Continuous EEG data were high-pass filtered with a 1 Hz zero phase filter. Additional processing steps were identical to those in the ERP analysis above with two differences. Epochs were 5 s in length (2 s preceding the K onset and 3 s following it) to facilitate wavelet processing of low-frequency activity and trials were rejected for artifacts outside of a smaller range (±75 μV). The time–frequency analysis was done with a Morlet wavelet decomposition (Tallon-Baudry et al. 1997) using FieldTrip software (http://fieldtrip.fcdonders.nl/). Its Gaussian shape was defined by a constant ratio (σ f= f/7) and wavelet duration (6σ t), where f was the center frequency and σ t = 1/(2πσf). Typical wavelet decompositions convolve the EEG signal with complex wavelets for all frequencies of interest, moving sample-by-sample in the time domain. FieldTrip achieves the same result by multiplying the Fast Fourier Transform (FFT) of the wavelet by the FFT of the EEG signal. The inverse FFT of the resultant is then adjusted so that the time course of the data corresponds to the time course of the original signal.
