Biology subjects

Egelhaaf, M.

Publications and source records attributed to Egelhaaf, M..

11 recordsLinked to original sources

bioRxiv2025

Embodied Navigation: whole-body movement drives path integration in large-scale free-walking virtual reality

Human navigation relies on combining body cues (vestibular and proprioceptive signals) with visual cues such as optic flow. The weighting and integration of these signals during the continuous tracking of walked distances and angles, known as path integration, remain poorly understood. Previous path integration studies have been limited to small spaces (< 150 m2) and the influence of complex environments on cue weighting of body and vision cues is still unclear. Here, we conducted the largest-environment free-walking virtual reality navigation study to date in a 45 x 25 m facility (1, 215 m2) using triangle completion tasks in naturalistic environments. We systematically manipulated sensory input across three conditions: natural active walking (full sensory integration), active joystick control (visual cues only), and blindfolded active walking (body cues only). Participants navigated through both sparse fallow land without trees and more complex forest environments with 400 trees. We embedded performance data in a Bayesian cue combination model to analyse the underlying combination mechanism. Our results provide evidence that most participants substantially favour body cues over visual cues in a non-Bayesian combination process, with considerable inter-individual variance in cue dominance strength and side biases. While transitioning from fallow land to forests reduced directional variance, weighting of body and visual information remained constant. These findings advance our understanding of human spatial navigation by demonstrating that body-based cues dominate path integration even in visually rich, large-scale environments, challenging assumptions about optimal Bayesian cue integration in human navigation.

neuroscience↗

bioRxiv2025

Uncovering persistent biases in human path integration by separating left and right trials

Navigation ability strongly varies between humans. Careful analysis of errors occurring in navigation, or indeed any cognitive process, offers insight into the underlying mechanisms at different levels. While analyses at the individual level allow nuanced identification of error persistences across conditions and time, the population level facilitates generalisation but precludes conclusions about lower-level phenomena. Regarding the critical navigation mechanism of path integration - the continuous tracking of navigated paths for self-localisation - previous studies have focused on populationlevel analyses, revealing systematic errors in estimating the travelled angles and distances. However, at the individual level, there are indications that people also possess left or right biases that are classically overlooked when pooling left and right trials. Therefore, we carefully investigate individual path integration errors in (1) a re-analysis of data from several influential human navigation studies, and (2) our own virtual reality path integration experiment. For both, we confirm time-persistent individual side biases, but find no evidence for consistent errors at the population level, suggesting that important aspects in human navigation performance might be overlooked by averaging across sides.

animal behavior and cognition↗

bioRxiv2025

Learning to avoid collisions: Bees use cues perceived before and after a collision to prevent negative consequences during navigation in cluttered areas

Bumblebees navigate complex environments where collisions with obstacles can impair flight performance. While bees possess innate collision avoidance reflexes, they may benefit from learning to identify and avoid high-risk collision areas using environmental cues. However, the temporal dynamics of how bees form associations between visual cues and collision experiences remain unclear. We investigated whether bumblebees associate visual cues perceived before or after collision events with a movement direction. Individual foragers were trained to navigate through a flight tunnel containing a transparent barrier and an LED panel that switched colours immediately after the bees first collision. Following training, we tested bees responses to each colour cue without the barrier. Bees demonstrated significant preferences for avoiding the previously blocked side when presented with either the pre-collision colour (81% correct responses) or post-collision colour (71% correct responses), while showing no preference when no colour cue was presented. Individual analysis revealed that 61% of bees responded to both cue types, while others showed selective responses to specific temporal windows. These results demonstrate that bees can form associations with visual cues encountered in different time windows relative to negative experiences, revealing temporal flexibility in associative learning that contributes to successful navigation in cluttered environments.

animal behavior and cognition↗

bioRxiv2025

Navigating in clutter: How bumblebees optimize flight behaviour through experience

Bumblebees are excellent navigators that travel long distances while retracing paths to known locations. They forage not only in open terrains but also in cluttered environments where obstacles force them to deviate from direct paths. This study investigates the underexplored aspect of how bees become experienced foragers and optimize flight behaviour in cluttered terrains. We recorded flight trajectories of novice bees inexperienced in navigating cluttered environments and monitored their behavioural performance as they gained experience on subsequent foraging trips through numerous obstacles. By controlling for experience levels, we analysed how flight characteristics evolve with increasing expertise. Successful navigation in cluttered terrains requires avoiding collisions with obstacles. This is only possible if these can be detected by visual features such as the retinal displacement of contrast edges. Obstacles which are harder to detect and to avoid by the bees can affect their flight performance. By introducing transparent objects into our dense environment, we challenged collision avoidance and learning mechanisms, analysing their impact on flight optimization under different environmental conditions. Our findings reveal that experienced bees fly similar paths through clutter and quickly adapt their flight regardless of their training environment. However, the specific paths followed are influenced by environmental conditions. Transparent objects primarily affect naive bees flight patterns while having minimal impact on flight optimization, suggesting that the efficient flights of experienced bees result not solely from reflexive collision avoidance but from learning and previous experience in cluttered environments.

animal behavior and cognition↗

bioRxiv2024

Bumblebees increase their learning flight altitude in dense environments

Bumblebees rely on visual memories acquired during the first outbound flights to relocate their nest. While these learning flights have been extensively studied in sparse environments with few objects, little is known about how bees adapt their flight in more dense, cluttered, settings that better mimic their natural habitats. Here we investigated how environmental complexity influences the first outbound flights of bumblebees. In a large arena we tracked the bees 3D positions to examine the flight patterns, body orientations, and nest fixations across environmental conditions characterised by different object constellations around the nest entrance. In cluttered environments, bees prioritised altitude gain over horizontal distance, suggesting a strategy to overcome obstacles and visual clutter. Body orientation patterns became more diverse in dense environments, indicating a balance between nest-oriented learning and obstacle avoidance. Notably, bees consistently preferred to fixate the location of the nest entrance from elevated positions above the dense environment across all conditions. Our results reveal significant changes in the 3D flight structure, body orientations, and nest fixation behaviours as object density increases. This highlights the importance of considering 3D space and environmental complexity in understanding insect navigation.

animal behavior and cognition↗

bioRxiv2024

Bumblebees locate goals in 3D with absolute height estimation from ventral optic flow

When foraging, flying animals like bees are often required to change their flight altitude from close to the ground to above the height of the vegetation to reach their nest or a food source. While the mechanisms of navigating towards a goal in two dimensions are well investigated, the explicit use of height as a source for navigation in three dimensions remains mostly unknown. Our study aims to unravel which strategies bumble-bees use for height estimation and whether they rely on global or local cues. We expanded a 2D goal localization paradigm, where a goal location is indicated by cylindrical landmarks, to the third dimension by using spherical landmarks to indicate a feeders position in 3D and examined the search pattern of bumblebees. Additionally, we assessed the ability of bees to estimate the height of a feeder based on local landmarks and global references such as the ground floor. The search distribution for a feeders position in 3D was less spatially concentrated compared to in 2D. Assessing the bees height estimation ability, we found that bees could estimate a feeders height using the ground floor as a reference. However, the feeder needed to be sufficiently close to the ground floor for the bees to choose correctly. When bumblebees are faced with the challenge of foraging in a 3D environment where the height of a food source and landmark cues are important, they demonstrate the ability to learn and return to a specific flower height. This suggests they rely on ventral optic flow for goal height estimation in bumblebees.

animal behavior and cognition↗

bioRxiv2023

Switching perspective: Comparing ground-level and bird's-eye views for bees navigating clutter

Animals navigating in three dimensions encounter different perspectives of their world, often transitioning from birds eye views at higher altitudes to ground views closer to the ground. How they integrate this information to pinpoint a goal location is virtually unknown. Here we tested the ability of bumblebees to use both types of views when homing in a dense environment in the vicinity of their inconspicuous nest entrance. Our combined modelling and experimental approach examined various views for localising a goal in dense settings. Whereas, birds-eye views performed best in simulations of current nest-centered snapshot homing models, behavioural experiments revealed that bumblebees predominantly relied on ground views when pinpointing nest entrances in dense environments. These findings reveal the limitations of snapshot-homing models and suggest that bumblebees use a combination of navigational tools to successfully find their way home in dense environments. This is not only relevant for understanding bee navigation, but also for other animals and humans navigating in 3D as well as the development of technologies inspired by natural systems, such as autonomous flying robots.

animal behavior and cognition↗

bioRxiv2023

Not seeing the forest for the trees: Combination of path integration and landmark cues in human virtual navigation

IntroductionIn order to successfully move from place to place, our brain often combines sensory inputs from various sources by dynamically weighting spatial cues according to their reliability and relevance for a given task. Two of the most important cues in navigation are the spatial arrangement of landmarks in the environment, and the continuous path integration of travelled distances and changes in direction. Several studies have shown that Bayesian integration of cues provides a good explanation for navigation in environments dominated by small numbers of easily identifiable landmarks. However, it remains largely unclear how cues are combined in more complex environments. MethodsTo investigate how humans process and combine landmarks and path integration in complex environments, we conducted a series of triangle completion experiments in virtual reality, in which we varied the number of landmarks from an open steppe to a dense forest, thus going beyond the spatially simple environments that have been studied in the past. We analysed spatial behaviour at both the population and individual level with linear regression models and developed a computational model, based on maximum likelihood estimation (MLE), to infer the underlying combination of cues. ResultsOverall homing performance was optimal in an environment containing three landmarks arranged around the goal location. With more than three landmarks, individual differences between participants in the use of cues are striking. For some, the addition of landmarks does not worsen their performance, whereas for others it seems to impair their use of landmark information. DiscussionIt appears that navigation success in complex environments depends on the ability to identify the correct clearing around the goal location, suggesting that some participants may not be able to see the forest for the trees.

neuroscience↗

bioRxiv2021

Random attention can explain apparent object choice behavior in free-walking blowflies

Flies are often observed to approach dark objects. To a naive observer they seem to pay selective attention to one out of several objects although previous research identified a reflex-like fixation behavior integrating responses to all objects as possible underlying mechanism. In a combination of behavioral experiments and computational modelling, we investigate the choice behavior of flies freely walking towards an arrangement of two objects placed at a variable distance from each other. The walking trajectories are oriented towards one of the objects much earlier than predicted by a simple reactive model. We show that object choice can be explained by a continuous control scheme in combination with a mechanism randomly responding to the position of each object according to a stochastic process. Although this may be viewed as a special form of an attention-like mechanism, the model does not require an explicit decision mechanism or a memory for the drawn decision. Summary StatementWalking blowflies apparently choose one of two objects to approach. In model simulations, a fixation scheme combined with random attention replicates this behavior without an explicit decision mechanism.

animal behavior and cognition↗

bioRxiv2018

Gap perception in bumblebees

A number of insects fly over long distances below the natural canopy where the physical environment is highly cluttered consisting of obstacles of varying shape, size and texture. While navigating within such environments animals need to perceive and disambiguate environmental features that might obstruct their flight. The most elemental aspect of aerial navigation through such environments is gap identification and passability evaluation. We used bumblebees to seek insights into the mechanisms used for gap identification when confronted with an obstacle in their flight path and behavioral compensations employed to assess gap properties. Initially, bumblebee foragers were trained to fly though an unobstructed flight tunnel that led to a foraging chamber. After the bees were familiar with this situation, we placed a wall containing a gap that unexpectedly obstructed the flight path on a return trip to the hive. The flight trajectories of the bees as they approached the obstacle wall and traversed the gap were analyzed in order to evaluate their behavior as a function of the distance between the gap and a background wall that was placed behind the gap. Bumblebees initially decelerate when confronted with an unexpected obstacle. Deceleration was first noticed when the obstacle subtended around 35{degrees} on the retina but also depended on the properties of the gap. Subsequently the bees gradually traded off their longitudinal velocity to lateral velocity and approached the gap increasing lateral displacements and lateral velocity. Bumblebees shaped their flight trajectory depending on the salience of the gap, in our case, indicated by the optic flow contrast between the region within the gap and on the obstacle, which increases with decreasing distance between the gap and the background wall. As the optic flow contrast decreased the bees spent increasing time moving laterally across the obstacles. During these repeated lateral maneuvers the bees are likely assessing gap geometry and passability.

animal behavior and cognition↗

bioRxiv2017

Taking a semi-local dynamic snapshot as a possibility for local homing in initially naive bumblebees

For central place foragers, such as bumblebees, it is essential to return reliably to their nest. Instead of just flying away to forage, bumblebees, leaving their inconspicuous nest hole for the first time, need to gather and learn sufficient information about the surroundings to allow them to return to the nest at the end of their trip. Therefore, we assume an intrinsic learning program that manifests itself in the flight structure immediately after leaving the nest for the first time.\n\nIn this study, we recorded and analysed the first outbound flight of individually marked naive bumblebees in an indoor environment. We found characteristic loop-like features in the flight pattern that appear to be necessary for the bees to acquire environmental information and might be relevant for finding the nest hole after a foraging trip.\n\nDespite common features in their spatio-temporal organisation, the first departure flights from the nest are characterised by a high level of variability in their loop-like flight structure across animals. Changes in turn direction of body orientation, for example, are distributed evenly across the entire area used for the flights without any systematic relation to the nest location. By considering the common flight motifs as well as this variability, we came to the hypothesis, that a kind of dynamic snapshot is taken during the early phase of departure flights in the close vicinity of the nest location. The quality of this snapshot is hypothesised to be tested during the later phases of the departure flights concerning its usefulness for local homing.

animal behavior and cognition↗