Computational Exploration of Neural Dynamics Underlying Music Cues Among Trained and Amateur Subjects

2020 
Abstract Exploring the neural basis of music perception and processing has become relevant in neuroscience research for studying human cognition and emotion. Recently many neuroimaging studies have seen brain structure differences in responses to various auditory cue, including music stimuli among diverse individuals. Research still lacks to correlate cortical dynamics in accordance with music familiarity among professionally trained musicians and amateur subjects. With this context, this short-term study reports on effectively recording and computational analysis of neural signals for understanding the cortical network correlates associated with different auditory cues (Western music, Indian classical music, Guitar music and stressor noise) on trained and amateur subjects. On the basis of cognitive battery score analysis, the study recruited 20 volunteering healthy subjects, and grouped as trained subjects (N=10), having music training and amateur subjects (N=10), having no prior music training. EEG recordings were taken for 7 minutes in an eye closed relaxed state, for different auditory stimuli, in a sound proof and dimly lit Indian laboratory settings. In both amateur and trained subjects, heat maps indicated cortical re-organization of ɵ, α, β, and γ rhythms when exposed to different auditory stimuli at similar time bins. Cortical mapping indicated frontal (F3, F4, F7, F8), temporal (T7, T8) and parietal (P7 and P8) as functional regions for processing an auditory information with improved cognitive, attention, memory and language processing skills among trained and amateur subjects in response to familiar music stimuli. With other biosignals analysis techniques and using electrical engineering principles, the study could be further expanded to explore brain anatomy with music therapy as a tool in clinical, therapeutic and community settings.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    17
    References
    2
    Citations
    NaN
    KQI
    []