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  • 标题:Is subliminal face processing modulated by attentional task sets? Evidence from masked priming effects in a gender decision task
  • 本地全文:下载
  • 作者:Eun-Jim Sim ; Marcel Harpaintner ; Markus Kiefer
  • 期刊名称:Open Psychology
  • 电子版ISSN:2543-8883
  • 出版年度:2020
  • 卷号:2
  • 期号:1
  • 页码:76-89
  • DOI:10.1515/psych-2020-0006
  • 摘要:Unlike classical theories of automaticity, refined theories suggest that unconscious automatic processes depend on cognitive control settings. Cognitive control influences on unconscious word and object processing are well documented, but corresponding findings in the field of face processing are heterogeneous. The present study therefore investigated, whether subliminal face priming in a gender categorization task is susceptible to feature-specific attention. Participants performed a gender decision task by orthogonally varying gender congruency (prime-target: same vs. different gender) and emotion congruency (prime-target: same vs. different emotional facial expression) using a masked priming paradigm. Perceptual vs. emotional induction tasks, performed prior to prime presentation, served to activate corresponding attentional task sets. Subliminal gender priming (faster reactions to gender-congruent primes) differed as a function of induction task and emotional congruency. Following perceptual induction, gender priming was only obtained in the emotionally congruent condition, whereas following emotional induction gender priming was observed independently of emotional congruency. In line with the classical notion of automaticity, subliminal gender priming did not depend on a specific attentional focus. However, attention to shape facilitated subliminal processing of task-irrelevant emotional facial expressions. Most likely, mutual facilitation of emotionally congruent prime and target representations enhanced gender priming compared with emotionally incongruent pairings.
  • 关键词:consciousness ; automatic processes ; attentional control ; subliminal perception ; subliminal priming of faces
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