Fig. 2.

Schematic diagram illustrating the process of extracting each of the four main quantitative EEG variables used in this study, for one participant in the posterior region. The filtered, pre-processed EEG signal on each of the electrodes in posterior derivations (N = 35) is windowed in 2 s long epochs. The signal undergoes fast-Fourier transform (FFT) and using Bartlett’s method the absolute power spectral density (PSD) is calculated for each epoch, for each electrode. The relative PSD (rPSD) is then calculated to normalize the signal. The mean rPSD is obtained across posterior electrodes, for each epoch (up to 47 epochs) of the recording, and the percentage of the total power in the 3–20.75 Hz range allocated to the theta (4–7.75 Hz), alpha (8–13.75 Hz) and beta (14–20.75 Hz) frequency ranges is calculated. The frequency with the highest power within the slow-theta (4–5.5 Hz), fast-theta (5.5–7.75 Hz), alpha and theta-alpha (4–13.75 Hz) frequency ranges was identified within each epoch, and that value corresponded to the dominant frequency (DF). The mean DF and the standard deviation of the mean DF (DF variability; DFV) across epochs were then calculated. Finally, the DF within each epoch was assessed and was characterised to be in the slow-theta, fast-theta or alpha range. The epochs that were characterised by a DF within each of these ranges are shown as a percentage of the total number of epochs. These percentages were the slow-theta, fast-theta and alpha frequency prevalence (FP). The same procedure was followed for the other three cortical regions.