Documento de conferencia

Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm

Journal cp
International Journal of Neural Systems
  • Volumen: 26
  • Número: 7
  • Fecha: 01 noviembre 2016
  • ISSN: 01290657
  • Tipo de fuente: Revista
  • DOI: 10.1142/S0129065716500210
  • Tipo de documento: Documento de conferencia
  • Editorial: World Scientific Publishing Co. Pte Ltdwspc@wspc.com.sg
© 2016 World Scientific Publishing Company.The retina is a very complex neural structure, which contains many different types of neurons interconnected with great precision, enabling sophisticated conditioning and coding of the visual information before it is passed via the optic nerve to higher visual centers. The encoding of visual information is one of the basic questions in visual and computational neuroscience and is also of seminal importance in the field of visual prostheses. In this framework, it is essential to have artificial retina systems to be able to function in a way as similar as possible to the biological retinas. This paper proposes an automatic evolutionary multi-objective strategy based on the NSGA-II algorithm for tuning retina models. Four metrics were adopted for guiding the algorithm in the search of those parameters that best approximate a synthetic retinal model output with real electrophysiological recordings. Results show that this procedure exhibits a high flexibility when different trade-offs has to be considered during the design of customized neuro prostheses.

Palabras clave del autor

    Palabras clave indexadas

      Detalles de financiación