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A Normalization Model of Attentional Modulation of Single Unit Responses
Open accessAbstract
Although many studies have shown that attention to a stimulus can enhance the responses of individual cortical sensory neurons, little is known about how attention accomplishes this change in response. Here, we propose that attention-based changes in neuronal responses depend on the same response normalization mechanism that adjusts sensory responses whenever multiple stimuli are present. We have implemented a model of attention that assumes that attention works only through this normalization mechanism, and show that it can replicate key effects of attention. The model successfully explains how attention changes the gain of responses to individual stimuli and also why modulation by attention is more robust and not a simple gain change when multiple stimuli are present inside a neuron's receptive field. Additionally, the model accounts well for physiological data that measure separately attentional modulation and sensory normalization of the responses of individual neurons in area MT in visual cortex. The proposal that attention works through a normalization mechanism sheds new light a broad range of observations on how attention alters the representation of sensory information in cerebral cortex.
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“Attentional modulation of neural gain has been particularly well studied in the non-human primate visual system1,42,43, in which visual spatial attention within the receptive field of a recorded neuron enhances both contrast gain (that is, scaling of that neuron’s stimulus-response relationship along the contrast axis)43 and response gain (that is, multiplicative transformation of responses to all”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [46]
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Metadata
- Authors
- Lee, J., & Maunsell, J. H. R.
- Affiliations
- Baylor College of Medicine (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Maunsell, John H. R.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2009-02-27
- Volume
- 4
- Issue
- 2
- Pages
- e4651
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC2645695
- OpenAlex
- W2163588736
- Cited by
- 257
- References
- 51
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 6 · 2023: 27 · 2022: 10 · 2021: 14 · 2020: 11 · 2019: 18 · 2018: 13 · 2017: 13 · 2016: 18 · 2015: 18 · 2014: 20 · 2013: 18 · 2012: 17
- FWCI
- 9.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- National Eye Institute (R01EY005911)
- 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
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- attentional modulation, single-unit responses, gain modulation, multiple stimuli, receptive fields, area MT, visual cortex, computational model of attention, neuronal gain
- MeSH terms
- Attention, Cerebral Cortex, Humans, Models, Theoretical
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