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Han S, Rezanejad M, Walther DB. Memorability of line drawings of scenes: the role of contour properties. Mem Cognit 2025; 53:33-53. [PMID: 37903987 DOI: 10.3758/s13421-023-01478-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/04/2023] [Indexed: 11/01/2023]
Abstract
Why are some images more likely to be remembered than others? Previous work focused on the influence of global, low-level visual features as well as image content on memorability. To better understand the role of local, shape-based contours, we here investigate the memorability of photographs and line drawings of scenes. We find that the memorability of photographs and line drawings of the same scenes is correlated. We quantitatively measure the role of contour properties and their spatial relationships for scene memorability using a Random Forest analysis. To determine whether this relationship is merely correlational or if manipulating these contour properties causes images to be remembered better or worse, we split each line drawing into two half-images, one with high and the other with low predicted memorability according to the trained Random Forest model. In a new memorability experiment, we find that the half-images predicted to be more memorable were indeed remembered better, confirming a causal role of shape-based contour features, and, in particular, T junctions in scene memorability. We performed a categorization experiment on half-images to test for differential access to scene content. We found that half-images predicted to be more memorable were categorized more accurately. However, categorization accuracy for individual images was not correlated with their memorability. These results demonstrate that we can measure the contributions of individual contour properties to scene memorability and verify their causal involvement with targeted image manipulations, thereby bridging the gap between low-level features and scene semantics in our understanding of memorability.
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Affiliation(s)
- Seohee Han
- Department of Psychology, University of Toronto, 100 St. George Street, Toronto, Canada.
| | - Morteza Rezanejad
- Department of Psychology, University of Toronto, 100 St. George Street, Toronto, Canada
| | - Dirk B Walther
- Department of Psychology, University of Toronto, 100 St. George Street, Toronto, Canada
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2
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Torres RE, Duprey MS, Campbell KL, Emrich SM. Not all objects are created equal: The object benefit in visual working memory is supported by greater recollection-like memory, but only for memorable objects. Mem Cognit 2024:10.3758/s13421-024-01655-z. [PMID: 39467965 DOI: 10.3758/s13421-024-01655-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/10/2024] [Indexed: 10/30/2024]
Abstract
Visual working memory is thought to have a fixed capacity limit. However, recent evidence suggests that a greater number of real-world objects than simple features (i.e., colors) can be maintained, an effect termed the object benefit. Here, we examined whether this object benefit in visual working memory is due to qualitatively different memory processes employed for meaningful stimuli compared to simple features. In online samples of young adults, real-world objects were better remembered than colors, had higher measures of recollection, and showed a greater proportion of high-confidence responses (Exp. 1). Objects were also remembered better than their scrambled counterparts (Exp. 2), suggesting that this benefit is related to semantic information, rather than visual complexity. Critically, the specific objects that were likely to be remembered with high confidence were highly correlated across experiments, consistent with the idea that some objects are more memorable than others. Visual working memory performance for the least-memorable objects was worse than that of colors and scrambled objects. These findings suggest that real-world objects give rise to recollective, or at least high-confidence, responses at retrieval that may depend on activation of semantic features, but that this effect is limited to certain objects.
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Affiliation(s)
- Rosa E Torres
- Department of Psychology, Brock University, St. Catharines, ON, Canada
| | - Mallory S Duprey
- Department of Psychology, Brock University, St. Catharines, ON, Canada
| | - Karen L Campbell
- Department of Psychology, Brock University, St. Catharines, ON, Canada
| | - Stephen M Emrich
- Department of Psychology, Brock University, St. Catharines, ON, Canada.
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3
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Lee FM, Berman MG, Stier AJ, Bainbridge WA. Navigating Memorability Landscapes: Hyperbolic Geometry Reveals Hierarchical Structures in Object Concept Memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.22.614329. [PMID: 39386606 PMCID: PMC11463604 DOI: 10.1101/2024.09.22.614329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/12/2024]
Abstract
Why are some object concepts (e.g., birds, cars, vegetables, etc.) more memorable than others? Prior studies have suggested that features (e.g., color, animacy, etc.) and typicality (e.g., robin vs. penguin) of object images influences the likelihood of being remembered. However, a complete understanding of object memorability remains elusive. In this study, we examine whether the geometric relationship between object concepts explains differences in their memorability. Specifically, we hypothesize that image concepts will be geometrically arranged in hierarchical structures and that memorability will be explained by a concept's depth in these hierarchical trees. To test this hypothesis, we construct a Hyperbolic representation space of object concepts (N=1,854) from the THINGS database (Hebart et al., 2019), which consists of naturalistic images of concrete objects, and a space of 49 feature dimensions derived from data-driven models. Using ALBATROSS (Stier, A. J., Giusti, C., & Berman, M. G., In prep), a stochastic topological data analysis technique that detects underlying structures of data, we demonstrate that Hyperbolic geometry efficiently captures the hierarchical organization of object concepts above and beyond a traditional Euclidean geometry and that hierarchical organization is related to memorability. We find that concepts closer to the center of the representational space are more prototypical and also more memorable. Importantly, Hyperbolic distances are more predictive of memorability and prototypicality than Euclidean distances, suggesting that concept memorability and typicality are organized hierarchically. Taken together, our work presents a novel hierarchical representational structure of object concepts that explains memorability and typicality.
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Stoinski LM, Perkuhn J, Hebart MN. THINGSplus: New norms and metadata for the THINGS database of 1854 object concepts and 26,107 natural object images. Behav Res Methods 2024; 56:1583-1603. [PMID: 37095326 PMCID: PMC10991023 DOI: 10.3758/s13428-023-02110-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 04/26/2023]
Abstract
To study visual and semantic object representations, the need for well-curated object concepts and images has grown significantly over the past years. To address this, we have previously developed THINGS, a large-scale database of 1854 systematically sampled object concepts with 26,107 high-quality naturalistic images of these concepts. With THINGSplus, we significantly extend THINGS by adding concept- and image-specific norms and metadata for all 1854 concepts and one copyright-free image example per concept. Concept-specific norms were collected for the properties of real-world size, manmadeness, preciousness, liveliness, heaviness, naturalness, ability to move or be moved, graspability, holdability, pleasantness, and arousal. Further, we provide 53 superordinate categories as well as typicality ratings for all their members. Image-specific metadata includes a nameability measure, based on human-generated labels of the objects depicted in the 26,107 images. Finally, we identified one new public domain image per concept. Property (M = 0.97, SD = 0.03) and typicality ratings (M = 0.97, SD = 0.01) demonstrate excellent consistency, with the subsequently collected arousal ratings as the only exception (r = 0.69). Our property (M = 0.85, SD = 0.11) and typicality (r = 0.72, 0.74, 0.88) data correlated strongly with external norms, again with the lowest validity for arousal (M = 0.41, SD = 0.08). To summarize, THINGSplus provides a large-scale, externally validated extension to existing object norms and an important extension to THINGS, allowing detailed selection of stimuli and control variables for a wide range of research interested in visual object processing, language, and semantic memory.
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Affiliation(s)
- Laura M Stoinski
- Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany.
| | - Jonas Perkuhn
- Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany
| | - Martin N Hebart
- Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany
- Justus Liebig University, Gießen, Germany
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5
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Hebart MN, Contier O, Teichmann L, Rockter AH, Zheng CY, Kidder A, Corriveau A, Vaziri-Pashkam M, Baker CI. THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior. eLife 2023; 12:e82580. [PMID: 36847339 PMCID: PMC10038662 DOI: 10.7554/elife.82580] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 02/25/2023] [Indexed: 03/01/2023] Open
Abstract
Understanding object representations requires a broad, comprehensive sampling of the objects in our visual world with dense measurements of brain activity and behavior. Here, we present THINGS-data, a multimodal collection of large-scale neuroimaging and behavioral datasets in humans, comprising densely sampled functional MRI and magnetoencephalographic recordings, as well as 4.70 million similarity judgments in response to thousands of photographic images for up to 1,854 object concepts. THINGS-data is unique in its breadth of richly annotated objects, allowing for testing countless hypotheses at scale while assessing the reproducibility of previous findings. Beyond the unique insights promised by each individual dataset, the multimodality of THINGS-data allows combining datasets for a much broader view into object processing than previously possible. Our analyses demonstrate the high quality of the datasets and provide five examples of hypothesis-driven and data-driven applications. THINGS-data constitutes the core public release of the THINGS initiative (https://things-initiative.org) for bridging the gap between disciplines and the advancement of cognitive neuroscience.
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Affiliation(s)
- Martin N Hebart
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
- Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Department of Medicine, Justus Liebig University GiessenGiessenGermany
| | - Oliver Contier
- Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Max Planck School of Cognition, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Lina Teichmann
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Adam H Rockter
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Charles Y Zheng
- Machine Learning Core, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Alexis Kidder
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Anna Corriveau
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Maryam Vaziri-Pashkam
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
| | - Chris I Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of HealthBethesdaUnited States
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Li X, Bainbridge WA, Bakkour A. Item memorability has no influence on value-based decisions. Sci Rep 2022; 12:22056. [PMID: 36543818 PMCID: PMC9772201 DOI: 10.1038/s41598-022-26333-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
While making decisions, we often rely on past experiences to guide our choices. However, not all experiences are remembered equally well, and some elements of an experience are more memorable than others. Thus, the intrinsic memorability of past experiences may bias our decisions. Here, we hypothesized that individuals would tend to choose more memorable options than less memorable ones. We investigated the effect of item memorability on choice in two experiments. First, using food images, we found that the same items were consistently remembered, and others consistently forgotten, across participants. However, contrary to our hypothesis, we found that participants did not prefer or choose the more memorable over the less memorable items when choice options were matched for the individuals' valuation of the items. Second, we replicated these findings in an alternate stimulus domain, using words that described the same food items. These findings suggest that stimulus memorability does not play a significant role in determining choice based on subjective value.
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Affiliation(s)
- Xinyue Li
- Department of Psychology, University of Chicago, 5848 S University Ave, Chicago, IL, 60637, USA
| | - Wilma A Bainbridge
- Department of Psychology, University of Chicago, 5848 S University Ave, Chicago, IL, 60637, USA
- Neuroscience Institute, University of Chicago, 5812 S Ellis Ave, Chicago, IL, 60637, USA
| | - Akram Bakkour
- Department of Psychology, University of Chicago, 5848 S University Ave, Chicago, IL, 60637, USA.
- Neuroscience Institute, University of Chicago, 5812 S Ellis Ave, Chicago, IL, 60637, USA.
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Prasad D, Bainbridge WA. The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People. Psychol Sci 2022; 33:1971-1988. [PMID: 36219739 DOI: 10.1177/09567976221108944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The Mandela effect is an Internet phenomenon describing shared and consistent false memories for specific icons in popular culture. The visual Mandela effect is a Mandela effect specific to visual icons (e.g., the Monopoly Man is falsely remembered as having a monocle) and has not yet been empirically quantified or tested. In Experiment 1 (N = 100 adults), we demonstrated that certain images from popular iconography elicit consistent, specific false memories. In Experiment 2 (N = 60 adults), using eye-tracking-like methods, we found no attentional or visual differences that drive this phenomenon. There is no clear difference in the natural visual experience of these images (Experiment 3), and these errors also occur spontaneously during recall (Experiment 4; N = 50 adults). These results demonstrate that there are certain images for which people consistently make the same false-memory error, despite the majority of visual experience being the canonical image.
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