There is a fundamental gap in understanding how the parallel processing of visual information performed by the retina is modified by light adaptation and the circadian cycle. The existence of this gap precludes an understanding of how visual scenes are encoded by the retina, and decoded by the brain, across the diverse visual environments encountered from night to day. The objective here is to identify how light adaptation with the circadian cycle alters retinal ganglion cell (RGC) function. RGCs consist of ~20 distinct types. Each type carries different information about the visual scene to the brain. Cumulatively, the RGCs send this information to ~25 different brain areas. To cope with the diverse lighting conditions of natural environments, light adaptation and the circadian cycle dovetail to dynamically modulate retinal function. Dopamine and melatonin are two key signaling molecules in this process. Yet, their net impact on modulating visual signals across diverse RGC types remains elusive. The central hypothesis is that light adaptation, bolstered by the circadian cycle, exerts different changes in different RGC types. To test this hypothesis, this proposal has three specific aims: (1) determine the impact of light adaptation on response properties in many RGC types; (2) determine the impact of circadian cycle on response properties in many RGC types; and (3) determine the impact of two key circadian signals, dopamine and melatonin, on RGC function. Electrophysiological recording will be made from hundreds of RGCs simultaneously using a large-scale multielectrode array. Diverse visual stimuli will be presented to the isolated retina while recording from the RGCs to determine their light response properties. These response properties will be measured at different light levels and during different phases of the circadian cycle. Mouse lines with disrupted dopamine and/or melatonin signaling, will be used to understand how these molecules alter RGC responses under diverse lighting conditions. The proposed research is innovative because it utilizes a recently developed large-scale parallel neural recording technology to determine the interplay between parallel processing, light adaptation and the circadian cycle. The proposed research is significant because it will provide major advances in our understanding of how neural populations in the retina adapt to changes in light level, and how this adaptation is modulated by the circadian cycle. Further, these data will provide strong constraints in three areas: (1) how cellular and circuit mechanisms in the retina contribute to light adaptation and circadian modulation of visual signaling; (2) how central visual areas process retinal signals across light levels between night and day; and (3) the development of computational and theoretical principles for describing and explaining the functional impact of light adaptation. Ultimately this research will unify our understanding of the two most central functions of the neural retina: establishing the parallel processing of visual information and adapting to diverse visual environments.

Public Health Relevance

Restoring vision to those with retinal degeneration, whether through gene-therapy, stem cells, or retinal prosthetics, requires identifying and understanding the differences between healthy and degenerating retina. Thus, this proposal is relevant to public health because it targets advancing our knowledge about the mechanisms of normal retinal function. Furthermore, it targets Goals and Objectives outlined in the NEI's Retinal Diseases Program to better understand light adaptation and the retinal circadian cycle.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY024567-03
Application #
8910742
Study Section
Neurotransporters, Receptors, and Calcium Signaling Study Section (NTRC)
Program Officer
Greenwell, Thomas
Project Start
2014-09-01
Project End
2019-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Duke University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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