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Your search keyword '"Megan Sammons"' showing total 4 results
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4 results on '"Megan Sammons"'

1. Neural circuit mechanisms for transforming learned olfactory valences into wind-oriented movement

Author

Yoshinori Aso, Daichi Yamada, Daniel Bushey, Karen L Hibbard, Megan Sammons, Hideo Otsuna, Yichun Shuai, and Toshihide Hige

Subjects
dopamine, mushroom body, neural circuit, associative learning, olfactory navigation, memory, Medicine, Science, Biology (General), QH301-705.5
Abstract

How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in Drosophila, multiple compartments of the mushroom body act in parallel to assign a valence to a stimulus. Here, we show that appetitive memories stored in different compartments induce different levels of upwind locomotion. Using a photoactivation screen of a new collection of split-GAL4 drivers and EM connectomics, we identified a cluster of neurons postsynaptic to the mushroom body output neurons (MBONs) that can trigger robust upwind steering. These UpWind Neurons (UpWiNs) integrate inhibitory and excitatory synaptic inputs from MBONs of appetitive and aversive memory compartments, respectively. After formation of appetitive memory, UpWiNs acquire enhanced response to reward-predicting odors as the response of the inhibitory presynaptic MBON undergoes depression. Blocking UpWiNs impaired appetitive memory and reduced upwind locomotion during retrieval. Photoactivation of UpWiNs also increased the chance of returning to a location where activation was terminated, suggesting an additional role in olfactory navigation. Thus, our results provide insight into how learned abstract valences are gradually transformed into concrete memory-driven actions through divergent and convergent networks, a neuronal architecture that is commonly found in the vertebrate and invertebrate brains.

Published
2023
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2. Hierarchical architecture of dopaminergic circuits enables second-order conditioning in Drosophila

Author

Daichi Yamada, Daniel Bushey, Feng Li, Karen L Hibbard, Megan Sammons, Jan Funke, Ashok Litwin-Kumar, Toshihide Hige, and Yoshinori Aso

Subjects
dopamine, associative learning, higher order conditioning, EM connectome, neural circuits, mushroom body, Medicine, Science, Biology (General), QH301-705.5
Abstract

Dopaminergic neurons with distinct projection patterns and physiological properties compose memory subsystems in a brain. However, it is poorly understood whether or how they interact during complex learning. Here, we identify a feedforward circuit formed between dopamine subsystems and show that it is essential for second-order conditioning, an ethologically important form of higher-order associative learning. The Drosophila mushroom body comprises a series of dopaminergic compartments, each of which exhibits distinct memory dynamics. We find that a slow and stable memory compartment can serve as an effective ‘teacher’ by instructing other faster and transient memory compartments via a single key interneuron, which we identify by connectome analysis and neurotransmitter prediction. This excitatory interneuron acquires enhanced response to reward-predicting odor after first-order conditioning and, upon activation, evokes dopamine release in the ‘student’ compartments. These hierarchical connections between dopamine subsystems explain distinct properties of first- and second-order memory long known by behavioral psychologists.

Published
2023
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3. 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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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

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