The retina does not act as a simple camera, rather visual information goes through multiple layers of processing before it reaches the brain. Retinal ganglion cells (RGCs) are the output neurons of the retina and process visual information in the retina and then project into the brain. There are over 40 types of RGCs in the mouse each believed to carry parallel streams of information about different features of the visual environment. Cell types are defined by their gene expression patterns, morphology, and physiological responses to light. The area of space over which a cell will respond is called its receptive field. Receptive fields carry information about a particular region of space, polarity information, and more complex features. Cells are said to be feature selective if they strongly fire in response to a particular pattern of light, and how these computations occur is an active area of research. A majority of research into these computations focus on network mechanisms; however, the intrinsic properties of a neuron are also a powerful computational tool.First, I present a literature review that covers the common techniques for measuring and modeling receptive fields. Then using standardized measurement techniques, I determine which RGC subtypes are labeled by two different genes. Finally, I characterize a novel RGC type, the Bursty Suppressed-by-Contrast and investigate how its intrinsic properties contribute to its contrast response function. The work in this thesis lays the groundwork for studying RGC receptive fields and specifically, the contribution of intrinsic properties to feature selectivity computations.

Creator

• Wienbar, Sophia Rose

DOI

• https://doi.org/10.21985/n2-hv74-w248

Subject

• Neurosciences

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:16017
• etdadmin_upload_898849

Keyword

• Vision
• Retinal ganglion cells
• Neuroscience
• Retina

Date created

• 2022-01-01

Resource type

• Dissertation

Rights statement

• In Copyright