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23 Publications

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    06/26/18 | Honeybee detection and pose estimation using convolutional neural networks.
    Rodriguez IF, Branson KM, Acuna E, Agosto-Rivera J, Giray T, Megret R
    RFIAP 2018. 2018 Jun 26:

    The ability to automatize the analysis of video for monitoring animals and insects is of great interest for behavior science and ecology [1]. In particular, honeybees play a crucial role in agriculture as natural pollinators. However, recent studies has shown that phenomena such as colony collapse disorder are causing the loss of many colonies [2]. Due to the high number of interacting factors to explain these events, a multi-faceted analysis of the bees in their environment is required. We focus in our work in developing tools to help model and understand their behavior as individuals, in relation with the health and performance of the colony.

    In this paper, we report the development of a new system for the detection, locali- zation and tracking of honeybee body parts from video on the entrance ramp of the colony. The proposed system builds on the recent advances in Convolutional Neu- ral Networks (CNN) for Human pose estimation and evaluates the suitability for the detection of honeybee pose as shown in Figure 1. This opens the door for novel animal behavior analysis systems that take advantage of the precise detection and tracking of the insect pose. 

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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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    06/21/18 | Imaging dynamic and selective low-complexity domain interactions that control gene transcription.
    Chong S, Dugast-Darzacq C, Liu Z, Dong P, Dailey GM, Cattoglio C, Heckert A, Banala S, Lavis L, Darzacq X, Tjian R
    Science (New York, N.Y.). 2018 Jun 21;361(6400):eaar2555. doi: 10.1126/science.aar2555

    Many eukaryotic transcription factors (TFs) contain intrinsically disordered low-complexity domains (LCDs), but how they drive transactivation remains unclear. Here, live-cell single-molecule imaging reveals that TF-LCDs form local high-concentration interaction hubs at synthetic and endogenous genomic loci. TF-LCD hubs stabilize DNA binding, recruit RNA polymerase II (Pol II), and activate transcription. LCD-LCD interactions within hubs are highly dynamic, display selectivity with binding partners, and are differentially sensitive to disruption by hexanediols. Under physiological conditions, rapid and reversible LCD-LCD interactions occur between TFs and the Pol II machinery without detectable phase separation. Our findings reveal fundamental mechanisms underpinning transcriptional control and suggest a framework for developing single-molecule imaging screens for novel drugs targeting gene regulatory interactions implicated in disease.

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    Singer Lab
    06/20/18 | A transgenic mouse for imaging activity-dependent dynamics of endogenous Arc mRNA in live neurons.
    Das S, Moon HC, Singer RH, Park HY
    Science Advances. 2018 Jun;4(6):eaar3448. doi: 10.1126/sciadv.aar3448

    Localized translation plays a crucial role in synaptic plasticity and memory consolidation. However, it has not been possible to follow the dynamics of memory-associated mRNAs in living neurons in response to neuronal activity in real time. We have generated a novel mouse model where the endogenous Arc/Arg3.1 gene is tagged in its 3' untranslated region with stem-loops that bind a bacteriophage PP7 coat protein (PCP), allowing visualization of individual mRNAs in real time. The physiological response of the tagged gene to neuronal activity is identical to endogenous Arc and reports the true dynamics of Arc mRNA from transcription to degradation. The transcription dynamics of Arc in cultured hippocampal neurons revealed two novel results: (i) A robust transcriptional burst with prolonged ON state occurs after stimulation, and (ii) transcription cycles continue even after initial stimulation is removed. The correlation of stimulation with Arc transcription and mRNA transport in individual neurons revealed that stimulus-induced Ca activity was necessary but not sufficient for triggering Arc transcription and that blocking neuronal activity did not affect the dendritic transport of newly synthesized Arc mRNAs. This mouse will provide an important reagent to investigate how individual neurons transduce activity into spatiotemporal regulation of gene expression at the synapse.

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    06/19/18 | Lamellar junctions in the endolymphatic sac act as a relief valve to regulate inner ear pressure.
    Ian A. Swinburne , Kishore R. Mosaliganti , Srigokul Upadhyayula , Tsung-Li Liu , David G. C. Hildebrand , Tony Y.-C. Tsai , Anzhi Chen , Ebaa Al-Obeidi , Anna K. Fass , Samir Malhotra , Florian Engert , Jeff W. Lichtman , Tom Kirchhausen , Sean G. Megason , Eric Betzig
    eLife. 2018 Jun 19:. doi: 10.7554/eLife.37131
    06/19/18 | Lamellar projections in the endolymphatic sac act as a relief valve to regulate inner ear pressure.
    Swinburne IA, Mosaliganti KR, Upadhyayula S, Liu T, Hildebrand DG, Tsai TY, Chen A, Al-Obeidi E, Fass AK, Malhotra S, Engert F, Lichtman JW, Kirchausen T, Betzig E, Megason SG
    eLife. 2018 Jun 19;7:. doi: 10.7554/eLife.37131

    The inner ear is a fluid-filled closed-epithelial structure whose function requires maintenance of an internal hydrostatic pressure and fluid composition. The endolymphatic sac (ES) is a dead-end epithelial tube connected to the inner ear whose function is unclear. ES defects can cause distended ear tissue, a pathology often seen in hearing and balance disorders. Using live imaging of zebrafish larvae, we reveal that the ES undergoes cycles of slow pressure-driven inflation followed by rapid deflation. Absence of these cycles in mutants leads to distended ear tissue. Using serial-section electron microscopy and adaptive optics lattice light-sheet microscopy, we find a pressure relief valve in the ES comprised of partially separated apical junctions and dynamic overlapping basal lamellae that separate under pressure to release fluid. We propose that this lmx1-dependent pressure relief valve is required to maintain fluid homeostasis in the inner ear and other fluid-filled cavities.

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    06/18/18 | A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus.
    Hunt DL, Linaro D, Si B, Romani S, Spruston N
    Nature Neuroscience. 2018 Jun 18;21(7):985-95. doi: 10.1038/s41593-018-0172-7

    To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified 'athorny' pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.

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    Murphy Lab
    06/13/18 | Distinct cell types in the superficial superior colliculus project to the dorsal lateral geniculate and lateral posterior thalamic nuclei.
    Gale SD, Murphy GJ
    Journal of Neurophysiology. 2018 Jun 13;120(3):1286-92. doi: 10.1152/jn.00248.2018

    The superficial layers of the superior colliculus (sSC) receive retinal input and project to thalamic regions - the dorsal lateral geniculate (dLGN) and lateral posterior (LP; or pulvinar) nuclei -that convey visual information to cortex. A critical step towards understanding the functional impact of sSC neurons on these parallel thalamo-cortical pathways is determining whether different classes of sSC neurons, which are known to respond to different features of visual stimuli, innervate overlapping or distinct thalamic targets. Here, we identified a transgenic mouse line that labels sSC neurons that project to dLGN but not LP. We utilized selective expression of fluorophores and channelrhodopsin in this and previously characterized mouse lines to demonstrate that distinct cell types give rise to sSC projections to dLGN and LP. We further show that the glutamatergic sSC cell type that projects to dLGN also provides input to the sSC cell type that projects to LP. These results clarify the cellular origin of parallel sSC-thalamo-cortical pathways and reveal an interaction between these pathways via local connections within the sSC.

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    06/12/18 | A connectome based hexagonal lattice convolutional network model of the Drosophila visual system.
    Tschopp FD, Reiser MB, Turaga SC
    arXiv. 2018 Jun 12:1806.04793

    What can we learn from a connectome? We constructed a simplified model of the first two stages of the fly visual system, the lamina and medulla. The resulting hexagonal lattice convolutional network was trained using backpropagation through time to perform object tracking in natural scene videos. Networks initialized with weights from connectome reconstructions automatically discovered well-known orientation and direction selectivity properties in T4 neurons and their inputs, while networks initialized at random did not. Our work is the first demonstration, that knowledge of the connectome can enable in silico predictions of the functional properties of individual neurons in a circuit, leading to an understanding of circuit function from structure alone.

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