One important consideration regarding ERPs such as the FRN is that they are computed as the average signal across time-locked trials. Hence, ERPs inevitably only capture the stimulus- or response-driven partial phase alignment and power increases in the ongoing EEG brought about by the event (Le Van Quyen & Bragin, 2007; Sauseng et al., 2007). While this fixed-latency average amplitude approach has utility, it discards important information about task-relevant EEG oscillatory dynamics that may be important for interrogating the neurophysiology of reward processing (see Cohen, 2011). Using an approach broadly conceived as event-related brain dynamics (Makeig, Debener, Onton, & Delorme, 2004), advanced signal processing techniques such as short-time Fourier and wavelet transform can investigate the EEG signal in terms of frequency, power and phase. Importantly, characterizing oscillatory dynamics in this way probably more closely reflects the activity of underlying neuronal assemblies (Buzsáki, 2006).
