Temporal dynamics and task-dependent neural mechanisms in facial symmetry processing.

Abstract

Although symmetry has long been recognized as a critical feature in facial perception, relatively little research has examined the temporal dynamics of the neural mechanisms underlying the processing of facial symmetry. To address this gap, the present study employed event-related potentials (ERPs) to investigate these dynamics. Using a classic stimulus-response paradigm, behavioral and electroencephalography (EEG) data were collected from 27 participants under different task conditions. The results revealed that the neural mechanisms of symmetrical face processing exhibit not only distinct temporal dynamics but also partial automation. Specifically, symmetrical faces elicited larger N170 and later Sustained Posterior Negativity (SPN) amplitudes compared to asymmetrical faces in explicit symmetry tasks. The N170 component likely reflects an early stage of visual-perceptual processing, oriented toward aesthetic appraisal and face recognition, whereas the SPN reflects a mid-to-late stage of sustained integration involved in symmetry processing. These findings suggest that facial symmetry processing is a dynamic, strategy-driven process, with different priorities emerging at distinct stages of neural activity.Additionally, in the implicit task, symmetrical faces elicited larger P300 amplitudes compared to asymmetrical faces, suggesting a degree of automaticity in the processing of facial symmetry. N170 and P300 components were also observed when processing emoji stimuli in the explicit symmetry task, indicating that face-like materials engage similar neural mechanisms under certain conditions. Taken together, this study not only provides direct evidence of the neural mechanisms underlying facial symmetry processing in explicit tasks but also underscores the complexity and specificity of this process, as revealed through implicit tasks and the use of face-like stimuli such as emojis. These findings offer valuable insights into the temporal dynamics of the neural mechanisms involved in facial symmetry processing, advancing our understanding of its nuanced and multifaceted nature.