A previous experiment tested subjects' new/old judgments of previously-studied faces, distractors, and morphs between pairs of studied parents. We examine the extent to which models based on principal component analysis (eigenfaces) can predict human recognition of studied faces and false alarms to the distractors and morphs. We also compare eigenface models to the predictions of previous models based on the positions of faces in a multidimensional "face space" derived from a multidimensional scaling (MDS) of human similarity ratings. We find that the error in reconstructing a test face from its position in an "eigenface space" provides a good overall prediction of human familiarity ratings. However, the model has difficulty accounting for the fact that humans false alarm to morphs with similar parents more frequently than they false alarm to morphs with dissimilar parents. We ascribe this to the limitations of the simple reconstruction error-based model. We then outline preliminary work to improve the fine-grained fit within the eigenface-based modeling framework, and discuss the results' implicadons for exemplar- and face space-based models of face processing.

Shiffrin and Schneider (1977) demonstrated that highly efficient memory- and visual-search performance could be achieved through consistent item-to-response mapping (CM) training. It is theorized that subjects shifted from relying on working memory to learned item-response associations in long-term memory (Logan, 1988). The theory was tested and explored mostly through behavioral experiments and computational modeling. In a recent series of articles involving visual search (e.g. Woodman et al, 2013; Carlisle et al. 2011), Woodman and colleagues found that the contralateral-delay activity (CDA) of human event-related potentials is related to the maintenance of information in visual working memory and that the magnitude of the CDA decreases when target information is stored in long-term memory. We employed the CDA and other neural measures to study the nature of memory retrieval in CM memory search tasks. We observed a significant reduction in the magnitude of the CDA in CM training compared to a control condition in which item-response mappings varied from trial to trial (VM). The results provided converging evidence supporting the classic theoretical interpretation of the bases for CM and VM memory search. The results also raised interesting questions concerning the detailed interpretation of CDA.