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.
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“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
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Lucena, F. (2012) · Institutional Repositories DataBase (IRDB)
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0016
Takahashi, T., & Ogishima, H. (2021) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/8efxv
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0012
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0018
Information Processing Analysis in Neural Networks
Zhang, C. (2019) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-7498
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0001
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Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0017
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Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0005
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Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0011
Modelling Instantaneous Firing Rate of DBS Target Neuronal Ensembles in Basal Ganglia and ThalamusPreprint
Tian, Y., Murphy, M. J. H., Steiner, L. A., Kalia, S. K., Hodaie, M., Lozano, A. M., Hutchison, W. D., Popović, M. R., Milosevic, L., & Lankarany, M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.28.497834
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0003
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0006
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0009
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0004
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0007
(2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.002.0005
Angelucci, A., Vafaei, A., Clark, A., Khadir, A., Dai, W., & Federer, F. (2025) · Research Square · doi:10.64898/2025.12.23.696300 · Cited by 2
Uncovering the “hidden” synaptic microarchitecture of the retinal direction selective circuit
deRosenroll, G., Sethuramanujam, S., & Awatramani, G. B. (2026) · Cell Reports · doi:10.1016/j.celrep.2025.116833
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
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