@article {69439, title = {Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster}, journal = {Cell}, volume = {187}, year = {2024}, month = {2024 May 09}, pages = {2574-2594.e23}, abstract = {

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87\% for individual synapses, 94\% for neurons, and 91\% for known cell types across a D.\ melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

}, keywords = {Animals, Brain, Connectome, Drosophila melanogaster, gamma-Aminobutyric Acid, Microscopy, Electron, Neural Networks, Computer, Neurons, Neurotransmitter Agents, Synapses}, issn = {1097-4172}, doi = {10.1016/j.cell.2024.03.016}, author = {Eckstein, Nils and Bates, Alexander Shakeel and Champion, Andrew and Du, Michelle and Yin, Yijie and Schlegel, Philipp and Lu, Alicia Kun-Yang and Rymer, Thomson and Finley-May, Samantha and Paterson, Tyler and Parekh, Ruchi and Dorkenwald, Sven and Matsliah, Arie and Yu, Szi-Chieh and McKellar, Claire and Sterling, Amy and Eichler, Katharina and Costa, Marta and Seung, Sebastian and Murthy, Mala and Hartenstein, Volker and Jefferis, Gregory S X E and Funke, Jan} } @article {49095, title = {NeuroStorm: accelerating brain science discovery in the cloud.}, journal = {arXiv}, year = {2018}, month = {2018 Mar 09}, abstract = {

Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.

}, url = {https://arxiv.org/abs/1803.03367}, author = {Kiar, Gregory and Anderson, Robert J and Baden, Alex and Badea, Alexandra and Bridgeford, Eric W and Champion, Andrew and Chandrashekar, Jayaram and Collman, Forrest and Duderstadt, Brandon and Evans, Alan C and Engert, Florian and Falk, Benjamin and Glatard, Tristan and Roncal, William Gray and Kennedy, David N and Maitlin-Shepard and Marren, Ryan A and Nnaemeka, Onyeka and Perlman, Eric and Seshamani, Sharmishtaas} } @article {47062, title = {Quantitative neuroanatomy for connectomics in Drosophila.}, journal = {eLife}, year = {2016}, month = {2016 Mar 18}, pages = {e12059}, abstract = {

Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of\ Drosophila\ sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free {\textquoteright}twigs{\textquoteright} which branch off a single microtubule-containing {\textquoteright}backbone{\textquoteright}. Omission of individual twigs accounted for 96\% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.

}, doi = {10.7554/eLife.12059}, author = {Schneider-Mizell, Casey M. and Gerhard, Stephan and Longair, Mark and Kazimiers, Tom and Li, Feng and Zwart, Maarten and Champion, Andrew and Midgley, Frank and Fetter, Richard D and Saalfeld, Stephan and Cardona, Albert} }