Introduction

Abstract

Can music be defined? Most of us may agree that it is composed of a complex time series comprising of the three fundamental bases of physics–frequency, amplitude and timbre, but in real life music is something much more than that. Music is a mode of communication between human beings as well as between other living creatures. At first sight music shows a complex behavior: at every instant components (in micro and macro scale: pitch, timbre, accent, duration, phrase, melody etc) are close linked to each other. A self similar structure, or a process, and a part of it appear to be the same when compared. The expansion of the Universe from the big bang and the collapse of a star to a singularity both tend to self similarity in some circumstances. The most common “human made” self similar system include music. Self similarity in music comes from the coherent nature of the sounds. The coherencies are agreeing with each other in every scale and dimension in which they are perceived. The process of human cognition facilitates in different scales and similarity. Human mind groups similar objects of the same size into a single level of scale. The human brain, which is the most complex organ of human body, involves billions of interacting physiological and chemical processes, can now be measured with the help of neuro-scientific biosensors, viz. EEG, PET, fMRI etc. Since music cognition has many emotional aspects, it is expected that EEG recorded during music listening may reflect the electrical activities of brain regions related to those emotional aspects. Indian music is melodic and has somewhat different pitch perception mechanisms, thus it demands qualitatively different cognitive engagement. Although there is an emerging picture of the relationship between induced musical emotions and brain activity, a need for further refinement and exploration of neural correlates of emotional responses induced by music cannot be overruled. This book provides a comprehensive record of how fractal analytics can lead to the extraction of interesting features from complex EEG signal, which opens up new vistas in the direction of emotional categorization and quantification mainly from Hindustani Classical Music. Other characteristics of Hindustani Music like improvisation and universality are also dealt here.