The functional brain networks activated by music listening : a neuroimaging meta-analysis and implications for treatment

Abstract

Objective: Previous behavioral studies show that music listening enhances attention and working memory in both healthy and clinical populations. However, how music listening engages brain functional networks remains elusive due to inconsistent results from previous findings. Method: A meta-analysis of functional magnetic resonance imaging data using seed-based d mapping (SDM) with permutation of subject images was performed. Studies that presented music listening paradigms to healthy individuals were included. Subgroup analyses were performed to investigate the effects of music genres on brain activation. To examine functional network correlates, voxels that were significantly activated by music listening were overlaid onto cortical, subcortical, and striatal network parcellations. Results: Whole-group analysis showed that ventral attention, somatomotor, default, dorsal attention, frontoparietal, and limbic networks significantly coactivated during music listening (familywise error-corrected p <.01). Specifically, music listening activated multiple frontal, temporal, subcortical, and cerebellar regions. Subgroup analyses revealed that classical music, but not songs or simple tunes, activated the limbic network. Meta-regression analysis revealed nonsignificant correlations between years of music training and all brain regions activated during music listening. Conclusions: Music listening bilaterally activated multiple cortical, subcortical, and cerebellar regions encompassing multiple brain networks that were not modulated by music training experience. It is recommended that music listening can be applied to people with neurological disorders to modulate the disordered functional brain networks known to underlie the pathophysiology of these diseases, while future studies may help delineate the effects of music preferences on brain activation patterns among these patients to promote the development of evidence-based medicine