A Nonlinear Neuro-Cognitive Exploration on the Timbre Dependence of Emotion

Indian Classical Music (ICM) has been known to convey a variety of emotional responses among the listeners since time immemorial, but neural attributes of these emotional experiences are largely unexplored till date. One of our earlier studies based on acoustical time series analysis reported that the timbre of an instrument can play significant role in conveying different emotions through various raga clips. This study aims to explore the neuro-cognitive attributes of the same. Taking two-minute aalaap (opening) sections of six popular ragas (three of them are conventionally known to portray happiness and the rest three sadness) of ICM, played in three different musical instruments (sitar, sarod and flute) by three maestros of ICM, this study attempted to look for the neural cues for these two contrasting emotions and if (and how) the timbre of the instrument plays any significance in their perception. EEG data was recorded from 10 (8 male, 2 female) participants while they listened to these music clips and their brain responses for each clip were analyzed with nonlinear chaos-based MFDFA technique in a comparative manner in order to look for specific arousal activities in different lobes of the brain corresponding to the contrasting music-evoked emotions. Our findings revealed that the multifractal spectral width obtained from alpha/theta frequency ranges of EEG data can be developed as a parameter for the development of an automated emotion recognition system. This study may prove to have far reaching implications in the development of an automated emotion classifier algorithm in future.