Attention is biased in favor of stimuli that signal either threat or reward; this experience-dependent attentional bias develops via associative learning and persists into extinction. Physically salient yet task-irrelevant stimuli are also prioritized by the attention system, but the attentional priority of a physically salient distractor can be suppressed when it appears in a location in which it has been frequently encountered in the past. Similar effects of statistical learning on distractor suppression have been observed for distractors appearing in a predictable color. A pair of recent studies demonstrate that statistically learned distractor suppression and valence-based attentional biases combine additively, suggesting independent influences of learning on attentional priority. One limitation of these prior studies, however, is that the effects of statistical learning were defined with respect to spatial attention and the effects of associative learning with respect to feature-based attention. A strong version of the independence account would predict additive influences on attention even when both sources of priority are represented within a single domain of attentional control, which we tested in the present study. The attentional priority of a distractor was elevated when its color was previously associated with electric shock and reduced when its shape was frequently encountered as a distractor in a prior training phase, with these two influences on priority combining additively. Our findings provide strong evidence for the idea that statistical learning and valance-based associative learning exert independent influences on the control of attention, which has implications for contemporary theories of selection history.
Keywords: Attentional capture; Selection history; Signal suppression; Statistical learning.
© 2022. The Psychonomic Society, Inc.