Klasik Türk Müziği Makamlarının Minör/Majör Depresyon Hastalarının Üzerindeki Duygu Değişimlerine ve Tedavi Süreçlerine Etkilerinin Beyin EEG Sinyalleri Kullanılarak Analiz Edilmesi Potansiyelinin Meta-Sentez Yöntemi ile İncelenmesi

Yıl 2020, Cilt: 9 Sayı: 27, 947 - 978, 15.12.2020

Naciye Hardalaç , Hüseyin Yaşar , Pınar Akdemir Özışık

Öz

Müzikle tedaviyi sistemli olarak ilk defa kullanan Türklerde, bu tedavi yöntemi yaklaşık 6000 yıl kadar eskiye dayanmaktadır. Modern bilimin gelişimine paralel olarak müzikle tedavi üzerine bir çok literatür çalışması gerçekleştirilmiştir. Klasik Türk Müziği makam esasına dayanan bir Türk müzik türüdür. Klasik Türk Müziği ile müzik terapisi çok eski dönemlerden itibaren uygulanmasına rağmen bu kapsamdaki uluslararası modern literatür çalışmalarının gerçekleştirilmesine ancak 2000’li yılların ikinci yarısından itibaren başlandığı görülmektedir. Müzik dinlemenin beyin EEG (Elektroensefalografi) sinyallerine etkisinin incelenmesine ilişkin ilk çalışmalar 1980’li yılların başlarında yapılmıştır. Literatürde dinlenilen müzik eserinin beğenilip beğenilmediği ya da hangi duyguları
uyandırdığının beyin EEG sinyalleri ile tahmin edilmesi-sınıflandırılması yönünde birçok çalışma gerçekleştirilmiştir. Ayrıca, son yıllarda yapılan literatür çalışmaları dikkate alındığında müzik terapisinin oluşturduğu EEG sinyallerinin mühendislik analizi ile hastalığın gidişatı üzerindeki tıbbi değerlendirmelerin birlikte yapıldığı multi-disipliner literatür çalışmalarında artış görülmektedir. Müzik ile beyin EEG sinyalleri arasındaki ilişkileri inceleyen çalışmalarda kullanılan müzik eserlerinin, çalışmayı yapan ekiplerin etnik ve kültürel kökenlerinin de etkisiyle genellikle Klasik Batı Müziği, Klasik Hint Müziği, Rock Müzik, Klasik İran Müziği gibi müzik türlerinden seçildiği görülmektedir. Sınırlı sayıda olmakla birlikte Klasik Türk Müziği ile beyin EEG sinyalleri arasındaki ilişkiyi inceleyen çalışmalarda gerçekleştirilmiştir. Depresyon; uyaranlara karşı duyarlığın azalması, girişim gücünün ve kendine
güvenin yiterek umutsuzluğun, karamsarlığın güçlenmesi biçiminde beliren ruhsal bozukluk hali olarak tanımlanabilir. Depresyon genel olarak majör depresyon ve minör depresyon olmak üzere iki başlıkta incelenmektedir. Sağlık Bakanlığının antidepresan kullanımına ilişkin verileri yıllık ortalama % 10 civarında bir artışa işaret etmektedir. Ayrıca, bu veriler depresyonun ülkemiz adına bir hastalık olmaktan ziyade bir halk sağlığı problemine dönüşmek üzere olduğunu açıkça ortaya koymaktadır.
Bu meta-sentez çalışmasında literatür üzerinde kapsamlı bir inceleme yapılarak Klasik Türk Müziği makamlarının minör/majör depresyon hastaları üzerindeki duygu değişimlerine ve tedavi süreçlerine etkilerinin beyin EEG sinyalleri
kullanılarak analiz edilmesine yönelik potansiyelinin incelenmesi ve açığa çıkarılması hedeflenmiştir. Bu kapsamda gerçekleştirilen çalışmanın araştırmacıların konu hakkında multi-disipliner çalışmalar yapmalarını teşvik edeceği ve kolaylaştıracağı değerlendirilmektedir.

Anahtar Kelimeler

Müzik Analizi, Müzik Tedavisi, EEG Sinyalleri

Kaynakça

• AK, Ahmet Şahin, (2009), Türk Mûsikîsi Tarihi, Ankara: Akçağ Yayınları.
• AKAR, Saime, Sadık. KARA, Fatma. LATİFOĞLU. ve Vedat. BİLGİÇ, (2012), “Wavelet-Welch methodology for analysis of EEG signals of schizophrenia patients”, Cairo International Biomedical Engineering Conference (CIBEC), 6-9.
• AKAR, Saime, Sadık. KARA, Fatma. LATİFOĞLU. ve Vedat. BİLGİÇ, (2015), “Estimation of nonlinear measures of schizophrenia patients’ EEG in emotional states”, IRBM, XXXVI, 4:250-258.
• AKDEMİR, Saime, Sadık. KARA. ve Vedat. BİLGİÇ, (2010), “The investigation of respiratory differences during different auditory stimuli in schizophrenia patients”, 15th National Biomedical Engineering Meeting (BIYOMUT), 1-4.
• ALTENMULLER, Eckart, Wilfried. GRUHN, Dietrich. PARLITZ. ve Gundhild.
• LIEBERT, (2000), “The impact of music education on brain networks: evidence from EEG-studies”, International Journal of Music Education, 1:47-53.
• AL-GALAL, Sabaa Ahmed Yahya, Imad. Fakhri. Taha. ALSHAIKHLI, Abdul. Wahab. Bin. Abdul. RAHMAN. ve Mariam. Adawiah.
• DZULKUIFLI, (2015),“EEG-based Emotion Recognition while Listening to Quran Recitation Compared with Relaxing Music Using Valence-Arousal Model”, 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT),245-250.
• AL-GALAL, Sabaa Ahmed Yahya, Imad. Fakhri. Taha. ALSHAIKHLI. ve Abdul. Wahab. Bin. Abdul. RAHMAN, (2016), “Automatic emotion recognition based on EEG and ECG signals while listening to quranic recitation compared with listening to music”, International Conference on Information and Communication Technology for The Muslim World (ICT4M), 269-274.
• ARSLAN, Sevban, Nadiye. ÖZER. ve Funda. ÖZYURT, (2008), “Effect of music on preoperative anxiety in men undergoing urogenital surgery”, Australian Journal of Advanced Nursing, XXVI, 2:46-54.
• ASPFORS, Jessica. ve Göran. FRANSSON, (2015), “Research on mentor education for mentors of newly qualified teachers: A qualitative meta-synthesis”, Teaching and Teacher Education, 48:75-86.
• AYDAR, Deniz, (2018), “Türk Müziği Nazariyatına Genel Bir Bakış”, Bilig, 84:179-196.
• AYDEMİR, Murat, (2010), Türk Müziği Makam Rehberi, İstanbul: Pan Yayınevi.
• BAJOULVAND, Atena, Ramtin. Zargari. MARANDI, Mohammad. Reza. DALIRI. ve Seyed. Hojjat. SABZPOUSHAN, (2017), “Analysis of folk music preference of people from different ethnic groups using kernel-based methods on EEG signals”, Applied Mathematics and Computation, 307:62-70.
• BALASUBRAMANIAN, Geethanjali, Adalarasu. KANAGASABAI, Jagannath. MOHAN. ve Guhan. SESHADRI, (2018), “Music induced emotion using wavelet packet decomposition-An EEG study”, Biomedical Signal Processing and Control, 42:115-128.
• BANERJEE, Archi, Shankha. SANYAL, Anirban. PATRANABIS, Kaushik.
• BANERJEE, Tarit. GUHATHAKURTA, Ranjan. SENGUPTA, Dipak. GHOSH. ve Partha. GHOSE, (2016), “Study on brain dynamics by non linear analysis of music induced EEG signals”, Physica A: Statistical Mechanics and its Applications, 444:110-120.
• BEKİROĞLU, Tansel, Nimet. OVAYOLU, Yusuf. ERGÜN. ve Hasan. Ç. EKERBİÇER, (2013), “Effect of Turkish classical music on blood pressure: a randomized controlled trial in hypertensive elderly patients”, Complementary Therapies in Medicine, XXI, 3:147-154.
• BHATTACHARYA, Joydeep, Hellmuth. PETSCHE. ve Ernesto. PEREDA, (2001), “Interdependencies in the spontaneous EEG while listening to music”, International Journal of Psychophysiology, XLII, 3:287-301.
• BHATTACHARYA, Joydeep. ve Hellmuth. PETSCHE, (2005), “Phase synchrony analysis of EEG during music perception reveals changes in functional connectivity due to musical expertise”, Signal Processing, LXXXV, 11:2161-2177.
• BHATTACHARYA, Joydeep. ve Eun-Jeong. LEE, (2016), “Modulation of EEG theta band signal complexity by music therapy”, International Journal of Bifurcation and Chaos, XXVI, 1:1650001.
• BONDAS, Terese. ve Elisabeth. O. HALL, (2007), “Challenges in approaching metasynthesis research”, Qualitative Health Research, XVII, 1:113-121.
• CONG, Fengyu, Vinoo. ALLURI, Asoke. K. NANDI, Petri. TOIVIAINEN, Rui. FA, Basel. ABU-JAMOUS, Liyun. GONG, Bart. G. W. CRAENEN, Hanna.
• POIKONEN, Minna. HUOTILAINEN. ve Tapani. RISTANIEMI, (2013), “Linking brain responses to naturalistic music through analysis of ongoing EEG and stimulus features”, IEEE Transactions on Multimedia, XV, 5:1060-1069.
• ÇALIK, Muammer. ve Mustafa. SÖZBİLİR, (2014), “İçerik analizinin parametreleri”, Eğitim ve Bilim, XXXIX, 174:33-38.
• DEWITT-BRINKS, Dawn. ve Steven C. RHODES, (1992), “Listening Instruction: A Qualitative Meta-Analysis of Twenty-Four Selected Studies”.
• DONG, Qunxi, Yongchang. LI, Bin. HU, Qunying. LIU, Xiaowei. LI. ve Li. LIU, (2010), “A solution on ubiquitous EEG-based biofeedback music therapy”, 5th International Conference on Pervasive Computing and Applications, 32-37.
• DUAN, Ruo-Nan, Xiao-Wei. WANG. ve Bao-Liang. LU, (2012), “EEG-based emotion recognition in listening music by using support vector machine and linear dynamic system”, International Conference on Neural Information Processing, 468-475.
• ENGİN, Mehmet, Tayfun. DALBASTI, Erkan. Zeki. ENGİN, Doğa. YAVUZYILMAZ, Ender. ÖZDEMİR. ve Ömer. Sinan. AKAYDIN, (2010), “Non-Linear Analysis of Instrumental Turkish Traditional Music Modes Via Human’s EEGS”, İstanbul University-Journal of Electrical & Electronics Engineering, X, 1:1135-1141.
• FACHNER, Jörg, Christian. GOLD. ve Jaakko. ERKKILÄ, (2013), “Music therapy modulates fronto-temporal activity in rest-EEG in depressed clients”, Brain Topography, XXVI, 2:338-354.
• GUNTHER, Wilfried, Norbert. MULLER, Wolfgang. TRAPP, Johannes. C. HAAG, Andreas. STRAUBE, (1996), “Quantitative EEG analysis during motor function and music perception in Tourette’s syndrome”, European Archives of Psychiatry and Clinical Neuroscience, CCXLVI, 4:197-202.
• HADJIDIMITRIOU, Stelios. ve Leontios. J. HADJILEONTIADIS, (2012), “Toward an EEG-based recognition of music liking using time-frequency analysis”, IEEE Transactions on Biomedical Engineering, LIX, 12:3498-3510.
• HADJIDIMITRIOU, Stelios. ve Leontios. J. HADJILEONTIADIS, (2013), “EEG-based classification of music appraisal responses using time-frequency analysis and familiarity ratings”, IEEE Transactions on Affective Computing, IV, 2:161-172.
• HERNANDEZ-REIF, Maria, Miguel. DIEGO. ve Tiffany. FIELD, (2006), “Instrumental and vocal music effects on EEG and EKG in neonates of depressed and non-depressed mothers”, Infant Behavior and Development, XXIX, 4:518-525.
• HORUZ, Dilek, Mehmet. A. KURCER. ve Zeynep. ERDOĞAN, (2017), “The effect of music therapy on anxiety and various physical findings in patients with COPD in a pulmonology service”, Holistic Nursing Practice, XXXI, 6:378-383.
• HSU, Jia-Lien, Yan-Lin. ZHEN, Tzu-Chieh. LIN. ve Yi-Shiuan. CHIU, (2018), “Affective content analysis of music emotion through EEG”, Multimedia Systems, XXIV, 2:195-210.
• http://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER2017.2-eng.pdf (Erişim Tarihi: 04 Ocak 2020).
• http://www.hurriyet.com.tr/gundem/depresyon-artiyor-40815790 (Erişim Tarihi: 04 Ocak 2020).
• https://tr.wikipedia.org/wiki/Klasik_T%C3%BCrk_m%C3%BCzi%C4%9Fi (Erişim Tarihi: 04 Ocak 2020).
• https://tr.wikipedia.org/wiki/Depresyon (Erişim Tarihi: 04 Ocak 2020).
• ITO, Shin-ichi, Yasue. MITSUKURA, Minoru. FUKUMI. ve Norio. AKAMATSU, (2003), “A feature extraction of the EEG during listening to the music using the factor analysis and neural networks”, International Joint Conference on Neural Networks, 3:2263-2267.
• İBİŞ BABACAN, Şehnaz, (1998), “Türkiye›de Ruh Hastalıklarının Tedavisinde Müziğin Rolünün Müzik Eğitimi Açısından İncelenmesi ve Yorumlanması”, Gazi Üniversitesi Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Ankara.
• JENNI, Raoul, Mathias. S. OECHSLIN. ve Clara. E. JAMES, (2017), “Impact of major and minor mode on EEG frequency range activities of music processing as a function of expertise”, Neuroscience Letters, 647:159-164.
• KABUTO, Michinori, Takayuki. KAGEYAMA. ve Hiroshi. NITTA, (1993), “EEG power spectrum changes due to listening to pleasant musics and their relation to relaxation effects”, Nippon Eiseigaku Zasshi (Japanese Journal of Hygiene), XLVIII, 4:807-818.
• KADIR, Ros Shilawani S. Abdul, Mohd. H. GHAZALI, Zunairah. H. MURAT, Mohd. N. TAIB, Husna. A. RAHMAN. ve Siti. A. M. ARIS, (2010), “The preliminary study on the effect of nasyid music and rock music on brainwave signal using EEG”, International Congress on Engineering Education, 58-63. KARTHICK, Ng, Thajudin. AHAMED. ve Joseph. K. PAUL, (2006), “Music and the EEG: A study using nonlinear methods”, International Conference on Biomedical and Pharmaceutical Engineering, 424-427.
• KAUR, Barjinder, Dinesh. SINGH. ve Partha. Pratim. ROY, (2017), “A novel framework of EEG-based user identification by analyzing music-listening behavior”, Multimedia Tools and Applications, LXXVI, 24:25581-25602.
• KAWINTIRANON, Kornraphop, Yanika. BUATONG. ve Peerapon. VATEEKUL, (2016), “Online music emotion prediction on multiple sessions of EEG data using SVM”, International Joint Conference on Computer Science and Software Engineering (JCSSE), 1-6.
• KAYIM, Gonca, (2017), “Dünya’da Müzik Terapi Tarihi ve Eğitimi”, Haliç Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, İstanbul.
• KEPREOTES, Elizabeth, (2009), “The Metasynthesis: Reducing the Isolation of Qualitative Research”, HNE, 47.
• KOÇ, Havva, Gülcan. ERK, Yılmaz. APAYDIN, Eyüp. HORASANLI, Betül.
• YİĞİTBAŞI. ve Bayazit. DİKMEN, (2009), “Epidural Anestezi ile Herni Operasyonu Uygulanan Hastalarda Klasik Türk Müziğinin İntraoperatif Sedasyon Üzerine Etkileri”, Journal of the Turkish Anaesthesiology & Intensive Care Society-JTAICS/Türk Anestezi ve Reanimasyon Dergisi, XXXVII, 6:366-373.
• KOELSTRA, Sander, Ashkan. YAZDANI, Mohammad. SOLEYMANI, Christian. MUHL, Jong-Seok. LEE, Anton. NIJHOLT, Thierry. PUN, Touradj. EBRAHINaciye HARDALAÇ / Hüseyin YAŞAR / Pınar AKDEMIR ÖZIŞIK Klasik Türk Müziği Makamlarının Minör/Majör Depresyon Hastalarının Üzerindeki Duygu Değişimlerine ve Tedavi Süreçlerine Etkilerinin Beyin EEG SinyalleriKullanılarak Analiz Edilmesi Potansiyelinin Meta-Sentez Yöntemi ile İncelenmesi MI. ve Ioannis.
• PATRAS, (2010), “Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos”, International Conference on Brain Informatics, 89-100.
• KORHAN, Akın, Meltem. UYAR, Can. EYİGÖR, Gülendam. HAKVERDİOĞLU YÖNT, Serkan. ÇELİK. ve Leyla. KHORSHID, (2014), “The effects of music therapy on pain in patients with neuropathic pain”, Pain Management Nursing, XV, 1:306-314.
• KROUPI, Eleni, Ashkan. YAZDANI. ve Touradj. EBRAHIMI, (2011), “EEG correlates of different emotional states elicited during watching music videos”, Affective Computing and Intelligent Interaction, 457-466.
• KUMAR, Satheesh. ve P. BHUVANESWARI, (2012), “Analysis of Electroencephalography (EEG) Signals and İts Categorization–A Study”, Procedia Engineering, 38:2525-2536.
• KUMAGAI, Yuiko, Mahnaz. ARVANEH. ve Toshihisa. TANAKA, (2017), “Familiarity affects entrainment of EEG in music listening”, Frontiers in Human Neuroscience, 11:384.
• KURDOĞLU, Veli Behçet, (1967), Şair Tabipler, İstanbul: Baha Matbaası.
• LI, Zhao. ve Guo. XUHONG, (2012), “EEG Control of Music Player”, Fifth International Conference on Intelligent Networks and Intelligent Systems, 189- 192.
• LIN, Yuan-Pin, Chi-Hong. WANG, Tien-Lin. WU, Shyh-Kang. JENG. ve Jyh-Horng. CHEN, (2007), “Multilayer perceptron for EEG signal classification during listening to emotional music”, TENCON 2007-2007 IEEE Region 10 Conference, 1-3.
• LIN, Yuan-Pin, Chi-Hong. WANG, Tien-Lin. WU, Shyh-Kang. JENG. ve Jyh-Horng. CHEN, (2008), “Support vector machine for EEG signal classification during listening to emotional music”, 10th Workshop on Multimedia Signal Processing, 127-130.
• LIN, Yuan-Pin, Chi-Hong. WANG, Tien-Lin. WU, Shyh-Kang. JENG. ve Jyh-Horng. CHEN, (2009), “EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine”, International Conference on Acoustics, Speech and Signal Processing, 489-492.
• LIN, Yuan-Pin, Chi-Hong. WANG, Tzyy-Ping. JUNG, Tien-Lin. WU, Shyh-Kang. JENG, Jeng-Ren. DUANN. ve Jyh-Horng. CHEN, (2010), “EEG-based emotion recognition in music listening”, IEEE Transactions on Biomedical Engineering, LVII, 7:1798-1806.
• LIU, Ning-Han, Cheng-Yu. CHIANG. ve Hsiang-Ming. HSU, (2013), “Improving driver alertness through music selection using a mobile EEG to detect brainwaves”, Sensors, XIII, 7:8199-8221.
• LOEWY, Joanne, Cathrine. H. L. PSYCH, Eliezer. FRIEDMAN. ve Christine.
• MARTINEZ, (2005), “Sleep/sedation in children undergoing EEG testing: A comparison of chloral hydrate and music therapy”, Journal of PeriAnesthesia Nursing, XX, 5:323-331.
• LU, Huisheng, Mingshi. WANG. ve Hongqiang. YU, (2006), “EEG model and location in brain when enjoying music”, 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2695-2698.
• LU, Jing, Dan. WU, Hua. YANG, Cheng. LUO, Chaoyi. LI. ve Dezhong. YAO, (2012), “Scale-free brain-wave music from simultaneously EEG and fMRI recordings”, PloS One, VII, 11:e49773.
• MAITY, Akash Kumar, Ruchira. PRATIHAR, Vishal. AGRAWAL, Anubrato.
• MITRA, Subham. DEY, Shankha. SANYAL, Archi. BANERJEE, Ranjan. SENGUPTA. ve Dipak. GHOSH, (2015), “Multifractal Detrended Fluctuation Analysis of the music induced EEG signals”, International Conference on Communications and Signal Processing, 0252-0257.
• MARTSOLF, Donna, Claire. B. DRAUCKER, Christina. B. COOK, Ratchneewan. ROSS, Andrea. Warner. STIDHAM. ve Prudencia. MWEEMBA, (2010), “A meta-summary of qualitative findings about professional services for survivors of sexual violence”, Qualitative Report (Online), XV, 3:489.
• MCDERMOTT, Elizabeth, Hilary. GRAHAM. ve Val. HAMILTON, (2004), “Experiences of being a teenage mother in the UK: a report of a systematic review of qualitative studies”, Lancaster: Lancaster University, 39-42.
• MERCADİÉ, Lolita, Julie. CABALLE, Jean‐Julien. AUCOUTURIER. ve Emmanuel. BIGAND, (2014), “Effect of synchronized or desynchronized music listening during osteopathic treatment: An EEG study”, Psychophysiology, LI, 1:52-59.
• MIKHAILOVA, Elen, (1991), “EEG Mapping Of Three Alpha-subbands In Healthy And Depressive Subjects Under Music Test”, Engineering in Medicine and Biology Society, 13:1201-1202.
• MIRANDA, E. Reck. ve Bram. BOSKAMP, (2005), “Steering generative rules with the EEG: An approach to brain-computer music interfacing”, Proceedings of Sound and Music Computing, 5.
• MUDGE, Suzie, Nicola. KAYES. ve Kathryn. MCPHERSON, (2015), “Who is in control? Clinicians’ view on their role in self-management approaches: a qualitative metasynthesis”, BMJ Open, V, 5:p.e007413.
• NAWASALKAR, Ram, Pradeep. K. BUTEY, Swapnil. G. DESHPANDE. ve Vilas. M. THAKARE, (2015), “EEG based stress recognition system based on Indian classical music”, International Conference on Advances in Computer Engineering and Applications, 936-939.
• NELSON, J. Craig, (2016), “Minor Depression: Is it Important? How Should it be Treated?”, The American Journal of Geriatric Psychiatry, XXIV, 8:624-626.
• NICOLAOU, Nicoletta, Asad. MALIK, Ian. DALY, James. WEAVER, Faustina.
• HWANG, Alexis. KIRKE, Etienne. B. ROESCH, Duncan. WILLIAMS, Eduardo.
• R. MIRANDA. ve Slawomir. J. NASUTO, (2017), “Directed motor-auditory EEG connectivity is modulated by music tempo”, Frontiers in Human Neuroscience, 11:502.
• NOBLIT, George. ve R. Dwight. HARE, (1988), Meta-Ethnography: Synthesizing Qualitative Studies, California: SAGE. OGAWA, Takahiro, Shin-ichi. ITO, Yasue. MİTSUKURA, Minoru. FUKUMI. ve Norio. AKAMATSUA, (2004), “Feature extraction from EEG patterns in music listening”, International Symposium on Intelligent Signal Processing and Communication Systems, 17-21.
• OVAYOLU, Nimet, Özlem. UÇAN, Seda. PEHLİVAN, Yavuz. PEHLİVAN, Hakan. BUYUKHATİPOGLU, Cemil. SAVAŞ. ve Murat. T. GÜLSEN, (2006), “Listening to Turkish classical music decreases patients’ anxiety, pain, dissatisfaction and the dose of sedative and analgesic drugs during colonoscopy: a prospective randomized controlled trial”, World Journal of Gastroenterology, XII, 46:7532-7536.
• OVERMAN, Amy, Jessica. HOGE, Alexander. DALE, Jeffrey. CROSS. ve Alec.
• CHIEN, (2003), “EEG alpha desynchronization in musicians and nonmusicians in response to changes in melody, tempo, and key in classical music”, Perceptual and Motor Skills, XCVII, 2:51
• PAN, Yaozhang, Cuntai. GUAN, Juanhong. YU, Kai. Keng. ANG. ve Ti. Eu.
• CHAN, (2013), “Common frequency pattern for music preference identification using frontal EEG”, 6th International IEEE/EMBS Conference on Neural Engineering (NER), 505-508.
• PARK, Seung-Min. ve Kwee-Bo. SIM, (2011), “A study on the analysis of auditory cortex active status by music genre: Drawing on EEG”, Eighth International Conference on Fuzzy Systems and Knowledge Discovery, 3:1916-1919.
• PETERSON, David A. ve Michael. H. THAUT, (2007), “Music increases frontal EEG coherence during verbal learning”, Neuroscience Letters, CDXII, 3:217-221. PETSCHE, Helmuth, Kathleen. A. LINDER, P. RAPPELSBERGER. ve Gerold.
• W. GRUBER, (1988), “The EEG: An adequate method to concretize brain processes elicited by music”, Music Perception: An Interdisciplinary Journal, VI, 2:133-159.
• POLAT, Seyat. ve Osman. AY, (2016), “Meta-sentez: kavramsal bir çözümleme”, Eğitimde Nitel Araştırmalar Dergisi, IV, 2:52-64.
• PORTNOVA, Galina, Alexandra. MASLENNIKOVA. ve Anton. VARLAMOV, (2018), “Same music, different emotions: assessing emotions and EEG correlates of music perception in children with ASD and typically developing peers”, Advances in Autism.
• RAMIREZ, Rafael, Josep. PLANAS, Nuria. ESCUDE, Jordi. MERCADE. ve Cristina. FARRIOLS, (2018), “EEG-Based Analysis of the Emotional Effect of Music Therapy on Palliative Care Cancer Patients”, Frontiers in Psychology, 9:254.
• SAIWAKI, Naoki, Hisashi. TSUJIMOTO, Shogo. NISHIDA. ve Seiji. INOKUCHI, (1996), “Directed coherence analysis of EEG recorded during music listening”, Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE, 2:827-828.
• SAKHAROV, Dmitry, Vi. DAVYDOV. ve Ra. PAVLYGINA, (2005), “Intercentral relations of the human EEG during listening to music”, Human Physiology, XXXI, 4:392-397.
• SANDELOWSKI, Margarete. ve Julie. BARROSO, (2003), “Classifying the findings in qualitative studies”, Qualitative Health Research, XIII, 7:905-923.
• SARITAŞ, Seyhan, Serdar. SARITAŞ, Rahşan. ÇEVİK AKYIL. ve Kevser. IŞIK, (2018), “The effects of Turkish classical music on physiological parameters, pain and analgesic use in patients with myocardial infarction: A non-randomized controlled study”, European Journal of Integrative Medicine, 22:50-53.
• SARNTHEIN, Johannes, Astrid. VONSTEIN, Peter. RAPPELSBERGER, Hellmuth. PETSCHE, Frances. RAUSCHER. ve Gordon. SHAW, (1997), “Persistent patterns of brain activity: an EEG coherence study of the positive effect of music on spatial-temporal reasoning”, Neurological Research, XIX, 2:107-116.
• SAWATA, Ryosuke, Takahiro. OGAWA. ve Miki. HASEYAMA, (2015), “Human-centered favorite music estimation: EEG-based extraction of audio features reflecting individual preference”, IEEE International Conference on Digital Signal Processing (DSP), 818-822.
• SAWATA, Ryosuke, Takahiro. OGAWA. ve Miki. HASEYAMA, (2016), “Novel favorite music classification using EEG-based optimal audio features selected via KDLPCCA”, International Conference on Acoustics, Speech and Signal Processing (ICASSP), 759-763.
• SCHAEFER, Rebecca, Peter. DESAIN. ve Jason. FARQUHAR, (2013), “Shared processing of perception and imagery of music in decomposed EEG”, Neuroimage, 70:317-326.
• SENGUPTA, Sourya, Sayan. BISWAS, Shankha. SANYAL, Archi. BANERJEE, Ranjan. SENGUPTA. ve Dipak. GHOSH, (2016), “Quantification and categorization of emotion using cross cultural music: An EEG based fractal study”, 2nd International Conference on Next Generation Computing Technologies (NGCT), 759-764.
• SHAHABI, Hossein. ve Sahar. MOGHIMI, (2016), “Toward automatic detection of brain responses to emotional music through analysis of EEG effective connectivity”, Computers in Human Behavior, 58:231-239.
• SHAHNAZ, Celia, Shoaib. MASUD. ve S. M. Shafiul. HASAN, (2016), “Emotion recognition based on wavelet analysis of Empirical Mode Decomposed EEG signals responsive to music videos”, Region 10 Conference (TENCON), 424-427.
• SOURINA, Olga, Yisi. LIU. ve Minh. K. NGUYEN, (2012), “Real-time EEG-based emotion recognition for music therapy”, Journal on Multimodal User Interfaces, V, 1-2:27-35.
• SREEDEVI M, A. AJESH, R. AJITHNATH. ve L. BINU, (2009), “A study of effect of music pitch variation in EEG using factor analysis and neural networks”, 2nd International Conference on Biomedical Engineering and Informatics,1-3.
• STURM, Irene, Sven. DÄHNE, Benjamin. BLANKERTZ. ve Gabriel. CURIO, (2015), “Multi-variate EEG analysis as a novel tool to examine brain responses to naturalistic music stimuli”, PloS One, X, 10:e0141281.
• ŞENGÜL, Enver, (2008), “Kültür Tarihi İçinde Müzikle Tedavi ve Edirne Sultan II. Bayezid Darüşşifası”, Trakya Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, Edirne.
• UÇAN, Ali, (1985), “İnsan ve Müzik”, Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, I, 1:74-92.
• UĞRAŞ, Gülay, Güven. YILDIRIM, Serpil. YÜKSEL, Yusuf. ÖZTÜRKÇÜ, Mustafa. KUZDERE. ve Seher. D. ÖZTEKİN, (2018), “The effect of different types of music on patients’ preoperative anxiety: A randomized controlled trial”, Complementary Therapies in Clinical Practice, 31:158-163.
• USLU, Gonca, (2017), “Influence of Music Therapy on the State of Anxiety During Radiotherapy”, Turkish Journal of Oncology, XXXII, 4:141-147. TANDLE, Avinash, Nandini. JOG, Ambrish. DHARMADHIKARI, Suyog.
• JAISWAL. ve Vishal. SWANT, (2016), “Study of valence of musical emotions and its laterality evoked by instrumental Indian classical music: An EEG study”, International Conference on Communication and Signal Processing (ICCSP), 0327- 0331.
• THAMMASAN, Nattapong, Ken-ichi. FUKUI. ve Masayuki. NUMAO, (2016), “An investigation of annotation smoothing for eeg-based continuous music-emotion recognition”, IEEE International Conference on Systems, Man, and Cybernetics (SMC), 003323-003328.
• THAMMASAN, Nattapong, Ken-ichi. FUKUI. ve Masayuki. NUMAO, (2016), “Application of deep belief networks in eeg-based dynamic music-emotion recognition”, International Joint Conference on Neural Networks (IJCNN), 881-888.
• THAMMASAN, Nattapong, Ken-ichi. FUKUI. ve Masayuki. NUMAO, (2017), “Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition”, Association for the Advancement of Artificial Intelligence, 4991-4992.
• TORNEK, Alexandra, Tiffany. FIELD, Maria. HERNANDEZ-REIF, Miguel. DIEGO. ve Nancy. JONES, (2003), “Music effects on EEG in intrusive and withdrawn mothers with depressive symptoms”, Psychiatry, LXVI, 3:234-243.
• TREDER, Matthias Sebastian, Hendrik. PURWINS, Daniel. MIKLODY, Irene. STURM. ve Benjamin. BLANKERTZ, (2014), “Decoding auditory attention to instruments in polyphonic music using single-trial EEG classification”, Journal of Neural Engineering, XI, 2:026009.
• TSENG, Kevin, Bor-Shyh. LIN, Chang-Mu. HAN. ve Psi-Shi. WANG, (2013), “Emotion recognition of EEG underlying favourite music by support vector machine”, International Conference on Orange Technologies (ICOT), 155-158.
• VAROTTO Giulia, Patrik. FAZIO, D. Rossi. SEBASTIANO, Giuliano. AVANZINI, Silvana. FRANCESCHETTI. ve Ferruccio. PANZICA, (2012), “Music and emotion: An EEG connectivity study in patients with disorders of consciousness”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5206-5209.
• VERMA, Tapish. ve Indu. SAINI, (2016), “Age-related variation in EEG to music stimulation: A nonlinear analysis”, 2nd International Conference on Next Generation Computing Technologies, 137-143.
• VIJAYALAKSHMI, K, Susmita. SRIDHAR. ve Payal. KHANWANI, (2010), “Estimation of effects of alpha music on EEG components by time and frequency domain analysis”, International Conference on Computer and Communication Engineering, 1-5.
• VIJAYARAGAVAN, Gautham Raj, Revathy. RAGHAV, Kompella. PHANI. ve Vivek. VAIDYANATHAN, (2015), “EEG monitored mind de-stressing smart phone application using Yoga and Music Therapy”, International Conference on Green Computing and Internet of Things (ICGCIoT), 412-415.
• WALKER, James, (1980), “Alpha EEG correlates of performance on a music recognition task”, Physiological Psychology, VIII, 3:417-420. WEED, Mike, (2005), ““Meta Interpretation”: A Method for the Interpretive Synthesis of Qualitative Research”, Forum Qualitative Sozialforschung/Forum:Qualitative Social Research, VI, 1.
• YİĞİTBAŞ, Sadık, (1972), Musiki ile Tedavi (1. Basım), İstanbul: İstanbul Yayınevi. ZHAO, Wei, Xinxi. WANG. ve Ye. WANG, (2010), “Automated sleep quality measurement using EEG signal: first step towards a domain specific music recommendation system”, 18th ACM International Conference on Multimedia, 1079- 1082