Antenna movements as a function of odorants’ biological value in honeybees (Apis mellifera L.)

Cholé, Hanna; Merlin, Alice; Henderson, Nicholas; Paupy, Estelle; Mahé, Prisca; Arnold, Gérard; Sandoz, Jean‐Christophe

doi:10.1038/s41598-022-14354-z

Cited by 8 publications

(7 citation statements)

References 112 publications

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“…Further studies are therefore needed to assess the influence of the incident direction of the odor flux on the capture by an oscillating antenna, and on the way an insect reorients itself in a directional odor flux. Indeed, for bees at least, several contradictory behaviors have been observed, see Cholé et al (2022) [17]. Furthermore, the concentration field in nature presents complex micro-structures containing information on the odor source [28].…”

Section: Limits Of the Papermentioning

confidence: 99%

“…This active sensing behavior is characterized by a vertical scanning movement, orthogonal to the flow direction (figure 1). Very recent studies with bees however show a dependency of antennal movement with odor characteristics [17,18]. Other authors also recently report that antennal movements and orientations might be related with strategies to obtain additional information about the odor source [19].…”

Section: Introductionmentioning

confidence: 98%

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Oscillations for active sensing in olfaction: bioinspiration from insect antennal movements

Claverie¹,

Steinmann²,

Bandjee³

et al. 2022

Bioinspir. Biomim.

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Crustacean and insect antennal scanning movements have been postulated to increase odorant capture but the exact mechanisms as well as measures of efficiency are wanting. The aim of this work is to test the hypothesis that an increase in oscillation frequency of a simplified insect antenna model translates in an increase of odorant capture, and to quantify by how much and through which mechanism. We approximate the antennal movements of bumblebees, quantified in a previous study, by a vertical oscillatory movement of a cylinder in a homogeneous horizontal flow with odorants. We test our Multiphysics flow and mass transfer numerical model with dedicated experiments using Particle Image Velocimetry. A new entire translating experimental measurement setup containing an oil tank enables us to work at appropriate Strouhal and Reynolds numbers. Increasing antennal oscillating frequency does increase the odorant capture rate, up to 200 %, proving this behavior being active sensing. This result holds however only up to a critical frequency. A decrease of efficiency characterizes higher frequencies, due to molecules depletion within oversampled regions, themselves defined by overlaying boundary layers. Despite decades of work on thermal and mass transfer studies on oscillating cylinders, no analogy with published cases was found. This is due to the unique flow regimes studied here, resulting from the combination of organ small size and low frequencies of oscillations. A theory for such flow regimes is thus to be developed, with applications to fundamental research on animal perception up to bioinspired olfaction.

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Section: Limits Of the Papermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Oscillations for active sensing in olfaction: bioinspiration from insect antennal movements

Claverie¹,

Steinmann²,

Bandjee³

et al. 2022

Bioinspir. Biomim.

View full text Add to dashboard Cite

show abstract

“…A previous study reported that ARs to odorants were limited in newly emerged workers and acquired in the adult life (Cholé et al, 2022). Thus, we next compared the AR to the vertical motion stimuli of newly merged (NE) and flying (F) workers to investigate whether ARs to visual stimuli also mature after emergence.…”

Section: Developmental Maturation Of Ar After Emergencementioning

confidence: 97%

“…In previous studies, the movements of insect antennae were measured by manually determining their position and angle for each frame of video or using phototransistors, which register the movement of the antennae (Erber and Kloppenburg, 1995;Erber et al, 1993;Okada and Toh, 2004). Recently, video analysis technologies have advanced, and methods for automatically tracking the movement of body parts of the honey bee have been reported, such as tracking the marked colors at the tip of the antennae or separating the outline of the antennae from the background by image processing (Cholé et al, 2015;Cholé et al, 2022;Roy Khurana and Sane, 2016). In addition, a markerless posture-tracking tool using deep learning, DeepLabCut (Mathis et al, 2018;Nath et al, 2019), has been widely used in various research fields, such as ecology and neuroscience (Mathis and Mathis, 2020), and is becoming recognized as a powerful tool that does not require special devices or expertise, in addition to being noninvasive and robust in analyzing .…”

Section: Introductionmentioning

confidence: 99%

Analysis of antennal responses to motion stimuli in the honey bee by automated tracking using DeepLabCut

Kohno

Kamata

Kubo

2023

Preprint

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Considering recent developments in gene manipulation methods for honey bees, establishing simple, robust, and indoor assay systems which can analyze behavioral components in detail is important for the rise of honey bee behavioral genetics. We focused on the antennal movements of the honey bee, which are used for not only multimodal sensory perception but also interactions between individuals. We developed an experimental system for analyzing the antennal responses (ARs) of the honey bee using DeepLabCut, a markerless posture-tracking tool using deep learning. The tracking of antennal movements during the presentation of vertical (downward and upward) motion stimuli using DeepLabCut successfully detected the ARs reported in the previous studies, where bees tilted their antennae in the direction opposite to the motion stimuli. In addition, we successfully detected ARs in response to horizontal (forward and backward) motion stimuli. An investigation of the developmental maturation of honey bee ARs showed that ARs to motion stimuli were not detected in bees immediately after emergence but became detectable through post-emergence development in an experience-independent manner. Furthermore, unsupervised clustering analysis using multidimensional data created by processing tracking data using DeepLabCut classified antennal movements into different clusters, suggesting that data-driven behavioral classification can apply to AR paradigms. These results reveal novel AR to visual stimuli and developmental maturation of ARs and suggest the efficacy of data-driven analysis for behavioral classification in behavioral studies of the honey bee.

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“…Our first aim was to investigate how antennal movement participates in spatial sampling. It has recently been shown that honeybees orient their antennae towards appetitive odour sources and away from aversive ones (Cholé et al (2022); Gascue et al (2022)). Moreover, the analysis demonstrated a general trend of positive correlation between the time the antennae spent focused on an odour target and its valence (Gascue et al (2022)).…”

Section: Exploration-exploitation Trade-offmentioning

confidence: 99%

Active smelling in the American cockroach

Hoffmann

Couzin-Fuchs

2022

Preprint

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Motion plays an essential role in sensory acquisition. From changing the position in which information can be acquired to fine scale probing and active sensing, animals actively control the way they interact with the environment. In olfaction, movement impacts the time and location of odour sampling as well as the flow of odour molecules around the olfactory organs. Employing a high resolution analysis, we investigate how the insect antennae interact with the olfactory environment in a species with a well studied olfactory system – the American cockroach. Cockroaches were tested in a wind-tunnel setup during the presentation of odours with different attractivity levels: colony extract, butanol and linalool. Our analysis revealed significant changes in antennal kinematics when odours are presented, including a shift towards the stream position, an increase in vertical movement and high-frequency local oscillations. Nevertheless, the antennal shifting occurred predominantly in a single antenna while the overall range covered by both antennae was maintained throughout. These findings hold true for both static and moving stimuli and are more pronounced for attractive odours. Furthermore, we find that upon odour encounter, there is an increased occurrence of high-frequency antennal sweeps and vertical strokes, which are shown to impact the olfactory environment's statistics directly. Our study lays out a tractable system for exploring the tight coupling between sensing and movement, in which antennal sweeps, in parallel to mammalian sniffing, are actively involved in facilitating odour capture and transport, generating odour intermittency in environments with low air movement where cockroaches dwell.

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Antenna movements as a function of odorants’ biological value in honeybees (Apis mellifera L.)

Cited by 8 publications

References 112 publications

Oscillations for active sensing in olfaction: bioinspiration from insect antennal movements

Oscillations for active sensing in olfaction: bioinspiration from insect antennal movements

Analysis of antennal responses to motion stimuli in the honey bee by automated tracking using DeepLabCut

Active smelling in the American cockroach

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