Auditory deviance detection across time scales: Effects of local and global context
Matthew Blunt1, Stephanie Graceffo1, Nahaleh Fatemi1
1Laboratory for Computational Audio Perception, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.
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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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