Configural learning in contextual cuing of visual search

The effect of gaze information associated with the search items on contextual cueing effect

Previous research on the mechanisms of contextual cueing effect has been inconsistent, with some researchers showing that the contextual benefit was derived from the attentional guidance whereas others argued that the former theory was not the source of contextual cueing effect. We brought the "stare-in-the-crowd" effect that used pictures of gaze with different orientations as stimuli into a traditional contextual cueing effect paradigm to investigate whether attentional guidance plays a part in this effect. We embedded the letters used in a traditional contextual cueing effect paradigm into the gaze pictures with direct and averted orientation. In Experiment 1, we found that there was a weak interaction between the contextual cueing effect and the "stare-in-the-crowd" effect. In Experiments 2 and 3, we found that the contextual cueing effect was influenced differently when the direct gaze was combined with the target or distractors. These results suggested that attentional guidance played an important role in the generation of a contextual cueing effect and the direct gaze had a special impact on visual search. To summarize the three findings, the direct gaze on target location facilitates the contextual cueing effect, and such an effect is even greater when we compared condition with the direct gaze on target location with condition with the direct gaze on distractor location (Experiments 2 and 3). Such an effect of gaze on a contextual cueing effect is manifested even when the effect of gaze ("stare-in-the-crowd" effect) was absent in the New configurations (search trials without learning).

No exploitation of temporal sequence context during visual search

The human visual system can rapidly extract regularities from our visual environment, generating predictive context. It has been shown that spatial predictive context can be used during visual search. We set out to see whether observers can additionally exploit temporal predictive context based on sequence order, using an extended version of a contextual cueing paradigm. Though we replicated the contextual cueing effect, repeating search scenes in a structured order versus a random order yielded no additional behavioural benefit. This was also true when we looked specifically at participants who revealed a sensitivity to spatial predictive context. We argue that spatial predictive context during visual search is more readily learned and subsequently exploited than temporal predictive context, potentially rendering the latter redundant. In conclusion, unlike spatial context, temporal context is not automatically extracted and used during visual search.

Response time modeling reveals multiple contextual cuing mechanisms

Contextual cuing refers to a response time (RT) benefit that occurs when observers search through displays that have been repeated over the course of an experiment. Although it is generally agreed that contextual cuing arises via an associative learning mechanism, there is uncertainty about the type(s) of process(es) that allow learning to influence RT. We contrast two leading accounts of the contextual cuing effect that differ in terms of the general process that is credited with producing the effect. The first, the expedited search account, attributes the cuing effect to an increase in the speed with which the target is acquired. The second, the decision threshold account, attributes the cuing effect to a reduction in the response threshold used by observers when making a subsequent decision about the target (e.g., judging its orientation). We use the diffusion model to contrast the quantitative predictions of these two accounts at the level of individual observers. Our use of the diffusion model allows us to also explore a novel decision-level locus of the cuing effect based on perceptual learning. This novel account attributes the RT benefit to a perceptual learning process that increases the quality of information used to drive the decision process. Our results reveal both individual differences in the process(es) involved in contextual cuing but also identify several striking regularities across observers. We find strong support for both the decision threshold account as well as the novel perceptual learning account. We find relatively weak support for the expedited search account.