Abstract
Introduction. Race is a perceptual and social category. People automatically encode the race of indivduals and often categorize them by which. Many studies examined the behavioral effects of race on face recognition and categorization; very few investigated the neural underpinnings of race perception. Here we explore the spatiotemporal characteristics of brain signals responding to face race with magnetoencephalography (MEG). Methods. Thirteen Asian participants (mean age: 24.27 ± 2.13) joined the study. We used five morphing face stimuli, averaged between an Asian female and a Caucasian female (A0/C100, A25/C75, A50/C50, A75/C25, and A100/C0), to manipulate the strength of “race typicality.” In the MEG (Elekta Neuromag TRIUX MEG), the participants passively viewed the stimuli in random order. They also completed a 2AFC race categorization task separately. The Principal Component Analysis (PCA) for time series between −50 and 450 ms, Time-Frequency Representations (TFRs), and the group differences of Event-Related Fields (ERFs) at M170 and M250 were performed. Results. Three major components (48% of total variance) captured the main differences between seeing Asian (A100/C0) and Caucasian (A0/C100) faces: PCA1 shows strong Caucasian preference at M170 (MEG1721, left temporal lobe); PCA2 shows strong Asian preference at M170 and strong Caucasian preference at M250 (MEG2641, right temporal lobe); PCA3 component shows strong Caucasian preference at both M170 and M250 (MEG1723, left temporal lobe). The TFRs between 150–200 ms revealed a stronger power for Asian faces in the left prefrontal lobe and Caucasian faces in the right temporal lobe. The ERFs of Asian and Caucasian faces were significantly different in prefrontal lobes and right temporal lobe at M170, and in prefrontal and temporal lobes at M250. Conclusion. Our analyses revealed that both M170 and M250 components are correlated with race categorization temporally, while bilateral temporal lobes and a portion of prefrontal lobe might be involved spatially.
Acknowledgement: Taiwanese Ministry of Science and Technology MOST 105-2420-H-039-001-MY3, to Dr. Sarina H.L. Chien