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      Multimodal cue integration in the dung beetle compass

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          Abstract

          South African ball-rolling dung beetles exhibit a unique orientation behavior to avoid competition for food: after forming a piece of dung into a ball, they efficiently escape with it from the dung pile along a straight-line path. To keep track of their heading, these animals use celestial cues, such as the sun, as an orientation reference. Here we show that wind can also be used as a guiding cue for the ball-rolling beetles. We demonstrate that this mechanosensory compass cue is only used when skylight cues are difficult to read, i.e., when the sun is close to the zenith. This raises the question of how the beetles combine multimodal orientation input to obtain a robust heading estimate. To study this, we performed behavioral experiments in a tightly controlled indoor arena. This revealed that the beetles register directional information provided by the sun and the wind and can use them in a weighted manner. Moreover, the directional information can be transferred between these 2 sensory modalities, suggesting that they are combined in the spatial memory network in the beetle’s brain. This flexible use of compass cue preferences relative to the prevailing visual and mechanosensory scenery provides a simple, yet effective, mechanism for enabling precise compass orientation at any time of the day.

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          Most cited references46

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          Visual Place Learning in Drosophila melanogaster

          The ability of insects to learn and navigate to specific locations in the environment has fascinated naturalists for decades. While the impressive navigation abilities of ants, bees, wasps, and other insects clearly demonstrate that insects are capable of visual place learning 1–4 , little is known about the underlying neural circuits that mediate these behaviors. Drosophila melanogaster is a powerful model organism for dissecting the neural circuitry underlying complex behaviors, from sensory perception to learning and memory. Flies can identify and remember visual features such as size, color, and contour orientation 5, 6 . However, the extent to which they use vision to recall specific locations remains unclear. Here we describe a visual place-learning platform and demonstrate that Drosophila are capable of forming and retaining visual place memories to guide selective navigation. By targeted genetic silencing of small subsets of cells in the Drosophila brain we show that neurons in the ellipsoid body, but not in the mushroom bodies, are necessary for visual place learning. Together, these studies reveal distinct neuroanatomical substrates for spatial versus non-spatial learning, and substantiate Drosophila as a powerful model for the study of spatial memories.
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            An Anatomically Constrained Model for Path Integration in the Bee Brain

            Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task – a celestial-cue based visual compass, and an optic-flow based visual odometer – but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light based compass-neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically-identified neurons suggested for each processing step. The resulting model-circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e. a ground velocity that is not precisely aligned with body orientation) typical of bee-flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model-circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings – suggesting a more basic function for central-complex connectivity from which path integration may have evolved.
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              The neural basis of Drosophila gravity-sensing and hearing.

              The neural substrates that the fruitfly Drosophila uses to sense smell, taste and light share marked structural and functional similarities with ours, providing attractive models to dissect sensory stimulus processing. Here we focus on two of the remaining and less understood prime sensory modalities: graviception and hearing. We show that the fly has implemented both sensory modalities into a single system, Johnston's organ, which houses specialized clusters of mechanosensory neurons, each of which monitors specific movements of the antenna. Gravity- and sound-sensitive neurons differ in their response characteristics, and only the latter express the candidate mechanotransducer channel NompC. The two neural subsets also differ in their central projections, feeding into neural pathways that are reminiscent of the vestibular and auditory pathways in our brain. By establishing the Drosophila counterparts of these sensory systems, our findings provide the basis for a systematic functional and molecular dissection of how different mechanosensory stimuli are detected and processed.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                June 24 2019
                : 201904308
                Article
                10.1073/pnas.1904308116
                6628800
                31235569
                8959f2dc-12da-4781-a2ef-a0123fc9a0fd
                © 2019

                Free to read

                https://www.pnas.org/site/aboutpnas/licenses.xhtml

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