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Musicality of Human Brain through Fractal Analytics 1st ed. 2018 [Hardback]

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  • Formāts: Hardback, 232 pages, height x width: 235x155 mm, weight: 5029 g, 111 Illustrations, color; 8 Illustrations, black and white; XVII, 232 p. 119 illus., 111 illus. in color., 1 Hardback
  • Sērija : Signals and Communication Technology
  • Izdošanas datums: 05-Oct-2017
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9811065101
  • ISBN-13: 9789811065101
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Musicality of Human Brain through Fractal Analytics 1st ed. 2018Palielināt
  • Formāts: Hardback, 232 pages, height x width: 235x155 mm, weight: 5029 g, 111 Illustrations, color; 8 Illustrations, black and white; XVII, 232 p. 119 illus., 111 illus. in color., 1 Hardback
  • Sērija : Signals and Communication Technology
  • Izdošanas datums: 05-Oct-2017
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9811065101
  • ISBN-13: 9789811065101
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789811065101.html
This book provides a comprehensive overview of how fractal analytics can lead to the extraction of interesting features from the complex electroencephalograph (EEG) signals generated by Hindustani classical music. It particularly focuses on how the brain responses to the emotional attributes of Hindustani classical music that have been long been a source of discussion for musicologists and psychologists. Using robust scientific techniques that are capable of looking into the most intricate dynamics of the complex EEG signals, it deciphers the human brains response to different ragas of Hindustani classical music, shedding new light on what happens inside the performers brain when they are mentally composing the imagery of a particular raga. It also explores the much- debated issue in the musical fraternity of whether there are any universal cues in music that make it identifiable for people throughout the world, and if so, what are the neural correlates associated with the universal cues? This book is of interest to researchers and scholars of music and the brain, nonlinear science, music cognition, music signal processing and music information retrieval. In addition, researchers in the field of nonlinear biomedical signal processing and music signal analysis benefit from this book.





 
1 Introduction
1(20)
1.1 Music and Science
1(2)
1.2 Music and Emotion: Looking into Historical Perspective
3(1)
1.3 Psychological Analysis of Emotion
4(2)
1.4 Chaos Theory: Small Fluctuations Large Outcome
6(1)
1.5 Fractals and Multifractals: A New Dialogue Between Human and Nature
7(3)
1.6 How Music Affects Our Brain: From a Neuro-Physical Approach to Fractal Analysis Techniques
10(3)
1.7 Study of Effects of Music on Brain: An Indian Perspective
13(8)
References
15(6)
2 Non Linear Techniques for Studying Complex Systems
21(28)
2.1 Introduction
21(2)
2.2 Empirical Mode Decomposition (EMD)
23(2)
2.3 Wavelet Transform
25(4)
2.4 Detrended Fluctuation Analysis
29(3)
2.5 Multifractal Detrended Fluctuation Analysis (DFA)
32(4)
2.6 Multifractal Detrended Cross-Correlation Analysis (MFDXA)
36(4)
2.7 Estimation of Neural Jitter and Shimmer
40(4)
2.8 Estimation of Pitch of EEG Signal from Zero-Crossings
44(5)
References
46(3)
3 Emotions from Hindustani Classical Music: An EEG based study including Neural Hysteresis
49(24)
3.1 Introduction
49(6)
3.1.1 Background
49(1)
3.1.2 What Is Hysteresis?
50(1)
3.1.3 Neural Plasticity and Hysteresis
50(1)
3.1.4 Hindustani Classical Music and Emotions
51(1)
3.1.5 EEG and Musical Emotions
52(1)
3.1.6 Use of DFA to Assess Emotions and also Neural Hysteresis
53(1)
3.1.7 Overview of Our Work
54(1)
3.2 Experimental Details
55(2)
3.2.1 Subjects Summary
55(1)
3.2.2 Choice of Ragas: Chayanat and Darbari Kanada/Bahar and Mian Ki Malhar
55(1)
3.2.3 Experimental Protocol
56(1)
3.3 Methodology
57(1)
3.3.1 Empirical Mode Decomposition (EMD)
57(1)
3.3.2 Wavelet Transform
57(1)
3.3.3 Detrended Fluctuation Analysis (DFA)
58(1)
3.4 Results and Discussion
58(10)
3.5 Conclusion
68(5)
References
69(4)
4 Musical Perception and Visual Imagery: Do Musicians visualize while Performing?
73(30)
4.1 Introduction
73(5)
4.1.1 Creativity in Musical Performances: Brain Response
74(1)
4.1.2 Improvisation in Hindustani Music
75(1)
4.1.3 Musicians and Visual Imagery: Claims and Beliefs
76(1)
4.1.4 Musical Imagination and the Role of Occipital Lobe
76(1)
4.1.5 Use of MFDFA and MFDXA to Study Musical Imagination
77(1)
4.2 Experimental Details
78(2)
4.2.1 Subjects Summary
78(1)
4.2.2 Choice of Raga: Jayjayanti
78(1)
4.2.3 Experimental Protocol
79(1)
4.3 Methodology
80(1)
4.4 Results and Discussion
80(18)
4.5 Conclusion
98(5)
References
100(3)
5 Tanpura Drone and Brain Response
103(14)
5.1 Introduction
103(4)
5.1.1 What Is Tanpura Drone?
104(1)
5.1.2 How Does a Tanpura Drone Affect Brain Rhythm?
105(1)
5.1.3 Use of Tanpura Drone as a Baseline
105(1)
5.1.4 Use of MFDFA to Assess the Effect of Drone
106(1)
5.2 Experimental Details
107(1)
5.2.1 Subjects Summary
107(1)
5.2.2 Processing of Tanpura Drone
107(1)
5.2.3 Experimental Protocol
107(1)
5.3 Methodology
108(1)
5.4 Results and Discussions
109(4)
5.5 Conclusion
113(4)
References
114(3)
6 Genesis of Universality of Music: Effect of Cross Cultural Instrumental Clips
117(28)
6.1 Introduction
117(5)
6.1.1 What Is Universality of Music?
117(1)
6.1.2 Previous Research to Look for Universal Cues of Music
118(1)
6.1.3 Neuro-Cognition of Emotional Music Across Different Cultures
118(2)
6.1.4 Use of MFDFA on EEG to Assess Universality and Domain Specificity of Musical Emotion
120(1)
6.1.5 Overview of Our Work
121(1)
6.2 Experimental Details
122(4)
6.2.1 Collection of Human Response Data
122(1)
6.2.2 Processing of Music Signals
123(1)
6.2.3 Subjects Summary
123(1)
6.2.4 Experimental Protocol
124(1)
6.2.5 Methodology
125(1)
6.3 Results and Discussions
126(12)
6.4 Conclusion
138(7)
References
140(5)
7 Gestalt Phenomenon in Music: Which Frequencies Do We Really Hear?
145(20)
7.1 Introduction
145(5)
7.1.1 What Is Gestalt Psychology?
145(1)
7.1.2 Applications of Gestalt in Visual Domain
146(1)
7.1.3 Gestalt in Auditory Domain
146(1)
7.1.4 Creativity and Gestalt Theory
147(1)
7.1.5 Response of Brain to Certain Frequency Bands of Music Using Non-linear Techniques
147(2)
7.1.6 Doctoring of Clips from Tagore Songs
149(1)
7.1.7 Overview of Our Work
149(1)
7.2 Experimental Details
150(3)
7.2.1 Collection and Analysis of Human Response Data
150(2)
7.2.2 Subjects Summary
152(1)
7.2.3 Experimental Protocol
152(1)
7.3 Methodology
153(1)
7.4 Results and Discussions
154(4)
7.5 Conclusion
158(7)
References
160(5)
8 Emotion and Ambiguity: A Study
165(20)
8.1 Introduction
165(4)
8.1.1 Emotions in Hindustani Music and the Importance of Ambiguity
165(1)
8.1.2 Non Linear Source Modeling of Musical Instruments
166(1)
8.1.3 Neural Response to Emotional Stimuli
167(1)
8.1.4 Use of MFDFA to Assess Acoustical/Human Response
168(1)
8.2 Experimental Details
169(3)
8.2.1 Choice of Three Pairs of Ragas
169(1)
8.2.2 Analysis of the Acoustic Signal Using MFDFA
170(1)
8.2.3 Subjects Summary for EEG
170(1)
8.2.4 Experimental Protocol
170(2)
8.3 Methodology
172(1)
8.4 Results and Discussions
172(8)
8.5 Conclusion
180(5)
References
182(3)
9 Improvisation---A New Approach of Characterization
185(28)
9.1 Introduction
185(6)
9.1.1 Complex Structure of Music Signals
185(1)
9.1.2 Brief Introduction to Raga in Hindustani Classical Music
186(1)
9.1.3 Improvisation: Hindustani Classical Versus Western Music
186(2)
9.1.4 Earlier Studies to Capture Improvisation
188(1)
9.1.5 Fractal Study on Music Signals
188(1)
9.1.6 Essence of Multifractal Study on Music Signals
189(1)
9.1.7 Multifractal Cross Correlation Study and Its Implications
190(1)
9.2 Experimental Details
191(1)
9.2.1 Choice of Ragas
191(1)
9.3 Methodology
191(1)
9.4 Results and Discussion
192(15)
9.5 Conclusion
207(6)
References
209(4)
10 Neural Jitter-Shimmer and Extraction of Pitch from EEG Signals
213(18)
10.1 Introduction
213(4)
10.1.1 Application of Jitter/Shimmer and Pitch in Speech and Music Analysis
214(1)
10.1.2 Different EEG Frequency Bands and Their Importance
215(1)
10.1.3 Evaluation of Neural Jitter/Shimmer and Extraction of Fundamentals
216(1)
10.1.4 Probability of Occurrence of Fundamentals? Does a Preferred Fundamental Exist?
217(1)
10.2 Experimental Details
217(1)
10.3 Methodology
218(1)
10.4 Results and Discussion
218(8)
10.5 Conclusion
226(5)
References
227(4)
Epilogue 231
Prof. Dipak Ghosh, a University Gold medalist and a PhD in the area of High Energy Physics, published more than four hundred papers in international journals across the world. He was the Professor and Dean of the faculty of Science, Jadavpur University. He supervised the PhD thesis of 70 students and still continuing in doing so. From 2004, he started to work in the area of physics and music and established the Sir C V Raman Centre for Physics and Music, Jadavpur University. He worked as the coordinator of the Centre till his retirement in 2010. In this connection he has published more than hundred papers on music information retrieval and clinical psychology. Presently he is the Emeritus Professor at the Centre. His area interest for the last three years is to study the effect of music on human brain from the neuro-physics perspective. Prof. Ghosh is the recipient of many awards including Sir C.V. Raman Award by U.G.C, Govt. of India for his in-depth research work in various disciplines.

Dr. Ranjan Sengupta, a PhD in High energy Physics, was the Senior Research Scientist and Head, Scientific Research Department, ITC Sangeet Research Academy, Kolkata for 27 years. From 2010 he is associated with Sir C V Raman Centre of Physics and Music, Jadavpur University, Kolkata as a Scientific Consultant. He has published nearly 200 papers in the area of High Energy Physics, Music Signal Processing, Speaker Recognition, Music Information Retrieval, Music Perception and Cognition and Music Acoustics. He is a recipient of Sir C V Raman Award from Acoustical Society of India. A Life Fellow of the Acoustical Society of India, he is also a life member of Indian Physical Society and Indian Association for the Cultivation of Science, Kolkata. Mr. Shankha Sanyal is currently pursuing Ph.D in the field of Cognitive Neurophysics at Sir C.V. Raman Centre for Physics and Music, Jadavpur University. He completed Post Graduation in Physics from Jadavpur University, Kolkata in the year 2012. He is also a Graduate from Jadavpur University. He has been awarded the prestigious S.N. Bose Research Fellowship Award by Department of Science and Technology, Govt. of West Bengal. He is also a CSIR Senior Research Fellow Awardee, Govt. of India. He has more than 50 publications in different journals of international repute and Conference proceedings during his tenure of Ph.D. His main research interests involve emotion recognition and improvisational cues from different renditions of Hindustani Classical music as well as biomedical signal processing algorithms. 

Ms. Archi Banerjee is currently pursuing Ph.D in the field of Music Cognition at Sir C.V. Raman Centre for Physics and Music, Jadavpur University. She completed her Post Graduation in Physics from Jadavpur University, Kolkata in the year 2012. She did her Graduation also from Jadavpur University. She has been awarded the prestigious Inspire Scholarship by the Department of Science and Technology, Government of India. She is a student of music for the past 15 years at Shrutinandan school of Music under the patronage of her Guru Pt. Ajoy Chakraborty. She has published more than 50 high quality papers in peer-reviewed International Journals and Conferences in the domain of music signal processing and cognitive neuroscience.