Revisiting foraging approaches in neuroscience

Many complex real-world decisions, such as deciding which house to buy or whether to switch jobs, involve trying to maximise 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-maximisation in sequential situations. In this article, we review recent insights from foraging neuroscience, behavioural 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 real-world settings, nor does it reflect efficient reward-maximising behaviour. 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 behavioural and neural predictions that deepen our understanding of sequential, value-based choice.