Neuroanatomic localization of priming effects for famous faces with latency-corrected event-related potentials

The late components of event-related brain potentials (ERPs) pose a difficult problem in source localization. One of the reasons is the smearing of these components in conventional averaging because of trial-to-trial latency-variability. The smearing problem may be addressed by reconstructing the ERPs after latency synchronization with the Residue Iteration Decomposition (RIDE) method. Here we assessed whether the benefits of RIDE at the surface level also improve source localization of RIDE-reconstructed ERPs (RERPs) measured in a face priming paradigm. Separate source models for conventionally averaged ERPs and RERPs were derived and sources were localized for both early and late components. Jackknife averaging on the data was used to reduce the residual variance during source localization compared to conventional source model fitting on individual subject data. Distances between corresponding sources of both ERP and RERP models were measured to check consistency in both source models. Sources for activity around P100, N170, early repetition effect (ERE/N250r) and late repetition effect (LRE/N400) were reported and priming effects in these sources were evaluated for six time windows. Significant improvement in priming effect of the late sources was found from the RERP source model, especially in the Medio-Temporal Lobe, Prefrontal Cortex, and Anterior Temporal Lobe. Consistent with previous studies, we found early priming effects in the right hemisphere and late priming effects in the left hemisphere. Also, the priming effects in right hemisphere outnumbered the left hemisphere, signifying dominance of right hemisphere in face recognition. In conclusion, RIDE reconstructed ERPs promise a comprehensive understanding of the time-resolved dynamics the late sources play during face recognition.