Abstract

Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.

The auditory system adapts to properties of sounds reaching the ear, but it is unclear whether this affects the way sounds are perceived. Here, the authors found that auditory responses in the brain predict changes in the perception of sounds, suggesting that adaptation shapes the way we hear.

Details

Title
Dynamics of cortical contrast adaptation predict perception of signals in noise
Author
Angeloni, Christopher F. 1 ; Młynarski, Wiktor 2 ; Piasini, Eugenio 3   VIAFID ORCID Logo  ; Williams, Aaron M. 4 ; Wood, Katherine C. 5 ; Garami, Linda 5 ; Hermundstad, Ann M. 6   VIAFID ORCID Logo  ; Geffen, Maria N. 7   VIAFID ORCID Logo 

 University of Pennsylvania, Psychology Graduate Group, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Otorhinolaryngology, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 Ludwig Maximilian University of Munich, Faculty of Biology, Munich, Germany (GRID:grid.5252.0) (ISNI:0000 0004 1936 973X); Bernstein Center for Computational Neuroscience, Munich, Germany (GRID:grid.455093.e) 
 International School for Advanced Studies (SISSA), Trieste, Italy (GRID:grid.5970.b) (ISNI:0000 0004 1762 9868) 
 University of Pennsylvania, Department of Otorhinolaryngology, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Neuroscience Graduate Group, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 University of Pennsylvania, Department of Otorhinolaryngology, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, USA (GRID:grid.443970.d) 
 University of Pennsylvania, Department of Otorhinolaryngology, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Neuroscience Graduate Group, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Neuroscience, Department of Neurology, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
Pages
4817
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2848021333
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.