Marisel Villafane-Delgado

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—Functional connectivity brain networks have been shown to demonstrate interesting complex network behavior such as small-worldness. Transforming networks to time series has provided an alternative way of characterizing the structure of complex networks. However, previously proposed deterministic methods are limited to unweighted graphs. In this paper, we(More)
Resting-state fMRI (rs-fMRI) studies of the human brain have demonstrated that low-frequency fluctuations can define functionally relevant resting state networks (RSNs). The majority of these methods rely on Pearson's correlation for quantifying the functional connectivity between the time series from different regions. However, it is well-known that(More)
Speech intelligibility in adverse situations, such as reverberation and noise, is conserved until the degradations reach certain thresholds. Psychoacoustic studies have described the properties of speech that lead to the conservation of its intelligibility under those circumstances. The neural mechanisms that underlie the robustness of intelligibility in(More)
— Magnetoencephalography (MEG) is a brain imaging technique that non-invasively measures neurally-generated magnetic fields. Earlier MEG studies have focused on the neural responses to amplitude modulated (AM) auditory signals near 40Hz. Speech signals, however, contain a wide range of modulation rates, most of which are well below 40 Hz. Therefore we seek(More)
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