Foraging for foundations in decision neuroscience: insights from ethology

Abstract

Modern decision neuroscience offers a powerful and broad account of human behaviour using computational techniques that link psychological and neuroscientific approaches to the ways that individuals can generate near-optimal choices in complex controlled environments. However, until recently, relatively little attention has been paid to the extent to which the structure of experimental environments relates to natural scenarios, and the survival problems that individuals have evolved to solve. This situation not only risks leaving decision-theoretic accounts ungrounded but also makes various aspects of the solutions, such as hard-wired or Pavlovian policies, difficult to interpret in the natural world. Here, we suggest importing concepts, paradigms and approaches from the fields of ethology and behavioural ecology, which concentrate on the contextual and functional correlates of decisions made about foraging and escape and address these lacunae.

Fig. 1 |. Example of classic apple-picking task.

Subjects forage in an unlimited orchard and have to decide whether to continue picking from their current tree or to switch to another one to maximize their harvest. Switching is associated with a time penalty; however, if the subject decides to stay and pick apples from the tree, the rate of return will decrease. Thus, at some point, the subject should switch to a new tree. To maximize the long-term harvest rate of apples, the subject repeatedly decides between choosing to stay at a tree and switching to a new one.

Fig. 2 |. Example of foraging and escape choice, and the cost-of-fleeing and cost-of-staying curves.

a | The solitary prey (for example, a zebra) must make a decision about whether to flee to safety when a predator is approaching (for example, a lion). The flight initiation distance (FID) is the measurable distance at which the prey makes the decision to flee from an approaching threat. The FID is influenced by several factors, including the degree of threat posed by the predator (for example, whether it is a fast-moving or slow-moving predator) and the value of its current location (for example, there is an abundance of food or mates). b | The schematic represents the cost of fleeing versus remaining and is based on the model proposed by Ydenberg and Dill. As the distance between the prey and the predator decreases, the cost of fleeing decreases (red line), whereas the cost of not fleeing increases (blue line). d* represents the optimal distance between the prey and the predator at which the prey should flee. c | In situations in which there are multiple benefits of remaining at a particular patch but a single cost of fleeing, d* is longer for the higher of the two cost-of-not-fleeing curves. d | Conversely, d* is longer for the lower of the two cost-of-fleeing curves when there is a single cost-of-not-fleeing curve. d*_CH, high cost; d*_CL, low cost; d*_NH, not fleeing, high cost; d*_NL, not fleeing, low cost. Adapted with permission from REF.,Cambridge University Press.