Coding of the contrasts in natural images by populations of neurons in primary visual cortex (V1)
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It is possible to discriminate between grating contrasts over a 300-fold contrast range, whereas V1 neurons have very limited dynamic ranges. Using populations of model neurons with contrast-response parameters taken from electrophysiological studies (cat and macaque), we investigated ways of combining responses to code contrast over the full range. One model implemented a pooling rule that retained information about individual response patterns. The second summed responses indiscriminately. We measured accuracy of contrast identification over a wide range of contrasts and found the first model to be more accurate; the mutual information between actual and estimated contrast was also greatest for this model. The accuracy peak for the population of cat neurons coincided with the peak of the distribution of contrasts in natural images, suggesting an ecological match. Macaque neurons seem better able to code contrasts that are slightly higher on average than those found in the natural environment.
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Several studies have found good agreement between population-level responses of gain-modulated neurons and psychophysical performance in visual contrast discrimination in humans and non-human primates.
“Indeed, several studies have found good agreement between the population-level responses of gain-modulated neurons (such as the population-average contrast response function) and psychophysical performance (for example, in visual contrast discrimination) in humans and non-human primates12,20–24.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [22]
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Research works printed but not linked: 3
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Cited by
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- Authors
- Clatworthy, P. L., Chirimuuta, M., Lauritzen, J. S., & Tolhurst, D. J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Chirimuuta, M.
- Venue
- Vision Research
- Publisher
- Elsevier BV
- Published
- 2003-08
- Volume
- 43
- Issue
- 18
- Pages
- 1983-2001
- ISSN
- 0042-6989 (ISSN-L)
- OpenAlex
- W1964102929
- Cited by
- 54
- References
- 102
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 1 · 2022: 3 · 2021: 1 · 2020: 1 · 2019: 2 · 2018: 1 · 2017: 2 · 2016: 5 · 2015: 4 · 2013: 2 · 2012: 2
- FWCI
- 1.96
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Vision Research (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Funders
- Medical Research Council
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- contrast coding, primary visual cortex, population coding, grating contrast, dynamic range, contrast response function, natural image statistics, mutual information, cats, macaque, ecological validity
- MeSH terms
- Animals, Haplorhini, Cats, Computer Simulation, Humans, Neurons, Visual Cortex, Contrast Sensitivity
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