The Normalization Model of Attention
Open accessAbstract
Attention has been found to have a wide variety of effects on the responses of neurons in visual cortex. We describe a model of attention that exhibits each of these different forms of attentional modulation, depending on the stimulus conditions and the spread (or selectivity) of the attention field in the model. The model helps reconcile proposals that have been taken to represent alternative theories of attention. We argue that the variety and complexity of the results reported in the literature emerge from the variety of empirical protocols that were used, such that the results observed in any one experiment depended on the stimulus conditions and the subject's attentional strategy, a notion that we define precisely in terms of the attention field in the model, but that has not typically been completely under experimental control.
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Gain modulation (wherein attention multiplicatively scales neural activity) has been found in many neural systems.
“Similar to self-attention, gain modulation (wherein attention multiplicatively scales neural activity) has been found in many neural systems (Treue & Trujillo 1999, Reynolds & Heeger 2009).”
From Consciousness in Artificial Intelligence: Insights from the Science of Consciousness (2023) · cites this paper as Reynolds & Heeger 2009
The Introduction reports studies in which attention multiplicatively increases neuronal responses, and the section on spatial attention describes scaling in visual cortical areas V4 and MT. The paper reviews visual cortex, however, so it does not establish the broader claim that this effect has been found in many neural systems; it also notes other forms of attentional modulation. (LLM, conf=0.84)
Experimental — accuracy not yet measuredMultiplicative amplitude modulations of response tuning functions preserve feature selectivity.
“Particularly interesting are multiplicative amplitude modulations of the response tuning function since they preserve feature selectivity”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Reynolds and Heeger, 2009
Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration.
“Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration1–3,7,8,13–17.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [1]
In non-human primate visual system, visual spatial attention within the receptive field of a recorded neuron enhances both contrast gain and response gain.
“Attentional modulation of neural gain has been particularly well studied in the non-human primate visual system1,42,43, in which visual spatial attention within the receptive field of a recorded neuron enhances both contrast gain (that is, scaling of that neuron’s stimulus-response relationship along the contrast axis)43 and response gain (that is, multiplicative transformation of responses to all”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [1]
Attention produces widespread effects throughout early and late visual areas, increasing the signal from the attended item and suppressing noise from unattended distractors.
“These studies have shown that attention produces widespread effects throughout early and late visual areas, which collectively increase the signal from the attended item and suppress noise from unattended distractors (Reynolds and Heeger, 2009).”
From Attention, learning, and the value of information (2012) · cites this paper as Reynolds and Heeger, 2009
Attention affects sensory representations at all levels of the visual hierarchy, from low-level areas such as the lateral geniculate nucleus through high-level cortical areas in the inferior temporal lobe.
“Intensive research into this system has shown that attention affects sensory representations at all levels of the visual hierarchy, starting from low-level areas such as the lateral geniculate nucleus, through high-level cortical areas in the inferior temporal lobe (Reynolds and Heeger, 2009; Saalmann and Kastner, 2011).”
From Attention, learning, and the value of information (2012) · cites this paper as Reynolds and Heeger, 2009
A recent normalization model of attention has been particularly successful in explaining a large number of sensory effects using a simple biologically-plausible circuit.
“A recent “normalization” model of attention has been particularly successful in explaining a large number of sensory effects using a simple biologically-plausible circuit (Reynolds and Heeger, 2009).”
From Attention, learning, and the value of information (2012) · cites this paper as Reynolds and Heeger, 2009
The normalization model proposes that a spatially selective attention field is fed back to the visual system and multiplicatively scales visual inputs in spatially specific fashion, followed by divisive normalization based on local competition, resulting in a biased visual representation where the attended stimulus is more strongly represented.
“As illustrated in Fig. 1B, the model proposes that a spatially selective “attention field” is fed back to the visual system and multiplicatively scales visual inputs in spatially specific fashion. Followed by divisive normalization based on local competition with other visual inputs (“suppressive drive”), this attentional influence results in a biased visual representation where the attended”
From Attention, learning, and the value of information (2012) · cites this paper as Reynolds and Heeger, 2009
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Cites
James, W. (1891) · Henry Holt and Company eBooks · doi:10.1037/11059-000 · Cited by 25,799 · see citing works
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 · see citing works
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881 · see citing works
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388 · see citing works
(2005) · Choice Reviews Online · doi:10.5860/choice.43-0626 · Cited by 4,726 · see citing works
Attention and the detection of signals.
Posner, M. I., Snyder, C. R., & Davidson, B. J. (1980) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.109.2.160 · Cited by 3,778 · see citing works
Spatiotemporal energy models for the perception of motion
Adelson, E. H., & Bergen, J. R. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.000284 · Cited by 3,442 · see citing works
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309 · see citing works
Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention
Fries, P., Reynolds, J. H., Rorie, A. E., & Desimone, R. (2001) · Science · doi:10.1126/science.1055465 · Cited by 2,786 · see citing works
Self-citationNatural Image Statistics and Neural Representation
Simoncelli, E. P., & Olshausen, B. A. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.1193 · Cited by 2,460 · see citing works
Selective Attention Gates Visual Processing in the Extrastriate Cortex
Moran, J., & Desimone, R. (1985) · Science · doi:10.1126/science.4023713 · Cited by 2,433 · see citing works
Selective Attention Gates Visual Processing in the Extrastriate Cortex
Moran, J., & Desimone, R. (2003) · The MIT Press eBooks · doi:10.7551/mitpress/2834.003.0024 · Cited by 2,164 · see citing works
Mechanisms of visual attention in the human cortex
Ungerleider, S. K. A. L. G. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.315 · Cited by 2,159 · see citing works
Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex
McCormick, D. A., Connors, B. W., Lighthall, J. W., & Prince, D. A. (1985) · Journal of Neurophysiology · doi:10.1152/jn.1985.54.4.782 · Cited by 1,935 · see citing works
Visual attention within and around the field of focal attention: A zoom lens model
Eriksen, C. W., & St. James, J. D. (1986) · Perception & Psychophysics · doi:10.3758/bf03211502 · Cited by 1,907 · see citing works
Normalization of cell responses in cat striate cortex
Heeger, D. J. (1992) · Visual Neuroscience · doi:10.1017/s0952523800009640 · Cited by 1,835 · see citing works
Self-citationKastner, S., Pinsk, M. A., De Weerd, P., Desimone, R., & Ungerleider, L. G. (1999) · Neuron · doi:10.1016/s0896-6273(00)80734-5 · Cited by 1,622 · see citing works
Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex
Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.1.24 · Cited by 1,615 · see citing works
Feature-based attention influences motion processing gain in macaque visual cortex
Treue, S., & Trujillo, J. C. M. (1999) · Nature · doi:10.1038/21176 · Cited by 1,465 · see citing works
Correlated neuronal activity and the flow of neural information
Salinas, E., & Sejnowski, T. J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35086012 · Cited by 1,333 · see citing works
Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit
Hahnloser, R. H. R., Sarpeshkar, R., Mahowald, M. A., Douglas, R. J., & Seung, H. S. (2000) · Nature · doi:10.1038/35016072 · Cited by 1,293 · see citing works
Principles of rhythmic motor pattern generation
Marder, E. E., & Calabrese, R. (1996) · Physiological Reviews · doi:10.1152/physrev.1996.76.3.687 · Cited by 1,287 · see citing works
Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4
Reynolds, J. H., Chelazzi, L., & Desimone, R. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-05-01736.1999 · Cited by 1,236 · see citing works
Self-citationEffects 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 1,214 · see citing works
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 · see citing works
Self-citationSelective gating of visual signals by microstimulation of frontal cortex
Moore, T., & Armstrong, K. M. (2003) · Nature · doi:10.1038/nature01341 · Cited by 1,156 · see citing works
A neural basis for visual search in inferior temporal cortex
Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (1993) · Nature · doi:10.1038/363345a0 · Cited by 1,114 · see citing works
Allocation of attention in the visual field.
Eriksen, C. W., & Yeh, Y. (1985) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.11.5.583 · Cited by 1,094 · see citing works
Computational Models of Visual Processing
(1991) · The MIT Press eBooks · doi:10.7551/mitpress/2002.001.0001 · Cited by 1,086 · see citing works
Motter, B. C. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.70.3.909 · Cited by 1,055 · see citing works
Attentional modulation of visual motion processing in cortical areas MT and MST
Treue, S., & Maunsell, J. H. R. (1996) · Nature · doi:10.1038/382539a0 · Cited by 1,025 · see citing works
Chalupa, L. M., Werner, J. S., & Barnstable, C. J. (2004) · Cited by 1,020 · see citing works
Attention Increases Sensitivity of V4 Neurons
Reynolds, J. H., Pasternak, T., & Desimone, R. (2000) · Neuron · doi:10.1016/s0896-6273(00)81206-4 · Cited by 1,017 · see citing works
Self-citationGain 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 · see citing works
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 956 · see citing works
A 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 · see citing works
Self-citationThe columnar organization of the neocortex.
Mountcastle, V. B. (1997) · Brain : a journal of neurology · doi:10.1093/brain/120.4.701 · Cited by 941 · see citing works
Brain States: Top-Down Influences in Sensory Processing
Gilbert, C. D., & Sigman, M. (2007) · Neuron · doi:10.1016/j.neuron.2007.05.019 · Cited by 936 · see citing works
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 · see citing works
Self-citationSpatial 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 · see citing works
Natural signal statistics and sensory gain control
Schwartz, O., & Simoncelli, E. P. (2001) · Nature Neuroscience · doi:10.1038/90526 · Cited by 835 · see citing works
Increased Attention Enhances Both Behavioral and Neuronal Performance
Spitzer, H., Desimone, R., & Moran, J. (1988) · Science · doi:10.1126/science.3353728 · Cited by 815 · see citing works
Nature and Interaction of Signals From the Receptive Field Center and Surround in Macaque V1 Neurons
Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00692.2001 · Cited by 784 · see citing works
Response properties of vibrissa units in rat SI somatosensory neocortex
Simons, D. J. (1978) · Journal of Neurophysiology · doi:10.1152/jn.1978.41.3.798 · Cited by 771 · see citing works
On the actions that one nerve cell can have on another: distinguishing “drivers” from “modulators”
Sherman, S. M., & Guillery, R. W. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.12.7121 · Cited by 746 · see citing works
Responses of Neurons in Inferior Temporal Cortex During Memory-Guided Visual Search
Chelazzi, L., Duncan, J., Miller, E. K., & Desimone, R. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.6.2918 · Cited by 726 · see citing works
Attention modulates synchronized neuronal firing in primate somatosensory cortex
Steinmetz, P. N., Roy, A., Fitzgerald, P. J., Hsiao, S. S., Johnson, K. O., & Niebur, E. (2000) · Nature · doi:10.1038/35004588 · Cited by 725 · see citing works
Lateral inhibition between orientation detectors in the cat's visual cortex
Blakemore, C. B., & Tobin, E. (1972) · Experimental Brain Research · doi:10.1007/bf00234129 · Cited by 703 · see citing works
Feature-Based Attention Increases the Selectivity of Population Responses in Primate Visual Cortex
Martinez-Trujillo, J. C., & Treue, S. (2004) · Current Biology · doi:10.1016/j.cub.2004.04.028 · Cited by 697 · see citing works
Differential attention-dependent response modulation across cell classes in macaque visual area V4
Mitchell, J. F., Sundberg, K. A., & Reynolds, J. H. (2007) · Neuron · doi:10.1016/j.neuron.2007.06.018 · Cited by 665 · see citing works
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 · see citing works
Hasenstaub, A. R., Shu, Y., Haider, B., Kraushaar, U., Duque, A., & McCormick, D. A. (2005) · Neuron · doi:10.1016/j.neuron.2005.06.016 · Cited by 654 · see citing works
Contour Enhancement, Short Term Memory, and Constancies in Reverberating Neural Networks
Grossberg, S. (1982) · Boston studies in the philosophy of science · doi:10.1007/978-94-009-7758-7_8 · Cited by 652 · see citing works
Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4
Bichot, N. P., Rossi, A. F., & Desimone, R. (2005) · Science · doi:10.1126/science.1109676 · Cited by 651 · see citing works
Control of eye movements and spatial attention
Moore, T., & Fallah, M. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.3.1273 · Cited by 649 · see citing works
Summation and Division by Neurons in Primate Visual Cortex
Carandini, M., & Heeger, D. J. (1994) · Science · doi:10.1126/science.8191289 · Cited by 649 · see citing works
Self-citationContour Enhancement, Short Term Memory, and Constancies in Reverberating Neural Networks
Grossberg, S. (1973) · Studies in Applied Mathematics · doi:10.1002/sapm1973523213 · Cited by 638 · see citing works
Allman, J. M., Miezin, F. M., & McGuinness, E. R. (1985) · Perception · doi:10.1068/p140105 · Cited by 635 · see citing works
Tracking multiple targets with multifocal attention
Cavanagh, P., & ALVAREZ, G. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.05.009 · Cited by 633 · see citing works
Receptive field organization of complex 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.sp012489 · Cited by 623 · see citing works
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 · see citing works
Allocation of attention in the visual field.
Eriksen, C. W., & Yeh, Y. (1985) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.11.5.583 · Cited by 607 · see citing works
LOCAL CIRCUITS IN PRIMARY VISUAL CORTEX OF THE MACAQUE MONKEY
Callaway, E. M. (1998) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.21.1.47 · Cited by 603 · see citing works
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 · see citing works
The physiological basis of attentional modulation in extrastriate visual areas
Chawla, D., Rees, G. E., & Friston, K. J. (1999) · Nature Neuroscience · doi:10.1038/10230 · Cited by 536 · see citing works
The effect of contrast on the transfer properties of cat retinal ganglion cells.
Shapley, R. M., & Victor, J. D. (1978) · The Journal of Physiology · doi:10.1113/jphysiol.1978.sp012571 · Cited by 528 · see citing works
Fast and Slow Contrast Adaptation in Retinal Circuitry
Baccus, S. A., & Meister, M. (2002) · Neuron · doi:10.1016/s0896-6273(02)01050-4 · Cited by 515 · see citing works
Contrast dependence of contextual effects in primate visual cortex
Levitt, J. B., & Lund, J. S. (1997) · Nature · doi:10.1038/387073a0 · Cited by 510 · see citing works
Activity in primary visual cortex predicts performance in a visual detection task
Ress, D. B., Backus, B. T., & Heeger, D. J. (2000) · Nature Neuroscience · doi:10.1038/78856 · Cited by 501 · see citing works
Self-citationNeural correlates of attentive selection for color or luminance in extrastriate area V4
Motter, B. C. (1994) · Journal of Neuroscience · doi:10.1523/jneurosci.14-04-02178.1994 · Cited by 482 · see citing works
Bonds, A. B. (1989) · Visual Neuroscience · doi:10.1017/s0952523800004314 · Cited by 477 · see citing works
Length and width tuning of neurons in the cat's primary visual cortex
DeAngelis, G. C., Freeman, R. D., & Ohzawa, I. (1994) · Journal of Neurophysiology · doi:10.1152/jn.1994.71.1.347 · Cited by 475 · see citing works
Acetylcholine contributes through muscarinic receptors to attentional modulation in V1
Herrero, J. L., Roberts, M. J., Delicato, L. S., Gieselmann, M. A., Dayan, P., & Thiele, A. (2008) · Nature · doi:10.1038/nature07141 · Cited by 459 · see citing works
The response of area MT and V1 neurons to transparent motion
Snowden, R., Treue, S., Erickson, R. G., & Andersen, R. A. (1991) · Journal of Neuroscience · doi:10.1523/jneurosci.11-09-02768.1991 · Cited by 457 · see citing works
State dependent activity in monkey visual cortex
Haenny, P. E., & Schiller, P. H. (1988) · Experimental Brain Research · doi:10.1007/bf00247569 · Cited by 443 · see citing works
A different universe: reinventing physics from the bottom down
(2005) · Choice Reviews Online · doi:10.5860/choice.43-1629 · Cited by 442 · see citing works
Scale Mixtures of Gaussians and the Statistics of Natural Images
Wainwright, M. J., & Simoncelli, E. P. (1999) · Cited by 439 · see citing works
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 · see citing works
Visual Coding and Adaptability
(2014) · Psychology Press eBooks · doi:10.4324/9781315803043 · Cited by 431 · see citing works
Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00693.2001 · Cited by 426 · see citing works
The Contribution of Noise to Contrast Invariance of Orientation Tuning in Cat Visual Cortex
Anderson, J. S., Lampl, I., Gillespie, D. C., & Ferster, D. (2000) · Science · doi:10.1126/science.290.5498.1968 · Cited by 422 · see citing works
Morrone, M. C., Burr, D. C., & Maffei, L. (1982) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1982.0078 · Cited by 421 · see citing works
Membrane Potential and Firing Rate in Cat Primary Visual Cortex
Carandini, M., & Ferster, D. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-01-00470.2000 · Cited by 413 · see citing works
Attentional Modulation Strength in Cortical Area MT Depends on Stimulus Contrast
Martínez-Trujillo, J., & Treue, S. (2002) · Neuron · doi:10.1016/s0896-6273(02)00778-x · Cited by 410 · see citing works
Interacting Roles of Attention and Visual Salience in V4
Reynolds, J. H., & Desimone, R. (2003) · Neuron · doi:10.1016/s0896-6273(03)00097-7 · Cited by 403 · see citing works
Self-citationProbabilistic Models of the Brain : Perception and Neural Function
Rao, R. P. N., Olshausen, B. A., & Lewicki, M. S. (2002) · Cited by 385 · see citing works
Independence of luminance and contrast in natural scenes and in the early visual system
Mante, V., Frazor, R. A., Bonin, V., Geisler, W. S., & Carandini, M. (2005) · Nature Neuroscience · doi:10.1038/nn1556 · Cited by 374 · see citing works
Neural mechanisms of object recognition
Riesenhuber, M., & Poggio, T. (2002) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(02)00304-5 · Cited by 373 · see citing works
State dependent activity in monkey visual cortex
Haenny, P. E., Maunsell, J. H. R., & Schiller, P. H. (1988) · Experimental Brain Research · doi:10.1007/bf00247570 · Cited by 364 · see citing works
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 · see citing works
Mapping the Matrix: The Ways of Neocortex
Douglas, R. J., & Martin, K. A. C. (2007) · Neuron · doi:10.1016/j.neuron.2007.10.017 · Cited by 355 · see citing works
Fast-spike Interneurons and Feedforward Inhibition in Awake Sensory Neocortex
Swadlow, H. A. (2002) · Cerebral Cortex · doi:10.1093/cercor/13.1.25 · Cited by 354 · see citing works
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 · see citing works
Microstimulation of the superior colliculus focuses attention without moving the eyes
Müller, J. R., Philiastides, M. G., & Newsome, W. T. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408311101 · Cited by 351 · see citing works
Verghese, P. (2001) · Neuron · doi:10.1016/s0896-6273(01)00392-0 · Cited by 347 · see citing works
Time Course and Time-Distance Relationships for Surround Suppression in Macaque V1 Neurons
Bair, W., Cavanaugh, J. R., & Movshon, J. A. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-20-07690.2003 · Cited by 345 · see citing works
Cortical mechanisms of space-based and object-based attentional control
Yantis, S., & Serences, J. T. (2003) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(03)00033-3 · Cited by 342 · see citing works
Constantinidis, C., & Goldman-Rakic, P. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00188.2002 · Cited by 337 · see citing works
Gain Modulation by Nicotine in Macaque V1
Disney, A. A., Aoki, C., & Hawken, M. J. (2007) · Neuron · doi:10.1016/j.neuron.2007.09.034 · Cited by 331 · see citing works
Bottom-Up Dependent Gating of Frontal Signals in Early Visual Cortex
Ekstrom, L. B., Roelfsema, P. R., Arsenault, J. T., Bonmassar, G., & Vanduffel, W. (2008) · Science · doi:10.1126/science.1153276 · Cited by 329 · see citing works
A model of multiplicative neural responses in parietal cortex.
Salinas, E., & Abbott, L. F. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.21.11956 · Cited by 319 · see citing works
Dynamics of spatial summation in primary visual cortex of alert monkeys
Kapadia, M. K., Westheimer, G., & Gilbert, C. D. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.21.12073 · Cited by 303 · see citing works
Multiple Spotlights of Attentional Selection in Human Visual Cortex
McMains, S. A., & Somers, D. C. (2004) · Neuron · doi:10.1016/s0896-6273(04)00263-6 · Cited by 301 · see citing works
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 · see citing works
The Attention Operating Characteristic: Examples from Visual Search
Sperling, G., & Melchner, M. J. (1978) · Science · doi:10.1126/science.694536 · Cited by 295 · see citing works
Quantitative aspects of repetitive firing of mammalian motoneurones, caused by injected currents
Granit, R., Kernell, D., & Shortess, G. K. (1963) · The Journal of Physiology · doi:10.1113/jphysiol.1963.sp007230 · Cited by 293 · see citing works
Neural correlates of feature selective memory and pop-out in extrastriate area V4
Motter, B. (1994) · Journal of Neuroscience · doi:10.1523/jneurosci.14-04-02190.1994 · Cited by 282 · see citing works
Computational 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 280 · see citing works
Self-citationHalf-squaring in responses of cat striate cells
Heeger, D. J. (1992) · Visual Neuroscience · doi:10.1017/s095252380001124x · Cited by 262 · see citing works
Self-citationIntracortical facilitation among co-oriented, co-axially aligned simple cells in cat striate cortex
Nelson, J. I., & Frost, B. J. (1985) · Experimental Brain Research · doi:10.1007/bf00235620 · Cited by 255 · see citing works
Task difficulty modulates the activity of specific neuronal populations in primary visual cortex
Chen, Y., Martínez‐Conde, S., Macknik, S. L., Bereshpolova, Y., Swadlow, H. A., & Alonso, J. (2008) · Nature Neuroscience · doi:10.1038/nn.2147 · Cited by 251 · see citing works
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 · see citing works
Direct afferent excitation and long-term potentiation of hippocampal interneurons.
Buzsáki, G., & Eidelberg, E. (1982) · Journal of Neurophysiology · doi:10.1152/jn.1982.48.3.597 · Cited by 246 · see citing works
Lu, Z., & Dosher, B. A. (2008) · Psychological Review · doi:10.1037/0033-295x.115.1.44 · Cited by 245 · see citing works
Modeling simple-cell direction selectivity with normalized, half-squared, linear operators
Heeger, D. J. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.70.5.1885 · Cited by 240 · see citing works
Self-citationThe Suppressive Field of Neurons in Lateral Geniculate Nucleus
Bonin, V., Mante, V., & Carandini, M. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.3562-05.2005 · Cited by 239 · see citing works
Neurodynamics of Biased Competition and Cooperation for Attention: A Model With Spiking Neurons
Deco, G., & Rolls, E. T. (2005) · Journal of Neurophysiology · doi:10.1152/jn.01095.2004 · Cited by 238 · see citing works
Extraretinal representations in area V4 in the macaque monkey
Maunsell, J. H. R., Sclar, G., Nealey, T. A., & DePriest, D. D. (1991) · Visual Neuroscience · doi:10.1017/s095252380001035x · Cited by 237 · see citing works
Subcortical Modulation of Attention Counters Change Blindness
Cavanaugh, J. R., & Wurtz, R. H. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.3724-04.2004 · Cited by 237 · see citing works
Neural Correlates of Sustained Spatial Attention in Human Early Visual Cortex
Silver, M. A., Ress, D. B., & Heeger, D. J. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00677.2006 · Cited by 237 · see citing works
Self-citationThe dynamics of the cat retinal X cell centre.
Victor, J. D. (1987) · The Journal of Physiology · doi:10.1113/jphysiol.1987.sp016531 · Cited by 232 · see citing works
Seeing multiple directions of motion—physiology and psychophysics
Treue, S., Hol, K., & Rauber, H.-J. (2000) · Nature Neuroscience · doi:10.1038/72985 · Cited by 229 · see citing works
Miller, E. K., Gochin, P. M., & Gross, C. G. (1993) · Brain Research · doi:10.1016/0006-8993(93)90187-r · Cited by 229 · see citing works
Object-based attention determines dominance in binocular rivalry
Mitchell, J. F., Stoner, G. R., & Reynolds, J. H. (2004) · Nature · doi:10.1038/nature02584 · Cited by 229 · see citing works
Self-citationGain control of firing rate by shunting inhibition: Roles of synaptic noise and dendritic saturation
Prescott, S. A., & De Koninck, Y. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0337591100 · Cited by 226 · see citing works
Model for Visual Luminance Discrimination and Flicker Detection
Sperling, G., & Sondhi, M. M. (1968) · Journal of the Optical Society of America · doi:10.1364/josa.58.001133 · Cited by 222 · see citing works
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 · see citing works
Self-citationMultiple Object Response Normalization in Monkey Inferotemporal Cortex
Zoccolan, D., Cox, D., & DiCarlo, J. J. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.2058-05.2005 · Cited by 218 · see citing works
Figure-ground mechanisms provide structure for selective attention
Qiu, F. T., Sugihara, T., & von der Heydt, R. (2007) · Nature Neuroscience · doi:10.1038/nn1989 · Cited by 218 · see citing works
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 · see citing works
Kaplan, E., Purpura, K. P., & Shapley, R. M. (1987) · The Journal of Physiology · doi:10.1113/jphysiol.1987.sp016737 · Cited by 207 · see citing works
Spatial Summation in the Receptive Fields of MT Neurons
Britten, K. H., & Heuer, H. W. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-12-05074.1999 · Cited by 200 · see citing works
How the contrast gain control modifies the frequency responses of cat retinal ganglion cells.
Shapley, R. M., & Victor, J. D. (1981) · The Journal of Physiology · doi:10.1113/jphysiol.1981.sp013856 · Cited by 200 · see citing works
State changes rapidly modulate cortical neuronal responsiveness
Hasenstaub, A., Sachdev, R. N. S., & McCormick, D. A. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.2184-07.2007 · Cited by 196 · see citing works
Carrasco, M. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)54003-8 · Cited by 174 · see citing works
Intermodal Selective Attention in Monkeys. II: Physiological Mechanisms of Modulation
Mehta, A. D. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.4.359 · Cited by 172 · see citing works
Responses 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 · see citing works
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 163 · see citing works
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 157 · see citing works
Visual responses of inferior temporal neurons in awake rhesus monkey
Richmond, B. J., Wurtz, R. H., & Sato, T. (1983) · Journal of Neurophysiology · doi:10.1152/jn.1983.50.6.1415 · Cited by 155 · see citing works
Spatial vision in humans and robots
Harris, L. R., & Jenkin, M. R. M. (1994) · Cited by 155 · see citing works
Drivers 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 · see citing works
Rolls, E. T., & Tovée, M. J. (1995) · Experimental Brain Research · doi:10.1007/bf00241500 · Cited by 153 · see citing works
A Feedback Model of Visual Attention
Spratling, M., & Johnson, M. H. (2004) · Journal of Cognitive Neuroscience · doi:10.1162/089892904322984526 · Cited by 152 · see citing works
Dynamics of feature binding during object-selective attention
Schoenfeld, M. A., Tempelmann, C., Martı́nez, A., Hopf, J., Sattler, C., Heinze, H. –., & Hillyard, S. A. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1932820100 · Cited by 151 · see citing works
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 · see citing works
Attention and visual perception
Boynton, G. M. (2005) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2005.06.009 · Cited by 138 · see citing works
Contrast Dependence of Response Normalization in Area MT of the Rhesus Macaque
Heuer, H. W., & Britten, K. H. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00255.2002 · Cited by 136 · see citing works
Effects of Attention on MT and MST Neuronal Activity During Pursuit Initiation
Recanzone, G. H., & Wurtz, R. H. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.83.2.777 · Cited by 131 · see citing works
Nonlinear Model of Neural Responses in Cat Visual Cortex
Heeger, D. J. (1991) · The MIT Press eBooks · doi:10.7551/mitpress/2002.003.0014 · Cited by 127 · see citing works
Self-citationSato, T. (1989) · Experimental Brain Research · doi:10.1007/bf00250563 · Cited by 125 · see citing works
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 · see citing works
Vision and attention: the role of training
Braun, J. (1998) · Nature · doi:10.1038/30875 · Cited by 108 · see citing works
Spatial Attention and the Latency of Neuronal Responses in Macaque Area V4
Lee, J., Williford, T. H., & Maunsell, J. H. R. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2734-07.2007 · Cited by 105 · see citing works
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 · see citing works
Tolhurst, D. J., & Heeger, D. J. (1997) · Visual Neuroscience · doi:10.1017/s0952523800011433 · Cited by 99 · see citing works
Self-citationPreparing to Move Increases the Sensitivity of Superior Colliculus Neurons
Li, X., & Basso, M. A. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.5683-07.2008 · Cited by 92 · see citing works
Inhibitory refinement of spatial frequency selectivity in single cells of the cat striate cortex
Bauman, L. A., & Bonds, A. B. (1991) · Vision Research · doi:10.1016/0042-6989(91)90201-f · Cited by 89 · see citing works
Circuits that build visual cortical receptive fields
Hirsch, J. A., & Martı́nez, L. M. (2005) · Trends in Neurosciences · doi:10.1016/j.tins.2005.11.001 · Cited by 87 · see citing works
Ghose, G. M., & Maunsell, J. H. R. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.0138-08.2008 · Cited by 85 · see citing works
Attention to object files defined by transparent motion.
Valdés-Sosa, M. J., Cobo, A., & Pinilla, T. (2000) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.26.2.488 · Cited by 83 · see citing works
Specialized Circuits from Primary Visual Cortex to V2 and Area MT
Nassi, J. J., & Callaway, E. M. (2007) · Neuron · doi:10.1016/j.neuron.2007.07.037 · Cited by 71 · see citing works
The role of early visual cortex in visual short-term memory and visual attention
Offen, S., Schluppeck, D., & Heeger, D. J. (2008) · Vision Research · doi:10.1016/j.visres.2007.12.022 · Cited by 69 · see citing works
Self-citationDistinct Mechanisms for Top-Down Control of Neural Gain and Sensitivity in the Owl Optic Tectum
Winkowski, D. E., & Knudsen, E. I. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.013 · Cited by 66 · see citing works
Mishra, J., Fellous, J., & B, T. J. S. A. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.08.005 · Cited by 65 · see citing works
Khoe, W., Mitchell, J. F., Reynolds, J. H., & Hillyard, S. A. (2005) · Vision Research · doi:10.1016/j.visres.2005.04.021 · Cited by 64 · see citing works
Self-citationHamker, F. H., & Zirnsak, M. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.08.006 · Cited by 54 · see citing works
Joshi, S., & Hawken, M. J. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2006.02.004 · Cited by 51 · see citing works
Responses of macaque inferior temporal neurons to overlapping shapes
Missal, M. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.8.758 · Cited by 50 · see citing works
Receptive fields and suppressive fields in the early visual system
Carandini, M. (2004) · Cited by 44 · see citing works
Model of visual motion sensing
Heeger, D. J., & Simoncelli, E. P. (1994) · Cited by 43 · see citing works
Self-citationTolhurst, D. J., & Heeger, D. J. (1997) · Visual Neuroscience · doi:10.1017/s0952523800008725 · Cited by 38 · see citing works
Self-citationModeling the Apparent Frequency-specific Suppression in Simple Cell Responses
Nestares, O., & Heeger, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(96)00268-4 · Cited by 21 · see citing works
Self-citationLocal Analysis of Visual Motion
Simoncelli, E. P. (2003) · The MIT Press eBooks · doi:10.7551/mitpress/7131.003.0124 · Cited by 20 · see citing works
Flagged first, then by citations
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Sorted by citations
The free-energy principle: a unified brain theory?
Friston, K. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2787 · Cited by 8,120 · see citing works
Rhythms for cognition: communication through coherence
Fries, P. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.034 · Cited by 2,725 · see citing works
Normalization as a canonical neural computation
Carandini, M., & Heeger, D. J. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3136 · Cited by 1,906 · see citing works
Self-citationHow Inhibition Shapes Cortical Activity
Isaacson, J. S., & Scanziani, M. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.027 · Cited by 1,678 · see citing works
Attention, uncertainty, and free-energy
Feldman, H., & Friston, K. J. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00215 · Cited by 1,365 · see citing works
Spectral fingerprints of large-scale neuronal interactions
Siegel, M., Donner, T. H., & Engel, A. K. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3137 · Cited by 1,295 · see citing works
Top-down influences on visual processing
Gilbert, C. D., & Li, W. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3476 · Cited by 1,224 · see citing works
Robertson, C. E., & Baron-Cohen, S. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.112 · Cited by 1,157 · see citing works
Expectation (and attention) in visual cognition
Summerfield, C., & Egner, T. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.06.003 · Cited by 950 · see citing works
Waking state: rapid variations modulate neural and behavioral responses
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.012 · Cited by 801 · see citing works
“Particularly interesting are multiplicative amplitude modulations of the response tuning function since they preserve feature selectivity (Desimone and Duncan, 1995; McAdams and Maunsell, 1999a, b; Reynolds and Heeger, 2009).”
Long-range and local circuits for top-down modulation of visual cortex processing
Zhang, S., Xu, M., Kamigaki, T., Hoang Do, J. P., Chang, W.-C., Jenvay, S., Miyamichi, K., Luo, L., & Dan, Y. (2014) · Science · doi:10.1126/science.1254126 · Cited by 804 · see citing works
Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4
Mitchell, J. F., Sundberg, K. A., & Reynolds, J. H. (2009) · Neuron · doi:10.1016/j.neuron.2009.09.013 · Cited by 710 · see citing works
Self-citationMather, M., Clewett, D., Sakaki, M., & Harley, C. W. (2016) · Behavioral and Brain Sciences · doi:10.1017/s0140525x15000667 · Cited by 695 · see citing works
Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex
Kerlin, A. M., Andermann, M. L., Berezovskii, V. K., & Reid, R. C. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.002 · Cited by 613 · see citing works
Action understanding and active inference
Friston, K., Mattout, J., & Kilner, J. (2011) · Biological Cybernetics · doi:10.1007/s00422-011-0424-z · Cited by 665 · see citing works
Division 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 · see citing works
Divisive 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 · see citing works
Towards a neuroscience of active sampling and curiosity
Gottlieb, J., & Oudeyer, P.-Y. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0078-0 · Cited by 494 · see citing works
Attention reverses the effect of prediction in silencing sensory signals
Kok, P., Rahnev, D., Jehee, J. F. M., Lau, H. C., & de Lange, F. P. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr310 · Cited by 430 · see citing works
Neural mechanisms of selective visual attention.
Moore, T., & Zirnsak, M. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033400 · Cited by 471 · see citing works
Rapid Neocortical Dynamics: Cellular and Network Mechanisms
Haider, B., & McCormick, D. A. (2009) · Neuron · doi:10.1016/j.neuron.2009.04.008 · Cited by 441 · see citing works
Mechanisms of top-down attention
Baluch, F., & Itti, L. (2011) · Trends in Neurosciences · doi:10.1016/j.tins.2011.02.003 · Cited by 437 · see citing works
The Border Between Seeing and Thinking
Block, N. (2023) · doi:10.1093/oso/9780197622223.001.0001 · Cited by 367 · see citing works
Thiele, A., & Bellgrove, M. A. (2018) · Neuron · doi:10.1016/j.neuron.2018.01.008 · Cited by 350 · see citing works
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 · see citing works
Not Noisy, Just Wrong: The Role of Suboptimal Inference in Behavioral Variability
Beck, J. M., Ma, W. J., Pitkow, X., Latham, P. E., & Pouget, A. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.016 · Cited by 316 · see citing works
A normalization model of multisensory integration
Ohshiro, T., Angelaki, D. E., & DeAngelis, G. C. (2011) · Nature Neuroscience · doi:10.1038/nn.2815 · Cited by 320 · see citing works
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 · see citing works
“In addition to sensory processing, the divisive normalization model has been used to characterize attentional effects in visual cortex (Reynolds and Heeger, 2009).”
BackgroundMethodInfluentialDissociable prior influences of signal probability and relevance on visual contrast sensitivity
Wyart, V., Nobre, A. C., & Summerfield, C. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1120118109 · Cited by 268 · see citing works
Distinct neural mechanisms of distractor suppression in the frontal and parietal lobe
Suzuki, M., & Gottlieb, J. (2013) · Nature Neuroscience · doi:10.1038/nn.3282 · Cited by 281 · see citing works
Prefrontal contributions to visual selective attention
Squire, R. F., Noudoost, B., Schafer, R. J., & Moore, T. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150439 · Cited by 260 · see citing works
A 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 · see citing works
Representation of Concurrent Stimuli by Population Activity in Visual Cortex
Busse, L., Wade, A. R., & Carandini, M. (2009) · Neuron · doi:10.1016/j.neuron.2009.11.004 · Cited by 247 · see citing works
Locomotion controls spatial integration in mouse visual cortex
Ayaz, A., Saleem, A. B., Schölvinck, M. L., & Carandini, M. (2013) · Current Biology · doi:10.1016/j.cub.2013.04.012 · Cited by 249 · see citing works
Attention, learning, and the value of information
Gottlieb, J. (2012) · Neuron · doi:10.1016/j.neuron.2012.09.034 · Cited by 241 · see citing works
“…this system has shown that attention affects sensory representations at all levels of the visual hierarchy, starting from low-level areas such as the lateral geniculate nucleus, through high-level cortical areas in the inferior temporal lobe (Reynolds and Heeger, 2009; Saalmann and Kastner, 2011).”
BackgroundMethodInfluentialPrediction and memory: A predictive coding account
Barron, H. C., Auksztulewicz, R., & Friston, K. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101821 · Cited by 220 · see citing works
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 · see citing works
Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
Butlin, P., Long, R., Elmoznino, E., Bengio, Y., Birch, J., Constant, A., Deane, G., Fleming, S. M., Frith, C., Ji, X., et al. (2023) · arXiv · doi:10.48550/arxiv.2308.08708 · Cited by 196 · see citing works
Learning what to expect (in visual perception)
Seriès, P., & Seitz, A. R. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00668 · Cited by 194 · see citing works
Attention stabilizes the shared gain of V4 populations
Rabinowitz, N. C., Goris, R. L., Cohen, M., & Simoncelli, E. P. (2015) · eLife · doi:10.7554/elife.08998 · Cited by 194 · see citing works
Buzsáki, G., & Llinás, R. (2017) · Science · doi:10.1126/science.aan8869 · Cited by 175 · see citing works
Laminar fMRI: applications for cognitive neuroscience
Lawrence, S. J. D., Formisano, E., Muckli, L., & de Lange, F. P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.004 · Cited by 186 · see citing works
Wei, Z., Wang, X.-J., & Wang, D.-H. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.0735-12.2012 · Cited by 163 · see citing works
Spatial attention alters visual appearance
Carrasco, M., & Barbot, A. (2019) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.10.010 · Cited by 161 · see citing works
Why Does Space Feel the Way it Does? Towards a Principled Account of Spatial Experience
Haun, A., & Tononi, G. (2019) · Entropy · doi:10.3390/e21121160 · Cited by 143 · see citing works
A computational perspective on autism
Rosenberg, A., Patterson, J. S., & Angelaki, D. E. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510583112 · Cited by 156 · see citing works
Mineault, P. J., Tring, E., Trachtenberg, J. T., & Ringach, D. L. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.0430-16.2016 · Cited by 148 · see citing works
Kaliukhovich, D. A., & Vogels, R. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq207 · Cited by 131 · see citing works
Automatic versus Choice-Dependent Value Representations in the Human Brain
Grueschow, M., Polania, R., Hare, T. A., & Ruff, C. C. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.054 · Cited by 130 · see citing works
Grossberg, S. (2017) · Neural Networks · doi:10.1016/j.neunet.2016.11.003 · Cited by 120 · see citing works
Thalamic contributions to the state and contents of consciousness
Whyte, C. J., Redinbaugh, M. J., Shine, J. M., & Saalmann, Y. B. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.019 · Cited by 105 · see citing works
Predictive Coding in Sensory Cortex
Kok, P., & de Lange, F. P. (2015) · An Introduction to Model-Based Cognitive Neuroscience · doi:10.1007/978-1-4939-2236-9_11 · Cited by 98 · see citing works
On the Structure of Neuronal Population Activity under Fluctuations in Attentional State
Ecker, A. S., Denfield, G. H., Bethge, M., & Tolias, A. S. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.2044-15.2016 · Cited by 88 · see citing works
Ekstrom, L. B., Roelfsema, P. R., Arsenault, J. T., Kolster, H., & Vanduffel, W. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.0673-09.2009 · Cited by 83 · see citing works
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Wieser, M. J., & Keil, A. (2020) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2020.05.004 · Cited by 72 · see citing works
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Phillips, W. A. (2017) · Brain and Cognition · doi:10.1016/j.bandc.2015.09.005 · Cited by 62 · see citing works
Response-dependent dynamics of cell-specific inhibition in cortical networks in vivo
El-Boustani, S., & Sur, M. (2014) · Nature Communications · doi:10.1038/ncomms6689 · Cited by 61 · see citing works
Modulation of visual physiology by behavioral state in monkeys, mice, and flies
Maimon, G. (2011) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2011.05.001 · Cited by 56 · see citing works
Montijn, J. S., Goltstein, P. M., & Pennartz, C. M. (2015) · eLife · doi:10.7554/elife.10163 · Cited by 46 · see citing works
Niyogi, R. K., & Wong-Lin, K. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003099 · Cited by 47 · see citing works
Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains
Litwin-Kumar, A., Oswald, A.-M. M., Urban, N. N., & Doiron, B. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002305 · Cited by 46 · see citing works
Wilterson, A. I., & Graziano, M. S. A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2102421118 · Cited by 26 · see citing works
Muscarinic and Nicotinic Contribution to Contrast Sensitivity of Macaque Area V1 Neurons
Herrero, J. L., Gieselmann, M. A., & Thiele, A. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00106 · Cited by 25 · see citing works
Multiplicative mixing of object identity and image attributes in single inferior temporal neurons
Ratan Murty, N. A., & Arun, S. P. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714287115 · Cited by 15 · see citing works
The Cooperative Neuron: Cellular Foundations of Mental Life
Phillips, W. A. (2023) · doi:10.1093/oso/9780198876984.001.0001 · Cited by 13 · see citing works
- Authors
- Reynolds, J. H., & Heeger, D. J.
- Affiliations
- Salk Institute for Biological Studies (US)
- New York University (US)
- Corresponding author
- Reynolds, John H.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 61
- Issue
- 2
- Pages
- 168-185
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC2752446
- OpenAlex
- W2149166988
- Cited by
- 1,457
- References
- 174
- Citations by year
- 2026: 72 · 2025: 92 · 2024: 86 · 2023: 123 · 2022: 79 · 2021: 94 · 2020: 85 · 2019: 106 · 2018: 77 · 2017: 73 · 2016: 73 · 2015: 83 · 2014: 96 · 2013: 77 · 2012: 72
- FWCI
- 5.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01ey016161-05)
- National Institute of Mental Health (R01-MH69880, R01MH069880)
- National Eye Institute (R01-EY016161, R01EY013802)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- attention, normalization model, visual cortex, attentional modulation, selective attention, attentional strategies, neural responses, stimulus conditions
- MeSH terms
- Action Potentials, Animals, Attention, Computer Simulation, Humans, Models, Neurological, Neurons, Visual Cortex, Visual Fields, Visual Perception, Contrast Sensitivity
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.
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