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7 Janelia Publications

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    08/24/22 | A single-cell transcriptomic atlas of complete insect nervous systems across multiple life stages.
    Corrales M, Cocanougher BT, Kohn AB, Wittenbach JD, Long XS, Lemire A, Cardona A, Singer RH, Moroz LL, Zlatic M
    Neural Development. 2022 Aug 24;17(1):8. doi: 10.1186/s13064-022-00164-6

    Molecular profiles of neurons influence neural development and function but bridging the gap between genes, circuits, and behavior has been very difficult. Here we used single cell RNAseq to generate a complete gene expression atlas of the Drosophila larval central nervous system composed of 131,077 single cells across three developmental stages (1 h, 24 h and 48 h after hatching). We identify 67 distinct cell clusters based on the patterns of gene expression. These include 31 functional mature larval neuron clusters, 1 ring gland cluster, 8 glial clusters, 6 neural precursor clusters, and 13 developing immature adult neuron clusters. Some clusters are present across all stages of larval development, while others are stage specific (such as developing adult neurons). We identify genes that are differentially expressed in each cluster, as well as genes that are differentially expressed at distinct stages of larval life. These differentially expressed genes provide promising candidates for regulating the function of specific neuronal and glial types in the larval nervous system, or the specification and differentiation of adult neurons. The cell transcriptome Atlas of the Drosophila larval nervous system is a valuable resource for developmental biology and systems neuroscience and provides a basis for elucidating how genes regulate neural development and function.

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    08/19/22 | Flexible control of behavioral variability mediated by an internal representation of head direction
    Chuntao Dan , Brad K. Hulse , Vivek Jayaraman , Ann M. Hermundstad
    bioRxiv. 2022 Aug 19:. doi: 10.1101/2021.08.18.456004

    Internal representations are thought to support the generation of flexible, long-timescale behavioral patterns in both animals and artificial agents. Here, we present a novel conceptual framework for how Drosophila use their internal representation of head direction to maintain preferred headings in their surroundings, and how they learn to modify these preferences in the presence of selective thermal reinforcement. To develop the framework, we analyzed flies’ behavior in a classical operant visual learning paradigm and found that they use stochastically generated fixations and directed turns to express their heading preferences. Symmetries in the visual scene used in the paradigm allowed us to expose how flies’ probabilistic behavior in this setting is tethered to their head direction representation. We describe how flies’ ability to quickly adapt their behavior to the rules of their environment may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in the structure of their circuits. Many of the mechanisms we outline may also be relevant for rapidly adaptive behavior driven by internal representations in other animals, including mammals.

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    05/28/22 | An essential experimental control for functional connectivity mapping with optogenetics.
    David Tadres , Hiroshi M. Shiozaki , Ibrahim Tastekin , David L. Stern , Matthieu Louis
    bioRxiv. 2022 May 28:. doi: 10.1101/2022.05.26.493610

    To establish functional connectivity between two candidate neurons that might form a circuit element, a common approach is to activate an optogenetic tool such as Chrimson in the candidate pre-synaptic neuron and monitor fluorescence of the calcium-sensitive indicator GCaMP in a candidate post-synaptic neuron. While performing such experiments, we found that low levels of leaky Chrimson expression can lead to strong artifactual GCaMP signals in presumptive postsynaptic neurons even when Chrimson is not intentionally expressed in any particular neurons. Withholding all-trans retinal, the chromophore required as a co-factor for Chrimson response to light, eliminates GCaMP signal but does not provide an experimental control for leaky Chrimson expression. Leaky Chrimson expression appears to be an inherent feature of current Chrimson transgenes, since artifactual connectivity was detected with Chrimson transgenes integrated into three different genomic locations (two insertions tested in larvae; a third insertion tested in the adult fly). These false-positive signals may complicate the interpretation of functional connectivity experiments. We illustrate how a no-Gal4 negative control improves interpretability of functional connectivity assays. We also propose a simple but effective procedure to identify experimental conditions that minimize potentially incorrect interpretations caused by leaky Chrimson expression.

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    05/26/22 | One engram two readouts: stimulus dynamics switch a learned behavior in Drosophila
    Mehrab N Modi , Adithya Rajagopalan , Hervé Rouault , Yoshinori Aso , Glenn C Turner
    bioRxiv. 2022 May 26:. doi: 10.1101/2022.05.24.492551

    Memory guides the choices an animal makes across widely varying conditions in dynamic environments. Consequently, the most adaptive choice depends on the options available. How can a single memory support optimal behavior across different sets of choice options? We address this using olfactory learning in Drosophila. Even when we restrict an odor-punishment association to a single set of synapses using optogenetics, we find that flies still show choice behavior that depends on the options it encounters. Here we show that how the odor choices are presented to the animal influences memory recall itself. Presenting two similar odors in sequence enabled flies to not only discriminate them behaviorally but also at the level of neural activity. However, when the same odors were encountered as solitary stimuli, no such differences were detectable. These results show that memory recall is not simply a comparison to a static learned template, but can be adaptively modulated by stimulus dynamics.

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    05/25/22 | Expectation-based learning rules underlie dynamic foraging in Drosophila
    Adithya E. Rajagopalan , Ran Darshan , James E. Fitzgerald , Glenn C. Turner
    bioRxiv. 2022 May 25:. doi: 10.1101/2022.05.24.493252

    Foraging animals must use decision-making strategies that dynamically account for uncertainty in the world. To cope with this uncertainty, animals have developed strikingly convergent strategies that use information about multiple past choices and reward to learn representations of the current state of the world. However, the underlying learning rules that drive the required learning have remained unclear. Here, working in the relatively simple nervous system of Drosophila, we combine behavioral measurements, mathematical modeling, and neural circuit perturbations to show that dynamic foraging depends on a learning rule incorporating reward expectation. Using a novel olfactory dynamic foraging task, we characterize the behavioral strategies used by individual flies when faced with unpredictable rewards and show, for the first time, that they perform operant matching. We build on past theoretical work and demonstrate that this strategy requires the existence of a covariance-based learning rule in the mushroom body - a hub for learning in the fly. In particular, the behavioral consequences of optogenetic perturbation experiments suggest that this learning rule incorporates reward expectation. Our results identify a key element of the algorithm underlying dynamic foraging in flies and suggest a comprehensive mechanism that could be fundamental to these behaviors across species.

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    04/02/22 | Hierarchical architecture of dopaminergic circuits enables second-order conditioning in Drosophila
    Daichi Yamada , Daniel Bushey , Li Feng , Karen Hibbard , Megan Sammons , Jan Funke , Ashok Litwin-Kumar , Toshihide Hige , Yoshinori Aso
    bioRxiv. 2022 Apr 02:. doi: 10.1101/2022.03.30.486484

    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.

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    03/14/22 | A population of descending neurons that regulates the flight motor of Drosophila.
    Namiki S, Ros IG, Morrow C, Rowell WJ, Card GM, Korff W, Dickinson MH
    Current Biology. 2022 Mar 14;32(5):1189-1196. doi: 10.1016/j.cub.2022.01.008

    Similar to many insect species, Drosophila melanogaster is capable of maintaining a stable flight trajectory for periods lasting up to several hours. Because aerodynamic torque is roughly proportional to the fifth power of wing length, even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to both the damaged and intact wings. Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this study, we describe an unusual type of descending neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using two-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of descending neurons that provides the sensitivity and dynamic range required for flight control.

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