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FoMo: A unifying theory of visual foraging.
Alasdair D F Clarke1, Anna E Hughes1
1Department of Psychology, University of Essex, Colchester, United Kingdom.
Plos Computational Biology
|May 12, 2026
Summary
We updated FoMo, a model for analyzing visual foraging data, to include spatial structure. This enhanced model improves predictions by capturing organized spatial behaviors and individual differences in decision-making.
Area of Science:
- Cognitive Science
- Computational Neuroscience
- Behavioral Ecology
Background:
- Visual foraging generates complex sequential decision data, posing analytical challenges.
- Existing models may not fully capture spatial components of foraging behavior.
- Understanding decision-making in foraging requires robust analytical tools.
Purpose of the Study:
- To present an updated version of the Foraging Model (FoMo) incorporating spatial structure.
- To improve the prediction accuracy of selection behavior in visual foraging tasks.
- To provide a unified framework for analyzing individual differences in foraging strategies.
Main Methods:
- Developed a generative model (FoMo) for spatial-sequential data.
- Incorporated spatial structure parameters into the FoMo model.
- Utilized Bayesian statistical methods for parameter estimation.
Main Results:
- The updated FoMo model demonstrates improved prediction accuracy for visual foraging datasets.
- Incorporating spatial structure enhanced model performance, particularly for participants using grid-following strategies.
- The model successfully accounts for individual differences in behavior.
Conclusions:
- The spatially-enhanced FoMo model offers a robust framework for analyzing visual foraging behavior.
- This approach facilitates a deeper understanding of the causes behind behavioral variations in decision-making.
- FoMo provides a unified method for analyzing diverse foraging data across species.
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