Statistical learning in the past modulates contextual cueing in the future.

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.