QEEG pilot study shows objective changes of bioelectric brain activity as a result of TaKeTiNa
Quantitative event-related analysis of bioelectric correlates of cerebral activity has long been part of human medical research – even beyond traditional therapeutic indications (e.g. in epileptology). Thanks to modern high-performance computer systems and complex mathematic algorithms, these techniques not only lay the foundations for a new understanding of the relevance of these signals for classical neurological indications, but also open entirely new perspectives in regard to their usefulness for complex psychological questions and alternative therapeutic approaches. Despite impressive subjective improvements of these approaches – especially in indications considered as problematic by academic medicine (such as chronic pain etc.), methodical inadequacies have long made it impossible to verify them objectively, explaining the fact that they play no significant role in the medical canon, or at best an outside role.
With the aim of more closely investigating the remarkable success of TaKeTiNa especially in connection with refractory chronic pain syndrome, a pilot-study was carried out in summer 2010 at the TaKeTiNa Institute in Vienna. Neurophysiological correlates of cerebral brain activity were recorded using multi-channel electrode in participants attending a corresponding training program and subsequently offline analyzed using quantitative procedures.
As a-priori working hypothesis, we assumed that
a) certain chaotic phases participants experience repeatedly during a polyrhythmic TaKeTiNa journey, which – from the standpoint of learning theory – are of central importance for the development of new endogenous coping strategies to manage chronic illnesses, should actually be objectifiable and thus verifiable through corresponding neurophysiological correlates (e.g. sudden changes to the frequency bands typical for trance, hypnagogic consciousness phases, waking dreams, hypnosis, meditation, deep relaxation and increased learning ability).
b) time and duration of these phases can be clearly definable using QEEG analysis.
c) QEEG changes associated with these phases should be distinctly more pronounced than the initial values measured before the exercise phase, i.e. when participants were in a state of complete relaxation and calm.
d) characteristics of these objectively verifiable changes would neither spatially nor temporally correspond to other known QEEG changes (e.g. vigilance-dependent or medication-related).
The mathematical procedure used was a variation of the multichannel quantitative DAS time series trend analysis, which translates the spatio-temporal and energetic characteristics of the morphological dynamics of the continuously recorded EEG into a biometrically unique macro-indicator for the brain as the underlying macrosystem – which enables as a stochastic measurement (in analogy to the theory developed by Selye in the mid-twentieth century for the general adaptation syndrome formulated as integrative EEG-vigilance) the objective quantification of specific physiological functions within the framework of an integrative concept.
As a matter of fact – and this was (despite all hypotheses and theories ) somewhat surprising to all involved– we succeeded and were not only able to clearly discover and identify these chaotic phases, i.e. "falling out of the rhythm", within the EEG traces, but also nearly complete bioelectrical resting states (sometimes accompanied by sections of initial frustration from falling out of the rhythm journey) that were far beyond those states of relaxation achieved by participants immediately before the TaKeTiNa journey – despite optimal preconditions (see example below). In addition, it could be shown that the experiences gathered from the rhythm journey initiated an autonomous learning process that improved not only the ability of participants to integrate these unconsciously – during the TaKeTiNa exercises – learned relaxation techniques into daily live, but also empowered them to utilize them well-directed – e.g. during the resting period of the subsequent follow up EEG registration – (see differences in the measurement phases of rest before and after the actual exercise phase).
This is the first time that modern measurement and computer procedures have found objective proof for TaKeTiNa-induced neurophysiological changes in cerebral brain electrical activity, which can not only become the foundation for an accepted explanatory model for the remarkable effects of this rhythm-based therapeutical concept but also the starting point for completely new TaKeTiNa-supported biofeedback therapies.
PD Dr. med. Michael A. Überall
Institute for Neurosciences, Algesiology and Pediatrics – IFNAP
Graph of the energetic rhythm of the QEEG macro-indicator before, during and after an almost 90-minute TaKeTiNa rhythm journey. Note the inadequate relaxation during the resting phase before the actual exercise (characterized by the significant red color), the clear tension/activity during the polyrhythmic rhythm journey (strong red color), the sudden onset of four phases of (deep) relaxation – each associated with "falling out of rhythm" events (block-like blue/green phases) as well as the relaxation during the final resting phase (significant less red/yellow color compared to the initial situation).