ArticleBehavior research methods2024
THINGSplus: New norms and metadata for the THINGS database of 1854 object concepts and 26,107 natural object images.
Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed.
- Img2EEG: A Scalable and Interpretable Encoding Framework for Simulating Human EEG Responses to Visual Inputs.bioRxiv : the preprint server for biology · 2026Article
- Food, mammals, & countries: Stimuli, their pairwise similarities, and MDS dimension values for modeling judgment, categorization, and memory in three real-world domains.Behavior research methods · 2026Article
- Progressive loss of independence in neuronal representations predicts cognitive decline.bioRxiv : the preprint server for biology · 2026Article
- Determinants of visual ambiguity resolution.Communications psychology · 2026Article
- Reverse engineering what makes a symbol memorable.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- What makes memories vivid?Journal of experimental psychology. General · 2026Article
- Drawings of THINGS: A large-scale drawing dataset of 1854 object concepts.Behavior research methods · 2026Article
- CNeuroMod-THINGS, a densely-sampled fMRI dataset for visual neuroscience.Scientific data · 2026Article
- Article
- Semantic Dimensions Support the Cortical Representation of Object Memorability.Journal of cognitive neuroscience · 2025Article
- Revealing emergent human-like conceptual representations from language prediction.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images.bioRxiv : the preprint server for biology · 2025Article
- Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations.Diagnostics (Basel, Switzerland) · 2025Review
- Dimensions underlying the representational alignment of deep neural networks with humans.Nature machine intelligence · 2025Article
- BRAND: Brand recognition and attitude norms database.Behavior research methods · 2024Article
- Distributed representations of behaviour-derived object dimensions in the human visual system.Nature human behaviour · 2024Article
- Distributed representations of behavior-derived object dimensions in the human visual system.bioRxiv : the preprint server for biology · 2024Article
- The features underlying the memorability of objects.Science advances · 2023Article
- Article
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3 authors.
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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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