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Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4
Open accessAbstract
It is well established that attention modulates visual processing in extrastriate cortex. However, the underlying neural mechanisms are unknown. A consistent observation is that attention has its greatest impact on neuronal responses when multiple stimuli appear together within a cell’s receptive field. One way to explain this is to assume that multiple stimuli activate competing populations of neurons and that attention biases this competition in favor of the attended stimulus. In the absence of competing stimuli, there is no competition to be resolved. Accordingly, attention has a more limited effect on the neuronal response to a single stimulus. To test this interpretation, we measured the responses of neurons in macaque areas V2 and V4 using a behavioral paradigm that allowed us to isolate automatic sensory processing mechanisms from attentional effects. First, we measured each cell’s response to a single stimulus presented alone inside the receptive field or paired with a second receptive field stimulus, while the monkey attended to a location outside the receptive field. Adding the second stimulus typically caused the neuron’s response to move toward the response that was elicited by the second stimulus alone. Then, we directed the monkey’s attention to one element of the pair. This drove the neuron’s response toward the response elicited when the attended stimulus appeared alone. These findings are consistent with the idea that attention biases competitive interactions among neurons, causing them to respond primarily to the attended stimulus. A quantitative neural model of attention is proposed to account for these results.
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“Later in time, competition can be biased by top-down control—either by prioritizing a spatial location (Moran & Desimone, 1985) or the perceptual feature(s) summarized in an “attentional template” (Chelazzi, Duncan, Miller, & Desimone, 1998; Reynolds, Chelazzi, & Desimone, 1999).”
From Selection history: How reward modulates selectivity of visual attention. (2018) · cites this paper as Reynolds, Chelazzi, & Desimone, 1999
Experimental — accuracy not yet measuredIn the citing paper
“It also shows good agreement (23) with other data in V4 (28) about the response of neurons to combinations of simple two-bar stimuli (within the receptive field of the S 2 units)”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [28]
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Metadata
- Authors
- Reynolds, J. H., Chelazzi, L., & Desimone, R.
- Affiliations
- National Institutes of Health (US)
- University of Verona (IT)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 1999-03-01
- Volume
- 19
- Issue
- 5
- Pages
- 1736-1753
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6782185
- OpenAlex
- W2170478537
- Cited by
- 1,236
- References
- 46
- Citations by year
- 2026: 22 · 2025: 20 · 2024: 26 · 2023: 28 · 2022: 23 · 2021: 38 · 2020: 31 · 2019: 28 · 2018: 35 · 2017: 26 · 2016: 43 · 2015: 49 · 2014: 55 · 2013: 54 · 2012: 56
- FWCI
- 24.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Keywords
- visual attention, competition mechanism, V2, area V4, extrastriate cortex, receptive fields, macaque visual cortex
- MeSH terms
- Animals, Attention, Behavior, Animal, Electrodes, Implanted, Macaca, Male, Models, Neurological, Neurons, Photic Stimulation, Reaction Time, Task Performance and Analysis, Visual Cortex, Visual Pathways, Visual Perception
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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 ›
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