The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
The Contribution of Noise to Contrast Invariance of Orientation Tuning in Cat Visual Cortex
Abstract
Feedforward models of visual cortex appear to be inconsistent with a well-known property of cortical cells: contrast invariance of orientation tuning. The models' fixed threshold broadens orientation tuning as contrast increases, whereas in real cells tuning width is invariant with contrast. We have compared the orientation tuning of spike and membrane potential responses in single cells. Both are contrast invariant, yet a threshold-linear relation applied to the membrane potential accurately predicts the orientation tuning of spike responses. The key to this apparent paradox lies in the noisiness of the membrane potential. Responses that are subthreshold on average are still capable of generating spikes on individual trials. Unlike the iceberg effect, contrast invariance remains intact even as threshold narrows orientation selectivity. Noise may, by extension, smooth the average relation between membrane potential and spike rate throughout the brain.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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
“Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration1–3,7,8,13–17.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [13]
In the citing paper
“These fluctuations may contribute to contrast-invariant tuning in neurons of the visual cortex of cats and rodents10,13,63,64.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [13]
In the citing paper
“Synaptically driven fluctuations in the Vm smooth the transformation from Vm depolarization to spike output, creating a power-law relationship between the mean Vm and the mean firing rate13,63.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [13]
In the citing paper
“Similarly, background synaptic noise that is uncorrelated with ongoing visual stimulation contributes to maintaining stable orientation tuning in visual cortex neurons across varying levels of visual contrast13.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [13]
Citations
Cites
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 19,308
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
The VideoToolbox software for visual psychophysics: transforming numbers into movies
Pelli, D. G. (1997) · Spatial Vision · doi:10.1163/156856897x00366 · Cited by 11,110
Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs
Wiesenfeld, K., & Moss, F. (1995) · Nature · doi:10.1038/373033a0 · Cited by 1,830
Theory of orientation tuning in visual cortex.
Ben-Yishai, R., Bar‐Or, R. L., & Sompolinsky, H. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.9.3844 · Cited by 1,091
An emergent model of orientation selectivity in cat visual cortical simple cells
Somers, D., Nelson, S., & Sur, M. (1995) · The Journal of Neuroscience · doi:10.1523/jneurosci.15-08-05448.1995 · Cited by 860
Dynamics of Encoding in a Population of Neurons
Knight, B. W. (1972) · The Journal of General Physiology · doi:10.1085/jgp.59.6.734 · Cited by 720
Neural Mechanisms of Orientation Selectivity in the Visual Cortex
Ferster, D., & Miller, K. D. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.441 · Cited by 665
Self-citationPrecisely correlated firing in cells of the lateral geniculate nucleus
Alonso, J., Usrey, W. M., & Reid, R. C. (1996) · Nature · doi:10.1038/383815a0 · Cited by 514
Synchronous Membrane Potential Fluctuations in Neurons of the Cat Visual Cortex
Lampl, I., Reichova, I., & Ferster, D. (1999) · Neuron · doi:10.1016/s0896-6273(00)81096-x · Cited by 435
Self-citation
Cited by
Sorted by citations
Faisal, A. A., Selen, L. P. J., & Wolpert, D. M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2258 · Cited by 2,883
Bayesian inference with probabilistic population codes
Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A. (2006) · Nature Neuroscience · doi:10.1038/nn1790 · Cited by 1,457
The Normalization Model of Attention
Reynolds, J. H., & Heeger, D. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.002 · Cited by 1,457
Turning on and off recurrent balanced cortical activity
Shu, Y., Hasenstaub, A., & McCormick, D. A. (2003) · Nature · doi:10.1038/nature01616 · Cited by 1,054
Stochastic resonance and sensory information processing: A tutorial and review of application
Moss, F., Ward, L. M., & Sannita, W. G. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2003.09.014 · Cited by 994
Metadata
- Authors
- Anderson, J. S., Lampl, I., Gillespie, D. C., & Ferster, D.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Ferster, David
- Venue
- Science
- Published
- 2000-12-08
- Volume
- 290
- Issue
- 5498
- Pages
- 1968-1972
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2028546686
- Cited by
- 422
- References
- 23
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 10 · 2023: 7 · 2022: 7 · 2021: 10 · 2020: 16 · 2019: 10 · 2018: 10 · 2017: 11 · 2016: 9 · 2015: 13 · 2014: 18 · 2013: 20 · 2012: 19
- FWCI
- 10.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Eye Institute (R01 EY-04726, R01EY004726)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- contrast invariance, orientation tuning, visual cortex, noise, membrane potential, spike responses, feedforward models, cats, orientation selectivity, subthreshold responses
- MeSH terms
- Action Potentials, Animals, Cats, Membrane Potentials, Microelectrodes, Models, Neurological, Nerve Net, Neurons, Orientation, Photic Stimulation, Visual Cortex, Visual Perception, Contrast Sensitivity, Patch-Clamp Techniques
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