title: Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm.
abstract: 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.
authors.affiliation: 1 Department of Computer Technology, University of Alicante, Carretera San Vicente s/n, Alicante 03690, Spain.
authors.forename: Antonio
authors.initials: A
authors.lastname: Martínez-Álvarez
authors.affiliation: 1 Department of Computer Technology, University of Alicante, Carretera San Vicente s/n, Alicante 03690, Spain.
authors.forename: Rubén
authors.initials: R
authors.lastname: Crespo-Cano
authors.affiliation: 2 Institute of Bioengineering, University Miguel Hernández and CIBER BBN, Av. de la Universidad s/n, Elche (Alicante), 03202, Spain.
authors.forename: Ariadna
authors.initials: A
authors.lastname: Díaz-Tahoces
authors.affiliation: 1 Department of Computer Technology, University of Alicante, Carretera San Vicente s/n, Alicante 03690, Spain.
authors.forename: Sergio
authors.initials: S
authors.lastname: Cuenca-Asensi
authors.affiliation: 3 Telecomm School, Universidad Politécnica de Cartagena, Campus Muralla del Mar s/n, Cartagena (Murcia), 30202, Spain.
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Ferrández Vicente
authors.affiliation: 2 Institute of Bioengineering, University Miguel Hernández and CIBER BBN, Av. de la Universidad s/n, Elche (Alicante), 03202, Spain.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Fernández
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D000818:Animals; D002875:Chromosomes / Q000235:genetics / Q000378:metabolism; D005240:Feasibility Studies; D008810:Mice, Inbred C57BL; D008839:Microelectrodes; D008959:Models, Neurological; D058117:Neural Prostheses; D010363:Pattern Recognition, Automated / Q000379:methods*; D010775:Photic Stimulation; D012160:Retina / Q000502:physiology; D012165:Retinal Ganglion Cells / Q000502:physiology; D046509:Tissue Culture Techniques; D014785:Vision, Ocular / Q000502:physiology; D014793:Visual Cortex / Q000502:physiology; D014796:Visual Perception / Q000502:physiology
keywords: NSGA-II; Retinal modeling; evolutionary search; multi-objective optimization; visual neuroprostheses