Cone-Driven, Geniculocortical Responses in Canine Models of Outer Retinal Disease

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Abstract

Purpose: Canine models of inherited retinal degeneration are used for proof of concept of emerging gene and cell-based therapies that aim to produce functional restoration of cone-mediated vision. We examined functional magnetic resonance imaging (MRI) measures of the postretinal response to cone-directed stimulation in wild-type (WT) dogs, and in three different retinal disease models. Methods: Temporal spectral modulation of a uniform field of light around a photopic background was used to target the canine L/M (hereafter “L”) and S cones and rods. Stimuli were designed to separately target the postreceptoral luminance (L+S) and chrominance (L–S) pathways, the rods, and all photoreceptors jointly (light flux). These stimuli were presented to WT, and mutant PDE6B-RCD1, RPGR-XLPRA2, and NPHP5-CRD2 dogs during pupillometry and functional MRI (fMRI). Results: Pupil responses in WT dogs to light flux, L+S, and rod-directed stimuli were consistent with responses being driven by cone signals alone. For WT animals, both luminance and chromatic (L–S) stimuli evoked fMRI responses in the lateral geniculate nucleus or visual cortex; RCD1 animals with predominant rod loss had similar responses. Responses to cone-directed stimulation were reduced in XLPRA2 and absent in CRD2. NPHP5 gene augmentation restored the cortical response to luminance stimulation in a CRD2 animal. Conclusions: Cone-directed stimulation during fMRI can be used to measure the integrity of luminance and chrominance responses in the dog visual system. The NPHP5-CRD2 model is appealing for studies of recovered cone function. Translational Relevance: fMRI assessment of cone-driven cortical response provides a tool to translate cell/gene therapies for vision restoration.

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Taskin, H. O., Wivel, J., Aguirre, G. D., Beltran, W. A., & Aguirre, G. K. (2024). Cone-Driven, Geniculocortical Responses in Canine Models of Outer Retinal Disease. Translational Vision Science and Technology, 13(1). https://doi.org/10.1167/tvst.13.1.18

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