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Configural learning in contextual cuing of visual search

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Abstract

Two experiments explore the role of configural representations in contextual cuing of visual search. Repeating patterns of distractors (contexts) were trained incidentally as predictive of the target location. Training these repeating contexts in consistent configurations led to stronger contextual cuing than when contexts were trained in inconsistent configurations. Computational simulations with an elemental associative learning model of contextual cuing demonstrated that purely elemental representations could not account for the results. However, a configural model of associative learning was able to simulate the ordinal pattern of data.

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... For example, Beesley, Vadillo, Pearson, and Shanks (2015) found that preexposure of distractor configurations in an incidental learning task enhanced contextual cuing during a subsequent learning phase. This preexposure benefit could not be accounted for by a model that only learned target-distractor associations (i.e., Brady & Chun, 2007) but could successfully be explained by a model that also learned distractor configurations (Beesley, Vadillo, Pearson, & Shanks, 2016). In addition to learning distractor-distractor relationships, there is evidence that nonconfigural Bbackground^cues, such as colors, textures, or natural scenes, can support contextual cuing (e.g., Brockmole, Castelhano, & Henderson, 2006;Kunar, Flusberg, & Wolfe, 2006). ...
... The reduction in the number of fixations for repeated displays has been replicated repeatedly (e.g., Beesley, Hanafi, Vadillo, Shanks, & Livesey, 2017;Manginelli & Pollmann, 2009;Tseng & Li, 2004;Zhao et al., 2012), and is broadly consistent with data that has found cuing effects on search slopes. The idea that people are able to search through repeated displays faster has been incorporated into computational models of the cuing effect, which assume that search time is a function of the predicted number of locations searched by the model (Beesley et al., 2015(Beesley et al., , 2016Brady & Chun, 2007). ...
... We refer to this novel alternative as the perceptual learning account. According to this idea, people learn about the composition of the repeated displays (e.g., Beesley et al., 2015Beesley et al., , 2016Brady & Chun, 2007) and use this information to facilitate decision-making about the orientation of the target stimulus. We conjecture that, for repeated displays, the information people use to judge the orientation of the target might be influenced by (learnable) factors other than the perceptual properties of the target stimulus itself. ...
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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.
... Visual search scenes are more complex, representing multiple target-distractor relations. Even though recent work shows there is also a component of scene memory to contextual cueing [32,33], this might not be strong enough to enable one 'scene' to function as a predictor of the next, analogous to how an object predicts the next one in typical temporal statistical learning tasks. A previous study exposed observers to sequenced information in addition to, but independent of, spatial predictive context. ...
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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.
... Reaction time (RT) was our primary, and accuracy our secondary variable of interest. Statistical assessment of the RT data was done for the second half of the experiment, i.e. blocks [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] (selected a priori). Only RT data from correct trials was used. ...
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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, 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 true both for participants who were sensitive to spatial predictive context, and for those who were not. 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.
... Pre-exposure to repeated displays with unpredictive target locations facilitates contextual cueing at a later stage when the preexposed distractor-distractor configurations predict the target location (Beesley, Vadillo, Pearson, & Shanks, 2015). Moreover, inconsistent displays composed of recombined sub-patterns of distractors that were associated with target positions lead to a weakened contextual cueing effect suggesting that configural presentations contribute to contextual cueing (Beesley, Vadillo, Pearson, & Shanks, 2016). For both of these studies, computational simulations with a configural model of associative learning accounted better for the results than a model, which only considered elementary representations. ...
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Learned spatial regularities can efficiently guide visual search. This effect has been extensively studied using the contextual cueing paradigm. We investigated age-related changes in the initial learning of contextual configurations and the relearning after target relocation. Younger and older participants completed a contextual cueing experiment on two days. On day one, they were tested with a standard contextual cueing task. On day two, for the repeated displays the location of the targets was moved while keeping the distractor configurations unchanged. Older participants developed a reliable contextual cueing effect but the emergence of this effect required more repetitions compared to younger individuals. Contextual cueing was apparent quickly after target relocation in younger and older participants. Especially in older adults, the fast updating might be due to learned distractor-distractor associations rather than the updating of target-distractor configurations.
... It would seem therefore that the Selective attention in contextual cuing Beesley,Hanafi,Vadillo,Shanks,& Livesey 34 benefit of segregating the predictive and nonpredictive information occurs during the initial encoding of the configuration, rather than the recall of that information from memory. While further experimental evidence will be needed to support these conclusions, these findings may well have important implications for the manner in which surface feature information is realized in formal models of contextual cuing (e.g., Brady & Chun, 2007;Beesley et al., , 2016. ...
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