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

熟悉和不熟悉的人脸识别之间存在很大差异，然而，该领域的进展缓慢（Burton, 2013）。熟悉的面孔识别速度更快（Clutterbuck & Johnston, 2002），更准确（Burton, Wilson, Cowan & Bruce, 1999），对观点（Hill & Bruce, 1996）和表情（Bruce, 1982）的变化具有鲁强性。迄今为止，这些研究使用的是传统的面部熟悉方法，即让参与者接触到目标面部的不同照片。我提出的博士项目的中心目标是建立一种新的面部熟悉方法，该方法基于现实世界的社会互动，参与者与他们从未见过的演员互动。这一点之所以重要，有三个原因；首先，面部识别每天都在发生，在每次社会互动中，我的研究为实验室实验增加了现实世界的有效性。其次，这些现实世界的互动可能会驱动更强的神经反应，这将增加我提议的功能磁共振成像研究的力量。最后，重要的是要改进用于区分熟悉和不熟悉面部识别之间差异的方法，因为它们在使用目击证人证词（Brewer & Wells, 2011）以及在机场和其他高安全环境中使用带照片的身份证（White, Kemp, Jenkins, Matheson & Burton, 2014）方面具有重要意义。尽管熟悉的面孔识别的行为影响已经得到了很好的研究，但其神经关联还没有得到很好的证实。枕部面部区、梭状回面部区和颞上沟是面部选择区域，它们对面部的反应比物体或场景更强烈（Kanwisher, McDermott & Chun, 1997; Pitcher, Dilks, Saxe, Triantafyllou & Kanwisher, 2011）。然而，神经成像和神经刺激研究对大脑中面孔熟悉程度的研究产生了不同的结果。一些fMRI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，1999）。一些经颅磁刺激研究表明，在身份识别之前，OFA代表了早期处理阶段的面部部分（Pitcher, Walsh， Yovel和Duchaine, 2007; Pitcher， Walsh和Duchaine， 2011），而其他经颅磁刺激实验发现OFA在面部识别中起作用（Solomon-Harris， Mullin和Steeves， 2013）。至关重要的是，所有这些先前的研究都使用了传统的面部熟悉方法。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，面部表现出的人与人之间的变化不能被一张照片捕捉到（Jenkins, White, Van Montfort & Burton, 2011）。可以使用环境图像代替熟悉技术，在不同照明条件和角度下的个人自然照片等，因为它们不会对个人内部变化视而不见。此外，与目标面部的实时互动也以生态有效的方式捕捉到人的内部变化。此外，人脸学习还没有被完全理解。众所周知，观察人脸的时间越长，人脸识别效果越好（Downes et al., 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）。变化和时间长度的精确权重还没有经过系统的测试。因此，需要进一步的研究来梳理面部学习的不同因素。在我的硕士项目（Sliwinska et al., In prep）中，参与者亲自与目标身份进行互动，这是一种新的高度生态有效的熟悉技术，可使识别准确率提高15%。在我的博士学位，我的目标是完善这个新的和有前途的方法来澄清矛盾的文献OFA和FFA的作用，使用fMRI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.