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1. A connectome and analysis of the adult Drosophila central brain

Author

Temour Tokhi, Tom Dolafi, Nneoma Okeoma, Tanya Wolff, Philip M Hubbard, Kazunori Shinomiya, Madelaine K Robertson, Gerald M. Rubin, Gregory S.X.E. Jefferis, Christopher J Knecht, Laramie Leavitt, Alia Suleiman, Satoko Takemura, Christopher Ordish, Jody Clements, Ian A. Meinertzhagen, Alexander Shakeel Bates, Takashi Kawase, Samantha Finley, Nicholas Padilla, Jackie Swift, C. Shan Xu, Stuart Berg, Tyler Paterson, Ashley L Scott, Erika Neace, Shirley Lauchie, Sean M Ryan, Emily M Joyce, Shin-ya Takemura, Tim Blakely, Michael A Cook, Christopher Patrick, Bryon Eubanks, Audrey Francis, Robert Svirskas, William T. Katz, Eric T. Trautman, Caroline Mooney, Ting Zhao, Nicole A Kirk, Megan Sammons, Brandon S Canino, Reed A. George, Louis K. Scheffer, Jolanta A. Borycz, Jon Thomson Rymer, Natasha Cheatham, Dagmar Kainmueller, Gary B. Huang, Khaled Khairy, Nicole Neubarth, Elliott E Phillips, John A. Bogovic, Neha Rampally, Larry Lindsey, Viren Jain, David G. Ackerman, Jane Anne Horne, Kelli Fairbanks, Lowell Umayam, Jens Goldammer, Emily M Phillips, Donald J. Olbris, Feng Li, Emily A Manley, Philipp Schlegel, Hideo Otsuna, Marta Costa, Stephen M. Plaza, Omotara Ogundeyi, Samantha Ballinger, Charli Maldonado, Kelsey Smith, Gary Patrick Hopkins, Vivek Jayaraman, Emily Tenshaw, Julie Kovalyak, Peter H. Li, Tansy Yang, Masayoshi Ito, Miatta Ndama, Claire Smith, Michał Januszewski, Alanna Lohff, SungJin Kim, Anne K Scott, Kei Ito, Iris Talebi, Jeremy Maitlin-Shepard, Nora Forknall, Marisa Dreher, Harald F. Hess, Sari McLin, Patricia K. Rivlin, Dennis A Bailey, Kenneth J. Hayworth, Octave Duclos, Caitlin Ribeiro, John J. Walsh, Zhiyuan Lu, Dorota Tarnogorska, Ruchi Parekh, Aya Shinomiya, Stephan Saalfeld, Margaret A Sobeski, Natalie L Smith, Chelsea X Alvarado, Scheffer, Louis K [0000-0002-3289-6564], Xu, C Shan [0000-0002-8564-7836], Januszewski, Michal [0000-0002-3480-2744], Lu, Zhiyuan [0000-0002-4128-9774], Takemura, Shin-ya [0000-0003-2400-6426], Huang, Gary B [0000-0002-9606-3510], Shinomiya, Kazunori [0000-0003-0262-6421], Maitlin-Shepard, Jeremy [0000-0001-8453-7961], Hubbard, Philip M [0000-0002-6746-5035], Katz, William T [0000-0002-9417-6212], Ackerman, David [0000-0003-0172-6594], Blakely, Tim [0000-0003-0995-5471], Bogovic, John [0000-0002-4829-9457], Kainmueller, Dagmar [0000-0002-9830-2415], Khairy, Khaled A [0000-0002-9274-5928], Li, Peter H [0000-0001-6193-4454], Trautman, Eric T [0000-0001-8588-0569], Bates, Alexander S [0000-0002-1195-0445], Goldammer, Jens [0000-0002-5623-8339], Wolff, Tanya [0000-0002-8681-1749], Svirskas, Robert [0000-0001-8374-6008], Schlegel, Philipp [0000-0002-5633-1314], Knecht, Christopher J [0000-0002-5663-5967], Alvarado, Chelsea X [0000-0002-5973-7512], Bailey, Dennis A [0000-0002-4675-8373], Borycz, Jolanta A [0000-0002-4402-9230], Canino, Brandon S [0000-0002-8454-865X], Cook, Michael [0000-0002-7892-6845], Dreher, Marisa [0000-0002-0041-9229], Eubanks, Bryon [0000-0002-9288-2009], Fairbanks, Kelli [0000-0002-6601-4830], Finley, Samantha [0000-0002-8086-206X], Forknall, Nora [0000-0003-2139-7599], Francis, Audrey [0000-0003-1974-7174], Joyce, Emily M [0000-0001-5794-6321], Kovalyak, Julie [0000-0001-7864-7734], Lauchie, Shirley A [0000-0001-8223-9522], Lohff, Alanna [0000-0002-1242-1836], McLin, Sari [0000-0002-9120-1136], Patrick, Christopher M [0000-0001-8830-1892], Phillips, Elliott E [0000-0002-4918-2058], Phillips, Emily M [0000-0001-7615-301X], Robertson, Madelaine K [0000-0002-1764-0245], Rymer, Jon Thomson [0000-0002-4271-6774], Ryan, Sean M [0000-0002-8879-6108], Sammons, Megan [0000-0003-4516-5928], Shinomiya, Aya [0000-0002-6358-9567], Smith, Natalie L [0000-0002-8271-9873], Swift, Jackie [0000-0003-1321-8183], Takemura, Satoko [0000-0002-2863-0050], Talebi, Iris [0000-0002-0173-8053], Tarnogorska, Dorota [0000-0002-7063-6165], Walsh, John J [0000-0002-7176-4708], Yang, Tansy [0000-0003-1131-0410], Horne, Jane Anne [0000-0001-9673-2692], Parekh, Ruchi [0000-0002-8060-2807], Jayaraman, Vivek [0000-0003-3680-7378], Costa, Marta [0000-0001-5948-3092], Jefferis, Gregory SXE [0000-0002-0587-9355], Ito, Kei [0000-0002-7274-5533], Saalfeld, Stephan [0000-0002-4106-1761], Rubin, Gerald M [0000-0001-8762-8703], Hess, Harald F [0000-0003-3000-1533], Plaza, Stephen M [0000-0001-7425-8555], Apollo - University of Cambridge Repository, Takemura, Shin-Ya [0000-0003-2400-6426], and Jefferis, Gregory Sxe [0000-0002-0587-9355]

Subjects
Male, Computer science, computational biology, 0302 clinical medicine, Drosophila Proteins, Research article, Biology (General), Neurons, Cognitive science, 0303 health sciences, biology, D. melanogaster, General Neuroscience, connectome, Brain, systems biology, graph properties, General Medicine, Human brain, Drosophila melanogaster, medicine.anatomical_structure, Connectome, Medicine, Drosophila, Female, synapse detecton, Insight, Function and Dysfunction of the Nervous System, cell types, Research Article, Computational and Systems Biology, brain regions, Connectomes, QH301-705.5, Ubiquitin-Protein Ligases, Science, connectome reconstuction methods, Small mammal, Central region, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, medicine, Animals, 030304 developmental biology, General Immunology and Microbiology, biology.organism_classification, synapse detection, Synapses, 030217 neurology & neurosurgery, Neuroscience
Abstract

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Published
2020

2. A Connectome and Analysis of the Adult Drosophila Central Brain

Author

C. Shan Xu, Jackie Swift, Miatta Ndama, Philipp Schlegel, SungJin Kim, Khaled Khairy, Christopher Ordish, Omotara Ogundeyi, Kelli Fairbanks, Kenneth J. Hayworth, Samantha Finley, Natasha Cheatham, Nora Forknall, Laramie Leavitt, Temour Tokhi, Nicole A Kirk, Shin-ya Takemura, Nneoma Okeoma, Robert Svirskas, Kazunori Shinomiya, Madelaine K Robertson, Caitlin Ribeiro, Christopher J Knecht, Emily M Joyce, Margaret A Sobeski, Ruchi Parekh, Alia Suleiman, Shirley Lauchie, Sean M Ryan, Iris Talebi, Harald F. Hess, Christopher Patrick, William T. Katz, Stephen M. Plaza, Dagmar Kainmueller, Feng Li, Natalie L Smith, Michał Januszewski, Satoko Takemura, Chelsea X Alvarado, Michael A Cook, Sari McLin, Tom Dolafi, Hideo Otsuna, Jeremy Maitin-Shepard, Kei Ito, Viren Jain, Donald J. Olbris, Tanya Wolff, Takashi Kawase, Tyler Paterson, Patricia K. Rivlin, Jolanta A. Borycz, Ashley L Scott, Claire Smith, Nicholas Padilla, Gary Patrick Hopkins, Vivek Jayaraman, Emily Tenshaw, Zhiyuan Lu, Stuart Berg, Dorota Tarnogorska, Samantha Ballinger, Audrey Francis, Julie Kovalyak, Ting Zhao, Anne K Scott, Alanna Lohff, Caroline Mooney, Brandon S Canino, Gary B. Huang, Jon Thomson Rymer, Marisa Dreher, Jody Clements, Nicole Neubarth, Larry Lindsey, John A. Bogovic, David G. Ackerman, Jane Anne Horne, Louis K. Scheffer, Elliott E Phillips, Lowell Umayam, Jens Goldammer, Eric T. Trautman, Emily A Manley, Charli Maldonado, Peter H. Li, Octave Duclos, John J. Walsh, Stephan Saalfeld, Reed A. George, Gerald M. Rubin, Philip M Hubbard, Ian A. Meinertzhagen, Emily M Phillips, Masayoshi Ito, Erika Neace, Kelsey Smith, Bryon Eubanks, Neha Rampally, Tim Blakely, Tansy Yang, Dennis A Bailey, Megan Sammons, and Aya Shinomiya

Subjects
0303 health sciences, Cell type, biology, Computer science, biology.organism_classification, Synapse, 03 medical and health sciences, 0302 clinical medicine, Connectome, Biological neural network, Drosophila melanogaster, Function and Dysfunction of the Nervous System, Neuroscience, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain.

Published
2020
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3. A Connectome of the Adult Drosophila Central Brain

Author

Audrey Francis, Ting Zhao, Feng Li, Megan Sammons, Madelaine K Robertson, SungJin Kim, Tyler Paterson, Philipp Schlegel, Chelsea X Alvarado, Viren Jain, Brandon S Canino, Omotara Ogundeyi, Nora Forknall, Dagmar Kainmueller, Tansy Yang, Natasha Cheatham, Neha Rampally, Caitlin Ribeiro, Kimothy L. Smith, Emily M Phillips, Ruchi Parekh, Jackie Swift, Donald J. Olbris, Takashi Kawase, Jon Thomson Rymer, Zhiyuan Lu, Nicholas Padilla, Christopher Ordish, Dorota Tarnogorska, Nicole Neubarth, Aya Shinomiya, Miatta Ndama, Samantha Finley, Stuart Berg, Erika Neace, Bryon Eubanks, John A. Bogovic, David G. Ackerman, Robert Svirskas, Sari McLin, Emily A Manley, Jane Anne Horne, Michael A Cook, Samantha Ballinger, Michał Januszewski, Jeremy Maitin-Shepard, Caroline Mooney, Nicole A Kirk, Shin-ya Takemura, Iris Talebi, Temour Tokhi, Kei K. Ito, Khaled Khairy, Stephen M. Plaza, Julie Kovalyak, Patricia K. Rivlin, Emily M Joyce, Kelli Fairbanks, Philip M Hubbard, Charli Maldonado, Nneoma Okeoma, Hideo Otsuna, Laurence F. Lindsey, Tim Blakely, Gerald M. Rubin, Alanna Lohff, William T. Katz, Anne K Scott, Mutsumi Ito, Peter H. Li, Ian A. Meinertzhagen, Natalie L Smith, Gary B. Huang, Dennis A Bailey, Reed A. George, Kenneth J. Hayworth, Tom Dolafi, Marisa Dreher, Tanya Wolff, Kazunori Shinomiya, Harald F. Hess, E.T. Troutman, Christopher J Knecht, Gary Patrick Hopkins, Alia Suleiman, Vivek Jayaraman, Emily Tenshaw, Octave Duclos, John J. Walsh, Stephan Saalfeld, Louis K. Scheffer, Elliott E Phillips, Lowell Umayam, Jens Goldammer, Sobeski, Jody Clements, Ashley L Scott, Shirley Lauchie, Sean M Ryan, Christopher Patrick, Jolanta A. Borycz, Claire Smith, C.S. Xu, and Laramie Leavitt

Subjects
Cell type, Computer science, Cell, Machine learning, computer.software_genre, Synapse, 03 medical and health sciences, 0302 clinical medicine, medicine, Biological neural network, 030304 developmental biology, Structure (mathematical logic), 0303 health sciences, biology, business.industry, Motor control, biology.organism_classification, Associative learning, medicine.anatomical_structure, Mushroom bodies, Identity (object-oriented programming), Connectome, Artificial intelligence, Drosophila melanogaster, Function and Dysfunction of the Nervous System, business, computer, 030217 neurology & neurosurgery
Abstract

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

Published
2020
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4. neuPrint: Analysis Tools for EM Connectomics

Author

Nicole Neubarth, Tom Dolafi, Stephen M. Plaza, Louis K. Scheffer, Lowell Umayam, Stuart Berg, and Jody Clements

Subjects
Connectomics, Graph database, Computer science, business.industry, Deep learning, Connectome, Artificial intelligence, computer.software_genre, business, computer, Data science, Abstraction (linguistics)
Abstract

Due to technological advances in electron microscopy (EM) and deep learning, it is now practical to reconstruct a connectome, a description of neurons and the connections between them, for significant volumes of neural tissue. The limited scope of past reconstructions meant they were primarily used by domain experts, and performance was not a serious problem. But the new reconstructions, of common laboratory creatures such as the fruit fly Drosophila melanogaster, upend these assumptions. These natural neural networks now contain tens of thousands of neurons and tens of millions of connections between them, with yet larger reconstructions pending, and are of interest to a large community of non-specialists. This requires new tools that are easy to use and efficiently handle large data. We introduce neuPrint to address these data analysis challenges. neuPrint is a database and analysis ecosystem that organizes connectome data in a manner conducive to biological discovery. In particular, we propose a data model that allows users to access the connectome at different levels of abstraction primarily through a graph database, neo4j, and its powerfully expressive query language Cypher. neuPrint is compatible with modern connectome reconstruction workflows, providing tools for assessing reconstruction quality, and offering both batch and incremental updates to match modern connectome reconstruction flows. Finally, we introduce a web interface and programmer API that targets a diverse user skill set. We demonstrate the effectiveness and efficiency of neuPrint through example database queries.

Published
2020
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