Visual place learning by walking bumblebees in virtual reality

Central-place foragers, such as bumblebees, must navigate complex and ever-changing environments to locate food sources and return to their nests. Visual cues in the vicinity of the target play a crucial role in this process, particularly in distinguishing between otherwise visually similar but nutritionally distinct targets. In this study, we used a virtual reality (VR) trackball system and a free-walk paradigm to investigate how bumblebees utilize visual information for place-learning. We specifically examined how bees resolve conflicts between previously learned and currently available visual cues surrounding a target, how the perceived valence of a target changes through association with rewards or punishments, and how they distinguish between visually identical targets based on differences in surrounding visual features. We found that bumblebees prioritize spatial proximity, probably using motion parallax information over static image matching strategies. Furthermore, bees demonstrated flexibility in associating visual features with rewards or punishments by adapting to reversed valence pairings. However, potential intrinsic preferences for specific colours and patterns influenced learning success. These findings challenge traditional snapshot navigation models and suggest that walking bumblebees employ flexible strategies for solving spatial learning tasks in virtual and real environments.

Authors

Institutions

Publication Details

Journal
Journal of Experimental Biology
Published
2025-08-08
DOI
https://doi.org/10.1242/jeb.250485
Citations
3
Primary Topic
Plant and animal studies
Type
article
Field-Weighted Citation Impact
9.08

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Visual place learning by walking bumblebees in virtual reality

Jens Peter Lindemann, Martin Egelhaaf, Sonja Eckel
3 citations
Journal of Experimental Biology
Plant and animal studies
9.08
article

Visual place learning by walking bumblebees in virtual reality

Jens Peter Lindemann, Martin Egelhaaf, Sonja Eckel
article en
3 citations

Abstract

Central-place foragers, such as bumblebees, must navigate complex and ever-changing environments to locate food sources and return to their nests. Visual cues in the vicinity of the target play a crucial role in this process, particularly in distinguishing between otherwise visually similar but nutritionally distinct targets. In this study, we used a virtual reality (VR) trackball system and a free-walk paradigm to investigate how bumblebees utilize visual information for place-learning. We specifically examined how bees resolve conflicts between previously learned and currently available visual cues surrounding a target, how the perceived valence of a target changes through association with rewards or punishments, and how they distinguish between visually identical targets based on differences in surrounding visual features. We found that bumblebees prioritize spatial proximity, probably using motion parallax information over static image matching strategies. Furthermore, bees demonstrated flexibility in associating visual features with rewards or punishments by adapting to reversed valence pairings. However, potential intrinsic preferences for specific colours and patterns influenced learning success. These findings challenge traditional snapshot navigation models and suggest that walking bumblebees employ flexible strategies for solving spatial learning tasks in virtual and real environments.

Journal of Experimental BiologyVol. 228(18)
Bielefeld University (DE), Hochschule Bielefeld (DE), Klinikum Bielefeld (DE)
Deutsche Forschungsgemeinschaft
Zero hunger
Openalex Percentile: Top 2%
Plant and animal studies
9.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.