Besson G, Barragan-Jason G, Thorpe S J, Fabre-Thorpe M, Puma S, Ceccaldi M, Barbeau E J
Centre de Recherche Cerveau et Cognition, UPS, Université de Toulouse, 118 Route de Narbonne, 31062 Toulouse, France; CerCo CNRS UMR 5549, Pavillon Baudot CHU Purpan, BP 25202, 31052 Toulouse Cedex, France; Institut de neurosciences des systèmes, INSERM UMR 1106, Aix-Marseille Université, Faculté de Médecine, 27, Boulevard Jean Moulin, 13005 Marseille, France.
Centre de Recherche Cerveau et Cognition, UPS, Université de Toulouse, 118 Route de Narbonne, 31062 Toulouse, France; CerCo CNRS UMR 5549, Pavillon Baudot CHU Purpan, BP 25202, 31052 Toulouse Cedex, France.
Cognition. 2017 Jan;158:33-43. doi: 10.1016/j.cognition.2016.10.004. Epub 2016 Oct 21.
Verifying that a face is from a target person (e.g. finding someone in the crowd) is a critical ability of the human face processing system. Yet how fast this can be performed is unknown. The 'entry-level shift due to expertise' hypothesis suggests that - since humans are face experts - processing faces should be as fast - or even faster - at the individual than at superordinate levels. In contrast, the 'superordinate advantage' hypothesis suggests that faces are processed from coarse to fine, so that the opposite pattern should be observed. To clarify this debate, three different face processing levels were compared: (1) a superordinate face categorization level (i.e. detecting human faces among animal faces), (2) a face familiarity level (i.e. recognizing famous faces among unfamiliar ones) and (3) verifying that a face is from a target person, our condition of interest. The minimal speed at which faces can be categorized (∼260ms) or recognized as familiar (∼360ms) has largely been documented in previous studies, and thus provides boundaries to compare our condition of interest to. Twenty-seven participants were included. The recent Speed and Accuracy Boosting procedure paradigm (SAB) was used since it constrains participants to use their fastest strategy. Stimuli were presented either upright or inverted. Results revealed that verifying that a face is from a target person (minimal RT at ∼260ms) was remarkably fast but longer than the face categorization level (∼240ms) and was more sensitive to face inversion. In contrast, it was much faster than recognizing a face as familiar (∼380ms), a level severely affected by face inversion. Face recognition corresponding to finding a specific person in a crowd thus appears achievable in only a quarter of a second. In favor of the 'superordinate advantage' hypothesis or coarse-to-fine account of the face visual hierarchy, these results suggest a graded engagement of the face processing system across processing levels as reflected by the face inversion effects. Furthermore, they underline how verifying that a face is from a target person and detecting a face as familiar - both often referred to as "Face Recognition" - in fact differs.
验证一张脸是否来自目标人物(例如在人群中找到某人)是人脸处理系统的一项关键能力。然而,完成这项任务的速度有多快尚不清楚。“因专业技能导致的入门级转变”假说表明,由于人类是面部识别专家,处理个体面部的速度应该与处理上级层面的面部速度一样快,甚至更快。相比之下,“上级优势”假说认为,面部处理是从粗略到精细的,因此应该观察到相反的模式。为了澄清这场争论,我们比较了三种不同的面部处理水平:(1)上级面部分类水平(即在动物面孔中检测人类面孔),(2)面部熟悉度水平(即在不熟悉的面孔中识别名人面孔),以及(3)验证一张脸是否来自目标人物,这是我们感兴趣的条件。此前的研究已大量记录了对面孔进行分类(约260毫秒)或识别为熟悉面孔(约360毫秒)的最低速度,因此为将我们感兴趣的条件与之进行比较提供了界限。研究纳入了27名参与者。由于它能促使参与者采用最快的策略,因此使用了最近的速度与准确性提升程序范式(SAB)。刺激物以正立或倒立的形式呈现。结果显示,验证一张脸是否来自目标人物(最短反应时间约为260毫秒)非常快,但比面部分类水平(约2