ArticleAttention, perception & psychophysics2023
Combined influence of valence and statistical learning on the control of attention II: Evidence from within-domain additivity.
Article in Attention, perception & psychophysics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Distinct underlying mechanisms contribute to learning-dependent distractor rejection.Psychonomic bulletin & review · 2026Article
- Guidance of attention by statistical learning when multiple guidance mechanisms compete.Attention, perception & psychophysics · 2026Article
- Differential Modulation of Attention by Aversive Associative and Statistical Learning in Distinct Visual Search Modes.Behavioral sciences (Basel, Switzerland) · 2025Article
- Visual statistical learning requires attention.Psychonomic bulletin & review · 2025Article
- Trichotomy revisited: A monolithic theory of attentional control.Vision research · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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