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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.
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“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]
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“Two models have recently been proposed for the mediation of contrast gain control: one by Shapley and Victor (1981), the other by Carandini and Heeger (1994) and Carandini et al. (1997).”
InfluentialA single spike suffices: the simplest form of stochastic resonance in model neurons
Stemmler, M. (1996) · Network Computation in Neural Systems · doi:10.1088/0954-898x_7_4_005 · Cited by 133
A framework for describing the effects of attention on visual responses
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BackgroundAdaptive Temporal Integration of Motion in Direction-Selective Neurons in Macaque Visual Cortex
Bair, W., & Movshon, J. A. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.0554-04.2004 · Cited by 133
“…contrast influences the relative sensitivity to low and high TFs in retinal ganglion cells (Shapley and Victor, 1981), and it affects the phase of cortical simple-cell responses to drifting gratings (Dean and Tolhurst, 1986; Carandini and Heeger, 1994; Albrecht, 1995; Carandini et al., 1997).”
InfluentialMechanisms of dendritic integration underlying gain control in fly motion-sensitive interneurons
Borst, A., Egelhaaf, M., & Haag, J. (1995) · Journal of Computational Neuroscience · doi:10.1007/bf00962705 · Cited by 129
“Interestingly, Carandini and Heeger (1994) proposed a somewhat similar mechanism to account for the response properties of orientation selective cells in primate visual cortex.”
BackgroundInvariant Visual Responses From Attentional Gain Fields
Salinas, E., & Abbott, L. F. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.6.3267 · Cited by 129
Orientation Selectivity of Synaptic Input to Neurons in Mouse and Cat Primary Visual Cortex
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“Inhibition may also contribute to selectivity by acting as a gain control mechanism (Heeger, 1992; Carandini and Heeger, 1994; Borg-Graham et al., 1998) or by controlling response timing (Wehr and Zador, 2003; Higley and Contreras, 2006).”
BackgroundInter-ocular contrast normalization in human visual cortex
Moradi, F., & Heeger, D. J. (2009) · Journal of Vision · doi:10.1167/9.3.13 · Cited by 122
“…introduced in the early 1990s to explain a variety of such suppressive phenomena evident in the response properties of V1 neurons (Albrecht & Geisler, 1991; Carandini & Heeger, 1994; Carandini et al., 1997; Heeger, 1991, 1992a, 1992b, 1993; Nestares & Heeger, 1997; Tolhurst & Heeger, 1997a, 1997b).”
BackgroundSelf-citationSuppressive Surrounds and Contrast Gain in Magnocellular-Pathway Retinal Ganglion Cells of Macaque
Solomon, S. G., Lee, B. B., & Sun, H. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.0821-06.2006 · Cited by 125
“The biophysical mechanism for such effects remains elusive, although there are several candidates (Carandini and Heeger, 1994; Chance et al., 2002).”
BackgroundModular processes in mind and brain
Sternberg, S. (2011) · Cognitive Neuropsychology · doi:10.1080/02643294.2011.557231 · Cited by 132
“gif"/> changes nonlinearly (Albrecht, Geisler, & Crane, 2003 ; Carandini & Heeger, 1994 ; Geisler & Albrecht, 1995; Heeger et al, 2000 ; Li, Miller, & Desimone, 1993 ; Meeter, Myers, & Gluck, 2005 ; Sawamura, Organ, & Vogels, 2006).”
Linguistic Structure and Meaning Organize Neural Oscillations into a Content-Specific Hierarchy
Kaufeld, G., Bosker, H. R., ten Oever, S., Alday, P. M., Meyer, A. S., & Martin, A. E. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.0302-20.2020 · Cited by 117
Deterministic Multiplicative Gain Control with Active Dendrites
Mehaffey, W. H., Doiron, B., Maler, L., & Turner, R. W. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.2682-05.2005 · Cited by 120
“Division or multiplication of firing rate by synaptic input, originally suggested by Reichardt (1961), has since become a key component of many models of neural processing (Salinas and Sejnowski, 2001) and is required in models characterizing the response of cells in the visual cortex (Carandini and Heeger, 1994) and…”
BackgroundChromatic Gain Controls in Visual Cortical Neurons
Solomon, S. G., & Lennie, P. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.5316-04.2005 · Cited by 121
Dynamics of attentional selection under conflict: Toward a rational Bayesian account.
Yu, A. J., Dayan, P., & Cohen, J. D. (2009) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/a0013553 · Cited by 131
“…by the sum of the unnormalized quantities, reminiscent of the divisive normalization that is commonly supposed to occur during visual processing (e.g., Carandini & Heeger, 1994; Yu, 2005b) and in neural computations more generally (e.g., O'Reilly & Munakata, 2000; Schwartz & Simoncelli, 2001).”
BackgroundAdaptive, Fast Walking in a Biped Robot under Neuronal Control and Learning
Manoonpong, P., Geng, T., Kulvicius, T., Porr, B., & Wörgötter, F. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030134 · Cited by 119
Functional Selection of Adaptive Auditory Space Map by GABA A -Mediated Inhibition
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Normalization and the Cholinergic Microcircuit: A Unified Basis for Attention
Schmitz, T. W., & Duncan, J. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.02.011 · Cited by 119
How mechanisms of perceptual decision-making affect the psychometric function
Gold, J. I., & Ding, L. (2012) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2012.05.008 · Cited by 120
“and uncertainty about how past experiences can inform future decisions (Britten and Heuer, 1999; Carandini and Heeger, 1994; Carandini et al., 1997; Koch et al., 2004; Kouh and Poggio, 2008; Law and Gold, 2009a; Miller and Troyer, 2002; Nassar et al., 2010; Petrov et al., 2005; Purushothaman and Bradley, 2005; Rust et…”
BackgroundA Model of Binocular Rivalry and Cross-orientation Suppression
Said, C. P., & Heeger, D. J. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002991 · Cited by 115
“Biophysically plausible implementations of this equation have been described elsewhere [19,31].”
MethodSelf-citationTexture contrast attracts overt visual attention in natural scenes
Parkhurst, D. J., & Niebur, E. (2004) · European Journal of Neuroscience · doi:10.1111/j.0953-816x.2003.03183.x · Cited by 135
Local Contrast in Natural Images: Normalisation and Coding Efficiency
Brady, N. P., & Field, D. J. (2000) · Perception · doi:10.1068/p2996 · Cited by 118
Tuned Normalization Explains the Size of Attention Modulations
Ni, A. M., Ray, S., & Maunsell, J. H. R. (2012) · Neuron · doi:10.1016/j.neuron.2012.01.006 · Cited by 109
“An influential divisive normalization model hypothesizes that the response of a neuron is reduced in proportion to the pooled activity of other neurons in the neighborhood (Heeger, 1992; Carandini and Heeger, 1994; Carandini et al., 1997).”
Subtractive and Divisive Inhibition: Effect of Voltage-Dependent Inhibitory Conductances and Noise
Doiron, B., Longtin, A., Berman, N. J., & Maler, L. (2001) · Neural Computation · doi:10.1162/089976601300014691 · Cited by 110
Neural Representation of Natural Images in Visual Area V2
Willmore, B. D. B., Prenger, R., & Gallant, J. L. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.4099-09.2010 · Cited by 111
“Thus, the suppressive tuning in Figure 5a is likely to reflect known mechanisms of contrast normalization (Heeger, 1992; Carandini and Heeger, 1994; Zipser et al., 1996; Rossi et al., 2001) and cross-orientation suppression (DeAngelis et al.”
BackgroundSuppression of the magnocellular pathway during saccades
Ross, J., Burr, D. C., & Morrone, M. C. (1996) · Behavioural Brain Research · doi:10.1016/0166-4328(96)00012-5 · Cited by 107
Geisler, W. S., & Albrecht, D. G. (1995) · Vision Research · doi:10.1016/0042-6989(95)00029-y · Cited by 105
Anderson, J. S., Lampl, I., Gillespie, D. C., & Ferster, D. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-06-02104.2001 · Cited by 101
“Cortical gain control and contrast adaptation may be affected by the size of a stimulus (Ohzawa et al., 1985; Carandini and Heeger, 1994; Sceniak et al., 1999).”
Alternation rate in perceptual bistability is maximal at and symmetric around equi-dominance
Moreno‐Bote, R., Shpiro, A., Rinzel, J., & Rubin, N. (2010) · Journal of Vision · doi:10.1167/10.11.1 · Cited by 100
“Gain modulation is thought to be an important step in the processing of sensory inputs (see, e.g., Carandini & Heeger, 1994; Ohzawa et al., 1982, 1985) and here it is modeled as a normalization of the strengths of the competing inputs (Equation 5, Methods section).”
Tolhurst, D. J., & Heeger, D. J. (1997) · Visual Neuroscience · doi:10.1017/s0952523800011433 · Cited by 99
Self-citationDistinct Properties of Stimulus-Evoked Bursts in the Lateral Geniculate Nucleus
Alitto, H. J., Weyand, T. G., & Usrey, W. M. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.3369-04.2005 · Cited by 97
“, 1992 ; Carandini and Heeger , 1994 ; Albrecht , 1995 ; Kremers et al .”
Spatial vision thresholds in the near absence of attention
Lee, D. K., Koch, C., & Braun, J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00055-2 · Cited by 95
“…between filters, for example, the inhibitory interactions between filters at the same visual location suggested by Heeger and others (Heeger, 1993; Carandini & Heeger, 1994), or the competitive interactions between filters at distant visual locations postulated by Koch, Desimone and others (Koch…”
BackgroundBiophysiologically Plausible Implementations of the Maximum Operation
Yu, A. J., Giese, M. A., & Poggio, T. (2002) · Neural Computation · doi:10.1162/089976602760805313 · Cited by 96
“Such network interactions have been been previously proposed to account for response of V1 neurons receiving afferent LGN inputs and lateral cortical inputs (Carandini & Heeger, 1994).”
Linearity and Gain Control in V1 Simple Cells
Carandini, M., Heeger, D. J., & Movshon, J. A. (1999) · Cerebral cortex · doi:10.1007/978-1-4615-4903-1_7 · Cited by 94
“After (Carandini and Heeger, 1994).”
BackgroundMethodInfluentialSelf-citationA Biologically Inspired Appearance Model for Robust Visual Tracking
Zhang, S., Lan, X., Yao, H., Zhou, H., Tao, D., & Li, X. (2016) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2586194 · Cited by 93
“An operator of removing these dependences is divisive normalization [60], [65], which represents each coefficient by a weighted combination of its rectified neighbors.”
BackgroundArandia-Romero, I., Tanabe, S., Drugowitsch, J., Kohn, A., & Moreno‐Bote, R. (2016) · Neuron · doi:10.1016/j.neuron.2016.01.044 · Cited by 89
“Multiplicative modulation of tuning is also evident with manipulations of stimulus contrast (Carandini and Heeger, 1994; Finn et al., 2007; Priebe and Ferster, 2012).”
Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits
Louie, K., LoFaro, T., Webb, R., & Glimcher, P. W. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.2851-14.2014 · Cited by 85
“Normalization operates in multiple sensory levels and modalities, explaining features of both early stimulus coding (Heeger, 1992; Carandini and Heeger, 1994; Britten and Heuer, 1999; Bonin et al., 2005; Rabinowitz et al., 2011) and higher-order processing such as object identification, visual…”
BackgroundInfluentialContrast response characteristics of long-range lateral interactions in cat striate cortex
Chen, C., Kasamatsu, T., Polat, U., & Norcia, A. M. (2001) · Neuroreport · doi:10.1097/00001756-200103260-00008 · Cited by 90
Luminance-contrast mechanisms in humans: Visual evoked potentials and a nonlinear model
Zemon, V. M., & Gordon, J. (2006) · Vision Research · doi:10.1016/j.visres.2006.07.007 · Cited by 90
Chen, H. (1995) · Proceedings of the IEEE · doi:10.1109/5.362753 · Cited by 90
Malina, K. C.-K., Tsivourakis, E., Kushinsky, D., Apelblat, D., Shtiglitz, S., Zohar, E., Sokoletsky, M., Tasaka, G., Mizrahi, A., Lampl, I., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.05.001 · Cited by 95
“We then analyzed the type of inhibition that is conveyed by L1 NDNF INs onto excitatory neurons (i.e., subtractive or divisive; Carandini and Heeger, 1994; Isaacson and Scanziani, 2011; Wilson et al., 2012) by comparing the effects of optogenetic L1 NDNF IN activation on excitatory neuron”
Free-Energy and Illusions: The Cornsweet Effect
Brown, H. R., & Friston, K. J. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00043 · Cited by 88
“…the following sense: If we assume that the brain uses divisive normalization (Weber, 1846; Fechner, 1860; Craik, 1938; Geisler and Albrecht, 1992; Carandini and Heeger, 1994), the key change in sensory information, following an increase in contrast, is an increase in signal to noise; in other…”
Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model
Sit, Y. F., Chen, Y., Geisler, W. S., Miikkulainen, R. P., & Seidemann, E. (2009) · Neuron · doi:10.1016/j.neuron.2009.08.041 · Cited by 81
“To account for the observed properties in both time and space, we propose a simple feedforward population gain-control (PGC) model that generalizes earlier normalization models for single V1 neurons (Albrecht and Geisler, 1991; Heeger, 1991, 1992; Carandini and Heeger, 1994; Carandini et al., 1997).”
InfluentialFrazor, R. A., Albrecht, D. G., Geisler, W. S., & Crane, A. M. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00858.2003 · Cited by 83
“…of the response as a code for spatial frequency We have known for many decades that the latency of the response of visual cortex neurons decreases as the contrast increases (e.g., Albrecht 1978, 1995; Carandini and Heeger 1994; Carandini et al. 1997; Dean and Tolhurst 1986; Reid et al. 1992).”
BackgroundThe processing and encoding of information in the visual cortex
Reid, R. C., & Alonso, J. (1996) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(96)80052-3 · Cited by 84
Poggio, T., & Serre, T. (2006) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 85
Revisiting spatial vision: toward a unifying model
Itti, L., Koch, C., & Braun, J. (2000) · Journal of the Optical Society of America A · doi:10.1364/josaa.17.001899 · Cited by 84
Rapid categorization of achromatic natural scenes: how robust at very low contrasts?
Macé, M. J. ‐., Thorpe, S. J., & Fabre‐Thorpe, M. (2005) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2005.04029.x · Cited by 83
“In the striate cortex, a decrease in contrast from 100% to 5–10% generally induces a latency increase of 30–50 ms (Carandini & Heeger, 1994; Albrecht, 1995; Gawne et al., 1996; Reich et al., 2001).”
BackgroundSceniak, M. P., Hawken, M. J., & Shapley, R. M. (2002) · Journal of Neurophysiology · doi:10.1152/jn.2002.88.3.1363 · Cited by 81
Intracortical Origins of Interocular Suppression in the Visual Cortex
Sengpiel, F., & Vorobyov, V. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.0862-05.2005 · Cited by 79
“An alternative view interprets cross-orientation inhibition as a means of response normalization with respect to local image contrast (Heeger, 1992; Carandini and Heeger, 1994; Carandini et al., 1997).”
BackgroundRobust Visual Tracking via Basis Matching
Zhang, S., Lan, X., Qi, Y., & Yuen, P. C. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2539860 · Cited by 81
“3) As supported by the biological studies [36], [37]”
ResultKagan, I., Gur, M., & Snodderly, D. M. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00858.2001 · Cited by 80
Dysfunction of early-stage visual processing in schizophrenia: Harmonic analysis
Kim, D., Zemon, V., Saperstein, A., Butler, P. D., & Javitt, D. C. (2005) · Schizophrenia Research · doi:10.1016/j.schres.2004.10.011 · Cited by 79
“Alternatively, deficits in nonlinear mechanisms present in cortex, such as shunting inhibition which are important in producing responses at higher harmonics or temporal frequencies (Carandini and Heeger, 1994) would also result in greater attenuation of higher harmonic responses in patients than controls.”
BackgroundDynamic causal modelling of precision and synaptic gain in visual perception — an EEG study
Brown, H. R., & Friston, K. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.044 · Cited by 84
“This manipulation was based onWeber's law (Weber, 1846) and evidence that the brain uses divisive normalisation (Brady and Field, 2000; Carandini and Heeger, 1994), meaning that higher contrast stimuli have a higher signal-to-noise ratio and therefore higher precision.”
MethodPerceptual Inference Predicts Contextual Modulations of Sensory Responses
Lochmann, T., Ernst, U. A., & Denève, S. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0817-11.2012 · Cited by 77
“Such models were motivated e.g., by experimentally observed properties of sensory processing like divisive normalization (Heeger, 1992; Carandini and Heeger, 1994) or synaptic depression (Carandini et al., 2002; Goldman et al., 2002).”
InfluentialNetwork model of top-down influences on local gain and contextual interactions in visual cortex
Piëch, V., Li, W., Reeke, G. N., & Gilbert, C. D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317019110 · Cited by 77
Improving performance of robots using human-inspired approaches: a survey
Qiao, H., Zhong, S., Chen, Z., & Wang, H. (2022) · Science China Information Sciences · doi:10.1007/s11432-022-3606-1 · Cited by 79
“Two-dimensional Gabor function [94] Gain control operation [95] “Winner is king” model [96,97] Gaussian response model [98] Macro models Neocognitron model [99] HMAX model [100,101] Three stages model [102] Models based on attention mechanism [103–105] Models based on multiple mechanisms…”
BackgroundLateral modulation of contrast discrimination: Flanker orientation effects
Chen, C., & Tyler, C. W. (2002) · Journal of Vision · doi:10.1167/2.6.8 · Cited by 73
“It may be noted that that the original divisive inhibition-based gain-control models (Albrecht & Geisler, 1991; Carandini & Heeger, 1994; Foley, 1994; Heeger, 1992; Ross & Speed, 1991), which were designed to account for the interaction among mechanisms, are incompatible with many aspects of the…”
BackgroundOrigins of Cross-Orientation Suppression in the Visual Cortex
Li, B., Thompson, J. K., Duong, T., Peterson, M. R., & Freeman, R. D. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00425.2006 · Cited by 73
“Intracortical inhibitory connections included in other models (Albrecht and Geisler 1991; Ben-Yishai et al. 1995; Carandini and Heeger 1994; Carandini and Ringach 1997; Heeger 1992; McLaughlin et al. 2000, 2003; Shelley and McLaughlin 2002; Shelley et al. 2002; Wielaard et al. 2001) are not…”
BackgroundInfluentialA dynamic normalization model of temporal attention
Denison, R. N., Carrasco, M., & Heeger, D. J. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01129-1 · Cited by 72
“Dynamic normalization models have been developed to account for the time courses of neuronal responses 5, 10, 23–27 and dynamic sensory processes like adaptation 2, 28–32 .”
Self-citationThe Role of V1 Surround Suppression in MT Motion Integration
Tsui, J. M. G., Hunter, J. N., Born, R. T., & Pack, C. C. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00654.2009 · Cited by 71
Gain Modulation of Neuronal Responses by Subtractive and Divisive Mechanisms of Inhibition
Ayaz, A., & Chance, F. S. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90547.2008 · Cited by 70
“We incorporate subtractive and divisive mechanisms of inhibition into a model based on the “normalization model” (Carandini and Heeger 1994; Carandini et al. 1997; Heeger 1992, 1993; Tolhurst and Heeger 1997) and examine whether they can reproduce realistic gain modulation effects on model neuron…”
BackgroundMethodWidespread Inhibition Proportional to Excitation Controls the Gain of a Leech Behavioral Circuit
Baca, S. M., Marín‐Burgin, A., Wagenaar, D. A., & Kristan, W. B. (2008) · Neuron · doi:10.1016/j.neuron.2007.11.028 · Cited by 72
“Because it produces a nonlinear change in excitatory synaptic inputs, shunting inhibition has been proposed as a mechanism for division (Carandini and Heeger, 1994), but the effect of having a threshold for spiking acts to offset this nonlinearity and make the input/output function for spiking activity very nearly lin…”
Dynamics of Normalization Underlying Masking in Human Visual Cortex
Tsai, J. J., Wade, A. R., & Norcia, A. M. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.4485-11.2012 · Cited by 71
“A more detailed model of membrane conductances, such as shunting inhibition (Carandini and Heeger, 1994; Carandini et al., 1997; Sit et al., 2009) may be a way to augment the model.”
BackgroundThe Nature of Physical Computation
Shagrir, O. (2022) · doi:10.1093/oso/9780197552384.001.0001 · Cited by 70
Different attentional resources modulate the gain mechanisms for color and luminance contrast
Morrone, M. C., Denti, V., & Spinelli, D. (2003) · Vision Research · doi:10.1016/j.visres.2003.10.014 · Cited by 73
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model
Simoncelli, E. P., & Schwartz, O. (1998) · Cited by 70
Contrast Gain Control in the Visual Cortex: Monocular Versus Binocular Mechanisms
Truchard, A. M., Ohzawa, I., & Freeman, R. D. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-08-03017.2000 · Cited by 70
“Furthermore, for monocularly viewed stimuli, a change in contrast can result in an advance in response phase (Dean and Tolhurst, 1986; Carandini and Heeger, 1994) and a change in contrast gain (Albrecht and Hamilton, 1982).”
BackgroundA recurrent circuit implements normalization, simulating the dynamics of V1 activity
Heeger, D. J., & Zemlianova, K. O. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005417117 · Cited by 72
“, increasing conductance by a balanced increase in excitation and inhibition without changing the total synaptic current (6, 94).”
BackgroundResultSelf-citationLong-Range Parallel Processing and Local Recurrent Activity in the Visual Cortex of the Mouse
Polack, P., & Contreras, D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.6304-11.2012 · Cited by 68
“The variation of the latency of the response with contrast is in line with measurements from single cells (Dean and Tolhurst, 1986; Carandini and Heeger, 1994; Albrecht, 1995).”
ResultCortical-subcortical interactions in goal-directed behavior
Cruz, K. G., Leow, Y. N., Le, N. M., Adam, E. M., Huda, R., & Sur, M. (2022) · Physiological Reviews · doi:10.1152/physrev.00048.2021 · Cited by 76
A precise form of divisive suppression supports population coding in the primary visual cortex
MacEvoy, S. P., Tucker, T. R., & Fitzpatrick, D. (2009) · Nature Neuroscience · doi:10.1038/nn.2310 · Cited by 64
Spratling, M. (2011) · Neural Computation · doi:10.1162/neco_a_00222 · Cited by 67
FlpStop, a tool for conditional gene control in Drosophila
Fisher, Y. E., Yang, H. H., Isaacman-Beck, J., Xie, M., Gohl, D. M., & Clandinin, T. R. (2017) · eLife · doi:10.7554/elife.22279 · Cited by 64
Background Synaptic Activity as a Switch Between Dynamical States in a Network
Salinas, E. (2003) · Neural Computation · doi:10.1162/089976603321891756 · Cited by 66
“…such consistency is somewhat remarkable because the divisive mechanism was originally derived from empirical observations (Wilson & Humanski, 1993; Carandini & Heeger, 1994; Carandini et al., 1997; Simoncelli & Heeger, 1998; Wilson, 1998; Schwartz & Simoncelli, 2001) and its biophysical…”
BackgroundMethodInfluentialProbabilistic Models of the Brain.
Long, D. M. (2002) · Neurosurgery Quarterly · doi:10.1097/00013414-200212000-00005 · Cited by 67
Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback
Brosch, T., & Heiko Neumann, B. (2014) · Neural Computation · doi:10.1162/neco_a_00675 · Cited by 64
“Simple cells in area V1 tend to saturate their activation as a consequence of increasing stimulus contrast and surround activities (Heeger, 1992; Carandini & Heeger, 1994; Carandini et al., 1999; Carandini, Heeger, & Movshon, 1997; see Smith, 2006, for a summary).”
BackgroundMethodStimulus-driven competition in a cholinergic midbrain nucleus
Asadollahi, A., Mysore, S. P., & Knudsen, E. I. (2010) · Nature Neuroscience · doi:10.1038/nn.2573 · Cited by 64
“2 ), a property that is distinct from the typical effects of divisive normalization of neural activit”
BackgroundEstimating multiple temporal mechanisms in human vision
Fredericksen, R. E., & Hess, R. F. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00239-3 · Cited by 64
Stimulus Dependence of Correlated Variability across Cortical Areas
Ruff, D. A., & Cohen, M. R. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.0504-16.2016 · Cited by 64
“The simplest prevailing hypothesis concerning the relationship between V1 and MT responses is that the activity of MT neurons reflect summed inputs from V1 that have been passed through a divisive nonlinearity (Carandini and Heeger, 1994; Rust et al., 2006).”
BackgroundPairwise normalization: A neuroeconomic theory of multi-attribute choice
Landry, P., & Webb, R. (2021) · Journal of Economic Theory · doi:10.1016/j.jet.2021.105221 · Cited by 64
One mechanism, many models: a distributed theory of mechanistic explanation
Hochstein, E. (2015) · Synthese · doi:10.1007/s11229-015-0844-8 · Cited by 62
“To illustrate this point, Chirimuuta (2014) offers the example of Heeger’s contrast normalisation model of the primary visual cortex (Heeger 1992; Carandini and Heeger 1994, 2012).”
BackgroundRecanzone, G. H., & Wurtz, R. H. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.82.4.1710 · Cited by 62
Competitive Dynamics in Cortical Responses to Visual Stimuli
Moldakarimov, S. B., Rollenhagen, J. E., Olson, C. R., & Chow, C. C. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00159.2005 · Cited by 61
“1) In the biased competition framework (Desimone and Duncan 1995), competition takes the form of normalization: two simultaneously presented images elicit levels of activation intermediate between those elicited by the images in isolation (Carandini and Heeger 1994; Reynolds et al. 1999).”
BackgroundStriosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington’s Disease Model
Friedman, A., Hueske, E., Drammis, S. M., Arana, S. E. T., Nelson, E. D., Carter, C. W., Delcasso, S., Rodriguez, R. X., Lutwak, H., DiMarco, K. S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.060 · Cited by 58
“We developed a graph-based model by which PV interneurons exerting inhibition onto striosomal neurons could improve discrimination through shifting excitation-inhibition balance (van Vreeswijk and Sompolinsky, 1996; Vogels and Abbott, 2009) due to modulating SNR alongside gain (Atallah et al., 2012; Carandini and Heeg…”
Sadagopan, S., & Ferster, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.05.007 · Cited by 62
Sundberg, K. A., Mitchell, J. F., Gawne, T. J., & Reynolds, J. H. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0489-12.2012 · Cited by 58
Contrast-Dependent Nonlinearities Arise Locally in a Model of Contrast-Invariant Orientation Tuning
Kayser, A. S., Priebe, N. J., & Miller, K. D. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.85.5.2130 · Cited by 61
Visual Contrast Gain Control in Migraine: Measures of Visual Cortical Excitability and Inhibition
McColl, S. L., & Wilkinson, F. (2000) · Cephalalgia · doi:10.1046/j.1468-2982.2000.00033.x · Cited by 61
Koechlin, É., Anton, J. L., & Burnod, Y. (1999) · Biological Cybernetics · doi:10.1007/s004220050502 · Cited by 60
“The precise form of normalization across filter units is similar to that proposed by Heeger (1993; Carandini and Heeger, 1994 ), although this choice has no significant influence on the present model performance.”
MethodMejías, J. F., & Longtin, A. (2014) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2014.00107 · Cited by 58
“Divisive gain control mechanisms is often assumed as a key operation for neural computations (Carandini and Heeger, 1994; Chance and Abbott, 2000), but biophysical mechanisms for such a modulation have been hard to identify, regardless of being network-based mechanisms (Holt and Koch, 1997; Doiron…”
BackgroundRollenhagen, J. E., & Olson, C. R. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00158.2005 · Cited by 59
“inhibitory circuits are capable of producing averaging responses (Carandini and Heeger, 1994; Carandini et al., 1997).”
BackgroundAdaptation of the simple or complex nature of V1 receptive fields to visual statistics
Fournier, J., Monier, C., Pananceau, M., & Frégnac, Y. (2011) · Nature Neuroscience · doi:10.1038/nn.2861 · Cited by 58
“Another minimal adaptation hypothesis is to consider a gain control process before the nonlinear filtering stage (pre-NL), that rescales the gain of the afferent subunits with regard to the increase in the stimulus powe”
BackgroundCross-Orientation Suppression: Monoptic and Dichoptic Mechanisms Are Different
Li, B., Peterson, M. R., Thompson, J. K., Duong, T., & Freeman, R. D. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00203.2005 · Cited by 56
Heeger, D. J., & Mackey, W. E. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911633116 · Cited by 55
“Several hypotheses for the recurrent circuits underlying normalization have been proposed (50, 51, 96, 106 – 108), but most of them are inconsistent with experimental observations suggesting that normalization is implemented via recurrent amplification (109 – 114).”
BackgroundSelf-citationDifferential attentional modulation of cortical responses to S-cone and luminance stimuli
Wang, J., & Wade, A. R. (2011) · Journal of Vision · doi:10.1167/11.6.1 · Cited by 52
Local masking in natural images: A database and analysis
Alam, M. M., Vilankar, K. P., Field, D. J., & Chandler, D. M. (2014) · Journal of Vision · doi:10.1167/14.8.22 · Cited by 54
Burkitt, A. N., Hamish Meffin, A., & Grayden, D. B. (2003) · Biological Cybernetics · doi:10.1007/s00422-003-0408-8 · Cited by 54
“…of these two opposing effects in different parameter regions explains many of the the differing results on gain modulation reported by a number of authors (Nelson, 1994; Carandini & Heeger, 1994; Holt & Koch, 1997; Tiesinga et al., 2000; Capaday, 2002; Longtin et al., 2002; Chance et al., 2002).”
BackgroundResultInfluentialMotoneuron 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
“After applying our estimation method for the Poissonian firing intensity to all of the data, we report an exponential increase of the firing intensity with depolarizing membrane potential, which is comparable with the quadratic shape reported in previous studies (Anderson et al. 2000; Carandini and Heeger 1994; Gabbia…”
BackgroundMethodResultInfluentialBanitt, Y., Martin, K. A. C., & Segev, I. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1640-07.2007 · Cited by 52
“…gain-control mechanism must arise from local cortical interactions, e.g., from a divisive inhibitory mechanism (Rose, 1977; Morrone et al., 1982; Worgotter and Koch, 1991; Carandini and Heeger, 1994; Ben-Yishai et al., 1995; Sompolinsky and Shapley, 1997; Troyer et al., 1998; Teich and Qian, 2006).”
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
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