Do We Know What the Early Visual System Does?

We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single “standard model” for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.

[1]  S. W. Kuffler Discharge patterns and functional organization of mammalian retina. , 1953, Journal of neurophysiology.

[2]  H. Barlow,et al.  MAINTAINED ACTIVITY IN THE CAT'S RETINA IN LIGHT AND DARKNESS , 1957, The Journal of general physiology.

[3]  D. Hubel,et al.  Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.

[4]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[5]  A. Hodgkin,et al.  Changes in time scale and sensitivity in the ommatidia of Limulus , 1964, The Journal of physiology.

[6]  C. Enroth-Cugell,et al.  The contrast sensitivity of retinal ganglion cells of the cat , 1966, The Journal of physiology.

[7]  B. Cleland,et al.  Quantitative aspects of sensitivity and summation in the cat retina , 1968, The Journal of physiology.

[8]  P Kuyper,et al.  Triggered correlation. , 1968, IEEE transactions on bio-medical engineering.

[9]  P. O. Bishop,et al.  Spatial vision. , 1971, Annual review of psychology.

[10]  L. Maffei,et al.  Neural Correlate of Perceptual Adaptation to Gratings , 1973, Science.

[11]  C. Enroth-Cugell,et al.  Flux, not retinal illumination, is what cat retinal ganglion cells really care about , 1973, The Journal of physiology.

[12]  C. Enroth-Cugell,et al.  Adaptation and dynamics of cat retinal ganglion cells , 1973, The Journal of physiology.

[13]  A. Hodgkin,et al.  Reconstruction of the electrical responses of turtle cones to flashes and steps of light , 1974, The Journal of physiology.

[14]  P Lennie,et al.  Surround contribution to light adaptation in cat retinal ganglion cells. , 1975, The Journal of physiology.

[15]  L. Maffei,et al.  The unresponsive regions of visual cortical receptive fields , 1976, Vision Research.

[16]  R. Shapley,et al.  Linear and nonlinear spatial subunits in Y cat retinal ganglion cells. , 1976, The Journal of physiology.

[17]  M. P. Friedman,et al.  HANDBOOK OF PERCEPTION , 1977 .

[18]  R. Shapley,et al.  The effect of contrast on the transfer properties of cat retinal ganglion cells. , 1978, The Journal of physiology.

[19]  F. Ratliff,et al.  The spatiotemporal transfer function of the Limulus lateral eye , 1978, The Journal of general physiology.

[20]  J. Movshon,et al.  Spatial summation in the receptive fields of simple cells in the cat's striate cortex. , 1978, The Journal of physiology.

[21]  J. Movshon,et al.  Receptive field organization of complex cells in the cat's striate cortex. , 1978, The Journal of physiology.

[22]  J. Victor Nonlinear systems analysis: comparison of white noise and sum of sinusoids in a biological system. , 1979, Proceedings of the National Academy of Sciences of the United States of America.

[23]  R. Shapley,et al.  Receptive field mechanisms of cat X and Y retinal ganglion cells , 1979, The Journal of general physiology.

[24]  G. Shepherd The Synaptic Organization of the Brain , 1979 .

[25]  R. Shapley,et al.  Nonlinear spatial summation and the contrast gain control of cat retinal ganglion cells. , 1979, The Journal of physiology.

[26]  D. Pollen,et al.  Relationship between spatial frequency selectivity and receptive field profile of simple cells. , 1979, The Journal of physiology.

[27]  E Kaplan,et al.  Effects of dark adaptation on spatial and temporal properties of receptive fields in cat lateral geniculate nucleus. , 1979, The Journal of physiology.

[28]  J. Daugman Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.

[29]  C. Enroth-Cugell,et al.  Suppression of cat retinal ganglion cell responses by moving patterns. , 1980, The Journal of physiology.

[30]  L. Palmer,et al.  Receptive-field structure in cat striate cortex. , 1981, Journal of neurophysiology.

[31]  J D Victor,et al.  How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. , 1981, The Journal of physiology.

[32]  R. Shapley,et al.  Spatial tuning of cells in and around lateral geniculate nucleus of the cat: X and Y relay cells and perigeniculate interneurons. , 1981, Journal of neurophysiology.

[33]  D. G. Albrecht,et al.  Striate cortex of monkey and cat: contrast response function. , 1982, Journal of neurophysiology.

[34]  D. Tolhurst,et al.  On the distinctness of simple and complex cells in the visual cortex of the cat. , 1983, The Journal of physiology.

[35]  R. Shapley,et al.  The receptive field organization of X-cells in the cat: Spatiotemporal coupling and asymmetry , 1984, Vision Research.

[36]  J. Movshon,et al.  Length summation in simple cells of cat striate cortex , 1984, Vision Research.

[37]  P. Lennie,et al.  Spatial and temporal contrast sensitivities of neurones in lateral geniculate nucleus of macaque. , 1984, The Journal of physiology.

[38]  C. Enroth-Cugell,et al.  Chapter 9 Visual adaptation and retinal gain controls , 1984 .

[39]  E H Adelson,et al.  Spatiotemporal energy models for the perception of motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[40]  P. Lennie,et al.  Spatial frequency analysis in the visual system. , 1985, Annual review of neuroscience.

[41]  Yoshiro Fukada,et al.  Gain control mechanisms in X- and Y-type retinal ganglion cells of the cat , 1986, Vision Research.

[42]  D. Field,et al.  The structure and symmetry of simple-cell receptive-field profiles in the cat’s visual cortex , 1986, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[43]  R. Desimone,et al.  Visual properties of neurons in area V4 of the macaque: sensitivity to stimulus form. , 1987, Journal of neurophysiology.

[44]  J. Victor The dynamics of the cat retinal X cell centre. , 1987, The Journal of physiology.

[45]  J. P. Jones,et al.  The two-dimensional spatial structure of simple receptive fields in cat striate cortex. , 1987, Journal of neurophysiology.

[46]  Klein,et al.  Nonlinear directionally selective subunits in complex cells of cat striate cortex. , 1987, Journal of neurophysiology.

[47]  C. Enroth-Cugell,et al.  The receptive‐field spatial structure of cat retinal Y cells. , 1987, The Journal of physiology.

[48]  E Kaplan,et al.  Contrast affects the transmission of visual information through the mammalian lateral geniculate nucleus. , 1987, The Journal of physiology.

[49]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[50]  A B Watson,et al.  Efficiency of a model human image code. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[51]  B. Cleland,et al.  Visual adaptation is highly localized in the cat's retina. , 1988, The Journal of physiology.

[52]  D. Ferster Spatially opponent excitation and inhibition in simple cells of the cat visual cortex , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[53]  William Bialek,et al.  Real-time performance of a movement-sensitive neuron in the blowfly visual system: coding and information transfer in short spike sequences , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[54]  L. Palmer,et al.  Contribution of linear spatiotemporal receptive field structure to velocity selectivity of simple cells in area 17 of cat , 1989, Vision Research.

[55]  N. Graham Visual Pattern Analyzers , 1989 .

[56]  A. B. Bonds Role of Inhibition in the Specification of Orientation Selectivity of Cells in the Cat Striate Cortex , 1989, Visual Neuroscience.

[57]  D. Tolhurst,et al.  The effect of threshold on the relationship between the receptive-field profile and the spatial-frequency tuning cure in simple cells of the cat's striate cortex , 1989, Visual Neuroscience.

[58]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[59]  A. L. Humphrey,et al.  Spatial and temporal response properties of lagged and nonlagged cells in cat lateral geniculate nucleus. , 1990, Journal of neurophysiology.

[60]  R. Shapley,et al.  Light adaptation in the primate retina: Analysis of changes in gain and dynamics of monkey retinal ganglion cells , 1990, Visual Neuroscience.

[61]  John H. R. Maunsell,et al.  Coding of image contrast in central visual pathways of the macaque monkey , 1990, Vision Research.

[62]  D. Tolhurst,et al.  Evaluation of a linear model of directional selectivity in simple cells of the cat's striate cortex , 1991, Visual Neuroscience.

[63]  D. G. Albrecht,et al.  Motion selectivity and the contrast-response function of simple cells in the visual cortex , 1991, Visual Neuroscience.

[64]  R. Shapley,et al.  Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex. , 1991, Journal of neurophysiology.

[65]  D. V. van Essen,et al.  Neuronal responses to static texture patterns in area V1 of the alert macaque monkey. , 1992, Journal of neurophysiology.

[66]  R. Desimone,et al.  Predicting responses of nonlinear neurons in monkey striate cortex to complex patterns , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[67]  D. Heeger Half-squaring in responses of cat striate cells , 1992, Visual Neuroscience.

[68]  I. Ohzawa,et al.  Organization of suppression in receptive fields of neurons in cat visual cortex. , 1992, Journal of neurophysiology.

[69]  D. Heeger Normalization of cell responses in cat striate cortex , 1992, Visual Neuroscience.

[70]  J. Robson,et al.  Steady discharges of X and Y retinal ganglion cells of cat under photopic illuminance , 1992, Visual Neuroscience.

[71]  M. J. M. Lankheet,et al.  The dynamics of light adaptation in cat horizontal cell responses , 1993, Vision Research.

[72]  J. Eggermont Wiener and Volterra analyses applied to the auditory system , 1993, Hearing Research.

[73]  I. Ohzawa,et al.  Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. II. Linearity of temporal and spatial summation. , 1993, Journal of neurophysiology.

[74]  D. Heeger Modeling simple-cell direction selectivity with normalized, half-squared, linear operators. , 1993, Journal of neurophysiology.

[75]  D. Ferster,et al.  Linearity of summation of synaptic potentials underlying direction selectivity in simple cells of the cat visual cortex. , 1993, Science.

[76]  M. J. M. Lankheet,et al.  The lateral spread of light adaptation in cat horizontal cell responses , 1993, Vision Research.

[77]  I. Ohzawa,et al.  Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. I. General characteristics and postnatal development. , 1993, Journal of neurophysiology.

[78]  M. Carandini,et al.  Summation and division by neurons in primate visual cortex. , 1994, Science.

[79]  Earl L. Smith,et al.  Transfer characteristics of lateral geniculate nucleus X neurons in the cat: effects of spatial frequency and contrast. , 1995, Journal of neurophysiology.

[80]  James R. Bergen,et al.  Pyramid-based texture analysis/synthesis , 1995, Proceedings., International Conference on Image Processing.

[81]  E. Kaplan,et al.  Dynamics of neurons in the cat lateral geniculate nucleus: in vivo electrophysiology and computational modeling. , 1995, Journal of neurophysiology.

[82]  H. Sakai,et al.  Response dynamics and receptive-field organization of catfish ganglion cells [published erratum appears in J Gen Physiol 1995 Aug;106(2):following 388] , 1995, The Journal of general physiology.

[83]  J. Atick,et al.  Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus , 1995 .

[84]  W. Guido,et al.  Burst responses in thalamic relay cells of the awake behaving cat. , 1995, Journal of neurophysiology.

[85]  Shinsuke Shimojo,et al.  Visual surface representation: a critical link between lower-level and higher level vision , 1995 .

[86]  Barry B. Lee,et al.  The time course of adaptation in macaque retinal ganglion cells , 1996, Vision Research.

[87]  D. C. Essen,et al.  Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey. , 1996, Journal of neurophysiology.

[88]  E. Bizzi,et al.  The Cognitive Neurosciences , 1996 .

[89]  R C Reid,et al.  Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory , 1996, The Journal of Neuroscience.

[90]  Michael J. Berry,et al.  Adaptation of retinal processing to image contrast and spatial scale , 1997, Nature.

[91]  B. Knight,et al.  Response variability and timing precision of neuronal spike trains in vivo. , 1997, Journal of neurophysiology.

[92]  J. Movshon,et al.  Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex , 1997, The Journal of Neuroscience.

[93]  D. Heeger,et al.  Comparison of contrast-normalization and threshold models of the responses of simple cells in cat striate cortex , 1997, Visual Neuroscience.

[94]  D. V. van Essen,et al.  Spatial Attention Effects in Macaque Area V4 , 1997, The Journal of Neuroscience.

[95]  R. Shapley,et al.  The use of m-sequences in the analysis of visual neurons: Linear receptive field properties , 1997, Visual Neuroscience.

[96]  J. Kremers,et al.  Temporal properties of marmoset lateral geniculate cells , 1997, Vision Research.

[97]  J A Solomon,et al.  Model of visual contrast gain control and pattern masking. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[98]  Edward E. Smith,et al.  An Invitation to cognitive science , 1997 .

[99]  G. DeAngelis,et al.  Spatiotemporal receptive field organization in the lateral geniculate nucleus of cats and kittens. , 1997, Journal of neurophysiology.

[100]  Michael J. Berry,et al.  The structure and precision of retinal spike trains. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[101]  D. Heeger,et al.  Contrast normalization and a linear model for the directional selectivity of simple cells in cat striate cortex , 1997, Visual Neuroscience.

[102]  R. Reid,et al.  Synaptic Integration in Striate Cortical Simple Cells , 1998, The Journal of Neuroscience.

[103]  C. Blakemore,et al.  Different mechanisms underlie three inhibitory phenomena in cat area 17 , 1998, Vision Research.

[104]  Eero P. Simoncelli,et al.  A model of neuronal responses in visual area MT , 1998, Vision Research.

[105]  R. W. Rodieck The First Steps in Seeing , 1998 .

[106]  E. Kaplan,et al.  The dynamics of primate M retinal ganglion cells , 1999, Visual Neuroscience.

[107]  J. Anthony Movshon,et al.  Linearity and gain control in V1 simple cells , 1999 .

[108]  I. Ohzawa,et al.  Linear and nonlinear contributions to orientation tuning of simple cells in the cat's striate cortex , 1999, Visual Neuroscience.

[109]  J. B. Demb,et al.  Functional Circuitry of the Retinal Ganglion Cell's Nonlinear Receptive Field , 1999, The Journal of Neuroscience.

[110]  William Bialek,et al.  Adaptive Rescaling Maximizes Information Transmission , 2000, Neuron.

[111]  K. Sen,et al.  Spectral-temporal Receptive Fields of Nonlinear Auditory Neurons Obtained Using Natural Sounds , 2022 .

[112]  J L Gallant,et al.  Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.

[113]  D. Fitzpatrick Seeing beyond the receptive field in primary visual cortex , 2000, Current Opinion in Neurobiology.

[114]  R. Reid,et al.  Low Response Variability in Simultaneously Recorded Retinal, Thalamic, and Cortical Neurons , 2000, Neuron.

[115]  M. Carandini,et al.  Membrane Potential and Firing Rate in Cat Primary Visual Cortex , 2000, The Journal of Neuroscience.

[116]  S. Sherman,et al.  Fourier analysis of sinusoidally driven thalamocortical relay neurons and a minimal integrate-and-fire-or-burst model. , 2000, Journal of neurophysiology.

[117]  R. Masland Neuronal diversity in the retina , 2001, Current Opinion in Neurobiology.

[118]  I. Ohzawa,et al.  Beyond the classical receptive field in the visual cortex. , 2001, Progress in brain research.

[119]  E. Chichilnisky,et al.  Adaptation to Temporal Contrast in Primate and Salamander Retina , 2001, The Journal of Neuroscience.

[120]  F. Rieke Temporal Contrast Adaptation in Salamander Bipolar Cells , 2001, The Journal of Neuroscience.

[121]  E J Chichilnisky,et al.  A simple white noise analysis of neuronal light responses , 2001, Network.

[122]  J. Gallant,et al.  Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. , 2001, Network.

[123]  C. Enroth-Cugell,et al.  Effects of Remote Stimulation on the Mean Firing Rate of Cat Retinal Ganglion Cells , 2001, The Journal of Neuroscience.

[124]  J. B. Demb,et al.  Bipolar Cells Contribute to Nonlinear Spatial Summation in the Brisk-Transient (Y) Ganglion Cell in Mammalian Retina , 2001, The Journal of Neuroscience.

[125]  Michael Shelley,et al.  How Simple Cells Are Made in a Nonlinear Network Model of the Visual Cortex , 2001, The Journal of Neuroscience.

[126]  F. Werblin,et al.  Vertical interactions across ten parallel, stacked representations in the mammalian retina , 2001, Nature.

[127]  D. Tolhurst,et al.  Characterizing the sparseness of neural codes , 2001, Network.

[128]  S. Sherman Tonic and burst firing: dual modes of thalamocortical relay , 2001, Trends in Neurosciences.

[129]  S. Laughlin,et al.  An Energy Budget for Signaling in the Grey Matter of the Brain , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[130]  Eero P. Simoncelli,et al.  Natural image statistics and neural representation. , 2001, Annual review of neuroscience.

[131]  Kerry J. Kim,et al.  Temporal Contrast Adaptation in the Input and Output Signals of Salamander Retinal Ganglion Cells , 2001, The Journal of Neuroscience.

[132]  D. Ferster,et al.  Prediction of Orientation Selectivity from Receptive Field Architecture in Simple Cells of Cat Visual Cortex , 2001, Neuron.

[133]  R. Reid,et al.  Predicting Every Spike A Model for the Responses of Visual Neurons , 2001, Neuron.

[134]  Maneesh Sahani,et al.  How Linear are Auditory Cortical Responses? , 2002, NIPS.

[135]  R. Guillery,et al.  Thalamic Relay Functions and Their Role in Corticocortical Communication Generalizations from the Visual System , 2002, Neuron.

[136]  Jonathan B Demb,et al.  Multiple Mechanisms for Contrast Adaptation in the Retina , 2002, Neuron.

[137]  M. Carandini,et al.  A Synaptic Explanation of Suppression in Visual Cortex , 2002, The Journal of Neuroscience.

[138]  M. Meister,et al.  Fast and Slow Contrast Adaptation in Retinal Circuitry , 2002, Neuron.

[139]  Paul R. Martin,et al.  Extraclassical Receptive Field Properties of Parvocellular, Magnocellular, and Koniocellular Cells in the Primate Lateral Geniculate Nucleus , 2002, The Journal of Neuroscience.

[140]  Brian Lau,et al.  Computational subunits of visual cortical neurons revealed by artificial neural networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[141]  Barry B. Lee,et al.  Processing of Natural Temporal Stimuli by Macaque Retinal Ganglion Cells , 2002, The Journal of Neuroscience.

[142]  Robert Shapley,et al.  Receptive field structure of neurons in monkey primary visual cortex revealed by stimulation with natural image sequences. , 2002, Journal of vision.

[143]  M. Carandini,et al.  Suppression without Inhibition in Visual Cortex , 2002, Neuron.

[144]  J. Gallant,et al.  Natural Stimulation of the Nonclassical Receptive Field Increases Information Transmission Efficiency in V1 , 2002, The Journal of Neuroscience.

[145]  D. Ringach,et al.  On the classification of simple and complex cells , 2002, Vision Research.

[146]  J. Touryan,et al.  Isolation of Relevant Visual Features from Random Stimuli for Cortical Complex Cells , 2002, The Journal of Neuroscience.

[147]  Ben Willmore,et al.  The Receptive-Field Organization of Simple Cells in Primary Visual Cortex of Ferrets under Natural Scene Stimulation , 2003, The Journal of Neuroscience.

[148]  Kerry J. Kim,et al.  Slow Na+ Inactivation and Variance Adaptation in Salamander Retinal Ganglion Cells , 2003, The Journal of Neuroscience.

[149]  Eero P. Simoncelli,et al.  Biases in white noise analysis due to non-Poisson spike generation , 2003, Neurocomputing.

[150]  N. Lesica,et al.  Adaptive encoding in the visual pathway , 2003, Network.

[151]  Darragh Smyth,et al.  Methods for first-order kernel estimation: simple-cell receptive fields from responses to natural scenes , 2003, Network.

[152]  Y. Frégnac,et al.  The “silent” surround of V1 receptive fields: theory and experiments , 2003, Journal of Physiology-Paris.

[153]  Tai Sing Lee,et al.  Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[154]  József Fiser,et al.  Coding of Natural Scenes in Primary Visual Cortex , 2003, Neuron.

[155]  D. Smyth,et al.  Methods for first-order kernel estimation: simple-cell receptive fields from responses to natural scenes. , 2003 .

[156]  Rodrigo F. Salazar,et al.  Responses to natural scenes in cat V1. , 2003, Journal of neurophysiology.

[157]  D. Berson,et al.  Strange vision: ganglion cells as circadian photoreceptors , 2003, Trends in Neurosciences.

[158]  J. B. Demb,et al.  Different Circuits for ON and OFF Retinal Ganglion Cells Cause Different Contrast Sensitivities , 2003, The Journal of Neuroscience.

[159]  J. A. Hirsch Synaptic physiology and receptive field structure in the early visual pathway of the cat. , 2003, Cerebral cortex.

[160]  J. Gallant,et al.  Goal-Related Activity in V4 during Free Viewing Visual Search Evidence for a Ventral Stream Visual Salience Map , 2003, Neuron.

[161]  Konrad P. Körding,et al.  The world from a cat’s perspective – statistics of natural videos , 2003, Biological Cybernetics.

[162]  Barry B. Lee,et al.  Dynamics of sensitivity regulation in primate outer retina: the horizontal cell network. , 2003, Journal of vision.

[163]  P. Lennie The Cost of Cortical Computation , 2003, Current Biology.

[164]  W. R. Taylor,et al.  New directions in retinal research , 2003, Trends in Neurosciences.

[165]  Stephen A. Baccus,et al.  Segregation of object and background motion in the retina , 2003, Nature.

[166]  C. Enroth-Cugell,et al.  X and Y ganglion cells inform the cat's brain about contrast in the retinal image , 2004, Experimental Brain Research.

[167]  J. Gallant,et al.  Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons , 2004, The Journal of Neuroscience.

[168]  Bruno A Olshausen,et al.  Sparse coding of sensory inputs , 2004, Current Opinion in Neurobiology.

[169]  C. Blakemore,et al.  Lateral inhibition between orientation detectors in the cat's visual cortex , 2004, Experimental Brain Research.

[170]  D. Tolhurst,et al.  The effects of contrast on the linearity of spatial summation of simple cells in the cat's striate cortex , 2004, Experimental Brain Research.

[171]  Andreas V. M. Herz,et al.  Searching for Optimal Sensory Signals: Iterative Stimulus Reconstruction in Closed-Loop Experiments , 2004, Journal of Computational Neuroscience.

[172]  D. Tolhurst,et al.  Spatial summation by simple cells in the striate cortex of the cat , 2004, Experimental Brain Research.

[173]  Eero P. Simoncelli,et al.  Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model , 2004, Neural Computation.

[174]  Ryan J. Prenger,et al.  Nonlinear V1 responses to natural scenes revealed by neural network analysis , 2004, Neural Networks.

[175]  Peter Sterling,et al.  How retinal ganglion cells prevent synaptic noise from reaching the spike output. , 2004, Journal of neurophysiology.

[176]  E. Chichilnisky,et al.  Precision of spike trains in primate retinal ganglion cells. , 2004, Journal of neurophysiology.

[177]  D. Perrett,et al.  Rapid serial visual presentation for the determination of neural selectivity in area STSa. , 2004, Progress in brain research.

[178]  J. Movshon,et al.  Adaptive Temporal Integration of Motion in Direction-Selective Neurons in Macaque Visual Cortex , 2004, The Journal of Neuroscience.

[179]  G. Sclar,et al.  Expression of “retinal” contrast gain control by neurons of the cat's lateral geniculate nucleus , 2004, Experimental Brain Research.

[180]  William Bialek,et al.  Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions , 2002, Neural Computation.

[181]  H. Ozeki,et al.  Relationship between Excitation and Inhibition Underlying Size Tuning and Contextual Response Modulation in the Cat Primary Visual Cortex , 2004, The Journal of Neuroscience.

[182]  Nicholas J. Priebe,et al.  The contribution of spike threshold to the dichotomy of cortical simple and complex cells , 2004, Nature Neuroscience.

[183]  Alexander Borst,et al.  Quantifying variability in neural responses and its application for the validation of model predictions , 2004, Network.

[184]  D. Tolhurst,et al.  Factors influencing the temporal phase of response to bar and grating stimuli for simple cells in the cat striate cortex , 2004, Experimental Brain Research.

[185]  L. Chalupa,et al.  The visual neurosciences , 2004 .

[186]  Matteo Carandini,et al.  How local contrast determines gain and temporal integration of LGN , 2004 .

[187]  Heinz Wässle,et al.  Parallel processing in the mammalian retina , 2004, Nature Reviews Neuroscience.

[188]  Heather J. Chisum,et al.  The contribution of vertical and horizontal connections to the receptive field center and surround in V1 , 2004, Neural Networks.

[189]  M. Carandini Receptive fields and suppressive fields in the early visual system , 2004 .

[190]  V. D. Glezer,et al.  Spatio-temporal organization of receptive fields of the cat striate cortex , 2004, Biological Cybernetics.

[191]  Eero P. Simoncelli,et al.  To appear in: The New Cognitive Neurosciences, 3rd edition Editor: M. Gazzaniga. MIT Press, 2004. Characterization of Neural Responses with Stochastic Stimuli , 2022 .

[192]  N. Lesica,et al.  Encoding of Natural Scene Movies by Tonic and Burst Spikes in the Lateral Geniculate Nucleus , 2004, The Journal of Neuroscience.

[193]  David J. Field,et al.  How Close Are We to Understanding V1? , 2005, Neural Computation.

[194]  M. Meister,et al.  Dynamic predictive coding by the retina , 2005, Nature.

[195]  J. Gallant,et al.  Predicting neuronal responses during natural vision , 2005, Network.

[196]  J. Touryan,et al.  Spatial Structure of Complex Cell Receptive Fields Measured with Natural Images , 2005, Neuron.

[197]  F. Sengpiel,et al.  Intracortical Origins of Interocular Suppression in the Visual Cortex , 2005, The Journal of Neuroscience.

[198]  J. Gallant,et al.  Time Course of Attention Reveals Different Mechanisms for Spatial and Feature-Based Attention in Area V4 , 2005, Neuron.

[199]  J. B. Demb,et al.  Contrast Adaptation in Subthreshold and Spiking Responses of Mammalian Y-Type Retinal Ganglion Cells , 2005, The Journal of Neuroscience.

[200]  Eero P. Simoncelli,et al.  Spatiotemporal Elements of Macaque V1 Receptive Fields , 2005, Neuron.

[201]  Robert A. Frazor,et al.  Independence of luminance and contrast in natural scenes and in the early visual system , 2005, Nature Neuroscience.

[202]  R. Freeman,et al.  Cross-orientation suppression: monoptic and dichoptic mechanisms are different. , 2005, Journal of neurophysiology.

[203]  Feng Qi Han,et al.  Cortical Sensitivity to Visual Features in Natural Scenes , 2005, PLoS biology.

[204]  J. Pokorny,et al.  Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN , 2005, Nature.

[205]  D. Ringach,et al.  Spatial overlap of ON and OFF subregions and its relation to response modulation ratio in macaque primary visual cortex. , 2005, Journal of neurophysiology.

[206]  M. Carandini,et al.  The Suppressive Field of Neurons in Lateral Geniculate Nucleus , 2005, The Journal of Neuroscience.

[207]  Valerio Mante,et al.  Gain controls based on luminance and contrast in the early visual system , 2005 .

[208]  K. O’Connor,et al.  Adaptive stimulus optimization for auditory cortical neurons. , 2005, Journal of neurophysiology.

[209]  J W Gnadt,et al.  Higher-order thalamic relays burst more than first-order relays. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[210]  R. Reid,et al.  Receptive field structure varies with layer in the primary visual cortex , 2005, Nature Neuroscience.

[211]  RussLL L. Ds Vnlos,et al.  SPATIAL FREQUENCY SELECTIVITY OF CELLS IN MACAQUE VISUAL CORTEX , 2022 .