The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Population coding of shape in area V4
Overview
Integrity signals
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The size and complexity of receptive fields increases as one progresses through the visual hierarchy: in the retina/LGN receptive fields respond preferentially to spots of light, in V1 they are tuned for orientation (preferring lines or bars) (12), and in area V2 they respond preferentially to corners or junctions (13), whereas in V4 they prefer more complex feature arrangements (14).”
From Visual perception and its impairment in schizophrenia (2008) · cites this paper as [14]
In the citing paper
“The size and complexity of receptive fields increases as one progresses through the visual hierarchy: in the retina/LGN receptive fields respond preferentially to spots of light, in V1 they are tuned for orientation (preferring lines or bars) (12), and in area V2 they respond preferentially to corners or junctions (13), whereas in V4 they prefer more complex feature arrangements (14).”
From Visual perception and its impairment in schizophrenia (2008) · cites this paper as [14]
Citations
Cites
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Receptive fields and functional architecture of monkey striate cortex
Hubel, D. H., & Wiesel, T. N. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008455 · Cited by 6,520
Recognition-by-components: A theory of human image understanding.
Biederman, I. (1987) · Psychological Review · doi:10.1037/0033-295x.94.2.115 · Cited by 5,621
Receptive fields of single neurones in the cat's striate cortex
Hubel, D. H., & Wiesel, T. N. (1959) · The Journal of Physiology · doi:10.1113/jphysiol.1959.sp006308 · Cited by 4,653
Ingle, D., Goodale, M. A., & Mansfield, R. J. W. (1982) · The MIT Press eBooks · Cited by 4,118
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
A Method of Measuring Eye Movemnent Using a Scieral Search Coil in a Magnetic Field
Robinson, D. A. (1963) · IEEE Transactions on Bio-medical Electronics · doi:10.1109/tbmel.1963.4322822 · Cited by 2,231
Representation and recognition of the spatial organization of three-dimensional shapes
Marr, D., & Nishihara, H. K. (1978) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1978.0020 · Cited by 2,159
Single Units and Sensation: A Neuron Doctrine for Perceptual Psychology?
Barlow, H. B. (1972) · Perception · doi:10.1068/p010371 · Cited by 1,714
A method of measuring eye movements using a scleral search coil in a magnetic field
Robinson, D. A. (1963) · Medical Entomology and Zoology · Cited by 1,709
Cited by
Sorted by citations
Performance-optimized hierarchical models predict neural responses in higher visual cortex
Yamins, D. L. K., Hong, H., Cadieu, C. F., Solomon, E. A., Seibert, D., & DiCarlo, J. J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403112111 · Cited by 1,924
Using goal-driven deep learning models to understand sensory cortex
Yamins, D. L. K., & DiCarlo, J. J. (2016) · Nature Neuroscience · doi:10.1038/nn.4244 · Cited by 1,621
Neural Mechanisms for Interacting with a World Full of Action Choices
Cisek, P., & Kalaska, J. F. (2010) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.051508.135409 · Cited by 1,543
Vagaries of Visual Perception in Autism
Dakin, S. C., & Frith, U. (2005) · Neuron · doi:10.1016/j.neuron.2005.10.018 · Cited by 763
Brain plasticity through the life span: Learning to learn and action video games
Bavelier, D., Green, C. S., Pouget, A., & Schrater, P. (2012) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-060909-152832 · Cited by 541
Metadata
- Authors
- Pasupathy, A., & Connor, C. E.
- Affiliations
- Massachusetts Institute of Technology (US)
- Johns Hopkins University (US)
- Corresponding author
- Connor, Charles E.
- Venue
- Nature Neuroscience
- Published
- 2002-11-11
- Volume
- 5
- Issue
- 12
- Pages
- 1332-1338
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- DOI
- 10.1038/972
- OpenAlex
- W2005108691
- Cited by
- 552
- References
- 51
- Citations by year
- 2026: 22 · 2025: 18 · 2024: 27 · 2023: 17 · 2022: 22 · 2021: 28 · 2020: 16 · 2019: 26 · 2018: 29 · 2017: 13 · 2016: 32 · 2015: 38 · 2014: 32 · 2013: 24 · 2012: 30
- FWCI
- 5.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- population coding, shape representation, area V4, macaque visual cortex, ventral stream, shape recovery, object recognition
- MeSH terms
- Action Potentials, Animals, Brain Mapping, Female, Macaca mulatta, Nerve Net, Neurons, Pattern Recognition, Visual, Photic Stimulation, Visual Cortex, Visual Fields, Visual Pathways, Normal Distribution
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.
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Population coding of shape in area V4. https://app.cochat.ai/papers/10.1038/972
- The paper
- Pasupathy, A., & Connor, C. E. (2002). Population coding of shape in area V4. Nature Neuroscience. https://doi.org/10.1038/972
