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 |