SAMUEL SMITH SAMUEL.SMITH4@NOTTINGHAM.AC.UK
Assistant Professor
Inferring the basis of binaural detection with a modified autoencoder
Smith, Samuel; Sollini, Joseph; Akeroyd, Michael A.
Authors
JOSEPH SOLLINI JOSEPH.SOLLINI@NOTTINGHAM.AC.UK
Nottingham Research Fellow
Professor MICHAEL AKEROYD MICHAEL.AKEROYD@NOTTINGHAM.AC.UK
Professor of Hearing Sciences
Abstract
The binaural system utilizes interaural timing cues to improve the detection of auditory signals presented in noise. In humans, the binaural mechanisms underlying this phenomenon cannot be directly measured and hence remain contentious. As an alternative, we trained modified autoencoder networks to mimic human-like behavior in a binaural detection task. The autoencoder architecture emphasizes interpretability and, hence, we “opened it up” to see if it could infer latent mechanisms underlying binaural detection. We found that the optimal networks automatically developed artificial neurons with sensitivity to timing cues and with dynamics consistent with a cross-correlation mechanism. These computations were similar to neural dynamics reported in animal models. That these computations emerged to account for human hearing attests to their generality as a solution for binaural signal detection. This study examines the utility of explanatory-driven neural network models and how they may be used to infer mechanisms of audition.
Citation
Smith, S., Sollini, J., & Akeroyd, M. A. (2023). Inferring the basis of binaural detection with a modified autoencoder. Frontiers in Neuroscience, 17, Article 1000079. https://doi.org/10.3389/fnins.2023.1000079
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 2, 2023 |
Online Publication Date | Jan 26, 2023 |
Publication Date | Jan 26, 2023 |
Deposit Date | Jan 4, 2023 |
Publicly Available Date | Mar 29, 2024 |
Journal | Frontiers in Neuroscience |
Print ISSN | 1662-4548 |
Electronic ISSN | 1662-453X |
Publisher | Frontiers Media SA |
Peer Reviewed | Peer Reviewed |
Volume | 17 |
Article Number | 1000079 |
DOI | https://doi.org/10.3389/fnins.2023.1000079 |
Keywords | General Neuroscience |
Public URL | https://nottingham-repository.worktribe.com/output/15712787 |
Publisher URL | https://www.frontiersin.org/articles/10.3389/fnins.2023.1000079/full |
Files
2023 SmithSolliniAkeroyd FrontiersNeuroscience NeuralNetworkBMLDS Authoracceptedmanuscript
(4.5 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Image 1
(467 Kb)
Other
Image 2
(426 Kb)
Other
You might also like
Serratus anterior weakness is a key determinant of arm-assisted standing difficulties
(2019)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search