@article {68258, title = {NeuronBridge: an intuitive web application for neuronal morphology search across large data sets}, journal = {BMC Bioinformatics}, volume = {25}, year = {2024}, month = {2024 Mar 15}, pages = {114}, abstract = {

Background

Neuroscience research in\ Drosophila\ is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome{\textquoteright}s structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities.

Results

Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine.

Conclusions

NeuronBridge fills a critical gap in the\ Drosophila\ research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at\ http://neuronbridge.janelia.org.

}, doi = {10.1186/s12859-024-05732-7}, url = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-024-05732-7}, author = {Jody Clements and Cristian Goina and Philip M. Hubbard and Takashi Kawase and Donald J. Olbris and Hideo Otsuna and Robert Svirskas and Konrad Rokicki} } @article {69146, title = {Song Torrent: A modular, open-source 96-chamber audio and video recording apparatus with optogenetic activation and inactivation capabilities for Drosophila}, journal = {bioRxiv}, year = {2024}, month = {2024 Jan 10}, abstract = {

Background

Results

Implications

}, doi = {10.1101/2024.01.09.574712}, url = {https://doi.org/10.1101/2024.01.09.574712}, author = {Steve Sawtelle and Lakshmi Narayan and Yun Ding and Elizabeth Kim and Emily L. Behrman and Joshua L. Lillvis and Takashi Kawase and David L. Stern} } @article {67849, title = {Rapid reconstruction of neural circuits using tissue expansion and lattice light sheet microscopy}, journal = {eLife}, year = {2022}, month = {2022 Oct 26}, abstract = {

Electron microscopy (EM) allows for the reconstruction of dense neuronal connectomes but suffers from low throughput, limiting its application to small numbers of reference specimens. We developed a protocol and analysis pipeline using tissue expansion and lattice light-sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many samples with single synapse resolution and molecular contrast. We validate this approach in\ Drosophila, demonstrating that it yields synaptic counts similar to those obtained by EM, can be used to compare counts across sex and experience, and to correlate structural connectivity with functional connectivity. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

}, doi = {10.7554/eLife.81248}, url = {https://doi.org/10.7554/eLife.81248}, author = {Joshua L. Lillvis and Hideo Otsuna and Xiaoyu Ding and Igor Pisarev and Takashi Kawase and Jennifer Colonell and Konrad Rokicki and Cristian Goina and Ruixuan Gao and Amy Hu and Kaiyu Wang and John Bogovic and Daniel E. Milkie and Edward S. Boyden and Stephan Saalfeld and Paul W. Tillberg and Barry J. Dickson} }