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Auditory Cortex Processes Variation in Our Own Speech

Overview of attention for article published in PLOS ONE, December 2013
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Title
Auditory Cortex Processes Variation in Our Own Speech
Published in
PLOS ONE, December 2013
DOI 10.1371/journal.pone.0082925
Pubmed ID
Authors

Kevin R. Sitek, Daniel H. Mathalon, Brian J. Roach, John F. Houde, Caroline A. Niziolek, Judith M. Ford

Abstract

As we talk, we unconsciously adjust our speech to ensure it sounds the way we intend it to sound. However, because speech production involves complex motor planning and execution, no two utterances of the same sound will be exactly the same. Here, we show that auditory cortex is sensitive to natural variations in self-produced speech from utterance to utterance. We recorded event-related potentials (ERPs) from ninety-nine subjects while they uttered "ah" and while they listened to those speech sounds played back. Subjects' utterances were sorted based on their formant deviations from the previous utterance. Typically, the N1 ERP component is suppressed during talking compared to listening. By comparing ERPs to the least and most variable utterances, we found that N1 was less suppressed to utterances that differed greatly from their preceding neighbors. In contrast, an utterance's difference from the median formant values did not affect N1. Trial-to-trial pitch (f0) deviation and pitch difference from the median similarly did not affect N1. We discuss mechanisms that may underlie the change in N1 suppression resulting from trial-to-trial formant change. Deviant utterances require additional auditory cortical processing, suggesting that speaking-induced suppression mechanisms are optimally tuned for a specific production.

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Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 2%
Germany 1 2%
Netherlands 1 2%
United Kingdom 1 2%
Spain 1 2%
United States 1 2%
Unknown 58 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 33%
Researcher 12 19%
Student > Master 9 14%
Student > Bachelor 3 5%
Professor 2 3%
Other 6 9%
Unknown 11 17%
Readers by discipline Count As %
Psychology 14 22%
Linguistics 8 13%
Agricultural and Biological Sciences 7 11%
Neuroscience 7 11%
Engineering 6 9%
Other 4 6%
Unknown 18 28%