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Invariance to background noise as a signature of non-primary auditory cortex

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Listed:
  • Alexander J. E. Kell

    (MIT
    McGovern Institute for Brain Research, MIT
    Center for Brains, Minds, and Machines, MIT
    Columbia University)

  • Josh H. McDermott

    (MIT
    McGovern Institute for Brain Research, MIT
    Center for Brains, Minds, and Machines, MIT
    Harvard University)

Abstract

Despite well-established anatomical differences between primary and non-primary auditory cortex, the associated representational transformations have remained elusive. Here we show that primary and non-primary auditory cortex are differentiated by their invariance to real-world background noise. We measured fMRI responses to natural sounds presented in isolation and in real-world noise, quantifying invariance as the correlation between the two responses for individual voxels. Non-primary areas were substantially more noise-invariant than primary areas. This primary-nonprimary difference occurred both for speech and non-speech sounds and was unaffected by a concurrent demanding visual task, suggesting that the observed invariance is not specific to speech processing and is robust to inattention. The difference was most pronounced for real-world background noise—both primary and non-primary areas were relatively robust to simple types of synthetic noise. Our results suggest a general representational transformation between auditory cortical stages, illustrating a representational consequence of hierarchical organization in the auditory system.

Suggested Citation

  • Alexander J. E. Kell & Josh H. McDermott, 2019. "Invariance to background noise as a signature of non-primary auditory cortex," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11710-y
    DOI: 10.1038/s41467-019-11710-y
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    Cited by:

    1. Nathaniel J Zuk & Jeremy W Murphy & Richard B Reilly & Edmund C Lalor, 2021. "Envelope reconstruction of speech and music highlights stronger tracking of speech at low frequencies," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-32, September.

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