Charlotte Atzert
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Charlotte Atzert has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Filip Děchtěrenko
Institute of Psychology, Czech Academy of Sciences, Prague, Czech Republic
1 shared publication - Jiri Lukavsky
Prague College of Psychosocial Studies, Prague 4, Czech Republic
1 shared publication - Niko A. Busch
Institute of Psychology, University of Münster, Germany
1 shared publication
Latest Publications
- Open Access
Scene memorability reflects representational distinctiveness within visual categories
Some images are consistently remembered better than others, suggesting that memorability reflects intrinsic image properties. We tested whether within-category distinctiveness underlies this effect. Across three experiments ( N = 477), participants categorized indoor scenes previously rated for subjective typicality and then completed recognition memory tests. Typical scenes were categorized faster and more accurately, but were remembered worse and showed a more liberal response bias than atypical scenes. These opposing effects were robust across categories. To link subjective typicality to visual representations, we quantified image distinctiveness using a convolutional neural network (CNN). Across layers, CNN-derived distinctiveness closely tracked human typicality judgments and predicted both categorization speed and memorability, with strongest effects in higher, semantic layers. Critically, the memory advantage for atypical scenes persisted even when most images were atypical, ruling out rarity within the experimental context. Together, the results show that intrinsic scene memorability reflects an image’s position within a category-specific representational space.
Open AccessScene memorability reflects representational distinctiveness within visual categories
Some images are consistently remembered better than others, suggesting that memorability reflects intrinsic image properties. We tested whether within-category distinctiveness underlies this effect. Across three experiments ( N = 477), participants categorized indoor scenes previously rated for subjective typicality and then completed recognition memory tests. Typical scenes were categorized faster and more accurately, but were remembered worse and showed a more liberal response bias than atypical scenes. These opposing effects were robust across categories. To link subjective typicality to visual representations, we quantified image distinctiveness using a convolutional neural network (CNN). Across layers, CNN-derived distinctiveness closely tracked human typicality judgments and predicted both categorization speed and memorability, with strongest effects in higher, semantic layers. Critically, the memory advantage for atypical scenes persisted even when most images were atypical, ruling out rarity within the experimental context. Together, the results show that intrinsic scene memorability reflects an image’s position within a category-specific representational space.