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First published online March 12, 2009
Journal of Experimental Biology 212, 901-905 (2009)
Published by The Company of Biologists 2009
doi: 10.1242/jeb.024539

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Local and global navigational coordinate systems in desert ants

Matthew Collett^1,* and Thomas S. Collett²

¹ Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK
² School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, UK

^* Author for correspondence (e-mail: matthew.collett{at}zoo.ox.ac.uk)

Accepted 16 December 2008

While foraging, the desert ant Cataglyphis fortis keeps track of its position with respect to its nest through a process of path integration (PI). Once it finds food, it can then follow a direct home vector to its nest. Furthermore, it remembers the coordinates of a food site, and uses these coordinates to return to the site. Previous studies suggest, however, that it does not associate any coordinates remembered from previous trips with familiar views such that it can produce a home vector when displaced to a familiar site. We ask here whether a desert ant uses any association between PI coordinates and familiar views to ensure consistent PI coordinates as it travels along a habitual route. We describe an experiment in which we manipulated the PI coordinates an ant has when reaching a distinctive point along a habitual route on the way to a feeder. The subsequent home vectors of the manipulated ants, when displaced from the food-site to a test ground, show that also when a route memory is evoked at a significant point on the way to a food site, C. fortis does not reset its PI coordinates to those it normally has at that point. We use this result to argue that local vector memories, which encode the metric properties of a segment of a habitual route, must be encoded in a route-based coordinate system that is separate from the nest-based global coordinates. We propose a model for PI-based guidance that can account for several puzzling observations, and that naturally produces the route-based coordinate system required for learning and following local vectors.

Key words: insect cognition, navigation, spatial learning, inverse model

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