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.

scholarly journals Orientation tuning depends on spatial frequency in mouse visual cortex

2016 ◽  
Author(s):  
Inbal Ayzenshtat ◽  
Jesse Jackson ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Orientation Selectivity ◽  
Natural Scenes ◽  
Response Properties ◽  
Layer 2 ◽  
Mouse Visual Cortex

AbstractThe response properties of neurons to sensory stimuli have been used to identify their receptive fields and functionally map sensory systems. In primary visual cortex, most neurons are selective to a particular orientation and spatial frequency of the visual stimulus. Using two-photon calcium imaging of neuronal populations from the primary visual cortex of mice, we have characterized the response properties of neurons to various orientations and spatial frequencies. Surprisingly, we found that the orientation selectivity of neurons actually depends on the spatial frequency of the stimulus. This dependence can be easily explained if one assumed spatially asymmetric Gabor-type receptive fields. We propose that receptive fields of neurons in layer 2/3 of visual cortex are indeed spatially asymmetric, and that this asymmetry could be used effectively by the visual system to encode natural scenes.Significance StatementIn this manuscript we demonstrate that the orientation selectivity of neurons in primary visual cortex of mouse is highly dependent on the stimulus SF. This dependence is realized quantitatively in a decrease in the selectivity strength of cells in non-optimum SF, and more importantly, it is also evident qualitatively in a shift in the preferred orientation of cells in non-optimum SF. We show that a receptive-field model of a 2D asymmetric Gabor, rather than a symmetric one, can explain this surprising observation. Therefore, we propose that the receptive fields of neurons in layer 2/3 of mouse visual cortex are spatially asymmetric and this asymmetry could be used effectively by the visual system to encode natural scenes.Highlights–Orientation selectivity is dependent on spatial frequency.–Asymmetric Gabor model can explain this dependence.

scholarly journals Sub-Optimality of the Early Visual System Explained Through Biologically Plausible Plasticity

2021 ◽  
Vol 15 ◽  
Author(s):  
Tushar Chauhan ◽  
Timothée Masquelier ◽  
Benoit R. Cottereau
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Spike Timing ◽  
Orientation Tuning ◽  
Biologically Relevant ◽  
Tuning Curves ◽  
Stdp Rule ◽  
Early Visual Cortex ◽  
Minimisation Problem

The early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often studied under the assumption that neural populations are optimised for the most efficient (in terms of energy, information, spikes, etc.) representation of natural statistics. Normative models such as Independent Component Analysis (ICA) and Sparse Coding (SC) consider the phenomenon as a generative, minimisation problem which they assume the early cortical populations have evolved to solve. However, measurements in monkey and cat suggest that receptive fields (RFs) in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the RFs do not emerge through a global minimisation of generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity (STDP). Using a network endowed with an abstract, rank-based STDP rule, we show that the shape and orientation tuning of the converged units are remarkably close to single-cell measurements in the macaque primary visual cortex. We quantify this similarity using physiological parameters (frequency-normalised spread vectors), information theoretic measures [Kullback–Leibler (KL) divergence and Gini index], as well as simulations of a typical electrophysiology experiment designed to estimate orientation tuning curves. Taken together, our results suggest that compared to purely generative schemes, process-based biophysical models may offer a better description of the suboptimality observed in the early visual cortex.

Processing of first-order motion in marmoset visual cortex is influenced by second-order motion

2006 ◽  
Vol 23 (5) ◽  
pp. 815-824 ◽  
Author(s):  
NICK BARRACLOUGH ◽  
CHRIS TINSLEY ◽  
BEN WEBB ◽  
CHRIS VINCENT ◽  
ANDREW DERRINGTON
Keyword(s):  
Visual Cortex ◽  
Low Frequency ◽  
Second Order ◽  
The Other ◽  
Motion Processing ◽  
Single Neurons ◽  
First Order ◽  
The Third ◽  
Early Visual Cortex ◽  
Direction Sensitivity

We measured the responses of single neurons in marmoset visual cortex (V1, V2, and the third visual complex) to moving first-order stimuli and to combined first- and second-order stimuli in order to determine whether first-order motion processing was influenced by second-order motion. Beat stimuli were made by summing two gratings of similar spatial frequency, one of which was static and the other was moving. The beat is the product of a moving sinusoidal carrier (first-order motion) and a moving low-frequency contrast envelope (second-order motion). We compared responses to moving first-order gratings alone with responses to beat patterns with first-order and second-order motion in the same direction as each other, or in opposite directions to each other in order to distinguish first-order and second-order direction-selective responses. In the majority (72%, 67/93) of cells (V1 73%, 45/62; V2 70%, 16/23; third visual complex 75%, 6/8), responses to first-order motion were significantly influenced by the addition of a second-order signal. The second-order envelope was more influential when moving in the opposite direction to the first-order stimulus, reducing first-order direction sensitivity in V1, V2, and the third visual complex. We interpret these results as showing that first-order motion processing through early visual cortex is not separate from second-order motion processing; suggesting that both motion signals are processed by the same system.

scholarly journals The spatial structure of feedforward information in mouse primary visual cortex

2019 ◽  
Author(s):  
Jun Zhuang ◽  
Rylan S Larsen ◽  
Kevin T Takasaki ◽  
Naveen D Ouellette ◽  
Tanya L Daigle ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spatial Structure ◽  
Structural Properties ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Laminar Structure ◽  
Motion Direction ◽  
Multiple Modalities ◽  
New Model ◽  
Spatial Frequencies

Location-sensitive and motion-sensitive units are the two major functional types of feedforward projections from lateral genicular nucleus (LGN) to primary visual cortex (V1) in mouse. The distribution of these inputs in cortical depth remains under debate. By measuring the calcium activities of LGN axons in V1 of awake mice, we systematically mapped their functional and structural properties. Although both types distributed evenly across cortical depth, we found that they differ significantly across multiple modalities. Compared to the location-sensitive axons, which possessed confined spatial receptive fields, the motion-sensitive axons lacked spatial receptive fields, preferred lower temporal, higher spatial frequencies and had wider horizontal bouton spread. Furthermore, the motion-sensitive axons showed a strong depth-dependent motion direction bias while the location-sensitive axons showed a depth-independent OFF dominance. Overall, our results suggest a new model of receptive biases and laminar structure of thalamic inputs to V1.

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.

Spatial Structure and Symmetry of Simple-Cell Receptive Fields in Macaque Primary Visual Cortex

2002 ◽  
Vol 88 (1) ◽  
pp. 455-463 ◽  
Author(s):  
Dario L. Ringach
Keyword(s):  
Visual Cortex ◽  
Spatial Structure ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Image Coding ◽  
Population Analysis ◽  
Receptive Fields ◽  
Simple Cell ◽  
Field Function ◽  
Symmetry Classes

I present measurements of the spatial structure of simple-cell receptive fields in macaque primary visual cortex (area V1). Similar to previous findings in cat area 17, the spatial profile of simple-cell receptive fields in the macaque is well described by two-dimensional Gabor functions. A population analysis reveals that the distribution of spatial profiles in primary visual cortex lies approximately on a one-parameter family of filter shapes. Surprisingly, the receptive fields cluster into even- and odd-symmetry classes with a tendency for neurons that are well tuned in orientation and spatial frequency to have odd-symmetric receptive fields. The filter shapes predicted by two recent theories of simple-cell receptive field function, independent component analysis and sparse coding, are compared with the data. Both theories predict receptive fields with a larger number of subfields than observed in the experimental data. In addition, these theories do not generate receptive fields that are broadly tuned in orientation and low-pass in spatial frequency, which are commonly seen in monkey V1. The implications of these results for our understanding of image coding and representation in primary visual cortex are discussed.

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 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.

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