Abstract
Many attention theories assume that selection is guided by a preattentive, spatial representation of the scene that combines bottom-up stimulus information with top-down influences (task goals and prior experience) to code for potentially relevant locations (priority map). At which level(s) of priority computation top-down influences modulate bottom-up stimulus signals is an open question. In a visual-search task, here we induced experience-driven spatial suppression (statistical learning) by presenting 1 of 2 salient distractors more frequently in one display region than the other. When a distractor standing out in the same dimension as the target was spatially biased in Experiment 1, processing of both the target and another, spatially unbiased distractor standing out in a different dimension was likewise hampered in the suppressed region. This indicates that constraining spatial suppression to a specific distractor feature is not possible, and participants instead resort to purely space-based (distractor-feature-independent) suppression at a supradimensional, overall-priority map. In line with a common locus of suppression, a novel computational model of distraction in visual search captures all 3 location effects with a single spatial-weighting parameter. In contrast, when the different-dimension distractor was spatially biased in Experiment 2, processing of other objects in the suppressed region was unaffected, indicating suppression constrained to a subordinate, dimension-specific level of priority computation. In sum, we demonstrate experience-driven top-down modulations of saliency signals at the overall-priority and dimension-specific levels that do not reach down to the specific distractor features.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Psychologie und Pädagogik > Department Psychologie |
Themengebiete: | 100 Philosophie und Psychologie > 150 Psychologie |
ISSN: | 0096-3445 |
Sprache: | Englisch |
Dokumenten ID: | 100119 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:33 |
Letzte Änderungen: | 17. Okt. 2023, 15:03 |