Temporal coherence shapes cortical responses to speech mixtures in a ferret cocktail party

Perceptual segregation of complex sounds such as speech and music simultaneously emanating from multiple sources is a remarkable ability that is common in humans and other animals alike. Unlike animal physiological experiments with simplified sounds or human investigations with spatially broad imaging techniques, this study combines insights from animal single-unit recordings with segregation of speech-like sound mixtures. Ferrets are trained to attend to a female voice and detect a target word, both in presence and absence of a concurrent equally salient male voice. Recordings are made in primary and secondary auditory cortical fields, and in frontal cortex. During task performance, representation of the female words becomes enhanced relative to the male in all, but especially in higher cortical regions. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings underscore the role of the principle of temporal coherence whereby attention to a target voice binds together all neural responses coherently modulated with the target, thus ultimately forming and extracting a common auditory stream.

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Publication Details

Journal
Communications Biology
Published
2024-10-25
DOI
https://doi.org/10.1038/s42003-024-07096-3
Citations
4
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
1.37

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article

Temporal coherence shapes cortical responses to speech mixtures in a ferret cocktail party

Daniel Duque, Pingbo Yin, Neha Joshi, Mounya Elhilali et al.
4 citations
Communications Biology
Neural dynamics and brain function
1.37
article

Temporal coherence shapes cortical responses to speech mixtures in a ferret cocktail party

Daniel Duque, Pingbo Yin, Neha Joshi, Mounya Elhilali, Jonathan B. Fritz, Shihab Shamma, Karan Thakkar, William Ng
article en
4 citations

Abstract

Perceptual segregation of complex sounds such as speech and music simultaneously emanating from multiple sources is a remarkable ability that is common in humans and other animals alike. Unlike animal physiological experiments with simplified sounds or human investigations with spatially broad imaging techniques, this study combines insights from animal single-unit recordings with segregation of speech-like sound mixtures. Ferrets are trained to attend to a female voice and detect a target word, both in presence and absence of a concurrent equally salient male voice. Recordings are made in primary and secondary auditory cortical fields, and in frontal cortex. During task performance, representation of the female words becomes enhanced relative to the male in all, but especially in higher cortical regions. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings underscore the role of the principle of temporal coherence whereby attention to a target voice binds together all neural responses coherently modulated with the target, thus ultimately forming and extracting a common auditory stream.

Communications BiologyVol. 7(1)
Johns Hopkins University (US), Universidad de Salamanca (ES), Johns Hopkins Medicine (US), École Normale Supérieure - PSL (FR), Instituto de Estudios de Ciencias de la Salud de Castilla y León (ES), École Normale Supérieure (BI), New York University (US), University of Maryland, College Park (US)
National Institutes of Health, Multidisciplinary University Research Initiative, Office of Naval Research, Air Force Office of Scientific Research
Openalex Percentile: Top 19%
Neural dynamics and brain function
1.37
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