Visual search is facilitated when targets are repeatedly encountered at a fixed position relative to an invariant distractor layout, compared to random distractor arrangements. However, standard investigations of this contextual-facilitation effect employ fixed distractor layouts that predict a constant target location, which does not always reflect real-world situations where the target location may vary relative to an invariant distractor arrangement. To explore the mechanisms involved in contextual learning, we employed a training-test procedure, introducing not only the standard full-repeated displays with fixed target-distractor locations but also distractor-repeated displays in which the distractor arrangement remained unchanged but the target locations varied. During the training phase, participants encountered three types of display: full-repeated, distractor-repeated, and random arrangements. The results revealed full-repeated displays to engender larger performance gains than distractor-repeated displays, relative to the random-display baseline. In the test phase, the gains were substantially reduced when full-repeated displays changed into distractor-repeated displays, while the transition from distractor-repeated to full-repeated displays failed to yield additional gains. We take this pattern to indicate that contextual learning can improve performance with both predictive and non-predictive (repeated) contexts, employing distinct mechanisms: contextual guidance and context suppression, respectively. We consider how these mechanisms might be implemented (neuro-)computationally.
Keywords: Context suppression; Context-based guidance; Contextual cueing; Visual search.
© 2024. The Author(s).