• Users Online: 471
  • Print this page
  • Email this page

 
Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 64  |  Issue : 3  |  Page : 159-165

The effect of listening to SMT music made using musical expectancy violations on brain concentration and activation


1 Department of Psychotherapy, Graduate School of Health Care Science, Soonchunhyang University, Cheonan, Republic of Korea
2 Department of Educational Science, Graduate School, Soonchunhyang University, Cheonan, Republic of Korea
3 Department of Physiology, College of Medicine, Soonchunhyang University, Cheonan, Republic of Korea

Date of Submission28-Dec-2020
Date of Decision20-May-2021
Date of Acceptance27-May-2021
Date of Web Publication24-Jun-2021

Correspondence Address:
Dr. JeongBeom Lee
Department of Physiology, College of Medicine, Soonchunhyang University, Cheonan 31151
Republic of Korea
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/cjp.cjp_112_20

Rights and Permissions
  Abstract 


This study investigated the effect of listening to self-music therapy training (SMT) music, which was specially developed using musical expectancy violations, on improving brain concentration and activation. It was performed with a sample of 12 adults. Electroencephalograms (EEG) were obtained and analyzed after allowing the participants to listen to SMT music. An EEG device with eight channels was used to measure the brain waves. The changes in the EEGs were recorded when listening to SMT music in three states (stable, basic, and stimulated) after attaching the electrodes to the prefrontal cortex (Fp1 and Fp2), and the frontal (F3 and F4), temporal (T3 and T4), and parietal lobes (P3 and P4) according to the International 10/20 system. The EEG data were analyzed to determine the m-β wave appearance rate and absolute total power (ATP) for the three conditions, and a t-test was performed. The results showed that the rate of m-β wave appearance was higher in the stimulated and basic states than in the stable state (Fp1, Fp2, F4, T3, T4, P3, and P4) and higher in the stimulated state than in the basic state (Fp1, Fp2, T3, T4, and P4). The ATP was lower in the basic state than in the stable state (Fp2, F3, F4, and T3), but the ATP in the stimulated state was higher than in the basic or stable state in all areas excluding the left and right parietal lobes (Fp1, Fp2, F3, F4, T3, and T4). These results demonstrated that listening to SMT music by normal adults could increase brain concentration and activation.

Keywords: Electroencephalograms, music therapy, musical expectancy violations, self-music therapy training


How to cite this article:
Yeo H, Nam HW, Lee J. The effect of listening to SMT music made using musical expectancy violations on brain concentration and activation. Chin J Physiol 2021;64:159-65

How to cite this URL:
Yeo H, Nam HW, Lee J. The effect of listening to SMT music made using musical expectancy violations on brain concentration and activation. Chin J Physiol [serial online] 2021 [cited 2021 Jul 28];64:159-65. Available from: https://www.cjphysiology.org/text.asp?2021/64/3/159/319284




  Introduction Top


In general, when patients are treated by their doctor, they are prescribed either a medication or exercise. A prescription implies that the patient should voluntarily comply with the recommended task until the next treatment, which is called “prescription adherence.” It entails taking medication at a set time, exercising as recommended, as well as other activities that are consistent with the best health-care recommendations.[1],[2] A prescription is a specialized program for the treatment of patients based on expertise and involves a low level of difficulty and exertion by the patients.[1],[3] The role of a prescription in treatment is so important that it is hard to imagine a treatment without a prescription. In addition, based on clinical evidence, doctors can provide appropriate prescriptions to most patients relatively easily.

Similar to the concept of a prescription, in psychological counseling, a counseling technique called “homework” is administered to the client between the current and the next session.[4],[5],[6] In counseling practice, homework is frequently assigned by most counselors and represents an important technical strategy in the counseling process.[7],[8],[9],[10],[11],[12] Homework assignments in counseling serve as an ongoing treatment by ensuring therapy between sessions and sessions that are outside the therapist's control and enhances the counseling performance by maintaining the continuity of treatment.[8],[9],[13],[14]

Homework also has a positive effect on the therapeutic outcome of counseling. Burns and Nolen-Hoeksema found that the client's performance of homework was an important factor influencing the improvement of symptoms by analyzing the results of the cognitive treatment of patients with emotional disorders.[15] Moreover, studies comparing the difference in treatment effects according to the assignment of homework to the client undergoing cognitive therapy for depression showed that, when homework was given, the depressive symptoms improved more.[16],[17],[18] In addition, the results of a meta-analysis of homework assignment and counseling outcomes showed that the treatment effect was greater when homework was assigned than when it was not.[19] Such homework is known as a self-training program because it is carried out by the client alone without the therapist.[4],[5] However, in the field of music therapy, appropriate self-training programs such as homework have yet to be provided to the clients.

Self-music therapy training (SMT) is the same concept as homework given to the client in psychological counseling. The only difference is that SMT uses music. Like homework, SMT itself is not a treatment, but its contents allow the client to perform one or two purposes that can be helpful for treatment. Considering the reality of music therapy interventions where the interval between sessions is relatively long and it is not easy to reduce the interval, studies investigating music therapy self-training programs are imperative for clients who are inattentive between sessions. In addition, during the COVID-19 pandemic when in-office treatment has not been feasible, the availability of self-training programs for music therapy is an effective alternative.

The purpose of this study was to design and develop an independent self-training program in music therapy known as SMT as a pilot case for possible clinical application in actual music therapy based on the outcomes. Therefore, in this study, the self-training music therapy program was newly named SMT. Moreover, based on the reports that the concentration and activation of the brain are related to the improvement of language ability,[20],[21] and the research results that musical expectancy violations stimulus can be helpful for brain activation,[22],[23] after experimentally developing SMT music with functions appropriate for speech therapy using musical expectancy violations, before applying it to the actual music therapy field for speech impairment, the effect of listening to SMT music on the improvement of brain concentration and activation was investigated through electroencephalograms (EEG) analysis.


  Materials And Methods Top


The effects of listening to SMT music including musical expectancy violations on changes in brain concentration and activation in 12 adults were analyzed by EEGs. The collected EEG data were analyzed separately in three conditions (the stable, basic, and stimulated states). The stable state was a state, in which music was not listened to, and the basic state was the state of listening to a normal musical part of SMT music that did not contain musical expectancy violations stimulus, and the stimulated state was a state, in which the participants listened to a part of the music that contained musical expectancy violations.

The m-β wave appearance rate and absolute total power (ATP) were calculated after subtracting the delta waves that are susceptible to contamination by facial muscle or eye movements from the power value per unit frequency obtained through Fast Fourier Transform (FFT). In addition, the changes in the brain concentration based on the m-β wave appearance rate and the overall brain activation by the ATP were also analyzed. The m-β wave appearance rate refers to the ratio of the m-β wave to the total EEG calculated as the amplitude and is expressed as a unit percentage (%). ATP refers to the amount of total EEG calculated as amplitude over a certain period of time and is expressed as μV2.

Participants

The study was conducted on 12 adults (six males and six females) aged between 22 and 57 years who had normal hearing and no specific disease and received no medication in the last week or more. The average age of the participants in this study was 37.9 years, and only adults were tested because of the lack of stable brain waves and difficulties in the accurate analysis of children. Furthermore, only right-handed subjects with a high school or higher educational background were targeted to minimize the impact of differences in educational level and left and right brain development. The subjects fasted for 6 h before the test and were instructed to refrain from consuming alcohol and taking medication 48 h before the test. Each subject was thoroughly briefed on the purpose of the study, experimental procedures, and potential risks. All procedures complied with the 2013 Helsinki Declaration of the World Medical Association (No. 1040875-202009-SB-076) from the Institutional Review Board on Human Subjects Research and Ethics Committees, Soonchunhyang University, Cheonan, Korea.

Self-music therapy training music

By referring to the Melon Music Chart, ten pieces of music that could be converted to music with an MM 60 (MM: Malzel's metronome, beats-per-minute) tempo were temporarily selected in MP3 format with a traditional four-four time (4/4) signature without lyrics as preferred by adults, regardless of the genre. Next, using smartphones or e-mails, a preference survey based on a 5-point Likert scale format and the sound sources were sent to all participants, and the participants were asked to select their preferences for each piece of music. Based on the preferences, the music selected as “normal” or “favorite” by all participants was used as the final basic music. Therefore, the basic music intended for SMT music creation included the following three pieces: the original soundtrack (OST) of The Wizard of Oz “Over the Rainbow,” “You Are My Everything” (OST of Descendants of the Sun), and “Canon in D” (J. Pachelbel).

Based on the final selected music, musical expectancy violations stimulation was generated by additionally selecting music for the modulation of specific bars of the basic music. The melody of music for modulation was similar to each basic musical piece, and two musical elements with instruments, performers, and recording environment differing from the basic music were selected for one basic music type. These complex tone differences were modulated to generate the musical expectancy violations as shown in [Figure 1]. For example, SMT music A used Harold Arlen's “Over the Rainbow” violin performance as the basic music, and three bars were modulated into a guitar performance (A') of the same music (”Over the Rainbow).” Another three bars were also produced by modulating an “Over the Rainbow” orchestra performance (A″). SMT music B and C were produced using the same principle [Figure 2].
Figure 1: Composition of self-music therapy training music. Each self-music therapy training music type consisted of a single set of 48 bars (measures) of basic music (A). Six bars randomly selected from the music for modulation (A', A”) were replaced and used as the stimulus in the same position as in the basic music to induce musical expectancy violations. Only one bar was changed for each phrase (4 bars), and a three-bar gap was maintained between the changed bars. The composition of the stimulated music differed in each of the basic music patterns.

Click here to view
Figure 2: Self music therapy training music production example. Base music (A): “Over the Rainbow,” Composer Harold Arlen, violin performance cover version (by Jenny Yoon). Music for modulation (A′): Guitar playing the cover version (by Park Chang-gon). Music for modulation (A″): Prosper Chamber Orchestra Performance.

Click here to view


All the music used to create the SMT music was converted to the same tonality as the basic music, and the tempo was fixed at 60 beats per minute (MM = 60) for accurate EEG measurement. In addition, the modulation of the basic music was performed within 48 bars, and only the 48 bars containing the modulation were extracted from each modulated basic music and used as SMT music in the study. Thus, the length of the SMT music was matched uniformly for EEG testing. When SMT is applied to the actual music therapy field, it is not necessary to adjust the length to 48 bars. The 48 bars corresponded to 192 s at a tempo of MM = 60, and each SMT music contained six modulated bars created using the modulated music.

Procedure

BioAMP was used as the EEG measurement equipment, and EEGs were obtained by attaching dry electrodes to eight scalp areas of the prefrontal cortex (Fp1 and Fp2), frontal lobes (F3 and F4), temporal lobes (T3 and T4), and parietal lobes (P3 and P4) according to the International 10/20 system. Each participant listened to three pieces of SMT music bearing musical expectancy violations.

All music and stimuli were delivered to the participants through headphones (Audio-Technica, ATH-M40x) connected to a PC while sitting in a chair with eyes closed. The volume was based on the standard 75 dB, which is the normal volume for comfortable listening with headphones and was adjusted at the request of the participants. The participants were prohibited from using cosmetics and perfumes that could affect their sense of smell on the day of the experiment, and alcohol and caffeine consumption were also prohibited. The EEG measurements are shown in [Figure 3].
Figure 3: Electroencephalograms measurement. Each participant listened to the original (unmodulated) basic music for 3 min before the experiment, and a stable interval of 30 s was set immediately before each self-music therapy training musical note was played. Each self-music therapy training musical piece composed of 48 bars (A, B, and C) had six musical expectancy violations stimulus bars.

Click here to view


Data analysis

Each of the three pieces of SMT music listened to by the participants for the EEG measurements consisted of 48 bars including six stimulated bars, and thus included a total of 18 musical expectancy violations. In this study, the EEG of the 18 stimulated bars was measured including background EEG in the first stable state, and one bar immediately before each stimulated bar (basic bar). The basic bar refers to an unmodulated bar without musical expectancy violations stimulus in the SMT music, and the stimulated bar refers to a modulated bar containing musical expectancy violations stimulus. The stable state was a state, in which the participant was at rest without listening to music. The quantitative EEG was measured by extracting 18 epochs from each stimulated bar and one basic bar immediately before it, and seven epochs were extracted from the stable bar (background EEG). The size of each epoch was 2.048 s, so the data of 88.064 s per participant were used. The power value per unit frequency was obtained through FFT, and the m-β wave appearance rate and the ATP were calculated.

The values are expressed as means ± standard deviations. The BrainBay program, which is an EEG s/w for Windows, was used for data collection and analysis, and the SPSS program (IBM SPSS statistics for Windows, Version 24.0, IBM Crop., Armonk, NY, USA) was used for statistical processing. The three conditions of basic-stable, stimulated-stable, and stimulated-basic were analyzed using the multiple comparison of Bonferroni's t-statistic to control the type one error rate.


  Results Top


Brain concentration based on the m-β wave appearance rate

Using the EEG data in the three conditions, the differences in the m-β wave appearance rate between each condition were analyzed. The results showed that the m-β wave appearance rate in the basic state was significantly higher in both the left and right sites of the prefrontal cortex (Fp1 and Fp2, t(df) =11, P < 0.05), the right frontal lobe (F4, t(df) =11, P < 0.05), both temporal lobes (T3 and T4, t(df) =11, P < 0.05), and both parietal lobes (P3 and P4, t(df) =11, P < 0.05) than in the stable state. The m-β wave appearance rate in the stimulated state was significantly higher in the prefrontal cortex (Fp1 and Fp2, t(df) =11, P < 0.05), the right frontal lobe (F4, t(df) =11, P < 0.05), both temporal lobes (T3 and T4, t(df) =11, P < 0.05), and both parietal lobes (P3 and P4, t(df) =11, P < 0.05) than in the stable state. It was also found to be significantly higher in the prefrontal cortex (Fp1 and Fp2, t(df) =11, P < 0.05), both temporal lobes (T3 and T4, t(df) =11, P < 0.05), and the right parietal lobe (P4, t(df) =11, P < 0.05) than in the basic state. The analysis of the mean of the entire scalp showed that the basic state was significantly higher than the stable state (t(df) =11, P < 0.05). The stimulated state was significantly higher than the stable state (t(df) =11, P < 0.05) and the basic state (t(df) =11, P < 0.05) [Table 1] and [Figure 4].
Table 1: Results of t-test analyzing changes in the participants' m-β wave appearance rate

Click here to view
Figure 4: Comparison of mean of m-β wave appearance rates in stable, basic, and stimulated states. In the stimulated state, the m-β wave appearance rates were statistically significantly higher than in the stable and basic states (*P < 0.05). The unit percentage of the mean of the quantitative m-β wave appearance rates in the stable, basic, and stimulated states [Table 1]. Values are the mean ± standard deviation.

Click here to view


The changes in the m-β wave appearance rate between the three conditions for each area of the participant's brain were higher in the stimulated and basic states than in the stable state (Fp1, Fp2, F4, T3, T4, P3, and P4) and also higher in the stimulated state than in the basic state (Fp1, Fp2, T3, T4, and P4). The findings suggest that normal adults listening to SMT music showed increased levels of brain concentration compared to listening to basic music or remaining in the stable state.

Brain activation by absolute total power

The ATP in the basic state was significantly lower in the right prefrontal cortex (Fp2, t(df) =11, P < 0.05), both frontal lobes (F3, F4, t(df) =11, P < 0.05), and the left temporal lobe (T3, t(df) =11, P < 0.05) than in the stable state. In addition, the ATP in the stimulated state was significantly higher in both left and right sites of the prefrontal cortex (Fp1 and Fp2, t(df) =11, P < 0.05), both frontal lobes (F3 and F4, t(df) =11, P < 0.05), and both temporal lobes (T3 and T4, t(df) =11, P < 0.05) than in the stable or basic state. The analysis of the mean of all areas showed that the basic state was significantly lower than the stable state (t(df) =11, P < 0.05), and the stimulated state was significantly higher than both the stable and basic states (t(df) =11, P < 0.05) [Table 2] and [Figure 5].
Table 2: Results of t-test analyzing the participant's absolute total power changes

Click here to view
Figure 5: Comparison of mean absolute total power levels in the stable, basic, and stimulated states. In the stimulated state, the mean absolute total power levels were statistically significantly higher than in the stable and basic states (*P < 0.05). The mean absolute total power level (μV2) refers to the integrated amount of brain waves by electroencephalograms amplitude for a certain period of time [Table 2]. Values are the mean ± standard deviation.

Click here to view


The ATP changes in the three conditions for each area of the participants' brains were lower in the basic than in the stable state (Fp2, F3, F4, and T3), but the ATP in the stimulated state was higher than in the basic or stable state in all areas except both parietal lobes (Fp1, Fp2, F3, F4, T3, and T4). The findings suggest that listening to SMT music can increase the level of brain activation in the prefrontal cortex (Fp1 and Fp2), frontal lobes (F3, F4), and temporal lobes (T3 and T4) in normal adults.


  Discussion Top


This study analyzed the effects of listening to SMT music, which was specially developed using musical expectancy violations to improve brain concentration and activation. It was performed in a sample of 12 adults. EEGs were obtained in three conditions.

The EEG results related to brain concentration revealed that, under stimulated conditions, the rate of m-β wave appearance was increased more than in the stable or basic states in all areas where the electrodes were attached, and there were significant differences in both sites on the prefrontal cortex (Fp1 and Fp2, t(df) =11, P < 0.05), both temporal lobes (T3 and T4, t(df) =11, P < 0.05), and the right parietal lobe (P4, t(df) =11, P < 0.05). In particular, the largest difference was detected in the prefrontal cortex (Fp1 and Fp2), and the overall mean also showed a significant difference in the m-β wave appearance rate in the stimulated state (9.71% ±1.45%) compared to the stable (5.39% ±0.79%) and basic states (6.09% ±0.85%) [Table 1] and [Figure 4]. In addition, in the basic state, a significant increase was observed in all areas (Fp1, Fp2, F4, T3, T4, P3, and P4) except for the frontal lobe (F3) compared to the stable state, but the difference was very small compared to the stimulated state.

The m-β wave pattern is an important variable recognized by most EEG analytical indicators of brain concentration such as the ratio of SMR + m-β to theta (RSMT), relative m-β to theta (RMT), and relative m-β power spectrum (RMB). The increase in m-β wave type is associated with increased concentration in the normal brain.[24],[25] Therefore, the above results indicating that the m-β wave appearance rate increased significantly in the stable compared to the basic state suggests that listening to general music may increase brain concentration. The significant increase in the rate of m-β waves in the stimulated state suggests that listening to SMT music along with general music and the stimulation of musical expectancy violations can effectively increase the level of brain concentration.

In terms of brain activation, the ATP of the basic state was lower in all areas than in the stable state and was significantly lower in the right prefrontal cortex (Fp2), both frontal lobes (F3 and F4), and the left temporal lobe (T3). In addition, the ATP in the stimulated state was significantly higher in both sites of the prefrontal cortex (Fp1 and Fp2) and both the frontal (F3 and F4) and temporal lobes (T3 and T4) compared to the stable or basic states. Based on the analysis of the mean of all areas, the ATP in the basic state (69.24 ± 35.36 μV2) was significantly lower than in the stable state (75.38 ± 39.48 μV2) and was significantly higher in the stimulated state (91.78 ± 48.28 μV2) than in the stable and basic states [Table 2] and [Figure 5].

Of the three conditions (stable, basic, and stimulated), the basic state referred to listening to basic music but not the stimulated bars in SMT music. Therefore, the above results indicate that brain activation may be decreased when listening to general music. However, because the ATP in the stimulated state was shown to be higher than in the stable or basic state in most areas including the prefrontal cortex, listening to SMT music containing stimulation helped to increase the level of brain activation.

The prefrontal cortex, similar to a chief executive, is responsible for the integrated control of execution, the order and timing of acts, such as planning, forecasting, and judgment and is responsible for focusing attention on performing tasks and expressing feelings in recognizable languages and emotions.[26],[27] The prefrontal cortex is an important part of the frontal lobe, highly connected to the temporal, parietal, and occipital lobes, and is also closely related to Broca's area responsible for language. The prefrontal cortex is a brain region that plays a key role in cognitive functions, thought processes, and creativity and is the region that contributes to mental activities related to learning behavior.[28],[29],[30],[31] Furthermore, reports suggest that brain functions are facilitated by the autonomous and synergistic effect of all neurons.[20],[32],[33] Thus, the prefrontal cortex reflects the active state of the entire brain. The results of this study imply that listening to SMT music, which included musical expectancy violations, increased the concentration and activation of the prefrontal cortex, and thereby, increased the activation of the entire brain.


  Conclusion Top


In conclusion, listening to SMT music produced using musical expectancy violations was shown to have a positive effect by increasing the levels of brain concentration and activation. If SMT music listening continues on a day when there is no actual music therapy clinic session, SMT can be helpful in improving the treatment effects, much like homework in psychological counseling. Therefore, the SMT music used in this study increased the effectiveness of music therapy by enhancing the efficiency of interventions based on music therapy such as Developmental Speech and Language Training through Music (DSLM) in the field of neurologic music therapy techniques. If SMT programs are developed in future to play the same role as homework in counseling, it may increase the efficacy of treatment with various types of music therapy. Currently, a study on increasing the treatment effects of SMT in music therapy clinical trials for patients with aphasia using the SMT music produced in this study is ongoing.

Acknowledgments

The authors extend their thanks to the subjects whose participation made this study possible. This work was supported by the Soonchunhyang University Research Fund.

Financial support and sponsorship

This study was financially supported by Soonchunhyan University Research Fund.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Brannon L, Feist J, Updegraff JA. Health Psychology: An Introduction to Behavior and Health. Boston: Cengage Learning; 2013.  Back to cited text no. 1
    
2.
Haynes R, Taylor D, Sackett D. Compliance in Health Care. Baltimore: Johns Hopkins University Press; 1979.  Back to cited text no. 2
    
3.
Baum A, Newman S, Weinman J, McManus C, West R. Cambridge Handbook of Psychology, Health and Medicine. Cambridge, UK: Cambridge University Press; 1997.  Back to cited text no. 3
    
4.
Hay CE, Kinnier RT. Homework in counseling. J Ment Health Counsel 1998;20:122.  Back to cited text no. 4
    
5.
Sheldon J, Ackerman J. Homework in Counseling and Psychotherapy: Springfield, IL: Charles C. Thomas; 1974.  Back to cited text no. 5
    
6.
Whisman MA, Jacobson NS. Brief Behavioral Marital Therapy. Handbook of the Brief Psychotherapies. Berlin: Springer; 1990. p. 325-49.  Back to cited text no. 6
    
7.
Beyebach M, Morejon AR, Palenzuela DL, Rodriguez-Arias JL. Research on the process of solution-focused therapy. In: Handbook of Solution-Focused Brief Therapy. San Francisco: Jossey-Bass Publishers; 1996. p. 299-334.  Back to cited text no. 7
    
8.
Halligan FR. The challenge: Short-term dynamic psychotherapy for college counseling centers. Psychother Theory Res Pract Train 1995;32:113.  Back to cited text no. 8
    
9.
Kazantzis N, Deane FP. Psychologists' use of homework assignments in clinical practice. Prof Psychol Res Pract 1999;30:581.  Back to cited text no. 9
    
10.
Koss MP, Shiang J. Research on brief psychotherapy. In A. E. Bergin & S. L. Garfield (Eds.), Handbook of psychotherapy and behavior change (p. 664–700). New York: John Wiley & Sons; 1994.  Back to cited text no. 10
    
11.
Norcross JC, Alford BA, DeMichele JT. The future of psychotherapy: Delphi data and concluding observations. Psychotherapy Theory Res Pract Train 1992;29:150.  Back to cited text no. 11
    
12.
Sklare GB. Brief Counseling That Works: A Solution-Focused Approach for School Counselors. Practical Skills for Counselors. Thousand Oaks, CF: Corwin Press; 1997.  Back to cited text no. 12
    
13.
Beck AT. Cognitive Therapy of Depression. New York: Guilford Press; 1979.  Back to cited text no. 13
    
14.
Carich MS. Utilizing task assignments within Adlerian therapy. Individ Psychol 1990;46:217-24.  Back to cited text no. 14
    
15.
Burns DD, Nolen-Hoeksema S. Coping styles, homework compliance, and the effectiveness of cognitive-behavioral therapy. J Consult Clin Psychol 1991;59:305-11.  Back to cited text no. 15
    
16.
Neimeyer RA, Twentyman CT, Prezant D. Cognitive and interpersonal group therapies for depression: A progressive report. Cogn Behav 1985;7:21-2.  Back to cited text no. 16
    
17.
Neimeyer RA, Feixas G. The role of homework and skill acquisition in the outcome of group cognitive therapy for depression - Republished article. Behav Ther 2016;47:747-54.  Back to cited text no. 17
    
18.
Persons JB, Burns DD. Factors Associated with Dropout and Outcome in a Naturalistic Study of Cognitive Therapy for Depression. IL: Paper Presented at the Annual Meeting of the Society for Psychotherapy Research; 1985.  Back to cited text no. 18
    
19.
Kazantzis N, Deane FP, Ronan KR. Homework assignments in cognitive and behavioral therapy: A meta-analysis. Clin Psychol Sci Pract 2000;7:189-202.  Back to cited text no. 19
    
20.
Haken H. Principles of Brain Functioning: A Synergetic Approach to Brain Activity, Behavior and Cognition. Berlin: Springer;1996.  Back to cited text no. 20
    
21.
Tomaino CM. Effective music therapy techniques in the treatment of nonfluent aphasia. Ann N Y Acad Sci 2012;1252:312-7.  Back to cited text no. 21
    
22.
Steinbeis N, Koelsch S, Sloboda JA. Emotional processing of harmonic expectancy violations. Ann N Y Acad Sci 2005;1060:457-61.  Back to cited text no. 22
    
23.
Tew S, Fujioka T, He C, Trainor L. Neural representation of transposed melody in infants at 6 months of age. Ann N Y Acad Sci 2009;1169:287-90.  Back to cited text no. 23
    
24.
Lubar JF. Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback Self Regul 1991;16:201-25.  Back to cited text no. 24
    
25.
Sterman M. Sensorimotor EEG operant conditioning: Experimental and clinical effects. Pavlov J Biol Sci 1977;12:63-92.  Back to cited text no. 25
    
26.
Amen D. Healing the Hardware of the Soul How Making the Brain-Soul Connection can Optimize Your Life, Love, and Spiritual Growth. New York: Simon and Schuster; 2008.  Back to cited text no. 26
    
27.
Walsh D. Why do They act That Way? A Survival Guide to the Adolescent Brain for You and Your Teen. New York: Atria Books; 2004.  Back to cited text no. 27
    
28.
Della Rocchetta AI, Milner B. Strategic search and retrieval inhibition: The role of the frontal lobes. Neuropsychologia 1993;31:503-24.  Back to cited text no. 28
    
29.
Fuster J. The Prefrontal Cortex. Anatomy, Physiology, and Neuropsychology of the Frontal Lobe. London: Raven Press; 1997.  Back to cited text no. 29
    
30.
Luriiî AR. The Working Brain: An Introduction to Neuropsychology. New York: Basic Books; 1973  Back to cited text no. 30
    
31.
Simonov PV. Neurobiological basis of creativity. Neurosci Behav Physiol 1997;27:585-91.  Back to cited text no. 31
    
32.
Friedrich R, Fuchs A, Haken H. Synergetic Analysis of Spatio-Temporal EEG Patterns. Nonlinear Wave Processes in Excitable Media. Berlin: Springer; 1991. p. 23-37.  Back to cited text no. 32
    
33.
Kelso JAS, Bressler SL, Buchanan S, de Guzman GC, Ding M, Fuchs A, Holroyd T. Cooperative and Critical Phenomena in the Human Brain Revealed by Multiple SQuIDs. Measuring Chaos in the Human Brain. New Jersey:World Scientific; 1991. p. 97-112.  Back to cited text no. 33
    


    Figures

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

  [Table 1], [Table 2]



 

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
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed360    
    Printed0    
    Emailed0    
    PDF Downloaded47    
    Comments [Add]    

Recommend this journal