Thesis

Determining the optimal paradigm for investigating if M1 activations associated with step tracking wrist movements are direction or muscle related using EEG

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Awarding institution
  • University of Strathclyde
Date of award
  • 2013
Thesis identifier
  • T13658
Qualification Level
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Department, School or Faculty
Abstract
  • This study investigated whether activations detected within the primary motor cortex (M1) during a wrist step tracking task encoded movement direction or specific muscle groups used to achieve the movement. This will provide information on the processes which occur within M1 of the human brain. Experiments were designed to examine in more detail the results of a functional Magnetic Resonance Imaging (fMRI) study (Toxopeus, et al., 2011a) which detected spatially disjoint areas within the wrist area of M1 that appeared to process movement within horizontal and vertical directions. The experiments combined electroencephalography (EEG) and source localisation to observe M1 activations and confirm whether they resulted from the processing of discrete movements or specific muscle groups. The results of a pilot EMG test indicated that a 90° change in forearm orientation did not sufficiently disassociate direction and muscle use. Changing forearm orientation from fully pronated to supine sufficiently dissociated the movement direction from the muscles used to produce the movement. The new paradigm recorded 64-channel EEG. Observation of task related epochs during artefact rejection indicated the presence of a time locked artefact caused by eye movements (saccades). The effects of artefact detection and reduction methods applied to the raw EEG data to remove this artefact were compared. Independent component analysis was applied to the averaged epochs and components resulting from artefacts were removed. Source localisation methods were applied to the processed averages and their results assessed for physiological and anatomical feasibility. Artefact reduction methods were found to be ineffective at removing saccades when applied to raw EEG data, indicating the need for more advanced artefact reduction techniques such as Independent Component Analysis (ICA) to be applied to the data. The paradigm required the correct choice of a linear distribution source localisation model with 40μm spatial resolution to produce feasible results.
Resource Type
DOI
Date Created
  • 2013
Former identifier
  • 1005012

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