Rhythmic context influences the auditory evoked potentials of musicians and nonmusicians

Jongsma, M.L.A.; Desain, Peter; Honing, Henkjan

doi:10.1016/j.biopsycho.2003.10.002

Cited by 79 publications

(81 citation statements)

References 44 publications

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“…This provides further evidence for the general perceptual/ cognitive capability based interpretation of meter. While earlier research showed only a marginal sensitivity to meter in listeners with little or no formal music training (e.g., Jongsma et al, 2004;Palmer & Krumhansl, 1990), the current study demonstrated that meter is a mental representation that does not require advanced formal music training. This conclusion does not rule out the possibility that, similarly to other music-related processing capabilities, the representation of rhythmic structures can be improved by music training (see for example van Zuijen et al, 2005).…”

Section: General Discussion and Conclusioncontrasting

confidence: 78%

“…Specifically, the question is, whether or not listeners form multilevel hierarchical representations for rhythmic sequences. Expectations in adult listeners with formal music training suggest that they weight events within a measure in a hierarchical manner (Jongsma, Desain, & Honing, 2004;Palmer & Krumhansl, 1990). A study by Ladinig and Honing (2009) shows that this holds irrespective of listener's musical expertise.…”

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confidence: 99%

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Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training

et al. 2009

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Probing attentive and preattentive emergent meter in adult listeners without extensive music training Ladinig, O.; Honing, H.J.; Háden, G.P.; Winkler, I. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. BEAT AND METER INDUCTION ARE CONSIDERED important structuring mechanisms underlying the perception of rhythm. Meter comprises two or more levels of hierarchically ordered regular beats with different periodicities. When listening to music, adult listeners weight events within a measure in a hierarchical manner. We tested if listeners without advanced music training form such hierarchical representations for a rhythmical sound sequence under different attention conditions (Attend, Unattend, and Passive). Participants detected occasional weakly and strongly syncopated rhythmic patterns within the context of a strictly metrical rhythmical sound sequence. Detection performance was better and faster when syncopation occurred in a metrically strong as compared to a metrically weaker position. Compatible electrophysiological differences (earlier and higher-amplitude MMN responses) were obtained when participants did not attend the rhythmical sound sequences. These data indicate that hierarchical representations for rhythmical sound sequences are formed preattentively in the human auditory system.

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Section: General Discussion and Conclusioncontrasting

confidence: 78%

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confidence: 99%

Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training

et al. 2009

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“…For example, P3b responses were greater in musicians asked to listen for pitch deviants (for late positivity results, see Besson & Faïta, 1995; for the P3b specifically, see Nikjeh, Lister, & Frisch, 2009;Tervaniemi, Just, Koelsch, Widmann, & Schröger, 2005), rhythmic irregularities (Vuust, Ostergaard, Pallesen, Bailey, & Roepstorff, 2009), and sound location deviants (Nager, Kohlmetz, Altenmüller, RodriguezFornells, & Münte, 2003). In rhythmically trained musicians, P3b latencies were shorter for irregular sound omissions in rhythmic contexts (Jongsma, Desain, & Honing, 2004). Similarly, P3a latencies for pitch deviant sounds were shorter when musically trained participants were asked to ignore sounds (Nikjeh et al, 2009).…”

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confidence: 91%

Music training enhances the rapid plasticity of P3a/P3b event-related brain potentials for unattended and attended target sounds

Seppänen

Pesonen

Tervaniemi

2012

Atten Percept Psychophys

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Neurocognitive studies have shown that extensive musical training enhances P3a and P3b event-related potentials for infrequent target sounds, which reflects stronger attention switching and stimulus evaluation in musicians than in nonmusicians. However, it is unknown whether the short-term plasticity of P3a and P3b responses is also enhanced in musicians. We compared the short-term plasticity of P3a and P3b responses to infrequent target sounds in musicians and nonmusicians during auditory perceptual learning tasks. Target sounds, deviating in location, pitch, and duration with three difficulty levels, were interspersed among frequently presented standard sounds in an oddball paradigm. We found that during passive exposure to sounds, musicians had habituation of the P3a, while nonmusicians showed enhancement of the P3a between blocks. Between active tasks, P3b amplitudes for duration deviants were reduced (habituated) in musicians only, and showed a more posterior scalp topography for habituation when compared to P3bs of nonmusicians. In both groups, the P3a and P3b latencies were shortened for deviating sounds. Also, musicians were better than nonmusicians at discriminating target deviants. Regardless of musical training, better discrimination was associated with higher working memory capacity. We concluded that music training enhances short-term P3a/ P3b plasticity, indicating training-induced changes in attentional skills.

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“…These components, such as the N1/P2 complex (Dekio-Hotta et al, 2009), the P300 oddball response (Halpern et al, 2007;Krohn et al, 2007) and the mismatch negativity (MMN, Brattico et al, 2006;Trainor et al, 2002) have all been shown to be influenced by musical characteristics. ERP responses to musical rhythms have also been investigated, for different metric levels such as the note, beat and bar level (Jongsma et al, 2004), as well as subjective accents (Brochard et al, 2003). Combining a number of these types of musical accents, Palmer et al (2009) found that different types of accent in a melodic sequence (such as timbre changes, melodic and temporal accents) induce different types of ERP response, showing that listeners' neural responses to musical structure changed systematically as sequential predictability of the melodies and listeners' expectations changed across the melodic context.…”

Section: Introductionmentioning

confidence: 99%

Name that tune: Decoding music from the listening brain

et al. 2011

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a b s t r a c t a r t i c l e i n f oIn the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven different musical fragments of about three seconds, both individually and cross-participants, using only time domain information (the event-related potential, ERP). The best individual results are 70% correct in a seven-class problem while using single trials, and when using multiple trials we achieve 100% correct after six presentations of the stimulus. When classifying across participants, a maximum rate of 53% was reached, supporting a general representation of each musical fragment over participants. While for some music stimuli the amplitude envelope correlated well with the ERP, this was not true for all stimuli. Aspects of the stimulus that may contribute to the differences between the EEG responses to the pieces of music are discussed.

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Rhythmic context influences the auditory evoked potentials of musicians and nonmusicians

Cited by 79 publications

References 44 publications

Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training

Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training

Music training enhances the rapid plasticity of P3a/P3b event-related brain potentials for unattended and attended target sounds

Name that tune: Decoding music from the listening brain

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