Time-frequency (TF) data were derived using the S-transform signal processing method, introduced by Stockwell et al. [89]. S-transform has been explained in our previous papers [14,49]. S-transform is deduced from short-time Fourier transform and continuous Wavelet transform, and has a better flexibility and utility in the processing of non-stationary and complex signals [90]. This method has been applied in several recent studies to analyze time-frequency signals of event-related oscillations [4,14,65,66,91–93]. The S-transform is considered to be a generalization of the Gabor transform [94] and an extension to the continuous wavelet transform. The S-transform generates a time-frequency representation (TFR) of a signal by integrating the signal at each time point with a series of windowed harmonics of various frequencies as follows: ST(t,f)=∫−∞∞h(τ)|f|2πe−(t−τ)2f22e−i2πfτdτ where h(t)is the signal,f is frequency, τ is a translation parameter, the first exponential is the window function, and the second exponential is the harmonic function. The S-transform TFR is computed by shifting the window function down the signal in time by τ across a range of frequencies. The window function is Gaussian with 1/f 2 variance and scales
