by frequency transformations such as S-transform (Stockwell et al., 1996) or other wavelet-type analyses provide a time-based decomposition of the EEG signal associated with an event (van Vugt et al., 2007), and generate amplitude/power measures and phase information. EROs influence the timing of neural activity and coordinate synchronous activity in groups of active neurons (Fries, 2005). Synchronization of oscillations underlie self-organization of neural networks and are important indices of maturity and efficiency of these networks, providing an energy-efficient mechanism for coordination of distributed neural activity (Buzsaki and Draguhn, 2004). Phase relationships between signals from different brain regions provide a measure of temporal interactions between transient active cognitive networks; hence phase synchrony can be considered as an index of “crosstalk” or communication in the brain (Sauseng and Klimesch, 2008; Uhlhaas et al., 2010) and aids in the study of functional connectivity. High-frequency (i.e., beta and gamma) EROs are implicated in short-range communication, whereas low-frequency (i.e., delta, theta, and alpha) EROs are involved in longer-range communication between brain areas (von Stein and Sarnthein, 2000).
