The coupling between musical perception and action has been argued to be a function of rhythm associated with the evolutionary embedding of motor actions mirrored in others (Llinas & Ribary, 2001). Rhythm is known to have a powerful entraining effect (Molinari et al., 2003), which also appears to engage the mirror neuron system (Gallese et al., 1996) and cerebellum (Sakai et al., 1999). Whilst this example is descriptive of a general action-perception coupling, the skills specifically associated with musical learning are difficult and complex as Altenmüller & Schneider (2008) describe:
“Performing music at a professional level is probably the most demanding of human accomplishments. Making music requires the integration of multimodal sensory and motor information and precise monitoring of the performance via auditory feedback.” (Altenmüller & Schneider, 2008, p. 332)
Musical instrument learning has been described as a process of optimisation, which requires the planning, organisation and execution of complex motor sequences (Penhume & Steele, 2012). This process relies on the simultaneous coordination and control of movements from multiple body parts. The feedback/feedforward loops rely in turn on the integration of the auditory, visual and tactile receptors. This afferent nervous system information is often generally described as proprioception. However, Sherrington (1906) explored several different aspects of this in detail. Proprioception specifically refers to muscular, tendon and articular (joint) sensitivity; exteroception refers to afferent information regarding the mouth, eyes and skin; and interoception refers to information gathered from internal organs, such as the inner ear for balance. These may be useful terms regarding the specificities of musical training as musical playing relies on a
constant dynamic monitoring mode, or feedback loop which supports the notion of neural meta-plasticity (Schlaug et al., 2010; Zatorre et al., 2007).
Multiple brain regions in both hemispheres and neural networks have been associated with structural and functional changes either due to, or concomitant with, musical training. Karni et al., (1995) reported increased representation (enlargement of the hand area) in the Primary Motor Cortex (PMC, or M1) in adults. In comparison to a non-training group, the training group improved (speed and accuracy) to an optimal level after three weeks, though only on the specific finger movement sequence (in comparison to novel sequences). Associated activity-dependent changes were observed in M1 and the effect remained for several months after training was discontinued. However, this study did not report controlling for previous musical experience in the six male participants. Schlaug et al. (1995) did find evidence that violin and piano players, who had begun learning their instruments before the age of seven had a larger anterior area of the corpus callosum (CC; the white matter tract connecting the hemispheres). Subsequent research suggested that this adaptation in the CC enables increased independence between hands (Lee, Chen & Schlaug, 2002; Oztürk et al., 2008; Ridding et al., 2000). Furthermore, increased grey matter volume in left inferior frontal gyrus in the prefrontal cortex, which is known to inhibit inappropriate motor responses in musicians compared with non- musicians has been observed (Mahncke et al., 2006; Sluming et al., 2002; Swick, Ashley & Turken, 2008). The depth of the central sulcus, which is an indicator of the size of PMC, also appears to be larger in musicians than non-musicians and is more pronounced in the right hemisphere, possibly as a result of training demands on both the preferred and non-dominant hands associated with the musical learning (Amunts et al., 1997; Bangert & Altenmüller, 2003; Lotze et al., 2003; Schlaug, 2001). Specific neural adaptations to specific instruments have been shown (see e.g. Bangert et al., 2006; Elbert et al., 1995; Pantev et al., Ragert et al., 2004). Furthermore, the age of onset and amount of time spent learning a musical instrument is positively correlated with measures of grey matter volume in PMC, premotor area (PMA), the superior parietal lobe and left cerebellum (Amunts et al., 1997; Gaser & Schlaug, 2003; Grodd et al., 2001; Hutchinson, 2003). Herholtz and Zatorre (2012) suggest that co-activation of subcortical structures such as the basal ganglia, and limbic systems may account for associated pleasurable reward effects. As the area encompasses the fronto-tempero-parietal region, the overlap might result in a “hearing-doing or seeing-doing” network (Wan & Schlaug, 2010, p. 567).
Differences between musicians and non-musicians have also been observed using behavioural measures. At a basic level, the tapping rates of the index finger in both hands have been shown to be faster in musicians than non-musicians (Jänke, Schlaug &
Steinmetz, 1997). In adults, bi-manual tapping tasks which are similar to piano playing have revealed very different patterns of activation in professional musicians (piano players) and non-musicians (Jänke et al., 2001), which alongside other studies has led researchers to suggest that levels of automation contribute to efficiency in motor movement (Koeneke et al., 2004; Lang et al., 1990). Findings have also extended to the process of internal or ‘mental training’ in musicians whereby the PMC, supplementary motor area (SMA) and cerebellum were co-activated when musicians (in comparison to non-musicians) were asked to simply imagine playing their musical instrument during a functional magnetic resonance imaging experiment (Kuhtz-Buschbeck et al., 2003).
Functional changes associated with musicianship have been demonstrated using Diffuser Tension Imaging (DTI). Although evidence is currently mixed regarding levels of fractional anisotropy (FA) in the internal capsule14, there seems to be agreement regarding higher levels of FA in the CC and superior longitudinal fasciculus which correlates positively with the number of practice hours recorded in childhood (see e.g. Bengtsson et al., 2005; Imfield et al., 2009; Schmithorst & Wilke, 2002). Recently, between-group differences in diffusivity in the cortico-spinal tract suggest that practice- induced myelination contributes to changes in white matter tracts (Rüber, Lindenberg & Schlaug, 2013).
Positive effects associated with musical learning and motor movement have been exploited in neurological therapies such as Melodic Intonation Therapy (MIT) for aphasic stroke patients and Auditory-Motor Mapping Training (AMMT) for children with Autism Spectrum Disorder (Schlaug et al., 2015). Auditory-motor coupling has also been utilised therapeutically to help people with Parkinson’s disease15 manage their symptoms (Baumann et al., 2007; Grahn & Rowe, 2009; Thaut, McIntosh & Hoemberg, 2014).
In summary, it is clear that learning to play a musical instrument leads to structural and functional changes in the brain. These changes not only lead to instrument specific adaptations, but also to an effect of automaticity enabling efficiency (in turn promoting performance ability) and also increasing inhibition of inappropriate movements enabling independence of actions (thereby increasing technical function).
14 FA is thought to reflect fibre density, axonal diameter, and myelination in white matter (Basser,
Mattiello, & LeBihan, 1994). FA is used to measure of the microstructural status of white matter. Levels of diffusivity can be obtained as a reflection of fibre density. Where 0 density = isotropic, either unrestricted or equally restricted in all directions, a value of 1 = diffusion occurs only along one axis and is fully restricted along all other directions.
15 PD patients suffering cognitive, speech and communication as well as motor skill difficulties,
depression and memory dysfunction due to neural decay in the substantia nigra resulting in reduced dopamine production.
However, these studies are of adults, in the main (rather arbitrarily) comparing musicians and non-musicians. The effect seems to be associated with early learning, but what of children. How do these enhanced motor functions develop? The next section considers the evidence with regard to children in particular.