AUTHOR=Karpati Falisha J. , Giacosa Chiara , Foster Nicholas E. V. , Penhune Virginia B. , Hyde Krista L. TITLE=Structural Covariance Analysis Reveals Differences Between Dancers and Untrained Controls JOURNAL=Frontiers in Human Neuroscience VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2018.00373 DOI=10.3389/fnhum.2018.00373 ISSN=1662-5161 ABSTRACT=

Dancers and musicians differ in brain structure from untrained individuals. Structural covariance (SC) analysis can provide further insight into training-associated brain plasticity by evaluating interregional relationships in gray matter (GM) structure. The objectives of the present study were to compare SC of cortical thickness (CT) between expert dancers, expert musicians and untrained controls, as well as to examine the relationship between SC and performance on dance- and music-related tasks. A reduced correlation between CT in the left dorsolateral prefrontal cortex (DLPFC) and mean CT across the whole brain was found in the dancers compared to the controls, and a reduced correlation between these two CT measures was associated with higher performance on a dance video game task. This suggests that the left DLPFC is structurally decoupled in dancers and may be more strongly affected by local training-related factors than global factors in this group. This work provides a better understanding of structural brain connectivity and training-induced brain plasticity, as well as their interaction with behavior in dance and music.