Auditory deviance detection across time scales: Effects of local and global context

Auditory deviance detection reflects the ability to identify violations of statistical regularities in sound sequences and is influenced by stimulus properties and contextual expectations. Using a priming paradigm in which listeners were exposed to different pitch distributions prior to deviant detection trials, we examined how performance varied across the experiment (global context) and relative to short-term priors (local context). Results show that listeners accumulate statistical information across distinct contextual time scales, where local and global context influence deviance detection. Computational modeling using a predictive coding framework is consistent with these effects, highlighting the importance of integrating contextual information across scales in dynamic acoustic environments.

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Publication Details

Journal
JASA Express Letters
Published
2026-04-01
DOI
https://doi.org/10.1121/10.0043222
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Auditory deviance detection across time scales: Effects of local and global context

Nahaleh Fatemi, Matthew Blunt, Mounya Elhilali, Stephanie Graceffo
JASA Express Letters
Music and Audio Processing
article

Auditory deviance detection across time scales: Effects of local and global context

Nahaleh Fatemi, Matthew Blunt, Mounya Elhilali, Stephanie Graceffo
article en

Abstract

Auditory deviance detection reflects the ability to identify violations of statistical regularities in sound sequences and is influenced by stimulus properties and contextual expectations. Using a priming paradigm in which listeners were exposed to different pitch distributions prior to deviant detection trials, we examined how performance varied across the experiment (global context) and relative to short-term priors (local context). Results show that listeners accumulate statistical information across distinct contextual time scales, where local and global context influence deviance detection. Computational modeling using a predictive coding framework is consistent with these effects, highlighting the importance of integrating contextual information across scales in dynamic acoustic environments.

JASA Express LettersVol. 6(4)
Johns Hopkins University (US), Johns Hopkins Medicine (US)
National Science Foundation
Reduced inequalities
Openalex Percentile: Top 37%
Music and Audio Processing
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