Individual Differences in Neural Correlates of Face Processing – An Event-Related Brain Potential Study -

Abstract

Although people are generally highly effective at recognising faces of others whose identities they are familiar with, it has been well established that the skill does not translate to unfamiliar faces as well. Research exploring unfamiliar face processing has repeatedly
observed the existence of normally distributed individual differences amongst the general population. This naturally occurring variability in face recognition skill has emerged both from widely utilised psychometric tests and from event-related brain potential (ERP) studies, however it remains unclear how the two are related. The current study aims to offer a deeper understanding of the factors underlying neural markers of face recognition such as the N170
inversion and selectivity components and the image-independent N250r effect. 84 participants’ ERPs were recorded alongside their performance in a varied range of
behavioural tests, consisting of: three well-known psychometric tests (the Cambridge Face Memory Test +, the Glasgow Face Matching Test 2, and the Cambridge Car Memory Test), two behavioural priming tasks, and a general speed task. Results revealed that participants with better performances in the GFMT2 also presented a greater sensitivity to low-level visual properties as seen in the P1 ERP component, as well as having shorter N170 latencies.
Furthermore, participants with greater CFMT+ scores showed higher sensitivity to an atypical internal facial configuration, as indicated by the N170 inversion effect, computed by subtracting amplitudes elicited by inverted faces from those elicited by upright faces. In
addition, the N250r component, representing later stages of face processing, showed no significant relation to performances in the behavioural priming tasks, despite the latter showing clear behavioural priming effects. However, participants who had smaller N250r effects showed greater early visual processing sensitivity, as measured by the C1 component. Overall, these results provide valuable insights into the nuanced role of individual differences in face recognition, advancing our understanding of its neural mechanisms.