The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4
Abstract
To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene. To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene.
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
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388
Self-citationSelective Attention Gates Visual Processing in the Extrastriate Cortex
Moran, J., & Desimone, R. (1985) · Science · doi:10.1126/science.4023713 · Cited by 2,433
Self-citationGuided search: An alternative to the feature integration model for visual search.
Wolfe, J. M., Cave, K. R., & Franzel, S. L. (1989) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.15.3.419 · Cited by 2,147
SPACE AND ATTENTION IN PARIETAL CORTEX
Colby, C. L., & Goldberg, M. E. (1999) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.22.1.319 · Cited by 1,710
Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex
Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.1.24 · Cited by 1,615
Intentional Maps in Posterior Parietal Cortex
Andersen, R. A., & Buneo, C. A. (2002) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.25.112701.142922 · Cited by 1,294
Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4
Reynolds, J. H., Chelazzi, L., & Desimone, R. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-05-01736.1999 · Cited by 1,236
Self-citationA visual salience map in the primate frontal eye field
Thompson, K. G., & Bichot, N. P. (2005) · Progress in Brain Research · doi:10.1016/s0079-6123(04)47019-8 · Cited by 431
Self-citation
Cited by
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Rhythms for cognition: communication through coherence
Fries, P. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.034 · Cited by 2,725
Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices
Buschman, T. J., & Miller, E. K. (2007) · Science · doi:10.1126/science.1138071 · Cited by 2,380
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition
Wang, X.-J. (2010) · Physiological Reviews · doi:10.1152/physrev.00035.2008 · Cited by 1,939
Neuronal gamma-band synchronization as a fundamental process in cortical computation
Fries, P. (2009) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.051508.135603 · Cited by 1,713
Metadata
- Authors
- Bichot, N. P., Rossi, A. F., & Desimone, R.
- Venue
- Science
- Published
- 2005-04-22
- Volume
- 308
- Issue
- 5721
- Pages
- 529-534
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2139076245
- Cited by
- 650
- References
- 8
- FWCI
- 16.03
- Type
- journal article
- Language
- en
- Open access
- closed
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: Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4. https://app.cochat.ai/papers/10.1126/science.1109676
- The paper
- Bichot, N. P., Rossi, A. F., & Desimone, R. (2005). Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4. Science. https://doi.org/10.1126/science.1109676
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.