Early Musical Training Is Linked to Gray Matter Structure in the Ventral Premotor Cortex and Auditory–Motor Rhythm Synchronization Performance

Evidence in animals and humans indicates that there are sensitive periods during development, times when experience or stimulation has a greater influence on behavior and brain structure. Sensitive periods are the result of an interaction between maturational processes and experience-dependent plasticity mechanisms. Previous work from our laboratory has shown that adult musicians who begin training before the age of 7 show enhancements in behavior and white matter structure compared with those who begin later. Plastic changes in white matter and gray matter are hypothesized to co-occur; therefore, the current study investigated possible differences in gray matter structure between early-trained (ET; <7) and late-trained (LT; >7) musicians, matched for years of experience. Gray matter structure was assessed using voxel-wise analysis techniques (optimized voxel-based morphometry, traditional voxel-based morphometry, and deformation-based morphometry) and surface-based measures (cortical thickness, surface area and mean curvature). Deformation-based morphometry analyses identified group differences between ET and LT musicians in right ventral premotor cortex (vPMC), which correlated with performance on an auditory motor synchronization task and with age of onset of musical training. In addition, cortical surface area in vPMC was greater for ET musicians. These results are consistent with evidence that premotor cortex shows greatest maturational change between the ages of 6–9 years and that this region is important for integrating auditory and motor information. We propose that the auditory and motor interactions required by musical practice drive plasticity in vPMC and that this plasticity is greatest when maturation is near its peak.

[1]  Anatol C. Kreitzer,et al.  Plasticity in gray and white: neuroimaging changes in brain structure during learning , 2012, Nature Neuroscience.

[2]  Virginia B Penhune,et al.  Annals of the New York Academy of Sciences a Sensitive Period for Musical Training: Contributions of Age of Onset and Cognitive Abilities , 2022 .

[3]  J. Kleim,et al.  Synaptogenesis and FOS Expression in the Motor Cortex of the Adult Rat after Motor Skill Learning , 1996, The Journal of Neuroscience.

[4]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[5]  A. Geers.  Factors influencing spoken language outcomes in children following early cochlear implantation. , 2006, Advances in oto-rhino-laryngology.

[6]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[7]  J. Staiger,et al.  Increased corpus callosum size in musicians , 1995, Neuropsychologia.

[8]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[9]  Stefan Skare,et al.  See Blockindiscussions, Blockinstats, Blockinand Blockinauthor Blockinprofiles Blockinfor Blockinthis Blockinpublication Extensive Blockinpiano Blockinpracticing Blockinhas Blockinregionally Specific Blockineffects Blockinon Blockinwhite Blockinmatter Blockindevelopment , 2022 .

[10]  Stephen M. Smith,et al.  Evidence for abnormalities of cortical development in adolescent-onset schizophrenia , 2008, NeuroImage.

[11]  Antoni Rodríguez-Fornells,et al.  Structural neuroplasticity in expert pianists depends on the age of musical training onset , 2016, NeuroImage.

[12]  Anders M. Dale,et al.  Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data , 2006, NeuroImage.

[13]  T. Dumas,et al.  Rules of Engagement: Factors That Regulate Activity-Dependent Synaptic Plasticity During Neural Network Development , 2010, The Biological Bulletin.

[14]  Robert J Zatorre,et al.  The Role of Auditory and Premotor Cortex in Sensorimotor Transformations , 2009, Annals of the New York Academy of Sciences.

[15]  M. Scherg,et al.  Morphology of Heschl's gyrus reflects enhanced activation in the auditory cortex of musicians , 2002, Nature Neuroscience.

[16]  Robert J Zatorre,et al.  Expert music performance: cognitive, neural, and developmental bases. , 2015, Progress in brain research.

[17]  Robert V Harrison,et al.  Is there a critical period for cochlear implantation in congenitally deaf children? Analyses of hearing and speech perception performance after implantation. , 2005, Developmental psychobiology.

[18]  John O. Willis,et al.  Wechsler Adult Intelligence Scale–Third Edition , 2008 .

[19]  A. Geers,et al.  Will they catch up? The role of age at cochlear implantation in the spoken language development of children with severe to profound hearing loss. , 2007, Journal of speech, language, and hearing research : JSLHR.

[20]  Gottfried Schlaug,et al.  Musicians Differ from Nonmusicians in Brain Activation despite Performance Matching , 2003, Annals of the New York Academy of Sciences.

[21]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[22]  A. Toga,et al.  Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation , 2001, The Journal of Neuroscience.

[23]  M. Jenkinson.  Non-linear registration aka Spatial normalisation , 2007 .

[24]  P. Essens,et al.  Metrical and nonmetrical representations of temporal patterns , 1985, Perception & psychophysics.

[25]  S. Ogawa,et al.  Structural and functional plasticity specific to musical training with wind instruments , 2015, Front. Hum. Neurosci..

[26]  Lutz Jäncke,et al.  White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study , 2009, NeuroImage.

[27]  G. Yeni-Komshian,et al.  Age Constraints on Second-Language Acquisition , 1999 .

[28]  R. Zatorre,et al.  Moving on Time: Brain Network for Auditory-Motor Synchronization is Modulated by Rhythm Complexity and Musical Training , 2008, Journal of Cognitive Neuroscience.

[29]  R. Zatorre,et al.  Listening to musical rhythms recruits motor regions of the brain. , 2008, Cerebral cortex.

[30]  E. Saltzman,et al.  Action Representation of Sound: Audiomotor Recognition Network While Listening to Newly Acquired Actions , 2007, The Journal of Neuroscience.

[31]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[32]  G. Schlaug,et al.  Music Making as a Tool for Promoting Brain Plasticity across the Life Span , 2010, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[33]  B. Kolb,et al.  Contrasting effects of motor and visual spatial learning tasks on dendritic arborization and spine density in rats , 2008, Neurobiology of Learning and Memory.

[34]  Anders M. Dale,et al.  Improved Localization of Cortical Activity By Combining EEG and MEG with MRI Cortical Surface Reconstruction , 2002 .

[35]  Timothy Edward John Behrens,et al.  Training induces changes in white matter architecture , 2009, Nature Neuroscience.

[36]  Virginia B. Penhune,et al.  Rhythm synchronization performance and auditory working memory in early- and late-trained musicians , 2010, Experimental Brain Research.

[37]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[38]  Robert J. Zatorre,et al.  Repetition Suppression in Auditory–Motor Regions to Pitch and Temporal Structure in Music , 2013, Journal of Cognitive Neuroscience.

[39]  G. Schlaug,et al.  Brain structures differ between musicians and non-musician , 2001, NeuroImage.

[40]  Thomas R. Barrick,et al.  Voxel-Based Morphometry Reveals Increased Gray Matter Density in Broca's Area in Male Symphony Orchestra Musicians , 2002, NeuroImage.

[41]  Falisha J. Karpati,et al.  Sensorimotor integration is enhanced in dancers and musicians , 2016, Experimental Brain Research.

[42]  P. Essens,et al.  Structuring temporal sequences: Comparison of models and factors of complexity , 1995, Perception & psychophysics.

[43]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[44]  A. Dale,et al.  Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.

[45]  L. Trainor.  Are there critical periods for musical development? , 2005, Developmental psychobiology.

[46]  Patricia A. Reuter-Lorenz,et al.  Examining the relationship between skilled music training and attention , 2015, Consciousness and Cognition.

[47]  Paul M. Thompson,et al.  Brain structure changes visualized in early- and late-onset blind subjects , 2010, NeuroImage.

[48]  Niels Birbaumer,et al.  Evidence for Enhanced Interoceptive Accuracy in Professional Musicians , 2015, Front. Behav. Neurosci..

[49]  R. Schaefer,et al.  Can Musical Training Influence Brain Connectivity? Evidence from Diffusion Tensor MRI , 2014, Brain sciences.

[50]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[51]  R. Oostenveld,et al.  Increased auditory cortical representation in musicians , 1998, Nature.

[52]  P. Kuhl.  Brain Mechanisms in Early Language Acquisition , 2010, Neuron.

[53]  J. Tanji,et al.  Distinctions between dorsal and ventral premotor areas: anatomical connectivity and functional properties , 2007, Current Opinion in Neurobiology.

[54]  Eve C. Johnstone,et al.  Grey matter networks in people at increased familial risk for schizophrenia , 2015, Schizophrenia Research.

[55]  Allan L. Reiss,et al.  To modulate or not to modulate: Differing results in uniquely shaped Williams syndrome brains , 2006, NeuroImage.

[56]  Bruce Fischl,et al.  Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops , 2007, IEEE Transactions on Medical Imaging.

[57]  Tal Savion-Lemieux,et al.  The effect of early musical training on adult motor performance: evidence for a sensitive period in motor learning , 2006, Experimental Brain Research.

[58]  Alan C. Evans,et al.  A Unified Statistical Approach to Deformation-Based Morphometry , 2001, NeuroImage.

[59]  Karl J. Friston,et al.  Voxel-Based Morphometry , 2015 .

[60]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[61]  H. Neville,et al.  Sensitive periods differentiate processing of open- and closed-class words: an ERP study of bilinguals. , 2001, Journal of speech, language, and hearing research : JSLHR.

[62]  B. Barres,et al.  The complement system: an unexpected role in synaptic pruning during development and disease. , 2012, Annual review of neuroscience.

[63]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[64]  Alan C. Evans,et al.  Musical Training Shapes Structural Brain Development , 2009, The Journal of Neuroscience.

[65]  Alexander Leemans,et al.  Microstructural maturation of the human brain from childhood to adulthood , 2008, NeuroImage.

[66]  E. Knudsen.  Sensitive Periods in the Development of the Brain and Behavior , 2004, Journal of Cognitive Neuroscience.

[67]  Virginia B. Penhune,et al.  Sensitive periods in human development: Evidence from musical training , 2011, Cortex.

[68]  Laura M Parkes,et al.  Increased gray matter volume of left pars opercularis in male orchestral musicians correlate positively with years of musical performance , 2011, Journal of magnetic resonance imaging : JMRI.

[69]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[70]  A. May.  Experience-dependent structural plasticity in the adult human brain , 2011, Trends in Cognitive Sciences.

[71]  Lutz Jäncke,et al.  The plastic human brain. , 2009, Restorative neurology and neuroscience.

[72]  Alan C. Evans,et al.  Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry. , 2009, Cerebral cortex.

[73]  A. M. Dale,et al.  A hybrid approach to the skull stripping problem in MRI , 2004, NeuroImage.

[74]  Kate E. Watkins,et al.  Learning to play a melody: An fMRI study examining the formation of auditory-motor associations , 2012, NeuroImage.

[75]  Bryan M. Hooks,et al.  Critical Periods in the Visual System: Changing Views for a Model of Experience-Dependent Plasticity , 2007, Neuron.

[76]  W. Greenough,et al.  Plasticity of nonneuronal brain tissue: roles in developmental disorders. , 2004, Mental retardation and developmental disabilities research reviews.

[77]  Michael M Merzenich,et al.  Lifelong plasticity in the rat auditory cortex: basic mechanisms and role of sensory experience. , 2011, Progress in brain research.

[78]  Anders M. Dale,et al.  Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer , 2006, NeuroImage.

[79]  Nicole M. Russo,et al.  Musical experience shapes human brainstem encoding of linguistic pitch patterns , 2007, Nature Neuroscience.

[80]  Tyler K. Perrachione,et al.  Enhanced cognitive and perceptual processing: a computational basis for the musician advantage in speech learning , 2015, Front. Psychol..

[81]  R. Zatorre,et al.  Early Musical Training and White-Matter Plasticity in the Corpus Callosum: Evidence for a Sensitive Period , 2013, The Journal of Neuroscience.

[82]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[83]  Brigitte Landeau,et al.  The effects of musical practice on structural plasticity: The dynamics of grey matter changes , 2014, Brain and Cognition.

[84]  A. Schleicher,et al.  Motor cortex and hand motor skills: Structural compliance in the human brain , 1997, Human brain mapping.

[85]  Thomas F. Nugent,et al.  Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[86]  E. Kirino,et al.  A Voxel-Based Morphometry Study of the Brain of University Students Majoring in Music and Nonmusic Disciplines , 2015, Behavioural neurology.

[87]  Tomáš Paus,et al.  Growth of white matter in the adolescent brain: Myelin or axon? , 2010, Brain and Cognition.

[88]  B. Rockstroh,et al.  Increased Cortical Representation of the Fingers of the Left Hand in String Players , 1995, Science.

[89]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[90]  John O. Willis,et al.  Wechsler Abbreviated Scale of Intelligence , 2014 .

[91]  R. Zatorre,et al.  When the brain plays music: auditory–motor interactions in music perception and production , 2007, Nature Reviews Neuroscience.

[92]  Paul M. Thompson,et al.  Mapping Gray Matter Development: Implications for Typical Development and Vulnerability to Psychopathology , 2022 .

[93]  Robert J. Zatorre,et al.  Cortical structure predicts success in performing musical transformation judgments , 2010, NeuroImage.