Classifying Retinal Ganglion Cells for Bionic Vision

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dc.contributor.advisor Zrenner, Eberhart (Prof. Dr.)
dc.contributor.author Shabani, Hamed
dc.date.accessioned 2022-01-25T07:30:22Z
dc.date.available 2022-01-25T07:30:22Z
dc.date.issued 2022-01-25
dc.identifier.uri http://hdl.handle.net/10900/123506
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1235062 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-64870
dc.description.abstract Current retinal implants implement pulsate stimuli to activate the neural circuits of the retina. This type of stimulation can activate antagonist retinal pathways which lead to the improper perception of the visual scene. Developing a precise stimulation strategy with the ability to preferentially target retinal neural circuits is one of the alternative methods to improve the accuracy of restored vision. Previous studies tried to decipher the electrical properties of different retina ganglion cell (RGC) types by applying electrical Gaussian noise and estimating the electrical input filter of the cells. Sekhar et al reported that ON and OFF cells have different electrical input filters. In this study, we aimed to pursue the same goal by using a similar approach to assess the electrical profiles for a wider range of ganglion cell types. We implemented an array of visual stimuli along with an electrical noise stimulus to fully characterize the light and electrical response properties of both healthy and degenerated retina ganglion cells. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.ddc 600 de_DE
dc.subject.ddc 610 de_DE
dc.subject.other Bionic Vision en
dc.subject.other Retina en
dc.title Classifying Retinal Ganglion Cells for Bionic Vision en
dc.type PhDThesis de_DE
dcterms.dateAccepted 2021-09-29
utue.publikation.fachbereich Medizin de_DE
utue.publikation.fakultaet 4 Medizinische Fakultät de_DE
utue.publikation.noppn yes de_DE

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