• Media type: E-Article
  • Title: Automatic Attention Capture by Threatening, But Not by Semantically Incongruent Natural Scene Images
  • Contributor: Furtak, Marcin; Doradzińska, Łucja; Ptashynska, Alina; Mudrik, Liad; Nowicka, Anna; Bola, Michał
  • Published: Oxford University Press (OUP), 2020
  • Published in: Cerebral Cortex, 30 (2020) 7, Seite 4158-4168
  • Language: English
  • DOI: 10.1093/cercor/bhaa040
  • ISSN: 1047-3211; 1460-2199
  • Origination:
  • Footnote:
  • Description: Abstract Visual objects are typically perceived as parts of an entire visual scene, and the scene’s context provides information crucial in the object recognition process. Fundamental insights into the mechanisms of context-object integration have come from research on semantically incongruent objects, which are defined as objects with a very low probability of occurring in a given context. However, the role of attention in processing of the context-object mismatch remains unclear, with some studies providing evidence in favor, but other against an automatic capture of attention by incongruent objects. Therefore, in the present study, 25 subjects completed a dot-probe task, in which pairs of scenes—congruent and incongruent or neutral and threatening—were presented as task-irrelevant distractors. Importantly, threatening scenes are known to robustly capture attention and thus were included in the present study to provide a context for interpretation of results regarding incongruent scenes. Using N2 posterior-contralateral ERP component as a primary measure, we revealed that threatening images indeed capture attention automatically and rapidly, but semantically incongruent scenes do not benefit from an automatic attentional selection. Thus, our results suggest that identification of the context-object mismatch is not preattentive.
  • Access State: Open Access