RESUMEN
Understanding how >30 types of retinal ganglion cells (RGCs) in the mouse retina each contribute to visual processing in the brain will require more tools that label and manipulate specific RGCs. We screened and analyzed retinal expression of Cre recombinase using 88 transgenic driver lines. In many lines, Cre was expressed in multiple RGC types and retinal cell classes, but several exhibited more selective expression. We comprehensively mapped central projections from RGCs labeled in 26 Cre lines using viral tracers, high-throughput imaging, and a data processing pipeline. We identified over 50 retinorecipient regions and present a quantitative retina-to-brain connectivity map, enabling comparisons of target-specificity across lines. Projections to two major central targets were notably correlated: RGCs projecting to the outer shell or core regions of the lateral geniculate projected to superficial or deep layers within the superior colliculus, respectively. Retinal images and projection data are available online at http://connectivity.brain-map.org.
Asunto(s)
Retina/fisiología , Células Ganglionares de la Retina/fisiología , Vías Visuales/fisiología , Animales , Integrasas/metabolismo , Ratones , Ratones Transgénicos , Retina/metabolismo , Células Ganglionares de la Retina/metabolismo , Colículos Superiores/metabolismo , Colículos Superiores/fisiologíaRESUMEN
Three-dimensional (3D) bioimaging, visualization and data analysis are in strong need of powerful 3D exploration techniques. We develop virtual finger (VF) to generate 3D curves, points and regions-of-interest in the 3D space of a volumetric image with a single finger operation, such as a computer mouse stroke, or click or zoom from the 2D-projection plane of an image as visualized with a computer. VF provides efficient methods for acquisition, visualization and analysis of 3D images for roundworm, fruitfly, dragonfly, mouse, rat and human. Specifically, VF enables instant 3D optical zoom-in imaging, 3D free-form optical microsurgery, and 3D visualization and annotation of terabytes of whole-brain image volumes. VF also leads to orders of magnitude better efficiency of automated 3D reconstruction of neurons and similar biostructures over our previous systems. We use VF to generate from images of 1,107 Drosophila GAL4 lines a projectome of a Drosophila brain.