Login | Register

White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians

Title:

White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians

Penhune, Virginia, Vaquero, Lucía, Ramos-Escobar, Neus, François, Clément and Rodríguez-Fornells, Antoni (2018) White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians. NeuroImage . ISSN 10538119 (In Press)

[img]
Text (application/pdf)
Penhune 2018.pdf - Accepted Version
Restricted to Repository staff only until 19 June 2019.
Available under License Spectrum Terms of Access.
1MB

Official URL: http://dx.doi.org/10.1016/j.neuroimage.2018.06.054

Abstract

Music learning has received increasing attention in the last decades due to the variety of functions and brain plasticity effects involved during its practice. Most previous reports interpreted the differences between music experts and laymen as the result of training. However, recent investigations suggest that these differences are due to a combination of genetic predispositions with the effect of music training. Here, we tested the relationship of the dorsal auditory-motor pathway with individual behavioural differences in short-term music learning. We gathered structural neuroimaging data from 44 healthy non-musicians (28 females) before they performed a rhythm- and a melody-learning task during a single behavioural session, and manually dissected the arcuate fasciculus (AF) in both hemispheres. The macro- and microstructural organization of the AF (i.e., volume and FA) predicted the learning rate and learning speed in the musical tasks, but only in the right hemisphere. Specifically, the volume of the right anterior segment predicted the synchronization improvement during the rhythm task, the FA in the right long segment was correlated with the learning rate in the melody task, and the volume and FA of the right whole AF predicted the learning speed during the melody task. This is the first study finding a specific relation between different branches within the AF and rhythmic and melodic materials. Our results support the relevant function of the AF as the structural correlate of both auditory-motor transformations and the feedback-feedforward loop, and suggest a crucial involvement of the anterior segment in error-monitoring processes related to auditory-motor learning. These findings have implications for both the neuroscience of music field and second-language learning investigations.

Divisions:Concordia University > Faculty of Arts and Science > Psychology
Item Type:Article
Refereed:Yes
Authors:Penhune, Virginia and Vaquero, Lucía and Ramos-Escobar, Neus and François, Clément and Rodríguez-Fornells, Antoni
Journal or Publication:NeuroImage
Date:2018
Funders:
  • FEDER funds/European Regional Development Fund (ERDF)
Digital Object Identifier (DOI):10.1016/j.neuroimage.2018.06.054
Keywords:Arcuate fasciculus; Feedback-feedforward loop; Music learning; Non-experts; Predispositions; Error-monitoring
ID Code:984017
Deposited By: ALINE SOREL
Deposited On:06 Jul 2018 14:32
Last Modified:06 Jul 2018 14:54

References:

P. Albouy, J. Mattout, R. Bouet, E. Maby, G. Sanchez, P.E. Aguera, S. Daligault, C. Delpuech, O. Bertrand, A. Caclin, B. (2013). Tillmann Impaired pitch perception and memory in congenital amusia: the deficit starts in the auditory cortex, Brain, 136 (5), pp. 1639-1661

A. Angulo-Perkins, W. Aubé, I. Peretz, F.A. Barrios, J.L. Armony, L. Concha (2014). Music listening engages specific cortical regions within the temporal lobes: differences between musicians and non-musicians, Cortex, 59 pp. 126-137

J.A. Bailey, V.B. Penhune (2010). Rhythm synchronization performance and auditory working memory in early-and late-trained musicians, Exp. Brain Res., 204 (1), pp. 91-101

M. Bangert, T. Peschel, G. Schlaug, M. Rotte, D. Drescher, H. Hinrichs, H.J. Heinze, E. Altenmüller (2006). Shared networks for auditory and motor processing in professional pianists: evidence from fMRI conjunction, Neuroimage, 30 (3), pp. 917-926

P. Bermudez, J.P. Lerch, A.C. Evans, R.J. Zatorre (2009). Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry, Cerebr. Cortex, 19 (7), pp. 1583-1596

T. Blecher, I. Tal, M. Ben-Shachar (2016). White matter microstructural properties correlate with sensorimotor synchronization abilities,Neuroimage, 138, pp. 1-12

A. Boemio, S. Fromm, A. Braun, D. Poeppel (2005). Hierarchical and asymmetric temporal sensitivity in human auditory cortices, Nat. Neurosci., 8 (3), pp. 389-395

I. Bornkessel-Schlesewsky, M. Schlesewsky, S.L. Small, J.P. Rauschecker (2015). Neurobiological roots of language in primate audition: common computational properties,Trends Cognit. Sci., 19 (3), pp. 142-150

B. Bozkurt, K. Yagmurlu, E.H. Middlebrooks, A. Karadag, T.C. Ovalioglu, B. Jagadeesan, G. Sandhu, N. Tanriover, A.W. Grande (2016). Microsurgical and tractographic anatomy of the supplementary motor area complex in humans, World Neurosurgery, 95, pp. 99-107

R.M. Brown, J.L. Chen, A. Hollinger, V.B. Penhune, C. Palmer, R.J. Zatorre (2013). Repetition suppression in auditory–motor regions to pitch and temporal structure in music, J. Cognit. Neurosci., 25 (2), pp. 313-328

R.M. Brown, R.J. Zatorre, V.B. Penhune (2015). Expert music performance: cognitive, neural, and developmental bases, Prog. Brain Res., 217, pp. 57-86

S. Budisavljevic, F. Dell'Acqua, F.V. Rijsdijk, F. Kane, M. Picchioni, P. McGuire, T. Toulopoulou, A. Georgiades, S. Kalidindi, E. Kravariti, R.M. Murray (2015). Age-related differences and heritability of the perisylvian language networks, J. Neurosci., 35 (37), pp. 12625-12634

M. Catani, D.K. Jones, D.H. ffytche (2005). Perisylvian language networks of the human brain, Ann. Neurol., 57 (1), pp. 8-16

M. Catani, M.P. Allin, M. Husain, L. Pugliese, M.M. Mesulam, R.M. Murray, D.K. Jones (2007). Symmetries in human brain language pathways correlate with verbal recall, Proceedings of the National Academy of Sciences USA, 104 (43), pp. 17163-17168

M. Catani, M. Mesulam (2008). The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state, Cortex, 44 (8), pp. 953-961

J.L. Chen, V.B. Penhune, R.J. Zatorre (2008). Moving on time: brain network for auditory-motor synchronization is modulated by rhythm complexity and musical training,J. Cognit. Neurosci., 20 (2), pp. 226-239

J.L. Chen, V.B. Penhune, R.J. Zatorre (2008). Listening to musical rhythms recruits motor regions of the brain, Cerebr. Cortex, 18 (12), pp. 2844-2854

J.L. Chen, C. Rae, K.E. Watkins (2012). Learning to play a melody: an fMRI study examining the formation of auditory-motor associations, Neuroimage, 59 (2), pp. 1200-1208

T. Cunillera, E. Càmara, J.M. Toro, J. Marco-Pallares, N. Sebastián-Galles, H. Ortiz, J. Pujol, A. Rodríguez-Fornells (2009). Time course and functional neuroanatomy of speech segmentation in adults, Neuroimage, 48 (3), pp. 541-553

Ö. De Manzano, F. Ullén (2018). Same genes, different brains: neuroanatomical differences between monozygotic twins discordant for musical training, Cerebr. Cortex, 28 (1), pp. 387-394

A.S. Dick, P. Tremblay (2012). Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language, Brain, 135 (12), pp. 3529-3550

D.M. Dimitrov, P.D. Rumrill Jr. (2003). Pretest-posttest designs and measurement of change, Work, 20 (2), pp. 159-165

D. Drayna, A. Manichaikul, M. de Lange, H. Snieder, T. Spector (2001). Genetic correlates of musical pitch recognition in humans, Science, 291 (5510), pp. 1969-1972

S. Elmer, J. Hänggi, L. Jäncke (2016). Interhemispheric transcallosal connectivity between the left and right planum temporale predicts musicianship, performance in temporal speech processing, and functional specialization, Brain Struct. Funct., 221 (1), pp. 331-344

A. Engel, B.S. Hijmans, L. Cerliani, M. Bangert, L. Nanetti, P.E. Keller, C. Keysers (2014). Inter-individual differences in audio-motor learning of piano melodies and white matter fiber tract architecture, Hum. Brain Mapp., 35 (5), pp. 2483-2497

J.C. Fernández-Miranda, Y. Wang, S. Pathak, L. Stefaneau, T. Verstynen, F.C. Yeh (2015). Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain,Brain Struct. Funct., 220 (3), pp. 1665-1680

N.E. Foster, R.J. Zatorre (2010). Cortical structure predicts success in performing musical transformation judgments, Neuroimage, 53 (1), pp. 26-36

C. Gaser, G. Schlaug (2003). Brain structures differ between musicians and nonmusicians, J. Neurosci., 23 (27), pp. 9240-9245

N. Golestani, T. Paus, R.J. Zatorre (2002). Anatomical correlates of learning novel speech sounds, Neuron, 35 (5), pp. 997-1010

N. Golestani, R.J. Zatorre (2004). Learning new sounds of speech: reallocation of neural substrates, Neuroimage, 21 (2), pp. 494-506

J.A. Grahn, J.B. Rowe (2009). Feeling the beat: premotor and striatal interactions in musicians and nonmusicians during beat perception, J. Neurosci., 29 (23), pp. 7540-7548

J.A. Grahn (2012). Neural mechanisms of rhythm perception: current findings and future perspectives, Topics in Cognitive Science, 4 (4), pp. 585-606

G.F. Halwani, P. Loui, T. Rüber, G. Schlaug (2011). Effects of practice and experience on the arcuate fasciculus: comparing singers, instrumentalists, and non-musicians, Front. Psychol., 2, pp. 39-47

S.C. Herholz, R.J. Zatorre (2012). Musical training as a framework for brain plasticity: behavior, function, and structure, Neuron, 76 (3), pp. 486-502

S.C. Herholz, E.B. Coffey, C. Pantev, R.J. Zatorre (2015). Dissociation of neural networks for predisposition and for training-related plasticity in auditory-motor learning, Cerebr. Cortex, 26 (7), pp. 3125-3134

G. Hickok, J. Houde, F. Rong (2011). Sensorimotor integration in speech processing: computational basis and neural organization, Neuron, 69 (3), pp. 407-422

G. Hickok, D. Poeppel (2000). Towards a functional neuroanatomy of speech perception, Trends Cognit. Sci., 4 (4), pp. 131-138

G. Hickok, D. Poeppel (2004). Dorsal and ventral streams: a framework for understanding aspects of the functional anatomy of language, Cognition, 92 (1–2), pp. 67-99

G. Hickok, D. Poeppel (2007). The cortical organization of speech processing, Nat. Rev. Neurosci., 8 (5), pp. 393-402

G. Hickok, D. Poeppel (2015). Neural basis of speech, Handb. Clin. Neurol., 129, pp. 149-160

C.E. James, M.S. Oechslin, D. Van De Ville, C.A. Hauert, C. Descloux, F. Lazeyras (2014). Musical training intensity yields opposite effects on grey matter density in cognitive versus sensorimotor networks, Brain Struct. Funct., 219 (1), pp. 353-366

B. Kleber, A.G. Zeitouni, A. Friberg, R.J. Zatorre (2013). Experience-dependent modulation of feedback integration during singing: role of the right anterior insula, J. Neurosci., 33 (14), pp. 6070-6080

S. Koelsch (2005). Neural substrates of processing syntax and semantics in music, Curr. Opin. Neurobiol., 15 (2), pp. 207-212

S. Koelsch (2010). Towards a neural basis of music-evoked emotions, Trends Cognit. Sci., 14 (3), pp. 131-137

A. Lahav, E. Saltzman, G. Schlaug (2007). Action representation of sound: audiomotor recognition network while listening to newly acquired actions, J. Neurosci., 27 (2), pp. 308-314

A. Lahav, T. Katz, R. Chess, E. Saltzman (2013). Improved motor sequence retention by motionless listening, Psychol. Res., 77 (3), pp. 310-319

D. López-Barroso, M. Catani, P. Ripollés, F. Dell'Acqua, A. Rodríguez-Fornells, R. de Diego-Balaguer (2013). Word learning is mediated by the left arcuate fasciculus, Proc. Natl. Acad. Sci. Unit. States Am., 110 (32), pp. 13168-13173

D. López-Barroso, P. Ripollés, J. Marco-Pallarés, B. Mohammadi, T.F. Münte, A.C. Bachoud-Lévi, A. Rodriguez-Fornells, R. de Diego-Balaguer (2015). Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis, Neuroimage, 110, pp. 182-193

P. Loui, D. Alsop, G. Schlaug (2009). Tone deafness: a new disconnection syndrome?, J. Neurosci., 29 (33), pp. 10215-10220

P. Loui, H.C. Li, G. Schlaug (2011). White matter integrity in the right hemisphere predicts pitch-related grammar learning, Neuroimage, 55 (2), pp. 500-507

B.N. Macnamara, D.Z. Hambrick, F.L. Oswald (2014). Deliberate practice and performance in music, games, sports, education, and professions: a meta-analysis, Psychol. Sci., 25 (8), pp. 1608-1618

B.N. Macnamara, D. Moreau, D.Z. Hambrick (2016). The relationship between deliberate practice and performance in sports: a meta-analysis. Perspectives on Psychological Science, a journal of the Association for Psychological Science, 11 (3), pp. 333-350

P.C. Mamiya, T.L. Richards, B.P. Coe, E.E. Eichler, P.K. Kuhl (2016). Brain white matter structure and COMT gene are linked to second-language learning in adults, Proc. Natl. Acad. Sci. Unit. States Am., 113 (26), pp. 7249-7254

M.A. Mosing, G. Madison, N.L. Pedersen, R. Kuja-Halkola, F. Ullén (2014). Practice does not make perfect: No causal effect of music practice on music ability, Psychol. Sci., 25 (9), pp. 1795-1803

M.A. Mosing, N.L. Pedersen, G. Madison, F. Ullén (2014). Genetic pleiotropy explains associations between musical auditory discrimination and intelligence, PLoS One, 9 (11), p. e113874

D. Müllernsiefen, B. Gingras, J. Musil, L. Stewart (2014). The musicality of non-musicians: an index for assessing musical sophistication in the general population, PLoS One, 9 (2), p. e89642

G. Novembre, P.E. Keller (2014). A conceptual review on action-perception coupling in the musicians' brain: what is it good for?, Front. Hum. Neurosci., 8

S. Ocklenburg, L. Schlaffke, K. Hugdahl, R. Westerhausen (2014). From structure to function in the lateralized brain: how structural properties of the arcuate and uncinate fasciculus are associated with dichotic listening performance, Neurosci. Lett., 580, pp. 32-36

G. Padrão, V. Penhune, R. de Diego-Balaguer, J. Marco-Pallares, A. Rodriguez-Fornells (2014). ERP evidence of adaptive changes in error processing and attentional control during rhythm synchronization learning, Neuroimage, 100, pp. 460-470

A.D. Patel (2014). Can nonlinguistic musical training change the way the brain processes speech? The expanded OPERA hypothesis, Hear. Res., 308, pp. 98-108

V.B. Penhune, R.J. Zatorre, W.H. Feindel (1999). The role of auditory cortex in retention of rhythmic patterns as studied in patients with temporal lobe removals including Heschl's gyrus, Neuropsychologia, 37 (3), pp. 315-331

D. Perani, M.C. Saccuman, P. Scifo, D. Spada, G. Andreolli, R. Rovelli, C. Baldeoli, S. Koelsch (2010). Functional specializations for music processing in the human newborn brain, Proc. Natl. Acad. Sci. U.S.A., 107 (10) 4758–47-63

I. Peretz, A.S. Champod, K. Hyde (2003). Varieties of musical disorders, Ann. N. Y. Acad. Sci., 999 (1), pp. 58-75

I. Peretz, M. Coltheart (2003). Modularity of music processing, Nat. Neurosci., 6 (7), pp. 688-691

M. Petrides, F. Tomaiuolo, E.H. Yeterian, D.N. Pandya (2012). The prefrontal cortex: comparative architectonic organization in the human and the macaque monkey brains, Cortex, 48 (1), pp. 46-57

J. Phillips-Silver, P. Toiviainen, N. Gosselin, I. Peretz (2013). Amusic does not mean unmusical: beat perception and synchronization ability despite pitch deafness, Cogn. Neuropsychol., 30 (5), pp. 311-331

D. Poeppel (2003). The analysis of speech in different temporal integration windows cerebral lateralization as ‘asymmetric sampling in time’, Speech Commun., 41, pp. 245-255

D. Poeppel, G. Hickok (2004). Towards a new functional anatomy of language, Cognition, 92 (1–2), pp. 1-12

Z. Qi, M. Han, K. Garel, E. San Chen, J.D. Gabrieli (2015). White-matter structure in the right hemisphere predicts Mandarin Chinese learning success, J. Neurolinguistics, 33, pp. 14-28

N. Ramnani, R.E. Passingham (2001). Changes in the human brain during rhythm learning, J. Cognit. Neurosci., 13 (7), pp. 952-966

J.P. Rauschecker, B. Tian (2000). Mechanisms and streams for processing of “what” and “where” in auditory cortex, Proc. Natl. Acad. Sci. U.S.A., 97 (22), pp. 11800-11806

J.P. Rauschecker, S.K. Scott (2009). Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing, Nat. Neurosci., 12 (6), pp. 718-724

J.P. Rauschecker(2012). Ventral and dorsal streams in the evolution of speech and language, Front. Evol. Neurosci., 4 , p. 7

J. Raven (1989). The Raven Progressive Matrices: a review of national norming studies and ethnic and socioeconomic variation within the United States, J. Educ. Meas., 26 (1), pp. 1-16

P. Ripollés, N. Rojo, J. Grau-Sánchez, J.L. Amengual, E. Càmara, J. Marco-Pallarés, M. Juncadella, L. Vaquero, F. Rubio, E. Duarte, C. Garrido, E. Altenmüller, T.F. Münte, A. Rodríguez-Fornells (2016). Music supported therapy promotes motor plasticity in individuals with chronic stroke, Brain imaging and behavior, 10 (4), pp. 1289-1307

A. Rodríguez-Fornells, T. Cunillera, A. Mestres-Missé, R. de Diego-Balaguer (2009). Neurophysiological mechanisms involved in language learning in adults, Philos. Trans. R. Soc. Lond. B Biol. Sci., 364 (1536), pp. 3711-3735

A. Rodríguez-Fornells, N. Rojo, J.L. Amengual, P. Ripollés, E. Altenmüller, T.F. Münte (2012). The involvement of audio–motor coupling in the music-supported therapy applied to stroke patients, Ann. N. Y. Acad. Sci., 1252 (1), pp. 282-293

Z.M. Saygin, E.S. Norton, D.E. Osher, S.D. Beach, A.B. Cyr, O. Ozernov-Palchik, A. Yendiki, B. Fischl, N. Gaab, J.D. Gabrieli (2013). Tracking the roots of reading ability: white matter volume and integrity correlate with phonological awareness in prereading and early-reading kindergarten children, J. Neurosci., 33 (33), pp. 13251-13258

P. Schneider, M. Scherg, H.G. Dosch, H.J. Specht, A. Gutschalk, A. Rupp (2002). Morphology of Heschl's gyrus reflects enhanced activation in the auditory cortex of musicians, Nat. Neurosci., 5 (7), pp. 688-694

P. Schneider, V. Sluming, N. Roberts, M. Scherg, R. Goebel, H.J. Specht, H.G. Dosch, S. Bleeck, C. Stippich, A. Rupp (2005). Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference, Nat. Neurosci., 8 (9), pp. 1241-1247

P. Schneider, V. Sluming, N. Roberts, S. Bleeck, A. Rupp (2005). Structural, functional, and perceptual differences in Heschl's gyrus and musical instrument preference, Ann. N. Y. Acad. Sci., 1060 (1), pp. 387-394

E. Seesjärvi, T. Särkämö, E. Vuoksimaa, M. Tervaniemi, I. Peretz, J. Kaprio (2016). The nature and nurture of melody: a twin study of musical pitch and rhythm perception, Behav. Genet., 46 (4), pp. 506-515

A. Seither-Preisler, R. Parncutt, P. Schneider (2014). Size and synchronization of auditory cortex promotes musical, literacy, and attentional skills in children, J. Neurosci., 34 (33), pp. 10937-10949

B. Serrallach, C. Groβ, V. Bernhofs, D. Engelmann, J. Benner, N. Gündert, M. Blatow, M. Wengenroth, A. Seitz, M. Brunner, Sm Seither, R. Parncutt, P. Schneider, A. Seither-Preisler (2016). Neural biomarkers for dyslexia, ADHD, and ADD in the auditory cortex of children, Front. Neurosci., 10, p. 324

A.J. Sihvonen, P. Ripollés, V. Leo, A. Rodríguez-Fornells, S. Soinila, T. Särkämö (2016). Neural basis of acquired amusia and its recovery after stroke, J. Neurosci., 36 (34), pp. 8872-8881

A.J. Sihvonen, P. Ripollés, T. Särkämö, V. Leo, A. Rodríguez-Fornells, J. Saunavaara, R. Parkkola, S. Soinila (2017). Tracting the neural basis of music: deficient structural connectivity underlying acquired amusia, Cortex, 97, pp. 255-273

S.M. Smith (2002). Fast robust automated brain extraction, Hum. Brain Mapp., 17 (3), pp. 143-155

S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R.K. Niazy (2004). Advances in functional and structural MR image analysis and implementation as FSL, Neuroimage, 23, pp. S208-S219

R.M. Sreedharan, A.C. Menon, J.S. James, C. Kesavadas, S.V. Thomas (2015). Arcuate fasciculus laterality by diffusion tensor imaging correlates with language laterality by functional MRI in preadolescent children, Neuroradiology, 57 (3), pp. 291-297

L. Stewart, R. Henson, K. Kampe, V. Walsh, R. Turner, U. Frith (2003). Brain changes after learning to read and play music, Neuroimage, 20 (1), pp. 71-83

S. Telkemeyer, S. Rossi, S.P. Koch, T. Niergaus, J. Steinbrink, D. Poeppel, H. Obrig, I. Wartenburger (2009). Sensitivity of newborn auditory cortex to the temporal structure of sounds, J. Neurosci., 29 (47), pp. 14726-14733

F. Ullén, D.Z. Hambrick, M.A. Mosing (2016). Rethinking expertise: a multifactorial gene-environment interaction model of expert performance, Psychol. Bull., 142 (4), pp. 427-446

L. Vaquero, A. Rodríguez-Fornells, S.M. Reiterer (2016). The left, the better: white-matter brain integrity predicts foreign language imitation ability, Cerebr. Cortex, 27 (8), pp. 3906-3917

X. Wang, S. Pathak, L. Stefaneanu, F.C. Yeh, S. Li, J.C. Fernandez-Miranda (2016). Subcomponents and connectivity of the superior longitudinal fasciculus in the human brain, Brain Struct. Funct., 221 (4), pp. 2075-2092

J.E. Warren, R.J. Wise, J.D. Warren (2005). Sounds do-able: auditory–motor transformations and the posterior temporal plane, Trends Neurosci., 28 (12), pp. 636-643

D. WechslerWAIS III Escala de Inteligencia de Wechsler para Adultos–III. Madrid: TEA(1999)

M.W. Woolrich, S. Jbabdi, B. Patenaude, M. Chappell, S. Makni, T. Behrens, C. Beckmann, M. Jenkinson, S.M. Smith (2009). Bayesian analysis of neuroimaging data in FSL, Neuroimage, 45, pp. S173-S186

R.J. Zatorre, A.C. Evans, E. Meyer, A. Gjedde (1992). Lateralization of phonetic and pitch discrimination in speech processing, Science, 256 (5058), pp. 846-849

R.J. Zatorre, P. Belin, V.B. Penhune (2002). Structure and function of auditory cortex: music and speech, Trends Cognit. Sci., 6 (1), pp. 37-46

R.J. Zatorre, J.L. Chen, V.B. Penhune (2007). When the brain plays music: auditory–motor interactions in music perception and production, Nat. Rev. Neurosci., 8 (7), pp. 547-558

R.J. Zatorre, K. Delhommeau, J.M. Zarate (2012). Modulation of auditory cortex response to pitch variation following training with microtonal melodies, Front. Psychol., 3

R.J. Zatorre (2013). Predispositions and plasticity in music and speech learning: neural correlates and implications, Science, 342 (6158), pp. 585-589
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Back to top Back to top