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Published on: July 21, 2023
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Optimal multiguidance integration in insect navigation.
Thierry Hoinville1,2, Rüdiger Wehner3
1Biological Cybernetics Department, Bielefeld University, 33615 Bielefeld, Germany; thierry.hoinville@uni-bielefeld.de.
Summary
Desert ants use path integration and landmark guidance for navigation. A new decentralized model shows these routines optimally combine information, maximizing navigational certainty without a central cognitive map.
Area of Science:
- Animal Behavior
- Neuroethology
- Insect Navigation
Background:
- Desert ants are model organisms for studying insect navigation.
- Navigation relies on path integration (celestial compass) and landmark guidance (panoramic views).
- Previous theories proposed a centralized cognitive map for foraging terrain.
Purpose of the Study:
- To present a decentralized architecture for insect navigation.
- To demonstrate how path integration and landmark guidance optimally combine information.
- To challenge the necessity of a centralized cognitive map in insect navigation.
Main Methods:
- Development of a decentralized model architecture.
- Computation of path integration (global) and landmark guidance (local) vectors.
- Vector summation to determine the optimal directional estimate based on certainty.
Main Results:
- The decentralized model architecture successfully simulates diverse cue-conflict experiments.
- Results align with studies on desert ants and honeybees.
- The model explains experimental outcomes previously used to support a metric cognitive map.
Conclusions:
- Insect navigation can be explained by a decentralized system combining path integration and landmark guidance.
- Optimal navigation is achieved by maximizing the certainty of combined navigational information.
- A centralized cognitive map is not required for complex navigational behaviors in insects.
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