Neurotherapy and Neurofeedback, as a research field and evidence-based practice in applied neurophysiology, are still unknown to Bulgarian population

Transcription

1 [6] MathWorks, MATLAB and Simulink for Technical Computing. Available: (accessed March 27, 2011) [7] Meyer-Baese U., (2007), Digital Signal Processing with Field Programmable Gate Arrays. Springer, USA Neurotherapy and Neurofeedback, as a research field and evidence-based practice in applied neurophysiology, are still unknown to Bulgarian population Vezenkov, S.R. Department of Language and Speech Pathology, South West University Neofit Rilski, vezenkov.stoyan@swu.bg Abstract: Neurofeedback and Neurotherapy, an ultramodern computerized evidence-based practice worldwide, was shown here to be a completely unknown to Bulgarian population. The powerful combination of modern computerized signal processing of neurophysiological parameters (qeeg, amplitude, frequency bands, coherence), applied statistics (neurometrics and its normative databases) and principles of applied neurosciences opened a novel research field for Bulgarian scientists and practitioners. These novel methods could be used widely as supplementary therapy to many drug and other therapies, especially in the field of psychopathology and language-speech pathology. Several related methods such as neurotherapy, neurofeedback, neurometrics, etc. are shortly reviewed here and their relationship discussed. Key words: neurotherapy, neurofeedback, BCI (brain-computer interface), evidence-based practice, applied neurosciences Short overview of the methods in applied neurophysiology Neurotherapy includes electrophysiological based methods of modulating the state of the brain. The well-known methods until now are transcranial direct current stimulation (tdcs), AC-stimulation including deep brain stimulation (DBS), transcranial magnetic stimulation (TMS) and neurofeedback. Neurofeedback in turn can be divided into two discovered methods: EEG biofeedback and DC (or infra slow wave) biofeedback. EEG biofeedback is a method for modulating the brain activity by mean of neurophysiological feedback using such parameters as power of given brain 217

2 Faculty of Mathematics & Natural Science FMNS 2011 waves (delta, theta, alpha, beta etc.), intercortical coherence, beta theta ratio etc. (Buzsaki, 2006) Neurotherapy should be distinguished from eastern methods of selfregulation, confined by relaxation, and placebo effect, which has distinct neuronal mechanism. Placebo had been shown could amount up to 30 % from the effects even of medical drugs. Any physiological parameter measured within the body could be fed back to the patient and modified in inherently learning process. The latter is the concept of biofeedback method in general. In particular, neurofeedback uses EEG parameters such as spectral characteristics (absolute amplitude, relative amplitude of a given frequency band, amplitude ratio etc.), coherence measures (recordings from different points of the scalp, C3 to F3, for example), intracranial current density processed by LORETA or s- LORETA. LORETA, low resolution electromagnetic tomography, is an EEG imaging technology allows for a tomographic representation of EEG sources in 3D space. QEEG method as a main part of neurofeedback is computing spectral characteristics (amplitude, frequency bands, coherence) of recorded EEG signal. Several types of neurofeedback have been developed depending on the parameter fed back: ERD-based neurofeedback (ERD event related desynchronization, measures the percentage change of the EEG amplitude in response to a given event); (Pfurtscheller et al., 2006) ERP-based neurofeedback (ERP event related potential); Self-regulation of HEG (hemoencephalography, measures the oxygenation of local blood flow by spectrophotometry); (Toomim et al., 1999) Self-regulation of fmri (functional magnetic resonance imaging, dependent on the level of blood oxygen); (Fox et al., 2007; Weiskopf et al., 2004) Self-regulation of evoked slow cortical potentials, in response to warning stimuli; (Strehl et al., 2006) If the modulating of neuronal activity might be directed to control of computer, the approach has been called brain-computer interface (BCI). (Bayliss et al., 2004) For example, a patient has been learned to control a computer cursor by self-regulation of his EEG slow cortical potentials (Birbaumer, 2006). The idea of BCI is similar to the basics of neurofeedback. 218

3 Fig.1. Relationship between the methods. BCI brain computer interface; HEG hemoencephalography; fmri functional magnetic resonance imaging; qeeg quantitative electroencephalography; LORETA - low resolution electromagnetic tomography; tdcs transcranial direct current stimulation; DBS deep brain stimulation; TMS transcranial magnetic stimulation Neurometrics was born from applied statistics and has defined the neurophysiological basis of brain dysfunction and brain normative functioning. The normative databases developed in neurometrics are used nowadays as a basis of defining neurofeedback protocols of treatment each particular case as evidence-based practice. To ensure the evidence-based practice the top Labs developed normative databases and give us opportunity to compare the computed parameters (qeeg) of recorded individual signal to the normative values. There are several known databases developed HBI, NxLink, Neurorep AQR, Novatech LORETA, SKIL, BRC and Neuroguide. The relationship between the above mentioned methods is presented in Fig. 1. The purpose of this study was to gather preliminary data in what degree Bulgarian population is informed to the following terms EEG, neurotherapy, neurofeedback and evidence-based practice. Method A preliminary simple on-line questionnaire was composed and distributed to 1000 persons randomly. The obtained data was imported and analyzed in MS Excel 2010 (Microsoft corp.) and put into tables and figures. Results From the distributed 1000 questionnaires, were obtained 295 fully finished (57,63% women, 42,37%). Sex and age frequencies (in %) 219

4 Faculty of Mathematics & Natural Science FMNS 2011 within the gro up are shown in Fig. 2. The geographic diffusion of the tested persons is presented in Fig. 3. The responses of the questions are presented in Table 1. Table 1. The responses to the main questions. Fig.3. Geographic spreading of the tested persons (in %) 220 Fig.2. Frequencies (in %) of the sex and age of the tested persons Question Yes (in %) No (in %) 1 Do you know what EEG is? 37* 63* 2 Do you know what Biofeedback is? * 21* 79* 3 Do you know what Neurofeedback is? * 19* 81* 4 Do you know what Neurotherapy is? Is there any difference between Neurofeedback and 38* 62* Neurotherapy?* 6 Do you know what evidence-based practice is? * 23* 77* *The questions were followed by the open text box with the instruction to write down the meaning of the terms Only 35%, 5,01%, 15,25%, 3,34% and 3,39% of the test persons tried to describe the terms respectively to the questions 1, 2, 3, 5 and 6 in the following open text boxes. From them only 34%, 4,4%, 6,1%, 0% and 0,34% respectively answered right. 3,73% from the answers to question 3 were that neurofeedback is identical to neurotherapy. 1,36% from the respondents of question 5 said that neurotherapy is part of the neurofeedback method and nobody answered correctly. The most correct answers were obtained to the question 1 34%. Conclusions

5 Except to the abbreviation EEG (34% correct answers) to all other questions the correct answers were less than 5%. These results suggested that the terms neurotherapy, neurofeedback and evidence-based practice are completely or partial unknown for Bulgarian people. A tremendous educational work lies before the research and public health institutions in Bulgaria to inform the population about the methods of applied neurosciences including biofeedback, neurotherapy, neurofeedback and the relevant evidence-based practices. References [1] Birbaumer, N. (2006) Breaking the silence: brain-computer interface (BCI) for communication and motor control. Psychophysiology 43(6), [2] Buzsaki, G. (2006) Rhythms of the brain. Oxford University Press [3] Bayliss, J.D., S.A. Inverso and A.Tentler (2004) Changing the P300 brain computer interface. Cyberpsychol. Behav. 7(6), [4] Fox, M.D. and M.E. Raichle (2007) Spontaneous fluctuations of brain activity observed with functional magnetic resonance imaging. Nat. Rev., Neuroscience 8, [5] Weiskopf, N., K. Mathiak, S.W. Bock, F. Scharnowski, R. Veit, W. Grodd, R. Goebel and N. Birbaumer (2004) Principles of a braincomputer interface (BCI) based on real-time functional magnetic resonance imaging (fmri). IEEE Trans. Biomed.Eng. 51(6), [6] Strehl, U., U. Leins, G.Goth, C.Klinger, T. Hinterberger and N. Birbaumer (2006) Self-regulation of slow cortical potentials: a new treatment for children with ADHD. Pediatrics 118(5), [7] Toomim, H. and J. Carmen (1999) Hemoencephalography (HEG). Biofeedback 27(4), [8] Pfurtscheller, G. and C. Neuper (2006) Future prospects of ERD/ERS in the cortex of brain-computer interface (BCI) developments. Prog. Brain Res