Psychological Science · 2013 · 285 citations · 40 references
MedicineBehavioral SciencesPsychologyCognitive PsychologyVisual AttentionVisual PerceptionAttentional CaptureAttentional SelectionSelective AttentionSpatial AttentionSpatial CognitionVisual SearchAttentionAttention AllocationAttention BiasesAttentional LearningAttentional Priority MapsSalienceStatistical Learning TheoryTask-irrelevant Distractors
Regularities in the environment aid perception, memory, and language, yet their prioritization in attention is not explained by stimulus‑driven or goal‑directed models and may foster further statistical learning. The study tests whether statistically structured information gains attentional priority over noisier sources regardless of salience or relevance. Across three experiments, regularities bias both spatial and feature attention, with spatial search facilitated by temporal regularities and feature capture doubling when singletons appeared in temporally regular colors or dimensions.
Knowledge about regularities in the environment can be used to facilitate perception, memory, and language acquisition. Given this usefulness, we hypothesized that statistically structured sources of information receive attentional priority over noisier sources, independent of their intrinsic salience or goal relevance. We report three experiments that support this hypothesis. Experiment 1 shows that regularities bias spatial attention: Visual search was facilitated at a location containing temporal regularities, even though these regularities did not predict target location, timing, or identity. Experiments 2 and 3 show that regularities bias feature attention: Attentional capture doubled in magnitude when singletons appeared, respectively, in a color or dimension with temporal regularities among task-irrelevant stimuli. Prioritization of the locations and features of regularities is not easily accounted for in the conventional dichotomy between stimulus-driven and goal-directed attention. This prioritization may in turn promote further statistical learning, helping the mind to acquire knowledge about stable aspects of the environment.
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