scholarly journals Mapping Spatial Frequency Preferences Across Human Primary Visual Cortex

2021 ◽  
Author(s):  
William F. Broderick ◽  
Eero P. Simoncelli ◽  
Jonathan Winawer
Keyword(s):  
Visual Cortex ◽  
Visual Field ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Tuning Curve ◽  
Stimulus Orientation ◽  
Polar Coordinates ◽  
Small Constant ◽  
Spatial Frequencies

AbstractNeurons in primate visual cortex (area V1) are tuned for spatial frequency, in a manner that depends on their position in the visual field. Several studies have examined this dependency using fMRI, reporting preferred spatial frequencies (tuning curve peaks) of V1 voxels as a function of eccentricity, but their results differ by as much as two octaves, presumably due to differences in stimuli, measurements, and analysis methodology. Here, we characterize spatial frequency tuning at a millimeter resolution within human primary visual cortex, across stimulus orientation and visual field locations. We measured fMRI responses to a novel set of stimuli, constructed as sinusoidal gratings in log-polar coordinates, which include circular, radial, and spiral geometries. For each individual stimulus, the local spatial frequency varies inversely with eccentricity, and for any given location in the visual field, the full set of stimuli span a broad range of spatial frequencies and orientations. Over the measured range of eccentricities, the preferred spatial frequency is well-fit by a function that varies as the inverse of the eccentricity plus a small constant. We also find small but systematic effects of local stimulus orientation, defined in both absolute coordinates and relative to visual field location. Specifically, peak spatial frequency is higher for tangential than radial orientations and for horizontal than vertical orientations.

scholarly journals Model-based characterization of the selectivity of neurons in primary visual cortex

2021 ◽  
Author(s):  
Felix Bartsch ◽  
Bruce G Cumming ◽  
Daniel A Butts
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Frequency Tuning ◽  
Nonlinear Models ◽  
Field Size ◽  
V1 Neurons ◽  
Model Based ◽  
Spatial Frequencies

To understand the complexity of stimulus selectivity in primary visual cortex (V1), models constructed to match observed responses to complex time-varying stimuli, instead of to explain responses to simple parametric stimuli, are increasingly used. While such models often can more accurately reflect the computations performed by V1 neurons in more natural visual environments, they do not by themselves provide insight into established measures of V1 neural selectivity such as receptive field size, spatial frequency tuning and phase invariance. Here, we suggest a series of analyses that can be directly applied to encoding models to link complex encoding models to more interpretable aspects of stimulus selectivity, applied to nonlinear models of V1 neurons recorded in awake macaque in response to random bar stimuli. In linking model properties to more classical measurements, we demonstrate several novel aspects of V1 selectivity not available to simpler experimental measurements. For example, we find that individual spatiotemporal elements of the V1 models often have a smaller spatial scale than the overall neuron sensitivity, and that this results in non-trivial tuning to spatial frequencies. Additionally, our proposed measures of nonlinear integration suggest that more classical classifications of V1 neurons into simple versus complex cells are spatial-frequency dependent. In total, rather than obfuscate classical characterizations of V1 neurons, model-based characterizations offer a means to more fully understand their selectivity, and provide a means to link their classical tuning properties to their roles in more complex, natural, visual processing.

scholarly journals Dynamics of spatial frequency tuning in mouse visual cortex

2012 ◽  
Vol 107 (11) ◽  
pp. 2937-2949 ◽  
Author(s):  
Samme Vreysen ◽  
Bin Zhang ◽  
Yuzo M. Chino ◽  
Lutgarde Arckens ◽  
Gert Van den Bergh
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual Information ◽  
Frequency Tuning ◽  
Neuronal Response ◽  
Correlation Technique ◽  
Low Frequencies ◽  
Temporal Shift ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies

Neuronal spatial frequency tuning in primary visual cortex (V1) substantially changes over time. In both primates and cats, a shift of the neuron's preferred spatial frequency has been observed from low frequencies early in the response to higher frequencies later in the response. In most cases, this shift is accompanied by a decreased tuning bandwidth. Recently, the mouse has gained attention as a suitable animal model to study the basic mechanisms of visual information processing, demonstrating similarities in basic neuronal response properties between rodents and highly visual mammals. Here we report the results of extracellular single-unit recordings in the anesthetized mouse where we analyzed the dynamics of spatial frequency tuning in V1 and the lateromedial area LM within the lateral extrastriate area V2L. We used a reverse-correlation technique to demonstrate that, as in monkeys and cats, the preferred spatial frequency of mouse V1 neurons shifted from low to higher frequencies later in the response. However, this was not correlated with a clear selectivity increase or enhanced suppression of responses to low spatial frequencies. These results suggest that the neuronal connections responsible for the temporal shift in spatial frequency tuning may considerably differ between mice and monkeys.

Spatial Frequency-Specific Contrast Adaptation Originates in the Primary Visual Cortex

2007 ◽  
Vol 98 (1) ◽  
pp. 187-195 ◽  
Author(s):  
Thang Duong ◽  
Ralph D. Freeman
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Frequency Tuning ◽  
Adaptation Effect ◽  
Tuning Curves ◽  
Contrast Adaptation ◽  
Spatial Frequencies ◽  
Neurophysiological Studies ◽  
High Contrast Grating ◽  
Adaptation Effects

Adaptation to a high-contrast grating stimulus causes reduced sensitivity to subsequent presentation of a visual stimulus with similar spatial characteristics. This behavioral finding has been attributed by neurophysiological studies to processes within the visual cortex. However, some evidence indicates that contrast adaptation phenomena are also found in early visual pathways. Adaptation effects have been reported in retina and lateral geniculation nucleus (LGN). It is possible that these early pathways could be the physiological origin of the cortical adaptation effect. To study this, we recorded from single neurons in the cat's LGN. We find that contrast adaptation in the LGN, unlike that in the visual cortex, is not spatial frequency specific, i.e., adaptation effects apply to a broad range of spatial frequencies. In addition, aside from the amplitude attenuation, the shape of spatial frequency tuning curves of LGN cells is not affected by contrast adaptation. Again, these findings are unlike those found for cells in the visual cortex. Together, these results demonstrate that pattern specific contrast adaptation is a cortical process.

Cortical Maps of Separable Tuning Properties Predict Population Responses to Complex Visual Stimuli

2005 ◽  
Vol 94 (1) ◽  
pp. 775-787 ◽  
Author(s):  
Tanya I. Baker ◽  
Naoum P. Issa
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Sinusoidal Grating ◽  
Cortical Organization ◽  
Moving Images ◽  
Spatial Parameters

In the earliest cortical stages of visual processing, a scene is represented in different functional domains selective for specific features. Maps of orientation and spatial frequency preference have been described in the primary visual cortex using simple sinusoidal grating stimuli. However, recent imaging experiments suggest that the maps of these two spatial parameters are not sufficient to describe patterns of activity in different orientation domains generated in response to complex, moving stimuli. A model of cortical organization is presented in which cortical temporal frequency tuning is superimposed on the maps of orientation and spatial frequency tuning. The maps of these three tuning properties are sufficient to describe the activity in orientation domains that have been measured in response to drifting complex images. The model also makes specific predictions about how moving images are represented in different spatial frequency domains. These results suggest that the tangential organization of primary visual cortex can be described by a set of maps of separable neuronal receptive field features including maps of orientation, spatial frequency, and temporal frequency tuning properties.

Stimulus dependence of orientation and direction sensitivity of cat LGNd relay cells without cortical inputs: A comparison with area 17 cells

1994 ◽  
Vol 11 (5) ◽  
pp. 939-951 ◽  
Author(s):  
Kirk G. Thompson ◽  
Audie G. Leventhal ◽  
Yifeng Zhou ◽  
Dan Liu
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Frequency Tuning ◽  
Area 17 ◽  
Cortical Cells ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Direction Sensitivity ◽  
Cortical Inputs ◽  
Direction Tuning

AbstractThe cortical contribution to the orientation and direction sensitivity of LGNd relay cells was investigated by recording the responses of relay cells to drifting sinusoidal gratings of varying spatial frequencies, moving bars, and moving spots in cats in which the visual cortex (areas 17, 18, 19, and LS) was ablated. For comparison, the spatial-frequency dependence of orientation and direction tuning of striate cortical cells was investigated employing the same quantitative techniques used to test LGNd cells. There are no significant differences in the orientation and direction tuning to relay cells in the LGNd of normal and decorticate cats. The orientation and direction sensitivities of cortical cells are dependent on stimulus parameters in a fashion qualitatively similar to that of LGNd cells. The differences in the spatial-frequency bandwidths of LGNd cells and cortical cells may explain many of their differences in orientation and direction tuning. Although factors beyond narrowness of spatial-frequency tuning must exist to account for the much stronger orientation and direction preferences of cells in area 17 when compared to LGNd cells, the evidence suggests that the orientation and direction biases present in the afferents to the visual cortex may contribute to the orientation and direction selectivities found in cortical cells.

scholarly journals Multi-Unit Activity contains information about spatial stimulus structure in mouse primary visual cortex

2015 ◽  
Author(s):  
Marie Tolkiehn ◽  
Simon Schultz
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Unit Activity ◽  
Single Unit ◽  
Spatial Stimulus ◽  
Electrophysiological Recordings ◽  
Spatial Frequencies ◽  
Significant Performance ◽  
Directional Preference

This study investigates the spatial and directional tuning of Multi-Unit Activity (MUA) in mouse primary visual cortex and how MUA can reflect spatiotemporal structures contained in moving gratings. Analysis of multi-shank laminar electrophysiological recordings from mouse primary visual cortex indicates a directional preference for moving gratings around 180◦, while preferred spatial frequency peaks around 0.02 cycles per degree, which is similar as reported in single-unit studies. Using only features from MUA, we further achieved a significant performance in decoding spatial frequency or direc- tion of moving gratings, with average decoding performances of up to 58.54% for 8 directions, and 44% correctly identified spatial frequencies against chance level of 16.7%.

scholarly journals Flow stimuli reveal ecologically-appropriate responses in mouse visual cortex

2018 ◽  
Author(s):  
Luciano Dyballa ◽  
Mahmood S. Hoseini ◽  
Maria C. Dadarlat ◽  
Steven W. Zucker ◽  
Michael P. Stryker
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Frequency Analysis ◽  
Visual Processing ◽  
Temporal Frequency ◽  
Natural World ◽  
Spatial Frequencies ◽  
Spatial Frequency Analysis

AbstractAssessments of the mouse visual system based on spatial frequency analysis imply that its visual capacity is low, with few neurons responding to spatial frequencies greater than 0.5 cycles/degree. However, visually-mediated behaviors, such as prey capture, suggest that the mouse visual system is more precise. We introduce a new stimulus class—visual flow patterns—that is more like what the mouse would encounter in the natural world than are sine-wave gratings but is more tractable for analysis than are natural images. We used 128-site silicon microelectrodes to measure the simultaneous responses of single neurons in the primary visual cortex (V1) of alert mice. While holding temporal-frequency content fixed, we explored a class of drifting patterns of black or white dots that have energy only at higher spatial frequencies. These flow stimuli evoke strong visually-mediated responses well beyond those predicted by spatial frequency analysis. Flow responses predominate in higher spatial-frequency ranges (0.15–1.6 cycles/degree); many are orientation- or direction-selective; and flow responses of many neurons depend strongly on sign of contrast. Many cells exhibit distributed responses across our stimulus ensemble. Together, these results challenge conventional linear approaches to visual processing and expand our understanding of the mouse’s visual capacity to behaviorally-relevant ranges.Significance StatementThe visual system of the mouse is now widely studied as a model for development and disease in humans. Studies of its primary visual cortex (V1) using conventional grating stimuli to construct linear-nonlinear receptive fields suggest that the mouse must have very poor vision. Using novel stimuli resembling the flow of images across the retina as the mouse moves through the grass, we find that most V1 neurons respond reliably to very much finer details of the visual scene than previously believed. Our findings suggest that the conventional notion of a unique receptive field does not capture the operation of the neural network in mouse V1.

scholarly journals Human primary visual cortex (V1) is selective for second-order spatial frequency

2011 ◽  
Vol 105 (5) ◽  
pp. 2121-2131 ◽  
Author(s):  
Luke E. Hallum ◽  
Michael S. Landy ◽  
David J. Heeger
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Selective Adaptation ◽  
Second Order ◽  
Filter Model ◽  
First Order ◽  
Spatial Frequencies ◽  
Early Visual Cortex

A variety of cues can differentiate objects from their surrounds. These include “first-order” cues such as luminance modulations and “second-order” cues involving modulations of orientation and contrast. Human sensitivity to first-order modulations is well described by a computational model involving spatially localized filters that are selective for orientation and spatial frequency (SF). It is widely held that first-order modulations are represented by the firing rates of simple and complex cells (“first-order” neurons) in primary visual cortex (V1) that, likewise, have spatially localized receptive fields that are selective for orientation- and SF. Human sensitivity to second-order modulations is well described by a filter-rectify-filter (FRF) model, with first- and second-order filters selective for orientation and SF. However, little is known about how neuronal activity in visual cortex represents second-order modulations. We tested the FRF model by using an functional (f)MRI-adaptation protocol to characterize the selectivity of activity in visual cortex to second-order, orientation-defined gratings of two different SFs. fMRI responses throughout early visual cortex exhibited selective adaptation to these stimuli. The low-SF grating was a more effective adapter than the high-SF grating, incompatible with the FRF model. To explain the results, we extended the FRF model by incorporating normalization, yielding a filter-rectify-normalize-filter model, in which normalization enhances selectivity for second-order SF but only for low spatial frequencies. We conclude that neurons in human visual cortex are selective for second-order SF, that normalization (surround suppression) contributes to this selectivity, and that the selectivity in higher visual areas is simply fed forward from V1.

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