The Neural Dynamics of Facial Identity Processing: insights from EEG-Based Pattern Analysis and Image Reconstruction

Abstract

Uncovering the neural dynamics of facial identity processing along with its representational basis outlines a major endeavor in the study of visual processing. To this end, here we record human electroencephalography (EEG) data associated with viewing face stimuli; then, we exploit spatiotemporal EEG information to determine the neural correlates of facial identity representations and to reconstruct the appearance of the corresponding stimuli. Our findings indicate that multiple temporal intervals support: facial identity classification, face space estimation, visual feature extraction and image reconstruction. In particular, we note that both classification and reconstruction accuracy peak in the proximity of the N170 component. Further, aggregate data from a larger interval (50-650 ms after stimulus onset) support robust reconstruction results, consistent with the availability of distinct visual information over time. Thus, theoretically, our findings shed light on the time course of face processing while, methodologically, they demonstrate the feasibility of EEG-based image reconstruction.

Significance Statement Identifying a face is achieved through fast and efficient processing of visual information. Here, we investigate the nature of this information, its specific content and its availability at a fine-grained temporal scale. Notably, we provide a way to extract, to assess and to visualize such information from neural data associated with individual face processing. Thus, the present work accounts for the time course of face individuation through appeal to its underlying visual representations while, also, it provides a first demonstration regarding the ability to reconstruct the appearance of stimulus images from electroencephalography data.