Effect of a context shift on the inverse base rate effect

Abstract

The Inverse Base Rate Effect (IBRE; Medin and Edelson (1988)) is a non-rational behavioural phenomenon in predictive learning. In the IBRE, participants learn that a stimulus compound AB leads to one outcome and that another compound AC leads to a different outcome. Importantly, AB and its outcome are presented three times as often as AC (and its outcome). On test, when asked which outcome to expect on presentation of the novel compound BC, participants preferentially select the rarer outcome, previously associated with AC. This is irrational because, objectively, the common outcome is more likely. Usually, the IBRE is attributed to greater attention paid to cue C than to cue B, and so is an excellent test for attentional learning models. The current experiment tested a simple model of attentional learning proposed by Le Pelley, Mitchell, Beesley, George, and Wills (2016) where attention paid to a stimulus is determined by its associative strength. This model struggles to capture the IBRE, but a potential solution suggested by the authors appeals to the role of experimental context. In the present paper, we derive three predictions from their account concerning the effect of changing to a novel experimental context at test, and examine these predictions empirically. Only one of the predictions was supported, concerning the effect of a context shift on responding to a novel cue, was supported. In contrast, Kruschke (2001b)'s EXIT model, in which attention and associative strength can vary independently, captured the data with a high degree of quantitative accuracy.

Hearing hooves, thinking zebras: A review of the inverse base-rate effect

“…Juslin et al (2001) found a rare outcome bias for novel cues, and Johansen, Fouquet, and Shanks (2007) found a similar result in a text-based version of the task. However, Inkster et al (2019b) found a common bias on novel cue trials, and, as noted, Don and Livesey (2017) found a bias for the common outcomes on AX trials that contained the imperfect predictor plus a novel cue, which should also elicit a process of elimination. In this case, responding to novel cues may be based on the associations of other cues present (e.g., context, imperfect predictors).…”

“…These conditions were not sufficient to produce an inverse base-rate effect on BC trials. In addition, Inkster et al (2019b) found that changing the context in the test phase had no effect on the strength of the inverse base-rate effect or B>C effect. The failure to find any effect of a context shift on test performance is not consistent with the notion that context associations are heavily involved in the inverse baserate effect.…”

“…In the highlighting effect, BC trials elicit a preference for the late outcome, O2. While research on the inverse base-rate effect was most prominent between the late-1980s and early-2000s, it has recently received renewed interest (e.g., Don & Livesey, 2017;Don, Beesley, & Livesey, 2019a;Inkster, Milton, Edmunds, Benattayallah, & Wills, 2019a;Inkster, Mitchell, Schlegelmilch, & Wills, 2019b;Le Pelley et al, 2016;O'Bryan, Worthy, Livesey, & Davis, 2018;Wills et al, 2014). Specifically, for reasons that are discussed below, the inverse base-rate effect has been highlighted as an important phenomenon because it may discriminate between different attentionbased models of learning.…”

“…The authors state that this model can account for most effects of attention in human learning, with the exception of the inverse base-rate effect. The primary issue for this model is the finding that often, the inverse baserate effect occurs when common responses for B alone are greater than rare responses for C alone at test (e.g., Inkster et al, 2019b;Wills et al, 2014). We refer to this difference as the B>C effect.…”