The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Neural mechanisms of rapid natural scene categorization in human visual cortex
Open accessAbstract
The visual system has an extraordinary capability to extract categorical information from complex natural scenes. For example, subjects are able to rapidly detect the presence of object categories such as animals or vehicles in new scenes that are presented very briefly. This is even true when subjects do not pay attention to the scenes and simultaneously perform an unrelated attentionally demanding task, a stark contrast to the capacity limitations predicted by most theories of visual attention. Here we show a neural basis for rapid natural scene categorization in the visual cortex, using functional magnetic resonance imaging and an object categorization task in which subjects detected the presence of people or cars in briefly presented natural scenes. The multi-voxel pattern of neural activity in the object-selective cortex evoked by the natural scenes contained information about the presence of the target category, even when the scenes were task-irrelevant and presented outside the focus of spatial attention. These findings indicate that the rapid detection of categorical information in natural scenes is mediated by a category-specific biasing mechanism in object-selective cortex that operates in parallel across the visual field, and biases information processing in favour of objects belonging to the target object category.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
Broadbent, D. E. (1958) · doi:10.1037/10037-000 · Cited by 4,337
Speed of processing in the human visual system
Thorpe, S., Fize, D., & Marlot, C. (1996) · Nature · doi:10.1038/381520a0 · Cited by 3,538
A neural basis for visual search in inferior temporal cortex
Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (1993) · Nature · doi:10.1038/363345a0 · Cited by 1,114
Solving the “real” mysteries of visual perception: The world as an outside memory
O'Regan, J. K. (1992) · Canadian Journal of Psychology / Revue canadienne de psychologie · doi:10.1037/h0084327 · Cited by 997
Cited by
Pessoa, L., & Adolphs, R. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2920 · Cited by 1,794
Decoding Patterns of Human Brain Activity
Tong, F., & Pratte, M. S. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100412 · Cited by 375
From Behavior to Neural Dynamics: An Integrated Theory of Attention
Buschman, T. J., & Kastner, S. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.017 · Cited by 367
Self-citationAttention during natural vision warps semantic representation across the human brain
Çukur, T., Nishimoto, S., Huth, A. G., & Gallant, J. L. (2013) · Nature Neuroscience · doi:10.1038/nn.3381 · Cited by 351
THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images
Hebart, M. N., Dickter, A. H., Kidder, A., Kwok, W. Y., Corriveau, A., Van Wicklin, C., & Baker, C. I. (2019) · PLOS ONE · doi:10.1371/journal.pone.0223792 · Cited by 281
Metadata
- Authors
- Peelen, M. V., Fei-Fei, L., & Kastner, S.
- Venue
- Nature
- Published
- 2009-06-07
- Volume
- 460
- Issue
- 7251
- Pages
- 94-97
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1984891974
- Cited by
- 281
- References
- 5
- FWCI
- 11.72
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Neural mechanisms of rapid natural scene categorization in human visual cortex. https://app.cochat.ai/papers/10.1038/nature08103
- The paper
- Peelen, M. V., Fei-Fei, L., & Kastner, S. (2009). Neural mechanisms of rapid natural scene categorization in human visual cortex. Nature. https://doi.org/10.1038/nature08103
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.