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Suver, M. P.

Publications and source records attributed to Suver, M. P..

2 recordsLinked to original sources

Active antennal movements in Drosophila tune wind encoding

Many insects actively move their antennae, but how these movements influence sensory encoding is not fully understood. Antennae are used to smell odors1,2, detect auditory cues3,4, and sense mechanosensory stimuli such as wind5 and objects6-8, frequently by combining active movement with sensation. Genetic access to antennal motor systems would thus provide a powerful tool for dissecting the circuit mechanisms underlying active sensing, but little is known about how the most genetically tractable insect, Drosophila melanogaster, moves its antennae. Here we use DeepLabCut to measure how tethered Drosophila move their antennae in the presence of sensory stimuli, and identify genetic reagents for controlling antennal movement. We find that flies perform both slow and fast antennal movements in response to wind-induced deflections, but not the attractive odor apple cider vinegar. We describe four muscles in the first antennal segment that control antennal movements, and identify genetic driver lines that provide access to two groups of antennal motor neurons and an antennal muscle. Through optogenetic inactivation, we provide evidence that antennal motor neurons are specialized for different movement speeds. Finally, we show that activation of antennal motor neurons and muscles can improve the gain and acuity of wind direction encoding. Together, our experiments provide insight into the neural control of antennal movement and suggest that Drosophila actively position their antennae to tune the precision of wind encoding.

neuroscience↗

Encoding of wind direction by central neurons in Drosophila

Wind is a major navigational cue for insects, but how wind direction is decoded by central neurons in the insect brain is unknown. Here, we find that walking flies combine signals from both antennae to orient to wind during olfactory search behavior. Movements of single antennae are ambiguous with respect to wind direction, but the difference between left and right antennal displacements yields a linear code for wind direction in azimuth. Second-order mechanosensory neurons share the ambiguous responses of single antenna and receive input primarily from the ipsilateral antenna. Finally, we identify a novel set of neurons, which we call wedge projection neurons, that integrate signals across the two antennae and receive input from at least three classes of second-order neurons to produce a more linear representation of wind direction. This study establishes how a feature of the sensory environment - the wind direction - is decoded by single neurons that compare information across two sensors.

neuroscience↗