Learning influences the encoding of static and dynamic faces and their recognition across different spatial frequencies

Studies on face recognition have shown that observers are faster and more accurate at recognizing faces learned from dynamic sequences than those learned from static snapshots. Here, we investigated whether different learning procedures mediate the advantage for dynamic faces across different spatial frequencies. Observers learned two faces—one dynamic and one static—either in depth (Experiment 1) or using a more superficial learning procedure (Experiment 2). They had to search for the target faces in a subsequent visual search task. We used high-spatial frequency (HSF) and low-spatial frequency (LSF) filtered static faces during visual search to investigate whether the behavioural difference is based on encoding of different visual information for dynamically and statically learned faces. Such encoding differences may mediate the recognition of target faces in different spatial frequencies, as HSF may mediate featural face processing whereas LSF mediates configural processing. Our results show that the nature of the learning procedure alters how observers encode dynamic and static faces, and how they recognize those learned faces across different spatial frequencies. That is, these results point to a flexible usage of spatial frequencies tuned to the recognition task