Biology subjects

Nagel, K. I.

Publications and source records attributed to Nagel, K. I..

14 recordsLinked to original sources

bioRxiv2026

Ballistic food approaches in Parhyale hawaiensis require the antennae

Many arthropods (insects and crustaceans) rely on their antennular chemosensory system to detect key environmental resources like food. While odor mediated food search is well studied in insects, characterization of crustacean chemosensory behavior has been limited by the long lifespans and large size of traditional crustacean model species. Here, we report the first characterizations of the food search behaviors of the genetically tractable amphipod crustacean, Parhyale hawaiensis. We find that Parhyale can locate an odorous food pellet, and predominantly approach food using direct, targeted swims from the arena walls. Removal of both first and second antennae dramatically reduced foraging success and impaired Parhyales ability to control take-off angle and maintain a stable heading during swims. Removal of the first or second antenna alone did not significantly disrupt foraging, and resulted in mild disruption of orientation phenotypes. Intact animals performed sharp turns near the location of the food pellet, which were observed when either first or second antenna were present, but not when all antennae were removed. Turns were longer and had higher average angular velocities following removal of either set of antennae, with full antenna removals representing the most extreme phenotype. In contrast with the long-held theory that the crustacean second antennae exclusively mediate contact chemosensation, we report that first- and second- antennae both contribute similarly to food localization and stabilization of locomotion in Parhyale in our behavioral paradigm. This work establishes Parhyale as an accessible model for studying olfactory behaviors in an aquatic arthropod.

animal behavior and cognition↗

bioRxiv2026

Predicting Drosophila Body Orientation from a Translational Trajectory using an Artificial Neural Network

Body orientation is a key variable in the analysis of insect flight behavior, yet it remains difficult to measure across the full extent of a trajectory in most experimental settings. Although modern tracking systems reliably capture the position and velocity of the center of mass, resolving body yaw orientation typically requires dedicated hardware confined to a small, purpose-built volume, and is impractical for large-scale or long-duration studies. Here, we develop a data-driven estimator that predicts body yaw orientation directly from translational flight trajectory data. We trained a fully connected feedforward artificial neural network (ANN) on a dataset in which both flight trajectory and body orientation were recorded simultaneously in freely flying Drosophila, using a time-delay embedding of ground velocity, air velocity, and inferred thrust vectors as input features. Trained on 2,340 trajectories, the ANN predictor achieved a median absolute angular error of approximately 5{degrees}, with accurate heading recovery across the full [-{pi}, {pi}) range. The estimator provides a practical tool for recovering body orientation information from existing trajectory datasets in which only center-of-mass motion was recorded, extending the behavioral and computational analysis of insect navigation to previously inaccessible data.

animal behavior and cognition↗

bioRxiv2025

Molecular evolution of CO2-sensing ab1C neurons underlies divergent sensory responses in the Drosophila suzukii species group

Organisms evolve behavioral and morphological traits to adapt to their ecological niches, yet the genetic basis of adaptation remains largely unknown. Drosophila suzukii has evolved a distinctive oviposition preference for ripe fruit, unlike most Drosophila species such as D. melanogaster, which prefer overripe fruit. Carbon dioxide (CO2), a metabolic volatile that increases as fruit ripens and decays, may act as a critical ecological cue shaping these preferences. Here, we focus on D. suzukii and its sister species D. subpulchrella, which shows an intermediate preference, to investigate the genetic basis of CO2 responses. We report a previously unrecognized shift in CO2-guided oviposition: D. suzukii and D. subpulchrella readily lay eggs on CO2-enriched substrates, unlike the strong aversion displayed by D. melanogaster. Electrophysiological recordings revealed a species-specific sensory tuning, characterized by an early spike in CO2-evoked neuronal firing in D. suzukii and D. subpulchrella--a temporal response feature absent in D. melanogaster. To dissect the genetic basis of this shift, we generated transgenic D. melanogaster expressing either the D. suzukii Gr63a coding sequence or the D. subpulchrella Gr63a cis-regulatory element. Remarkably, both manipulations reproduced the early onset firing pattern of CO2 sensitivity, demonstrating that either receptor function or expression can independently drive this sensitivity adaptation. Our findings reveal that evolution can shape ecological adaptation through distinct genetic mechanisms, leading to convergent physiological traits among closely related species. Author SummaryAnimals rely on their senses to locate food sources and identify suitable reproductive sites in their environment. Closely related species can evolve strikingly different preferences as they adapt to new environments. For example, the invasive fruit fly D. suzukii lays its eggs in ripe fruit, unlike most other fruit flies, such as D. melanogaster, which prefer decaying fruit. Because CO2 levels increase as fruit ripens and ferments, changes in how flies detect CO2 may have contributed to these ecological differences. We compared CO2 responses between D. suzukii and its sister species D. subpulchrella, and found that both species respond to CO2 differently from D. melanogaster: both in their oviposition preferences and neural CO2 sensitivity. By introducing either the D. subpulchrella or D. suzukii CO2 receptor gene coding sequences or regulatory regions into D. melanogaster, we found that this altered sensitivity can arise from changes either in the receptors protein-coding region or in the DNA elements that control its expression. Our results show that evolution can act through multiple genetic mechanisms to fine-tune sensory systems, revealing how subtle molecular changes can generate ecological diversity among closely related species.

evolutionary biology↗

bioRxiv2025

Disinhibition of a recurrent attractor gates a persistent goal signal for navigation

Recurrent attractor networks are widely thought to form the basis of working memory1-3, but how stable attractor activity can be rapidly switched on and off is unclear4-7. Here we investigate how stability and rapid switching can be combined in a discrete recurrent circuit of the fly navigation center8. h{Delta}K and PFG neurons are recurrently connected in a ring structure. Using in vivo imaging, we find that these two populations exhibit shared persistent bump activity that turns on with odor and terminates at the end of a goal-directed upwind run. Using whole-cell recordings, we show that persistence in h{Delta}K depends on recurrent signalling, and that h{Delta}K receives slow recurrent excitation and fast inhibition from its synaptic partners. Computational modeling reveals that this combination of slow excitation with fast inhibition yields persistent attractor dynamics over a range of excitation and inhibition strengths. Next we examine the mechanisms that allow this activity bump to be rapidly turned on and off. We find that while both populations show positionally stable bump activity during goal-directed runs, during turns and rest the PFG bump tracks heading while h{Delta}K is supressed. We can reproduce these differential dynamics in our model by using inhibition to dynamically uncouple activity in h{Delta}K from PFG. When h{Delta}K is inhibited, PFG neurons follow their inputs from the compass system; when h{Delta}K is disinhibited, recurrent interactions lock this input into place, forming a heading memory. Consistent with this model, we find that inhibitory inputs onto h{Delta}K increase during turns and are suppressed during odor input and goal-directed upwind runs. Our work reveals how disinhibition can serve as a gate to rapidly write an ongoing measurement to a recurrent memory circuit.

neuroscience↗

bioRxiv2025

A compact multisensory representation of self-motion is sufficient for computing an external world variable

External forces such as gravity and wind fundamentally shape how an animal navigates through the world, but force magnitude and direction cannot be directly measured by an animal in motion. How the brain integrates multiple sensory cues to determine the direction of such external forces remains unclear. In the fruit fly (Drosophila melanogaster) columnar inputs to the navigation center, known as PFNs, have been shown to represent both visual and mechano-sensory cues about self-motion in a similar vector format, but the dynamics and integration of these cues, particularly during complex natural movements, are not known. Here we used 2-photon imaging to investigate the dynamic representation and integration of multi-sensory self-motion cues - optic flow and airflow - across PFNs. We find that one type, called PFNd, linearly integrates optic flow and airflow direction signals with distinct dynamics. We next reveal airflow speed as well as direction encoding by PFNp_c neurons. Imaging from available genetic lines suggests that many PFN types likely encode functions of airflow speed and direction. Based on these data, we construct and validate computational models of how visual and mechano-sensory dynamics are integrated and represented across PFN populations. We then use these models to estimate neural responses during real and simulated flight maneuvers. Applying a nonlinear empirical observability analysis to these responses, we show that active turning and deceleration maneuvers combined with PFN representations can decode the direction of an ambient external cue (wind) during free flight, and identify the theoretical contribution of different PFNs to this ability. Finally, we show that an anatomically-inspired artificial neural network can successfully decode wind direction from PFN representations and identify components of the algorithm used by both the network and real flies to orient upwind during olfactory navigation in flight. Our work provides evidence that active sensation, combined with multi-sensory encoding, can allow a compact system like the fly navigation center to infer a property of the external world that cannot be directly measured by a single sensory system.

neuroscience↗

bioRxiv2024

Neural dynamics for working memory and evidence integration during olfactory navigation in Drosophila

Working memory and evidence integration are fundamental components of cognition thought to arise from distributed circuits throughout the brain1-2. Theoretical3,4 and behavioral studies5,6 argue that both processes are required for plume navigation, an innate task in which animals use stochastic sensory cues to navigate towards the unknown location of an odor source7-10. Here we identify a small population of local neurons in the navigation center of Drosophila11-13 that exhibits both evidence integration and working memory dynamics during goal-directed olfactory navigation. Developing a closed-loop virtual plume navigation paradigm, we show that a bump of activity in this population ramps up with successive odor encounters, and can persist for variable intervals after odor loss. While bump activity persists, the fly maintains the goal heading it adopted during odor. Silencing these neurons impairs the persistence of upwind heading after odor loss. Simulations show that the time constant of persistence observed in these neurons optimizes navigation in a turbulent boundary layer plume. Our work localizes working memory and evidence integration to a specific group of genetically-identified neurons, which will facilitate the mechanistic dissection of these building blocks of cognition.

neuroscience↗

bioRxiv2024

Inhibitory control of locomotor statistics in walking Drosophila

In order to forage for food, many animals regulate not only specific limb movements but the statistics of locomotor behavior over time, switching between long-range dispersal and localized search depending on resource availability. How pre-motor circuits regulate such locomotor statistics is not clear. Here we analyze and model locomotor statistics in walking Drosophila, and their modulation by attractive food odor. Odor evokes three motor regimes in flies: baseline walking, upwind running during odor, and search behavior following odor loss. During search behavior, we find that flies adopt higher angular velocities and slower ground speeds, and tend to turn for longer periods of time in one direction. We further find that flies spontaneously adopt periods of different mean ground speed, and that these changes in state influence the length of odor-evoked runs. We next developed a simple model of neural locomotor control that suggests that contralateral inhibition plays a key role in regulating the statistical features of locomotion. As the fly connectome predicts decussating inhibitory neurons in the lateral accessory lobe (LAL), a pre-motor structure, we gained genetic access to a subset of these neurons and tested their effects on behavior. We identified one population of neurons whose activation induces all three signature of search and that bi-directionally regulates angular velocity at odor offset. We identified a second group of neurons, including a single LAL neuron pair, that bi-directionally regulate ground speed. Together, our work develops a biologically plausible computational architecture that captures the statistical features of fly locomotion across behavioral states and identifies potential neural substrates of these computations.

neuroscience↗

bioRxiv2023

Scalable Apparatus to Measure Posture and Locomotion (SAMPL): a high-throughput solution to study unconstrained vertical behavior in small animals

Balance and movement are impaired in a wide variety of neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and loco-motor kinematics, but without the throughput and scalability necessary to screen candidate genes / potential therapeutics. We present a powerful solution: a Scalable Apparatus to Measure Posture and Locomotion (SAMPL). SAMPL includes extensible imaging hardware and low-cost open-source acquisition software with real-time processing. We first demonstrate that SAMPLs hardware and acquisition software can acquire data from D. melanogaster, C.elegans, and D. rerio as they move vertically. Next, we leverage SAMPLs throughput to rapidly (two weeks) gather a new zebrafish dataset. We use SAMPLs analysis and visualization tools to replicate and extend our current understanding of how zebrafish balance as they navigate through a vertical environment. Next, we discover (1) that key kinematic parameters vary systematically with genetic background, and (2) that such background variation is small relative to the changes that accompany early development. Finally, we simulate SAMPLs ability to resolve differences in posture or vertical navigation as a function of effect size and data gathered - key data for screens. Taken together, our apparatus, data, and analysis provide a powerful solution for laboratories using small animals to investigate balance and locomotor disorders at scale. More broadly, SAMPL is both an adaptable resource for laboratories looking process video-graphic measures of behavior in real-time, and an exemplar of how to scale hardware to enable the throughput necessary for screening.

neuroscience↗

bioRxiv2022

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↗

bioRxiv2021

Synaptic control of temporal processing in the Drosophila olfactory system

Temporal filtering of sensory stimuli is a key neural computation, but the way such filters are implemented within the brain is unclear. One potential mechanism for implementing temporal filters is short-term synaptic plasticity, which is governed in part by the expression of pre-synaptic proteins that position synaptic vesicles at different distances to calcium channels. Here we leveraged the Drosophila olfactory system to directly test the hypothesis that short-term synaptic plasticity shapes temporal filtering of sensory stimuli. We used optogenetic activation to drive olfactory receptor neuron (ORN) activity with high temporal precision and knocked down the presynaptic priming factor unc13A specifically in ORNs. We found that this manipulation specifically decreases and delays transmission of high frequencies, leading to poorer encoding of distant plume filaments. We replicate this effect using a previously-developed model of transmission at this synapse, which features two components with different depression kinetics. Finally, we show that upwind running, a key component of odor source localization, is preferentially driven by high-frequency stimulus fluctuations, and this response is reduced by unc13A knock-down in ORNs. Our work links the extraction of particular temporal features of a sensory stimulus to the expression of particular presynaptic molecules.

neuroscience↗

bioRxiv2021

A neural circuit for wind-guided olfactory navigation

To navigate towards a food source, animals must frequently combine odor cues that tell them what sources are useful with wind direction cues that tell them where the source can be found. Where and how these two cues are integrated to support navigation is unclear. Here we identify a pathway to the Drosophila fan-shaped body (FB) that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify FB local neurons called h{Delta}C that receive input from this odor pathway and a previously described wind pathway. We show that h{Delta}C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h{Delta}C neurons promotes navigation in a reproducible direction, and that h{Delta}C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h{Delta}C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the FB to support goal-directed navigation.

neuroscience↗

bioRxiv2018

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↗

bioRxiv2018

Elementary sensory-motor transformations underlying olfactory navigation in walking fruit-flies

Odor attraction in walking Drosophila melanogaster is commonly used to relate neural function to behavior, but the algorithms underlying attraction are unclear. Here we develop a high-throughput assay to measure olfactory behavior in response to well-controlled sensory stimuli. We show that odor evokes two behaviors: an upwind run during odor (ON response), and a local search at odor offset (OFF response). Wind orientation requires antennal mechanoreceptors, but search is driven solely by odor. Using dynamic odor stimuli, we measure the dependence of these two behaviors on odor intensity and history. Based on these data, we develop a navigation model that recapitulates the behavior of flies in our apparatus, and generates realistic trajectories when run in a turbulent boundary layer plume. The ability to parse olfactory navigation into quantifiable elementary sensori-motor transformations provides a foundation for dissecting neural circuits that govern olfactory behavior.

neuroscience↗

bioRxiv2018

Dynamic integration of multisensory turn commands supports active reorienting during ongoing navigation.

A longstanding goal of systems neuroscience is to quantitatively describe how the brain integrates cues from multiple modalities over time. Here we develop a closed-loop orienting paradigm in Drosophila to study the algorithms by which stimuli from different modalities are combined during ongoing navigation. We show that flies faced with an attractive visual and an aversive mechanosensory cue exhibit sequential responses, first turning away from the co-localized stimuli before turning back toward them. We also find that the presence of the aversive cue slows flies turns toward the attractive target, suggesting that conflicting unimodal turn commands are summed to produce multisensory turns of intermediate velocity. We then test a series of computational frameworks and find that integration is best described by a model in which multimodal stimuli are continuously and dynamically scaled, converted into turn commands, and then summed to produce ongoing orientation behavior.

neuroscience↗