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

Author

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

Subjects
connectome, brain regions, cell types, graph properties, connectome reconstuction methods, synapse detecton, Medicine, Science, Biology (General), QH301-705.5
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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2. A field guide for aging passerine nestlings using growth data and predictive modeling

Author

Audrey A. Sanchez, Andrew W. Bartlow, Allison M. Chan, Jeanne M. Fair, Aaron A. Skinner, Kelly Hutchins, Maria A. Musgrave, Emily M. Phillips, Brent E. Thompson, and Charles D. Hathcock

Subjects
Cavity-nesting, Nest boxes, Nestling development, Predictive models, Western Bluebird, Zoology, QL1-991
Abstract

Abstract Background Accurate nestling age is valuable for studies on nesting strategies, productivity, and impacts on reproductive success. Most aging guides consist of descriptions and photographs that are time consuming to read and subjective to interpret. The Western Bluebird (Sialia mexicana) is a secondary cavity-nesting passerine that nests in coniferous and open deciduous forests. Nest box programs for cavity-nesting species have provided suitable nesting locations and opportunities for data collection on nestling growth and development. Methods We developed models for predicting the age of Western Bluebird nestlings from morphometric measurements using model training and validation. These were developed for mass, tarsus, and two different culmen measurements. Results Our models were accurate to within less than a day, and each model worked best for a specific age range. The mass and tarsus models can be used to estimate the ages of Western Bluebird nestlings 0–10 days old and were accurate to within 0.5 days for mass and 0.7 days for tarsus. The culmen models can be used to estimate ages of nestlings 0–15 days old and were also accurate to within less than a day. The daily mean, minimum, and maximum values of each morphometric measurement are provided and can be used in the field for accurate nestling age estimations in real time. Conclusions The model training and validation procedures used here demonstrate that this method can create aging models that are highly accurate. The methods can be applied to any passerine species provided sufficient nestling morphometric data are available.

Published
2021
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4. 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

5. Author response: A connectome and analysis of the adult Drosophila central brain

Author

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

Subjects
biology, Connectome, Drosophila (subgenus), biology.organism_classification, Neuroscience
Published
2020
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6. 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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View/download PDF

7. 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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8. To overlap or not to overlap: context-dependent coordinated singing in lekking long-billed hermits

Author

Katarzyna Wojczulanis-Jakubas, Daniel J. Mennill, Marcelo Araya-Salas, Emily M. Phillips, and Timothy F. Wright

Subjects
0106 biological sciences, Masking (art), Communication, biology, business.industry, 05 social sciences, Life Sciences, Context (language use), biology.organism_classification, 010603 evolutionary biology, 01 natural sciences, Lek mating, Phaethornis longirostris, 0501 psychology and cognitive sciences, Animal Science and Zoology, Animal communication, 050102 behavioral science & comparative psychology, Alternation (linguistics), Singing, business, Association (psychology), Psychology, Biology, Ecology, Evolution, Behavior and Systematics
Abstract

When using signals to attract mates or defend resources, animals often overlap the voices of other individuals in close proximity. In such contexts signal masking is likely and animals would benefit by adopting behavioural strategies that modify the timing of signals to minimize the negative effects of masking or take advantage of its signalling value. Indeed, temporal coordination has been commonly described in a wide variety of taxa, but compelling evidence demonstrating that it arises as an active process is scarce. Here we investigate the degree of coordinated singing by lekking long-billed hermit hummingbirds, Phaethornis longirostris, in the Neotropics, using randomization tests to study the timing of vocal signals. We first demonstrate that a randomization statistical approach is robust at detecting coordinated singing in simulated data. Then, we show that long-billed hermits engage in vocal interactions in which either song alternation or song overlap is used. Furthermore, we show that singing behaviour varies with the distance between singers: hermits alternate their songs when they are in close proximity, and they overlap songs at farther distances. Birds achieve these two behaviours by modifying the time intervals between signals. The association between pattern of coordination and distance is not fully explained by any of the current hypotheses for song overlap and suggests that multiple context-dependent singing strategies could be involved. Our findings provide compelling evidence on vocal coordination as an active process in this species and validate an analytical approach that could be extended to investigate similar patterns in other taxa. © 2016 The Association for the Study of Animal Behaviour

Published
2017

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