Identifying the Neural Correlates of Motor Sequence Learning and Movement Automaticity
Creators: name: Polskaia, Nadia
Publisher: name: Université d'Ottawa / University of Ottawa
Year: 2021
Subjects: fNIRS
Motor learning
Signal processing
Automaticity

description: Sequential movements have become a common experimental paradigm for evaluating the neural correlates of motor learning. Currently, the understanding is that motor sequence learning engages the cortico-cerebellar and cortico-striatal networks and that their contributions differ depending on the stage of learning. The prefrontal cortex (PFC), in particular, has been observed at the early/fast phase and late/slow phase of motor sequence learning, suggesting involvement in processes such as movement automaticity, stimulus-response conflicts, explicit learning, and retrieval, to name a few. However, it is difficult for neuroimaging studies to evaluate the relative permanence of motor sequence learning due to the financial burden associated with functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In this dissertation, four experiments were performed to examine the functionality of functional near-infrared spectroscopy (fNIRS) in elucidating the role of the PFC in motor sequence learning and movement automaticity. The first experiment (Chapter 2) focused on validating fNIRS as a comparable technique to fMRI by replicating a previous motor sequence learning study (Wu et al., 2004) that reported decreased activity in the left dorsolateral prefrontal cortex (DLPFC) following achievement of movement automaticity. The fNIRS findings were unable to detect a similar decrease in the left DLPFC. The second experiment (Chapter 3) further investigated the cerebral oxygenation changes in the PFC following motor sequence learning. To enable better distinction between learning and performance, this experiment including multiple motor sequence tasks, a control group, four practice sessions and a retention phase. The findings revealed increased contributions from the right hemisphere (e.g., right ventrolateral PFC (VLPFC)) and the suggestion that the left DLPFC may not reflect movement automaticity but rather attentional investment in movement preparation. To address the signal processing concerns observed in experiment one and two, the third experiment (Chapter 4) investigated the effect of five motion correction techniques on the statistical outcomes of a motor sequence learning experiment. Additionally, the corrections were evaluated to determine which would yield the greatest improvement in hemodynamic response function (HRF) recovery and within-subject standard deviation. The findings revealed the location of significance to vary depending on the motion correction applied. Also, wavelet and spline + wavelet demonstrated limited improvement in reducing within-subject standard deviation. Lastly, the fourth experiment (Chapter 5) examined changes in the PFC associated with dual-task processing before and after motor sequence learning. Findings revealed decreased activity in the right DLPFC, medial PFC (mPFC), and orbitofrontal cortex following practice for dual-task sequence-4. A similar but marginal trend was observed in the right VLPFC. Minimal significance was observed during the dual-task sequence-12 task. Collectively, the findings of this dissertation suggest that 1) motor sequence learning when acquired with explicit knowledge requires contribution from predominately the right hemisphere, 2) the left DLPFC may represent attentional investment in movement preparation rather than movement automaticity, 3) the neural representations of dual-task processing are associated with the complexity of the motor sequence task, and 4) low-frequency motion artifacts may be difficult to remove using certain signal processing methods.