GSP Cochlea: A graph signal processing approach for studying sound encoding
Humans are able to hear in a variety of complicated acoustic environments. This feat begins in the peripheral auditory system, where the cochlea collects and transmits thousands of individual bits of sound data to the brain. Here, we introduce GSP Cochlea: a graph signal processing-based framework to investigate and visualize sound encoding. We show that a cochlea graph with a mesh topology provides a mechanism of denoising, efficient information transfer, and modular processing. We demonstrate an application to assess hearing loss as more than just a decibel loss at particular frequencies of sound but also a significant change to the cochlea graph architecture. GSP Cochlea is a generalized approach that provides new insight into the higher-level functional activity of the inner ear.
Authors
- Santiago Segarra (ORCID: https://orcid.org/0000-0002-8408-9633)
- Melia E. Bonomo (ORCID: https://orcid.org/0000-0002-1551-5731)
- Robert M. Raphael (ORCID: https://orcid.org/0000-0003-4986-7847)
Institutions
- Rice University (US)
Publication Details
- Journal
- PNAS Nexus
- Published
- 2026-04-21
- DOI
- https://doi.org/10.1093/pnasnexus/pgag134
- Primary Topic
- Hearing, Cochlea, Tinnitus, Genetics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Rice University
- U.S. National Library of Medicine