Author

Lloyd Pellatt

University College LondonORCID 0000-0001-8278-5435Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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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

Fotios DrakopoulosiD· 2 shared Nicholas A. LesicaiD· 2 shared Shievanie Sabesan· 2 shared Yiqing XiaiD· 2 shared A. Fragner· 1 shared Andreas Fragner· 1 shared Tingchen GongiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 19 mutual co-author links

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2 shared papersBioengineering

Fotios DrakopoulosORCID

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2 papers

Recent·Most cited

BioengineeringbioRxivPreprintMay 12, 2026

Optimal hearing aid design through restoration of the neural code

Fotios Drakopoulos, Lloyd Pellatt, Shievanie Sabesan…·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.

DOI 10.64898/2026.02.02.703273

mouseelectrophysiology

𝕏 PostBluesky

BioengineeringNature Machine IntelligencePeer-reviewedSep 18, 2025

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

Fotios Drakopoulos, Lloyd Pellatt, Shievanie Sabesan…·Nicholas A. Lesica

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

12 citationstop 4%

mouseelectrophysiology

𝕏 PostBluesky