ReviewCognitive, affective & behavioral neuroscience2019
Revisiting foraging approaches in neuroscience.
Review in Cognitive, affective & behavioral neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Acetylcholine and noradrenaline enhance foraging optimality in humans.Proceedings of the National Academy of Sciences of the United States of America · 2023Trial
- Article
- Computational Urban Ecology of New York City Rats.bioRxiv : the preprint server for biology · 2025Article
- Increasing Response Vigour Under Time Pressure as a Transdiagnostic Marker of Eating Disorders.Computational psychiatry (Cambridge, Mass.) · 2025Review
- Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments.Advances in neural information processing systems · 2025Article
- Linking cognitive strategy, neural mechanism, and movement statistics in group foraging behaviors.Scientific reports · 2024Article
- Learning and organization of within-session sequences by pigeons (Columba livia).Animal cognition · 2023Article
- Dissecting the neurocomputational bases of patch-switching.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Synthetic Spatial Foraging With Active Inference in a Geocaching Task.Frontiers in neuroscience · 2022Article
- Choice history effects in mice and humans improve reward harvesting efficiency.PLoS computational biology · 2021Article
- Control over patch encounters changes foraging behavior.iScience · 2021Article
- Uncertainty drives deviations in normative foraging decision strategies.Journal of the Royal Society, Interface · 2021Article
- Systems Neuroscience of Natural Behaviors in Rodents.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Review
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Authors and funding
2 authors.
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Abstract
Many complex real-world decisions, such as deciding which house to buy or whether to switch jobs, involve trying to maximize reward across a sequence of choices. Optimal Foraging Theory is well suited to study these kinds of choices because it provides formal models for reward-maximization in sequential situations. In this article, we review recent insights from foraging neuroscience, behavioral ecology, and computational modelling. We find that a commonly used approach in foraging neuroscience, in which choice items are encountered at random, does not reflect the way animals direct their foraging efforts in certain real-world settings, nor does it reflect efficient reward-maximizing behavior. Based on this, we propose that task designs allowing subjects to encounter choice items strategically will further improve the ecological validity of foraging approaches used in neuroscience, as well as give rise to new behavioral and neural predictions that deepen our understanding of sequential, value-based choice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.