Doctor of Philosophy
Sequences of finger movements, such as making a cup of coffee or playing the piano, have a key role in our lives. An important neuroscientific question is how such movement sequences are represented in the brain. The central goal of this thesis was to investigate how different brain regions represent individual movements, and how these representations change when learning sequences of movements. To that end, we used 1) high-field functional magnetic resonance imaging (fMRI) to measure brain activation in humans while they produced finger movements on a keyboard-like device, and 2) advanced multivariate analyses to characterize the brain representations underlying the acquisition and control of finger movements. First, we examined the functional architecture of individual finger movements (Chapter 2). To dissociate sensory processing from movement, we designed an experiment including active finger movements and passive finger stimulation. We found that while the contralateral hemisphere represented individual fingers equally well during active movement and passive stimulation, the ipsilateral hemisphere represented fingers more clearly during active movement. Next, we assessed how brain representations for sequences of finger movements develop with learning (Chapters 3 and 4). Healthy volunteers were trained to execute a set of finger presses over five weeks and underwent repeated fMRI sessions. The results revealed widespread learning-related changes in premotor and parietal regions, including overall reduction in activation and a reorganization of how individual sequences are represented (Chapter 3). Contrary to previous research, none of these changes were observed in the primary motor cortex (M1). This distinction in learning between M1 and association regions was further supplemented by utilizing repetition suppression analysis and multivariate pattern analysis (Chapter 4). We demonstrate that M1 primarily represents the starting finger of the sequence, an effect which diminishes upon repeated sequence execution, but does not further represent sequence-specific features. Conversely, association regions reflect sequence identity and remain more stable across repetitions. Altogether, these studies revealed that M1 and association regions are differentially involved in execution and learning of movement sequences. The broad implication of this research is that premotor and parietal regions are likely fundamental to learning sequential skills, extending beyond finger movements.
Summary for Lay Audience
Our everyday lives are composed of sequences of movements – from the routine of making a cup of coffee to playing piano. With repeated practice, the execution of sequences like these becomes more fluid and efficient. What changes in the brain during learning that leads to such skillful control of movement sequences? To address this question, we investigated how the brain represents single finger movements and assessed what brain regions are involved in the acquisition of skilled finger movement sequences. We utilized functional magnetic resonance imaging (fMRI), a non-invasive technique that allowed us to measure brain activation in humans while they performed finger movements. One brain region that is of particular interest to motor neuroscientists is the primary motor cortex (M1). It sends commands to the muscles which then initiate the execution of movements. Prior research has established that hand movements are primarily controlled by the contralateral hemisphere (i.e., M1 in the left part of the brain controls right-hand movements), but the role of the ipsilateral hemisphere is not well understood. By contrasting brain activation during active finger movements and passive stimulation of fingers (analogous to depressing a piano key vs. the touch sensation from the key on the fingertip), we show that, while the contralateral hemisphere represents both of those conditions equally, the ipsilateral hemisphere represents active movement more than passive stimulation. Next, we asked how brain representations change as individuals learn sequences of finger movements over weeks of training. The activity of M1 during movement execution related most to the starting finger of the movement sequence, and did not show any learning-related changes. In contrast, brain regions that are typically implicated in movement planning showed activity decreases throughout learning, and represented different sequences as more distinct from one another. This altogether suggests that when learning a sequential skill, activity in areas supporting the skill decreases, perhaps reflecting increased efficiency, and is supplemented by more subtle changes of how patterns of activity represent individual sequences. These types of learning-related changes may apply more broadly to different types of learning, from sewing to touch-typing.
Berlot, Eva, "Brain Signatures of Human Skill Learning: From Single Movements to Movement Sequences" (2021). Electronic Thesis and Dissertation Repository. 7867.
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