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Modulation of EEG Theta Band Signal Complexity by Music Therapy

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International Journal of Bifurcation and Chaos
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Abstract

The primary goal of this study was to investigate the impact of monochord (MC) sounds, a type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal complexity values for monochords with those for progressive muscle relaxation (PMR), an alternative therapy for relaxation. Forty cancer patients were randomly allocated to one of the two relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were recorded during the first and last sessions. EEG signals were analyzed by applying signal mode complexity, a measure of complexity of neuronal oscillations. Across sessions, both groups showed a modulation of complexity of beta-2 band (20–29Hz) at midfrontal regions, but only MC group showed a modulation of complexity of theta band (3.5–7.5Hz) at posterior regions. Therefore, the neuronal complexity patterns showed different changes in EEG frequency band specific complexity resulting in two different types of interventions. Moreover, the different neural responses to listening to monochords and PMR were observed after regular relaxation interventions over a short time span.
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International Journal of Bifurcation and Chaos, Vol. 26, No. 1 (2016) 1650001 (9pages)
c
World Scientific Publishing Company
DOI: 10.1142/S0218127416500012
Modulation of EEG Theta Band Signal
Complexity by Music Therapy
Joydeep Bhattacharya
Department of Psychology, Goldsmiths,
University of London, New Cross, SE14 6NW, London, UK
j.bhattacharya@gold.ac.uk
Eun-Jeong Lee
Institute for Medical Psychology, University Hospital,
University of Heidelberg, Bergheimer Strasse 20,
D-69120 Heidelberg, Germany
Received November 14, 2011; Revised April 2, 2012
The primary goal of this study was to investigate the impact of monochord (MC) sounds, a
type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained
from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal
complexity values for monochords with those for progressive muscle relaxation (PMR), an alter-
native therapy for relaxation. Forty cancer patients were randomly allocated to one of the two
relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were
recorded during the first and last sessions. EEG signals were analyzed by applying signal mode
complexity, a measure of complexity of neuronal oscillations. Across sessions, both groups showed
a modulation of complexity of beta-2 band (20–29Hz) at midfrontal regions, but only MC group
showed a modulation of complexity of theta band (3.5–7.5Hz) at posterior regions. Therefore,
the neuronal complexity patterns showed different changes in EEG frequency band specific com-
plexity resulting in two different types of interventions. Moreover, the different neural responses
to listening to monochords and PMR were observed after regular relaxation interventions over
ashorttimespan.
Keywords: EEG; complexity; oscillations; theta band; music therapy; PMR.
1. Introduction
The human brain is often considered as the most
complex object in the known universe, and music,
with all its complexities and richness, is consid-
ered as one of the most unique characteristics of
our species. Music is present in all cultures, and
listening to (and performing) music is consistently
rated as one of the most pleasurable experiences
in our lives [Vuust & Kringelbach, 2010]. Listening
to music can engage a multitude of brain regions
including anterior cingulate cortex, hippocam-
pal formation, and dopaminergic neural networks
[Koelsch, 2010]. In particular, changes in brain
activity were shown during strong emotional experi-
ence induced by the listener’s most preferred music,
and this phenomenon, termed as “chill sensation”,
is perceived as an intensely positive or peak experi-
ence. Intensity of the chill experience was positively
Author for correspondence
Author Contributions: JB developed the complexity index and performed data analysis; EJL performed data collection; JB
and EJL wrote the paper.
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correlated with activations of right thalamus,
anterior cingulate cortex, supplementary motor
area, and insula, and negatively correlated with
activations of right amygdala, left hippocam-
pus/amygdala, and ventral medial prefrontal cor-
tex [Blood & Zatorre, 2001]. Listening to music
also alters the dynamical brain responses, i.e. oscil-
latory component(s) of the electroencephalogram
(EEG) signals, particularly theta frequency band
(3.5–7.5 Hz). For instance, pleasant music elicits
an increase of the frontal midline theta power
[Sammler et al., 2007], and listening to classical
music causes an increase in posterior theta power
[Chan et al., 2008], whereas the relaxation effects
of music are associated with a change in the total
theta power [Kabuto et al., 1993]. Further, broad-
band EEG complexity as measured by the correla-
tion dimension increases with increasingly complex
music and with musical sophistications [Birbaumer
et al., 1996]. Furthermore, EEG responses for music
with fractal or self-similar scaling properties were
associated with reduced correlation dimension and
largest Lyapunov exponent than for music without
scaling properties [Jeong et al., 1998].
It is therefore important to consider to what
extent the results from neurophysiological and neu-
rophenomenological studies on the effects of listen-
ing to music are significant for the clinical usage
of music. Previously, only a few neurobiological
studies have demonstrated the positive effect of
music (listening or playing) in a clinical context,
including in the music therapeutic context, such
as improvements for tinnitus sufferers [Okamoto
et al., 2010], cognitive rehabilitation after a stroke
[Sarkamo et al., 2008], improvement in fine as well
as gross motor skills after a stroke [Altenmuller
et al., 2009], or improvement of speech in patients
suffering from Broca’s aphasia [Schlaug et al., 2009].
Apart from functional improvements, music has also
been used in various clinical contexts to positively
influence patients’ psychological and physiological
states by reducing pain [Nilsson et al., 2003; Tan
et al., 2010], anxiety [Singh et al., 2009], and by
promoting relaxation [Nilsson, 2009]. Typically, in
oncological context, music has been shown to be
effective by reducing anxiety [Burns et al., 2008;
Sabo & Michael, 1996] and side effects [Ezzone
et al., 1998] in patients undergoing chemotherapy.
Despite such success with musical intervention
in clinical settings, the underlying neurophysiolog-
ical responses have rarely been studied, yet neural
correlates to these changes caused by music can
provide deeper insights into the effect of music in
patients. Moreover, these insights can be used as
neuroscientific evidence towards the broader accep-
tance of musical intervention and further establish
the evidence-based use of music and music therapy
as a scientifically supported therapeutic method in
the clinical context [Hillecke et al., 2005]. It is there-
fore necessary to investigate the neural changes
accompanying not only functional improvement but
also psychological and physical support (i.e. the
anxiolytic, analgesic, or relaxing effects) achieved
by listening to music.
The current study aims to fill this gap between
the music psychological, music physiological (neu-
rophysiological), and music therapeutic approaches
to analyzing how patients benefit from the receptive
use of music with a particular focus on listening to
monochord sounds. Monochord is an ancient music
instrument with approximately 30 strings tuned
on the same tone with many induced overtones,
and has been shown to improve the psychological
and physiological states of patients [Rose & Weis,
2008]. Unlike the excerpts of familiar music used
in music therapy [Khalfa et al., 2003], monochord
is rather unfamiliar, and contains minimal musi-
cal parameters, thereby minimizing the involvement
of different music psychological factors (subjective
preference, arousal, etc).
This study focused on neurophenomenological
patterns and on changes in the mode complexity
values in standard EEG frequency bands during
relaxation induced by monochord sounds and com-
pared them to those induced by the progressive
muscle relaxation (PMR) method. PMR is a widely
established technique for relaxation by alternately
tensing and relaxing the muscles [Jacobson, 1938].
Using a recently proposed index, signal mode com-
plexity, it is possible to quantify the complexity of
EEG signals by investigating the constituent oscil-
latory components within standard EEG frequency
bands [Bhattacharya & Pereda, 2010].
2. Materials and Methods
This randomized clinical study has been conducted
at the Women’s Hospital, University of Heidel-
berg, Germany. A total of 43 female patients with
gynaecological cancer receiving chemotherapy were
recruited into the study. Of these, 22 patients were
randomly assigned to the monochord group (MC)
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EEG Complexity in Music Therapy
(mean age: 49, range: 27–55) and 21 patients to the
PMR group (mean age: 51, range: 31–56). During
both relaxation treatments, patients were lying
down, awake but with eyes closed. Both groups
received the recorded intervention (either mono-
chord sounds or instructions for PMR) for 25 min
after a period of verbal introduction (4 min). Each
session was in sync with the onset of chemother-
apy. Patients received individual relaxation treat-
ment sessions — a total of four times over a span
of six months.
During the first and the last treatment sessions,
EEG signals were recorded with 23 Ag/AgCl elec-
trodes attached to the scalp (Fp1, Fp2, F3, F4, F7,
F8, C3, C4, T1, T2, T3, T4, T5, T6, P3, P4, O1,
O2, Fz, Cz, Pz, A1, A2) according to the Inter-
national 10–20 electrode placement system [Jasper,
1958]. All electrode impedances were kept below
10 KΩ. The sampling frequency was 128 Hz. The
EEGs were re-referenced offline to the algebraic
mean of the two earlobe electrodes. During EEG
recording, participants were awake but their eyes
were closed.
Data from five patients were excluded due to
excessive artefacts, and the data of a total of
38 patients were analyzed (MC: n=20,PMR:n=
18). EEG signal at each electrode location was
bandpass filtered in six standard frequency bands:
delta (<3 Hz), theta (3.5–7.5 Hz), alpha (8–12 Hz),
beta 1 (12–19.5 Hz), beta 2 (20–29 Hz), and gamma
(>30 Hz); in this study, we strategically focused our
analysis on theta, alpha and beta-2 bands based
on our earlier analysis (unpublished observation).
The EEG analysis concentrated on two 5 min long
periods within each treatment session: Begin period
(from the beginning phase of a treatment session)
and End period (from the final phase of a treatment
session). These periods were chosen so that the
within-session effect of each relaxation treatment
could be reliably assessed. Within each period, the
data were divided into 30 nonoverlapping epochs
of 10 sec. Epochs with maximum absolute ampli-
tude larger than 75 µV were considered as artefacts
and eliminated from subsequent complexity analy-
sis. The complexity values were computed for indi-
vidual epochs.
The procedure of calculating signal mode com-
plexity is described briefly as follows. Consider an
EEG time series, {x(k),k =1,2,...,N},whichis
normalized to zero mean and unit variance. We form
am×nmatrix,
An=
x(1) x(2) ··· x(n)
x(n+1) x(n+2) ··· x(2n)
.
.
..
.
.....
.
.
x(n(m1) + 1) x(n(m1) + 2) ··· x(mn)
and calculate its singular values (σ1
2,...,σ
p,p=
min(m, n)) [Golub & Van Loan, 1996]. By varying
the row length (n), new matrices are formed, and
their singular values are subsequently calculated.
For each configuration of An, the singular values
are linearly mapped to Rnormalized singular val-
ues but preserving the total energy spanned by the
sum of squares of singular values. This way all the
singular values for each matrix configuration were
considered and the associated singular value profiles
were made linearly equivalent to each other. Hence
for Mdifferent values of row length n,Msets of R
singular values are obtained:
{σi,j :i=1,2,...,M;j=1,2,...,R}.
An average singular value profile is obtained as:
ˆσj=1
M
M
i=1
σij .
Earlier we have shown that this average profile
could distinguish chaotic time series from a random
one, and further could be used to characterize phys-
iological signals.
The signal mode complexity, CS, is computed
as:
CS=
R
j=1
j2ˆσj
R
j=1
j2
.
The lower the CSvalue, the higher the likeli-
hood of regularly occurring pattern of synchronized
oscillations. CSis found to be able to detect changes
in the complexity of the signal that is very similar
to the changes in the largest Lyapunov exponent,
a hallmark of chaotic complexity. Further, CSis a
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measure with high reliability that can be applied
to small data sets, and further the method is
assumption-free. See [Bhattacharya & Pereda, 2010]
for further details.
The complexity values were log-transformed
prior to statistical analysis. A mixed factorial
ANOVA was performed with between-subject fac-
tors, group (2 levels: MC and PMR), and within-
subject factors, session (2 levels: Pre and Post),
time (2 levels: Begin-period and End-period), and
regi on (two levels: anterior (Fp1, Fp2, F3, F4, F7,
F8,T1,T2,Fz),andposterior(T5,T6,P3,P4,
Pz, O1, O2)). The statistical significance was set
at p<0.05. All statistical analyses were performed
using SPSS (version 16.0).
3. Results
First, we investigated the CSdifferences across ses-
sions. Figure 1 shows the CSvalues at 21 electrode
regions in three standard EEG frequency bands
(theta, alpha, and beta-2) for both groups during
the first (designated as Pre) and last (designated
as Post) sessions of treatment. At first glance, the
spatial profiles of CSvalues appeared to be similar
between Pre and Post within each group, and fur-
ther the scalp distribution of differences in CSval-
ues (Pre–Post) were quite similar across frequency
bands within each group. However, upon closer
inspection, several interesting features emerged.
The theta band complexity in the MC group was
0.014
0.016
0.018
0.02
0.022
CS
PMR Theta
Pre
Post
Difference
0.014
0.016
0.018
0.02
0.022
Monochord Theta
Pre
Post
0.014
0.016
0.018
0.02
0.022
CS
PMR Alpha
0.014
0.016
0.018
0.02
0.022
Monochord Alpha
0.02
0.03
0.04
0.05
0.06
CS
PMR Beta−2
Fp2 F4 C4 P4 O2 F8 T6 T4 T2 Fz Pz
Fp1F3C3P3O1F7T5T3T1Cz
0.02
0.03
0.04
0.05
0.06
Monochord Beta−2
Fp2F4C4P4O2F8T6 T4T2FzPz
Fp1F3C3P3O1F7T5T3T1Cz
−0.15
−0.1
−0.05
0
0.05
0.1
0.15
Difference
(a)
(b)
(c)
(d)
(e)
(f)
Fig. 1. Signal mode complexity (CS) of three frequency bands (theta, alpha and beta-2) at 21 scalp electrodes in the first
(Pre) and the last (Post) treatment sessions for (a)–(c) the PMR and (d)–(f) the MC groups. Results were averaged across two
periods (Begin and End, see text) within a session. Scalp map adjacent to each plot describes the topographical distribution
of difference (Pre–Post) CSvalues. Red color indicates a decrease in CSin the last session compared to the first session.
Electrodes showing statistically significant (p<0.05, Bonferroni corrected) changes are shown by bigger filled circles.
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EEG Complexity in Music Therapy
considerably lower in the last session compared to
the first session over a multitude of electrode regions
[Fig. 1(d)], but with a stronger emphasis in the pos-
terior region (F(1,19) = 5.15, p=0.03). Interest-
ingly, the PMR group displayed an opposite trend:
theta band complexity increased in the last session
compared to the first one over many brain regions
except frontopolar and midfrontal regions showing
the reverse pattern [Fig. 1(a)]. The alpha band com-
plexity in the MC group was rather similar between
first and last sessions but a trend towards decreased
complexity was found in midfrontal (Fz), right tem-
poral (T4, T2, T1) and occipital (O1, O2) elec-
trode regions [Fig. 1(e)]. In beta-2 band, CSvalue
in midfrontal electrode region was significantly low-
ered in the last session compared to the first session
in the MC group (F(1,19) = 5.66, p=0.02). The
results in the PMR group were quite similar across
frequency bands and the midfrontal region showed
consistently decreased complexity.
Next, we studied the within session CSdiffer-
ences. Figure 2 shows the general tendencies of the
change in theta band complexity values between
Begin (5min period from the beginning phase of a
session) and End (5minperiodfromtheendphase
of a session) periods within both first (Pre) and
last (Post) sessions. Within a session, the PMR
group showed very similar distributions without
any significant difference between the two periods
[Figs. 2(a) and 2(b)], whereas the MC group showed
large significant differences between the two periods
in both anterior (F(1,19) = 5.69, p=0.02) and
in posterior (F(1,19) = 8.80, p=0.00) electrode
regions. In both sessions, CSvalues decreased in
the End period from its values in the Begin period,
and the effect was larger in the anterior region in
the last session than in the first session. Regard-
ing alpha band complexity, the MC group showed
robust significant differences between the two peri-
odsinbothanterior(F(1,19) = 13.03, p=0.00)
and posterior (F(1,19) = 7.28, p=0.01) regions,
where the complexity value was decreased during
the End period compared to the Begin period.
Figure 3 shows the within session CSdiffer-
ences for beta-2 frequency band. Both MC and
PMR groups showed a robust increase of CSin the
frontopolar and midfrontal electrode regions during
the End period as compared to the Begin period
(p<0.00). Scalp maps were quite consistent across
both periods within individual groups.
0.018
0.019
0.02
0.021
0.022
CS
PMR Pre
Begin
End
Difference
0.018
0.019
0.02
0.021
0.022
Monochord Pre
Begin
End
Difference
0.018
0.019
0.02
0.021
0.022
CS
PMR Post
Fp2F4C4P4O2F8T6T4 T2FzPz
Fp1 F3 C3 P3 O1 F7 T5 T3 T1 Cz
0.018
0.019
0.02
0.021
0.022
Monochord Post
Fp2F4C4P4O2F8T6T4T2Fz Pz
Fp1F3C3P3O1F7T5T3T1Cz
−0.02
0
0.02
(a) (c)
(b) (d)
Fig. 2. (a) Signal mode complexity (CS) of theta frequency band at 21 scalp electrodes shown separately for Begin and End
period for the first session of PMR group. Scalp map shows the topographical distribution of difference (BeginEnd)CSvalues.
(b) Same as in (a) but for the last session of the PMR group. (c)–(d) Same as in (a)–(b) but for the MC group. Electrodes
showing statistically significant (p<0.05, Bonferroni corrected) changes are shown by bigger filled circles.
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Begin End
0
0.01
0.02
0.03
0.04
0.05
PMR
CS
PMR Begin PMR End
0.04
0.05
0.06
PMR Difference
Begin End
0
0.01
0.02
0.03
0.04
0.05
Monochord
CS
Monochord Begin Monochord End Monochord Difference
−0.1
0
0.1
(a)
(b)
Fig. 3. Signal mode complexity (CS) of beta-2 band at frontopolar and midfrontal electrode regions (Fp1, Fp2, F3, F4, Fz)
for Begin (empty bar) and End (gray bar) period for (a) PMR and (b) MC groups. Results were averaged across sessions
(first and last). Scalp maps on the right of each bar plot show the topographical distribution of CSfor Begin and End period
within each group. Electrodes showing statistically significant (p<0.05, Bonferroni corrected) changes are shown by bigger
filled circles.
4. Discussion
Listening to monochord sounds or practising PMR
to induce relaxation during chemotherapy pro-
duced different complexity profiles of electrical
brain responses of gynaecological patients in oncol-
ogy. The difference was most conspicuous in the
theta frequency band: in the MC group, theta band
complexity decreased both within a session and
across sessions, while no such decrease was observed
in the PMR group. Both groups showed an increase
of beta-2 band complexity within a session.
EEG signals are neither fully deterministic nor
fully stochastic, but rather a mix of both processes
[Lehnertz et al., 1999]. As the degree of stochasticity
or randomness increases or decreases, CSincreases
or decreases [Bhattacharya & Pereda, 2010]. There-
fore, a decrease of CSat an electrode region sug-
gests an increase of orderliness or regularity in the
oscillatory component of the time series recorded by
that electrode. Emergence of locally synchronized
oscillations is one candidate of such enhanced pat-
terned regularity. Hence, in the MC group, the theta
band spectral power was likely to be enhanced at
the end of a session compared to its beginning and
also at the last session compared to the first session.
This is in line with earlier studies showing that the
posterior theta band oscillation is an effective indi-
cator of induction of relaxation [Hari & Naukkari-
nen, 1977; Williams & Gruzelier, 2001]. This clearly
suggests that monochord sounds were quite effec-
tive as an inducer of relaxation even within one ses-
sion. Interestingly, the difference in midfrontal and
frontal theta complexity between End and Begin
period was larger in the second session than in
the first session [Figs. 2(c) and 2(d)]. This possibly
reflects a training effect of the monochord method.
Theta oscillations over midfrontal region are shown
to be modulated by various meditational techniques
[Aftanas & Golocheikine, 2002; Baijal & Srinivasan,
2010]. Training related changes in the MC group
were found also over other brain regions [Fig. 2(d)].
Decrease of signal mode complexity over multiple
brain regions is usually associated with an increase
of neuronal synchronization over these distant brain
regions [Bhattacharya & Pereda, 2010]; therefore
one could infer that the gradual intervention by
monochord sounds elicited a dense functionally con-
nected network.
While theta band effect was exclusive to
the MC group only, beta-2 band complexity was
increased in both MC and PMR groups. The
dimensional complexity of EEG during meditation
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EEG Complexity in Music Therapy
is negatively correlated with theta and positively
correlated with beta frequency band [Aftanas &
Golocheikine, 2002]. Therefore, if our earlier rela-
tionship between signal mode complexity and syn-
chronized oscillation holds, one expects a reduction
of beta band oscillations with both relaxation
methods. Note that the largest increase of beta
band complexity was found over frontal regions
[Figs. 3(a) and 3(b)], suggesting an anxiolytic
response common to both groups as frontal beta
oscillations are inversely correlated with the degree
of anxiety [Begic et al., 2001; Chen et al., 1989].
This is also the first study which has system-
atically analyzed the dynamic brain responses to
monochord sounds in a clinical context. Previously,
only two pilot studies investigated the effects of
body monochord using EEG [Fachner & Rittner,
2004; Sandler et al., 2008]. These studies demon-
strate altered states of consciousness induced by
the body monochord which was associated with an
increase of theta and beta-2 band spectral power
[Fachner & Rittner, 2004]. Both of these stud-
ies are purely exploratory and involve very few
healthy participants. Consequently, no neurophys-
iological account is available on the effect of mono-
chord sounds used in clinical context. Future studies
need to assess whether the relaxing effect or the
altered states as mentioned above in a specific clin-
ical context could offer similar therapeutic effects
to patients.
We acknowledge certain limitations of this
study. Firstly, the current study did not include
a control group. However, it was difficult to
conduct a comparison with a control group, given
that this was a clinical study with gynaecologic
cancer patients who were burdened both physi-
cally and psychologically with their illness. For
obvious ethical reasons, it was questionable to mea-
sure EEG, especially because these female patients
were already suffering from alopecia (a condition of
hair loss due to chemotherapy) and attaching elec-
trodes would therefore mean additional emotional
burden. It would nevertheless be scientifically inter-
esting to make a comparison with a control group,
provided that a study can be designed without
adding stress to the patients. Secondly, the length
of the intervention method should be investigated
more systemically. The process of relaxation and
the patterns of becoming relaxed are situational
and differ across individuals. It will be necessary to
track the changes in complexity (or in other suitably
chosen features) of brain responses over the course
of the intervention to find out the most effective
and efficient length of time for the relaxation inter-
vention and to develop an optimal and individually
adapted music relaxation treatment. Thirdly, one
could consider investigating the post effect after lis-
tening to monochord sounds, potentially increasing
the applicability of music in the clinical context.
Fourthly, the current study did not cover the entire
EEG frequency spectrum; it strategically focused
on three preselected frequency bands after previous
studies, yet other EEG frequency bands like gamma
(>35 Hz) are also shown to be modulated by varied
states of alertness [Aftanas & Golosheykin, 2005;
Sebastiani et al., 2005; Tei et al., 2009]. There-
fore, future research should attempt to establish a
relationship between music mediated relaxation and
signal complexity of higher EEG frequency bands.
Finally, any quantifier of complexity, be it CSor
any other, is, after all, a mathematically derived
index. In order to establish its prognostic value in
determining the efficacy in predicting the success of
an individual relaxation method, it would be essen-
tial to demonstrate that such a quantifier is sys-
tematically related to behavioral measures, thereby
establishing a link between neural and behavioral
responses. In the similar vein, it would also be rel-
evant, for future studies, to correlate changes in
signal mode complexity with peripheral or other
physiological measures (e.g. heart rate, respiration)
related with relaxation.
In summary, this is the first neuroscientific
study of the effect of listening to archaic sounds
(monochord) in patients that demonstrates the
changes in complexity in brain oscillation patterns
in comparison with PMR.
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... Studies that have investigated the impact of MC sounds on EEG signals have reported inconsistent results (Bhattacharya, 2016;Fachner and Rittner, 2005;Sandler et al., 2008). Bhattacharya (2016) compared the neurological effects of MC sounds to those induced by PMR and found a significant theta band effect induced by MC sounds. ...
... Studies that have investigated the impact of MC sounds on EEG signals have reported inconsistent results (Bhattacharya, 2016;Fachner and Rittner, 2005;Sandler et al., 2008). Bhattacharya (2016) compared the neurological effects of MC sounds to those induced by PMR and found a significant theta band effect induced by MC sounds. Sandler et al. (2008) also observed an increase in intensity of theta activity in participants exposed to MC sounds. ...
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Tibetan bowls and monochords are millennia-old instruments used for spiritual and therapeutic purposes. In the last few decades, there has been growing interest in the use of these instruments in meditation and therapeutic settings. Nevertheless, they are still rarely used in music therapy in the Western world, either because of technical difficulties or musical or cultural biases. The purpose of this pilot study was to examine the experiences of adults with mental health conditions and intellectual disabilities during sound meditation sessions using Tibetan bowls and a monochord. In this qualitative pilot, a group of six psychiatric inpatients participated in seven weekly sound meditation sessions over eight weeks that implemented Tibetan bowls and the monochord combined with meditation. Semi-structured interviews were conducted after each session to capture participants’ reflections on their experiences. The interview data was analysed using thematic analysis. Three main themes emerged: physical sensations, experiences of emotions, and visual experiences. The sounds of the Tibetan bowls and the monochord helped participants relax and evoked a wealth of emotions and mental imagery. These findings suggest that using these instruments with adults with mental health conditions and intellectual disabilities can foster relaxation, as well as heighten their awareness of physical sensations, feelings, and previous life events. Music therapists can thus integrate Tibetan bowls and the monochord into their skillset and use them during treatment sessions.
... see [30,32,40,41,46]. However, it was demonstrated that θ-activity increased with increasing distractions and decreased during deeper meditative experiences [43]. A reduction in θ-activity over the mid frontal region was also observed in chemotherapy subjects exposed to monaural sound therapy (MC) inducing relaxation [44]. ...
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... see [30,32,40,41,46]. However, it was demonstrated that θ-activity increased with increasing distractions and decreased during deeper meditative experiences [43]. A reduction in θ-activity over the mid frontal region was also observed in chemotherapy subjects exposed to monaural sound therapy (MC) inducing relaxation [44]. ...
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... A decrease in Alpha and Beta2 activity was reported while monitoring relaxation efects of listening to monochord compared to progressive muscle relaxation tapes of the same length and sonic characteristics during chemotherapy. Te researches indicate their results correlate with a signifcant improvement in participants' physical and psychological states as well as in their state of anxiety [47,126]. Lower levels of Alpha activity in the left front central region, as demonstrated here, were associated with higher levels of selfacceptance, environmental mastery, personal growth and psychological well-being [127]. ...
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... Similar to the case of BCI, the BCMI applications are advantageous in various fields spanning the entertainment industry and healthcare, such as in music therapy. Several studies have addressed the effectiveness of BCMI applications in music therapy by modulating the affective state of their users based on precise indices related to subjects' affective state, and by composing pieces of music that directly target the listener's mood [5][6][7]. However, wider application is limited by the selection of sensitive brain activity markers reflecting emotions that can be assessed accurately and fast, while keeping the system agile to adapt to new users. ...
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... Created with BioRender.com. electroencephalography (M/EEG) [142] provides a second point of contact, with abnormalities in dynamic complexity suggested as indicative of mental illness [143], while music engagement has been suggested to reflect and perhaps affect dynamic complexity [144,145]. ...
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... Given the emotional effects of music, there is potential for using musical stimuli as an adjuvant, or as a more actively patient-controlled output target for neurofeedback. Growing interest in measures of the dynamic complexity of brain activity in health and disease as measured by magnetic resonance imaging or MUSIC ENGAGEMENT AND MENTAL HEALTH 25 magneto/electroencephalography (M/EEG) 142 provides a second point of contact, with abnormalities in dynamic complexity suggested as indicative of mental illness 143 , while music engagement has been suggested to reflect and perhaps affect dynamic complexity 144,145 . ...
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Is engaging with music good for your mental health? This question has long been the topic of empirical clinical and nonclinical investigations, with studies indicating positive associations between music engagement and quality of life, reduced depression or anxiety symptoms, and less frequent substance use. However, many earlier investigations were limited by small populations and methodological limitations, and it has also been suggested that aspects of music engagement may even be associated with worse mental health outcomes. The purpose of this scoping review is first to summarize the existing state of music engagement and mental health studies, identifying their strengths and weaknesses. We focus on broad domains of mental health diagnoses including internalizing psychopathology (e.g., depression and anxiety symptoms and diagnoses), externalizing psychopathology (e.g., substance use), and thought disorders (e.g., schizophrenia). Second, we propose a theoretical model to inform future work that describes the importance of simultaneously considering music-mental health associations at the levels of (1) correlated genetic and/or environmental influences versus (bi)directional associations, (2) interactions with genetic risk factors, (3) treatment efficacy, and (4) mediation through brain structure and function. Finally, we describe how recent advances in large-scale data collection, including genetic, neuroimaging, and electronic health record studies, allow for a more rigorous examination of these associations that can also elucidate their neurobiological substrates.
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Music is the method of expressing feelings and thoughts in a melodical manner. The relationship of human with music starts from the embryonal stage. The method of treatment with music is based on a past of approximately 6000 years and was implemented by Turks who used music therapy systemically for the first time in the world. These first applications consist of treatment sessions carried out by religious people called Shamans. Furthermore, it is known that music was also employed in Egypt, China, India, Greece and Rome as a treatment method throughout history. Traces of music as a treatment method can even found in certain religious books including Psalter. In Islamic states of middle ages, philosophers including Zekeriya Er Razi, Farabi and İbni Sina had made researches about the therapeutic effect of music. Many hospitals in Seljuks and Ottomans used to employ music as treatment of certain mental conditions as well. In parallel to the development of modern science, many literature studies on music treatment have been carried out. The genre and melody of music performed throughout history, whether be it for therapeutic or entertainment purposes, have varied greatly depending on period, location and culture. Classical Turkish music is considered one of the few genres that have settled a contiunity and tradition alongside classical Western and Indian Music. It is a Turkish music genre based on modes called makams. Although Classical Turkish Music and music therapy have been practiced since medieval times, the international modern literature studies in this scope have been started only in the second half of the 2000s. The first studies on the effect of listening to music on EEG (Elektroensefalografi) signals of brain were made in the early 1980s. Numerous studies have been carried out in order to predict whether any musical work listened was admired by the listener or not, and what kind of emotions were aroused in the course of listening by using EEG signals of brain and analysing them. Besides, considering the literature studies conducted in recent years, there is an increase in the studies of multi-disciplinary literature in which the medical analysis of the EEG signals generated by music therapy and medical evaluations on the course of the disease are made together. It is seen that the musical works used in the studies examining the relationships between music and brain EEG signals are generally selected from music genres such as Classical Western Music, Classical Indian Music, Rock Music and Classical Iranian Music due to the ethnic and cultural origins of the teams. Although limited in number, there are some some studies investigating the relationship between Classical Turkish Music and EEG signals of brain. Depression can be defined as, a state of mental disorder that manifests itself as reduced sensitivity to stimuli, an ever-intensifying despair and pessimism in company with a lack of initiative power and self-confidence. There are a large number of factors that can yield to depression including but not limited to anxiety disorders, relationship problems, stress factors and childhood traumas. Depression is generally examined in two groups such as major depression and minor depression. Minor depression is described with lighter symptoms and generally not considered to lead fatal actions such as suicide. However, when left untreated, the probabilty of minor depression becoming major depression is considerably high. For this reason, detection and treatment of minor depression cases are of utmost importance. The data related to the use of antidepressants issued by the Republic of Turkey Ministry of Health indicate an increase of around 10% per year. Moreover, this data suggests that depression in Turkey is about to become a public health problem rather than being only a disease. In this meta-synthesis study, it is aimed to examine and reveal the potential of Classical Turkish Music makams on the effects of emotion changes and treatment processes on minor / major depression patients by using brain EEG signals. It is considered that the study carried out in this context will encourage and facilitate the researchers to carry out multi-disciplinary studies on the subject. The databases of Pubmed, Google Academic, Web of Science and Scopus are scanned with a number of keywords related to “Musical Theraphy” and it is observed that more than 2000 articles, books, book chapters and conference papers are written on this subject. %95 of these studies were entirely related to medicine. The remaining %5 can be considered as multi-disciplinary studies of medicine with other disciplines, with engineering as the most commonly encountered discipline. The time period covered in this meta-synthesis study is determined to be between January 1975 and June 2019, with some priority on more recent studies given.
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During the process of abstinence from chemical dependence, the user presents some common symptoms to any type of drug, such as anxiety, depression, hypomania / mania. In most cases, treatment is drug-associated with non-drug therapies. The receptive experience is a technique of music therapy and vibroacoustic therapy through Mesa Lira (ML) is one of the modalities of receptive music therapy used in the treatment of physical and emotional illness. Objective: To investigate whether Receptive Music Therapy with mesa lira can reduce drug addiction anxiety levels in an internment regime detox program, by comparing two distinct protocols for music therapy intervention. Methodology: Controlled randomized clinical trial in male and female drug users from 18-year-old on an average hospitalization period of 28 days at the Detoxification Program at Casa de Eurípedes institution, in Goiânia, Goiás, Brazil, with four groups, two intervention (GMT-A: five sessions of music therapy (MT) on consecutive days; GMT-B: five sessions of music therapy on alternate days) and two controls (GCA and GCB). The groups participants were submitted to a sociodemographic questionnaire, Drug Temptation Scale (ESTUD), Drug Abstinence Self-efficacy Scale (EAAD), Trait Anxiety Inventory and Status Anxiety Inventory to assess Anxiety Level (IDATE). Specifically to the participants of the music therapy groups, a scale of relaxation level (NR) subjective rating on Mesa Lira, Body Vibration Perception, Music Therapeutic Questionnaire (QMT) and Subjective Impression of the Subject (ISS) were applied. Results and Discussion: 40 subjects were included, 20 (19 men and 1 woman) for stage “A” and 20 (19 men and 1 woman) for stage B. Mean age: GMT-A (38.0), GC-A (32.2), GMT-B (43.6) and GC-B (41.4). In the intragroup evaluation, comparing pre and post MT sessions, both groups presented results with statistical significance for IDATE-E in the fourth session for GMT-A (ρ = 0.064) and in the third session of GMT-B (ρ = 0.012), NR presented significance levels for all sessions in both groups. Intergroup evaluation points to better results for GMT-B. The evaluation between intervention groups and their respective controls shows significant results for GMT-A (ESTUD ρ = 0.056 and EAAD ρ = 0.038). Reports from intervention group participants (ISS) confirm the quantitative findings. Regarding the aspect of treatment dropout / internment period, this was lower among participants in the intervention groups. Conclusion: Music therapy, as a complementary treatment, worked to improve anxiety symptoms, decrease the temptation to use the drug and strengthen during abstinence. The results are relevant, as they reflectedin the patient's better adherence to the treatment as a whole, since dropout is a problem for this clientele. We hope this study can contribute to the strengthening of music therapyas a complementary treatment of choice for this complex area. We suggest that further research be conducted with music therapy in chemical dependence, aiming to expand knowledge and, with this, strategies for treatment and prevention of drug abusive use.
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Zusammenfassung. Musiktherapeutischer Literatur zufolge soll durch die Rezeption des Klanges von Monochord bzw. Ganzkörper-Monochord das Erleben veränderter Wachbewusstseinszustände (VWB) induziert werden können. In der vorliegenden Studie wurde untersucht, ob die EEG-Aktivität und das subjektive Erleben während einer Behandlung mit einer Klangliege sich von einem mittels Progressiver Muskelrelaxation induzierten Entspannungszustand unterscheiden. Das Erleben eines VWBs wurde von 31 Probanden während beider Bedingungen quantitativ erfasst. Zusätzlich wurde das subjektive Erleben während der Klangexposition qualitativ erhoben. Während beiden Bedingungen wurde EEG abgeleitet, FFT-anaysiert und die EEG-Leistungsspektren der Alpha- und Theta-Power zwischen den Bedingungen verglichen. Es zeigte sich, dass sich während der Klangexposition bei den meisten Probanden ein bedeutend intensiveres Erleben eines VWBs einstellte. Bei der Subgruppe der Probanden mit intensiv erlebtem VWB konnte vor allem im parietalen Bereich des Gehirns ein Anstieg der EEG-Theta-Aktivität festgestellt werden. Die EEG-Alpha-Aktivität differenzierte nicht zwischen den Bedingungen.
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The goal of this study is to quantify and determine the way in which the emotional response to music is reflected in the electrical activities of the brain. When the power spectrum of sequences of musical notes is inversely proportional to the frequency on a log-log plot, we call it 1/f music. According to previous research, most listeners agree that 1/f music is much more pleasing than white (1/f 0) or brown (1/f 2) music. Based on these studies, we used nonlinear methods to investigate the chaotic dynamics of electroencephalograms (EEGs) elicited by computer-generated 1/f music, white music, and brown music. In this analysis, we used the correlation dimension and the largest Lyapunov exponent as measures of complexity and chaos. We developed a new method that is strikingly faster and more accurate than other algorithms for calculating the nonlinear invariant measures from limited noisy data. At the right temporal lobe, 1/f music elicited lower values of both the correlation dimension and the largest Lyapunov exponent than white or brown music. We observed that brains which feel more pleased show decreased chaotic electrophysiological behavior. By observing that the nonlinear invariant measures for the 1/f distribution of the rhythm with the melody kept constant are lower than those for the 1/f distribution of melody with the rhythm kept constant, we could conclude that the rhythm variations contribute much more to a pleasing response to music than the melody variations do. These results support the assumption that chaos plays an important role in brain function, especially emotion.
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