Music making as a tool for promoting brain plasticity across the life span

Abstract

Playing a musical instrument is an intense, multisensory, and motor experience that usually commences at an early age and requires the acquisition and maintenance of a range of skills over the course of a musician's lifetime. Thus, musicians offer an excellent human model for studying the brain effects of acquiring specialized sensorimotor skills. For example, musicians learn and repeatedly practice the association of motor actions with specific sound and visual patterns (musical notation) while receiving continuous multisensory feedback. This association learning can strengthen connections between auditory and motor regions (e.g., arcuate fasciculus) while activating multimodal integration regions (e.g., around the intraparietal sulcus). We argue that training of this neural network may produce cross-modal effects on other behavioral or cognitive operations that draw on this network. Plasticity in this network may explain some of the sensorimotor and cognitive enhancements that have been associated with music training. These enhancements suggest the potential for music making as an interactive treatment or intervention for neurological and developmental disorders, as well as those associated with normal aging.

Figure 1

Morphing a violin into a brain or a brain into a violin. Within the nature-nurture hypotheses, it is unclear in which direction the morphing goes. Does early and long-time music training lead to brain changes (nurture hypothesis), or are expert musicians born with an unusual brain (nature hypothesis) that allows them to excel at a task that requires highly specialized skills? Alternatively, do highly skilled and talented musicians have an inherent advantage by starting out with a brain anatomy that is ideal for acquiring skills that are necessary to master a musical instrument, even though the intense training changes their brains as it does for everybody else who undergoes long-term skills acquisition (nature and nurture hypothesis)? The individual brain in the upper left corner is colorized to show results of a study by Gaser and Schlaug (2003), revealing brain regions that show a positive correlation between musician status (professional musician > amateur musician > nonmusician) and increased gray matter volume. The distinction between professional and amateur musicians in this study was based on whether the keyboard player's main profession was being a musician (e.g., music teacher, performer). There was also a clear separation between both groups in terms of average practice intensity across their careers, with professional keyboard players having approximately double the amount of practice time than the group of amateur musicians (for more details, see Gaser and Schlaug 2003).

Figure 2

Corpus callosum differences in adults (musicians v. nonmusicians) and changes over time in children. The midsagittal slice of an adult musician (A) and nonmusician (B) shows a difference in the size of the anterior and midbody of the corpus callosum (see Schlaug and others 1995a). (C) The major subdivisions of the corpus callosum and locations of the interhemispheric fibers connecting the motor hand regions on the right and left hemisphere through the corpus callosum according to a scheme used by Hofer and Frahm (2006). Reprinted with permission from Elsevier. (D) Areas of significant difference in relative voxel size over 15 months comparing instrumental (n = 15) versus noninstrumental control children (n = 16) superimposed on an average image of all children (see also Hyde and others 2009). Interestingly, most changes over time were found in the midbody portion of the corpus callosum, representing parts of the corpus callosum that contain primary sensorimotor and premotor fibers.

Figure 3

Brain surface renderings of a typical keyboard and string player. The central sulcus is marked with a white line. The portion of the precentral gyrus containing the configuration similar to that of the inverted Greek letter “omega” is found within the red circles. In the 2 examples, a prominent omega sign can be seen on the left more than the right in the keyboard player and only on the right in the string player. In Bangert and Schlaug (2006), we reported significantly more prominent omega signs in the right hemisphere of string players compared to the right hemisphere of nonmusicians and more prominent omega signs in the left hemisphere of keyboard players compared to the left hemispheres of both nonmusicians and string players. Reproduced from Bangert and Schlaug 2006, with permission of Oxford University Press.

Figure 4

Changes in the arcuate fasciculus after instrumental music training. The top row shows the right (green and red fibers represent the ventral and dorsal components of the arcuate fasciculus) and left (yellow and pink fibers represent the ventral and dorsal components of the arcuate fasciculus) arcuate fasciculus of an 8-year-old child without instrumental music training scanned twice (A and B) 2 years apart. Bottom row shows the right and left arcuate fasciculus of an 8-year-old child before (C) and 2 years after (D) instrumental music training involving a string instrument.

Figure 5

Cerebral activation pattern of a rhythm discrimination task modulated by maturity and experience. Statistical parametric images superimposed onto a surface rendering of a standardized anatomical brain depict significant activations during a rhythmic discrimination task in a group of 5- to 7-year-old musically naïve children, adult nonmusicians, and adult musicians. The children showed prominent superior temporal gyrus activation on both sides. The adult groups show an extended pattern of activation involving polar and posterior planar regions of the superior temporal lobe as well as the parietal lobe (green circles), parts of the frontal lobe, in particular, the inferior frontal gyrus region (blue circles), and the cerebellum. Adult musicians differ from adult nonmusicians by having less activation of the primary auditory cortex but more activation of frontal regions bilaterally, particularly in the inferior frontal gyrus (blue circles). Reproduced from Bangert and Schlaug 2006, with permission of Oxford University Press.

Figure 6

The arcuate fasciculus, an auditory-motor tract, enhanced by music training. (A) The arcuate fasciculus of a healthy 65-year-old instrumental musician and (B) the arcuate fasciculus of a healthy 63-year-old nonmusician, otherwise matched with regard to their handedness, gender, and overall IQ. A comparison between both individuals shows that the musician has a larger arcuate fasciculus on the left as well as the right hemisphere than the nonmusician. Ongoing studies in our laboratory and other laboratories have shown evidence for structural plasticity of the arcuate fasciculus (Schlaug and others 2009) in individuals who undergo instrumental training or therapy using tasks that involve auditory-motor mapping, a task that musicians do throughout their life.

Figure 7

Shared brain resources of a music-motor imagery task and a mental calculation task. The functional magnetic resonance image on the left (A) shows significant activations of an fMRI experiment in which subjects were asked to imagine playing scales and short music phrases with their right hand compared to a visual imagery task of 4 objects. Contrasting motor imagery (MI) with visual imagery (VI) showed bilateral activations in the superior parietal lobe as well as around the intraparietal sulcus (IPS), medial superior precuneus region, premotor region, and the supplementary motor area (SMA). Significant activations are superimposed onto a standardized brain. The functional magnetic resonance images on the right (B) show the activation pattern of a mental subtraction task in which the subtraction task was contrasted with a letter-naming task (Chochon and others 1999). It is interesting to see the similarity in the activation pattern, in particular with regard to the parietal lobe activation. Reprinted from Chochon and others 1999, with permission of MIT Press Journals.