Investigation of complex and hypercomplex receptive fields of visual cortex of the cat as spatial frequency filters

1973 ◽  
Vol 13 (10) ◽  
pp. 1875-IN6 ◽  
Author(s):  
V.D. Glezer ◽  
V.A. Ivanoff ◽  
T.A. Tscherbach
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Receptive Fields

An investigation of spatial frequency characteristics of the complex receptive fields in the visual cortex of the cat

1976 ◽  
Vol 16 (8) ◽  
pp. 789-797 ◽  
Author(s):  
V.D. Glezer ◽  
A.M. Cooperman ◽  
V.A. Ivanov ◽  
T.A. Tsherbach
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Receptive Fields ◽  
Frequency Characteristics

scholarly journals Projection of orthogonal tiling from the retina to the visual cortex

2020 ◽  
Author(s):  
Jaeson Jang ◽  
Min Song ◽  
Gwangsu Kim ◽  
Se-Bum Paik
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Spatial Organization ◽  
Ocular Dominance ◽  
Receptive Fields ◽  
Orientation Tuning ◽  
List Type ◽  
Strongly Correlated ◽  
Electrode Recording ◽  
Alignment Angle

AbstractIn higher mammals, the primary visual cortex (V1) is organized into diverse tuning maps of visual features such as orientation, spatial frequency and ocular dominance. The topography of these maps is observed to intersect orthogonally, implying that a developmental principle for efficient tiling of sensory modules may exist. However, it remains unclear how such a systematic relationship among cortical tuning maps could develop. Here, we show that the orthogonal organization of tuning modules already exist in retinal ganglion cell (RGC) mosaics, and that this provides a blueprint of the orthogonal organization in V1. Firstly, from the analysis of multi-electrode recording data in V1, we found that the ON-OFF subregion distance of receptive fields varies periodically across the cortical surface, strongly correlated to ocular dominance and spatial frequency in the area. Further, the ON-OFF alignment angle, that is orthogonal to the ON-OFF distance, appears to correlate with orientation tuning. These suggest that the orthogonal organization in V1 may originate from the spatial organization of the ON-OFF receptive fields in the bottom-up projections, and this scenario was tested from analysis of the RGC mosaics data in monkeys and cats. We found that the ON-OFF RGC distance and ON-OFF angle of neighbouring RGCs are organized into a topographic tiling across mosaics, analogous to the orthogonal intersection of cortical tuning maps. These findings suggest that the regularly structured ON-OFF patterns mirrored from a retina may initiate efficient tiling of functional domains in V1.HighlightsOrthogonal organization of visual tuning maps are observed in both V1 and the retinaCortical tuning maps are correlated with the profile of ON-OFF feedforward projectionsThe profile of ON-OFF receptive fields varies periodically across the V1 surfaceRegularly structured RGC patterns initiate the orthogonal tiling of sensory modules in 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.

Comments on organization and spatial-frequency characteristics of receptive fields in the visual cortex

1978 ◽  
Vol 18 (7) ◽  
pp. 887-889 ◽  
Author(s):  
V.D. Glezer ◽  
V.E. Gauzelman ◽  
T.A. Tsherbach ◽  
K.N. Dudkin
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Receptive Fields ◽  
Frequency Characteristics

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.

RECEPTIVE FIELD PROPERTIES OF NEAR NEIGHBOR ORIENTATION SELECTIVE NEURONS IN THE VISUAL CORTEX: A MODELING STUDY

2005 ◽  
Vol 15 (01n02) ◽  
pp. 31-40
Author(s):  
BASABI BHAUMIK ◽  
ALOK AGARWAL ◽  
MANISH MANOHAR
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Spatial Frequency ◽  
Receptive Fields ◽  
Near Neighbor ◽  
Orientation Tuning ◽  
Cortical Cells ◽  
Orientation Preference ◽  
Receptive Field Properties ◽  
Wide Range

The primary visual cortex is organized into clusters of cells having similar receptive fields (RFs). A purely feedforward model has been shown to produce realistic simple cell receptive fields. The modeled cells capture a wide range of receptive field properties of orientation selective cortical cells. We have analyzed the responses of 78 nearby cell pairs to study which RF properties are clustered. Orientation preference shows strongest clustering. Orientation tuning width (hwhh) and tuning height (spikes/sec) at the preferred orientation are not as tightly clustered. Spatial frequency is also not as tightly clustered and RF phase has the least clustering. Clustering property of orientation preference, orientation tuning height and width depend on the location of cells in the orientation map. No such location dependence is observed for spatial frequency and RF phase. Our results agree well with experimental data.

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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