The Neural Mechanisms of Face Ensemble Processing: Decoding Facial Summary Statistics from ERP Signals

Previous behavioural work has demonstrated our ability to extract summary statistics from groups of faces such as identity. Because we know very little how the extraction of summary statistics for identity occurs in the cortex, I used electroencephalography (EEG) to explore the neural basis of identity summary statistics . I collected EEG data while participants viewed face ensembles or single faces presented one at a time. Different ensembles were designed so that they contained the same average face. Pattern analyses were then conducted across signals recorded from 12 occipitotemporal electrodes. The analyses revealed that ensembles with different averages could be decoded from one another suggesting that we possess a mechanism capable of summarizing identity well enough that the neural signal for one ensemble is decodable from that of an ensemble with a different average. This thesis investigation sheds new light on the neural basis of ensemble processing of identity.