The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Summation and Division by Neurons in Primate Visual Cortex
Abstract
Recordings from monkey primary visual cortex (V1) were used to test a model for the visually driven responses of simple cells. According to the model, simple cells compute a linear sum of the responses of lateral geniculate nucleus (LGN) neurons. In addition, each simple cell's linear response is divided by the pooled activity of a large number of other simple cells. The cell membrane performs both operations; synaptic currents are summed and then divided by the total membrane conductance. Current and conductance are decoupled (by a complementary arrangement of excitation and inhibition) so that current depends only on the LGN inputs and conductance depends only on the cortical inputs. Closed form expressions were derived for fitting and interpreting physiological data. The model accurately predicted responses to drifting grating stimuli of various contrasts, orientations, and spatiotemporal frequencies.
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
“In turn, this dynamic range can be adjusted through gain control that is mediated by the overall level of synaptic inhibition4,59,68,69.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [4]
Citations
Cites
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
Self-citationNonlinear neural networks: Principles, mechanisms, and architectures
Grossberg, S. (1988) · Neural Networks · doi:10.1016/0893-6080(88)90021-4 · Cited by 1,635
Striate cortex of monkey and cat: contrast response function.
Albrecht, D. G., & Hamilton, D. B. (1982) · Journal of Neurophysiology · doi:10.1152/jn.1982.48.1.217 · Cited by 953
Spatial summation in the receptive fields of simple cells in the cat's striate cortex.
Movshon, J. A., Thompson, I. D., & Tolhurst, D. J. (1978) · The Journal of Physiology · doi:10.1113/jphysiol.1978.sp012488 · Cited by 890
Synaptic background activity influences spatiotemporal integration in single pyramidal cells.
Bernander, Ö., Douglas, R. J., Martin, K. A. C., & Koch, C. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.24.11569 · Cited by 518
Bonds, A. B. (1989) · Visual Neuroscience · doi:10.1017/s0952523800004314 · Cited by 477
Motion selectivity and the contrast-response function of simple cells in the visual cortex
Albrecht, D. G., & Geisler, W. S. (1991) · Visual Neuroscience · doi:10.1017/s0952523800010336 · Cited by 433
The spatial selectivity of the visual cells of the cat
Campbell, F. W., Cooper, G. F., & Enroth‐Cugell, C. (1969) · The Journal of Physiology · doi:10.1113/jphysiol.1969.sp008861 · Cited by 392
Visual Sensitivity And Parallel Retinocortical Channels
Shapley, R. M. (1990) · Annual Review of Psychology · doi:10.1146/annurev.ps.41.020190.003223 · Cited by 321
Flagged first, then by citations
Research works printed but not linked: 2
- GROSSBERG, S, NEURAL NETWORKS 1: 17 (1988).
- Koch, C., Synaptic Function: 637 (1987).
Cited by
Sorted by citations
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733
“…a given broad feature dimension, however, strong local interactions between filters sensitive to different properties of that feature (for example, between different orientations within the broad orientation feature) have been precisely characterized, both in physiology 60 and psy-chophysics 45 .”
BackgroundLinear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1
Boynton, G., Engel, S., Glover, G., & Heeger, D. (1996) · Journal of Neuroscience · doi:10.1523/jneurosci.16-13-04207.1996 · Cited by 2,522
“Although the transformation from stimulus to neural activity is not known exactly, reasonable quantitative models do exist, especially for V1 (Heeger, 1992, 1993; Carandini and Heeger, 1994).”
BackgroundSelf-citationNormalization as a canonical neural computation
Carandini, M., & Heeger, D. J. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3136 · Cited by 1,906
“Indeed, the normalization model was first developed to account for the physiological responses of neurons in the primary visual cortex (V1”
MethodSelf-citationSensitive periods in the development of the brain and behavior
Knudsen, E. I. (2004) · Journal of Cognitive Neuroscience · doi:10.1162/0898929042304796 · Cited by 1,842
“Inhibitory networks become powerful and organized so that they suppress alternative patterns of excitation (Galarreta & Hestrin, 2001; Zheng & Knudsen, 2001; Hensch et al., 1998; Carandini & Heeger, 1994).”
BackgroundHow Inhibition Shapes Cortical Activity
Isaacson, J. S., & Scanziani, M. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.027 · Cited by 1,678
“…visual cortex offer a classical example of gain modulation, where two independent properties of a visual stimulus, contrast, and orientation, interact in a multiplicative manner in generating spike output (Anderson et al., 2000; Carandini and Heeger, 1994; Miller, 2003; Sclar and Freeman, 1982).”
Freeman, W. T., Pasztor, E. C., & Carmichael, O. T. (2000) · International Journal of Computer Vision · doi:10.1023/a:1026501619075 · Cited by 1,505
“This saves having to replicate the training set over all possible values of image contrast, and is a very simpli ed model of the contrast normalization which may take place in the mammalian visual system (Carandini and Heeger, 1994).”
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
“…in the early 1990s to explain a variety of such suppressive phenomena evident in the response properties of V1 neurons (Albrecht and Geisler, 1991; Carandini and Heeger, 1994; Carandini et al., 1997; Heeger, 1991, 1992a, 1992b, 1993; Nestares and Heeger, 1997; Robson, 1988; Tolhurst and Heeger,…”
BackgroundInfluentialSelf-citationModeling the role of salience in the allocation of overt visual attention
Parkhurst, D. J., Law, K., & Niebur, E. (2002) · Vision Research · doi:10.1016/s0042-6989(01)00250-4 · Cited by 1,435
“The normalization scales the activations of a map to the squared difference between its global maximum and the average of the remaining (local) maxima in the map (such a normalization has been used successfully to explain single-cell behavior in primary visual cortex; Carandini & Heeger, 1994).”
MethodEffects of Attention on Orientation-Tuning Functions of Single Neurons in Macaque Cortical Area V4
McAdams, C. J., & Maunsell, J. H. R. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-01-00431.1999 · Cited by 1,218
“Although mechanisms that would produce multiplicative scaling have been described (Albrecht and Geisler, 1991; Carandini and Heeger, 1994), it is not known why such separability of response sensitivities may be important for cortical processing.”
BackgroundTurning on and off recurrent balanced cortical activity
Shu, Y., Hasenstaub, A., & McCormick, D. A. (2003) · Nature · doi:10.1038/nature01616 · Cited by 1,054
Recurrent Excitation in Neocortical Circuits
Douglas, R. J., Christof Koch, A., Mahowald, M. A., Martin, K. A. C., & Suarez, H. H. (1995) · Science · doi:10.1126/science.7638624 · Cited by 985
Attentional modulation of visual processing
Reynolds, J. H., & Chelazzi, L. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131039 · Cited by 1,158
“…neurophysiology, and they have driven the development of increasingly detailed models of the underlying cortical circuit (Albrecht & Geisler 1991, Carandini & Heeger 1994, Carandini et al. 1997, Grossberg 1973, Heeger 1992, McLaughlin et al. 2000, Murphy & Miller 2003, Somers et al. 1995,…”
BackgroundMethodLinearity 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
“One is response saturation (Maffei and Fiorentini, 1973; Dean, 1981a; Albrecht and Hamilton, 1982; Ohzawa et al., 1982; Li and Creutzfeldt, 1984; Sclar et al., 1990; Bonds, 1991; Carandini and Heeger, 1994).”
BackgroundMethodInfluentialSelf-citationAn 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
Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory
Wang, X.-J. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-21-09587.1999 · Cited by 859
“Instead, it causes an increase in membrane conductance, which divides the excitatory synaptic current (Carandini and Heeger, 1994).”
BackgroundA model of neuronal responses in visual area MT
Simoncelli, E. P., & Heeger, D. J. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00183-1 · Cited by 941
“Many of these behaviors can be accounted for by incorporating response normalization (Robson, 1988; Bonds, 1989; Albrecht and Geisler, 1991; Heeger 1991, 1992a,b, 1993; DeAngelis et al., 1992; Carandini and Heeger, 1994; Carandini et al., 1997; Tolhurst and Heeger, 1997a,b; Nestares and Heeger, 1997).”
Self-citationNeural 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
“This shunt would lower the membrane time constant of the cell, thereby lowering its integration time, with the resulting effect of advancing the phase of responses to sinusoidal gratings and enhancing responses to higher temporal frequencies (Carandini & Heeger 1994, Carandini et al 1997).”
BackgroundVisual 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
Adaptive Rescaling Maximizes Information Transmission
Brenner, N., Bialek, W., & van Steveninck, R. R. D. R. (2000) · Neuron · doi:10.1016/s0896-6273(00)81205-2 · Cited by 650
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
Contrast's effect on spatial summation by macaque V1 neurons
Sceniak, M. P., Ringach, D. L., Hawken, M. J., & Shapley, R. M. (1999) · Nature Neuroscience · doi:10.1038/11197 · Cited by 608
“The effect of contrast on cortical receptive-field size is also relevant to our understanding of cortical contrast gain contro”
BackgroundDo We Know What the Early Visual System Does?
Carandini, M., Demb, J. B., Mante, V., Tolhurst, D. J., Dan, Y., Olshausen, B. A., Gallant, J. L., & Rust, N. C. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.3726-05.2005 · Cited by 604
“Elaborations of the contrast-normalization model (Carandini and Heeger, 1994; Carandini et al., 1997) have embraced additional nonlinear behaviors (previously unaccounted), such as “phase advance” at high contrasts (Dean and Tolhurst, 1986).”
BackgroundSelf-citationDivision and subtraction by distinct cortical inhibitory networks in vivo
Wilson, N. R., Runyan, C. A., Wang, F. L., & Sur, M. (2012) · Nature · doi:10.1038/nature11347 · Cited by 568
Motor Functions of the Superior Colliculus
Gandhi, N. J., & Katnani, H. A. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113728 · Cited by 490
“Although network architectures that can accomplish normalization have been proposed (Carandini & Heeger 1994, Groh 2001), there is still no substantial anatomical evidence in the oculomotor system to support this structure.”
BackgroundDivisive Normalization in Olfactory Population Codes
Olsen, S. R., Bhandawat, V., & Wilson, R. I. (2010) · Neuron · doi:10.1016/j.neuron.2010.04.009 · Cited by 500
“Generally an exponent >1 is required to fit the data (Albrecht and Hamilton, 1982; Heeger, 1992; Carandini and Heeger, 1994; Reynolds and Heeger, 2009), although the mechanisms underlying this are uncertain.”
BackgroundOrientation Tuning of Input Conductance, Excitation, and Inhibition in Cat Primary Visual Cortex
Anderson, J. S., Carandini, M., & Ferster, D. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.2.909 · Cited by 510
Self-citationSilver, R. A. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2864 · Cited by 481
Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion
Mital, P. K., Smith, T. J., Hill, R. L., & Henderson, J. M. (2010) · Cognitive Computation · doi:10.1007/s12559-010-9074-z · Cited by 460
“Such normalization of feature values is supported by neurobiological evidence of the non-linear single-cell behavior in the primary visual cortex [70].”
MethodAttention activates winner-take-all competition among visual filters
Lee, D. K., Itti, L., Koch, C., & Braun, J. (1999) · Nature Neuroscience · doi:10.1038/7286 · Cited by 465
“, specifically, the normalization of individual filter responses relative to the total response of the local filter population ('divisive inhibition”
BackgroundTroyer, T. W., Krukowski, A. E., Priebe, N. J., & Miller, K. D. (1998) · Journal of Neuroscience · doi:10.1523/jneurosci.18-15-05908.1998 · Cited by 429
“Copyright © 1998 Society for Neuroscience 0270-6474/98/185908-20$05.00/0 Geisler, 1991; Heeger, 1992; Carandini and Heeger, 1994; Carandini et al., 1997, 1998).”
BackgroundInfluentialEye movements and perception: A selective review
Schütz, A. C., Braun, D. I., & Gegenfurtner, K. R. (2011) · Journal of Vision · doi:10.1167/11.5.9 · Cited by 429
“The main assumption of the computation of local feature contrast has found empirical support from V1 physiology (reviewed in Carandini et al., 2005) and computational support in models of V1 (Carandini & Heeger, 1994; Carandini, Heeger, & Movshon, 1997).”
MethodSynaptic Depression and the Temporal Response Characteristics of V1 Cells
Chance, F. S., Nelson, S. B., & Abbott, L. F. (1998) · Journal of Neuroscience · doi:10.1523/jneurosci.18-12-04785.1998 · Cited by 403
“discussed by Heeger (1992) and Carandini and Heeger (1994).”
BackgroundNeuronal basis of contrast discrimination
Boynton, G. M., Demb, J. B., Glover, G. H., & Heeger, D. J. (1999) · Vision Research · doi:10.1016/s0042-6989(98)00113-8 · Cited by 391
“The particular form of the contrast‐response function (Eq. (1)) was chosen because it has been used successfully both to fit psychophysical TvC data (Foley, 1994; Foley & Boynton, 1994; Teo & Heeger, 1994, 1995) and to fit electrophysiological contrast‐response data (Bonds, 1989; Albrecht & Geisler, 1991; Heeger, 1991…”
MethodSelf-citationReading population codes: a neural implementation of ideal observers
Denève, S., Latham, P. E., & Pouget, A. (1999) · Nature Neuroscience · doi:10.1038/11205 · Cited by 397
Devor, A., Tian, P., Nishimura, N., Teng, I. C., Hillman, E. M. C., Narayanan, S. N., Ulbert, I., Boas, D. A., Kleinfeld, D., & Dale, A. M. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.0134-07.2007 · Cited by 393
“, 1982), it serves as a low bound because the contribution of “shunting” inhibition does not cause appreciable hyperpolarization (Carandini and Heeger, 1994).”
BackgroundGeneralization in vision and motor control
Poggio, T., & Bizzi, E. (2004) · Nature · doi:10.1038/nature03014 · Cited by 392
Buzsáki, G. (2019) · doi:10.1093/oso/9780190905385.001.0001 · Cited by 383
Effects of Spatial Attention on Contrast Response Functions in Macaque Area V4
Williford, T., & Maunsell, J. H. R. (2006) · Journal of Neurophysiology · doi:10.1152/jn.01207.2005 · Cited by 353
Freeman, W. T., & Pasztor, E. C. (1999) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1999.790414 · Cited by 351
Neural encoding of binocular disparity: Energy models, position shifts and phase shifts
Fleet, D. J., Wagner, H., & Heeger, D. J. (1996) · Vision Research · doi:10.1016/0042-6989(95)00313-4 · Cited by 343
Self-citationSynaptic Integration in Striate Cortical Simple Cells
Hirsch, J. A., Alonso, J., Reid, R. C., & Martı́nez, L. M. (1998) · Journal of Neuroscience · doi:10.1523/jneurosci.18-22-09517.1998 · Cited by 321
“Mechanistic models of normalization processes in cortex (Heeger, 1992; Carandini and Heeger, 1994; Carandini et al., 1997) such as the contrast gain control (Sclar and Freeman, 1982; Ohzawa et al., 1982) call for large, visually evoked changes in the membrane conductance, which, our results suggest…”
ResultMechanisms 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
Intrinsic Dynamics in Neuronal Networks. I. Theory
Latham, P. E., Richmond, B. J., Nelson, P. G., & Nirenberg, S. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.83.2.808 · Cited by 317
Reward value-based gain control: divisive normalization in parietal cortex
Louie, K., Grattan, L. E., & Glimcher, P. W. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1237-11.2011 · Cited by 308
“Normalization characterizes stimulus interaction within the V1 RF (Carandini and Heeger, 1994; Carandini et al., 1997), as well as interactions between the RF center and nonclassical suppressive surround (Cavanaugh et al.”
BackgroundMembrane Mechanisms Underlying Contrast Adaptation in Cat Area 17In Vivo
Sanchez-Vives, M. V., Nowak, L. G., & McCormick, D. A. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-11-04267.2000 · Cited by 315
“…adaptation aftereffects, if resulting from GABAA receptor-mediated inhibition, should be associated with substantial decreases of input resistance (Carandini and Heeger, 1994; Borg-Graham et al., 1998), which have not been detected (Ahmed et al., 1997; Carandini and Ferster, 1997; present study).”
BackgroundEncoding of binocular disparity by simple cells in the cat's visual cortex
Ohzawa, I., DeAngelis, G. C., & Freeman, R. D. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.75.5.1779 · Cited by 307
“A quantitative evaluation of re-neurons (Albrecht et al. 1984; Carandini and Heeger 1994; Heeger 1992a,b; Ohzawa et al. 1982, 1985), such mecha- sponses in the frequency domain shows that cells are not sensitive to motion-in-depth (Cynader and Regan 1978,nisms must clearly be incorporated.”
MethodBarrages 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
“Thus, changes in the barrages of synaptic activity may underlie diverse changes in neuronal responsiveness, owing to the combined influences of changes in membrane potential, conductance, and membrane potential variance (Matsumura et al., 1988; Bernander et al., 1991; Carandini and Heeger, 1994; Borg-Graham et al., 19…”
BackgroundResultLocal luminance and contrast in natural images
Frazor, R. A., & Geisler, W. S. (2006) · Vision Research · doi:10.1016/j.visres.2005.06.038 · Cited by 284
“…much faster form of contrast gain control in the primary visual cortex (Albrecht & Geisler, 1991; Albrecht et al., 2002; Albrecht & Hamilton, 1982; Carandini & Heeger, 1994; Carandini, Heeger, & Movshon, 1997; Frazor, Albrecht, Geisler, & Crane, 2004; Geisler & Albrecht, 1992, 1997; Heeger, 1991,…”
Spivey, M. J., & Tanenhaus, M. K. (1998) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037//0278-7393.24.6.1521 · Cited by 297
Visual Spatial Characterization of Macaque V1 Neurons
Sceniak, M. P., Hawken, M. J., & Shapley, R. M. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.85.5.1873 · Cited by 288
Motion Opponency in Visual Cortex
Heeger, D. J., Boynton, G. M., Demb, J. B., Seidemann, E., & Newsome, W. T. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-16-07162.1999 · Cited by 283
“The Simoncelli‐Heeger model posits a particular kind of divisive suppression in V1 in which the response of each individual V1 neuron is divided by a quantity proportional to the summed activity of a large pool of neighboring neurons (Robson, 1988; Bonds, 1989; Albrecht and Geisler, 1991; DeAngelis et al., 1992; Heege…”
BackgroundSelf-citationComputational models of cortical visual processing.
Heeger, D. J., Simoncelli, E. P., & Movshon, J. A. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.2.623 · Cited by 274
“…Heeger, 1992a for review) To explain non-speciic suppression and response saturation, a new model of simple cell responses , known as the the normalization model, has recently been proposed (Robson et al., 1991; Albrecht and Geisler, 1991; Heeger, 1991, 1992a, 1993; Carandini and Heeger, 1994).”
BackgroundMethodSelf-citationThe Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions
Neske, G. T. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2015.00088 · Cited by 296
“Changes in gain amplify or reduce neuronal responsiveness with minimal effects on stimulus selectivity or receptive field structure (Sclar and Freeman, 1982; Carandini and Heeger, 1994).”
BackgroundSeparate modifiability, mental modules, and the use of pure and composite measures to reveal them
Sternberg, S. (2001) · Acta Psychologica · doi:10.1016/s0001-6918(00)00045-7 · Cited by 266
“49 Example of relevant evidence are provided by Carandini and Heeger (1994) and Geisler and Albrecht”
BackgroundChung, S., & Ferster, D. (1998) · Neuron · doi:10.1016/s0896-6273(00)80498-5 · Cited by 270
“…inputs, were presented monocularly to the dominant eye at a frequency of either excitatory or inhibitory, accounts for this invari- 1 Hz or less. ance, as proposed in several models of cortical function (Carandini and Heeger, 1994; Somers et al., 1995; Troyer Electrical Stimulation et al., 1998).”
Gieselmann, M. A., & Thiele, A. (2008) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2008.06358.x · Cited by 264
“Neurons usually increase their firing rate with increasing stimulus size and somewhat reduce their firing rate when stimuli start to encroach into the suppressive surround (Carandini & Heeger, 1994; Sceniak et al., 1999; Cavanaugh et al., 2002; Levitt & Lund, 2002; Roberts et al., 2005).”
BackgroundA Normalization Model of Attentional Modulation of Single Unit Responses
Lee, J., & Maunsell, J. H. R. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004651 · Cited by 257
“simple cells, such as the sigmoidal shape of their contrast response functions (CRFs) and the inhibitory effect of adding a second stimulus to the receptive field at a non-preferred orientation [4–7].”
BackgroundShunting Inhibition Does Not Have a Divisive Effect on Firing Rates
Holt, G. R., & Koch, C. (1997) · Neural Computation · doi:10.1162/neco.1997.9.5.1001 · Cited by 250
A functional angle on some after-effects in cortical vision
Clifford, C. W. G., Wenderoth, P., & Špehar, B. (2000) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2000.1198 · Cited by 242
“In the language of control theory, centring is a form of additive (subtractive) gain control while scaling is divisive (multiplicative) in nature (Carandini & Heeger 1994).”
BackgroundNoise in Neural Populations Accounts for Errors in Working Memory
Bays, P. M. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3204-13.2014 · Cited by 250
“An important concept in models based on divisive normalization is that of the normalization pool, the pool of neurons whose summed activations provide the denominator of the divisive operation (Carandini and Heeger, 1994, 2012).”
BackgroundMethodDoes luminance‐contrast contribute to a saliency map for overt visual attention?
Einhäuser, W., & Peter König, B. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02508.x · Cited by 236
Dynamically Reconfigurable Silicon Array of Spiking Neurons With Conductance-Based Synapses
Vogelstein, R. J., Mallik, U., Vogelstein, J. T., & Cauwenberghs, G. (2007) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2006.883007 · Cited by 220
Predictive coding as a model of response properties in cortical area V1
Spratling, M. W. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.4911-09.2010 · Cited by 206
Timescales of Inference in Visual Adaptation
Wark, B., Fairhall, A. L., & Rieke, F. M. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.019 · Cited by 219
“This normalization is also consistent with models of contrast adaptation later in the visual system (e.g., Bonin et al., 2005; Carandini and Heeger, 1994).”
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
Self-citationCross-orientation suppression in human visual cortex
Brouwer, G. J., & Heeger, D. J. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00540.2011 · Cited by 226
Self-citationBayesian models: the structure of the world, uncertainty, behavior, and the brain
Vilares, I., & Kording, K. P. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.05965.x · Cited by 237
Suppression without Inhibition in Visual Cortex
Freeman, T., Durand, S., Kiper, D., & Carandini, M. (2002) · Neuron · doi:10.1016/s0896-6273(02)00819-x · Cited by 211
“Indeed, early conclusions (Carandini and Heeger, 1994; Carandini et al., 1997; drawn from similar experiments (Sillito, 1975) have later Heeger, 1992; Schwartz and Simoncelli, 2001). been challenged (Nelson et al., 1994).”
BackgroundSelf-citationGABAAInhibition Controls Response Gain in Visual Cortex
Katzner, S., Busse, L., & Carandini, M. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.5753-10.2011 · Cited by 201
“They have been ascribed to GABA inhibition from other cortical neurons (Morrone et al., 1982; Bonds, 1989; Carandini and Heeger, 1994; Carandini et al., 1997; Somers et al., 1998).”
Self-citationThe “silent” surround of V1 receptive fields: theory and experiments
Seriès, P., Lorenceau, J., & Frégnac, Y. (2003) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2004.01.023 · Cited by 214
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
“The equation itself is agnostic regarding the mechanism underlying contrast-dependent normalization; the normalization computation fits simple cell behavior well regardless of the origin of the contrast-dependent normalization signal (Carandini and Heeger, 1994).”
BackgroundVisual Cortex Neurons of Monkeys and Cats: Temporal Dynamics of the Contrast Response Function
Albrecht, D. G., Geisler, W. S., Frazor, R. A., & Crane, A. M. (2002) · Journal of Neurophysiology · doi:10.1152/jn.2002.88.2.888 · Cited by 207
A Flexible Model of Working Memory
Bouchacourt, F., & Buschman, T. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.04.020 · Cited by 207
Neuronal Integration of Synaptic Input in the Fluctuation-Driven Regime
Kuhn, A., Aertsen, A., & Rotter, S. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.3349-03.2004 · Cited by 200
“Several models of cortical function rely on the so-called “divisive” effect provided by the neuronal input conductance (invoked, for instance, to explain the saturation of simple cell spike response amplitude with increasing contrast) ( Carandini and Heeger, 1994 ).”
BackgroundNon-topographical contrast enhancement in the olfactory bulb
Cleland, T. A., & Sethupathy, P. (2006) · BMC Neuroscience · doi:10.1186/1471-2202-7-7 · Cited by 199
“While this chloride-mediated shunt inhibition may often be insufficiently hyperpolarizing to evoke clearly visible ipsps, it is highly effective at blocking spike initiation by multiplicatively decrementing the cumulative effect of excitatory sensory input (Figure 4Avi–vii;[61,65]; see also [66]).”
BackgroundPersistent Cortical Activity: Mechanisms of Generation and Effects on Neuronal Excitability
McCormick, D. A. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg104 · Cited by 200
“…explain diverse effects such as: (i) the ability of sensory context (i.e. far field stimuli) to modulate the response to discrete sensory stimuli (Carandini and Heeger, 1994; Angelucci et al., 2002; Stettler et al., 2002); (ii) the transformation of sensory to motor maps of external space…”
BackgroundA local circuit approach to understanding integration of long-range inputs in primary visual cortex
Somers, D. C. (1998) · Cerebral Cortex · doi:10.1093/cercor/8.3.204 · Cited by 191
“Other Models Contrast saturation effects have been achieved by other network models (e.g. Grossberg, 1973; Heeger, 1992, 1993; Carandini and Heeger, 1994); however, these models oversimplify cortical circuitry, effectively yoking together excitatory and inhibitory responses.”
MethodEncoding of Binocular Disparity by Complex Cells in the Cat's Visual Cortex
Ohzawa, I., DeAngelis, G. C., & Freeman, R. D. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.6.2879 · Cited by 186
“Since contrast of stimuli affects temporal responses (Shapley and Victor, 1981; Sclar 1987; Carandini and Heeger, 1994), it may be argued that the changes in latencies are due to changes in the stimulus energy (or effective contrast) contained in stimuli of different durations.”
BackgroundMethodBanerjee, A., Marbach, F., Anselmi, F., Koh, M., Davis, M. B., da Silva, P. G., Delevich, K. M., Oyibo, H. K., Gupta, P., Li, B., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.019 · Cited by 183
“The quest to find circuit motifs that mediate gain control has driven a large body of research in various sensory systems, including olfaction (Carandini and Heeger, 1994, 2012; Nikolaev et al., 2013; Ohshiro et al., 2011; Olsen et al., 2010; Robinson and McAlpine, 2009).”
A Range-Normalization Model of Context-Dependent Choice: A New Model and Evidence
Soltani, A., Martino, B. D., & Camerer, C. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002607 · Cited by 177
“More specifically, the response to the value of the saccade in the receptive field is divided by the weighted response of the saccadic values of all options presented in the choice set, similarly to what has been proposed for sensory neurons [55,56].”
BackgroundHansen, B. C., & Essock, E. A. (2004) · Journal of Vision · doi:10.1167/4.12.5 · Cited by 176
“However, the change in the orientation sensitivity obtained with broad-spectrum stimuli cannot be expected from standard models of contrast gain control (e.g., Bonds, 1989; Heeger, 1992; Geisler & Albrecht 1992; Wilson & Humanski , 1993, Carandini & Heeger, 1994; Carandini et al., 1997).”
BackgroundLiu, B.-H., Li, Y.-T., Ma, W.-P., Pan, C.-J., Zhang, L. I., & Tao, H. W. (2011) · Neuron · doi:10.1016/j.neuron.2011.06.017 · Cited by 173
“It proposes that inhibition scales down the membrane potential tuning by reducing responses in a divisive manner (Carandini and Heeger, 1994; Murphy and Miller, 2003; Wehr and Zador, 2003; Katzner et al., 2011).”
A selection model for motion processing in area MT of primates
Nowlan, S., & Sejnowski, T. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-02-01195.1995 · Cited by 206
“…recurrent excitation between local units in the population followed by mutual inhibition to normalize the responses (Hadeler, 1974; Feldman and Ballard, 1982; Carandini and Heeger, 1994) but other circuits can also perform the task that are faster and more reliable (Yuille and Grzywacz, 1989).”
BackgroundResponses of MT and MST Neurons to One and Two Moving Objects in the Receptive Field
Recanzone, G. H., Wurtz, R. H., & Schwarz, U. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.78.6.2904 · Cited by 171
Spatial Attention Modulates Center-Surround Interactions in Macaque Visual Area V4
Sundberg, K. A., Mitchell, J. F., & Reynolds, J. H. (2009) · Neuron · doi:10.1016/j.neuron.2009.02.023 · Cited by 157
“, 2002), which extended earlier normalization models (Sperling and Sondhi, 1968; Albrecht and Geisler, 1991; Heeger, 1992; Carandini and Heeger, 1994; Simoncelli and Heeger, 1998) to include a broad divisive surround component.”
A Canonical Neural Circuit for Cortical Nonlinear Operations
Kouh, M., & Poggio, T. (2008) · Neural Computation · doi:10.1162/neco.2008.02-07-466 · Cited by 165
“The energy model and many divisive normalization models (Adelson & Bergen, 1985; Carandini & Heeger, 1994; Rust et al., 2005) have used (half) squaring operations only.”
BackgroundMethodInfluentialDrivers and modulators from push-pull and balanced synaptic input
Abbott, L. F., & Chance, F. S. (2005) · Progress in brain research · doi:10.1016/s0079-6123(05)49011-1 · Cited by 153
“Gain modulation is seen in early visual processing (Weyland and Malpeli, 1993; Pouget and Sejnowski, 1994, 1997; Trotter and Celebrini, 1999), and it has been proposed as a mechanism for generating a variety of non-classical receptive field effects for neurons in primary visual cortex (Heeger, 1992, 1993; Carandini an…”
BackgroundAlbrecht, D. G. (1995) · Visual Neuroscience · doi:10.1017/s0952523800006817 · Cited by 158
“Further, the trends appear to be consistent with the behavior of the contrast-normalization model proposed by Carandini and Heeger (1994).”
BackgroundMethodResultInfluentialTilt Aftereffect and Adaptation-Induced Changes in Orientation Tuning in Visual Cortex
Jin, D. Z., Dragoi, V., Sur, M., & Seung, H. S. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00571.2004 · Cited by 154
On the Complexity of Computing and Learning with Multiplicative Neural Networks
Schmitt, M. (2002) · Neural Computation · doi:10.1162/08997660252741121 · Cited by 154
“In the 1960s, higher-order units were very common in pattern recognition, where they appear in the form of polynomial discriminant functions (Cover, 1965; Nilsson, 1965; Duda & Hart, 1973). There is an obvious reason for this popularity: higher-order units are computationally more powerful than single neurons since th…”
BackgroundSuarez, H., Christof Koch, A., & Douglas, R. J. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-10-06700.1995 · Cited by 154
“Conclusions From the early days of Hubel and Wiesel (1962) until today (e.g., Carandini and Heeger, 1994), it has always been assumed that geniculate input provides the dominant excitatory drive to striate cortex.”
BackgroundLack of cortical contrast gain control in human photosensitive epilepsy
Porciatti, V., Bonanni, P., Fiorentini, A., & Guerrini, R. (2000) · Nature Neuroscience · doi:10.1038/72972 · Cited by 152
“or the average activity of a large population of surrounding cell”
BackgroundChirimuuta, M. (2013) · Synthese · doi:10.1007/s11229-013-0369-y · Cited by 157
Pooresmaeili, A., Arrighi, R., Biagi, L., & Morrone, M. C. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1770-13.2013 · Cited by 147
“Typically, inhibitory circuits are responsible for control neuronal gain (Morrone et al., 1982; Heeger, 1992; Carandini and Heeger, 1994).”
BackgroundA Hierarchical Model of Binocular Rivalry
Dayan, P. (1998) · Neural Computation · doi:10.1162/089976698300017377 · Cited by 145
“Another extension is some form of contrast gain control ( Carandini & Heeger, 1994 ).”
BackgroundInfluence of Contrast on Orientation and Temporal Frequency Tuning in Ferret Primary Visual Cortex
Alitto, H. J., & Usrey, W. M. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00943.2003 · Cited by 143
Predictions of a recurrent model of orientation selectivity
Carandini, M., & Ringach, D. L. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00100-4 · Cited by 143
“Indeed, a large number of observations suggest the presence of broadly tuned inhibition acting as a gain control mechanism in ~ahe visual cortex, both in cat and in monkey (Heeger, 1992; Carandini & Heeger, 1994; Carandinl, 1996 ).”
BackgroundSelf-citationMultiple mechanisms underlying the orientation selectivity of visual cortical neurones
Vidyasagar, T. R., Pei, X., & Volgushev, M. (1996) · Trends in Neurosciences · doi:10.1016/s0166-2236(96)20027-x · Cited by 142
Mapping receptive fields in primary visual cortex
Ringach, D. L. (2004) · The Journal of Physiology · doi:10.1113/jphysiol.2004.065771 · Cited by 148
“A number of investigators proposed to extend the LN model by adding a gain control mechanism (Albrecht & Geisler, 1991; Bonds, 1991; Heeger, 1992; Carandini & Heeger, 1994; Tolhurst & Heeger, 1997; Carandini et al. 1997).”
BackgroundLampl, I., Ferster, D., Poggio, T., & Riesenhuber, M. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00060.2004 · Cited by 139
“It is also possible that differences in integration properties at low compared to high contrasts are related to the well-known stimulusdependent level of saturation of V1 neurons that was suggested to arise from a contrast normalization mechanism (Carandini and Heeger 1994; Heeger 1992).”
Background
Metadata
- Authors
- Carandini, M., & Heeger, D. J.
- Affiliations
- New York University (US)
- Venue
- Science
- Published
- 1994-05-27
- Volume
- 264
- Issue
- 5163
- Pages
- 1333-1336
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2038718814
- Cited by
- 649
- References
- 28
- Citations by year
- 2026: 7 · 2025: 20 · 2024: 22 · 2023: 19 · 2022: 22 · 2021: 23 · 2020: 18 · 2019: 30 · 2018: 12 · 2017: 10 · 2016: 17 · 2015: 22 · 2014: 20 · 2013: 20 · 2012: 31
- FWCI
- 9.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institutes of Health (5r29mh050228-05)
- National Institute of Mental Health (1-R29-MH-50228-01)
- 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
- primary visual cortex, simple cells, lateral geniculate nucleus, synaptic summation, membrane conductance, excitation-inhibition balance, contrast sensitivity, orientation selectivity, monkey visual cortex
- MeSH terms
- Animals, Electric Conductivity, Geniculate Bodies, Macaca, Membrane Potentials, Models, Neurological, Neurons, Synapses, 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