In the vertebrate retina, neurons process visual signals, generating feature selectivity in their activity levels. We use computational models to understand these behaviors by interpreting them mathematically. One component of this analysis is the spatial selectivity or receptive field, a property found in all visual sensory neurons. The neurons found in the retina can be classified into cell types, which share many properties. Some retinal neurons are connected by gap junction synapses, which are small pores between their cytoplasms, which convey low-latency signals between them.I have profiled two types of retinal ganglion cells (RGCs): the F-mini-ON and F-mini-OFF. I report the discovery of a systematic spatial offset between the ON and OFF receptive subfields in F-mini-ON. Surprisingly, this property does not come from spatially offset ON and OFF layer dendrites but instead arises from a network of electrical synapses via gap junctions to RGCs of a different type, the F-mini-OFF. I show that the asymmetric morphology and connectivity of these RGCs can explain their receptive field offset, and I use a multicell model to explore the effects of receptive field offset on the precision of edge-location representation in a population. This RGC network forms a new electrical channel combining the ON and OFF feedforward pathways within the output layer of the retina. I also performed a survey of the ganglion cell types of the W3-Thy1 mouse line, aligned to complete typology datasets, as a reference for use by the retinal neuroscience community.

Creator

• Cooler, Sam

DOI

• https://doi.org/10.21985/n2-mnbd-ft11

Subject

• Neurosciences

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:15450
• etdadmin_upload_792568

Keyword

• Vision
• Neuron
• Retina

Date created

• 2021-01-01

Resource type

• Dissertation

Rights statement

• In Copyright