Vector-based navigation in desert ants: the significance of path-integration vectors

In the longstanding discussion of whether insects, especially central place foragers such as bees and ants, use metric representations of their landmark surroundings (so-called "cognitive maps"), the ability to find novel shortcuts between familiar locations has been considered one of the most decisive proofs for the use of such maps. Here we show by channel-based field experiments that desert ants Cataglyphis can travel such shortcuts between locations (defined by memorized goal vectors) just on the basis of path integration. When trained to visit two spatially separated feeders A and B they later travel the hitherto novel route A→B. This behavior may originate from the interaction of goal vectors retrieved from long-term memory and the current vector computed by the continuously running path integrator. Based on former experiments, we further argue that path integration is a necessary requirement also for acquiring landmark information (in form of learned goal-directed views). This emphasizes the paramount importance of path integration in these central place foragers. Finally we hypothesize that the ant's overall system of navigation consists in the optimal combination of path-integration vectors and view-based vectors, and thus handles and uses vectorial information without the need of constructing a "vector map", in which vectors are linked to known places in the environment others than to the origin of all journeys, the nest.

Authors

Institutions

Publication Details

Journal
Journal of Comparative Physiology A
Published
2024-12-03
DOI
https://doi.org/10.1007/s00359-024-01725-2
Primary Topic
Insect and Arachnid Ecology and Behavior
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Vector-based navigation in desert ants: the significance of path-integration vectors

Markus Knaden, Rüdiger Wehner, Stefan Sommer, Beatrice Voegeli
Journal of Comparative Physiology A
Insect and Arachnid Ecology and Behavior
article

Vector-based navigation in desert ants: the significance of path-integration vectors

Markus Knaden, Rüdiger Wehner, Stefan Sommer, Beatrice Voegeli
article en

Abstract

In the longstanding discussion of whether insects, especially central place foragers such as bees and ants, use metric representations of their landmark surroundings (so-called "cognitive maps"), the ability to find novel shortcuts between familiar locations has been considered one of the most decisive proofs for the use of such maps. Here we show by channel-based field experiments that desert ants Cataglyphis can travel such shortcuts between locations (defined by memorized goal vectors) just on the basis of path integration. When trained to visit two spatially separated feeders A and B they later travel the hitherto novel route A→B. This behavior may originate from the interaction of goal vectors retrieved from long-term memory and the current vector computed by the continuously running path integrator. Based on former experiments, we further argue that path integration is a necessary requirement also for acquiring landmark information (in form of learned goal-directed views). This emphasizes the paramount importance of path integration in these central place foragers. Finally we hypothesize that the ant's overall system of navigation consists in the optimal combination of path-integration vectors and view-based vectors, and thus handles and uses vectorial information without the need of constructing a "vector map", in which vectors are linked to known places in the environment others than to the origin of all journeys, the nest.

Journal of Comparative Physiology AVol. 211(2)
University of Zurich (CH), Max Planck Institute for Chemical Ecology (DE)
National Science Foundation, Volkswagen Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Universität Zürich
Life below water
Openalex Percentile: Top 76%
Insect and Arachnid Ecology and Behavior
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.