Mapping Tonal Hierarchy in the Brain

Sauvé, Sarah A.; Cho, Alex; Zendel, Benjamin Rich

doi:10.1016/j.neuroscience.2021.03.019

Cited by 11 publications

(23 citation statements)

References 47 publications

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“…These ERPs reflect different neurocognitive functions: Specifically, the mismatch negativity cooccurs with unexpected events based on auditory memory and the early right anterior negativity cooccurs with unexpected events based on music-syntactical expectations 39 . However, in contrast to the ERP marker found in our study, these earlier neurophysiological differences are found to not systematically relate to behavioral ratings: For example, a recent paper showed that the relationship between the early right anterior negativity and probe-tone ratings differed greatly between participants 31 . Note however that the authors of the paper employed a passive task, in which participants did not attend to the stimuli while their neurophysiological data were collected.…”

Section: Discussioncontrasting

confidence: 99%

“…Differences found in earlier time windows, e.g., the mismatch negativity or the early right anterior negativity, are ascribed to inattentive processes that take place when the listener is not explicitly attending to the stimuli 31 , 37 . These ERPs reflect different neurocognitive functions: Specifically, the mismatch negativity cooccurs with unexpected events based on auditory memory and the early right anterior negativity cooccurs with unexpected events based on music-syntactical expectations 39 .…”

Section: Discussionmentioning

confidence: 99%

“…30 , p. 16), for which previous research has identified the early right anterior negativity 18 as a neurophysiological marker. In fact, recent results 31 show that the early right anterior negativity does not map clearly onto knowledge about tonal hierarchies.…”

Section: Introductionmentioning

confidence: 90%

“…To enable comparison to the data reported previously 31 we analyzed the behavioral data in the same manner as it was analyzed in that paper, using a mixed-effects model, for all probe-tone judgments with the random effect of Participant, the fixed effects of Exposure, Probe-Tone Block, and Time. Here, we expected a significant three-way interaction between Time, Exposure, and Probe-Tone Block, such that ratings for probe-tone categories C ~ and C E would be significantly different only after the exposure phase.…”

Section: Methodsmentioning

confidence: 99%

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Electrophysiological and behavioral indicators of musical knowledge about unfamiliar music

Cui

Troje

Cuddy

2022

Sci Rep

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Most listeners possess sophisticated knowledge about the music around them without being aware of it or its intricacies. Previous research shows that we develop such knowledge through exposure. This knowledge can then be assessed using behavioral and neurophysiological measures. It remains unknown however, which neurophysiological measures accompany the development of musical long-term knowledge. In this series of experiments, we first identified a potential ERP marker of musical long-term knowledge by comparing EEG activity following musically unexpected and expected tones within the context of known music (n = 30). We then validated the marker by showing that it does not differentiate between such tones within the context of unknown music (n = 34). In a third experiment, we exposed participants to unknown music (n = 40) and compared EEG data before and after exposure to explore effects of time. Although listeners’ behavior indicated musical long-term knowledge, we did not find any effects of time on the ERP marker. Instead, the relationship between behavioral and EEG data suggests musical long-term knowledge may have formed before we could confirm its presence through behavioral measures. Listeners are thus not only knowledgeable about music but seem to also be incredibly fast music learners.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

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Electrophysiological and behavioral indicators of musical knowledge about unfamiliar music

Cui

Troje

Cuddy

2022

Sci Rep

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“…Microtonal intervals have been discussed in the context of harmony by [5,14]. Several results from cognitive neuroscience studies in the context of music perception also need to be considered for a geometric model [57,116,72,109,84]. A more conventional and more elaborate account on a scientific approach to music can be found in [30].…”

Section: Introductionmentioning

confidence: 99%

Geometry of Music Perception

Himpel¹

2022

Preprint

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Prevalent neuroscientific theories are combined with acoustic observations from various studies to create a consistent differential-geometric model for music perception in order to rationalize, explain and predict psycho-acoustic phenomena. The space of all chords is shown to be a stratifold, whose Riemannian metric naturally yields a geodesic distance function compatible with voiceleading satisfying the triangle inequality even between chords with a different number of chord tones. The stratifold model allows for rigorous studies of psychoacoustic quantities like roughness and harmonicity as height functions. Lastly, concepts for the perceptive strength of chord resolutions are introduced and analyzed based on the differential-geometric framework.

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Cortical representation of musical pitch in event-related potentials

et al. 2023

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Neural coding of auditory stimulus frequency is well-documented; however, the cortical signals and perceptual correlates of pitch have not yet been comprehensively investigated. This study examined the temporal patterns of event-related potentials (ERP) in response to single tones of pitch chroma, with an assumption that these patterns would be more prominent in musically-trained individuals than in non-musically-trained individuals. Participants with and without musical training (N = 20) were presented with seven notes on the C major scale (C4, D4, E4, F4, G4, A4, and B4), and whole-brain activities were recorded. A linear regression analysis between the ERP amplitude and the seven notes showed that the ERP amplitude increased or decreased as the frequency of the pitch increased. Remarkably, these linear correlations were anti-symmetric between the hemispheres. Specifically, we found that ERP amplitudes of the left and right frontotemporal areas decreased and increased, respectively, as the pitch frequency increased. Although linear slopes were significant in both groups, the musically-trained group exhibited marginally steeper slope, and their ERP amplitudes were most discriminant for frequency of tone of pitch at earlier latency than in the non-musically-trained group (~ 460 ms vs ~ 630 ms after stimulus onset). Thus, the ERP amplitudes in frontotemporal areas varied according to the pitch frequency, with the musically-trained participants demonstrating a wider range of amplitudes and inter-hemispheric anti-symmetric patterns. Our findings may provide new insights on cortical processing of musical pitch, revealing anti-symmetric processing of musical pitch between hemispheres, which appears to be more pronounced in musically-trained people.

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Mapping Tonal Hierarchy in the Brain

Cited by 11 publications

References 47 publications

Electrophysiological and behavioral indicators of musical knowledge about unfamiliar music

Electrophysiological and behavioral indicators of musical knowledge about unfamiliar music

Geometry of Music Perception

Cortical representation of musical pitch in event-related potentials

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