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17 Janelia Publications

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    03/27/20 | Unc-4 acts to promote neuronal identity and development of the take-off circuit in the Drosophila CNS.
    Lacin H, Williamson WR, Card GM, Skeath JB, Truman JW
    eLife. 2020 Mar 27;9:. doi: 10.7554/eLife.55007
    02/03/20 | Wiring patterns from auditory sensory neurons to the escape and song-relay pathways in fruit flies.
    Kim H, Horigome M, Ishikawa Y, Li F, Lauritzen JS, Card G, Bock DD, Kamikouchi A
    Journal of Comparative Neurology. 2020 Feb 03:. doi: 10.1002/cne.24877

    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'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.

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    07/01/19 | State-dependent decoupling of sensory and motor circuits underlies behavioral flexibility in Drosophila.
    Ache JM, Namiki S, Lee A, Branson K, Card GM
    Nature Neuroscience. 2019 Jul 01;22(7):1132-1139. doi: 10.1038/s41593-019-0413-4

    An approaching predator and self-motion toward an object can generate similar looming patterns on the retina, but these situations demand different rapid responses. How central circuits flexibly process visual cues to activate appropriate, fast motor pathways remains unclear. Here we identify two descending neuron (DN) types that control landing and contribute to visuomotor flexibility in Drosophila. For each, silencing impairs visually evoked landing, activation drives landing, and spike rate determines leg extension amplitude. Critically, visual responses of both DNs are severely attenuated during non-flight periods, effectively decoupling visual stimuli from the landing motor pathway when landing is inappropriate. The flight-dependence mechanism differs between DN types. Octopamine exposure mimics flight effects in one, whereas the other probably receives neuronal feedback from flight motor circuits. Thus, this sensorimotor flexibility arises from distinct mechanisms for gating action-specific descending pathways, such that sensory and motor networks are coupled or decoupled according to the behavioral state.

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    02/28/19 | Neural basis for looming size and velocity encoding in the Drosophila giant fiber escape pathway.
    Ache JM, Polsky J, Alghailani S, Parekh R, Breads P, Peek MY, Bock DD, von Reyn CR, Card GM
    Current Biology : CB. 2019 Feb 28;29(6):1073. doi: 10.1016/j.cub.2019.01.079

    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'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.

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    11/06/18 | Tools for rapid high-resolution behavioral phenotyping of automatically isolated Drosophila.
    Williamson WR, Peek MY, Breads P, Coop B, Card GM
    Cell Reports. 2018 Nov 06;25(6):1636-1649.e5. doi: 10.1016/j.celrep.2018.10.048

    Sparse manipulation of neuron excitability during free behavior is critical for identifying neural substrates of behavior. Genetic tools for precise neuronal manipulation exist in the fruit fly, Drosophila melanogaster, but behavioral tools are still lacking to identify potentially subtle phenotypes only detectible using high-throughput and high spatiotemporal resolution. We developed three assay components that can be used modularly to study natural and optogenetically induced behaviors. FlyGate automatically releases flies one at a time into an assay. FlyDetect tracks flies in real time, is robust to severe occlusions, and can be used to track appendages, such as the head. GlobeDisplay is a spherical projection system covering the fly's visual receptive field with a single projector. We demonstrate the utility of these components in an integrated system, FlyPEZ, by comprehensively modeling the input-output function for directional looming-evoked escape takeoffs and describing a millisecond-timescale phenotype from genetic silencing of a single visual projection neuron type.

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    09/12/18 | Speed dependent descending control of freezing behavior in Drosophila melanogaster.
    Zacarias R, Namiki S, Card GM, Vasconcelos ML, Moita MA
    Nature Communications. 2018 Sep 12;9(1):3697. doi: 10.1038/s41467-018-05875-1

    The most fundamental choice an animal has to make when it detects a threat is whether to freeze, reducing its chances of being noticed, or to flee to safety. Here we show that Drosophila melanogaster exposed to looming stimuli in a confined arena either freeze or flee. The probability of freezing versus fleeing is modulated by the fly's walking speed at the time of threat, demonstrating that freeze/flee decisions depend on behavioral state. We describe a pair of descending neurons crucially implicated in freezing. Genetic silencing of DNp09 descending neurons disrupts freezing yet does not prevent fleeing. Optogenetic activation of both DNp09 neurons induces running and freezing in a state-dependent manner. Our findings establish walking speed as a key factor in defensive response choices and reveal a pair of descending neurons as a critical component in the circuitry mediating selection and execution of freezing or fleeing behaviors.

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    12/09/17 | Optogenetic dissection of descending behavioral control in Drosophila.
    Cande J, Namiki S, Qiu J, Korff W, Card GM, Shaevitz JW, Stern DL, Berman GJ
    eLife. 2018:e34275. doi: 10.7554/eLife.34275

    In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how descending neurons control an insect's movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and we associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a large collection of descending neurons, we found that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.

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    06/26/18 | The functional organization of descending sensory-motor pathways in Drosophila.
    Namiki S, Dickinson MH, Wong AM, Korff W, Card GM
    eLife. 2018 Jun 26:e34272. doi: 10.7554/eLife.34272

    In most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck. DN activity activates, maintains or modulates locomotion and other behaviors. Individual DNs have been well-studied in species from insects to primates, but little is known about overall connectivity patterns across the DN population. We systematically investigated DN anatomy in Drosophila melanogaster and created over 100 transgenic lines targeting individual cell types. We identified roughly half of all Drosophila DNs and comprehensively map connectivity between sensory and motor neuropils in the brain and nerve cord, respectively. We find the nerve cord is a layered system of neuropils reflecting the fly's capability for two largely independent means of locomotion -- walking and flight -- using distinct sets of appendages. Our results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of neural circuits.

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    11/08/17 | Ultra-selective looming detection from radial motion opponency.
    Klapoetke NC, Nern A, Peek MY, Rogers EM, Breads P, Rubin GM, Reiser MB, Card GM
    Nature. 2017 Nov 08;551(7679):237-241. doi: 10.1038/nature24626

    Nervous systems combine lower-level sensory signals to detect higher-order stimulus features critical to survival, such as the visual looming motion created by an imminent collision or approaching predator. Looming-sensitive neurons have been identified in diverse animal species. Different large-scale visual features such as looming often share local cues, which means loom-detecting neurons face the challenge of rejecting confounding stimuli. Here we report the discovery of an ultra-selective looming detecting neuron, lobula plate/lobula columnar, type II (LPLC2) in Drosophila, and show how its selectivity is established by radial motion opponency. In the fly visual system, directionally selective small-field neurons called T4 and T5 form a spatial map in the lobula plate, where they each terminate in one of four retinotopic layers, such that each layer responds to motion in a different cardinal direction. Single-cell anatomical analysis reveals that each arm of the LPLC2 cross-shaped primary dendrites ramifies in one of these layers and extends along that layer's preferred motion direction. In vivo calcium imaging demonstrates that, as their shape predicts, individual LPLC2 neurons respond strongly to outward motion emanating from the centre of the neuron's receptive field. Each dendritic arm also receives local inhibitory inputs directionally selective for inward motion opposing the excitation. This radial motion opponency generates a balance of excitation and inhibition that makes LPLC2 non-responsive to related patterns of motion such as contraction, wide-field rotation or luminance change. As a population, LPLC2 neurons densely cover visual space and terminate onto the giant fibre descending neurons, which drive the jump muscle motor neuron to trigger an escape take off. Our findings provide a mechanistic description of the selective feature detection that flies use to discern and escape looming threats.

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    07/13/17 | Mapping the neural substrates of behavior.
    Robie AA, Hirokawa J, Edwards AW, Umayam LA, Lee A, Phillips ML, Card GM, Korff W, Rubin GM, Simpson JH, Reiser MB, Branson KM
    Cell. 2017-07-13;170(2):393-406. doi: 10.1016/j.cell.2017.06.032

    Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.

    •We developed machine-vision methods to broadly and precisely quantify fly behavior•We measured effects of activating 2,204 genetically targeted neuronal populations•We created whole-brain maps of neural substrates of locomotor and social behaviors•We created resources for exploring our results and enabling further investigation

    Machine-vision analyses of large behavior and neuroanatomy data reveal whole-brain maps of regions associated with numerous complex behaviors.

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