Author

A. Fragner

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:electrophysiology· 2 Organism:mouse· 2 Research Focus:drug response / drug discovery· 1 Research Focus:synaptic & neural circuits· 1

Frequent Co-Authors

F. Drakopoulos· 1 shared Fotios DrakopoulosiD· 1 shared L. Pellatt· 1 shared Lloyd PellattiD· 1 shared N. A. Lesica· 1 shared Nicholas A. LesicaiD· 1 shared S. Sabesan· 1 shared Shievanie Sabesan· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioengineering

F. Drakopoulos

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2 papers

Recent·Most cited

Optimal hearing aid design through restoration of the neural code

Fotios Drakopoulos, Lloyd Pellatt, Shievanie Sabesan, Yiqing Xia, Tingchen Gong, A. Fragner, Nicholas A. Lesica

This paper develops a deep learning-based hearing aid that restores neural coding by simulating normal auditory processing in impaired brains, outperforming existing methods in distortion correction and phoneme recognition.

bioRxiv · May 12, 2026 · PreprintBioengineering

Modeling neural coding in the auditory midbrain with high resolution and accuracy

F. Drakopoulos, L. Pellatt, S. Sabesan, Y. Xia, A. Fragner, N. A. Lesica

The paper introduces ICNet, a deep learning model that accurately simulates neural dynamics in the auditory midbrain across various sounds, including speech.

bioRxiv · Jun 17, 2024Bioengineering