Year: 2017
Type: dissertation
Abstract: Simultaneous acquisition of Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) enables studying of brain function with high spatial resolution of fMRI and high temporal resolution of EEG. The complementary characteristics of the two modalities have made simultaneous EEG-fMRI into a rapidly growing neuroimaging technique with a wide range of cognitive and clinical applications. This thesis uses simultaneous EEG-fMRI to investigate the relationship between electrophysiological activity of the brain and the corresponding hemodynamic response during sensory processing of auditory and visual stimuli. Despite major improvements during the short history of EEG-fMRI, several technical and methodological challenges still remain. The main challenge in EEG-fMRI is the compromised EEG data quality. EEG data recorded inside the MR scanner is contaminated by artifacts caused by the MR magnetic fields. This thesis provides a comparative evaluation of the existing EEG artifact removal methods and proposes new analysis approaches to improve the EEG data quality. Another open question in the field of EEG-fMRI is the optimal choice of measures and techniques for data integration. This thesis proposes a new multivariate approach for EEG-fMRI data integration, which enables taking advantage of the full spectrum of the data available in two modalities. The proposed multivariate technique as well as conventional univariate methods are then used to explore the relationship between various aspects of the brainâ s electrophysiological activity (i.e. the transient evoked activity, oscillatory evoked activity and spontaneous oscillatory activity) and the associated hemodynamic response in auditory and visual cortices.
Source: TSpace (University of Toronto)
Author: Nasim Shams
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2767368959