Eeg based interpretation of human brain during yoga and

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

Acknowledgements