oscillations (Freunberger et al., 2007, Freunberger et al., 2008, Gruber et al., 2005, Klimesch et al., 2007, Klimesch et al., 2004, Sauseng and Klimesch, 2008, Yeung et al., 2004, Yeung et al., 2007). It has also been demonstrated that averaged ERPs provide limited representation of the underlying event-related neural dynamics, whereas ERO analysis permits the separation of phase and amplitude effects of different frequencies that contribute to the averaged ERP waveform and therefore provide important insights into the neural dynamics underlying the ERP response (Fell et al., 2004, Makeig et al., 2004, Makeig et al., 2002, Onton and Makeig, 2006, Roach and Mathalon, 2008). Another advantage of ERO analyses is the potential for transfer of knowledge obtained by the analysis of spontaneous EEG to findings of ERP research and vice versa (e.g., Button et al., 2007), thereby facilitating the understanding of how different cortical networks are integrated in response to an external stimulus and how information can be transferred between such circuits (e.g., Carr et al., 2004), as well as dissociating cognitive processes which were not dissociable by ERPs (e.g., Branchey et al., 1988, see for review Sauseng and Klimesch, 2008).
