ABSTRACT
Over the years, the question arose again and again as to whether a “one-size-ts-all” approach or individualized training strategies should be preferred. e strength of each model is obvious: the “one-size-ts-all” approach is especially suitable for research, because there is no large variability of the training parameters and the results do not depend on the therapeutic skills and the experience of the clinician. e individualized approach is more attractive for the seasoned clinician because the training eects are quicker and more specic and the training can be adapted to the individual needs of each client. Still, the question is then how to adapt the training to the individual needs of the client. Can the treatment plan be derived from the norm-based interpretation of QEEG data8,9 or should the change of the client’s symptoms guide one through the training?10 In theory,
it might be an attractive idea to collect actual data and then train the client’s brain to a nominal value by rewarding amplitudes in frequency bands where the amplitude is too low compared to reference values, and inhibiting amplitudes in frequency bands where the amplitude is too high. Juri Kropotov, a specialist in the QEEG eld, calls this the “bulldozer” method: to cut whatever is too high and ll up whatever is too low.9 Nevertheless, daily clinical work shows that brains react idiosyncratically to any type of training protocol and this individual reaction is not readily predictable from the EEG. If we understand the brain’s neural circuits as excitable media, this is of course what we would expect, due to the intrinsic properties of excitable media.
