Neural correlates of music training

: a systematic review and voxel-based meta analysis

Abstract

It has been widely suggested that music training changes brain structure and function. Most evidence comes from cross-sectional studies, though, limiting conclusions about causality. In this work, we conducted a systematic review and meta-analysis of the existing neuroimaging evidence on associations between music training and brain structure and function, including 113 cross-sectional studies and 10 longitudinal studies (N = 3256). For cross-sectional studies on gray matter, a seed-based d mapping metaanalysis revealed that music training is associated with increased gray matter in the left superior temporal gyrus, and this association was not moderated by participants’ age, age of onset of training, or duration of music training. A narrative synthesis of crosssectional studies on white matter provided initial evidence for an association between music training and increased fractional anisotropy and directional diffusivity in the right corticospinal tract. Finally, a narrative synthesis of longitudinal studies on brain structure showed that only three studies provided evidence for significant effects of training. Moreover, one of them did not have an active control group, and the other two had a partially overlapping sample of participants and results were limited to a minority of the hypothesized effects. Several methodological limitations of the existing literature were also identified, such as small sample sizes. Altogether, our findings document associations between music training and brain structure, but the evidence that they are caused by the training is weak. It is possible that the cross-sectional differences observed in musicians reflect preexisting factors, such as genetic predispositions for music.

Date of Award	13 Dec 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	César Lima (Supervisor), Daniel Martins (Co-Supervisor) & Maria Vânia Silva Nunes (Co-Supervisor)