Prior to forming and refining synaptic connections, axons of projection neurons navigate long distances to their targets. While much is known about guidance cues for axon navigation through intermediate choice points, whether and how axons are organized within tracts is less clear. Here we analyze the organization of retinal ganglion cell (RGC) axons in the developing mouse retinogeniculate pathway. RGC axons are organized by both eye-specificity and topography in the optic nerve and tract: ipsilateral RGC axons are segregated from contralateral axons and are offset laterally in the tract relative to contralateral axon topographic position. To identify potential cell-autonomous factors contributing to the segregation of ipsilateral and contralateral RGC axons in the visual pathway, we assessed their fasciculation behavior in a retinal explant assay. Ipsilateral RGC neurites self-fasciculate more than contralateral neurites in vitro and maintain this difference in the presence of extrinsic chiasm cues. To further probe the role of axon self-association in circuit formation in vivo, we examined RGC axon organization and fasciculation in an EphB1-/- mutant, in which a subset of ipsilateral RGC axons aberrantly crosses the midline but targets the ipsilateral zone in the dorsal lateral geniculate nucleus on the opposite side. Aberrantly crossing axons retain their association with ipsilateral axons in the contralateral tract, indicating that cohort-specific axon affinity is maintained independently of guidance signals present at the midline. Our results provide a comprehensive assessment of RGC axon organization in the retinogeniculate pathway and suggest that axon self-association contributes to pre-target axon organization.
Pubmed ID: 29322522 RIS Download
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Gene expression data and maps of mouse central nervous system. Gene expression atlas of developing adult central nervous system in mouse, using in situ hybridization and transgenic mouse techniques. Collection of pictorial gene expression maps of brain and spinal cord of mouse. Provides tools to catalog, map, and electrophysiologically record individual cells. Application of Cre recombinase technologies allows for cell-specific gene manipulation. Transgenic mice created by this project are available to scientific community.
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View all literature mentionsMus musculus with name C57BL/6J from IMSR.
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View all literature mentionsStatistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.
View all literature mentionsA Python-based environment of open-source software for mathematics, science, and engineering. The core packages of SciPy include: NumPy, a base N-dimensional array package; SciPy Library, a fundamental library for scientific computing; and IPython, an enhanced interactive console.
View all literature mentionsSoftware package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.
View all literature mentionsNeurolucida is advanced scientific software for brain mapping, neuron reconstruction, anatomical mapping, and morphometry. Since its debut more than 20 years ago, Neurolucida has continued to evolve and has become the worldwide gold-standard for neuron reconstruction and 3D mapping. Neurolucida has the flexibility to handle data in many formats: using live images from digital or video cameras; stored image sets from confocal microscopes, electron microscopes, and scanning tomographic sources, or through the microscope oculars using the patented LucividTM. Neurolucida controls a motorized XYZ stage for integrated navigation through tissue sections, allowing for sophisticated analysis from many fields-of-view. Neurolucidas Serial Section Manager integrates unlimited sections into a single data file, maintaining each section in aligned 3D space for full quantitative analysis. Neurolucidas neuron tracing capabilities include 3D measurement and reconstruction of branching processes. Neurolucida also features sophisticated tools for mapping delineate and map anatomical regions for detailed morphometric analyses. Neurolucida uses advanced computer-controlled microscopy techniques to obtain accurate results and speed your work. Plug-in modules are available for confocal and MRI analysis, 3D solid modeling, and virtual slide creation. The user-friendly interface gives you rapid results, allowing you to acquire data and capture the full 3D extent of neurons and brain regions. You can reconstruct neurons or create 3D serial reconstructions directly from slides or acquired images, and Neurolucida offers full microscope control for brightfield, fluorescent, and confocal microscopes. Its added compatibility with 64-bit Microsoft Vista enables reconstructions with even larger images, image stacks, and virtual slides. Adding the Solid Modeling Module allows you to rotate and view your reconstructions in real time. Neurolucida is available in two separate versions Standard and Workstation. The Standard version enables control of microscope hardware, whereas the Workstation version is used for offline analysis away from the microscope. Neurolucida provides quantitative analysis with results presented in graphical or spreadsheet format exportable to Microsoft Excel. Overall, features include: - Tracing Neurons - Anatomical Mapping - Image Processing and Analysis Features - Editing - Morphometric Analysis - Hardware Integration - Cell Analysis - Visualization Features Sponsors: Neurolucida is supported by MBF Bioscience.
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