After acquisition, visual inspection removed epochs with movement and muscle artifacts. Data reduction was implemented using custom scripts in Matlab. A blink rejection algorithm rejected data segments where ocular activity exceeded +/- 75 microvolts in the vertical ocular channel, and an artifact rejection algorithm rejected segments with large fast deviations in amplitude in any channel (e.g., DC shifts and spikes) that may have eluded human inspection. Data were segmented into one-minute EEG blocks and further epoched into 117 epochs of 2.048 sec per block, overlapping by 1.5 s. This overlapping compensates for the minimal weight applied to the end of the epoch by the use of the Hamming window function. Following windowing, a Fast Fourier Transform (FFT) was applied to all artifact-free epochs. The power spectra from all artifact free epochs across all eight minutes were averaged to provide a summary spectrum for each resting session.2 Total alpha power (8-13 Hz) was then extracted from the spectrum for each resting session and site. An asymmetry score for each resting session for each reference montage was calculated by subtracting the natural
