Active Sensing in Bees Through Antennal Movements Is Independent of Odor Molecule

Abstract

When sampling odors, many insects are moving their antennae in a complex but repeatable fashion. Previous studies with bees have tracked antennal movements in only two dimensions, with a low sampling rate and with relatively few odorants. A detailed characterization of the multimodal antennal movement patterns as function of olfactory stimuli is thus wanted. The aim of this study is to test for a relationship between the scanning movements and the properties of the odor molecule. We tracked several key locations on the antennae of bumblebees at high frequency and in three dimensions while stimulating the insect with puffs of 11 common odorants released in a low-speed continuous flow. Water and paraffin were used as negative controls. Movement analysis was done with the neural network Deeplabcut. Bees use a stereotypical oscillating motion of their antennae when smelling odors, similar across all bees, independently of the identity of the odors and hence their diffusivity and vapor pressure. The variability in the movement amplitude among odors is as large as between individuals. The main type of oscillation at low frequencies and large amplitude is triggered by the presence of an odor and is in line with previous work, as is the speed of movement. The second oscillation mode at higher frequencies and smaller amplitude is constantly present. Antennae are quickly deployed when a stimulus is perceived, decorrelate their movement trajectories rapidly and oscillate vertically with a large amplitude and laterally with a smaller one. The cone of air space thus sampled was identified through the 3D understanding of the motion patterns. The amplitude and speed of antennal scanning movements seem to be function of the internal state of the animal, rather than determined by the odorant. Still, bees display an active olfactory sampling strategy. First, they deploy their antennae when perceiving an odor. Second, fast vertical scanning movements further increase the odorant capture rate. Finally, lateral movements might enhance the likelihood to locate the source of odor, similarly to the lateral scanning movement of insects at odor plume boundaries.

Predictive Uncertainty in State-Estimation Drives Active Sensing

“…While manifold forms of active sensing movements pervade animal behavior, full comprehension of the dynamics underpinning these movements continues to evade researchers [5, 22, 23]. A prevalent hypothesis suggests that active sensing operates akin to an open-loop system where process noise, or a population of active sensing neurons, introduces broad-spectrum disruptions to the motor commands [41].…”

“…Animals demonstrably employ manifold forms of active sensing movements [Bush et al, 2016, Claverie et al, 2023, Crimaldi et al, 2022. A prevalent hypothesis suggests that active sensing operates as an open-loop system where process noise, or a population of active sensing neurons, introduces broadspectrum disruptions to the motor commands [Feldman, 2016].…”

“…The diversity of active sensing is further exemplified by cockroaches, which utilize antenna movements to detect obstacles and gather tactile information [Okada andToh, 2006, Chen et al, 2020], spiders that interpret vibration signals transmitted through their webs for object localization [Nakata, 2010, Blamires et al, 2011, and various animals that dynamically modify their sensory volume through adjustments in physical orientation and focus. By selectively fortifying their sensory inputs, these animals continuously reshape their interactions with the environment [Uyanik et al, 2019, Crimaldi et al, 2022, Claverie et al, 2023, Hofmann et al, 2013.…”