Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 53  |  Issue : 2  |  Page : 91-99

Yogic postures and brain wave activation: An experimental approach


1 Department of Physical Education and Sport Science, Visva-Bharati University, Santiniketan, West Bengal, India
2 Postgraduate Government Institute for Physical Education, Banipur, West Bengal, India

Date of Submission29-Apr-2021
Date of Decision22-Jun-2021
Date of Acceptance24-Sep-2021
Date of Web Publication22-Dec-2021

Correspondence Address:
Anup De
Former Senior Research Fellow, Department of Physical Education and Sport Science, Visva-Bharati University, Santiniketan, West Bengal
India
Login to access the Email id


DOI: 10.4103/ym.ym_34_21

Rights and Permissions
  Abstract 


Background: Yoga is a practice to control and develop the mental function. Scientists are trying to establish the effect of yoga on the various systems and organs in the human body by using different scientific methods and research techniques. The brain is one of the main targeted organs in yoga research.
Objective: The objective of this study is to identify the electrical responses of the brain after immediate yogasana practices.
Materials and Methods: Ten male (n=10) yoga practitioners having more than 8 years of experience in yogasana practice were selected as participants. Before and after immediate practices of six specific yoga postures were assessed on three different consecutive days for 15, 22.5, and 30 min. Delta, theta, alpha, sensory-motor rhythm (SMR), beta, and gamma amplitudes were assessed under the circumstance of electrical activity of the brain and measured using NeXus-10 device.
Results: The outcome of the brain wave components showed that there was a decrease in delta (9.12%, 12.3%, and 19.52%), theta (12.32%, 15.9%, and 16.09%), alpha (11.99%, 17.49%, and 13.21%), SMR (6.89%, 17.27%, and 13.5%), beta (0.29%, 13.95%, and 14.4%) amplitude immediately after 15, 22.5, and 30 min practice of yoga postures, respectively. In the case of gamma amplitude, initially, it increased 8.58% in 15 min practice, there after decreasing trend was observed in 22.5 min (11.47%) and 30 min practice (15.9%).
Conclusions: Immediate yogasana practices may enhance the functions of brain wave activity which increases motor activity, autonomic flexibility, and associates with a better cognitive state.

Keywords: Brain waves, cognitive function, electrical activity, electroencephalography, frontal lobe, yoga


How to cite this article:
De A, Mondal S, Ghosh SN. Yogic postures and brain wave activation: An experimental approach. Yoga Mimamsa 2021;53:91-9

How to cite this URL:
De A, Mondal S, Ghosh SN. Yogic postures and brain wave activation: An experimental approach. Yoga Mimamsa [serial online] 2021 [cited 2022 Jan 26];53:91-9. Available from: https://www.ym-kdham.in/text.asp?2021/53/2/91/333354




  Introduction Top


Yoga is one of the six ancient orthodox systems of Indian philosophy. It means to bind, join, attach, and yoke, to direct and concentrate one's attention on, to use, and apply. It means the disciplining of the intellect, the mind, the emotions, the will, which that yoga presupposes. It was collated, coordinated, and systematized by Patanjali in his classical work, the “Yoga Sutras” (Iyenger, 1966). Patanjali also defines yoga as the elimination of mental fluctuations and a wide range of techniques that slowly harmonize the mind and gradually induce more subtle perception. Raja Yoga (including Patanjali Yoga) is the science of mental discipline and includes the various methods of making the mind one-pointed which is concerned with exploring the inner world and unleashing the power and knowledge contained within. Before everything, yogasana (posture) is spoken of as the first part of Hatha Yoga which is defined by Patanjali as a steady and comfortable sitting position. The purpose of a yogasana in Patanjali yoga is to balance the different nerve impulses, feelings of pain and pleasures, heat and cold, and all other opposite sensations (Saraswati, 1976).

The ancient Sanskrit text “Hatharatnavali” identified 84 yogasanas (Muktibodhananda, 1985) and these yogasanas are claimed and believed to improve the different physiological systems and organs including circulatory, excretory, endocrine, muscular, nervous, and respiratory. (De & Mondal, 2019; Saraswati, 1969a). Apart from this, few specific yogasana practices are mainly targeted to the brain where it is seen that the brain becomes down from the body during the practice of the final position. Hence, the researcher is interested to identify the effect this brain targeted specific yogasana practices on brain wave activity and has selected the following six specific yogasanas for this present investigation; (i) sirshasana (head stand pose), (ii) sarvangasana (shoulder stand pose), (iii) vrischikasana (scorpion pose), (iv) chakrasana (wheel pose), (v) padahastasana (forward bending pose), and (vi) pranamasana (bowing pose).

The ancient books have called sirshasana (head stand pose) as the king of all asanas, its mastery gives one balance and poise, both physically and mentally. The skull encases the brain which controls the nervous system and the organs of sense. The brain is the seat of intelligence, knowledge, discrimination, wisdom, and power. The human body cannot prosper without a healthy brain. Regular practice of sirshasana makes healthy pure blood flow through the brain cells. This rejuvenates them to increase thinking power and to make thoughts clear. This asana is a tonic for people whose brains tire quickly. People suffering from the loss of sleep, memory, and vitality have recovered by the regular and correct practice of this asana and have become fountains of energy. One becomes balanced and self-reliant in pain and pleasures, loss and gain, shame and fame, and defeat and victory (Iyenger, 1966). Sirshasana revitalizes the entire body and mind. This asana reverses the effect of gravity on the body (Saraswati, 1969a). The whole nervous system which spreads throughout the body like a network of wires is directly or indirectly connected with this organ. When a man stands on his head, he sends a richer supply of arterial blood to the brain and thus maintains the health of not only the brain itself, but of the whole nervous system. The organs of the sense of sight, smell, hearing, and taste depend on their efficient functioning upon the different centers situated in the brain (Kuvalayananda, 1933).

Sarvangasana (shoulder stand pose) generally balances the nervous and endocrine systems. As the head remains firm in this inverted position and the supply of the blood to it is regulated by the firm chin lock, the nerves are soothed and headache-even chronic ones disappear. Due to the soothing effect of the pose on the nerves, those sufferings from hypertension, irritation, shortness of temper, nervous breakdown, and insomnia are relieved. The flexibility of the neck vertebrae is improved and the nerves passing through the neck to the brain are toned (Kuvalayananda, 1933; Saraswati, 1969a). It also tranquilizes the mind, relieves mental and emotional stress, and helps clear psychological disturbances boosting the immune system. Hence, the mind will be at peace and will feel the joy of life (Iyenger, 1966).

The practitioners of vrischikasana (scorpion pose) stamping on the head with feet, attempt to eradicate these self-destroying emotions and passions. By kicking head the practitioners seek to develop humility, calmness, and tolerance and thus to be freed of ego. The subjugation of the ego leads to harmony and happiness (Iyenger, 1966). The head which is the seat of knowledge and power is also the seat of pride, anger, hatred, jealousy, intolerance, and malice. This emotion is more deadly than the poison which the scorpion carries in its sting. The ancient text also describes that practice of this asana may improve the blood flow to the brain and pituitary gland, revitalizing all the body's systems. The arched position stretches and loosens the back, toning the nerves of the spine which may strengthen the sense of balance. However, much more controlled scientific experiment is required to reach any specific conclusion (Saraswati, 1969a).

Chakrasana (wheel pose) tones the spine by stretching it fully and keeps the body alert and supple. The back feels strong and full of life. It has a very soothing effect on the brain. It gives one great vitality, energy, and a feeling of lightness (Iyenger, 1966). Chakrasana may also be beneficial to the nervous system for better autonomic flexibility with parasympathetic modulation (Saraswati, 1969a). The spine and head region can be adjusted and activated during the practice of padahastasana (forward bending pose) (Iyenger, 1966). Spinal nerves are also stimulated and toned (Saraswati, 1969a). Whereas, pranamasana (bowing pose) is a preparatory practice for sirshasana (head stand pose), it allows the brain to gradually adopt the extra pressure in the head when the body is inverted. It gives many benefits of sirshasana, but to a lesser degree (Saraswati, 1969a).

The above discussion is made from the ancient texts or literatures and all of them very especially concluded that the above-mentioned six yogasanas may be beneficial for the improvement of brain functions and mental activities. Therefore, the present study is designed to investigate the immediate effect of these six specific yoga postures on the electrical activity of the brain. It has been also hypothesized that immediate yogasana practices may have positive impact on the brain wave activity similar to meditation or pranayama practice effects.


  Materials and Methods Top


Participants

In this investigation, ten healthy participants (n = 10) were interested to participate from the Department of Yogic Art and Science, Visva-Bharati University, Santiniketan, West Bengal. The inclusion criteria were the following: participant should be male and needed to have a normal health on routine clinical examination, all the participants were advanced/experienced practitioners and participated in Inter-University Yoga Competition. The exclusion criteria consisted of the previous history of disabling physical and mental diseases, individuals who had consumed alcohol in the last 24 h before the data collection, individuals with reports of using psychotropic drugs or having neurological disease, difficulty in focusing/concentrating, based on an interview, not to be involved in other ongoing research activity. Each participant was informed about the experimental procedures and signed the written consent form for participation in the study. Ethical approval was taken from the Institutional Ethics Committee for Human Research, Visva-Bharati University, West Bengal, India. A total of sixty samples were collected in three consecutive days for three different time durations, i.e., 15, 22.5, and 30 min. All the participants have 8.7 ± 2.49 years' experience in yogasana practice. The average age of the participants was 20 ± 1.28 years.

Assessments

In this investigation, six brain waves were assessed for the measurement of electrical responses of the brain activity, namely delta amplitude, theta amplitude, alpha amplitude, sensory-motor rhythm (SMR) amplitude, beta amplitude, and gamma amplitude, which are claimed and believed to identify the characteristics of the state of mental functions (De & Mondal, 2016).

Study design

The design of the study was pre-post repetitive assessments where all the participants underwent for three intervention conditions. The data were collected before and after the immediate yogasana practice for three consecutive days, but at the same time in different time schedule interventions in a systematic way. The ten participants were intervened with a self as control condition with a time series condition, i.e., 15, 22.5, and 30 min.

Intervention

In this experiment, six specific yoga postures, mainly associated with the brain and nervous system, were selected for intervention (Saraswati, 1969b) with a time series design i.e., 15, 22.5, and 30 min practice. The selected yoga postures were padahastasana (forward bending pose), pranamasana (bowing pose), sarvangasana (shoulder stand pose), chakrasana (wheel pose), vrischikasana (scorpion pose), and sirshasana (head stand). Detail of yogasana practice protocol is given in [Table 1].
Table 1: Details of yogasana practice protocol

Click here to view


Brain waves measurement

Nexus-10 Mark II (Mind Media BV, The Netherlands) instrument was employed for measuring brain wave activity. It is multi-channel neurophysiological monitoring and bio-feedback platform with 8 analogs and 2 digital inputs, supporting a wide range of sensors for 10 channels amplifier input, that utilizes blue-tooth wireless communication, USB and flash memory (SD) technologies.

Electroencephalography setting and recordings

Electroencephalography (EEG) signals were recorded using a 10-channel amplifier with a sampling frequency of 256 Hz., sampling rate 2048 Hz. and providing 12.2-bit A/D conversion for raw EEG data acquisitions (Kober, Schweiger, Reichert, Neuper, & Wood, 2017). The ground electrode was located at the middle of the forehead and two reference electrodes were placed on both sides of the ground electrodes. Electro gel was inserted through each sensor to improve conductance (Kober et al., 2017). After collecting the pre data, electrodes were not removed. After the practice of yogasana, all the electrodes were checked properly (fortunately everything was found in the correct condition) then it was proceeded for postdata immediately. Participants were seated in a relaxed and comfortable position on the chair while 10 min of resting-state EEG data were collected.

Electroencephalography data processing and extraction

EEG data processing and extraction were performed online using the Brain Vision Analyzer software (version 2.01, Brain Products GmbH, Munich, Germany, 2009) and filtered with a 0.5–40 Hz Bandpass online filter. EEG spectral amplitudes were calculated through Short Time Fourier Transform in overlapping 2-s epochs in each of the bandwidths (Keller & Garbacenkaite, 2015; Kober, Witte, Ninaus, Neuper, & Wood, 2013). Ocular artifacts such as eye blinks, muscular voluntary movements were detected and eliminated manually by visual inspection based on the information about electrooculography (EOG) activity provided by the EOG channel. After ocular artifact correction, automated rejection of other EEG artifacts (e.g., muscles) were performed (criteria for rejection: >50.00 μV voltage step per sampling point, absolute voltage value >±120.00 μV). All data points with artifacts were excluded from the EEG analysis (Kober et al., 2013, 2017).

Statistical analysis

In this study, descriptive statistics, namely mean, standard deviation, standard error of the mean, percentage changes were analyzed for the generalizing of pre to post-assessment outcomes. Paired t-test was used, and further, one-way analysis of variance (ANOVA) was also used for the measurements of significant differences of pre to post changes among the three different durations of yogasana practices. All the data were analyzed by using RStudio programming language software, version 3.1.2 (Northern Ave, Boston, MA 02210, USA).


  Results Top


The outcomes of the brain wave components showed that there was a decrease in delta (9.12%, 12.3%, and 19.52%), theta (12.32%, 15.9%, and 16.09%), alpha (11.99%, 17.49%, and 13.21%), SMR (6.89%, 17.27%, and 13.5%), and beta (0.29%, 13.95%, and 14.4%) amplitude immediately after 15 and 22.5 and 30 min practice of yoga postures, respectively. In the case of gamma amplitude, initially, it increased 8.58% in 15 min practice, there after decreasing trend was observed in 22.5 min (11.47%) and 30 min practice (15.9%). Detail descriptive result is given in [Table 2], and detail results of brain waves are given in [Figure 1],[Figure 2],[Figure 3],[Figure 4],[Figure 5],[Figure 6]. After yogasana practices, it was seen that no statistically significant difference was found between pre and post-assessment outcomes in delta, theta, alpha, SMR, beta, and gamma amplitude after 15, 22.5, and 30 min yogasana practices [Table 3]. ANOVA was analyzed among the differences from pre to post-changes on three different durations of yogasana practices to determine which the duration of changes is statistically significant and no significant difference was found in respect of all brain wave amplitudes. All the obtained p values were found to be >0.05 level; delta (p = 0.53, F = 0.66), theta (p = 0.66, F = 0.43), alpha (p = 0.86, F = 0.15), SMR (p = 0.9, F = 0.11), beta (p = 0.77, F = 0.26) and gamma amplitude (p = 0.77, F = 0.26) among three different durations (15, 22.5 and 30 min) of yogasana practices [Table 4].
Table 2: Observations of brain wave amplitudes after immediate yogasana practice

Click here to view
Figure 1: Delta amplitude changes after immediate yogasana practice

Click here to view
Figure 2: Theta amplitude changes after immediate yogasana practice

Click here to view
Figure 3: Alpha amplitude changes after immediate yogasana practice

Click here to view
Figure 4: Sensory-motor rhythm amplitude changes after immediate yogasana practice

Click here to view
Figure 5: Beta amplitude changes after immediate yogasana practice

Click here to view
Figure 6: Gamma amplitude changes after immediate yogasana practice

Click here to view
Table 3: Paired t-test of brain wave amplitudes between before and after yogasana practice

Click here to view
Table 4: Analysis of variance of brain wave activity among different durations of yogasana practices

Click here to view



  Discussion Top


The results of the present study showed that there was a general decreasing trend in brain wave amplitudes (delta, theta, alpha, SMR, beta, and gamma) in proportion with durations of yogasana practices. Most of the brain wave amplitudes decrease with the increase of yogasana practice durations. EEG amplitudes determine the other aspects of electrical brain activity in healthy people and it is responsible for improved cognitive function (Egner, Zech, & Gruzelier, 2004; Kober et al., 2017). Alpha amplitude reductions have been locally associated with increased motor cortical excitability (Sauseng, Klimesch, Gerloff, & Hummel, 2009), underlying cortical metabolism (Oishi et al., 2007), attention (Thut, Nietzel, Brandt, & Pascual-Leone, 2006), and globally with behavioral activation (Rougeul-Buser & Buser, 1997). Conversely, alpha synchronization has been shown to reflect functional inhibition of the motor cortex (Neuper, Wörtz, & Pfurtscheller, 2006). SMR amplitude reduction leads to improve motor imagery function over the motor cortex (Kober et al., 2013; Kübler et al., 2005). Delta wave is associated with the deepest states of consciousness (Santhosh & Agrawal, 2015). Activation of theta wave reduces anxiety, improves short-term memory, influences the process of building memories (Lisman & Idiart, 1995). Whereas, low amplitude beta waves are often associated with active, busy or anxious thinking, and active concentration (Baumeister, Barthel, Geiss, & Weiss, 2008).

In the human body, the brain is the supreme coordinator that regulates any kind of movement and function. The electrical activity of the brain results in the emergence of new oscillations which indicates the state of mental functions (De & Mondal, 2016). The scientists correlate this electrical activity with a state of mental activity as an intervention of yoga. An increase of frontal theta activity indicates intellectual concentration and meditative state which reduce nervousness and are negatively related to sympathetic activation (De, Mondal, & Deepeshwar, 2019; De & Mondal, 2019; Khadka, Paudel, Sharma, Kumar, & Bhattacharya, 2010). Theta wave also provides heightened intuition, healing of the body, reprogramming of the subconscious mind (Kumar & Valliamma, 2015). Theta waves are attributed to be responsible for concentration, relaxation, linked to memory formation and overall health issue (Lega, Jacobs, & Kahana, 2012; Tesche & Karhu, 2000), navigation (Buzsaki, 2011; Ekstrand, Waldén, & Hägglund, 2016) and is involved in spatial learning ability (Buzsáki, 2005). Scientists examined that asana meditation practice increases the alpha and theta brain wave activity that reduces anxiety (Desai, Tailor, & Bhatt, 2015; Trakroo, Bhavanani, Pal, Udupa, & Krishnamurthy, 2013).

Whereas, an increase in beta activity indicates a higher level of alertness and engagement task and enhancement in various cognitive abilities (Islam, 2020; Islam & Kundu, 2019) such as memory, attention, concentration, and reaction time (Bashein et al., 1992; Freeman, Mikulka, Prinzel, & Scerbo, 1999), while alpha and delta indicate synchronization of brain activity with greater alertness (Freeman et al., 1999). Domination of beta waves causes an elevation in blood sugar level which causes hyperglycemia, weight gain, uneasiness, anxiety (Ghosh, De, & Mondal, 2018; Premkumar & Vasuki, 2016; Roy & De, 2016). Increased beta waves over the motor cortex by a form of electrical stimulation called transcranial alternating current stimulation consistent with its link to isotonic contraction (Islam & De, 2018) produce a slowing of motor movements (Pogosyan, Gaynor, Eusebio, & Brown, 2009). Arousal theory also suggests that increased beta activity is associated with an increased mental activity or arousal (Andreassi, 2007) and it occurs when a person is in an attentive and active state of mind (Mandviwala et al., 2018). The beta signal physiologically correlates to alert, active but not agitated, general activation of mind and bodily functions (Korde & Paikrao, 2018). Scientists found that yoga meditation practice increases the alpha and beta values of around 90% of practitioners, which reflects an extreme relaxation state which increases alertness to the external world (Chandana et al, 2015, & Kochupillai, 2015).

Besides, improvement of alpha activity indicates greater mental silence, tasks requiring, memory and imagination (Cooper, Burgess, Croft, & Gruzelier, 2006; Jensen, Gelfand, Kounios, & Lisman, 2002), while the high frequency of alpha is mainly associated with centering, healing, and improving mind/body connection (De & Mondal, 2020; Korde & Paikrao, 2018). The lower alpha band appears for vigilance and attention while the upper alpha band is thought to reflect task-specific processes, i.e., perceptual and cognitive processes (Fink & Benedek, 2014; Klimesch, 1999). Alpha and theta can be interpreted as signifiers of increased attention with alpha specifically representing internalized attention as well as indexing states of relaxation (Aftanas & Golocheikine, 2002). Scientists established that breathing, meditation, and asana-based yoga practices increase the alpha wave activity which is associated with better perception (De & Ghosh, 2016) and calmness (Desai et al., 2015). Another researcher reported that Yoga Nidra produces alpha dominance in the brain which is characterized by mental relaxation (Kumar & Joshi, 2009).

Enhancing gamma power indicates a higher level of awareness and consciousness, for this, mind and body achieve new emerging energy. Gamma waves originate from the thalamus and it moves anteriorly that activates synchronize neuronal activity with establishing neuronal circuitry (Desai et al., 2015), that associates with enhanced attention, neural activation (Braboszcz, Cahn, Levy, Fernandez, & Delorme, 2017), higher mental activities, and perceptual tasks (Prasad, Matsuno, Bakardjian, Vialatte, & Cichocki, 2006). Scientists also examined that yogic intervention increases occipital gamma power that is related to enhanced sensory awareness (Cahn, Delorme, & Polich, 2010; Ganpat, Nagendra, & Muralidhar, 2011), increases overall brain wave activity which decreases anxiety and increases focusing ability (Desai et al., 2015).

SMR waves improve better motor control and cortical inhibitory functions (Fielenbach, Donkers, Spreen, & Bogaerts, 2017). An increase in SMR activity via neuro-feedback may be beneficial for people with learning difficulties (Tansey, 1984; Vernon et al., 2003), epilepsy (Egner & Sterman, 2006), and autism (Pineda et al., 2008). SMR amplitude is produced when the corresponding sensorimotor areas are idle, e.g. during states of immobility (Niedermeyer & da Silva, 2005). Delta wave may indicate the person is in an extreme relaxation state (Chandana et al., 2015) and its activity helps to improve declarative and explicit memory formation (Hobson & Pace-Schott, 2002). Delta waves can arise either in the thalamus or in the cortex, when it associates with the thalamus, coordination with the reticular formation arises (Gross, 1997; Maquet et al., 1997), and when in the cortex it improves the suprachiasmatic nuclei function that reflects in motor imagination (Mistlberger, Bergmann, & Rechtschaffen, 1987). Whereas, researchers reported that yoga practice significantly increases in delta wave coherence which is associated with the higher states of consciousness (Darrow. 1947; Ganpat et al., 2011).

The researchers measured only the frontal brain waves and tried to generalize the signals. But there were other brain regions and the researchers were unable to measure the whole brain waves. If it was done, some another results might be seen. A prospective study with more sample size could have enhanced more scopes for observations relating to the frontal lobe. The researchers tried to observe only the immediate effects with limited time of yogasana practices. If long term experimental design or intervention with increasing durations could be done, some another effects might be seen. Our study did not include a control group that received no treatment, which limited our ability to refute the argument that the observed improvement from pre to post intervention occurred naturally by the effects of yogasana.


  Conclusions Top


Immediate yogasana practices may enhance the functions of brain wave activity which increases motor activity and autonomic flexibility and associates with a better cognitive state.

Acknowledgments

The researchers are very much thankful to the University Grant Commission, Ministry of Human Resource Development, Government of India, for their support. We are also grateful to the Department of Physical Education and Sport Science and Department of Yogic Art and Science, Visva-Bharati University, India for providing participants and facilities for conducting this experiment so successfully.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.[67]



 
  References Top

1.
Aftanas, L. I., & Golocheikine, S. A. (2002). Non-linear dynamic complexity of the human EEG during meditation. Neuroscience Letters, 330(2), 143-146. doi: 10.1016/s0304-3940(02)00745-0.  Back to cited text no. 1
    
2.
Andreassi, J. L. (2007). Psychophysiology: Human Behavior & Physiological Response (5th ed.). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.  Back to cited text no. 2
    
3.
Bashein, G., Nessly, M. L., Bledsoe, S. W., Townes, B. D., Davis, K. B., Coppel, D. B., … & Hornbein, T. F. (1992). Electroencephalography during surgery with cardiopulmonary bypass and hypothermia. Anesthesiology, 76(6), 878-891. doi: 10.1097/00000542-199206000-00003.  Back to cited text no. 3
    
4.
Baumeister, J., Barthel, T., Geiss, K. R., & Weiss, M. (2008). Influence of phosphatidylserine on cognitive performance and cortical activity after induced stress. Nutritional Neuroscience, 11(3), 103-110. doi: 10.1179/147683008X301478.  Back to cited text no. 4
    
5.
Braboszcz, C., Cahn, B. R., Levy, J., Fernandez, M., & Delorme, A. (2017). Increased gamma brainwave amplitude compared to control in three different meditation traditions. PLOS One, 12(1), 1-27. doi: 10.1371/journal.pone.0170647.  Back to cited text no. 5
    
6.
Buzsáki, G. (2005). Theta rhythm of navigation: Link between path integration and landmark navigation, episodic and semantic memory. Hippocampus, 15(7), 827-840. doi: 10.1002/hipo.20113.  Back to cited text no. 6
    
7.
Buzsaki, G. (2011). Rhythms of the Brain. (1st ed) Oxford University Press, Madison Avenue, New York 10016: Oxford University Press.  Back to cited text no. 7
    
8.
Cahn, B. R., Delorme, A., & Polich, J. (2010). Occipital gamma activation during Vipassana meditation. Cognitive Processing, 11(1), 39-56. doi: 10.1007/s10339-009-0352-1.  Back to cited text no. 8
    
9.
Chandana, Vijayalakshmi, & Kochupillai, V. (2015). Quantitative analysis of EEG signal before and after Sudharshana Kriya yoga. International Journal of Public Mental Health and Neurosciences, 2(2), 19-22.  Back to cited text no. 9
    
10.
Cooper, N. R., Burgess, A. P., Croft, R. J., & Gruzelier, J. H. (2006). Investigating evoked and induced electroencephalogram activity in task-related alpha power increases during an internally directed attention task. Neuroreport, 17(2), 205-208. doi: 10.1097/01.wnr.0000198433.29389.54.  Back to cited text no. 10
    
11.
Darrow, C. W. (1947). Psychological and psychophysiological significance of the electroencephalogram. Psychological Review, 54(3), 157-168. doi: 10.1037/h0054893.  Back to cited text no. 11
    
12.
De, A., & Ghosh, S. N. (2016). Effect of healthy activity programmes on kinesthetic perception and self-concept among school students. International Journal of Advanced Scientific Research, 1(7), 29-33.  Back to cited text no. 12
    
13.
De, A., & Mondal, S. (2016). Improvement of brain function through combined yogic intervention, meditation and pranayama: A critical analysis. European Journal of Physical Education and Sport, 13(3), 89-96. doi: 10.13187/ejpe.2016.13.89.  Back to cited text no. 13
    
14.
De, A., & Mondal, S. (2019). Immediate effect of yogic postures on autonomic neural responses. Research in Cardiovascular Medicine, 8(4), 106-113. doi: 10.4103/rcm.rcm_26_19.  Back to cited text no. 14
    
15.
De, A., & Mondal, S. (2020). Yoga and brain wave coherence: A systematic review for brain function improvement. Heart and Mind, 4(2), 33-39. doi: 10.4103/hm.hm_78_19.  Back to cited text no. 15
    
16.
De, A., Mondal, S., & Deepeshwar, S. (2019). Single bout of yoga practices (Asana) effect on low frequency (LF) of heart rate variability – A pilot study. International Journal of Medicine and Public Health, 9(4), 160-163. doi: 10.5530/ijmedph.2019.4.34.  Back to cited text no. 16
    
17.
Desai, R., Tailor, A., & Bhatt, T. (2015). Effects of yoga on brain waves and structural activation: A review. Complementary Therapies in Clinical Practice, 21(2), 112-118. doi: 10.1016/j.ctcp.2015.02.002.  Back to cited text no. 17
    
18.
Egner, T., & Sterman, M. B. (2006). Neurofeedback treatment of epilepsy: From basic rationale to practical application. Expert Review of Neurotherapeutics, 6(2), 247-257. doi: 10.1586/14737175.6.2.247.  Back to cited text no. 18
    
19.
Egner, T., Zech, T. F., & Gruzelier, J. H. (2004). The effects of neurofeedback training on the spectral topography of the electroencephalogram. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 115(11), 2452-2460. doi: 10.1016/j.clinph.2004.05.033.  Back to cited text no. 19
    
20.
Ekstrand, J., Waldén, M., & Hägglund, M. (2016). Hamstring injuries have increased by 4% annually in men's professional football, since 2001: A 13-year longitudinal analysis of the UEFA elite club injury study. British Journal of Sports Medicine, 50(12), 731-737. doi: 10.1136/bjsports-2015-095359.  Back to cited text no. 20
    
21.
Fielenbach, S., Donkers, F. C., Spreen, M., & Bogaerts, S. (2017). Neurofeedback as a treatment for impulsivity in a forensic psychiatric population with substance use disorder: Study protocol of a randomized controlled trial combined with an N-of-1 clinical trial. JMIR Research Protocols, 6(1), e13. doi: 10.2196/resprot.6907.  Back to cited text no. 21
    
22.
Fink, A., & Benedek, M. (2014). EEG alpha power and creative ideation. Neuroscience and Biobehavioral Reviews, 44(100), 111-123. doi: 10.1016/j.neubiorev.2012.12.002.  Back to cited text no. 22
    
23.
Freeman, F. G., Mikulka, P. J., Prinzel, L. J., & Scerbo, M. W. (1999). Evaluation of an adaptive automation system using three EEG indices with a visual tracking task. Biological Psychology, 50(1), 61-76. doi: 10.1016/s0301-0511(99)00002-2.  Back to cited text no. 23
    
24.
Ganpat, T. S., Nagendra, H. R., & Muralidhar, K. (2011). Effects of yoga on brain wave coherence in executives. Indian Journal of Physiology and Pharmacology, 55(4), 304-308.  Back to cited text no. 24
    
25.
Ghosh, S. N., De, A., & Mondal, S. (2018). Stress hormones and sports performance: A critical analysis. International Journal of Physiology, Nutrition and Physical Education, 3(1), 1752-1757.  Back to cited text no. 25
    
26.
Gross, R. (1997). Psychology: The Science of Mind and Behaviour. East Sussex, United Kingdom: Psychology Press.  Back to cited text no. 26
    
27.
Hobson, J. A., & Pace-Schott, E. F. (2002). The cognitive neuroscience of sleep: Neuronal systems, consciousness and learning. Nature Reviews. Neuroscience, 3(9), 679-693. doi: 10.1038/nrn915.  Back to cited text no. 27
    
28.
Islam, M. S. (2020). Introducing drone technology to soccer coaching. International Journal of Sports Science and Physical Education, 5(1), 1-4. doi: 10.11648/j.ijsspe.20200501.11.  Back to cited text no. 28
    
29.
Islam, M. S., & De, A. (2018). Functional hamstring to quadriceps strength ratio (H:Q) and hamstrings injury of soccer players: A qualitative analysis. Orthopedics and Sports Medicine: Open Access Journal, 2(2), 126-132. doi: 10.32474/OSMOAJ.2018.02.000133.  Back to cited text no. 29
    
30.
Islam, M. S., & Kundu, B. (2019). Digit ratio and soccer. Orthopedics and Sports Medicine: Open Access Journal, 3(1), 227-230. doi: 10.32474/OSMOAJ.2019.03.000154.  Back to cited text no. 30
    
31.
Iyenger, B. K. (1966). Light on Yoga (2003rd ed.). Noida, Uttar Pradesh: Harper Collins Publishers India.  Back to cited text no. 31
    
32.
Jensen, O., Gelfand, J., Kounios, J., & Lisman, J. E. (2002). Oscillations in the alpha band (9-12 Hz) increase with memory load during retention in a short-term memory task. Cerebral Cortex (New York, N.Y.: 1991), 12(8), 877-882. doi: 10.1093/cercor/12.8.877.  Back to cited text no. 32
    
33.
Keller, I., & Garbacenkaite, R. (2015). Neurofeedback in three patients in the state of unresponsive wakefulness. Applied Psychophysiology and Biofeedback, 40(4), 349-356. doi: 10.1007/s10484-015-9296-7.  Back to cited text no. 33
    
34.
Khadka, R., Paudel, B. H., Sharma, V. P., Kumar, S., & Bhattacharya, N. (2010). Effect of yoga on cardiovascular autonomic reactivity in essential hypertensive patients. Health Renaissance, 8(2), 102-109. doi: 10.3126/hren.v8i2.4421.  Back to cited text no. 34
    
35.
Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research. Brain Research Reviews, 29(2–3), 169-195. doi: 10.1016/s0165-0173(98)00056-3.  Back to cited text no. 35
    
36.
Kober, S. E., Schweiger, D., Reichert, J. L., Neuper, C., & Wood, G. (2017). Upper alpha based neurofeedback training in chronic stroke: Brain plasticity processes and cognitive effects. Applied Psychophysiology and Biofeedback, 42(1), 69-83. doi: 10.1007/s10484-017-9353-5.  Back to cited text no. 36
    
37.
Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013). Learning to modulate one's own brain activity: The effect of spontaneous mental strategies. Frontiers in Human Neuroscience, 7, 695. doi: 10.3389/fnhum.2013.00695.  Back to cited text no. 37
    
38.
Korde, K. S., & Paikrao, P. L. (2018). Analysis of EEG signals and biomedical changes due to meditation on brain: A review. International Research Journal of Engineering and Technology, 5(1), 603-606.  Back to cited text no. 38
    
39.
Kübler, A., Nijboer, F., Mellinger, J., Vaughan, T. M., Pawelzik, H., Schalk, G., … & Wolpaw, J. R. (2005). Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology, 64(10), 1775-1777. doi: 10.1212/01.WNL.0000158616.43002.6D.  Back to cited text no. 39
    
40.
Kumar, A. R., & Valliamma, G. (2015). A study on improving physiological and psychological personalities of the students by Vethathiri Maharishi′s nine-center meditation using electroencephalography. International Journal of Educational and Psychological Researches, 1(2), 166-170. doi: 10.4103/2395-2296.152247.  Back to cited text no. 40
    
41.
Kumar, K., & Joshi, B. (2009). Study on the effect of pranakarshan pranayama and yoga nidra on alpha EEG & GSR. Indian Journal of Traditional Knowlwdge, 8(3), 453-454.  Back to cited text no. 41
    
42.
Kuvalayananda, S. (1933). Asanas (9th ed.). Maharashtra: Forever News, Kaivalyadhama, Swami Kuvalayananda Marg.  Back to cited text no. 42
    
43.
Lega, B. C., Jacobs, J., & Kahana, M. (2012). Human hippocampal theta oscillations and the formation of episodic memories. Hippocampus, 22(4), 748-761. doi: 10.1002/hipo.20937.  Back to cited text no. 43
    
44.
Lisman, J. E., & Idiart, M. A. (1995). Storage of 7 +/- 2 short-term memories in oscillatory subcycles. Science (New York, N.Y.), 267(5203), 1512-1515. doi: 10.1126/science.7878473.  Back to cited text no. 44
    
45.
Mandviwala, J., Yadav, K. N., Baral, S. K., Vyas, N., Patil, R., & Yamin, S. (2018). Meditation analyzer using brainwaves. Open Access Intrnational Journal of Science and Engennering, 3(4), 1-6.  Back to cited text no. 45
    
46.
Maquet, P., Degueldre, C., Delfiore, G., Aerts, J., Péters, J. M., Luxen, A., … & Franck, G. (1997). Functional neuroanatomy of human slow wave sleep. Journal of Neuroscience, 17(8), 2807-2812. doi: 10.1523/JNEUROSCI.17-08-02807.1997.  Back to cited text no. 46
    
47.
Mistlberger, R. E., Bergmann, B. M., & Rechtschaffen, A. (1987). Relationships among wake episode lengths, contiguous sleep episode lengths, and electroencephalographic delta waves in rats with suprachiasmatic nuclei lesions. Sleep, 10(1), 12-24.  Back to cited text no. 47
    
48.
Muktibodhananda, S. (1985). Hatha Yoga Pradipika (2016th ed.). Munger, Bihar, India: Yoga Publications Trust.  Back to cited text no. 48
    
49.
Neuper, C., Wörtz, M., & Pfurtscheller, G. (2006). ERD/ERS patterns reflecting sensorimotor activation and deactivation. In Progress in Brain Research (Vol. 159, pp. 211-222). Netherlands: Elsevier. doi: 10.1016/S0079-6123(06)59014-4.  Back to cited text no. 49
    
50.
Niedermeyer, E., & da Silva, F. H. (2005). Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. New York, USA: Lippincott Williams & Wilkins.  Back to cited text no. 50
    
51.
Oishi, N., Mima, T., Ishii, K., Bushara, K. O., Hiraoka, T., Ueki, Y., … & Hallett, M. (2007). Neural correlates of regional EEG power change. NeuroImage, 36(4), 1301-1312. doi: 10.1016/j.neuroimage.2007.04.030.  Back to cited text no. 51
    
52.
Pineda, J. A., Brang, D., Hecht, E., Edwards, L., Carey, S., Bacon, M., … & Rork, A. (2008). Positive behavioral and electrophysiological changes following neurofeedback training in children with autism. Research in Autism Spectrum Disorders, 2(3), 557-581. doi: 10.1016/j.rasd.2007.12.003.  Back to cited text no. 52
    
53.
Pogosyan, A., Gaynor, L. D., Eusebio, A., & Brown, P. (2009). Boosting cortical activity at beta-band frequencies slows movement in humans. Current Biology, 19(19), 1637-1641. doi: 10.1016/j.cub.2009.07.074.  Back to cited text no. 53
    
54.
Prasad, R., Matsuno, F., Bakardjian, H., Vialatte, F., & Cichocki, A. (2006). EEG changes after bhramari pranayama. SCIS & ISIS, Tokio, Japan, 4, 390-395.  Back to cited text no. 54
    
55.
Premkumar, N. K., & Vasuki, D. R. (2016). Extraction and analysis of EEG waves for the study of enhancement and rejuvenation of brainwaves through meditation. International Journal of Pharmacy & Technology, 8(2), 13481-13488.  Back to cited text no. 55
    
56.
Rougeul-Buser, A., & Buser, P. (1997). Rhythms in the alpha band in cats and their behavioural correlates. International Journal of Psychophysiology, 26(1–3), 191-203. doi: 10.1016/S0167-8760(97)00764-2.  Back to cited text no. 56
    
57.
Roy, T., & De, A. (2016). Beneficial effect of bratachari and folk games programme on blood lipid profile of obese adolescent. International Journal of Physical Education, Sports and Health, 3(6), 128-133.  Back to cited text no. 57
    
58.
Santhosh, J., & Agrawal, G. (2015). Spatio-Temporal EEG Spectral Analysis of Shambhavi Maha Mudra Practice in Isha Yoga (pp. 1-6). New Delhi, India, Indian Institute of Technology.  Back to cited text no. 58
    
59.
Saraswati, S. S. (1969a). Asana Pranayama Mudra Bandha (2012th ed.). Munger, Bihar, India: Yoga Publications Trust.  Back to cited text no. 59
    
60.
Saraswati, S. S. (1969b). Asana Pranayama Mudra Bandha (2002nd ed.). Munger, Bihar, India: Yoga Publications Trust.  Back to cited text no. 60
    
61.
Saraswati, S. S. (1976). Four Chapter on Freedom (2006th ed.). Munger, Bihar, India: Yoga Publications Trust.  Back to cited text no. 61
    
62.
Sauseng, P., Klimesch, W., Gerloff, C., & Hummel, F. C. (2009). Spontaneous locally restricted EEG alpha activity determines cortical excitability in the motor cortex. Neuropsychologia, 47(1), 284-288. doi: 10.1016/j.neuropsychologia.2008.07.021.  Back to cited text no. 62
    
63.
Tansey, M. A. (1984). EEG sensorimotor rhythm biofeedback training: some effects on the neurologic precursors of learning disabilities. International Journal of Psychophysiology, 1(2), 163-177. doi: 10.1016/0167-8760(84)90036-9.  Back to cited text no. 63
    
64.
Tesche, C. D., & Karhu, J. (2000). Theta oscillations index human hippocampal activation during a working memory task. Proceedings of the National Academy of Sciences, 97(2), 919-924. doi: 10.1073/pnas.97.2.919.  Back to cited text no. 64
    
65.
Thut, G., Nietzel, A., Brandt, S. A., & Pascual-Leone, A. (2006). α band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. Journal of Neuroscience, 26(37), 9494-9502. doi: 10.1523/JNEUROSCI.0875-06.2006.  Back to cited text no. 65
    
66.
Trakroo, M., Bhavanani, A. B., Pal, G. K., Udupa, K., & Krishnamurthy, N. (2013). A comparative study of the effects of asan, pranayama and asan-pranayama training on neurological and neuromuscular functions of Pondicherry police trainees. International Journal of Yoga, 6(2), 96-103. doi: 10.4103/0973-6131.113398.  Back to cited text no. 66
    
67.
Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., … & Gruzelier, J. (2003). The effect of training distinct neurofeedback protocols on aspects of cognitive performance. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 47(1), 75-85. doi: 10.1016/s0167-8760(02)00091-0.  Back to cited text no. 67
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
Conclusions
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed796    
    Printed14    
    Emailed0    
    PDF Downloaded76    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]