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Individual Differences Predict Music Learning Success

Previous research has convincingly shown that music training results in changes in brain function as well as structure. However, as individuals differ in their learning abilities, it is unlikely that the effects of training on the brain would be identical for everyone. Therefore neuroscientific research on music-induced neuroplasticity has started focusing more on individual differences. including personality, motivation as well as other cognitive characteristics.

A study by Sibylle Herholz, Emily Coffey, Christo Pantev, and Robert Zatorre, recently published in Cerebral Cortex, examined how individual differences in neural networks were related to learning outcomes of music training. In the study, 14 adults with no prior training in music practiced playing melodies on a keyboard for six weeks. Their learning rate was monitored and the practice program adapted to learning achievements, becoming progressively more difficult. fMRI scans were performed on the participants prior to initiation of the practice program to determine their baseline neural activity when they listened to or imagined familiar tunes. The fMRI scan was repeated after the six weeks of training, and it was observed that there were significant changes in neural activation after the practice period. For example, the activation of areas related to storage of the newly learned auditory-motor associations increased as a result of practice. These changes in neural networks were expected given our understanding of music-training induced neuroplastic effects.

More surprisingly, it was seen that the activity of certain brain regions related to processing of sound and motor control in the baseline fMRI scan prior to the practice period was predictive of how fast and how accurately someone would learn a piece of music.

These results beautifully illustrate the mechanisms of predisposition and training-induced plasticity related to music training. There are individual differences in how basic perceptual information is processed and these differences influence the success of learning that makes use of this information. Better understanding of  individual differences in these mechanisms could in future be used to individualize and customize interventions that rely on learning.