Abstract
The M170 is a peak in scalp magnetoencephalography (MEG) that manifests roughly 170 milliseconds after image onset, and is believed to be face-specific. In this study, we explored the influence of image blur on M170 latency and amplitude. In separate behavioral experiments (Cherian et al., VSS 2008), we found an increase in reaction time on subordinate but not basic-level categorization tasks correlated with the level of degradation. With increasing blur, face identification accuracy decreased and latency increased, on the order of 100 milliseconds for no to highest blur used in the our study. We sought to determine whether changes in the latency and amplitude of the M170 reflect these behavioral findings. MEG signals across the entire scalp were recorded while participants viewed famous and non-famous face and building images, degraded to varying extents, and performed a one-back task. We found that as blur was increased, the M170 amplitude decreased, and the latency increased for all image types (on the order of 20 milliseconds from no to highest blur). The M170 amplitudes for celebrity and non-celebrity images were identical to each other, and greater than those for building images, for every blur level. For celebrity and non-celebrity images, the M170 latencies were identical, and larger than those for building images, at the different blur levels. Our data showed that the behaviorally manifested delay in face recognition could not be fully accounted for by the observed delay in the M170. This, coupled with the finding that celebrity and non-celebrity M170s were identical, suggests that the M170 is unlikely to reflect subordinate face identification. Additionally, the finding that blurring non-face images affects the corresponding M170 signal suggests that this component might not be entirely face-specific, but may instead reflect neural processing of a broader class of visual stimuli.