Statistical learning in the past modulates contextual cueing in the future

Abstract

Observers' capability to extract statistical regularities from the visual world can facilitate attentional orienting. For instance, visual search benefits from the repetition of target locations by means of probability learning. Furthermore, repeated (old) contexts of nontargets contribute to faster visual search in comparison to random (new) arrangements of nontargets. Chun and Jiang (1998) called this effect "contextual cueing" because old contexts provide spatial cues to repeated target locations. In the present study, we investigated how probability learning modulates the adaptation of contextual cueing to a change in target location. After an initial learning phase, targets were relocated within their respective contexts to new positions that were, however, familiar from previous presentations in other spatial contexts. Contextual cueing was observed for relocated targets that originated from old contexts, but it turned into costs when relocated targets had previously been presented in new contexts. Thus, probability learning was not sufficient to observe adaptive contextual cueing for relocated targets. Instead, the contextual past of target locations--whether they had been cued or not--modulated the integration of relocated targets into a learned context. These findings imply that observers extract multiple levels of available statistical information and use them to infer hypotheses about future occurrences of familiar stimuli.

Why are the batteries in the microwave?: Use of semantic information under uncertainty in a search task

“…In our study, some learning occurred in the semantically incongruent condition. This is similar to the effect Zellin et al (2013) found in a contextual cueing task, in which subjects maintained different sets of predictions for target locations depending on the surrounding context.…”

“…Learning has been reported in search tasks using abstract displays, where the statistics of target locations in relation to a surrounding context are learned quickly, and are retained in long-term memory (Chun & Jiang, 1998;Chun, 2000;Chun & Jiang, 2003). Learning the relationship between a target and the surrounding context depends on the predictability of the relationship Zellin et al, 2013). In our study, some learning occurred in the semantically incongruent condition.…”

Distributed attention beats the down-side of statistical context learning in visual search

“…The sample size was determined on the basis of previous comparable studies (e.g., Assumpção, Shi, Zang, Müller, & Geyer, 2015 ; Geringswald, Herbik, Hofmüller, Hoffmann, & Pollmann, 2015 ; Geyer et al, 2010 ; Zellin et al, 2011 ; Zellin et al, 2013a ; Zellin von Mühlenen, Müller, & Conci, 2013b ; Zellin von Mühlenen, Müller, & Conci, 2014 ; Zinchenko et al, 2018 ), which typically tested around 14 (or fewer) participants. Sample size estimation was informed by previous contextual-cueing studies using a training-phase/test-phase design (e.g., Assumpção et al, 2015 ; Geringswald et al, 2015 ; Zellin, von Mühlenen, et al, 2013b ; Zellin et al, 2014 ; Zinchenko et al, 2019 ). On the basis of the number of participants tested in and statistical measures provided by these studies, a sample size of 12 to 14 participants suffices to detect a lack-of-adaptation effect with a power of 0.8 in a single experiment.…”

Threat captures attention but does not affect learning of contextual regularities

“…The original study of this paradigm (Chun & Jiang, 1998) preselected target locations for random contexts. Thus, participants could have learned repeated target locations (Zellin, von Mühlenen, Müller, & Conci, 2013) and attended selectively to a subset of possible target locations when the context is unfamiliar to them. The present design excluded this form of learning with random contexts.…”