@article {69301, title = {Motor neurons generate pose-targeted movements via proprioceptive sculpting.}, journal = {Nature}, year = {2024}, month = {2024 Mar 20}, abstract = {

Motor neurons are the final common pathway through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically suppress a single class of proprioceptive neuron that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

}, issn = {1476-4687}, doi = {10.1038/s41586-024-07222-5}, author = {Gorko, Benjamin and Siwanowicz, Igor and Close, Kari and Christoforou, Christina and Hibbard, Karen L and Kabra, Mayank and Lee, Allen and Park, Jin-Yong and Li, Si Ying and Chen, Alex B and Namiki, Shigehiro and Chen, Chenghao and Tuthill, John C and Bock, Davi D and Rouault, Herv{\'e} and Branson, Kristin and Ihrke, Gudrun and Huston, Stephen J} } @article {68889, title = {Neuronal wiring diagram of an adult brain.}, journal = {Nature}, volume = {634}, year = {2024}, month = {2024 Oct 02}, pages = {124-138}, abstract = {

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 {\texttimes} 107 chemical synapses between 139,255 neurons reconstructed from an adult female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

}, doi = {10.1038/s41586-024-07558-y}, url = {https://doi.org/10.1038/s41586-024-07558-y}, author = {Dorkenwald, Sven and Matsliah, Arie and Sterling, Amy R and Schlegel, Philipp and Yu, Szi-Chieh and McKellar, Claire E and Lin, Albert and Costa, Marta and Eichler, Katharina and Yin, Yijie and Silversmith, Will and Schneider-Mizell, Casey and Jordan, Chris S and Brittain, Derrick and Halageri, Akhilesh and Kuehner, Kai and Ogedengbe, Oluwaseun and Morey, Ryan and Gager, Jay and Kruk, Krzysztof and Perlman, Eric and Yang, Runzhe and Deutsch, David and Bland, Doug and Sorek, Marissa and Lu, Ran and Macrina, Thomas and Lee, Kisuk and Bae, J Alexander and Mu, Shang and Nehoran, Barak and Mitchell, Eric and Popovych, Sergiy and Wu, Jingpeng and Jia, Zhen and Castro, Manuel and Kemnitz, Nico and Ih, Dodam and Bates, Alexander Shakeel and Eckstein, Nils and Funke, Jan and Collman, Forrest and Bock, Davi D and Jefferis, Gregory S X E and Seung, H Sebastian and Murthy, Mala} } @article {69459, title = {Ultrastructural differences impact cilia shape and external exposure across cell classes in the visual cortex}, journal = {Curr Biol}, year = {2024}, month = {2024 May 13}, abstract = {

A primary cilium is a membrane-bound extension from the cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. Primary cilia in the brain are less accessible than cilia on cultured cells or epithelial tissues because in the brain they protrude into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs) but were absent from oligodendrocytes and microglia. Ultrastructural comparisons revealed that the base of the cilium and the microtubule organization differed between neurons and glia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting that cilia are poised to encounter locally released signaling molecules. Our analysis indicated that synapse proximity is likely due to random encounters in the neuropil, with no evidence that cilia modulate synapse activity as would be expected in tetrapartite synapses. The observed cell class differences in proximity to synapses were largely due to differences in external cilia length. Many key structural features that differed between neuronal and glial cilia influenced both cilium placement and shape and, thus, exposure to processes and synapses outside the cilium. Together, the ultrastructure both within and around neuronal and glial cilia suggest differences in cilia formation and function across cell types in the brain.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2024.04.043}, author = {Ott, Carolyn M and Torres, Russel and Kuan, Tung-Sheng and Kuan, Aaron and Buchanan, JoAnn and Elabbady, Leila and Seshamani, Sharmishtaa and Bodor, Agnes L and Collman, Forrest and Bock, Davi D and Lee, Wei Chung and da Costa, Nuno Ma{\c c}arico and Lippincott-Schwartz, Jennifer} } @article {68147, title = {Drosophila gustatory projections are segregated by taste modality and connectivity.}, journal = {eLife}, volume = {11}, year = {2022}, month = {2022 May 25}, abstract = {

Gustatory sensory neurons detect caloric and harmful compounds in potential food and convey this information to the brain to inform feeding decisions. To examine the signals that gustatory neurons transmit and receive, we reconstructed gustatory axons and their synaptic sites in the adult brain, utilizing a whole-brain electron microscopy volume. We reconstructed 87 gustatory projections from the proboscis labellum in the right hemisphere and 57 from the left, representing the majority of labellar gustatory axons. Gustatory neurons contain a nearly equal number of interspersed pre- and postsynaptic sites, with extensive synaptic connectivity among gustatory axons. Morphology- and connectivity-based clustering revealed six distinct groups, likely representing neurons recognizing different taste modalities. The vast majority of synaptic connections are between neurons of the same group. This study resolves the anatomy of labellar gustatory projections, reveals that gustatory projections are segregated based on taste modality, and uncovers synaptic connections that may alter the transmission of gustatory signals.

}, keywords = {Animals, Drosophila, Drosophila melanogaster, Drosophila Proteins, Sensory Receptor Cells, Taste}, issn = {2050-084X}, doi = {10.7554/eLife.78110}, author = {Engert, Stefanie and Sterne, Gabriella R and Bock, Davi D and Scott, Kristin} } @article {68222, title = {Structured sampling of olfactory input by the fly mushroom body.}, journal = {Current Biology}, volume = {32}, year = {2022}, month = {2022 Aug 08}, pages = {3334-3349.e6}, abstract = {

Associative memory formation and recall in the fruit fly Drosophila melanogaster is subserved by the mushroom body (MB). Upon arrival in the MB, sensory information undergoes a profound transformation from broadly tuned and stereotyped odorant responses in the olfactory projection neuron (PN) layer to narrowly tuned and nonstereotyped responses in the Kenyon cells (KCs). Theory and experiment suggest that this transformation is implemented by random connectivity between KCs and PNs. However, this hypothesis has been challenging to test, given the difficulty of mapping synaptic connections between large numbers of brain-spanning neurons. Here, we used a recent whole-brain electron microscopy volume of the adult fruit fly to map PN-to-KC connectivity at synaptic resolution. The PN-KC connectome revealed unexpected structure, with preponderantly food-responsive PN types converging at above-chance levels on downstream KCs. Axons of the overconvergent PN types tended to arborize near one another in the MB main calyx, making local KC dendrites more likely to receive input from those types. Overconvergent PN types preferentially co-arborize and connect with dendrites of αβ and α{\textquoteright}β{\textquoteright} KC subtypes. Computational simulation of the observed network showed degraded discrimination performance compared with a random network, except when all signal flowed through the overconvergent, primarily food-responsive PN types. Additional theory and experiment will be needed to fully characterize the impact of the observed non-random network structure on associative memory formation and recall.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2022.06.031}, author = {Zheng, Zhihao and Li, Feng and Fisher, Corey and Ali, Iqbal J and Sharifi, Nadiya and Calle-Schuler, Steven and Hsu, Joseph and Masoodpanah, Najla and Kmecova, Lucia and Kazimiers, Tom and Perlman, Eric and Nichols, Matthew and Li, Peter H and Jain, Viren and Bock, Davi D} } @article {67189, title = {Circuit reorganization in the Drosophila mushroom body calyx accompanies memory consolidation.}, journal = {Cell Reports}, volume = {34}, year = {2021}, month = {2021 Mar 16}, pages = {108871}, abstract = {

The formation and consolidation of memories are complex phenomena involving synaptic plasticity, microcircuit reorganization, and the formation of multiple representations within distinct circuits. To gain insight into the structural aspects of memory consolidation, we focus on the calyx of the Drosophila mushroom body. In this essential center, essential for olfactory learning, second- and third-order neurons connect through large synaptic microglomeruli, which we dissect at the electron microscopy level. Focusing on microglomeruli that respond to a specific odor, we reveal that appetitive long-term memory results in increased numbers of precisely those functional microglomeruli responding to the conditioned odor. Hindering memory consolidation by non-coincident presentation of odor and reward, by blocking protein synthesis, or by including memory mutants suppress these structural changes, revealing their tight correlation with the process of memory consolidation. Thus, olfactory long-term memory is associated with input-specific structural modifications in a high-order center of the fly brain.

}, issn = {2211-1247}, doi = {10.1016/j.celrep.2021.108871}, author = {Baltruschat, Lothar and Prisco, Luigi and Ranft, Philipp and Lauritzen, J Scott and Fiala, Andr{\'e} and Bock, Davi D and Tavosanis, Gaia} } @article {67843, title = {Synaptic targets of photoreceptors specialized to detect color and skylight polarization in .}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Dec 16}, abstract = {

Color and polarization provide complementary information about the world and are detected by specialized photoreceptors. However, the downstream neural circuits that process these distinct modalities are incompletely understood in any animal. Using electron microscopy, we have systematically reconstructed the synaptic targets of the photoreceptors specialized to detect color and skylight polarization in Drosophila, and we have used light microscopy to confirm many of our findings. We identified known and novel downstream targets that are selective for different wavelengths or polarized light, and followed their projections to other areas in the optic lobes and the central brain. Our results revealed many synapses along the photoreceptor axons between brain regions, new pathways in the optic lobes, and spatially segregated projections to central brain regions. Strikingly, photoreceptors in the polarization-sensitive dorsal rim area target fewer cell types, and lack strong connections to the lobula, a neuropil involved in color processing. Our reconstruction identifies shared wiring and modality-specific specializations for color and polarization vision, and provides a comprehensive view of the first steps of the pathways processing color and polarized light inputs.

}, issn = {2050-084X}, doi = {10.7554/eLife.71858}, author = {Kind, Emil and Longden, Kit D and Nern, Aljoscha and Zhao, Arthur and Sancer, Gizem and Flynn, Miriam A and Laughland, Connor W and Gezahegn, Bruck and Ludwig, Henrique Df and Thomson, Alex G and Obrusnik, Tessa and Alarc{\'o}n, Paula G and Dionne, Heather and Bock, Davi D and Rubin, Gerald M and Reiser, Michael B and Wernet, Mathias F} } @article {65645, title = {Complete connectomic reconstruction of olfactory projection neurons in the fly brain.}, journal = {Current Biology}, volume = {30}, year = {2020}, month = {2020 Aug 17}, pages = {3183-99}, abstract = {

Nervous systems contain sensory neurons, local neurons, projection neurons, and motor neurons. To understand how these building blocks form whole circuits, we must distil these broad classes into neuronal cell types and describe their network connectivity. Using an electron micrograph dataset for an entire Drosophila melanogaster brain, we reconstruct the first complete inventory of olfactory projections connecting the antennal lobe, the insect analog of the mammalian olfactory bulb, to higher-order brain regions in an adult animal brain. We then connect this inventory to extant data in the literature, providing synaptic-resolution "holotypes" both for heavily investigated and previously unknown cell types. Projection neurons are approximately twice as numerous as reported by light level studies; cell types are stereotyped, but not identical, in cell and synapse numbers between brain hemispheres. The lateral horn, the insect analog of the mammalian cortical amygdala, is the main target for this olfactory information and has been shown to guide innate behavior. Here, we find new connectivity motifs, including axo-axonic connectivity between projection neurons, feedback, and lateral inhibition of these axons by a large population of neurons, and the convergence of different inputs, including non-olfactory inputs and memory-related feedback onto third-order olfactory neurons. These features are less prominent in the mushroom body calyx, the insect analog of the mammalian piriform cortex and a center for associative memory. Our work provides a complete neuroanatomical platform for future studies of the adult Drosophila olfactory system.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2020.06.042}, author = {Bates, Alexander S and Schlegel, Philipp and Roberts, Ruair{\'\i} J V and Drummond, Nikolas and Tamimi, Imaan F M and Turnbull, Robert and Zhao, Xincheng and Marin, Elizabeth C and Popovici, Patricia D and Dhawan, Serene and Jamasb, Arian and Javier, Alexandre and Serratosa Capdevila, Laia and Li, Feng and Rubin, Gerald M and Waddell, Scott and Bock, Davi D and Costa, Marta and Jefferis, Gregory S X E} } @article {65643, title = {Connectomics analysis reveals first-, second-, and third-order thermosensory and hygrosensory neurons in the adult Drosophila brain.}, journal = {Current Biology}, volume = {30}, year = {2020}, month = {2020 Aug 17}, pages = {3167-82}, abstract = {

Animals exhibit innate and learned preferences for temperature and humidity-conditions critical for their survival and reproduction. Leveraging a whole-brain electron microscopy volume, we studied the adult Drosophila melanogaster circuitry associated with antennal thermo- and hygrosensory neurons. We have identified two new target glomeruli in the antennal lobe, in addition to the five known ones, and the ventroposterior projection neurons (VP PNs) that relay thermo- and hygrosensory information to higher brain centers, including the mushroom body and lateral horn, seats of learned and innate behavior. We present the first connectome of a thermo- and hygrosensory neuropil, the lateral accessory calyx (lACA), by reconstructing neurons downstream of heating- and cooling-responsive VP PNs. A few mushroom body-intrinsic neurons solely receive thermosensory input from the lACA, while most receive additional olfactory and thermo- and/or hygrosensory PN inputs. Furthermore, several classes of lACA-associated neurons form a local network with outputs to other brain neuropils, suggesting that the lACA serves as a hub for thermo- and hygrosensory circuitry. For example, DN1a neurons link thermosensory PNs in the lACA to the circadian clock via the accessory medulla. Finally, we survey strongly connected downstream partners of VP PNs across the protocerebrum; these include a descending neuron targeted by dry-responsive VP PNs, meaning that just two synapses might separate hygrosensory inputs from motor circuits. These data provide a comprehensive first- and second-order layer analysis of Drosophila thermo- and hygrosensory systems and an initial survey of third-order neurons that could directly modulate behavior.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2020.06.028}, author = {Marin, Elizabeth C and B{\"u}ld, Laurin and Theiss, Maria and Sarkissian, Tatevik and Roberts, Ruair{\'\i} J V and Turnbull, Robert and Tamimi, Imaan F M and Pleijzier, Markus W and Laursen, Willem J and Drummond, Nik and Schlegel, Philipp and Bates, Alexander S and Li, Feng and Landgraf, Matthias and Costa, Marta and Bock, Davi D and Garrity, Paul A and Jefferis, Gregory S X E} } @article {65738, title = {The mind of a mouse.}, journal = {Cell}, volume = {182}, year = {2020}, month = {2020 Sep 17}, pages = {1372-1376}, abstract = {

Large scientific projects in genomics and astronomy are influential not because they answer any single question but because they enable investigation of continuously arising new questions from the same data-rich sources. Advances in automated mapping of the brain{\textquoteright}s synaptic connections (connectomics) suggest that the complicated circuits underlying brain function are ripe for analysis. We discuss benefits of mapping a mouse brain at the level of synapses.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2020.08.010}, author = {Abbott, Larry F and Bock, Davi D and Callaway, Edward M and Denk, Winfried and Dulac, Catherine and Fairhall, Adrienne L and Fiete, Ila and Harris, Kristen M and Helmstaedter, Moritz and Jain, Viren and Kasthuri, Narayanan and LeCun, Yann and Lichtman, Jeff W and Littlewood, Peter B and Luo, Liqun and Maunsell, John H R and Reid, R Clay and Rosen, Bruce R and Rubin, Gerald M and Sejnowski, Terrence J and Seung, H Sebastian and Svoboda, Karel and Tank, David W and Tsao, Doris and Van Essen, David C} } @article {65722, title = {The neuroanatomical ultrastructure and function of a biological ring attractor.}, journal = {Neuron}, volume = {108}, year = {2020}, month = {2020 Oct 14}, pages = {145-63}, abstract = {

Neural representations of head direction (HD) have been discovered in many species. Theoretical work has proposed that the dynamics associated with these representations are generated, maintained, and updated by recurrent network structures called ring attractors. We evaluated this theorized structure-function relationship by performing electron-microscopy-based circuit reconstruction and RNA profiling of identified cell types in the HD system of Drosophila melanogaster. We identified motifs that have been hypothesized to maintain the HD representation in darkness, update it when the animal turns, and tether it to visual cues. Functional studies provided support for the proposed roles of individual excitatory or inhibitory circuit elements in shaping activity. We also discovered recurrent connections between neuronal arbors with mixed pre- and postsynaptic specializations. Our results confirm that the Drosophila HD network contains the core components of a ring attractor while also revealing unpredicted structural features that might enhance the network{\textquoteright}s computational power.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2020.08.006}, author = {Turner-Evans, Daniel B and Jensen, Kristopher T and Ali, Saba and Paterson, Tyler and Sheridan, Arlo and Ray, Robert P and Wolff, Tanya and Lauritzen, J Scott and Rubin, Gerald M and Bock, Davi D and Jayaraman, Vivek} } @article {65656, title = {The wiring logic of an identified serotonergic neuron that spans sensory networks.}, journal = {Journal of Neuroscience}, volume = {40}, year = {2020}, month = {2020 Aug 12}, pages = {6309-27}, abstract = {

Serotonergic neurons project widely throughout the brain to modulate diverse physiological and behavioral processes. However, a single cell resolution understanding of the connectivity of serotonergic neurons is currently lacking. Using a whole-brain EM dataset of a female , we comprehensively determine the wiring logic of a broadly projecting serotonergic neuron (the "CSDn") that spans several olfactory regions. Within the antennal lobe, the CSDn differentially innervates each glomerulus, yet surprisingly, this variability reflects a diverse set of presynaptic partners, rather than glomerulus-specific differences in synaptic output, which is predominately to local interneurons. Moreover, the CSDn has distinct connectivity relationships with specific local interneuron subtypes, suggesting that the CSDn influences distinct aspects of local network processing. Across olfactory regions, the CSDn has different patterns of connectivity, even having different connectivity with individual projection neurons that also span these regions. Whereas the CSDn targets inhibitory local neurons in the antennal lobe, the CSDn has more distributed connectivity in the LH, preferentially synapsing with principal neuron types based on transmitter content. Lastly, we identify individual novel synaptic partners associated with other sensory domains that provide strong, top-down input to the CSDn. Taken together, our study reveals the complex connectivity of serotonergic neurons which combine the integration of local and extrinsic synaptic input in a nuanced, region-specific manner.All sensory systems receive serotonergic modulatory input. However, a comprehensive understanding of the synaptic connectivity of individual serotonergic neurons is lacking. In this study, we use a whole-brain EM microscopy dataset to comprehensively determine the wiring logic of a broadly projecting serotonergic neuron in the olfactory system of Collectively, our study demonstrates at a single cell level, the complex connectivity of serotonergic neurons within their target networks, identifies specific cell classes heavily targeted for serotonergic modulation in the olfactory system, and reveals novel extrinsic neurons that provide strong input to this serotonergic system outside of the context of olfaction. Elucidating the connectivity logic of individual modulatory neurons provides a ground plan for the seemingly heterogeneous effects of modulatory systems.

}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0552-20.2020}, author = {Coates, Kaylynn E and Calle-Schuler, Steven A and Helmick, Levi M and Knotts, Victoria L and Martik, Brennah N and Salman, Farzaan and Warner, Lauren T and Valla, Sophia V and Bock, Davi D and Dacks, Andrew M} } @article {65296, title = {Wiring patterns from auditory sensory neurons to the escape and song-relay pathways in fruit flies.}, journal = {Journal of Comparative Neurology}, volume = {528}, year = {2020}, month = {2020 Aug 01}, pages = {2068}, abstract = {

Many animals rely on acoustic cues to decide what action to take next. Unraveling the wiring patterns of the auditory neural pathways is prerequisite for understanding such information processing. Here we reconstructed the first step of the auditory neural pathway in the fruit fly brain, from primary to secondary auditory neurons, at the resolution of transmission electron microscopy. By tracing axons of two major subgroups of auditory sensory neurons in fruit flies, low-frequency tuned Johnston{\textquoteright}s organ (JO)-B neurons and high-frequency tuned JO-A neurons, we observed extensive connections from JO-B neurons to the main second-order neurons in both the song-relay and escape pathways. In contrast, JO-A neurons connected strongly to a neuron in the escape pathway. Our findings suggest that heterogeneous JO neuronal populations could be recruited to modify escape behavior whereas only specific JO neurons contribute to courtship behavior. We also found that all JO neurons have postsynaptic sites at their axons. Presynaptic modulation at the output sites of JO neurons could affect information processing of the auditory neural pathway in flies. This article is protected by copyright. All rights reserved.

}, issn = {1096-9861}, doi = {10.1002/cne.24877}, author = {Kim, Hyunsoo and Horigome, Mihoko and Ishikawa, Yuki and Li, Feng and Lauritzen, J Scott and Card, Gwyneth and Bock, Davi D and Kamikouchi, Azusa} } @article {64825, title = {Neural basis for looming size and velocity encoding in the Drosophila giant fiber escape pathway.}, journal = {Current Biology : CB}, volume = {29}, year = {2019}, month = {2019 Feb 28}, pages = {1073}, abstract = {

Identified neuron classes in vertebrate cortical [1-4] and subcortical [5-8] areas and invertebrate peripheral [9-11] and central [12-14] brain neuropils encode specific visual features of a panorama. How downstream neurons integrate these features to control vital behaviors, like escape, is unclear [15]. In Drosophila, the timing of a single spike in the giant fiber (GF) descending neuron [16-18] determines whether a fly uses a short or long takeoff when escaping a looming predator [13]. We previously proposed that GF spike timing results from summation of two visual features whose detection is highly conserved across animals [19]: an object{\textquoteright}s subtended angular size and its angular velocity [5-8, 11, 20, 21]. We attributed velocity encoding to input from lobula columnar type 4 (LC4) visual projection neurons, but the size-encoding\ source remained unknown. Here, we show that lobula plate/lobula columnar, type 2 (LPLC2) visual projection neurons anatomically specialized to detect looming [22] provide the entire GF size component. We find LPLC2 neurons to be necessary for GF-mediated escape and show that LPLC2 and LC4 synapse directly onto the GF via reconstruction in a fly brain electron microscopy (EM) volume [23]. LPLC2 silencing eliminates the size component of the GF looming response in patch-clamp recordings, leaving only the velocity component. A model summing a linear function of angular velocity (provided by LC4) and a Gaussian function of angular size (provided by LPLC2) replicates GF looming response dynamics and predicts the peak response time. We thus present an identified circuit in which information from looming feature-detecting neurons is combined by a common post-synaptic target to determine behavioral output.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2019.01.079}, author = {Ache, Jan M and Polsky, Jason and Alghailani, Shada and Parekh, Ruchi and Breads, Patrick and Peek, Martin Y and Bock, Davi D and von Reyn, Catherine R and Card, Gwyneth M} } @article {65141, title = {A neural circuit arbitrates between persistence and withdrawal in hungry drosophila.}, journal = {Neuron}, volume = {104}, year = {2019}, month = {2019 Nov 6}, pages = {544-58}, abstract = {

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the\ MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2019.07.028}, author = {Sayin, Sercan and De Backer, Jean-Francois and Siju, K P and Wosniack, Marina E and Lewis, Laurence P and Frisch, Lisa-Marie and Gansen, Benedikt and Schlegel, Philipp and Edmondson-Stait, Amelia and Sharifi, Nadiya and Fisher, Corey B and Calle-Schuler, Steven A and Lauritzen, J Scott and Bock, Davi D and Costa, Marta and Jefferis, Gregory S X E and Gjorgjieva, Julijana and Grunwald Kadow, Ilona C} } @article {65207, title = {A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila.}, journal = {Neuron}, year = {2019}, month = {2019 Aug 09}, abstract = {

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the\ MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2019.07.028}, author = {Sayin, Sercan and De Backer, Jean-Francois and Siju, K P and Wosniack, Marina E and Lewis, Laurence P and Frisch, Lisa-Marie and Gansen, Benedikt and Schlegel, Philipp and Edmondson-Stait, Amelia and Sharifi, Nadiya and Fisher, Corey B and Calle-Schuler, Steven A and Lauritzen, J Scott and Bock, Davi D and Costa, Marta and Jefferis, Gregory S X E and Gjorgjieva, Julijana and Grunwald Kadow, Ilona C} } @article {64933, title = {Neurogenetic dissection of the lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body.}, journal = {Elife}, volume = {8}, year = {2019}, month = {2019 May 21}, abstract = {

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In , one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30\% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

}, issn = {2050-084X}, doi = {10.7554/eLife.43079}, author = {Dolan, Michael-John and Frechter, Shahar and Bates, Alexander Shakeel and Dan, Chuntao and Huoviala, Paavo and Roberts, Ruair{\'\i} Jv and Schlegel, Philipp and Dhawan, Serene and Tabano, Remy and Dionne, Heather and Christoforou, Christina and Close, Kari and Sutcliffe, Ben and Giuliani, Bianca and Li, Feng and Costa, Marta and Ihrke, Gudrun and Meissner, Geoffrey Wilson and Bock, Davi D and Aso, Yoshinori and Rubin, Gerald M and Jefferis, Gregory Sxe} } @article {59913, title = {Regulation of modulatory cell activity across olfactory structures in Drosophila melanogaster.}, journal = {bioRxiv}, year = {2019}, month = {2019 Jan 16}, abstract = {

All centralized nervous systems possess modulatory neurons that arborize broadly across multiple brain regions. Such modulatory systems are critical for proper sensory, motor, and cognitive processing. How single modulatory neurons integrate into circuits within their target destination remains largely unexplored due to difficulties in both labeling individual cells and imaging across distal parts of the CNS. Here, we take advantage of an identified modulatory neuron in Drosophila that arborizes in multiple olfactory neuropils. We demonstrate that this serotonergic neuron has opposing odor responses in its neurites of the antennal lobe and lateral horn, first and second order olfactory neuropils respectively. Specifically, processes of this neuron in the antennal lobe have responses that are inhibitory and odor-independent, while lateral horn responses are excitatory and odor-specific. The results show that widespread modulatory neurons may not function purely as integrate-and-fire cells, but rather their transmitter release is locally regulated based on neuropil. As nearly all vertebrate and invertebrate neurons are subject to synaptic inputs along their dendro-axonic axis, it is likely that our findings generalize across phylogeny and other broadly-projecting modulatory systems.

}, doi = {10.1101/522177}, author = {Zhang, Xiaonan and Coates, Kaylynn and Dacks, Andrew and Gunay, Cengiz and Lauritzen, J Scott and Li, Feng and Calle-Schuler, Steven A and Bock, Davi D and Gaudry, Quentin} } @article {49435, title = {Integration of parallel opposing memories underlies memory extinction.}, journal = {Cell}, volume = {175}, year = {2018}, month = {2018 Sep 06}, pages = {709-22}, abstract = {

Accurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment,\ a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2018.08.021}, author = {Felsenberg, Johannes and Jacob, Pedro F and Walker, Thomas and Barnstedt, Oliver and Edmondson-Stait, Amelia J and Pleijzier, Markus W and Otto, Nils and Schlegel, Philipp and Sharifi, Nadiya and Perisse, Emmanuel and Smith, Carlas S and Lauritzen, J Scott and Costa, Marta and Jefferis, Gregory S X E and Bock, Davi D and Waddell, Scott} } @article {48254, title = {Multicut brings automated neurite segmentation closer to human performance.}, journal = {Nature Methods}, volume = {14}, year = {2017}, month = {2017 Jan 31}, pages = {101-102}, issn = {1548-7105}, doi = {10.1038/nmeth.4151}, author = {Beier, Thorsten and Pape, Constantin and Rahaman, Nasim and Prange, Timo and Berg, Stuart and Bock, Davi D and Cardona, Albert and Knott, Graham W and Plaza, Stephen M and Scheffer, Louis K and Koethe, Ullrich and Kreshuk, Anna and Hamprecht, Fred A} } @article {47599, title = {A large fraction of neocortical myelin ensheathes axons of local inhibitory neurons.}, journal = {eLife}, year = {2016}, month = {2016 Jul 6}, abstract = {

Myelin is best known for its role in increasing the conduction velocity and metabolic efficiency of long-range excitatory axons. Accordingly, the myelin observed in neocortical gray matter is thought to mostly ensheath excitatory axons connecting to subcortical regions and distant cortical areas. Using independent analyses of light and electron microscopy data from mouse neocortex, we show that a surprisingly large fraction of cortical myelin (half the myelin in layer 2/3 and a quarter in layer 4) ensheathes axons of inhibitory neurons, specifically of parvalbumin-positive basket cells. This myelin differs significantly from that of excitatory axons in distribution and protein composition. Myelin on inhibitory axons is unlikely to meaningfully hasten the arrival of spikes at their pre-synaptic terminals, due to the patchy distribution and short path-lengths observed. Our results thus highlight the need for exploring alternative roles for myelin in neocortical circuits.

}, doi = {10.7554/eLife.15784}, author = {Micheva, Kristina D and Wolman, Dylan and Mensh, Brett D and Pax, Elizabeth and Buchanan, JoAnn and Smith, Stephen J and Bock, Davi D} } @article {6880, title = {Automated detection of synapses in serial section transmission electron microscopy image stacks.}, journal = {PloS one}, volume = {9}, year = {2014}, month = {2014}, pages = {e87351}, abstract = {We describe a method for fully automated detection of chemical synapses in serial electron microscopy images with highly anisotropic axial and lateral resolution, such as images taken on transmission electron microscopes. Our pipeline starts from classification of the pixels based on 3D pixel features, which is followed by segmentation with an Ising model MRF and another classification step, based on object-level features. Classifiers are learned on sparse user labels; a fully annotated data subvolume is not required for training. The algorithm was validated on a set of 238 synapses in 20 serial 7197{\texttimes}7351 pixel images (4.5{\texttimes}4.5{\texttimes}45 nm resolution) of mouse visual cortex, manually labeled by three independent human annotators and additionally re-verified by an expert neuroscientist. The error rate of the algorithm (12\% false negative, 7\% false positive detections) is better than state-of-the-art, even though, unlike the state-of-the-art method, our algorithm does not require a prior segmentation of the image volume into cells. The software is based on the ilastik learning and segmentation toolkit and the vigra image processing library and is freely available on our website, along with the test data and gold standard annotations (http://www.ilastik.org/synapse-detection/sstem).}, issn = {1932-6203}, doi = {10.1371/journal.pone.0087351}, author = {Kreshuk, Anna and Koethe, Ullrich and Pax, Elizabeth and Bock, Davi D and Hamprecht, Fred A} } @article {6904, title = {The Open Connectome Project Data Cluster: Scalable analysis and vision for high-throughput neuroscience.}, journal = {Scientific and Statistical Database Management: International Conference, SSDBM ... : Proceedings. International Conference on Scientific and Statistical Database Management}, year = {2013}, month = {2013 Jun 18}, abstract = {

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

}, doi = {10.1145/2484838.2484870}, author = {Burns, Randal and Roncal, William Gray and Kleissas, Dean and Lillaney, Kunal and Manavalan, Priya and Perlman, Eric and Berger, Daniel R. and Bock, Davi D and Chung, Kwanghun and Grosenick, Logan and Kasthuri, Narayanan and Weiler, Nicholas C and Deisseroth, Karl and Kazhdan, Michael and Lichtman, Jeff and Reid, R Clay and Smith, Stephen J and Szalay, Alexander S and Vogelstein, Joshua T and Vogelstein, R Jacob} } @article {5341, title = {Volume electron microscopy for neuronal circuit reconstruction.}, journal = {Current Opinion in Neurobiology}, volume = {22}, year = {2012}, month = {2012 Feb}, pages = {154-61}, abstract = {

The last decade has seen a rapid increase in the number of tools to acquire volume electron microscopy (EM) data. Several new scanning EM (SEM) imaging methods have emerged, and classical transmission EM (TEM) methods are being scaled up and automated. Here we summarize the new methods for acquiring large EM volumes, and discuss the tradeoffs in terms of resolution, acquisition speed, and reliability. We then assess each method{\textquoteright}s applicability to the problem of reconstructing anatomical connectivity between neurons, considering both the current capabilities and future prospects of the method. Finally, we argue that neuronal {\textquoteright}wiring diagrams{\textquoteright} are likely necessary, but not sufficient, to understand the operation of most neuronal circuits: volume EM imaging will likely find its best application in combination with other methods in neuroscience, such as molecular biology, optogenetics, and physiology.

}, keywords = {Animals, Brain, Computer-Assisted, Electron, Humans, Image Processing, Microscopy, Neural Pathways}, issn = {1873-6882}, doi = {10.1016/j.conb.2011.10.022}, author = {Briggman, Kevin L and Bock, Davi D} } @article {4326, title = {Large-scale automated histology in the pursuit of connectomes.}, journal = {The Journal of Neuroscience: The Official Journal of the Society for Neuroscience}, volume = {31}, year = {2011}, month = {2011 Nov 9}, pages = {16125-38}, abstract = {

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain{\textquoteright}s computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.4077-11.2011}, author = {Kleinfeld, David and Bharioke, Arjun and Blinder, Pablo and Bock, Davi D and Briggman, Kevin L and Chklovskii, Dmitri B and Denk, Winfried and Helmstaedter, Moritz and Kaufhold, John P and Lee, Wei-Chung Allen and Meyer, Hanno S and Micheva, Kristina D and Oberlaender, Marcel and Prohaska, Steffen and Reid, R Clay and Smith, Stephen J and Takemura, Shinya and Tsai, Philbert S and Sakmann, Bert} } @article {2164, title = {Network anatomy and in vivo physiology of visual cortical neurons.}, journal = {Nature}, volume = {471}, year = {2011}, month = {2011 Mar 10}, pages = {177-82}, abstract = {

In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron{\textquoteright}s function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property{\textendash}the preferred stimulus orientation{\textendash}of a group of neurons in the mouse primary visual cortex. Large-scale electron microscopy of serial thin sections was then used to trace a portion of these neurons{\textquoteright} local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.

}, keywords = {Animals, Calcium Signaling, Electron, Fluorescence, Interneurons, Male, Mice, Microscopy, Microtomy, Nerve Net, Neural Inhibition, Neurons, Pyramidal Cells, Synapses, Transmission, Visual Cortex}, issn = {1476-4687}, doi = {10.1038/nature09802}, author = {Bock, Davi D and Lee, Wei-Chung Allen and Kerlin, Aaron M and Andermann, Mark L and Hood, Greg and Wetzel, Arthur W and Yurgenson, Sergey and Soucy, Edward R and Kim, Hyon Suk and Reid, R Clay} }