Yamashita, S. | Search bioRxiv

bioRxiv2019

Connectivity characterization of the mouse basolateral amygdalar complex

The basolateral amygdalar complex (BLA) is implicated in behavioral processing ranging from fear acquisition to addiction. Newer methods like optogenetics have enabled the association of circuit-specific functionality to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. In this work, we applied computational analysis techniques to the results of our circuit-tracing experiments to create a foundational, comprehensive, multiscale connectivity atlas of the mouse BLA. The analyses identified three domains within the classically defined anterior BLA (BLAa) that house target-specific projection neurons with distinguishable cell body and dendritic morphologies. Further, we identify brain-wide targets of projection neurons located in the three BLAa domains as well as in the posterior BLA (BLAp), ventral BLA (BLAv), lateral (LA), and posterior basomedial (BMAp) nuclei. Projection neurons that provide input to each nucleus are also identifed. Functional characterization of some projection-defined BLA neurons were demonstrated via optogenetic and recording experiments. Hypotheses relating function to connection-defined BLA cell types are proposed.

neuroscience↗

bioRxiv2019

From heterogenous morphogenetic fields to homogeneous regions as a step towards understanding complex tissue dynamics

Within developing tissues, cell proliferation, cell motility, and other cell behaviors vary spatially, and this variability gives a complexity to the morphogenesis. Recently, novel formalisms have been developed to quantify tissue deformation and underlying cellular processes. A major challenge for the study of morphogenesis now is to objectively define tissue sub-regions exhibiting different dynamics. Here we propose a method to automatically divide a tissue into regions where the local deformation rate is homogeneous. This was achieved by several steps including image segmentation, clustering, and region boundary smoothing. We illustrate the use of the pipeline using a large dataset obtained during the metamorphosis of the Drosophila pupal notum. We also adapt it to determine regions where the time evolution of the local deformation rate is homogeneous. Finally, we generalize its use to find homogeneous regions for the cellular processes such as cell division, cell rearrangement, or cell size and shape changes. We also illustrate it on wing blade morphogenesis. This pipeline will contribute substantially to the analysis of complex tissue shaping and the biochemical and bio-mechanical regulations driving tissue morphogenesis. 1 Summary statementTissue morphogenesis is driven by multiple mechanisms. This study proposes a methodology to identify regions in the developing tissue, where each of the regions has distinctive cellular dynamics and deformation.

developmental biology↗