ArticleJournal of cognitive neuroscience2022
Mid-level Feature Differences Support Early Animacy and Object Size Distinctions: Evidence from Electroencephalography Decoding.
Article in Journal of cognitive neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 31 citations in OpenAlex.
- Self-supervised learning yields representational signatures of category-selective cortex.Communications biology · 2026Article
- Achieving more human brain-like vision via human EEG representational alignment.Communications biology · 2026Article
- Natural Scene and Object Perception Based on Statistical Image Features: Psychophysics and EEG.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Article
- Teaching CORnet human fMRI representations for enhanced model-brain alignment.Cognitive neurodynamics · 2025Article
- Selective Attention Dynamically Modulates the Hierarchical Order of Perceptual and Conceptual Representations.Human brain mapping · 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
- Ensemble representation of animacy could be based on mid-level visual features.Attention, perception & psychophysics · 2025Article
- The neural code for "face cells" is not face-specific.Science advances · 2023Article
- Article
- Does the brain's ventral visual pathway compute object shape?Trends in cognitive sciences · 2022Review
- Investigating the temporal dynamics and modeling of mid-level feature representations in humans.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Responses to visually presented objects along the cortical surface of the human brain have a large-scale organization reflecting the broad categorical divisions of animacy and object size. Emerging evidence indicates that this topographical organization is supported by differences between objects in mid-level perceptual features. With regard to the timing of neural responses, images of objects quickly evoke neural responses with decodable information about animacy and object size, but are mid-level features sufficient to evoke these rapid neural responses? Or is slower iterative neural processing required to untangle information about animacy and object size from mid-level features, requiring hundreds of milliseconds more processing time? To answer this question, we used EEG to measure human neural responses to images of objects and their texform counterparts-unrecognizable images that preserve some mid-level feature information about texture and coarse form. We found that texform images evoked neural responses with early decodable information about both animacy and real-world size, as early as responses evoked by original images. Furthermore, successful cross-decoding indicates that both texform and original images evoke information about animacy and size through a common underlying neural basis. Broadly, these results indicate that the visual system contains a mid-level feature bank carrying linearly decodable information on animacy and size, which can be rapidly activated without requiring explicit recognition or protracted temporal processing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.