatomical limitations partially explain the difficulty, they were not hard limits and could be overcome. Finally, I show that cognitive factors do not explain the difficulty better than motoric factors.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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