Retinal Ganglion Cell Population Codes From Starlight to Sunlight

Loading...
Thumbnail Image

Date

2020

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

154
views
21
downloads

Abstract

The retina signals visual information to the brain with the parallel channels of different retinal ganglion cell (RGC) types, whose signals ultimately lead to visual perception. Between cloudy nights and sunny days, the retina must combat the trillion-fold change in mean light intensity to successfully convey visual information. Critically, the nature of both signal and noise in RGC populations is altered across this broad range of light levels, creating a rich problem of how visual messages are encoded by the retina and transmitted to the brain. This thesis addresses these topics using large-scale multielectrode array recordings of RGC populations in different light conditions. In Chapter 2, I characterize how retinal signaling is altered over a wide range of light intensities. Chapter 3 investigates how adaptation impacts visual encoding of different RGC types. My results suggest that although retinal computations change substantially over light conditions, there are some elements of visual encoding that are invariant to light adaptation. Finally, Chapter 4 examines adaptation-induced changes in the structure of correlated activity and the subsequent impact on processing retinal output. The findings of this chapter clarify the nature of RGC responses crucial for downstream readout across light levels. Overall, this work identifies aspects of RGC activity that are important for encoding visual information and decoding retinal output from starlight to sunlight.

Department

Description

Provenance

Citation

Citation

Ruda, Kiersten (2020). Retinal Ganglion Cell Population Codes From Starlight to Sunlight. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/22215.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.