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REHEAR: Reverse Engineered Hearing Evaluation for Auditory-neuropathy Recognition

Project description

Precision diagnosis of a poorly understood hearing disorder

Auditory neuropathy spectrum disorder affects up to 10 % of people with hearing loss. Unlike typical hearing loss, affected individuals can detect sounds but struggle to understand speech because the auditory nerve transmits signals with disrupted timing. Current diagnostic tools cannot identify the specific neural mechanisms involved, making treatment selection unpredictable. With the support of the Marie Skłodowska-Curie Actions programme, the REHEAR project is working on the first computational diagnostic framework for auditory neuropathy, using mathematical optimisation and AI. The goal is to convert neural dysfunction patterns into targeted speech tests that make underlying neural problems detectable. This approach will be validated in hearing and cochlear implant users, paving the way to precision diagnosis and improved treatment.

Objective

"Auditory Neuropathy Spectrum Disorder (ANSD) affects up to 10% of individuals with hearing loss. Unlike typical cases, people with ANSD detect sounds but struggle with speech understanding due to disrupted auditory nerve timing. Current tests cannot identify specific neural mechanisms, making treatment unpredictable. ANSD patients often cycle through multiple failed treatments - hearing aids provide minimal benefit, and cochlear implant outcomes vary dramatically from excellent to poor. This creates prolonged periods of communication difficulty during critical developmental years for children and significant quality-of-life impacts for adults. Cochlear implants provide unique access to neural responses via electrical recordings (ECAPs), enabling mechanism-specific diagnosis. This project develops the first computational-to-clinical bridge for ANSD using reverse engineering: instead of measuring neural dysfunction directly, we embed ANSD-specific disruption patterns into speech materials, creating diagnostic tests that make neural problems ""hearable."" Two complementary frameworks—mathematical optimization and AI-based learning—convert neural dysfunction patterns into targeted speech tests while preserving disorder-specific diagnostic signatures. The methodology includes three work packages: developing computational frameworks, validating through behavioral experiments with normal-hearing listeners (n=40) and cochlear implant users (n=12-15 each) alongside neural validation, and optimizing clinical protocols. Based at University Hospital Zurich's Deep Hearing Lab under Prof. Goehring's supervision, this fellowship advances expertise in computational neuroscience and clinical translation, delivering the first validated framework for ANSD subtype diagnosis and precision hearing care for thousands of patients annually across Europe, with potential healthcare savings through reduced diagnostic workup times and improved treatment matching.






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Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITAT ZURICH
Net EU contribution
€ 307 958,88
Address
RAMISTRASSE 71
8006 Zurich
Switzerland
Region
Schweiz/Suisse/Svizzera Zürich Zürich
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data