Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

End-to-end optimization of prosthetic vision

Jaap de Ruyter van Steveninck, Umut Güçlü, Richard van Wezel, Marcel van Gerven
doi: https://doi.org/10.1101/2020.12.19.423601
Jaap de Ruyter van Steveninck
1Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
2Department of Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: j.deruyter@donders.ru.nl
Umut Güçlü
1Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard van Wezel
2Department of Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
3Biomedical Signal and Systems, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marcel van Gerven
1Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a non-trivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments we show that such an approach is able to automatically find a task-specific stimulation protocol. The presented approach is highly modular and could be extended to dynamically optimize prosthetic vision for everyday tasks and requirements of the end-user.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted December 21, 2020.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
End-to-end optimization of prosthetic vision
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
End-to-end optimization of prosthetic vision
Jaap de Ruyter van Steveninck, Umut Güçlü, Richard van Wezel, Marcel van Gerven
bioRxiv 2020.12.19.423601; doi: https://doi.org/10.1101/2020.12.19.423601
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
End-to-end optimization of prosthetic vision
Jaap de Ruyter van Steveninck, Umut Güçlü, Richard van Wezel, Marcel van Gerven
bioRxiv 2020.12.19.423601; doi: https://doi.org/10.1101/2020.12.19.423601

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioengineering
Subject Areas
All Articles
  • Animal Behavior and Cognition (2535)
  • Biochemistry (4983)
  • Bioengineering (3487)
  • Bioinformatics (15242)
  • Biophysics (6914)
  • Cancer Biology (5404)
  • Cell Biology (7756)
  • Clinical Trials (138)
  • Developmental Biology (4543)
  • Ecology (7162)
  • Epidemiology (2059)
  • Evolutionary Biology (10240)
  • Genetics (7522)
  • Genomics (9802)
  • Immunology (4869)
  • Microbiology (13250)
  • Molecular Biology (5151)
  • Neuroscience (29495)
  • Paleontology (203)
  • Pathology (838)
  • Pharmacology and Toxicology (1468)
  • Physiology (2143)
  • Plant Biology (4759)
  • Scientific Communication and Education (1013)
  • Synthetic Biology (1339)
  • Systems Biology (4015)
  • Zoology (770)