ArticleScientific reports2017
Large scale matching of function to the genetic identity of retinal ganglion cells.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- A novel approach to the functional classification of retinal ganglion cells.Open biology · 2022Article
- Hybrid Electrical and Optical Neural Interfaces.Journal of micromechanics and microengineering : structures, devices, and systems · 2021Article
- Towards optogenetic vision restoration with high resolution.PLoS computational biology · 2020Article
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7 authors.
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Abstract
Understanding the role of neurons in encoding and transmitting information is a major goal in neuroscience. This requires insight on the data-rich neuronal spiking patterns combined, ideally, with morphology and genetic identity. Electrophysiologists have long experienced the trade-offs between anatomically-accurate single-cell recording techniques and high-density multi-cellular recording methods with poor anatomical correlations. In this study, we present a novel technique that combines large-scale micro-electrode array recordings with genetic identification and the anatomical location of the retinal ganglion cell soma. This was obtained through optogenetic stimulation and subsequent confocal imaging of genetically targeted retinal ganglion cell sub-populations in the mouse. With the many molecular options available for optogenetic gene expression, we view this method as a versatile tool for matching function to genetic classifications, which can be extended to include morphological information if the density of labelled cells is at the correct level.
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