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3 Janelia Publications

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    04/22/17 | The comprehensive connectome of a neural substrate for 'ON' motion detection in Drosophila.
    Takemura S, Nern A, Chklovskii DB, Scheffer LK, Rubin GM, Meinertzhagen IA
    eLife. 2017 Apr 22;6:. doi: 10.7554/eLife.24394

    Analysing computations in neural circuits often uses simplified models because the actual neuronal implementation is not known. For example, a problem in vision, how the eye detects image motion, has long been analysed using Hassenstein-Reichardt (HR) detector or Barlow-Levick (BL) models. These both simulate motion detection well, but the exact neuronal circuits undertaking these tasks remain elusive. We reconstructed a comprehensive connectome of the circuits of Drosophila's motion-sensing T4 cells using a novel EM technique. We uncover complex T4 inputs and reveal that putative excitatory inputs cluster at T4's dendrite shafts, while inhibitory inputs localize to the bases. Consistent with our previous study, we reveal that Mi1 and Tm3 cells provide most synaptic contacts onto T4. We are, however, unable to reproduce the spatial offset between these cells reported previously. Our comprehensive connectome reveals complex circuits that include candidate anatomical substrates for both HR and BL types of motion detectors.

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    04/10/17 | Stem cell-intrinsic, seven-up-triggered temporal factor gradients diversify intermediate neural progenitors.
    Ren Q, Yang C, Liu Z, Sugino K, Mok K, He Y, Ito M, Nern A, Otsuna H, Lee T
    Current Biology : CB. 2017 Apr 10;27(9):1303-13. doi: 10.1016/j.cub.2017.03.047

    Building a sizable, complex brain requires both cellular expansion and diversification. One mechanism to achieve these goals is production of multiple transiently amplifying intermediate neural progenitors (INPs) from a single neural stem cell. Like mammalian neural stem cells, Drosophila type II neuroblasts utilize INPs to produce neurons and glia. Within a given lineage, the consecutively born INPs produce morphologically distinct progeny, presumably due to differential inheritance of temporal factors. To uncover the underlying temporal fating mechanisms, we profiled type II neuroblasts' transcriptome across time. Our results reveal opposing temporal gradients of Imp and Syp RNA-binding proteins (descending and ascending, respectively). Maintaining high Imp throughout serial INP production expands the number of neurons and glia with early temporal fate at the expense of cells with late fate. Conversely, precocious upregulation of Syp reduces the number of cells with early fate. Furthermore, we reveal that the transcription factor Seven-up initiates progression of the Imp/Syp gradients. Interestingly, neuroblasts that maintain initial Imp/Syp levels can still yield progeny with a small range of early fates. We therefore propose that the Seven-up-initiated Imp/Syp gradients create coarse temporal windows within type II neuroblasts to pattern INPs, which subsequently undergo fine-tuned subtemporal patterning.

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    Rubin LabReiser LabFly Functional Connectome
    04/05/17 | The emergence of directional selectivity in the visual motion pathway of Drosophila.
    Strother JA, Wu S, Wong AM, Nern A, Rogers EM, Le JQ, Rubin GM, Reiser MB
    Neuron. 2017 Apr 05;94(1):168-182.e10. doi: 10.1016/j.neuron.2017.03.010

    The perception of visual motion is critical for animal navigation, and flies are a prominent model system for exploring this neural computation. In Drosophila, the T4 cells of the medulla are directionally selective and necessary for ON motion behavioral responses. To examine the emergence of directional selectivity, we developed genetic driver lines for the neuron types with the most synapses onto T4 cells. Using calcium imaging, we found that these neuron types are not directionally selective and that selectivity arises in the T4 dendrites. By silencing each input neuron type, we identified which neurons are necessary for T4 directional selectivity and ON motion behavioral responses. We then determined the sign of the connections between these neurons and T4 cells using neuronal photoactivation. Our results indicate a computational architecture for motion detection that is a hybrid of classic theoretical models.

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