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van Breugel, F.

Publications and source records attributed to van Breugel, F..

15 recordsLinked to original sources
bioRxiv2026

Neural control of respiration in Drosophila

Adaptive control of breathing is essential for life, yet the neural circuits that couple respiration to locomotion and internal physiological state remain poorly understood. Insects regulate gas exchange through spiracles: valve-like openings in the cuticle that allow oxygen uptake while minimizing water loss. We find that spiracle opening in Drosophila is dynamically matched to flight power and reduced by dehydration. We identify the motor neurons that innervate the spiracle muscles and show that their optogenetic activation closes all eighteen spiracles and rapidly limits flight power. Inhibitory interneurons transmit descending flight commands to the spiracle motor neurons, opening spiracles in proportion to metabolic demand. A parallel interoceptive pathway converges on the same interneurons to close the spiracles and suppress flight. Feedforward descending commands thus couple flight power to spiracle opening, while interoceptive feedback pathways close spiracles to balance oxygen supply against water loss. This compact circuit architecture may reflect a general solution for matching respiration to the competing demands of locomotion and water conservation.

neuroscience↗
bioRxiv2026

Olfactory Search Behavior Across Flow Regimes Supports a Unifying Framework

How animals perform odor-guided search across the broad range of dynamic flow conditions they encounter in nature is not well understood. Prior work treats established strategies such as circling and zigzagging as discrete, context-dependent behaviors. Here, we propose a parsimonious mathematical framework that unites these motifs into a continuum. We show that free flying Drosophila exhibit this continuum by smoothly reshaping search behavior between circling and zigzagging across unsteady flow, still air, and a range of wind speeds. Strikingly, a flow-invariant rhythmic course progression underlies this behavioral spectrum. Available data from moths and sharks across different flow regimes suggest a similarly preserved rhythm, while the rate of this rhythm varies across taxa. Together, these results support a common conceptual basis for olfactory search behavior and explain how search geometry can adapt automatically to local flow.

animal behavior and cognition↗
bioRxiv2026

Wind history shapes olfactory search response in free flying Drosophila melanogaster

The ability of flying insects to locate distant food and mates by tracking odor plumes through turbulent and unsteady flow represents a remarkable feat of sensorimotor integration. Successful navigation requires not only extracting a reliable directional estimate from an intermittent olfactory signal, but also contending with the challenging dynamics of variable winds. While prior work has established that insects integrate the history of odor encounters to shape search decisions, whether they also retain a working memory of recently experienced wind conditions has remained unknown. Here, we use optogenetics combined with controlled wind perturbations in a free-flight wind tunnel to investigate how wind history modulates the olfactory search behavior of Drosophila melanogaster. By introducing lateral "gust" flow via auxiliary fans and independently delivering olfactory stimuli, we show that the wind experienced during an olfactory stimulus shapes both the immediate surge response and the subsequent spatial search. Flies that received an olfactory stimulus while being displaced by a crosswind gust were significantly more likely to return to the gust zone during the post-stimulus search phase compared to flies that received the same odor cue in steady laminar flow. Meanwhile, surge responses and course directions exhibited during search indicate that moment-to-moment flight kinematics may be driven more by instantaneous flow. These results reveal that wind experience is tracked in addition to olfactory experience, and provide evidence that Drosophila maintain a short-term working memory of ambient wind conditions to guide olfactory navigation.

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

Vespula pensylvanica locate odor sources across diverse natural wind conditions

Many organisms across ecosystems track odor plumes to locate mates and food. In flying insects, the task of localizing an odor source is particularly challenging due to the complicated dynamics associated with wind flow and odor plume dispersion through spatially complex environments. Although wind tunnel experiments have been instrumental for answering many questions related to olfactory search, such experiments cannot replicate the complexity of natural wind conditions. Thus, our knowledge of how real-world wind characteristics influence insects success and strategies to locate odor sources remains an open area of investigation. Here, we tested whether certain wind conditions were more favorable for foraging insects by comparing yellowjacket arrival times and corresponding wind conditions across three distinct natural environments. Our results indicate that Vespula pensylvanica are capable of locating odor sources across the full range of observed wind conditions, without any clear preferences. This suggests that insects have adapted strategies to perform odor localization tasks across the full spectrum of natural wind that they may encounter. Our field-based approach provides insight into key considerations for future wind tunnel experiments which seek to better resolve insect plume tracking in understudied flow regimes.

animal behavior and cognition↗
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

Discovering and exploiting active sensing motifs forestimation with empirical observability

Organisms and machines must use measured sensory cues to estimate unknown information about themselves or their environment. Cleverly applied sensor motion can be exploited to enrich the quality of sensory data and improve estimation. However, a major barrier to modeling such active sensing problems is the lack of empirical, yet rigorous, tools for quantifying the relationship between movement and estimation performance. Here, we introduce "BOUNDS: Bounding Observability for Uncertain Nonlinear Dynamic Systems". BOUNDS can discover patterns of sensor motion that increase information and reduce uncertainty in either real or simulated data. Crucially, it is suitable for high dimensional and partially observable nonlinear systems with sensor noise. We demonstrate BOUNDS through a case study on how flying insects estimate wind properties, showing that specific active sensing motifs improve estimation. Additionally, we present a framework to refine sporadic estimates from active sensing. When combined with an artificial neural network, we show that the information gained via active sensing in real Drosophila flight trajectories is suitable for precise wind direction estimation. Collectively, our work will help decode active sensing in organisms and inform the design of estimation algorithms for machines.

systems biology↗
bioRxiv2023

Wind Gates Search States in Free Flight

For organisms tracking a chemical cue to its source, the motion of their surrounding fluid provides crucial information for success. Swimming and flying animals engaged in olfaction driven search often start by turning into the direction of an oncoming wind or water current. However, it is unclear how organisms adjust their strategies when directional cues are absent or unreliable, as is often the case in nature. Here, we use the genetic toolkit of Drosophila melanogaster to develop an optogenetic paradigm to deliver temporally precise "virtual" olfactory experiences for free-flying animals in either laminar wind or still air. We first confirm that in laminar wind flies turn upwind. Furthermore, we show that they achieve this using a rapid ([~]100 ms) turn, implying that flies estimate the ambient wind direction prior to "surging" upwind. In still air, flies adopt remarkably stereotyped "sink and circle" search state characterized by [~]60{degrees}turns at 3-4 Hz, biased in a consistent direction. Together, our results show that Drosophila melanogaster assess the presence and direction of ambient wind prior to deploying a distinct search strategy. In both laminar wind and still air, immediately after odor onset, flies decelerate and often perform a rapid turn. Both maneuvers are consistent with predictions from recent control theoretic analyses for how insects may estimate properties of wind while in flight. We suggest that flies may use their deceleration and "anemometric" turn as active sensing maneuvers to rapidly gauge properties of their wind environment before initiating a proximal or upwind search routine.

animal behavior and cognition↗
bioRxiv2023

Sensory neuron population expansion enhances odour tracking through relaxed projection neuron adaptation

The evolutionary expansion of sensory neuron populations detecting important environmental cues is widespread, but functionally enigmatic. We investigated this phenomenon through comparison of homologous neural pathways of Drosophila melanogaster and its close relative Drosophila sechellia, an extreme specialist for Morinda citrifolia noni fruit. D. sechellia has evolved species-specific expansions in select, noni-detecting olfactory sensory neuron (OSN) populations, through multigenic changes. Activation and inhibition of defined proportions of neurons demonstrate that OSN population increases contribute to stronger, more persistent, noni-odor tracking behavior. These sensory neuron expansions result in increased synaptic connections with their projection neuron (PN) partners, which are conserved in number between species. Surprisingly, having more OSNs does not lead to greater odor-evoked PN sensitivity or reliability. Rather, pathways with increased sensory pooling exhibit reduced PN adaptation, likely through weakened lateral inhibition. Our work reveals an unexpected functional impact of sensory neuron expansions to explain ecologically-relevant, species-specific behavior.

neuroscience↗
bioRxiv2023

Odor source location can be predicted from a time-history of odor statistics for a large-scale outdoor plume

Odor plumes in turbulent environments are intermittent and sparse. Lab-scaled experiments suggest that information about the source distance may be encoded in odor signal statistics, yet it is unclear whether useful and continuous distance estimates can be made under real-world flow conditions. Here we analyze odor signals from outdoor experiments with a sensor moving across large spatial scales in desert and forest environments to show that odor signal statistics can yield useful estimates of distance. We show that achieving accurate estimates of distance requires integrating statistics from 5-10 seconds, with a high temporal encoding of the olfactory signal of at least 20 Hz. By combining distance estimates from a linear model with wind-relative motion dynamics, we achieved source distance estimates in a 60x60 m2 search area with median errors of 3-8 meters, a distance at which point odor sources are often within visual range for animals such as mosquitoes.

ecology↗
bioRxiv2023

Near-surface wind variability over spatiotemporal scales relevant to plume tracking insects

Odor plume tracking is an important biological process for many organisms, and flying insects have served as popular model systems for studying these behaviors both in the field and in lab settings. The shape and statistics of the airborne odor plumes that insects follow are largely governed by the wind that advects them. Prior atmospheric studies have investigated aspects of microscale wind patterns with an emphasis on characterizing pollution dispersion, enhancing weather prediction models, and for assessing wind energy potential. Here, we aim to characterize microscale wind dynamics through the lens of short-term ecological functions by focusing on spatial and temporal scales most relevant to an insect actively searching for an odor source. We collected and compared near-surface wind data across three distinct environments (sage steppe, forest, and urban) in locations across Northern Nevada. Our findings show that near-surface wind direction variability decreases with increasing wind speeds and increases in environments with greater surface complexity. Across environments, there is a strong correlation between the variability in wind speed (i.e. turbulence intensity) and wind direction (i.e. the standard deviation in wind direction). In some environments, the standard deviation in wind direction varied as much as 15{degrees} to 75{degrees} on time scales of 1-10 minutes. We draw insights between our findings and previous plume tracking experiments to provide a general intuition for future field research and guidance for wind tunnel experimental design. From our analyses, we hypothesize that there may be an ideal range of wind speeds and environment complexity in which insects will be most successful when tracking an odor plume to its source.

ecology↗
bioRxiv2022

Active Anemosensing Hypothesis: How Flying Insects Could Estimate Ambient Wind Direction Through Sensory Integration & Active Movement

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction, and direction of motion. Here we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging maneuvers characteristic of plume tracking animals trajectories.

animal behavior and cognition↗
bioRxiv2020

Correlated decision making across multiple phases of olfactory guided search in Drosophila

All motile organisms must search for food, often requiring the exploration of heterogeneous environments across a wide range of spatial scales. Recent field and laboratory experiments with the fruit fly, Drosophila, have revealed that they employ different strategies across these regimes, including kilometer scale straight-path flights between resource clusters, zig-zagging trajectories to follow odor plumes, and local search on foot after landing. However, little is known about the extent to which experiences in one regime might influence decisions in another. To determine how a flies odor plume tracking during flight is related to their behavior after landing, I tracked the behavior of individually labelled fruit flies as they explored an array of three odor emitting, but food-barren, objects. The distance flies travelled on the objects in search of food was correlated with the time elapsed between their visits, suggesting that their in-flight plume tracking and on-foot local search behaviors are interconnected through a lossy memory-like process.

animal behavior and cognition↗
bioRxiv2020

The long-distance flight behavior of Drosophila suggests a general model for wind-assisted dispersal in insects.

Despite the ecological importance of long-distance dispersal in insects, its underlying mechanistic basis is poorly understood. One critical question is how insects interact with the wind to increase their travel distance as they disperse. To gain insight into dispersal using a species amenable to further investigation using genetic tools, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically-baited traps in a 1 km-radius ring around the release site, equipped with machine vision systems that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼15 km in a single flight in still air, and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by a model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air, but are increasingly advected downwind as winds intensify. In contrast, our field data do not support a Lévy flight model of dispersal, despite the fact that our experimental conditions almost perfectly match the core assumptions of that theory.Significance Statement Flying insects play a vital role in terrestrial ecosystems, and their decline over the past few decades has been implicated in a collapse of many species that depend upon them for food. By dispersing over large distances, insects transport biomass from one region to another and thus their flight behavior influences ecology on a global scale. Our experiments provide key insight into the dispersal behavior of insects, and suggest that these animals employ a single algorithm that is functionally robust in both still air and under windy conditions. Our results will make it easier to study the ecologically important phenomenon of long-distance dispersal in a genetic model organism, facilitating the identification of cellular and genetic mechanisms.Competing Interest StatementThe authors have declared no competing interest.View Full Text

animal behavior and cognition↗
bioRxiv2017

Drosophila have distinct activity-gated pathways that mediate attraction and aversion to CO2

Carbon dioxide is a volatile and broad signal of many organic processes, and serves as a convenient cue for insects in search of blood hosts1-6, flowers7, decaying matter8-11, communal nests12, fruit13, and wildfires14. Curiously, although Drosophila melanogaster feed on yeast that produce CO2 and ethanol during fermentation, laboratory experiments suggest that flies actively avoid CO215-25. Here, we resolve this paradox by showing that both flying and walking fruit flies do actually find CO2 attractive, but only when they are in an active state associated with foraging. Aversion at low activity levels may be an adaptation to avoid CO2-seeking-parasites, or succumbing to respiratory acidosis in the presence of high concentrations of CO2 that are occasionally found in nature26,27. In contrast to CO2, flies are attracted to ethanol in all behavioral states, and invest twice as much time searching near ethanol compared to CO2. These behavioral differences reflect the fact that whereas CO2 is a generated by many natural processes, ethanol is a unique signature of yeast fermentation. Using genetic tools, we determined that the evolutionarily ancient ionotropic co-receptor IR25a is required for both CO2 and ethanol attraction, and that the receptors previously identified for CO2 avoidance are not involved. Our study lays the foundation for future research to determine the neural circuits underlying both state- and odorant-dependent decision making in Drosophila.

neuroscience↗