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

Journal Article · · Nature Communications
 [1]; ORCiD logo [2]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). McGovern Inst. for Brain Research, Center for Brains, Minds, and Machines; Columbia Univ., New York, NY (United States). Zuckerman Inst. of Mind, Brain, and Behavior
  2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). McGovern Inst. for Brain Research, Center for Brains, Minds, and Machines; Harvard Univ., Boston, MA (United States)

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.

Research Organization:
Krell Institute, Ames, IA (United States)
Sponsoring Organization:
USDOE Office of Science (SC); National Institutes of Health (NIH)
Grant/Contract Number:
FG02-97ER25308; 1R01DC014739-01A1; R25GM067110; BCS-1634050; PHY17-48958
OSTI ID:
1610345
Journal Information:
Nature Communications, Vol. 10, Issue 1; ISSN 2041-1723
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 20 works
Citation information provided by
Web of Science

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Illusory sound texture reveals multi-second statistical completion in auditory scene analysis journal November 2019
EEG-based classification of natural sounds reveals specialized responses to speech and music journal April 2020
Illusory sound texture reveals multi-second statistical completion in auditory scene analysis journal November 2019