Abstract
The other-race classification advantage is the phenomenon that people classify faces of other-races faster than faces of their own-race. Familiarity has been shown to facilitate faster processes that promote face recognition as reflected in the proportion of familiar faces recognized just as fast at the subordinate level as the basic level. Limited research is available on the behavioral and neural effects of familiarity on the other-race classification advantage. The current study aimed to bridge this gap in the literature. A Face Classification task was used to examine this phenomenon by classifying stimuli faces as own-race, Caucasian, and other-race, African American. A Familiarity Rating task was used to indicate participants' level of familiarity with the own-race and other-race stimuli faces. Using N170 and P300, the current study captured the brain temporal dynamics of face classification by race and familiarity. My study replicated a number of findings like the other-race classification advantage in all faces and faster processing of familiar faces, but it did not provide evidence for an impact of familiarity on the other-race classification advantage. In conclusion, the current study found evidence of faster classification of familiar faces and the other-race classification advantage on RT and ERP component, N170, but found no association between stimuli race and familiarity and hence, familiarity did not modulate the other-race classification advantage.
Advisor
Herzmann, Grit
Second Advisor
John Neuhoff
Department
Neuroscience
Recommended Citation
Khan, Nashmia, "The Effect of Familiarity on Face Processing of the Other-Race Classification Advantage" (2020). Senior Independent Study Theses. Paper 9089.
https://openworks.wooster.edu/independentstudy/9089
Disciplines
Cognitive Neuroscience | Developmental Neuroscience | Mental and Social Health | Neuroscience and Neurobiology
Publication Date
2020
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2020 Nashmia Khan