EEG based interpretation of human Brain during Yoga and
Meditation : A systematic review
Dr. Padmavathi Kora1″,
Abstract
In this paper our goal is to discover the modifications in the EEG brainwave designs on
yoga and deep meditation. Past research has revealed huge mental and physical medical
advantages related with yoga. In general yoga can be classified as posture exercise (asana)”,
breathing (pranayama, Kriya), and deep meditation (Sahaj) practice. Studies shows psycho-
logical well-being results of these practices decreases anxiety, stress and improvement in brain
performance after yoga intercessions. Comparative investigations have additionally demon-
strated intellectual favorable circumstances among yoga professionals versus non-specialists.
The psychological wellness and intellectual advantages of yoga are obvious, however the
physiological and basic changes in the cerebrum remain a subject that needs to be studied.
Accordingly, the reason for this investigation was to look at impacts of yoga on mind waves
on physical and mental health.
Keywords:
1. Introduction
The demand for yoga has risen up nowa-
days as not just activity of exercise but as a
means of reducing anxiety and stress, improv-
ing physical fitness, and balancing mood and
overall wellbeing. It has been shown to im-
prove mood and life satisfaction scores while
reducing aggressiveness, emotional distress”,
and anxiety (1), (2). Interventions involv-
Email address: padma386@gmail.com (Dr.
Padmavathi Kora)
ing yoga have also shown to improve vari-
ous health, and physical fitness parameters
at both physiological and cellular levels.
Yoga has been demonstrated to have several
positive effects on cardiorespiratory health.
Multiple studies support evidence that yoga
can increase cardiorespiratory efficiency and
respiratory capacity (3), (4). 6 months of
yoga practice results in mainly decreasing
resting heart rate and blood pressure (3).
Yoga has also been beneficial for individuals
with metabolic conditions such as Type-2 di-
abetes and obesity, as it has shown to increase
Preprint submitted to Elsevier January 10, 2019
glycemic control and nerve conduction veloc-
ity, and decrease BMI and total serum choles-
terol level (5), (6). In addition the cardiores-
piratory and metabolic improvements, yoga
activity correlated with musculo-skeletal ben-
efits. Weight-bearing yoga activity can atten-
uate bone re-absorption and decrement the
risk of bone density in menopausal women
(7). An asana-based activity is standard
thought of as ’yoga’ in midwestern society.
Among the three types of yoga, this activ-
ity is mostly used as a form of practice”,
as it requires the participation of various
muscles(5). Yoga asanas involve different
body positions that the individual executes
dynamically. Each asana may also be held
isometrically for an allotted amount of time
or breath cycles. Vinyasa, bikram, kundalini
and hatha yoga are types of yoga that fall
into the category of asana-based yoga. These
models can be practiced individually or in a
classroom learning.
Many people take yoga a kind of medita-
tion. This practice session gives a meaning-
ful relaxation behavior in brain through with
the separation of thoughts and/or concentra-
tion on one’s own breathing. Meditation is
typically practiced sitting down and, aside
from breathing, does not require any dynamic
movements. Similar to asana-based practice”,
meditation can be practiced on an individual
basis or can be instructed in a group environ-
ment (7). The third type of yoga practice is
a breathing-based practice. This practice in-
volves purposeful inhalations and exhalations
at a designated speed and intensity, which is
referred to as pranayama. Pranayama can
also be broken down into various breathing
practices, which include sudarshan kriya and
bhastrika pranayama. Breathing-based prac-
tices are also practiced in a still and seated
position and can be practiced on an individ-
ual or classroom basis (8)”,(9). The above
three categories of yoga can be combined
into one session or can be practiced sepa-
rately. Asana, meditation, and breathing-
based practices elicit various and specific ef-
fects on cognitive and neurological functions.
In particular, their effects on brain waves and
structural activation will be further explored
in this review. With the positive impact of
yoga on the body, recent research has be-
gun to explore the cognitive effects of yoga.
Previous qualitative studies have shown sub-
ject self-reported positive effects of yoga on
depression and anxiety (10), (11). Various
studies have also shown an increase in cog-
nitive performance after a yoga intervention
or greater perceived cognition in practitioners
versus non practitioners. A study examining
108 school children, ages 10e17, assessed spa-
tial and verbal memory before and after a 10
day pranayama training protocol. The results
showed an improvement in spatial and ver-
bal memory scores after the Sudarshan Kriya
yoga training protocol (12). A study examin-
ing adjunctive treatments for bipolar patients
saw a high rate of self-reported cognitive ben-
efits as a result of yoga practice. Many sub-
jects with bipolar depression reported that
ongoing yoga practice assisted with their fo-
cus and sense of acceptance (13). Also related
to cognitive benefits, another study showed
that 6 weeks of hatha yoga improved work-
ing memory and attention switching ability
in healthy older adults (14). Breathing based
2
yoga, in the form of fast and slow pranayama
practice has also shown to improve cogni-
tive performance, in the domains of reac-
tion time (15). After 12 weeks of pranayama
practice, 84 healthy adult participants had
significantly improved scores in psychomet-
ric tests that included the letter cancellation
test, trail making tests A and B, forward and
reverse digit spans and auditory and visual
reaction times for red light and green light.
The improvement in cognitive performance
from yoga practice and interventions is ev-
ident, but the mechanisms behind this im-
provement remain unclear. Changes in cog-
nition are often a result of changes in neu-
ronal activity, structural activation, and gen-
eral structural changes within the brain. Un-
derstanding what can elicit changes that are
occurring within the brain that lead to im-
proved cognition, can give insight into the de-
velopment of cognitive interventions in both
healthy and clinical populations. Therefore”,
the purpose of this review is to examine the
specific neural changes that occur as a re-
sult of yoga practice which may influence the
mental health and overall wellbeing.
2. Background
It has been revealed in a study that elec-
tric function connectivity differs in five tra-
ditions of meditation like Tibetan Buddhists
(TB), Qigong, Sahaja Yoga (SY), Ananda
Marga Yoga (AY), and Zen (16). Theresults
have been taken for delta and beta2 bands
because all five meditations showed signifi-
cant changes in these two bands. In delta
band of TB group, moving out of medita-
tion showed left to right posterior connection
while it showed anterior left to right poste-
rior connectivity in AY group. Such types of
guesses evidently become impossible, for ex-
ample, Qigong, since it includes a large num-
ber of connections. This research shows the
common features in five traditions of medi-
tation butwith noCGand it did not explore
the difference. Analysis of principal func-
tional connectivities during delta band re-
flected that interdependence between differ-
ent functions is lowered with practicing med-
itation irrespective of meditation style and
inhibitory and excitatory (delta and beta2
band activities) brain region connectivities
show this reduction (17).
In another study, state effects of two medi-
tation styles, mindfulness breathing and lov-
ing kindness (or metta) meditation, have
been investigated (18).Effectsonprefrontal al-
pha asymmetry have been discussed. Sub-
jects low in brooding showed response to lov-
ing kindness meditation while the opposite
was observed for subjects with high brood-
ing. Comparisons to rest group showed use-
ful state effects of both the styles of medita-
tion. It accounts for their clinical use for pre-
viously depressed patients, although various
limitations like unspecific factors, small sam-
ple size, and novice subjects were observed in
the study.
2.1. Controversial Studies
It has also been reported thatmedita-
tion has an adverse effect of predisposing
to epileptogenesis panic attacks, overexcited
central nervous system, paradoxical rise in
anxiety, becoming more hypercritical, disori-
3
entation, and high BP (19). Regarding the
use of meditation for high BP, morerandom-
ized clinical trials are required that could
provide certain results (20). Some posi-
tive effects might become negative if over-
expressed in those with individual consti-
tutional neurophysiological properties [EEG
guided med.]. Deep meditation gives rise to
high frequency gamma band bursts (21).The
patients with general epilepsy show increased
gamma band activity especially 30-50Hz in
resting interictal EEG (22), (23). Epilep-
tiformEEG changes have been theorized in
TMmeditators. So some studies accounted
for meditation resulting in epilepsy but some
have rejected such claims [51-57]. Medita-
tion predisposing to epilepsy is a controversial
subject that requires scientific study. Dur-
ing Bhramari Pranayama (BhPr), paroxys-
mal gamma (PGW) has been observed (24).
Using complex Morlet wavelets and Fourier
analysis, features were extracted as high fre-
quencies in beta (15-35) and gamma (>35)
and increased theta activity. BhPr can repre-
sent epileptic activity since higher frequency
epilepsy also exhibits such spiky shape and
activity in temporal lobe as seen in BhPr.
Another study has brought light to TM as
aggravating or treating epilepsy (25).
3. Methods
The literature that was chosen for this
review began by searching for the terms
“yoga” and/or “pranayama” with the terms
“EEG”, “brain”, “cognition”, “activation””,
and/or “brain waves”. The databases used”,
to search for studies with these terms, in-
cluded PubMed, Google Scholar, and EB-
SCO host. Potential articles were categorized
into groups including, quantitative research”,
qualitative research, and single case studies.
The inclusion criteria consisted of quantita-
tive studies that were conducted between the
years 1990e2014 that were published in jour-
nals, and examined either the effects of a
yoga intervention or differences between yoga
practitioners and non-practitioners. The in-
clusion criteria was narrowed to studies that
examined posture (asana), breathing, and
meditation-based yoga and used brain waves”,
brain structural activation, and/or changes in
brain structure as outcome variables. The ex-
clusion criteria was composed of studies con-
ducted before the year 1990, studies not writ-
ten in English, unpublished work, or articles
based on an single individual’s opinion. Af-
ter screening for inclusion and exclusion crite-
ria, 15 studies were reviewed. These studies
were then further categorized based on the
outcome variables measured, into the groups:
“Brain Waves”, “Structural Activation”, and
“Structural Changes”.
3.1. Brain waves
Brain wave activation represents the elec-
trical activity of neurons, specifically the
voltage fluctuations from ionic flow within
neurons, in the brain. This electrical activity
is recorded via electroencephalogram, and the
EEG will represent this electrical activity as
waves or oscillations. These oscillations are
representative of specific activities through-
out the brain. Brain waves are naturally
occurring during both an active and rest-
ing state. However, external instruments can
4
also elicit these waves. Repetitive transcra-
nial magnetic stimulation, transcranial direct
current stimulation, and transcranial alter-
nating current stimulation are several tradi-
tional methods of eliciting and altering brain
waves. These methods are used in both clin-
ical and research settings to help assess the
integrity of and better understand the cen-
tral nervous system. These three methods
can help to modulate and influence exist-
ing rhythmic brain activity and elicit specific
brain wave types.
3.2. Signal Processing Challenges
Signal processing can add to this field of
study (26). The scalp electrodes, which con-
tain the brain activity in terms of electric
potentials, give signals which can be pro-
cessed using signal processing algorithms to
measure different mental activities and to re-
veal cognitive tasks. The internal language
of the mind can be understood using differ-
ent EEG patterns from electromagnetic field
activity (27), (28). EEG includes signals
that are associated with awareness, encour-
agement, and cognitive load and affecting
state of load (29), (30), (31). EEG data is
characterized by delta, theta, alpha, beta”,
and gamma (32). A detailed description of
assigned EEG band has been given in Ta-
ble . A pronounced attempt to characterize
EEG signatures for different types of med-
itation has been contributed by Travis and
Shear [4].They have not allocated rating but
have valued the nature ofmeditation styles.
A superior research in meditation is still re-
quired to categorize the EEG signatures cor-
responding to different meditation practices
[4, 5]. Directly observing the nonlinear and
nonstationary EEG raw data in time domain
is a very tedious task [67]. So various linear
and nonlinear signal processing techniques
and their correlation to physiology have been
proposed. Feature extraction algorithms ac-
quire the spectral information from the pre-
processed rawsignal. Time frequency anal-
ysis is beneficial in clarifying rhythmic in-
formation in EEG signals. Coherence tech-
niques can also be used. Spectral covari-
ance or coherence involves measurement of
phase regularity between signal pairs in each
frequency band.Higher alpha-theta coherence
has been identified as meditation capabil-
ity trait which appears intra- and interhemi-
spherical in meditation [68]. As coherence
cannot separate amplitude information and
phase information while relating two signals”,
it measures roundabout phase locking only.
Synchrony technique is being used rather
than having spectral or coherence analysis.
It is quantification of degree of phase lock-
ing between different narrowband signals [69].
Linear methods used are ICA (Independent
Component Analysis), CSP (Common Spa-
tial Patterns), LD (Linear Discriminator)”,
and linear prediction method [70]. In other
words, a wide range of algorithms extract the
information in EEG signals like algorithms
based on Fast Fourier Transform, Hilbert-
Huang Transform, Wavelet Transform, rule
based expert systems, and numerous other
algorithms to define the temporal extents
[70-72]. A method based on PBFT (Pe-
riod Based Frequency Tracker) has been pro-
posed to keep track of rhythmic variations of
alpha frequencies [73].Though STFT (Short
5
Time Fourier Transform) can analyze such
spectral variations, this method proved bet-
ter in terms of fairer frequency resolution
[73]. Also, problem of asymmetrical period-
icity of EEG has been solved reliably and ef-
ficiently. The inherent inhomogeneous char-
acteristics and multinature are dealt with us-
ing nonlinear signal processing techniques on
the basis of various parameters, for example”,
CD (Correlation Dimension), LLE (Largest
Lyapunov Exponent), and H (Hurst expo-
nent) [70]. Four-channel analysis of EEG has
been given for Compressed Spectral Array
(CSA), the running fractal dimension, and
running attractor dimension [74]. CSA yields
interesting features. The running attrac-
tor is more efficient in analyzing neural dy-
namics.Multiscale fractal dimension (MSFD)
technique is another area of research to ex-
plain the multiscale temporal patterns of
EEG [75]. Nonlinear methods are better than
time domain, frequency domain, and linear
methods.
4. Conclusion
5. Acknowledgements
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7
Introduction
Background
Controversial Studies
Methods
Brain waves
Signal Processing Challenges
Conclusion
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