Cited by 157Visual perception and processing mechanismsNeural dynamics and brain functionstochastic dynamics and bifurcation

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

How Noise Contributes to Contrast Invariance of Orientation Tuning in Cat Visual Cortex

Open access

Hansel, D., van Vreeswijk, C.·2002·The Journal of Neuroscience

DOI 10.1523/jneurosci.22-12-05118.2002PMC PMC6757721

Open this paper in CoChat — free account

Abstract

The width of the orientation tuning curves of the spike response of neurons in V1 is invariant to contrast. This property constrains the possible mechanisms underlying orientation selectivity. It has been suggested that noise circumvents the iceberg effect that would prevent contrast invariance in the purely feedforward mechanism. Here we investigate systematically how noise contributes to the contrast invariance of orientation tuning curves in V1. We study three models of increasing complexity: a simple threshold-linear firing rate model, a leaky integrate-and-fire model, and a conductance-based model. We show that the noise transmutes the threshold nonlinearity of the input-output relationships into an approximate power law without a threshold within some firing rate range. This implies that, under certain conditions which are derived here, the tuning of the neuron output is approximately contrast invariant. In particular we show that this mechanism for contrast invariance requires that the neuron firing rate must not be too large and that increasing or lowering the contrast too much destroys this invariance. We also show that if this mechanism operates in V1, the spike response, R, and average voltage response V of the neurons in V1 should vary with the contrast, C, according to R(C)gamma proportional to V(C)gamma. The exponent gamma can be estimated from the amount by which the spike tuning curve is sharpened with respect to the voltage tuning curves of the neurons. This prediction does not depend on the specifics of the model and can be tested experimentally.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1523/jneurosci.22-12-05118.2002

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

This paper’s reference list could not be split into single entries.

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
Normalization of cell responses in cat striate cortex
Heeger, D. J. (1992) · Visual Neuroscience · doi:10.1017/s0952523800009640 · Cited by 1,835
Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses
Arieli, A., Sterkin, A., Grinvald, A., & Aertsen, A. (1996) · Science · doi:10.1126/science.273.5283.1868 · Cited by 1,660
Introduction to Theoretical Neurobiology
Tuckwell, H. C. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511623202 · Cited by 1,174
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
Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex
Carandini, M., Heeger, D. J., & Movshon, J. A. (1997) · Journal of Neuroscience · doi:10.1523/jneurosci.17-21-08621.1997 · Cited by 926
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
Linking Spontaneous Activity of Single Cortical Neurons and the Underlying Functional Architecture
Tsodyks, M. V., Kenet, T., Grinvald, A., & Arieli, A. (1999) · Science · doi:10.1126/science.286.5446.1943 · Cited by 715
Visual input evokes transient and strong shunting inhibition in visual cortical neurons
Graham, L. J., Monier, C., & Frégnac, Y. (1998) · Nature · doi:10.1038/30735 · Cited by 669
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

Show all 28 references

Sorted by citations

A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input
Burkitt, A. N. (2006) · Biological Cybernetics · doi:10.1007/s00422-006-0068-6 · Cited by 1,214
Gain Modulation from Background Synaptic Input
Chance, F. S., Abbott, L. F., & Reyes, A. D. (2002) · Neuron · doi:10.1016/s0896-6273(02)00820-6 · Cited by 1,012
Shunting Inhibition Modulates Neuronal Gain during Synaptic Excitation
Mitchell, S. J., & Silver, R. A. (2003) · Neuron · doi:10.1016/s0896-6273(03)00200-9 · Cited by 602
How Spike Generation Mechanisms Determine the Neuronal Response to Fluctuating Inputs
Fourcaud‐Trocmé, N., Hansel, D., van Vreeswijk, C., & Brunel, N. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-37-11628.2003 · Cited by 603
Self-citation
Neuronal arithmetic
Silver, R. A. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2864 · Cited by 481
Inhibitory Stabilization of the Cortical Network Underlies Visual Surround Suppression
Ozeki, H., Finn, I. M., Schaffer, E., Miller, K. D., & Ferster, D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.028 · Cited by 470
Inhibition, Spike Threshold, and Stimulus Selectivity in Primary Visual Cortex
Priebe, N. J., & Ferster, D. (2008) · Neuron · doi:10.1016/j.neuron.2008.02.005 · Cited by 359
The Stabilized Supralinear Network: A Unifying Circuit Motif Underlying Multi-Input Integration in Sensory Cortex
Rubin, D. B., Hooser, S. D. V., & Miller, K. D. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.026 · Cited by 337
Mechanisms underlying gain modulation in the cortex
Ferguson, K. A., & Cardin, J. A. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0253-y · Cited by 327
Barrages of Synaptic Activity Control the Gain and Sensitivity of Cortical Neurons
Shu, Y., Hasenstaub, A., Badoual, M., Bal, T., & McCormick, D. A. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-32-10388.2003 · Cited by 298
The Emergence of Contrast-Invariant Orientation Tuning in Simple Cells of Cat Visual Cortex
Finn, I. M., Priebe, N. J., & Ferster, D. (2007) · Neuron · doi:10.1016/j.neuron.2007.02.029 · Cited by 248
Direction Selectivity of Excitation and Inhibition in Simple Cells of the Cat Primary Visual Cortex
Priebe, N. J., & Ferster, D. (2005) · Neuron · doi:10.1016/j.neuron.2004.12.024 · Cited by 250
On the Distribution of Firing Rates in Networks of Cortical Neurons
Roxin, A., Brunel, N., Hansel, D., Mongillo, G., & van Vreeswijk, C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1677-11.2011 · Cited by 252
Self-citation
Synaptic depression enables neuronal gain control
Rothman, J. S., Cathala, L., Steuber, V., & Silver, R. A. (2009) · Nature · doi:10.1038/nature07604 · Cited by 249
The mechanics of state-dependent neural correlations
Doiron, B., Litwin-Kumar, A., Rosenbaum, R., Ocker, G. K., & Josić́, K. (2016) · Nature Neuroscience · doi:10.1038/nn.4242 · Cited by 240
A Synaptic Explanation of Suppression in Visual Cortex
Carandini, M., Heeger, D. J., & Senn, W. (2002) · Journal of Neuroscience · doi:10.1523/jneurosci.22-22-10053.2002 · Cited by 219
The contribution of spike threshold to the dichotomy of cortical simple and complex cells
Priebe, N. J., Mechler, F., Carandini, M., & Ferster, D. (2004) · Nature Neuroscience · doi:10.1038/nn1310 · Cited by 217
Transition to Chaos in Random Neuronal Networks
Kadmon, J., & Sompolinsky, H. (2015) · Physical Review X · doi:10.1103/physrevx.5.041030 · Cited by 208
Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex
Carandini, M. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020264 · Cited by 210
Mechanisms of Neuronal Computation in Mammalian Visual Cortex
Priebe, N. J., & Ferster, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.011 · Cited by 209
Sensory stimulation shifts visual cortex from synchronous to asynchronous states
Tan, A. Y. Y., Chen, Y., Scholl, B., Seidemann, E., & Priebe, N. J. (2014) · Nature · doi:10.1038/nature13159 · Cited by 206
Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex
Cardin, J. A., Palmer, L. A., & Contreras, D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1692-07.2007 · Cited by 185
Mechanisms underlying cross-orientation suppression in cat visual cortex
Priebe, N. J., & Ferster, D. (2006) · Nature Neuroscience · doi:10.1038/nn1660 · Cited by 184
The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability
Hennequin, G., Ahmadian, Y., Rubin, D. B., Lengyel, M., & Miller, K. D. (2018) · Neuron · doi:10.1016/j.neuron.2018.04.017 · Cited by 172
Inhibitory synchrony as a mechanism for attentional gain modulation
Tiesinga, P. H. E., Fellous, J., Salinas, E., José, J. V., & B, T. J. S. A. (2004) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2005.09.002 · Cited by 161
The Mechanism of Orientation Selectivity in Primary Visual Cortex without a Functional Map
Hansel, D., & van Vreeswijk, C. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.6284-11.2012 · Cited by 147
Self-citation
Multiplicative Gain Changes Are Induced by Excitation or Inhibition Alone
Murphy, B. K., & Miller, K. D. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-31-10040.2003 · Cited by 144
Analysis of the Stabilized Supralinear Network
Ahmadian, Y., Rubin, D. B., & Miller, K. D. (2013) · Neural Computation · doi:10.1162/neco_a_00472 · Cited by 142
Inhibitory stabilization and visual coding in cortical circuits with multiple interneuron subtypes
Litwin-Kumar, A., Rosenbaum, R., & Doiron, B. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00732.2015 · Cited by 146
What is the dynamical regime of cerebral cortex?
Ahmadian, Y., & Miller, K. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.07.031 · Cited by 146
Canonical computations of cerebral cortex
Miller, K. D. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.01.008 · Cited by 136
Mechanisms of Orientation Selectivity in the Primary Visual Cortex
Priebe, N. J. (2016) · Annual Review of Vision Science · doi:10.1146/annurev-vision-111815-114456 · Cited by 134
Attentional modulation of firing rate and synchrony in a model cortical network
Buia, C., & Tiesinga, P. H. E. (2006) · Journal of Computational Neuroscience · doi:10.1007/s10827-006-6358-0 · Cited by 114
An Integrated Microcircuit Model of Attentional Processing in the Neocortex
Ardid, S., Wang, X., & Compte, A. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1145-07.2007 · Cited by 105
Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network
Mongillo, G., Amit, D. J., & Brunel, N. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02908.x · Cited by 100
Asynchronous Rate Chaos in Spiking Neuronal Circuits
Harish, O., & Hansel, D. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004266 · Cited by 101
Self-citation
Lack of Orientation and Direction Selectivity in a Subgroup of Fast-Spiking Inhibitory Interneurons: Cellular and Synaptic Mechanisms and Comparison with Other Electrophysiological Cell Types
Nowak, L. G., Sanchez-Vives, M. V., & McCormick, D. A. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm137 · Cited by 96
Cellular Mechanisms Underlying Stimulus-Dependent Gain Modulation in Primary Visual Cortex Neurons In Vivo
Cardin, J. A., Palmer, L. A., & Contreras, D. (2008) · Neuron · doi:10.1016/j.neuron.2008.05.002 · Cited by 90
Dynamics and Plasticity of Stimulus-selective Persistent Activity in Cortical Network Models
Brunel, N. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg096 · Cited by 85
Multiplication and stimulus invariance in a looming-sensitive neuron
Gabbiani, F., Krapp, H. G., Hatsopoulos, N. G., Mo, C., Christof Koch, A., & Laurent, G. (2004) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2004.03.001 · Cited by 83
A human-specific modifier of cortical connectivity and circuit function
Schmidt, E. R. E., Zhao, H. T., Park, J. M., Dipoppa, M., Monsalve-Mercado, M. M., Dahan, J. B., Rodgers, C. C., Lejeune, A., Hillman, E. M. C., Miller, K. D., et al. (2021) · Nature · doi:10.1038/s41586-021-04039-4 · Cited by 82
The Role of Degree Distribution in Shaping the Dynamics in Networks of Sparsely Connected Spiking Neurons
Roxin, A. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00008 · Cited by 79
Lognormal firing rate distribution reveals prominent fluctuation–driven regime in spinal motor networks
Petersen, P. C., & Berg, R. W. (2016) · eLife · doi:10.7554/elife.18805 · Cited by 76
Understanding Layer 4 of the Cortical Circuit: A Model Based on Cat V1
Miller, K. D. (2002) · Cerebral Cortex · doi:10.1093/cercor/13.1.73 · Cited by 75
Lyapunov spectra of chaotic recurrent neural networks
Engelken, R., Wolf, F., & Abbott, L. F. (2023) · Physical Review Research · doi:10.1103/physrevresearch.5.043044 · Cited by 102
Synchronous Chaos and Broad Band Gamma Rhythm in a Minimal Multi-Layer Model of Primary Visual Cortex
Battaglia, D. A., & Hansel, D. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002176 · Cited by 57
Self-citation
The Operating Point of the Cortex: Neurons as Large Deviation Detectors
Ringach, D. L., & Malone, B. J. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1048-07.2007 · Cited by 55
Mathematical Equivalence of Two Common Forms of Firing Rate Models of Neural Networks
Miller, K. D., & Fumarola, F. (2011) · Neural Computation · doi:10.1162/neco_a_00221 · Cited by 55
Calcium imaging with genetically encoded indicators in behaving primates
Seidemann, E., Chen, Y., Bai, Y., Chen, S. C., Mehta, P., Kajs, B. L., Geisler, W. S., & Zemelman, B. V. (2016) · eLife · doi:10.7554/elife.16178 · Cited by 54
Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process
Jahn, P., Berg, R. W., Hounsgaard, J., & Ditlevsen, S. (2011) · Journal of Computational Neuroscience · doi:10.1007/s10827-011-0326-z · Cited by 53
A Biologically Realistic Model of Contrast Invariant Orientation Tuning by Thalamocortical Synaptic Depression
Banitt, Y., Martin, K. A. C., & Segev, I. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1640-07.2007 · Cited by 52
Untuned Suppression Makes a Major Contribution to the Enhancement of Orientation Selectivity in Macaque V1
Xing, D., Ringach, D. L., Hawken, M. J., & Shapley, R. M. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.2245-11.2011 · Cited by 48
Membrane Voltage Fluctuations Reduce Spike Frequency Adaptation and Preserve Output Gain in CA1 Pyramidal Neurons in a High-Conductance State
Fernandez, F. R., Broicher, T., Truong, A., & White, J. A. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5076-10.2011 · Cited by 44
How effective delays shape oscillatory dynamics in neuronal networks
Roxin, A., & Montbrió, E. (2010) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2010.09.009 · Cited by 44
Strabismus Disrupts Binocular Synaptic Integration in Primary Visual Cortex
Scholl, B., Tan, A. Y. Y., & Priebe, N. J. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1831-13.2013 · Cited by 46
Adaptive Integration in the Visual Cortex by Depressing Recurrent Cortical Circuits
van Rossum, M. C. W., van der Meer, M. A. A., Xiao, D., & Oram, M. W. (2008) · Neural Computation · doi:10.1162/neco.2008.06-07-546 · Cited by 47
Intracellular Responses of Neurons in the Mouse Inferior Colliculus to Sinusoidal Amplitude-Modulated Tones
Geis, H.-R. A. P., & Borst, J. G. G. (2009) · Journal of Neurophysiology · doi:10.1152/jn.90966.2008 · Cited by 43
SeCNN: A semantic CNN parser for code comment generation
Li, Z., Wu, Y., Peng, B., Chen, X., Sun, Z., Liu, Y., & Yu, D. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.111036 · Cited by 45
Feedback-induced gain control in stochastic spiking networks
Sutherland, C., Doiron, B., & Longtin, A. (2009) · Biological Cybernetics · doi:10.1007/s00422-009-0298-5 · Cited by 42
Orientation selectivity in visual cortex by fluctuation-controlled criticality
Tao, L., Cai, D., McLaughlin, D. W., Shelley, M., & Shapley, R. M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605415103 · Cited by 41
Power-Law Input-Output Transfer Functions Explain the Contrast-Response and Tuning Properties of Neurons in Visual Cortex
Persi, E., Hansel, D., Nowak, L. G., Barone, P., & van Vreeswijk, C. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001078 · Cited by 41
Self-citation
Cellular and Circuit Mechanisms Maintain Low Spike Co-Variability and Enhance Population Coding in Somatosensory Cortex
Ly, C., Middleton, J. W., & Doiron, B. (2012) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2012.00007 · Cited by 37
Computational Diversity in Complex Cells of Cat Primary Visual Cortex
Finn, I. M., & Ferster, D. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2119-07.2007 · Cited by 37
Cross-Correlation in the Auditory Coincidence Detectors of Owls
Fischer, B. J., Christianson, G. B., & Peña, J. L. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1969-08.2008 · Cited by 35
How to Modify a Neural Network Gradually Without Changing Its Input-Output Functionality
DiMattina, C., & Zhang, K. (2009) · Neural Computation · doi:10.1162/neco.2009.05-08-781 · Cited by 31
Learning shapes cortical dynamics to enhance integration of relevant sensory input
Chadwick, A., Khan, A. G., Poort, J., Blot, A., Hofer, S. B., Mrsic‐Flogel, T. D., & Sahani, M. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.001 · Cited by 35
Spectrotemporal Processing in Spectral Tuning Modules of Cat Primary Auditory Cortex
Atencio, C. A., & Schreiner, C. E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031537 · Cited by 31
Divisive Gain Modulation of Motoneurons by Inhibition Optimizes Muscular Control
Vestergaard, M., & Berg, R. W. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.3899-14.2015 · Cited by 31
Stabilized supralinear network can give rise to bistable, oscillatory, and persistent activity
Kraynyukova, N., & Tchumatchenko, T. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700080115 · Cited by 29
Statistical physics approach to dendritic computation: The excitable-wave mean-field approximation
Gollo, L. L., Kinouchi, O., & Copelli, M. (2012) · Physical Review E · doi:10.1103/physreve.85.011911 · Cited by 27
Contrast Adaptation Contributes to Contrast-Invariance of Orientation Tuning of Primate V1 Cells
Nowak, L. G., & Barone, P. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004781 · Cited by 27
DIRECT CONTROL OF FIRING RATE GAIN BY DENDRITIC SHUNTING INHIBITION
Capaday, C., & van Vreeswijk, C. (2006) · Journal of Integrative Neuroscience · doi:10.1142/s021963520600115x · Cited by 26
Population codes enable learning from few examples by shaping inductive bias
Bordelon, B., & Pehlevan, C. (2022) · eLife · doi:10.7554/elife.78606 · Cited by 26
Learning Contrast-Invariant Cancellation of Redundant Signals in Neural Systems
Mejías, J. F., Marsat, G., Bol, K., Maler, L., & Longtin, A. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003180 · Cited by 25
Cellular-resolution optogenetics reveals attenuation-by-suppression in visual cortical neurons
LaFosse, P. K., Zhou, Z., O’Rawe, J. F., Friedman, N. G., Scott, V., Deng, Y., & Histed, M. H. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2318837121 · Cited by 33
Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model
Wagatsuma, N., Potjans, T. C., Diesmann, M., Sakai, K., & Fukai, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080788 · Cited by 28
FACED 2.0 enables large-scale voltage and calcium imaging in vivo
Zhong, J., Natan, R. G., Zhang, Q., Wong, J. S. J., Miehl, C., Bose, K., Lu, X., St-Pierre, F., Guo, S., Doiron, B., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02925-7 · Cited by 29
Voltage-Gated Intrinsic Conductances Shape the Input-Output Relationship of Cortical Neurons in Behaving Primate V1
Li, B., Routh, B. N., Johnston, D., Seidemann, E., & Priebe, N. J. (2020) · Neuron · doi:10.1016/j.neuron.2020.04.001 · Cited by 29
Mechanisms underlying reshuffling of visual responses by optogenetic stimulation in mice and monkeys
Sanzeni, A., Palmigiano, A., Nguyen, T. H., Luo, J., Nassi, J. J., Reynolds, J. H., Histed, M. H., Miller, K. D., & Brunel, N. (2023) · Neuron · doi:10.1016/j.neuron.2023.09.018 · Cited by 24
Chaotic dynamics in spatially distributed neuronal networks generate population-wide shared variability
Mosheiff, N., Ermentrout, B., & Huang, C. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010843 · Cited by 24
The Relationship between Subthreshold and Suprathreshold Ocular Dominance in Cat Primary Visual Cortex
Priebe, N. J. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.2182-08.2008 · Cited by 22
Chaos-induced modulation of reliability boosts output firing rate in downstream cortical areas
Tiesinga, P. H. E. (2004) · Physical Review E · doi:10.1103/physreve.69.031912 · Cited by 22
Stimulus‐selective spiking is driven by the relative timing of synchronous excitation and disinhibition in cat striate neurons in vivo
Azouz, R., & Gray, C. M. (2008) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2008.06434.x · Cited by 21
Contrast gain control occurs independently of both parvalbumin-positive interneuron activity and shunting inhibition in auditory cortex
Cooke, J. E., Kahn, M. C., Mann, E. O., King, A. J., Schnupp, J. W. H., & Willmore, B. D. B. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00587.2019 · Cited by 22
Course 9 Irregular activity in large networks of neurons
van Vreeswijk, C., & Sompolinsky, H. (2005) · Les Houches/Les Houches · doi:10.1016/s0924-8099(05)80015-0 · Cited by 25
Small changes in synaptic gain lead to seizure-like activity in neuronal network at criticality
Du, J., Vegh, V., & Reutens, D. C. (2019) · Scientific Reports · doi:10.1038/s41598-018-37646-9 · Cited by 18
Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons: Effect of Single Neuron Properties and Network Dynamics
Sadeh, S., & Rotter, S. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004045 · Cited by 18
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks
Podlaski, W. F., & Machens, C. K. (2024) · Neural Computation · doi:10.1162/neco_a_01658 · Cited by 19
Effects of Inhibitory Gain and Conductance Fluctuations in a Simple Model for Contrast-Invariant Orientation Tuning in Cat V1
Palmer, S. E., & Miller, K. D. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00152.2007 · Cited by 17
A model for the origin and development of visual orientation selectivity
Nguyen, G., & Freeman, A. W. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007254 · Cited by 16
Oscillations in the bistable regime of neuronal networks
Roxin, A., & Compte, A. (2016) · Physical review. E · doi:10.1103/physreve.94.012410 · Cited by 16
Antagonistic inhibitory subnetworks control cooperation and competition across cortical spacePreprint
Mossing, D. P., Veit, J., Palmigiano, A., Miller, K. D., & Adesnik, H. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.31.437953 · Cited by 16
Non-linear Membrane Properties in Entorhinal Cortical Stellate Cells Reduce Modulation of Input-Output Responses by Voltage Fluctuations
Fernandez, F. R., Malerba, P., & White, J. A. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004188 · Cited by 15
Neuronal Population Activity in Spinal Motor Circuits: Greater Than the Sum of Its Parts
Berg, R. W. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00103 · Cited by 17
How to incorporate biological insights into network models and why it matters
Timón, L. B., Ekelmans, P., Kraynyukova, N., Rose, T., Busse, L., & Tchumatchenko, T. (2022) · The Journal of Physiology · doi:10.1113/jp282755 · Cited by 17
The invariance of directional tuning with contrast and coherence
Fine, I., Anderson, C. M., Boynton, G. M., & Dobkins, K. R. (2004) · Vision Research · doi:10.1016/j.visres.2003.11.022 · Cited by 15
Dendritic Pooling of Noisy Threshold Processes Can Explain Many Properties of a Collision-Sensitive Visual Neuron
Keil, M. S. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004479 · Cited by 14
Logarithmically scaled, gamma distributed neuronal spiking
Levenstein, D., & Okun, M. (2022) · The Journal of Physiology · doi:10.1113/jp282758 · Cited by 13
Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons
Sadeh, S., Cardanobile, S., & Rotter, S. (2014) · SpringerPlus · doi:10.1186/2193-1801-3-148 · Cited by 14
Functional congruity in local auditory cortical microcircuits
Atencio, C. A., & Schreiner, C. E. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2015.12.057 · Cited by 14

Authors: Hansel, D., & van Vreeswijk, C.
Affiliations: Centre National de la Recherche Scientifique (FR)
ORCID: Hansel, D.
Venue: The Journal of Neuroscience
Publisher: Society for Neuroscience
Published: 2002-06-15
Volume: 22
Issue: 12
Pages: 5118-5128
ISSN: 0270-6474 (ISSN-L)
1529-2401
DOI: 10.1523/jneurosci.22-12-05118.2002
PMC: PMC6757721
OpenAlex: W2170697082
Cited by: 157
References: 28
Citations by year: 2026: 3 · 2025: 10 · 2024: 5 · 2023: 5 · 2022: 9 · 2021: 9 · 2020: 4 · 2019: 3 · 2018: 4 · 2017: 4 · 2016: 11 · 2015: 9 · 2014: 4 · 2013: 7 · 2012: 10
FWCI: 3.51
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Journal of Neuroscience (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
HAL (submittedVersion)
Funders: National Science Foundation (9907949)
Centre National de la Recherche Scientifique
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
Keywords: contrast invariance, orientation tuning, primary visual cortex, neural noise, orientation selectivity, leaky integrate-and-fire model, conductance-based models, threshold nonlinearity, power-law response, spike responses, voltage response, cat visual cortex
MeSH terms: Animals, Cats, Electric Conductivity, Kinetics, Membrane Potentials, Models, Neurological, Models, Theoretical, Synaptic Transmission, Neurons, Visual Cortex

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

How Noise Contributes to Contrast Invariance of Orientation Tuning in Cat Visual Cortex

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks