DOI: 10.5061/dryad.r2280gbhs
title: The optimal time to approach an unfamiliar object: A Bayesian model

description: Many organisms take time before approaching unfamiliar objects. This
 caution forms the basis of some well-known assays in the fields of
 behavioral ecology, comparative psychology and animal welfare, including
 quantifying the personality traits of individuals and evaluating the
 extent of their neophobia. In this paper we present a mathematical model
 which identifies the optimal time an observer should wait before
 approaching an unfamiliar object. The model is Bayesian, and simply
 assumes that the longer the observer goes without being attacked by an
 unfamiliar object, the lower will be the observer’s estimated probability
 that the object is dangerous. Given the information gained, a time is
 reached at which the expected benefits from approaching the object begin
 to exceed the costs. The model not only explains why latency to approach
 may be repeatable among individuals and vary with the object’s appearance,
 but also why individuals habituate to the stimulus, approaching it more
 rapidly over repeated trials. We demonstrate the applicability of our
 model by fitting it to published data on the time taken by chicks to
 attack artificial caterpillars which share no, one, or two signaling
 traits with snakes (eyespots and posture). We use this example to show
 that while the optimal time to attack an unfamiliar object reflects the
 observer’s expectation that the object is dangerous, the rate at which
 habituation arises is also a function of the observer’s certainty in their
 belief. In so doing, we explain why observers become more rapidly
 habituated to “weaker” stimuli than “stronger” ones. 
description: The data presented here were originally collected and interpreted
 by Skelhorn et al. (2016). Multicomponent deceptive signals reduce the
 speed at which predators learn that prey are profitable. Behavioral
 Ecology, <strong>27</strong>(1), 141–147.
 doi:10.1093/beheco/arv135.  Here we use these data to demonstrate the
 applicability of our Bayesian model, and in so doing we help explain why
 observers become more rapidly habituated to “weaker” stimuli than
 “stronger” ones.  In short, Skelhorn et al. (2016)
 presented naive domestic chicks with palatable pastry models of
 snake-mimicking caterpillars that varied in their resemblance to snakes.
 These models either had eyespots or not and were set in a resting or
 defensive posture in a 2 x 2 factorial design. All chicks were presented
 with just one caterpillar type and there were 9 chicks per treatment
 combination. Presentations of the caterpillars to the chicks were
 conducted over 4 consecutive trials which were completed in 2 days. The
 primary endpoints was the time (in seconds) taken for a given chick to
 attack the pastry bait.  The data provided lists the
 <strong>treatment</strong> (1 = resting posture, no eyespot; 
 2 = resting posture, eyespots; 3 defensive posture, no eyespot; 4 =
 defensive posture, eyespot), the <strong>trial</strong> (1-4),
 the <strong>latency</strong> of the chick to attack (in
 seconds) and the <strong>individual</strong> chick
 ID.
description: The R code used to analyze and plot the data are presented in the
 Supplementary Materials of Sherratt et al. (2023) The optimal time to
 approach an unfamiliar object: A Bayesian model. Behavioral
 Ecology.