From Unfamiliar Face Processing to Familiar Face Recognition: Behavioural and Neural Effects of Real World Face Learning

熟悉的和陌生的人脸识别之间有很大的区别，然而，这一领域的进展一直很缓慢(Burton，2013)。熟悉的人脸识别速度更快(Clutterbuck&Johnston，2002)，更准确(Burton，Wilson，Cowan&Bruce，1999)，对观点和表情的变化(Hill&Bruce，1996)和表情(Bruce，1982)具有较强的鲁棒性。到目前为止，这些研究使用了传统的面孔熟悉方法，参与者被暴露在目标面孔的不同照片中。我提议的博士项目的中心目标是建立一种新的面孔熟悉方法，这种方法基于真实世界的社交互动，参与者与他们从未谋面的参与者互动。这一点很重要，原因有三：首先，人脸识别每天都在发生，在每一次社交互动中，我的研究为基于实验室的实验增加了现实世界的有效性。其次，这些现实世界中的相互作用可能会驱动更强大的神经反应，这将增加我提议的功能磁共振研究的力量。最后，重要的是改进用于区分熟悉和陌生人脸识别的方法，因为它们在目击证人证词的使用中具有重要意义(布鲁尔和威尔斯，2011)，并在机场和其他高度安全的环境中使用带照片的身份证(White，Kemp，Jenkins，Matheon&Burton，2014)。尽管熟悉的人脸识别的行为影响已经得到了很好的研究，但神经关联还没有得到很好的确立。枕面区、梭形面区和上颞沟是面孔选择区域，它们对面孔的反应比对物体或场景的反应更多(Kanwisher，McDermott&Chun，1997；Pcher，Dilks，Saxe，Triantafyllou&Kanwisher，2011)。然而，研究大脑中面孔熟悉度的神经成像和神经刺激研究产生了喜忧参半的结果。一些功能磁共振研究发现，与不熟悉的面孔相比，熟悉面孔的FFA激活增加(Rotshtein，Henson，Treves，Driver&Dolan，2005)，而其他研究发现没有这种调节(Dubois等人，1999)。一些TMS研究表明，OFA代表了身份识别之前的早期加工阶段的人脸部分(Pcher，Walsh，Yovel&Duchaine，2007；Pcher，Walsh&Duchaine，2011)，而其他TMS实验发现，OFA在人脸识别中发挥作用(所罗门-Harris，Mullin&Steeves，2013)。关键是，所有这些先前的研究都使用了传统的人脸熟悉化方法。这是一个问题，因为这样的研究使用一张照片来代表要学习的脸。然而，面孔显示的是人与人之间的差异，这是一张照片无法捕捉到的(Jenkins，White，Van Montfort&Burton，2011)。可以使用使用环境图像的熟悉技术，即个人在不同照明条件和角度下的自然照片等，因为它们不会对人内的变化视而不见。此外，与目标面孔的现场互动也捕捉到了人内的差异，但以一种生态有效的方式。此外，面孔学习还没有完全被理解。众所周知，观察一张脸的时间越长，人脸识别效果越好(Downes等人，1997)，然而，最近的研究表明，在人脸学习过程中暴露于变化，例如从不同的角度呈现人脸，也会导致更好的人脸识别(Dwyer，Mundy，Vladeanu&Honey，2009)。变化和时间长度的准确权重还没有得到系统的测试。因此，需要进一步的研究来梳理面孔学习的不同因素。在我的硕士项目(Sliwinska等人，在Prep中)中，参与者亲自与目标身份互动，这是一种新的高度生态有效的熟悉技术，使识别准确率提高了15%。在我的博士学位中，我的目标是完善这一新的、有希望的方法，以澄清关于OFA和FFA角色的相互冲突的文献，使用功能磁共振成像和TMS。

There are large differences between familiar and unfamiliar face recognition, however, progress in the field has been slow (Burton, 2013). Familiar face recognition is faster (Clutterbuck & Johnston, 2002), more accurate (Burton, Wilson, Cowan & Bruce, 1999), robust to changes in viewpoint (Hill & Bruce, 1996) and expression (Bruce, 1982). To date, these studies have used traditional methods of face familiarisation in which participants are exposed to different pictures of the target face. The central aim of my proposed PhD project is to establish a new method of face familiarisation based on real-world social interactions in which participants interact with actors whom they have never met. This is important for three reasons; firstly, face recognition happens every day and in every social interaction, my research adds real world validity to lab-based experiments. Secondly, these real-world interactions are likely to drive stronger neural responses that will increase the power of my proposed fMRI studies. Finally, it is important to improve the methods used to tease apart the differences between familiar and unfamiliar face recognition as they have important implications in the use of eye-witness testimony (Brewer & Wells, 2011) and in the use of photo ID in airports and other high-security environments (White, Kemp, Jenkins, Matheson & Burton, 2014).Although the behavioural effects of familiar face recognition are well studied, the neural correlates are less well established. The occipital face area, fusiform face area, and superior temporal sulcus are face-selective regions, they respond more to faces than objects or scenes (Kanwisher, McDermott & Chun, 1997; Pitcher, Dilks, Saxe, Triantafyllou & Kanwisher, 2011). However, neuroimaging and neurostimulation studies examining face familiarity in the brain have produced mixed results. Some fMRI studies find increased FFA activation to familiar faces compared to unfamiliar (Rotshtein, Henson, Treves, Driver & Dolan, 2005), and others find no such modulation (Dubois et al., 1999). Some TMS studies demonstrate the OFA represents face parts in an early processing stage prior to identity recognition (Pitcher, Walsh, Yovel & Duchaine, 2007; Pitcher, Walsh & Duchaine, 2011), whereas other TMS experiments find the OFA plays a role in face recognition (Solomon-Harris, Mullin & Steeves, 2013).Crucially, all these prior studies have used conventional methods of face familiarisation. This is an issue as such studies use 1 photo to represent the face to be learnt. However, faces display within-person variation which cannot be captured by 1 photograph (Jenkins, White, Van Montfort & Burton, 2011). Familiarisation techniques using ambient images instead, natural photographs of an individual under different lighting conditions and angles etc., could be used as they are not blind to within-person variation. Moreover, live interaction with a target face also captures within-person variation but in an ecologically valid way.Furthermore, face learning is not yet fully understood. It is known that longer durations of time observing a face leads to better face recognition (Downes et al., 1997), however, more recent studies have shown that exposure to variation during face learning, e.g. presenting faces from different viewpoints, also leads to better face recognition (Dwyer, Mundy, Vladeanu & Honey, 2009). The precise weightings of variation and length of time have not yet been systematically tested. Therefore, further study is required to tease apart the different factors of face learning. In my master's project (Sliwinska et al., in prep), participants interacted with target identities in person, a new highly ecologically valid familiarisation technique, which lead to 15% increases in recognition accuracy. In my PhD, I aim to refine this new and promising method to clarify the conflicting literature on the OFA and FFA's roles using fMRI and TMS.