52 research outputs found
How specific classes of retinal cells contribute to vision: A Computational Model
Get PDFInternational audienceVision begins with the photoreceptors converting light from the visual scene into electrical signals, compressing our visual world into a code of action potentials sent to the brain by the retinal ganglion cells (RGCs). A human retina contains almost 1 million RGCs and each of these cells interprets different features of the visual scene (shape, motion, color, etc.). It is all these parallel streams of information received by the brain, that eventually lead to visual perception. Currently, there exist over 30 RGCs subtypes based on: Ø common anatomical features, Ø functional properties, Ø common gene expression. Contemporary questions: ✓What role does each RGC subtype play in vision? ✓How is vision impaired if one of these subtypes is inactivated? ☛ We propose a novel approach combining for the first time pharmacogenetics, electrophysiology, morphology, behavior and mathematical modelling in order to selectively inactivate specific RGCs types and decipher their role in vision, both at the single cell and population level
Investigating how specific classes of retinal cells contribute to vision with a multi-layered simulator
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A novel approach to the functional classification of retinal ganglion cells
Get PDFRetinal neurons are remarkedly diverse based on structure, function and genetic identity. Classifying these cells is a challenging task, requiring multimodal methodology. Here, we introduce a novel approach for retinal ganglion cell (RGC) classification, based on pharmacogenetics combined with immunohistochemistry and large-scale retinal electrophysiology. Our novel strategy allows grouping of cells sharing gene expression and understanding how these cell classes respond to basic and complex visual scenes. Our approach consists of several consecutive steps. First, the spike firing frequency is increased in RGCs co-expressing a certain gene (Scnn1a or Grik4) using excitatory DREADDs (designer receptors exclusively activated by designer drugs) in order to single out activity originating specifically from these cells. Their spike location is then combined with post hoc immunostaining, to unequivocally characterize their anatomical and functional features. We grouped these isolated RGCs into multiple clusters based on spike train similarities. Using this novel approach, we were able to extend the pre-existing list of Grik4-expressing RGC types to a total of eight and, for the first time, we provide a phenotypical description of 13 Scnn1a-expressing RGCs. The insights and methods gained here can guide not only RGC classification but neuronal classification challenges in other brain regions as well
Biovision project-team: Biological vision: integrative models and vision aid systems for visually impaired people
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