AUTHOR=Meek Benjamin P., Locheed Keri , Lawrence-Dewar Jane M., Shelton Paul A., Marotta Jonathan J. TITLE=Posterior cortical atrophy: an investigation of scan paths generated during face matching tasks JOURNAL=Frontiers in Human Neuroscience VOLUME=7 YEAR=2013 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2013.00309 DOI=10.3389/fnhum.2013.00309 ISSN=1662-5161 ABSTRACT=

When viewing a face, healthy individuals focus more on the area containing the eyes and upper nose in order to retrieve important featural and configural information. In contrast, individuals with face blindness (prosopagnosia) tend to direct fixations toward individual facial features—particularly the mouth. Presented here is an examination of face perception deficits in individuals with Posterior Cortical Atrophy (PCA). PCA is a rare progressive neurodegenerative disorder that is characterized by atrophy in occipito-parietal and occipito-temporal cortices. PCA primarily affects higher visual processing, while memory, reasoning, and insight remain relatively intact. A common symptom of PCA is a decreased effective field of vision caused by the inability to “see the whole picture.” Individuals with PCA and healthy control participants completed a same/different discrimination task in which images of faces were presented as cue-target pairs. Eye-tracking equipment and a novel computer-based perceptual task—the Viewing Window paradigm—were used to investigate scan patterns when faces were presented in open view or through a restricted-view, respectively. In contrast to previous prosopagnosia research, individuals with PCA each produced unique scan paths that focused on non-diagnostically useful locations. This focus on non-diagnostically useful locations was also present when using a restricted viewing aperture, suggesting that individuals with PCA have difficulty processing the face at either the featural or configural level. In fact, it appears that the decreased effective field of view in PCA patients is so severe that it results in an extreme dependence on local processing, such that a feature-based approach is not even possible.