Literature DB >> 15298788

Musical training enhances automatic encoding of melodic contour and interval structure.

Takako Fujioka1, Laurel J Trainor, Bernhard Ross, Ryusuke Kakigi, Christo Pantev.   

Abstract

In music, melodic information is thought to be encoded in two forms, a contour code (up/down pattern of pitch changes) and an interval code (pitch distances between successive notes). A recent study recording the mismatch negativity (MMN) evoked by pitch contour and interval deviations in simple melodies demonstrated that people with no formal music education process both contour and interval information in the auditory cortex automatically. However, it is still unclear whether musical experience enhances both strategies of melodic encoding. We designed stimuli to examine contour and interval information separately. In the contour condition there were eight different standard melodies (presented on 80% of trials), each consisting of five notes all ascending in pitch, and the corresponding deviant melodies (20%) were altered to descending on their final note. The interval condition used one five-note standard melody transposed to eight keys from trial to trial, and on deviant trials the last note was raised by one whole tone without changing the pitch contour. There was also a control condition, in which a standard tone (990.7 Hz) and a deviant tone (1111.0 Hz) were presented. The magnetic counterpart of the MMN (MMNm) from musicians and nonmusicians was obtained as the difference between the dipole moment in response to the standard and deviant trials recorded by magnetoencephalography. Significantly larger MMNm was present in musicians in both contour and interval conditions than in nonmusicians, whereas MMNm in the control condition was similar for both groups. The interval MMNm was larger than the contour MMNm in musicians. No hemispheric difference was found in either group. The results suggest that musical training enhances the ability to automatically register abstract changes in the relative pitch structure of melodies.

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Year:  2004        PMID: 15298788     DOI: 10.1162/0898929041502706

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  80 in total

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2.  Musical intervals and relative pitch: frequency resolution, not interval resolution, is special.

Authors:  Josh H McDermott; Michael V Keebler; Christophe Micheyl; Andrew J Oxenham
Journal:  J Acoust Soc Am       Date:  2010-10       Impact factor: 1.840

3.  Enhanced brainstem encoding predicts musicians' perceptual advantages with pitch.

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4.  Musicians and tone-language speakers share enhanced brainstem encoding but not perceptual benefits for musical pitch.

Authors:  Gavin M Bidelman; Jackson T Gandour; Ananthanarayan Krishnan
Journal:  Brain Cogn       Date:  2011-08-10       Impact factor: 2.310

5.  Sensorimotor integration is enhanced in dancers and musicians.

Authors:  Falisha J Karpati; Chiara Giacosa; Nicholas E V Foster; Virginia B Penhune; Krista L Hyde
Journal:  Exp Brain Res       Date:  2015-12-15       Impact factor: 1.972

6.  A mismatch negativity study of local-global auditory processing.

Authors:  Alexandra List; Timothy Justus; Lynn C Robertson; Shlomo Bentin
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7.  Bootstrap significance of low SNR evoked response.

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8.  Relative influence of musical and linguistic experience on early cortical processing of pitch contours.

Authors:  Bharath Chandrasekaran; Ananthanarayan Krishnan; Jackson T Gandour
Journal:  Brain Lang       Date:  2008-03-17       Impact factor: 2.381

9.  Language and music: differential hemispheric dominance in detecting unexpected errors in the lyrics and melody of memorized songs.

Authors:  Takuya Yasui; Kimitaka Kaga; Kuniyoshi L Sakai
Journal:  Hum Brain Mapp       Date:  2009-02       Impact factor: 5.038

10.  Neural correlates of pre-attentive processing of pattern deviance in professional musicians.

Authors:  Benedikt Habermeyer; Marcus Herdener; Fabrizio Esposito; Caroline C Hilti; Markus Klarhöfer; Francesco di Salle; Stephan Wetzel; Klaus Scheffler; Katja Cattapan-Ludewig; Erich Seifritz
Journal:  Hum Brain Mapp       Date:  2009-11       Impact factor: 5.038

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