Characterization of functional brain connectivity towards optimization of music selection for therapy: a fMRI study

Background: Music therapy, a nontraditional approach to patient care, has long been used to achieve a wide variety of positive results. To deepen our understanding of the connection and therapeutic potential of music, the effect of music therapy and music medicine (music administered to individuals without an interactive therapeutic relationship) on the brain remains a topic of active research. Objective: This study is aimed at investigating the effect of different music genres and individualized music selection on brain functional connectivity (FC) measured by functional magnetic resonance imaging (fMRI). Methods: Twelve healthy subjects listened to five excerpts: Bach with and without visual guide (unfamiliar), self-selected familiar music, Gagaku (unfamiliar music) and Chaplin (spoken word) while undergoing a block design fMRI study. fMRI datasets were imported into CONN (Matlab toolbox) and graph networks were created for 132 anatomical regions in MNI space. Group connectivity for each soundtrack was quantified and statistically analyzed using the R package. Results: Complex interactions between brain regions, cerebellar regions (713), superior frontal gyrus (178) and parahippocampus (223), were highest for self-selected music. Brain regions involving sound processing, memory retrieval, semantic processing and motor areas were continuously activated for all five excerpts; however, most connections were formed in language processing regions for the Bach excerpt. Conclusion: Functional brain connectivity varied by soundtrack with the largest degree of connectivity found consistently for self-selected and unfamiliar (Bach, Gagaku) music. Incorporating individualized music listening into existing therapy paradigms may positively contribute to standard protocol for stroke rehabilitation and prevention.