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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/12773
Title: Detection and Localization of Power and Coherence Dynamics with EEG
Authors: Ghahremani, Ayda
Advisor: Wong, Kon Max
Jeremic, Aleksandar
Jian-Kang Zhang, Nicola Nicolici
Department: Electrical and Computer Engineering
Keywords: EEG;spatial filter;magnitude-squared coherence;imaginary component;Biomedical;Biomedical
Publication Date: Apr-2013
Abstract: <p>It has been observed by researchers that periodic auditory stimuli can cause the activities in different brain areas to be periodically synchronized. Fast auditory stimuli have been shown to cause the brain sources to synchronize at the rate of stimuli. Brain sources respond to them not only by increase in local synchronization, but also in the global synchronization of cortical regions often regarded as functional connectivity. Spectral power and coherence are often used to characterize such neural synchronization. Beta band oscillations have been reported to underlie the neural mechanism during repetitive auditory stimuli. Cortical generators of these underlying beta oscillations were investigated in several studies based on MEG measurements. This research is intended to investigate (1) EEG can be used to detect and localize neural sources changing in power and coherence and (2) beta oscillations underlie such neural synchronization during fast repetitive auditory stimuli based on EEG measurements. The procedure of this study consists of several steps. First, the minimum variance (MV) scalar beamformer, an adaptive spatial filter, is used to estimate the temporal signals in the brain source space, given EEG recordings. The analysis of the estimated source temporal signals then consists of two stages firstly the power analysis and secondly the coherence analysis. The dynamics of power and coherence is investigated instantaneously over time and in the lower beta frequency band [14,20Hz]. This is done by detecting the most prominent changes in the two spectral parameters through singular value decomposition (SVD). Two coherence measures imaginary component (IC) and magnitude-squared coherence (MSC) are employed and compared in terms of their performance both mathematically and experimentally. In the simulations, we show the capability of using EEG to detect and localize power co-variations and dynamic functional connectivity in the cortical regions. We also perform the procedure on the recorded real data from subjects passively listening to rhythmic auditory stimuli. Beta oscillations are found to underlie the neural activity to percept auditory stimuli. This is shown by localization of auditory cortices and detection of power co-variation in this frequency band. We demonstrate the feasibility of using EEG to identify coupled and co-activated brain sources similar to those obtained from MEG signals in the previous studies. These include auditory and motor regions which were found to be functionally coherent and have a functional role in the auditory perception. The superiority of IC over MSC measure is proven mathematically and validated in both simulations and real data experiments.</p>
URI: http://hdl.handle.net/11375/12773
Identifier: opendissertations/7631
8690
3541499
Appears in Collections:Open Access Dissertations and Theses

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