<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> / Master of Applied Science (MASc)

The primary goal of this paper is to demonstrate the application of a relatively esoteric and interdisciplinary technique, called spectral analysis, to dyadic social sciences data. Spectral analysis is an analytical and statistical technique, commonly used in engineering, that allows times series data to be analyzed for the presence of significant regular/periodic fluctuations/oscillations. These periodic fluctuations are reflected in the frequency domain as amplitude or energy peaks at certain frequencies. Furthermore, a Magnitude Squared Coherence analysis may be used to interrogate more than one time series concurrently in order to establish the degree of frequency domain correlation between the two series, as well to establish the phase (lead/lag) relationship between the coherent frequency components. In order to demonstrate the application of spectral analysis, the current study utilizes a secondary dyadic dataset comprising 30 daily reports of perceived sexual desire for 65 couples. The secondary goal of this paper is to establish a) whether there is significant periodic fluctuation in perceived levels of sexual desire for men and/or women, and at which specific frequencies, and b) how much correlation or `cross-spectral coherence' there is between partners' sexual desire within the dyads, and c) what the phase lead-lag relationship is between the partners at any of the identified frequency components. Sexual desire was found to have significant periodic components for both men and women, with a fluctuation of once per month being the most common frequency component across the groups of individuals under analysis. Mathematical models are presented in order to describe and illustrate these principal fluctuations. Partners in couples, on average, were found to fluctuate together at a number of identified frequencies, and the phase lead/lag relationships of these frequencies are presented.

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