The “silent” imprint of musical training

Playing a musical instrument at a professional level is a complex multimodal task requiring information integration between different brain regions supporting auditory, somatosensory, motor, and cognitive functions. These kinds of task‐specific activations are known to have a profound influence on both the functional and structural architecture of the human brain. However, until now, it is widely unknown whether this specific imprint of musical practice can still be detected during rest when no musical instrument is used. Therefore, we applied high‐density electroencephalography and evaluated whole‐brain functional connectivity as well as small‐world topologies (i.e., node degree) during resting state in a sample of 15 professional musicians and 15 nonmusicians. As expected, musicians demonstrate increased intra‐ and interhemispheric functional connectivity between those brain regions that are typically involved in music perception and production, such as the auditory, the sensorimotor, and prefrontal cortex as well as Broca's area. In addition, mean connectivity within this specific network was positively related to musical skill and the total number of training hours. Thus, we conclude that musical training distinctively shapes intrinsic functional network characteristics in such a manner that its signature can still be detected during a task‐free condition. Hum Brain Mapp 37:536–546, 2016. © 2015 Wiley Periodicals, Inc.

[1]  Armin Thron,et al.  Cortical activation patterns during complex motor tasks in piano players and control subjects. A functional magnetic resonance imaging study , 2000, Neuroscience Letters.

[2]  Roberto D. Pascual-Marqui,et al.  Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: frequency decomposition , 2007, 0711.1455.

[3]  S. Koelsch.  Brain correlates of music-evoked emotions , 2014, Nature Reviews Neuroscience.

[4]  Lutz Jäncke,et al.  Increased cortical surface area of the left planum temporale in musicians facilitates the categorization of phonetic and temporal speech sounds , 2013, Cortex.

[5]  Karl J. Friston,et al.  Early visual learning induces long-lasting connectivity changes during rest in the human brain , 2013, NeuroImage.

[6]  M. Tervaniemi,et al.  Sound processing in amateur musicians and nonmusicians: event-related potential and behavioral indices , 2006, Neuroreport.

[7]  Edward T. Bullmore,et al.  Network-based statistic: Identifying differences in brain networks , 2010, NeuroImage.

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

[9]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[10]  Derek K. Jones,et al.  Perisylvian language networks of the human brain , 2005, Annals of neurology.

[11]  M. Rugg,et al.  Brain activity before an event predicts later recollection , 2006, Nature Neuroscience.

[12]  David C. Alsop,et al.  Differentiating maturational and training influences on fMRI activation during music processing , 2012, NeuroImage.

[13]  Justine Sergent,et al.  The brain basis of piano performance , 2005, Neuropsychologia.

[14]  S. Koelsch,et al.  Neural correlates of strategy use during auditory working memory in musicians and non‐musicians , 2011, The European journal of neuroscience.

[15]  William J. Tays,et al.  Inhibitory Control in Bilinguals and Musicians: Event Related Potential (ERP) Evidence for Experience-Specific Effects , 2014, PloS one.

[16]  Tae Young Lee,et al.  Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis , 2013, Front. Hum. Neurosci..

[17]  Andreas Kleinschmidt,et al.  EEG Alpha Power Modulation of fMRI Resting-State Connectivity , 2012, Brain Connect..

[18]  L. Jäncke,et al.  A strong parietal hub in the small-world network of coloured-hearing synaesthetes during resting state EEG. , 2011, Journal of neuropsychology.

[19]  A. Friederici,et al.  Investigating emotion with music: An fMRI study , 2006, Human brain mapping.

[20]  T. Milner,et al.  Functionally Specific Changes in Resting-State Sensorimotor Networks after Motor Learning , 2011, The Journal of Neuroscience.

[21]  D. Schön,et al.  The music of speech: music training facilitates pitch processing in both music and language. , 2004, Psychophysiology.

[22]  Lutz Jäncke,et al.  Diminished Whole-brain but Enhanced Peri-sylvian Connectivity in Absolute Pitch Musicians , 2012, Journal of Cognitive Neuroscience.

[23]  M Lotze,et al.  The musician's brain: functional imaging of amateurs and professionals during performance and imagery , 2003, NeuroImage.

[24]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

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

[26]  M. Corbetta,et al.  The Dynamical Balance of the Brain at Rest , 2011, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[27]  A. Friederici,et al.  Hierarchical functional connectivity between the core language system and the working memory system , 2013, Cortex.

[28]  J. Wolpaw,et al.  EMG contamination of EEG: spectral and topographical characteristics , 2003, Clinical Neurophysiology.

[29]  L. Jäncke,et al.  The effects of working memory training on functional brain network efficiency , 2013, Cortex.

[30]  W M Herrmann,et al.  Reflections on the topics: EEG frequency bands and regulation of vigilance. , 1979, Pharmakopsychiatrie, Neuro-Psychopharmakologie.

[31]  L. Jäncke,et al.  Bridging the Gap between Perceptual and Cognitive Perspectives on Absolute Pitch , 2015, The Journal of Neuroscience.

[32]  Lorena R. R. Gianotti,et al.  Functional brain network efficiency predicts intelligence , 2012, Human brain mapping.

[33]  R. Zatorre,et al.  Spectral and temporal processing in human auditory cortex. , 2001, Cerebral cortex.

[34]  G. Schlaug,et al.  Brain Structures Differ between Musicians and Non-Musicians , 2003, The Journal of Neuroscience.

[35]  Andreas Kleinschmidt,et al.  Functional interactions between intrinsic brain activity and behavior , 2013, NeuroImage.

[36]  M. Tervaniemi,et al.  Pitch discrimination accuracy in musicians vs nonmusicians: an event-related potential and behavioral study , 2005, Experimental Brain Research.

[37]  Daniel S. Margulies,et al.  Long-term effects of motor training on resting-state networks and underlying brain structure , 2011, NeuroImage.

[38]  Eckart Altenmüller,et al.  Chills As an Indicator of Individual Emotional Peaks , 2009, Annals of the New York Academy of Sciences.

[39]  Lutz Jäncke,et al.  Enhancement of Auditory-evoked Potentials in Musicians Reflects an Influence of Expertise but not Selective Attention , 2008, Journal of Cognitive Neuroscience.

[40]  Annemarie Seither-Preisler,et al.  Size and Synchronization of Auditory Cortex Promotes Musical, Literacy, and Attentional Skills in Children , 2014, The Journal of Neuroscience.

[41]  T. Griffiths,et al.  The planum temporale as a computational hub , 2002, Trends in Neurosciences.

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

[43]  M. Besson,et al.  Transfer of Training between Music and Speech: Common Processing, Attention, and Memory , 2011, Front. Psychology.

[44]  N. Gaab,et al.  Behavioral and Neural Correlates of Executive Functioning in Musicians and Non-Musicians , 2014, PloS one.

[45]  M. Annett.  A classification of hand preference by association analysis. , 1970, British journal of psychology.

[46]  Guillaume Thierry,et al.  Hemispheric Dissociation in Access to the Human Semantic System , 2003, Neuron.

[47]  E. Altenmüller,et al.  The musician's brain as a model of neuroplasticity , 2002, Nature Reviews Neuroscience.

[48]  W. Klimesch,et al.  EEG alpha oscillations: The inhibition–timing hypothesis , 2007, Brain Research Reviews.

[49]  Lutz Jäncke,et al.  Neurofunctional and behavioral correlates of phonetic and temporal categorization in musically trained and untrained subjects. , 2012, Cerebral cortex.

[50]  G. Schlaug,et al.  Training‐induced Neuroplasticity in Young Children , 2009, Annals of the New York Academy of Sciences.

[51]  K. Brodmann.  Vergleichende Lokalisationslehre der Großhirnrinde : in ihren Prinzipien dargestellt auf Grund des Zellenbaues , 1985 .

[52]  E. Schellenberg,et al.  Short-Term Music Training Enhances Verbal Intelligence and Executive Function , 2011, Psychological science.

[53]  J. Cohen,et al.  Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. , 2000, Science.

[54]  Alan C. Evans,et al.  Emotional responses to pleasant and unpleasant music correlate with activity in paralimbic brain regions , 1999, Nature Neuroscience.

[55]  Psyche Loui,et al.  Effects of Practice and Experience on the Arcuate Fasciculus: Comparing Singers, Instrumentalists, and Non-Musicians , 2011, Front. Psychology.

[56]  Sibylle C. Herholz,et al.  Auditory‐Somatosensory Integration and Cortical Plasticity in Musical Training , 2009, Annals of the New York Academy of Sciences.

[57]  O. Sporns,et al.  Identification and Classification of Hubs in Brain Networks , 2007, PloS one.

[58]  S. Micheloyannis,et al.  Cortical Network Analysis in Patients Affected by Schizophrenia , 2010, Brain Topography.

[59]  M. Bangert,et al.  Specialization of the specialized in features of external human brain morphology , 2006, The European journal of neuroscience.

[60]  M. Himmelbach,et al.  A parametric analysis of the `rate effect' in the sensorimotor cortex: a functional magnetic resonance imaging analysis in human subjects , 1998, Neuroscience Letters.

[61]  David Poeppel,et al.  The analysis of speech in different temporal integration windows: cerebral lateralization as 'asymmetric sampling in time' , 2003, Speech Commun..

[62]  Christian Keysers,et al.  Inter‐individual differences in audio‐motor learning of piano melodies and white matter fiber tract architecture , 2014, Human brain mapping.

[63]  Brigitte Landeau,et al.  Morphological brain plasticity induced by musical expertise is accompanied by modulation of functional connectivity at rest , 2014, NeuroImage.

[64]  H. Waldmann.  Kurzformen des HAWIK-IV: Statistische Bewertung in verschiedenen Anwendungsszenarien , 2008 .

[65]  L. Jäncke,et al.  Interhemispheric transcallosal connectivity between the left and right planum temporale predicts musicianship, performance in temporal speech processing, and functional specialization , 2014, Brain Structure and Function.

[66]  Y. Benjamini,et al.  Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics , 1999 .

[67]  伊澤 幸洋,et al.  Wechsler adult intelligence scale, 3rd edition (WAIS-3) : usefulness in the early detection of Alzheimer's disease , 2009 .

[68]  K. Amunts,et al.  Broca's region subserves imagery of motion: A combined cytoarchitectonic and fMRI study , 2000, Human brain mapping.

[69]  W. Klimesch.  EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.

[70]  L. M. Ward,et al.  Synchronous neural oscillations and cognitive processes , 2003, Trends in Cognitive Sciences.

[71]  T. Ohnishi,et al.  Functional anatomy of musical perception in musicians , 2001, NeuroImage.

[72]  Lutz Jäncke,et al.  Auditory Evoked Responses in Musicians during Passive Vowel Listening Are Modulated by Functional Connectivity between Bilateral Auditory-related Brain Regions , 2014, Journal of Cognitive Neuroscience.

[73]  T. Prescott,et al.  The brainstem reticular formation is a small-world, not scale-free, network , 2006, Proceedings of the Royal Society B: Biological Sciences.

[74]  Karl J. Friston.  Functional and Effective Connectivity: A Review , 2011, Brain Connect..

[75]  L. Jäncke.  The dynamic audio–motor system in pianists , 2012, Annals of the New York Academy of Sciences.

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

[77]  Nancy Kanwisher,et al.  Language-Selective and Domain-General Regions Lie Side by Side within Broca’s Area , 2012, Current Biology.

[78]  M. Matousek,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA) in the prediction of response to cholinesterase inhibitors in patients with Alzheimer's disease , 2008 .

[79]  J Sergent,et al.  Distributed neural network underlying musical sight-reading and keyboard performance. , 1992, Science.

[80]  M. Catani,et al.  The arcuate fasciculus and the disconnection theme in language and aphasia: History and current state , 2008, Cortex.

[81]  Donna Coch,et al.  Music training and working memory: An ERP study , 2011, Neuropsychologia.

[82]  B. Ross,et al.  COGNITIVE NEUROSCIENCE AND NEUROPSYCHOLOGY: Timbre-specific enhancement of auditory cortical representations in musicians , 2022 .

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

[84]  Eckart Altenmüller,et al.  How Does Music Arouse “Chills”? , 2005, Annals of the New York Academy of Sciences.

[85]  A. Friederici,et al.  Musical syntax is processed in Broca's area: an MEG study , 2001, Nature Neuroscience.

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

[87]  A. Schleicher,et al.  Broca's region revisited: Cytoarchitecture and intersubject variability , 1999, The Journal of comparative neurology.

[88]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.

[89]  T. Sejnowski,et al.  Removing electroencephalographic artifacts by blind source separation. , 2000, Psychophysiology.

[90]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[91]  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.

[92]  Wei Liao,et al.  Musical Training Induces Functional Plasticity in Perceptual and Motor Networks: Insights from Resting-State fMRI , 2012, PloS one.

[93]  Yong He,et al.  BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics , 2013, PloS one.

[94]  Neil Roberts,et al.  Structural, Functional, and Perceptual Differences in Heschl's Gyrus and Musical Instrument Preference , 2005, Annals of the New York Academy of Sciences.

[95]  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.

[96]  Tim Curran,et al.  Using single-trial EEG to predict and analyze subsequent memory , 2014, NeuroImage.

[97]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[98]  J. Brooks,et al.  Broca's Area Supports Enhanced Visuospatial Cognition in Orchestral Musicians , 2007, The Journal of Neuroscience.

[99]  M. Greicius,et al.  Resting-state functional connectivity reflects structural connectivity in the default mode network. , 2009, Cerebral cortex.

[100]  S. Koelsch,et al.  Working memory for speech and music , 2012, Annals of the New York Academy of Sciences.

[101]  K. Davis,et al.  Cognitive and default‐mode resting state networks: Do male and female brains “rest” differently? , 2010, Human brain mapping.