ArticleProceedings of the National Academy of Sciences of the United States of America2018
Mid-level visual features underlie the high-level categorical organization of the ventral stream.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 1 of them a synthesis that pooled it.
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Who cites it
112 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Structural Covariance of Early Visual Cortex Is Negatively Associated With Posttraumatic Stress Disorder Symptoms: A Mega-Analysis From the ENIGMA PTSD Working Group.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Pooled it
- The SPOT Grid: Naturalistic images with predefined settings, patterns, objects, and textures.Behavior research methods · 2026Article
- Self-supervised learning yields representational signatures of category-selective cortex.Communications biology · 2026Article
- Perceiving animacy in 'identical' images.eLife · 2026Article
- Article
- Neuronal tuning aligns dynamically with object and texture manifolds across the visual hierarchy.Nature neuroscience · 2026Article
- Sequential experience reshapes population representations in visual cortex.bioRxiv : the preprint server for biology · 2026Article
- Three-dimensional scene boundary representations for wall orientation and distance are represented distinctly in the human visual cortex.PLoS biology · 2026Article
- A 2D Gabor-wavelet baseline model out-performs a 3D surface model in scene-responsive cortex.PLoS computational 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
- Investigating action topography in visual cortex and deep artificial neural networks.Nature communications · 2025Article
- Impacts of early life adversity on the neurocircuitry of emotional memory in children.Development and psychopathology · 2025Article
- Category-specific perceptual learning of robust object recognition modelled using deep neural networks.PLoS computational biology · 2025Article
- Multidimensional Representation Dynamics for Abstract Visual Objects in Encoded Tangram Paradigms.Brain sciences · 2025Article
- Neural representations of visual categories are dynamically tailored to the discrimination required by the task.Cerebral cortex (New York, N.Y. : 1991) · 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
- Configural processing as an optimized strategy for robust object recognition in neural networks.Communications biology · 2025Article
- Responses of neurons in macaque V4 to object and texture images.bioRxiv : the preprint server for biology · 2025Article
- Affective Visual Circuit Dysfunction in Trauma and Stress-Related Disorders.Biological psychiatry · 2025Review
52 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a class of stimuli-texforms-which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information without requiring explicit recognition of intact objects.
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