Musical training intensity yields opposite effects on grey matter density in cognitive versus sensorimotor networks
- 1.5k Downloads
Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills. However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes. In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity. We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density. The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise. Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl’s gyrus. Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills. Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music.
KeywordsMusical training Voxel-based morphometry Grey matter density Plasticity Cognition Sensorimotor function
We would like to thank Andres Posada, Alexis Hervais Adelman and Sebastian Rieger for assisting in MR data acquisition and help with fMRI setup, and Julien Chanal and Olivier Renaud for advice on statistical data analysis. Finally we thank Alexis Hervais Adelman once more for assistance on analyses, and precious comments on the manuscript.
- Charness N, Krampe R, Mayr U (1996) The role of practice and coaching in entrepreneurial skill domains: an international comparison of life-span chess skill acquisition. In: Ericsson KA (ed) The road to excellence: the acquisition of expert performance in the arts and sciences, sports, and games. Lawrence Erlbaum Associates, Mahwah, pp 51–80Google Scholar
- Duvernoy HM (1991) The human brain: surface, three-dimensional sectional anatomy, and MRI. Springer, New YorkGoogle Scholar
- Garavan H, Kelley D, Rosen A, Rao SM, Stein EA (2000) Practice-related functional activation changes in a working memory task. Microsc Res Tech 51(1):54–63. doi: 10.1002/1097-0029(20001001)51:1<54::AID-JEMT6>3.0.CO;2-J PubMedCrossRefGoogle Scholar
- Ousdal OT, Jensen J, Server A, Hariri AR, Nakstad PH, Andreassen OA (2008) The human amygdala is involved in general behavioral relevance detection: evidence from an event-related functional magnetic resonance imaging Go-NoGo task. Neuroscience 156(3):450–455PubMedCentralPubMedCrossRefGoogle Scholar
- Raven J, Raven JC, Court JH (2003) Manual for raven’s progressive matrices and vocabulary scales. section 1: general overview. San Antonio, TX: Harcourt AssessmentGoogle Scholar
- Starkes JL, Deakin JM, Allard F, Hodges NJ, Hayes A (1996) Deliberate practice in sports: what is it anyway? In: Ericsson KA (ed) The road to excellence: the acquisition of expert performance in the arts and sciences, sports, and games. Lawrence Erlbaum Associates, Mahwah, pp 81–106Google Scholar
- Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15(1):273–289. doi: 10.1006/nimg.2001.0978 PubMedCrossRefGoogle Scholar