In Expt 2 we used a hybrid of Valentine's MDFS and Burton et al.
Within Valentine's MDFS framework caricatures have the same status as distinctive faces, therefore they can be thought of as 'distinctiveness-enhanced' representations of their faces.
This result is consistent with the idea that caricatures can be envisaged as distinctiveness-enhanced faces in MDFS.
We suggest that the results of all three experiments are best accommodated within a hybrid of Valentine's MDFS framework, which represents the best current account of 'front-end' processing, and Burton et al.
When a target is encoded, if it is located within the MDFS such that it is near to the norm, then it is more likely that the target also represents a face.
These effects can be accounted for by Valentine's MDFS framework.
Certainly, this is in accordance with an explanation in terms of Valentine's MDFS model.
Valentine's MDFS model makes no distinction across familiarity when describing the location of distinctive and typical faces.
Consequently, the present results provide a clear assessment of the predictive and explanatory power of Valentine's MDFS model.
The use of this technique to explore distinctiveness effects opens up a whole set of studies with predictions that arise directly from Valentine's MDFS model.