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Andrew B. Leber, Jun-ichiro Kawahara; Abstract learning of attentional set. Journal of Vision 2008;8(6):874. doi: 10.1167/8.6.874.
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© ARVO (1962-2015); The Authors (2016-present)
Does past experience shape the strategies we use to select visual information? Recent studies have made such a claim, based on results from the “option trial” procedure (Leber & Egeth, 2006), in which observers can choose from multiple strategies to search for a consistently-colored target (e.g., red) in a temporal stream of all-gray nontargets. That is, they can search narrowly for the specific target feature while ignoring non-matching stimuli (because the target feature is always known), or they can search more broadly for any oddball (because the target is always a feature singleton). The strategy used by observers on such trials has been shown to be largely determined by previous strategy use. For instance, when observers are required to search specifically for red in a 30-minute training phase preceding the option trials, they tend to continue searching specifically for red on the option trials. In the current work, we questioned whether such results constitute the transfer of the abstract search strategy, as previously argued, or if they instead reflect a lower-level phenomenon of “feature-specific learning.” By this latter account, observers gain considerable experience searching through the particular set of features presented during training, which biases them to continue using the initial strategy simply because of low-level perceptual improvements. For example, rather than learning to search for the consistent target feature, whatever it may be, observers may have merely improved their sensitivity to searching specifically for red. To remove any potential contribution of feature-specific learning, we replaced the entire set of stimulus colors from the training phase to the test phase of option trials. Here, the past experience effect still obtained, supporting the notion that observers do indeed bring their previous experiences with “abstract” search strategies into their task challenges of the present.
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