Properties Of Primary Visual Cortex Research Articles

Divisively Normalized Sparse Coding: Toward Perceptual Visual Signal Representation.

Sparse representation has been shown to be highly correlated with the visual perception of natural images, which can be characterized by a linear combination of neuronal responses in the visual cortex. Divisive normalization transform (DNT) has been proven to be an effective method in reducing statistical and perceptual dependencies for nonlinear properties in primary visual cortex. In this paper, we develop a divisively normalized sparse coding scheme, aiming to further bridge the gap between sparse representation and human visual perception. We show that such a scheme is perceptually meaningful for representing visual signals, with which the pixel-domain image representation and processing tasks can be feasibly and efficiently achieved in the divisively normalized sparse-domain. Specifically, we develop a sparse-domain similarity (SDS) index for perceptual quality evaluation, where the DNT is employed for transforming image signals into a perceptually uniform space. Furthermore, the proposed SDS index is employed to optimize the sparse coding process when representing natural images. The experimental results indicate that the SDS can provide accurate and consistent predictions of perceived image quality, and the performance of sparse coding can be significantly improved in terms of both objective and subjective quality evaluations.

Assessing the functional properties of primary visual cortex in the absence of extrastriate visual areas.

Assessing the functional properties of primary visual cortex in the absence of extrastriate visual areas.

Systematic variation of population receptive field properties across cortical depth in human visual cortex

Receptive fields (RFs) in visual cortex are organized in antagonistic, center-surround, configurations. RF properties change systematically across eccentricity and between visual field maps. However, it is unknown how center-surround configurations are organized in human visual cortex across lamina. We use sub-millimeter resolution functional MRI at 7Tesla and population receptive field (pRF) modeling to investigate the pRF properties in primary visual cortex (V1) across cortical depth. pRF size varies according to a U-shaped function, indicating smaller pRF center size in the middle compared to superficial and deeper intra-cortical portions of V1, consistent with non-human primate neurophysiological measurements. Moreover, a similar U-shaped function is also observed for pRF surround size. However, pRF center-surround ratio remains constant across cortical depth. Simulations suggest that this pattern of results can be directly linked to the flow of signals across cortical depth, with the visual input reaching the middle of cortical depth and then spreading towards superficial and deeper layers of V1. Conversely, blood-oxygenation-level-dependent (BOLD) signal amplitude increases monotonically towards the pial surface, in line with the known vascular organization across cortical depth. Independent estimates of the haemodynamic response function (HRF) across cortical depth show that the center-surround pRF size estimates across cortical depth cannot be explained by variations in the full-width half maximum (FWHM) of the HRF.

Corticocortical feedback increases the spatial extent of normalization.

Normalization has been proposed as a canonical computation operating across different brain regions, sensory modalities, and species. It provides a good phenomenological description of non-linear response properties in primary visual cortex (V1), including the contrast response function and surround suppression. Despite its widespread application throughout the visual system, the underlying neural mechanisms remain largely unknown. We recently observed that corticocortical feedback contributes to surround suppression in V1, raising the possibility that feedback acts through normalization. To test this idea, we characterized area summation and contrast response properties in V1 with and without feedback from V2 and V3 in alert macaques and applied a standard normalization model to the data. Area summation properties were well explained by a form of divisive normalization, which computes the ratio between a neuron's driving input and the spatially integrated activity of a “normalization pool.” Feedback inactivation reduced surround suppression by shrinking the spatial extent of the normalization pool. This effect was independent of the gain modulation thought to mediate the influence of contrast on area summation, which remained intact during feedback inactivation. Contrast sensitivity within the receptive field center was also unaffected by feedback inactivation, providing further evidence that feedback participates in normalization independent of the circuit mechanisms involved in modulating contrast gain and saturation. These results suggest that corticocortical feedback contributes to surround suppression by increasing the visuotopic extent of normalization and, via this mechanism, feedback can play a critical role in contextual information processing.

Refinement but Not Maintenance of Visual Receptive Fields Is Independent of Visual Experience

Visual deprivation is reported to prevent or delay the development of mature receptive field (RF) properties in primary visual cortex (V1) in several species. In contrast, visual deprivation neither prevents nor delays refinement of RF size in the superior colliculus (SC) of Syrian hamsters, although vision is required for RF maintenance in the SC. Here, we report that, contrary to expectation, visual cortical RF refinement occurs normally in dark-reared animals. As in the SC, a brief period of visual experience is required to maintain V1 RF refinement in adulthood. Whereas in the SC, 3 days of visual experience within a sensitive period (P37-40) was sufficient to protect RFs from deprivation-induced enlargement in adulthood, 7 days (P33-40) were required for RF size maintenance in V1. Thus, spontaneous activity is sufficient for RF refinement at these 2 levels of the visual pathway, and visual input is necessary only to prevent deprivation-induced RF enlargement in adulthood. These studies show that sensory experience during a late juvenile sensitive period protects the visual pathway against sensory deprivation in adulthood, and suggest that more importance may have been placed on the role of early visual experience in visual RF development than is warranted.

On the Relation Between Receptive Field Structure and Stimulus Selectivity in the Tree Shrew Primary Visual Cortex

There are notable differences in functional properties of primary visual cortex (V1) neurons among mammalian species, particularly those concerning the occurrence of simple and complex cells and the generation of orientation selectivity. Here, we present quantitative data on receptive field (RF) structure, response modulation, and orientation tuning for single neurons in V1 of the tree shrew, a close relative of primates. We find that spatial RF subfield segregation, a criterion for identifying simple cells, was exceedingly small in the tree shrew V1. In contrast, many neurons exhibited elevated F1/F0 modulation that is often used as a simple cell marker. This apparent discrepancy can be explained by the robust stimulus polarity preference in tree shrew V1, which inflates F1/F0 ratio values. RF structure mapped with sparse-noise-which is spatially restricted and emphasizes thalamo-cortical feed-forward inputs-appeared unrelated to orientation selectivity. However, RF structure mapped using the Hartley subspace stimulus-which covers a large area of the visual field and recruits considerable intracortical processing-did predict orientation preference. Our findings reveal a number of striking similarities in V1 functional organization between tree shrews and primates, emphasizing the important role of intracortical recurrent processing in shaping V1 response properties in these species.

Corticocortical Feedback Contributes to Surround Suppression in V1 of the Alert Primate

Feedback connections are prevalent throughout the cerebral cortex, yet their function remains poorly understood. Previous studies in anesthetized monkeys found that inactivating feedback from extrastriate visual cortex produced effects in striate cortex that were relatively weak, generally suppressive, largest for visual stimuli confined to the receptive field center, and detectable only at low stimulus contrast. We studied the influence of corticocortical feedback in alert monkeys using cortical cooling to reversibly inactivate visual areas 2 (V2) and 3 (V3) while characterizing receptive field properties in primary visual cortex (V1). We show that inactivation of feedback from areas V2 and V3 results in both response suppression and facilitation for stimuli restricted to the receptive field center, in most cases leading to a small reduction in the degree of orientation selectivity but no change in orientation preference. For larger-diameter stimuli that engage regions beyond the center of the receptive field, eliminating feedback from V2 and V3 results in strong and consistent response facilitation, effectively reducing the strength of surround suppression in V1 for stimuli of both low and high contrast. For extended contours, eliminating feedback had the effect of reducing end stopping. Inactivation effects were largest for neurons that exhibited strong surround suppression before inactivation, and their timing matched the dynamics of surround suppression under control conditions. Our results provide direct evidence that feedback contributes to surround suppression, which is an important source of contextual influences essential to vision.

Inhibitory Interneurons Decorrelate Excitatory Cells to Drive Sparse Code Formation in a Spiking Model of V1

Sparse coding models of natural scenes can account for several physiological properties of primary visual cortex (V1), including the shapes of simple cell receptive fields (RFs) and the highly kurtotic firing rates of V1 neurons. Current spiking network models of pattern learning and sparse coding require direct inhibitory connections between the excitatory simple cells, in conflict with the physiological distinction between excitatory (glutamatergic) and inhibitory (GABAergic) neurons (Dale's Law). At the same time, the computational role of inhibitory neurons in cortical microcircuit function has yet to be fully explained. Here we show that adding a separate population of inhibitory neurons to a spiking model of V1 provides conformance to Dale's Law, proposes a computational role for at least one class of interneurons, and accounts for certain observed physiological properties in V1. When trained on natural images, this excitatory-inhibitory spiking circuit learns a sparse code with Gabor-like RFs as found in V1 using only local synaptic plasticity rules. The inhibitory neurons enable sparse code formation by suppressing predictable spikes, which actively decorrelates the excitatory population. The model predicts that only a small number of inhibitory cells is required relative to excitatory cells and that excitatory and inhibitory input should be correlated, in agreement with experimental findings in visual cortex. We also introduce a novel local learning rule that measures stimulus-dependent correlations between neurons to support "explaining away" mechanisms in neural coding.

Long-term down-regulation of GABA decreases orientation selectivity without affecting direction selectivity in mouse primary visual cortex

Inhibitory interneurons play important roles in the development of brain functions. In the visual cortex, functional maturation of inhibitory interneurons is essential for ocular dominance plasticity. However, roles of inhibitory interneurons in the development of orientation and direction selectivity, fundamental properties of primary visual cortex, are less understood. We examined orientation and direction selectivity of neurons in GAD67-GFP (Δneo) mice, in which expression of GABA in the brain is decreased in the newborn. We used in vivo two-photon calcium imaging to examine visual response of neurons in these mice and found that long-term decrease of GABA led to increase of response amplitude to non-preferred orientation of visual stimuli, which decreased orientation selectivity. In contrast, direction selectivity was not affected. These results suggest that orientation selectivity is decreased in mice with GABA down-regulation during development.

Inhibitory interneurons enable sparse code formation in a spiking circuit model of V1

Sparse coding accounts for several physiological properties of primary visual cortex (V1), including the shapes of simple cell receptive fields and the highly kurtotic firing rates of V1 neurons [1]. Current spiking network models of pattern learning [2] and sparse coding [3] require direct inhibitory connections between the excitatory simple cells, in violation of Dale's Law which states that neurons can either excite or inhibit but not both. At the same time, the computational role of inhibitory neurons in cortical microcircuit function has yet to be fully explained. Here we show that adding a separate population of inhibitory neurons to a recently proposed model of V1 [3] not only brings spiking network models of sparse coding in line with Dale’s Law, but it also predicts excitatory-to-inhibitory neuron ratios and explains how inhibitory neurons may function computationally. When trained on natural images, this excitatory-inhibitory spiking circuit learns Gabor-like receptive fields as found in V1 using spiking neurons and synaptically local plasticity rules. The inhibitory cells enable sparse code formation using a novel learning rule by collaboratively discovering and suppressing correlations within the excitatory population (Figure ​(Figure1).1). The model predicts that only a small number of inhibitory cells is required relative to excitatory cells, matching physiological ratios observed in primary visual cortex. Figure 1 A. Circuit diagram of our spiking network with separate excitatory (E) and inhibitory (I) neural populations (top) compared to current single population models (bottom). This network was simulated with different numbers of excitatory and inhibitory cells. ...

A Multi-Stage Model for Fundamental Functional Properties in Primary Visual Cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (∼4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.

Scale-invariance of receptive field properties in primary visual cortex

BackgroundOur visual system enables us to recognize visual objects across a wide range of spatial scales. The neural mechanisms underlying these abilities are still poorly understood. Size- or scale-independent representation of visual objects might be supported by processing in primary visual cortex (V1). Neurons in V1 are selective for spatial frequency and thus represent visual information in specific spatial wavebands. We tested whether different receptive field properties of neurons in V1 scale with preferred spatial wavelength. Specifically, we investigated the size of the area that enhances responses, i.e., the grating summation field, the size of the inhibitory surround, and the distance dependence of signal coupling, i.e., the linking field.ResultsWe found that the sizes of both grating summation field and inhibitory surround increase with preferred spatial wavelength. For the summation field this increase, however, is not strictly linear. No evidence was found that size of the linking field depends on preferred spatial wavelength.ConclusionOur data show that some receptive field properties are related to preferred spatial wavelength. This speaks in favor of the hypothesis that processing in V1 supports scale-invariant aspects of visual performance. However, not all properties of receptive fields in V1 scale with preferred spatial wavelength. Spatial-wavelength independence of the linking field implies a constant spatial range of signal coupling between neurons with different preferred spatial wavelengths. This might be important for encoding extended broad-band visual features such as edges.

Invariant representations of visual patterns in a temporal population code.

Mammalian visual systems are characterized by their ability to recognize stimuli invariant to various transformations. Here, we investigate the hypothesis that this ability is achieved by the temporal encoding of visual stimuli. By using a model of a cortical network, we show that this encoding is invariant to several transformations and robust with respect to stimulus variability. Furthermore, we show that the proposed model provides a rapid encoding, in accordance with recent physiological results. Taking into account properties of primary visual cortex, the application of the encoding scheme to an enhanced network demonstrates favorable scaling and high performance in a task humans excel at.

Learning to see: experience and attention in primary visual cortex.

The response properties of neurons in primary sensory cortices remain malleable throughout life. The existence of such plasticity, and the characteristics of a form of implicit learning known as perceptual learning, suggest that changes in primary sensory cortex may mediate learning. We explored whether modification of the functional properties of primary visual cortex (V1) accompanies perceptual learning. Basic receptive field properties, such as location, size and orientation selectivity, were unaffected by perceptual training, and visual topography (as measured by magnification factor) was indistinguishable between trained and untrained animals. On the other hand, the influence of contextual stimuli placed outside the receptive field showed a change consistent with the trained discrimination. Furthermore, this property showed task dependence, only being manifest when the animal was performing the trained discrimination.

Response to movement of neurons in areas 17 and 18 of the cat: direction selectivity.

Response to movement of neurons in areas 17 and 18 of the cat: direction selectivity.G A Orban, H Kennedy, and H MaesG A Orban, H Kennedy, and H MaesPublished Online:01 Jun 1981https://doi.org/10.1152/jn.1981.45.6.1059MoreSectionsPDF (2 MB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat Previous Back to Top Next Download PDF FiguresReferencesRelatedInformation Cited ByCallosal Influence on Visual Receptive Fields Has an Ocular, an Orientation-and Direction Bias16 April 2018 | Frontiers in Systems Neuroscience, Vol. 12Selective interhemispheric circuits account for a cardinal bias in spontaneous activity within early visual areasNeuroImage, Vol. 146Laminar Organization of Response Properties in Primary Visual Cortex of the Gray Squirrel (Sciurus carolinensis)J. Alexander Heimel, Stephen D. Van Hooser, and Sacha B. Nelson1 November 2005 | Journal of Neurophysiology, Vol. 94, No. 5Rapid Processing of Retinal Slip During Saccades in Macaque Area MTN.S.C. Price, M. R. Ibbotson, S. Ono, and M. J. Mustari1 July 2005 | Journal of Neurophysiology, Vol. 94, No. 1Convergence of Y and non-Y channels onto single neurons in the superior colliculi of the catNeuroreport, Vol. 12, No. 13Response Latency of Macaque Area MT/V5 Neurons and Its Relationship to Stimulus ParametersS. E. Raiguel, D.-K. Xiao, V. L. Marcar, and G. A. Orban1 October 1999 | Journal of Neurophysiology, Vol. 82, No. 4The Speed Tuning of Medial Superior Temporal (Mst) Cell Responses to Optic-Flow Components25 June 2016 | Perception, Vol. 24, No. 3Augmenting and reducing of visual evoked potentials in Roman high- and low-avoidance ratsPhysiology & Behavior, Vol. 54, No. 4Isolating the effect of one-dimensional motion signals on the perceived direction of moving two-dimensional objectsVision Research, Vol. 33, No. 10Influence of spatial frequency on tuning and bias for orientation and direction in the cat's striate cortexVision Research, Vol. 30, No. 3Directional and orientational tuning of feline striate cortical neurones: Correlation with neuronal classVision Research, Vol. 29, No. 6Neural motion after-effects in the cat's striate cortex: Orientation selectivityVision Research, Vol. 29, No. 12Human velocity and direction discrimination measured with random dot patternsVision Research, Vol. 28, No. 12Responses to direction of stimulus movement are different for somatosensory and visual cells in cat superior colliculusBrain Research, Vol. 405, No. 2Influence of stimulus length on directional bias of complex cells in cat striate cortexNeuroscience, Vol. 18, No. 1The role of cortical directional selectivity in detection of motion and flickerVision Research, Vol. 26, No. 8Factors influencing cutaneous directional sensitivity: A correlative psychophysical and neurophysiological investigationBrain Research Reviews, Vol. 10, No. 3Receptive field properties of neurones in visual area 1 and visual area 2 in the baboonNeuroscience, Vol. 14, No. 2Responses of cat visual cortical cells to continuously and stroboscopically illuminated moving light slits comparedVision Research, Vol. 24, No. 5Direction asymmetry by moving stimuli and static receptive field plots for simple cells in cat striate cortexVision Research, Vol. 24, No. 1Factors influencing velocity coding in the human visual systemVision Research, Vol. 24, No. 1Effects of stimulus speed on direction discriminationsVision Research, Vol. 24, No. 10Receptive field characteristics of neurones in striate cortex of newborn lambs and adult sheepNeuroscience, Vol. 10, No. 2Functional properties of area 19 as compared to area 17 of the catBrain Research, Vol. 231, No. 2Receptive field structure of area 19 as compared to area 17 of the catBrain Research, Vol. 231, No. 2Low level modeling of the development of directionally selective microcircuits in cat striate cortex More from this issue > Volume 45Issue 6June 1981Pages 1059-73 https://doi.org/10.1152/jn.1981.45.6.1059PubMed7252530History Published online 1 June 1981 Published in print 1 June 1981 Metrics

Laminar distribution of first-order neurons and afferent terminals in cat striate cortex.

ArticlesLaminar distribution of first-order neurons and afferent terminals in cat striate cortexJ. Bullier, and G. H. HenryJ. Bullier, and G. H. HenryPublished Online:01 Sep 1979https://doi.org/10.1152/jn.1979.42.5.1271MoreSectionsPDF (2 MB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat Previous Back to Top Next Download PDF FiguresReferencesRelatedInformation Cited ByBiophysical Support for Functionally Distinct Cell Types in the Frontal Eye FieldJeremiah Y. Cohen, Pierre Pouget, Richard P. Heitz, Geoffrey F. Woodman, and Jeffrey D. Schall1 February 2009 | Journal of Neurophysiology, Vol. 101, No. 2Laminar Organization of Response Properties in Primary Visual Cortex of the Gray Squirrel (Sciurus carolinensis)J. Alexander Heimel, Stephen D. Van Hooser, and Sacha B. Nelson1 November 2005 | Journal of Neurophysiology, Vol. 94, No. 5NEURONAL CIRCUITS OF THE NEOCORTEXAnnual Review of Neuroscience, Vol. 27, No. 1Two Different Types of Y Cells in the Cat Lateral Geniculate NucleusChun-I Yeh, Carl R. Stoelzel, and Jose-Manuel Alonso1 September 2003 | Journal of Neurophysiology, Vol. 90, No. 3Substructure of Direction-Selective Receptive Fields in Macaque V1Margaret S. Livingstone, and Bevil R. Conway1 May 2003 | Journal of Neurophysiology, Vol. 89, No. 5Electrophysiological Classes of Cat Primary Visual Cortical Neurons In Vivo as Revealed by Quantitative AnalysesLionel G. Nowak, Rony Azouz, Maria V. Sanchez-Vives, Charles M. Gray, and David A. McCormick1 March 2003 | Journal of Neurophysiology, Vol. 89, No. 3Receptive Fields and Response Properties of Neurons in Layer 4 of Ferret Visual CortexW. Martin Usrey, Michael P. Sceniak, and Barbara Chapman1 February 2003 | Journal of Neurophysiology, Vol. 89, No. 2LGN Input to Simple Cells and Contrast-Invariant Orientation Tuning: An AnalysisTodd W. Troyer, Anton E. Krukowski, and Kenneth D. Miller1 June 2002 | Journal of Neurophysiology, Vol. 87, No. 6Contrast-Dependent Nonlinearities Arise Locally in a Model of Contrast-Invariant Orientation TuningAndrew Kayser*, Nicholas J. Priebe*, and Kenneth D. Miller1 May 2001 | Journal of Neurophysiology, Vol. 85, No. 5Anatomy, Physiology, and Synaptic Responses of Rat Layer V Auditory Cortical Cells and Effects of Intracellular GABAABlockadeBrenda J. Hefti, and Philip H. Smith1 May 2000 | Journal of Neurophysiology, Vol. 83, No. 5Receptive Field Properties of Single Neurons in Rat Primary Visual CortexSergej V. Girman, Yves Sauvé, and Raymond D. Lund1 July 1999 | Journal of Neurophysiology, Vol. 82, No. 1Inhibitory Contributions to Spatiotemporal Receptive-Field Structure and Direction Selectivity in Simple Cells of Cat Area 17Aditya Murthy, and Allen L. Humphrey1 March 1999 | Journal of Neurophysiology, Vol. 81, No. 3Strobe Rearing Prevents the Convergence of Inputs With Different Response Timings Onto Area 17 Simple CellsAllen L. Humphrey, Alan B. Saul, and Jordan C. Feidler1 December 1998 | Journal of Neurophysiology, Vol. 80, No. 6Encoding of Binocular Disparity by Complex Cells in the Cat's Visual CortexIzumi Ohzawa, Gregory C. Deangelis, and Ralph D. Freeman1 June 1997 | Journal of Neurophysiology, Vol. 77, No. 6The nature and origin of orientation specificity in neurons of the visual pathwaysProgress in Neurobiology, Vol. 43, No. 4-5Neurotransmitter actions in the thalamus and cerebral cortex and their role in neuromodulation of thalamocortical activityProgress in Neurobiology, Vol. 39, No. 4A model for self-organization of receptive fields and orientation-selective columns in the striate cortexNeuroscience Research, Vol. 11, No. 3Postnatal development of neuronal connections in cat visual cortex studied by intracellular recording in slice preparationBrain Research, Vol. 540, No. 1-2Responses of visual cortical neurons to curved stimuli and chevronsVision Research, Vol. 30, No. 2Lamina-specific differences of visual latencies following photic stimulation in the cat striate cortexBrain Research, Vol. 385, No. 2Intrinsic neocortical organization: Some comparative aspectsNeuroscience, Vol. 18, No. 1Vernier acuity in the cat: Its relation to hyperacuityVision Research, Vol. 26, No. 8Length summation of complex cells in cat striate cortex: A reappraisal of the “special/standard” classificationNeuroscience, Vol. 15, No. 3Sensitivity of complex cells in cat striate cortex to relative motionBrain Research, Vol. 301, No. 2Synaptic connections of morphologically identified and physiologically characterized large basket cells in the striate cortex of catNeuroscience, Vol. 10, No. 2Morphology of geniculo-striate afferents in a prosimian primateBrain Research, Vol. 270, No. 1Visual response properties of zebrafish tectal cellsNeuroscience, Vol. 7, No. 10Postnatal development of the corticofugal projection from striate cortex to lateral geniculate nucleus in kittensDevelopmental Brain Research, Vol. 4, No. 3Electron microscopic demonstration of thalamic axon terminations on identified commissural neurons in monkey somatic sensory cortexBrain Research, Vol. 196, No. 1Parallel visual pathways: A reviewVision Research, Vol. 20, No. 7 More from this issue > Volume 42Issue 5September 1979Pages 1271-1281 Copyright & PermissionsCopyright © 1979 the American Physiological Societyhttps://doi.org/10.1152/jn.1979.42.5.1271PubMed490198History Published online 1 September 1979 Published in print 1 September 1979 Metrics

Orientation specificity of cells in cat striate cortex.

Orientation specificity of cells in cat striate cortex.