Much of the work in alpha NFT has focused on evaluating changes in alpha amplitude. However, the generation mechanism of training-induced alpha activity has not yet been clarified. The present study aimed to identify sources of training-induced alpha activity through four temporal/spectral analytic techniques, i.e., the max peak average (MPA), positive average (PA), negative average (NA) and event-related spectral perturbation average (ERSPA) methods. Thirty-five healthy participants were recruited into an alpha group receiving feedback of 8–12-Hz amplitudes, and twenty-eight healthy participants were recruited into a control group receiving feedback of random 4-Hz amplitudes from the range of 7 to 20 Hz. Twelve sessions were performed within 4 weeks (3 sessions per week). The control group had no change in the amplitude spectrum. In contrast, twenty-nine participants in the alpha group showed significant alpha amplitude increases exclusively and were identified as “responders”. A whole-head EEG was recorded for the “responders” after NFT. The epochs of training-induced alpha activity from whole-head EEG were averaged by four different methods for equivalent current dipole source analysis. High agreement and Cohen’s kappa coefficients on dipole source localization between each method were observed, showing that the dipole clusters of training-induced alpha activity were consistently located in the precuneus, posterior cingulate cortex (PCC) and middle temporal gyrus. The residual variance (goodness of fit) for dipole estimation of the MPA was significantly smaller than that of the others. Our findings indicate that the precuneus, PCC and middle temporal gyrus play important roles in enhancing training-induced alpha activity. The four averaging methods (especially the MPA method) were suitable for investigating sources of brainwaves. Additionally, three dipoles can be used for dipole source analysis of training-induced alpha activity in future research, especially the training sites are around the central regions.
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