The difficulty of retrieving high-resolution, in vivo evidence of the proliferative and migratory processes occurring in neural germinal zones has limited our understanding of neurodevelopmental mechanisms. Here, we used a connectomic approach using a high-resolution, serial-sectioning scanning electron microscopy volume to investigate the laminar cytoarchitecture of the transient external granular layer (EGL) of the developing cerebellum, where granule cells coordinate a series of mitotic and migratory events. By integrating image segmentation, three-dimensional reconstruction, and deep-learning approaches, we found and characterized anatomically complex intercellular connections bridging pairs of cerebellar granule cells throughout the EGL. Connected cells were either mitotic, migratory, or transitioning between these two cell stages, displaying a chronological continuum of proliferative and migratory events never previously observed in vivo at this resolution. This unprecedented ultrastructural characterization poses intriguing hypotheses about intercellular connectivity between developing progenitors and its possible role in the development of the central nervous system.

The difficulty of retrieving high-resolution, in vivo evidence of the proliferative- and migratory processes occurring in neural germinal zones has limited our understanding of neurodevelopmental mechanisms. Here, we employed a connectomic approach using a high-resolution, serial-sectioning scanning electron microscopy volume to investigate the laminar cytoarchitecture of the transient external granular layer (EGL) of the developing cerebellum, where granule cells coordinate a series of mitotic and migratory events. By integrating image segmentation, 3D reconstruction, and deep learning approaches, we discovered and characterized anatomically complex intercellular connections bridging pairs of cerebellar granule cells throughout the EGL. Connected cells were either mitotic, migratory, or transitioning between these two cell stages, displaying a chronological continuum of proliferative and migratory events never previously observed in vivo at this resolution. This unprecedented ultra-structural characterization poses intriguing hypotheses about intercellular connectivity between developing progenitors, and its possible role in the development of the central nervous system (CNS).

The implementation of computational tools for analysis of microscopy images has been one of the most important technological innovations in biology, providing researchers unmatched capabilities to comprehend cell shape and connectivity. Most available tools frequently focus either on segmentation or morphological analysis, thus not providing an inclusive pipeline. We introduce CellWalker, a computational pipeline that streamlines and connects the segmentation step with the morphological analysis in a modular manner. This python-based pipeline starts with 'visible-source' IPython notebooks for segmentation of 2D/3D microscopy images using deep learning and visualization of the segmented images. The next module of CellWalker runs inside Blender, an open-source computer graphics software. This addon provides several morphometric analysis tools that can be used to calculate distances, volume, surface areas and to determine cross-sectional properties. It also includes tools to build skeletons, calculate distributions of sub-cellular organelles. Overall, CellWalker provides practical tools for segmentation and morphological analysis of microscopy images in the form of an open-source and modular pipeline which allows a complete access to fine-tuning of algorithms through visible source code while still retaining a result-oriented interface.