CHARACTERIZATION OF YÔGI MEDITATION STAGES BY EEG

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1 CHARACTERIZATION OF YÔGI MEDITATION STAGES BY EEG AV Cruz, AC Pimentel, CC Rosa, AC Rosa, Laseeb ISR IST Technical University of Lisbon Portugal Abstract The main objective of this work is to investigate the correlation between meditation stages and the hypnagogic stages of sleep and awakening. It reports the study on the brain electric activity during Yôga Svásthya meditation stages. These data were obtained by means of scalp electroencephalograms (EEGs), and confronted with the stages of meditation and hypnagogic EEG stages. The latter were based on established criteria through the study of the duration of individual occurrences of each of the nine considered hypnagogic EEG stages. Analysis made concerns time, frequency, power and signal amplitude. The results show that meditation stages reach only the first two hypnagogic EEG stages, and the spectral analysis of the EEG confirmed a dominance of rapid rhythms (beta) while the presence of lower ones (delta and theta) are not significant. Key Words EEG, meditation, Yôga, hypnagogic EEG stages.. Introduction. Brief Yôga historical approach Yôga [] appeared more than years ago, during the proto history, between the history and prehistory periods, in a civilization that lived in the Hindu s river valley, the Bravida civilization. The first registers of this practice refer to a dancer, Shiva, who belonged to that civilization and is pointed as the first Yôga practitioner. Only in century III B.C. Pátañjali has codified Yôga, based on the oral tradition and in the Upanishad, Maitri, Katha and Yogashara, important comments to Veda, the sacred Hinduism books. Although nowadays Yôga does have many different flavours, the most ancient philosophies had a naturalist perspective about the world around us, associating an effect to each cause; to reach the knowledge, the Yôga practitioner yogi proposes himself to find the track that leads to the samádhi (the last stage of meditation). So, the meditation starts with a sense abstraction, pratyhara, where the yogi tries to find an object or sound that allows him to more readily focus his attention. Afterwards the concentration phase begins, dháraná, in which the entire yogi s concentration is directed to the object chosen in the previews phase. The properly so called meditation, or contemplation, starts in the third phase, dhyána, in which the yogi acquires a linear intuition in terms of time, that is, during a short time period (a few seconds), he may have the sensation to pass away some minutes or a hole life time, like if time has expanded in the course of this meditation phase. In the fourth and last phase, the full consciousness is achieved, samádhi, in which the yogi achieves complete knowledge of himself. This project lays on the analysis of brain activities obtained by the electroencephalogram signal voltage difference measured on the scalp []. Few studies were made about EEGs analysis of meditation groups [], []. This work intends to compare the stages of Yôga meditation, through the EEGs analysis, with different stages of hypnagogic period presented in a study in [].. Hypnagogic stages according to Hori et al. The hypnagogic period occurs between the vigil stage and the first phase of sleep cycle. According to Hori et al., this period can be divided in to nine stages, in accordance with the characteristics of the EEG registers []. EEG stage Sequence of alpha activity, during a period of seconds, with minimum amplitude of µv. EEG stage Sequence of alpha activity, during a period of seconds, in which can be found at least % of alpha waves with amplitude superior or equal to µv. EEG stage Sequence of alpha activity during a period of seconds, in which the percentage of alpha waves with amplitude superior or equal to µv is inferior to % EEG stage EEG flattening: a period of seconds composed by suppressed waves with amplitude inferior to µv. EEG stage Ripples: a period of seconds composed of theta activity with low-voltage; amplitude between µv and µv and burst suppression. 8-

2 EEG stage Vertex sharp wave solitary: a period of seconds during which is distinguished one well-defined and isolated peak. EEG stage Vertex sharp wave train: a period of seconds during which at least two well-defined peaks are registered. EEG stage 8 Vertex sharp wave train and incomplete spindle: a period of seconds during which at least one well-defined vertex sharp wave and one incomplete spindle (duration inferior to, seconds and amplitude superior to µv and inferior to µv) are detected. EEG stage Spindles: considered when at least one well-defined spindle, with minimum duration of, seconds and µv amplitude, can be detected during a period of seconds.. Alpha wave train ( µv). Alpha wave intermitent (>%; µv). Alpha wave intermitent (<%; µv). EEG flattening (<µv). Ripples theta wave (µv<θ<µv). Vertex sharp wave solitary. Vertex sharp wave bursts 8. Vertex sharp wave and incomplete spindles (<,s; <µv; >µv). Spindles (,; µv) C in intervals of seconds; to this time interval was given the designation of epoch. Also, this study of stages meditation only covered the register of channel C in intervals with the same duration. The acquisition of data processed in this project was made in by a workgroup on the subject of Biomedical Engineering. The participants were individuals who practice Svásthya Yôga (average of years practice). The EEGs were made to two women and two men whose average age was years old. The data was collected in the Sleep Laboratory in the Egas Moniz Studies Center, at Hospital de Santa Maria, in Lisbon (Portugal), and was taken in digital format by a specific data acquisition program. The subjects were in lotus position and kept their eyes closed. Eight electrodes to EEG register were used three frontal, F, F, Fz, three central, C, C, Cz, and two occipital, O and O, all referenced to the contra-lateral mastoid (A or A), completing a total of eight electrodes, which correspond to eight channels to acquire. The sampling frequency was Hz.. Calibration Before treating the data, a calibration in terms of amplitude and temporal scales was necessary. In the beginning of each data gathering, a signal generator emitted a squared wave, which allowed the calibration of amplitude and time in each channel. Knowing that the signal amplitude, peak to peak, in the first seconds, was mv, the calibration was then possible by determining the voltage difference for each acquired point through the expression (), Figure. Typical EEG patterns during hypnagogic stages according to Hori et al. (adapted from [] ). amp( i) amp( i) = ampl ( i) ampl máx min ( i) [ mv ] (). Experimental Procedure. Materials/Subjects This research is based on a comparison between the data processed in this study and the results of the study referenced in [], which fell upon a population of young and healthy persons, males, aged between and years old (average,). They all attended Hiroshima University, taking a degree of Behavioral Science. After observation of EEGs, the individuals were separated in three different groups: those with low alpha activity exhibited less than % of alpha waves; those who revealed an alpha activity superior to 8%; and those with alpha activity in between more than % and less than 8%. The study focused only the individuals with high alpha activity. They used electrodes in the EEG s acquisition, and they studied only the register of channel where i is the ratio corresponding to each point, taking values between and.; amp max and amp min represent the maximum and minimum amplitude of the first calibration wave acquired in each channel. The time scale was calibrated knowing that the number of points between the minimum and maximum amplitude of that first calibration wave corresponds to an interval of one second. This value (number of points per second) is the sampling frequency, calculated for each C-A channel of every EEG. Once both scales are calibrated, a wave with amplitudes around millivolt and a time scale in seconds were obtained. Each individual s EEG was stored in three files of. points, which totalise, minutes, occurring small fluctuations according to the sampling frequency. It is important to become aware that one of the individuals only carried out the first third of the collect.

3 . Data Treatment In Table it can be observed the classification adopted concerning the frequency ranges to the different types of wave. Table. Frequency ranges to which correspond the several types of wave Waves Frequencies [Hz] Delta, -, Theta, - 8, Alpha 8, -, Sigma, -, Beta, -, An application was developed (in MATLAB) to compute the signal processing and study its characteristics, so it could be possible to verify to which stages, propound by Hori et al., each epoch of the signal corresponded. For a temporal analysis of the several waves it was necessary to apply a filter in time. A filter in frequency was avoided due to the large loss of information that would occur by applying the inverse FFT [], which would affect largely the final conclusions. The filters in time used were Butterworth bandwidth fourth order filters, for every frequency range. After the signal filtering, it was tested the amplitude and duration of the waves that characterize each stage for each Hori et al. criteria abovementioned. Sgnal power was calculated, on each artefact free epoch what sums, in average,. points the Fourier Transforms of 8 points. That is, the wave s frequencies to each of the small intervals (of 8 points) were obtained and then summed. To the last interval, with less than 8 points, zero padding was used. The criterion followed take into consideration the least loss of information possible and the sampling frequency. Next, the signal power for each epoch was computed by calculating the area of the signal s Fourier Transform. To evaluate the power in percentage, the signals for each frequency range found in Table were divided by the power value of the signal in the considered interval. For each frequency range, for each individual belonging to the population (N=), the power average (in percentage) per each epoch was calculated. The variation along time of the average power for each of the frequency ranges was then obtained.. Experimental Results from the study of the Hypnagogic Period The results shown in this sub-chapter are reported in []. The values in Table show the average time and the absolute percentage for each hypnagogic stage for the universe in study (N=). Table. Average times in seconds and in percentage for the nine hypnagogic stages, from the beginning of the EEG until minutes after reaching stage EEG stages Average Time (s) %,,,8,,8 8, 8, 8 8 8,, Total, Analysing Figure graphic, a frequency distribution of the durations of each EEG stage, short term intervals were confirmed to be more frequent in all stages, and more numerous at stages,, and 8, while the stages,, and have more long term intervals. Therefore it can be EEG stages 8 > Figure. Distribution in each stage of different time intervals (s) []. said the latter are stable while the others are unstable, because they quickly change between stages. In Figure graphic it can be seen the number of forward and backward transitions between stages. When analysing % of occurrences per EEG stage > Intervals duration (s)

4 Number of Transitions Transitions from this EEG stage... Figure. Transitions between EEG stages []. it one verifies that there are more transitions between stages, and. Forward and backward transitions are mainly from stage k to stage k±. Therefore, there were 8 transitions from stage to stage and from stage to stage. Transitions are smooth since backward transitions are more frequent than forward transitions. An example is that for stage, in the total, occurred upward changes and downward changes. In [] it is presented a chi-square analysis of this data, which confirm a higher percentage of downward transitions than upward in all EEG stages. This tendency leads to an approximately linear average hypnagogic stage evolution in time, passing from stage to stage, which correspond to the second phase of standard sleep, in about minutes.. Experimental Results obtained in the present study The experimental results obtained according to what was reported in the last sub-chapter are exposed. Thus, in Table is once more presented the average time for each hypnagogic stage, from the population in meditation stage (N=), and its absolute percentage. Table. Experimental results of average time for nine EEG stages, and its percentage, of all studied universe (N=)...to this EEG stage 8 Hypnagogic stages and defined by Hori et al. correspond to awaken phases of the sleeping cycle. In this study weren t found neither forward nor backward transitions for stages n >. It was confirmed a predominance in stage, which corresponds to a more relaxed period of the awaken period of the sleeping cycle, when alpha waves have lower amplitude. The high percentage of alpha waves may also occur because the individuals meditate with eyes shut, stimulating the rise of these waves in the waking stage. In Figure graphic it is shown the number of intervals multiple of an epoch for each EEG stage. Experimental EEG stages 8 > Figure Distribution in each stage of different time intervals (s) results show that the percentage of short-term intervals is larger for stage. This fact is due to sudden transitions from stage to stage and again to stage resulting on a momentary distraction that is quickly controlled. In the hypnagogic period there is a high quantity of transitions between stage (stable because there is a large percentage of a long-term interval in this stage) and (unstable because there is a large percentage of a shortterm interval (8) in this stage). According to it, these results show that stage is unstable because is less propitious for meditation, and stage is stable since it has Intervals duration (s) % of occurrences per EEG stage > EEG Stages Average Time (s) %,, 8,,8 8 Total,, Number of Transitions Transitions from this EEG stage......to this EEG stage 8 Figure. Transitions between EEG stages.

5 a large number of long-term intervals (8), and a small number of short-term intervals (). The graphic in Figure shows the transitions between EEG stages. As referred previously there are no transitions between EEG stages for n >. This happens because meditation is practiced while the individuals are awaken, (hypnagogic EEG stages and ), in order to be concentrated while meditating. The percentage of forward and backward transitions is %; therefore there is no dominance on the way transitions occurs. Figure shows the time evolution of the presence of each individual in the several stages. There are sudden EEG stage transitions between stages and with a longer permanence in stage. This longer duration in stage is due to the fact that this stage is more favorable to meditation than stage -- the brain is more active -- and than stage whose tendency is to change to stage, which is unstable and tends to pass to the first phase of sleep cycle which is not propitious for Yôgi meditation. The graphic in Figure shows the evolution in time of the band frequency (in relative percentage) of the signal (population average). When analysing it reveals that the relative percentage of the power energy in every power (relatif %) time (s) Figure. Time evolution of the stages for each individual of the population (N=). time (s) subject # subject # subject # subject # -Hz -8 Hz 8- Hz - Hz - Hz > Hz Figure. Evolution through time of power, in relative percentage, of the signal, to each frequency range. seconds interval was approximately constant through time; beta waves present the highest percentage, around %, because they are detected during concentration periods in the awaken phase, and delta waves showed the lowest percentage, around %, which is natural because they prevail during the phase of deep sleep.. Conclusions It is important to remark that the population in the present study was small. Even though some conclusions could be taken due to the fact that the results were quite homogeneous except for one individual that had a very high alpha activity, where the amplitude trough time of his alpha waves was much higher than the rest of the population, a fact that didn't influence the conclusions. The signals of the other individuals were very similar and no clear particularity was detected through time, except for some power peaks in the frequency interval to 8 Hz, which correspond to theta waves; these peaks didn't show any particular pattern and weren't classified by the Hori et al criteria. As for the distribution through the nine stages according to Hori et al., it was observed that all individuals were only in stages and, predominating in stage. That is, during the, minutes, in average, individuals went through some meditative stages without going through the first stage of the sleeping cycle. In the present study it was concluded that remaining for long term intervals in stage, which corresponds to a more relaxed stage of the awaken stage, as reported by Hori et al. criteria, demonstrated a high stability resulting from holding in a meditative stage, which requires a high capacity of being focused. There were only a few sparse moments of instability detected in the transition from stage to stage that were completely controlled, since individuals returned rapidly to stage ; this was probably due to slight perturbations in concentration. That long permanence of an individual in stage during meditation denoted a specific biological behavior due to, in a normal individual, the passage from the first hypnagogic stage to the first phase of deep sleep (eighth hypnagogic EEG stages) taking place in a considerable short time period. In terms of Hori classification, the meditation condition revealed a strong constancy through time. Analysis of signal s power average of all individuals for the different frequency ranges through time revealed a significant predominance of high rhythms over lower ones. The dominance of beta activity, in physiological terms, related to higher mental activity, which is a characteristic of concentrated stages. The weak presence of lower frequencies, theta and delta activity, indicated that the meditation stage is not a sleepy condition.

6 The signal power for different frequency range was very similar for stages and. In order to differentiate better the different meditation stages a more discriminative methodology has to be used. The Hori stages is more directed to the sleep on set problem, therefore not the adequate tool for this problem.. Acknowledgements We are grateful to Teresa Paiva, União Nacional de Yôga, Jorge Veiga and his disciples and to António Pereira. References [] Mestre DeRose, Yôga, Mitos e Verdades (Uni-Yôga: Martin Claret, 8). [] E. Niedermyer, Electroencephalography-Basic Principles, Clinical Applications and Related Fields (Baltimore-Munich, Edited by E. Niedermyer and F. H. Lopes da Silva, Urban & Schwarzenberg, 8 ). [] Douglas A., Newandee, M.S., Stanley S. Reisman, Measurement of the Electroencephalogram (EEG) in Group Meditation, IEEE,. -. [] An Analysis of Dimensional Complexity of Brain Electrical Activity During Meditation, N. Pradhan, D. Narayana Dutt, ProcRC.IEEE-EMBS & th BMESI,,.-. [] Hideki Tanaka, Mitsuo Hayashi, Tadao Hori, Statistical Features of Hypnagogic EEG Measured by a New Scoring System, Sleep, (),,-8. [] T. Hori, M. Hayashi, T. Morikawa Topographical EEG patterns and reaction time during hypnagogic experience. In: Ogilvie RD, Harsh JR, eds, Sleep onset: normal and abnormal processes. Washington DC: American Psychological Association, :-. [] Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing (Upper Saddle River, NJ: Prentice Hall, ).

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