Elsevier

NeuroImage

Volume 46, Issue 3, 1 July 2009, Pages 600-607
NeuroImage

White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study

https://doi.org/10.1016/j.neuroimage.2009.02.025Get rights and content

Abstract

With the advent of diffusion tensor imaging (DTI), the study of plastic changes in white matter architecture due to long-term practice has attracted increasing interest. Professional musicians provide an ideal model for investigating white matter plasticity because of their early onset of extensive auditory and sensorimotor training. We performed fiber tractography and subsequent voxelwise analysis, region of interest (ROI) analysis, and detailed slicewise analysis of diffusion parameters in the corticospinal tract (CST) on 26 professional musicians and a control group of 13 participants. All analyses resulted in significantly lower fractional anisotropy (FA) values in both the left and the right CST in the musician group. Furthermore, a right-greater-than-left asymmetry of FA was observed regardless of group. In the musician group, diffusivity was negatively correlated with the onset of musical training in childhood. A subsequent median split into an early and a late onset musician group (median = 7 years) revealed increased diffusivity in the CST of the early onset group as compared to both the late onset group and the controls. In conclusion, these DTI-based findings might indicate plastic changes in white matter architecture of the CST in professional musicians. Our results imply that training-induced changes in diffusion characteristics of the axonal membrane may lead to increased radial diffusivity as reflected in decreased FA values.

Introduction

Performing music at a professional level is arguably one of the most demanding of human activities on sensorimotor coordination. Accomplished and famous musicians usually began with musical training in early childhood, practicing several hours a day. Professional musicians represent therefore an ideal model for the study of training-induced plastic changes in the human brain (Münte et al., 2002, Schlaug, 2001).

Advances in neuroimaging technology and methods have underpinned extensive study of musicians over the past decade (Peretz and Zatorre, 2005). On the one hand, coarse anatomical plastic changes have been observed using in vivo magnetic resonance morphometry and voxel-based morphometry (VBM) (Gaser and Schlaug, 2003, Schlaug et al., 1995a). On the other hand, methods such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) (e.g. Baumann et al., 2008, Ohnishi et al., 2001, Pantev et al., 1998) have been employed to study functional plasticity.

There is evidence of structural differences in gray matter between musicians and non-musicians in a number of regions in the brain, including the planum temporale (Keenan et al., 2001, Schlaug et al., 1995b), Heschl's gyrus (Schneider et al., 2005), the anterior corpus callosum (Schlaug et al., 1995a), the primary hand motor area and the cerebellum (Gaser and Schlaug, 2003), and Broca's area (Sluming et al., 2002). Interestingly, structural differences in the primary motor cortex between keyboard and string instrument players have been reported (Schlaug et al., 2005). The majority of the keyboard players had an elaborated configuration of the precentral gyrus on both sides, whereas most of the adult string players demonstrated this atypicality only in the right hemisphere. This finding may reflect the stronger sensorimotor demand for the left hand and the right motor cortex in string players and lends support to the hypothesis of training-induced anatomical plasticity. In general, structural differences seem to be more pronounced in musicians who began learning at a younger age (Elbert et al., 1995, Schlaug et al., 1995a) and practiced with greater intensity (Gaser and Schlaug, 2003, Hutchinson et al., 2003, Schneider et al., 2005).

Studies of functional plasticity using MEG have shown modified somatosensory representations of the fingering digits in violinists (Elbert et al., 1995) and enhanced evoked magnetic fields in the auditory cortex in musicians while listening to piano, but not pure tones (Pantev et al., 1998). fMRI studies revealed differences in activations during motor tasks between piano players and control subjects in the primary, premotor, and supplementary motor cortex (Hund-Georgiadis and von Cramon, 1999, Jancke et al., 2000, Krings et al., 2000, Meister et al., 2005). Two of these studies found reduced primary motor cortical activations in musicians, this being explained in terms of more efficient wiring and less activated neurons (Jancke et al., 2000, Krings et al., 2000). Bangert and Altenmüller (2003) conducted a longitudinal EEG study on piano learning and observed changes in cortical activation patterns after only 20 min of performing auditory and motor tasks. The effect was enhanced after five weeks of practice, contributing elements of both perception and action to the mental representation of the instrument. Thus, they concluded that musical training triggers instant plasticity in the cortex.

DTI is a method for studying white matter anatomy of the human or animal brain and has attracted increasing attention over the past decade. While the focus of mainstream imaging-based neuropsychological research continues to be on function and anatomy of gray matter using for example fMRI or VBM, the in vivo neuroimaging technique of DTI offers a complementary way of studying the brain by directing interest towards white matter and axonal connectivity.

DTI is based on magnetic resonance (MR) technology and provides measures of water diffusion in different spatial directions in the brain. The most commonly studied diffusion parameter is fractional anisotropy (FA), which quantifies the directionality of diffusion within a voxel between 0 (undirected, isotropic) and 1 (directed, anisotropic) and is derived from the diffusion tensor (Mori and Zhang, 2006). Since white matter in the brain consists of aligned axonal fibers, diffusion is constrained perpendicular to the orientation of these fiber bundles, which leads to anisotropic diffusion. The principal direction of diffusion reflects the orientation of a fiber bundle in a specific voxel and is therefore exploited by fiber tracking algorithms.

Diffusivity (trace) is a measure for the amount of diffusion, which can be divided into an axial diffusivity component (λ||, diffusion along the axons) and a radial diffusivity component (λ, diffusion perpendicular to the axons). While λ|| corresponds to the first eigenvalue of the diffusion tensor (λ|| = λ1), λ is calculated by averaging the second and third eigenvalue: λ = (λ2 + λ3)/2 (Alexander et al., 2007). While diffusivity indicates the amount of diffusion, FA reflects the directionality of diffusion and is based on the relation between λ|| and λ.

FA has been found to increase during white matter maturation in the developing brain (Beaulieu, 2002, Cascio et al., 2007, Eluvathingal et al., 2007) and to decrease during normal aging (Bhagat and Beaulieu, 2004, Moseley, 2002). Reduced FA values have been reported in patients suffering from neurodegenerative diseases (Sundgren et al., 2004) or spinal chord injury (Wrigley et al., 2008). Potential clinical applications of DTI have been long suggested, the most successful application since the early 1990s being in brain ischemia as a consequence of the discovery that water diffusion drops at a very early stage of the ischemic event (Alexander et al., 2007, Bihan et al., 2001).

There is an increasing body of evidence emerging from DTI studies indicating learning-related structural plasticity in white matter. FA has been found to be positively correlated with behavioural measures such as reading ability (Beaulieu et al., 2005, Klingberg et al., 2000, Niogi and McCandliss, 2006), performance in a speeded lexical decision task (Gold et al., 2007), and musical sensorimotor practice (Bengtsson et al., 2005). However, the relations between white matter development, degeneration, and training-induced plastic changes on the one hand and water diffusion characteristics on the other hand still remain poorly understood and a matter of controversy (Alexander et al., 2007, Ashtari et al., 2007, Beaulieu, 2002). Nevertheless, FA is thought to be positively correlated with the thickness of the axon-surrounding myelin sheaths. It is therefore often broadly interpreted as an indicator of the quality of white matter fiber tracts or “white matter integrity” (Alexander et al., 2007) because of its increase during white matter maturation, decrease in neurodegenerative diseases, and its positive correlation with various performance measures.

Investigations of the association between musical expertise in general and white matter architecture are few in number. In a DTI study that compared 5 musicians with 6 non-musicians, Schmithorst and Wilke (2002) reported lower FA in musicians' left and right internal capsules and higher FA for example in the genu of the corpus callosum.

(Bengtsson et al. (2005)) conducted a DTI study with 8 pianists and 8 age-matched non-musicians. They reported clusters of positive correlations between estimated practice hours during childhood and FA in a variety of regions including the body and splenium of the corpus callosum, the posterior limb of the internal capsule (which contains fibers of the CST) bilaterally, and the right superior longitudinal fasciculus (SLF). In disagreement with Schmithorst and Wilke, 2002, Bengtsson et al., 2005 reported higher FA in the posterior limb of the right internal capsule in the pianist group. As a possible underlying physiological mechanism for learning-related white matter plasticity, Bengtsson et al. (2005) mentioned that myelination can be stimulated by electrical activity in premyelinated axons in mice (Demerens et al., 1996). Thicker myelin sheaths are supposed to constrain extracellular space, thus leading to higher degrees of FA (Vorísek and Syková, 1997).

The CST is known to convey sensorimotor information and professional musicians are highly trained in sensorimotor coordination from very early on. Therefore, white matter plasticity due to musical training is likely to be reflected in changes of microstructure in this fiber tract (Bengtsson et al., 2005, Schmithorst and Wilke, 2002). By focusing on the CST in professional musicians, the present study attempts to shed more light upon plastic changes in white matter associated with sensorimotor long-term practice. In order to address the unresolved question of whether sensorimotor training leads to increased (Bengtsson et al., 2005) or decreased (Schmithorst and Wilke, 2002) FA values in the CST of musicians, we tested a larger number of subjects and applied three different methods of analysis.

Section snippets

Subjects

A total of 39 subjects participated in this study: 13 professional musicians with absolute pitch, 13 professional musicians without absolute pitch, and 13 non-musicians as control subjects. Since absolute pitch seemed to have no influence on diffusion parameters in the CST, the two musicians groups were collapsed into one group of 26 musicians (16 females, 10 males, mean age = 24.6 ± 2.9 std.) and compared with the 13 age-matched healthy control subjects (7 females, 6 males, mean age = 25.6 ± 5.3). All

Group differences and lateralization

According to our prior expectations, group differences were found in the CST. ROI analysis revealed significantly lower mean FA values in both the left CST (P = 0.019, Cohen's d = 0.83) and the right CST (P = 0.001, Cohen's d = 1.25) of musicians as compared to the control group (Fig. 3, A). Furthermore, there was a significant right-greater-than-left asymmetry of FA in both groups (musicians: P = 0.001, Cohen's d = 0.55; controls: P = 0.003, Cohen's d = 0.93) which is shown in Fig. 3, B. Other fiber

Sensorimotor training effects

While ROI analysis revealed no group differences in FA in the SLF, CC, UNC, IFO, and the ILF, professional musicians exhibited lower FA values in the CST than controls. Statistical effects were moderate (left CST) to strong (right CST) and both voxelwise and slicewise analysis reflected this finding, indicating significant group differences over large parts of the CST. Since the ROIs covered large parts of these fiber structures, ROI analysis was conservative and putative effects of smaller

Acknowledgments

We are indebted to Nicki Langer for assisting in MR data acquisition. Funding was provided by Schweizerischer National Fonds (Swiss National Foundation) [SNF 46234101 to L.J. and M.O., SNF 320000-120661/1 to M.M.] and Research funding University of Zurich [56234101 to M.O.].

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    Adrian Imfeld and Mathias Oechslin equally contributed to this manuscript.

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