A biophysically detailed model of retinal degeneration
Neuroscience ePoster by Aiwen Xu and Michael Beyeler
Part of COSYNE 2023 posters, University of California, Santa Barbara; Computer Science; University of California, Santa Barbara
Friday
Abstract
Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. Although the processing of visual information in the healthy retina has been studied in detail, no comprehensive computational model exists that captures the many cell-level and network-level biophysical changes common to retinal degenerative diseases. To address this challenge, we developed a biophysically detailed model of the retinal circuitry and simulated the network-level response to both light and electrical stimulation. The model included 11,138 cells belonging to nine different cell types (cone photoreceptors, horizontal cells, ON/OFF bipolar cells, ON/OFF amacrine cells, and ON/OFF ganglion cells) confined to a 300 × 300 × 210 µm patch of the parafoveal retina. After verifying that the model reproduced seminal findings about the light response of retinal ganglion cells (RGCs), we systematically introduced anatomical and neurophysiological changes to the network and studied their effect on network activity. In early phases of degeneration, we found that cone outer segment truncation and cone cell death differentially affected ON and OFF RGC firing: whereas the light response of ON RGCs diminished more quickly than that of OFF RGCs, the spontanenous firing rate of OFF RGCs steadily increased. In late phases of degeneration, we found that migration and progressive death of inner retinal neurons led to a steady increase in electrical activation thresholds of both ON and OFF RGCs, especially for epiretinal stimulation. Our findings demonstrate how biophysical changes associated with retinal degeneration affect retinal responses to both light and electrical stimulation. A detailed model of the retina in health and disease has the potential to further our understanding of visual processing in the retina as well as inform the design of retinal prostheses.
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- Session
- Poster Session I
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