scholarly journals Bio-inspired Binocular Disparity with Position-Shift Receptive Field

2010 ◽  
pp. 351-358
Author(s):  
Fernanda da C. e C. Faria ◽  
Jorge Batista ◽  
Helder Araújo
Keyword(s):  
Receptive Field ◽  
Binocular Disparity ◽  
Position Shift

Relationship Between Phase and Energy Methods for Disparity Computation

2000 ◽  
Vol 12 (2) ◽  
pp. 279-292 ◽  
Author(s):  
Ning Qian ◽  
Samuel Mikaelian
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Energy Method ◽  
Field Model ◽  
Binocular Disparity ◽  
Phase Method ◽  
Energy Methods ◽  
Disparity Maps ◽  
Position Shift ◽  
Shift Model

The phase and energy methods for computing binocular disparity maps from stereograms are motivated differently, have different physiological relevances, and involve different computational steps. Nevertheless, we demonstrate that at the final stages where disparity values are made explicit, the simplest versions of the two methods are exactly equivalent. The equivalence also holds when the quadrature-pair construction in the energy method is replaced with a more physiologically plausible phase-averaging step. The equivalence fails, however, when the phase-difference receptive field model is replaced by the position-shift model. Additionally, intermediate results from the two methods are always quite distinct. In particular, the energy method generates a distributed disparity representation similar to that found in the visual cortex, while the phase method does not. Finally, more elaborate versions of the two methods are in general not equivalent. We also briefly compare these two methods with some other stereo models in the literature.

Receptive field properties of neurons in area V3 of macaque monkey extrastriate cortex

1987 ◽  
Vol 57 (4) ◽  
pp. 889-920 ◽  
Author(s):  
D. J. Felleman ◽  
D. C. Van Essen
Keyword(s):  
Receptive Field ◽  
Binocular Disparity ◽  
Visual Fields ◽  
Direction Selectivity ◽  
Extrastriate Cortex ◽  
Thin Strip ◽  
Stimulus Motion ◽  
Form Analysis ◽  
Tuning Curves ◽  
Receptive Field Properties

Receptive field properties of 147 neurons histologically verified to be located in area V3 were investigated during semichronic recording from paralyzed anesthetized macaque monkeys. Quantitative analyses were made of neuron selectivities for direction, orientation, speed, binocular disparity, and color. The majority of neurons in V3 (76%) were strongly orientation selective; 40% demonstrated strong direction selectivity. Most cells were tuned for stimulus speed and almost half showed optimum responses at 16 degrees/s. The distribution of optimum speeds ranged primarily from 4 to 32 degrees/s. Several cells in V3 displayed multi-peaked orientation- and/or direction-tuning curves. These cells had two or more narrowly tuned peaks that were not co-axial. In some ways, they resemble higher-order hypercomplex cells of cat area 19 and may subserve a higher level of form or motion analysis than is seen at antecedent visual areas. Roughly half (45%) of the cells were selective for binocular disparity. Approximately half of these were tuned excitatory in that they showed weak responses when tested through either eye alone, but showed strong binocular facilitation centered on the fixation plane. The other disparity-selective cells were tuned inhibitory or asymmetric in their responses in front and behind the fixation plane. Contrary to previous reports, approximately 20% of the neurons in V3 were color selective in terms of showing a severalfold greater response to the best monochromatic wavelength compared with the worst. Color-tuning curves of the subset of color selective cells had, on average, a full bandwidth at half maximum response of 80-100 nm. A comparison of the receptive field properties of neurons in V3 to those in other areas of visual cortex suggests that V3, like MT, is well suited for the analysis of several aspects of stimulus motion. V3 may also be involved in some aspects of form analysis, particularly at low contrast levels. Comparison with area VP, a thin strip of cortex anterior to ventral V2, which was previously considered part of V3, indicates that direction selectivity is much more prevalent in V3 than in VP. Conversely, color-selective cells are the majority in VP but a minority in V3. This suggests that visual information is processed differently in the upper and lower visual fields.

Disparity-Selective Neurons in Area V4 of Macaque Monkeys

2002 ◽  
Vol 87 (4) ◽  
pp. 1960-1973 ◽  
Author(s):  
Masayuki Watanabe ◽  
Hiroki Tanaka ◽  
Takanori Uka ◽  
Ichiro Fujita
Keyword(s):  
Receptive Field ◽  
Binocular Disparity ◽  
Temporal Cortex ◽  
Intermediate Stage ◽  
Visual Pathway ◽  
Inferior Temporal Cortex ◽  
Tuning Curves ◽  
Area V4 ◽  
Ventral Visual Pathway ◽  
V4 Neurons

Area V4 is an intermediate stage of the ventral visual pathway providing major input to the final stages in the inferior temporal cortex (IT). This pathway is involved in the processing of shape, color, and texture. IT neurons are also sensitive to horizontal binocular disparity, suggesting that binocular disparity is processed along the ventral visual pathway. In the present study, we examined the processing of binocular disparity information by V4 neurons. We recorded responses of V4 neurons to binocularly disparate stimuli. A population of V4 neurons modified their responses according to changes of stimulus disparity; neither monocular responses nor eye movements could account for this modulation. Disparity-tuning curves were similar for different locations within a neuron's receptive field. Neighboring neurons recorded using a single electrode displayed similar disparity-tuning properties. These findings indicate that a population of V4 neurons is selective for binocular disparity, invariant for the position of the stimulus within the receptive field. The finding that V4 neurons with similar disparity selectivity are clustered suggests the existence of functional modules for disparity processing in V4.

scholarly journals Human primary visual cortex shows larger population receptive fields for binocular disparity-defined stimuli

2021 ◽  
Author(s):  
Ivan Alvarez ◽  
Samuel A. Hurley ◽  
Andrew J. Parker ◽  
Holly Bridge
Keyword(s):  
Receptive Field ◽  
Binocular Disparity ◽  
Receptive Fields ◽  
Stereoscopic Vision ◽  
Neural Representation ◽  
Receptive Field Properties ◽  
Visual Areas ◽  
Electrophysiological Studies ◽  
Specific Stimulation

AbstractThe visual perception of 3D depth is underpinned by the brain’s ability to combine signals from the left and right eyes to produce a neural representation of binocular disparity for perception and behaviour. Electrophysiological studies of binocular disparity over the past 2 decades have investigated the computational role of neurons in area V1 for binocular combination, while more recent neuroimaging investigations have focused on identifying specific roles for different extrastriate visual areas in depth perception. Here we investigate the population receptive field properties of neural responses to binocular information in striate and extrastriate cortical visual areas using ultra-high field fMRI. We measured BOLD fMRI responses while participants viewed retinotopic mapping stimuli defined by different visual properties: contrast, luminance, motion, correlated and anti-correlated stereoscopic disparity. By fitting each condition with a population receptive field model, we compared quantitatively the size of the population receptive field for disparity-specific stimulation. We found larger population receptive fields for disparity compared with contrast and luminance in area V1, the first stage of binocular combination, which likely reflects the binocular integration zone, an interpretation supported by modelling of the binocular energy model. A similar pattern was found in region LOC, where it may reflect the role of disparity as a cue for 3D shape. These findings provide insight into the binocular receptive field properties underlying processing for human stereoscopic vision.

scholarly journals Human Primary Visual Cortex Shows Larger Population Receptive Fields for Binocular Disparity-Defined Stimuli

2021 ◽  
Author(s):  
Ivan Alvarez ◽  
Samuel Hurley ◽  
Andrew John Parker ◽  
Holly Bridge
Keyword(s):  
Receptive Field ◽  
Binocular Disparity ◽  
Receptive Fields ◽  
Stereoscopic Vision ◽  
Neural Representation ◽  
Neural Population ◽  
Receptive Field Properties ◽  
Visual Areas ◽  
Electrophysiological Studies

Abstract The visual perception of 3D depth is underpinned by the brain's ability to combine signals from the left and right eyes to produce a neural representation of binocular disparity for perception and behavior. Electrophysiological studies of binocular disparity over the past two decades have investigated the computational role of neurons in area V1 for binocular combination, while more recent neuroimaging investigations have focused on identifying specific roles for different extrastriate visual areas in depth perception. Here we investigate the neural population receptive field properties of responses to binocular information in striate and extrastriate cortical visual areas using ultra-high field fMRI. We measured BOLD fMRI responses while participants viewed retinotopic-mapping stimuli defined by different visual properties: contrast, luminance, motion, correlated and anti-correlated stereoscopic disparity. By fitting each condition with a population receptive field model, we were able to compare quantitatively the size of the population receptive field for disparity-defined vs not disparity-defined stimulation conditions. We found larger population receptive fields for disparity compared to the contrast and luminance stimuli in area V1, the first stage of binocular combination, which likely reflects the binocular integration zone, an interpretation supported by modelling of the binocular energy model. A similar pattern was found in region LOC, where it may reflect the role of disparity as a cue for 3D shape. These findings provide insight into the binocular receptive field properties underlying processing for human stereoscopic vision.

scholarly journals Neural Mechanisms for Encoding Binocular Disparity: Receptive Field Position Versus Phase

1999 ◽  
Vol 82 (2) ◽  
pp. 874-890 ◽  
Author(s):  
Akiyuki Anzai ◽  
Izumi Ohzawa ◽  
Ralph D. Freeman
Keyword(s):  
Receptive Field ◽  
Spatial Frequency ◽  
Striate Cortex ◽  
Binocular Disparity ◽  
High Spatial Frequency ◽  
Mapping Technique ◽  
Relative Depth ◽  
Simple Cells ◽  
Wide Range ◽  
Left And Right

The visual system uses binocular disparity to discriminate the relative depth of objects in space. Because the striate cortex is the first site along the central visual pathways at which signals from the left and right eyes converge onto a single neuron, encoding of binocular disparity is thought to begin in this region. There are two possible mechanisms for encoding binocular disparity through simple cells in the striate cortex: a difference in receptive field (RF) position between the two eyes (RF position disparity) and a difference in RF profiles between the two eyes (RF phase disparity). Although there is evidence that supports each of these schemes, both mechanisms have not been examined in a single study to determine their relative roles. In this study, we have measured RF position and phase disparities of individual simple cells in the cat’s striate cortex to address this issue. Using a sophisticated RF mapping technique that employs binary m-sequences, we have obtained left and right eye RF profiles of two or more cells recorded simultaneously. A version of the reference-cell method was used to estimate RF position disparity. We find that RF position disparities generally are limited to values that are not sufficient to encode large binocular disparities. In contrast, RF phase disparities cover a wide range of binocular disparities and exhibit dependencies on RF orientation and spatial frequency in a manner expected for a mechanism that encodes binocular disparity. These results suggest that binocular disparity is encoded mainly through RF phase disparity. However, RF position disparity may play a significant role for cells with high spatial frequency selectivity that are constrained to have only small RF phase disparities.

Parallel processing of binocular disparity in the cat’s retinogeniculocortical pathways

1987 ◽  
Vol 232 (1268) ◽  
pp. 297-321 ◽  
Keyword(s):  
Receptive Field ◽  
Cortical Neurons ◽  
Binocular Disparity ◽  
Ganglion Cells ◽  
Border Region ◽  
Area 17 ◽  
Area 19 ◽  
Area Centralis ◽  
Receptive Field Disparity ◽  
The Mean

In the cat, parallel streams of information processing have been traced from X-, Y- and W-type retinal ganglion cells to visual cortical areas 17 (X-, Y- and W-type), 18 (Y-type) and 19 (W-type). In the present study we have examined, in the anaesthetized and paralysed adult cat, the role played by X-, Y- and W-subsystems, projecting to areas 17 and 19, in the processing of binocular retinal disparity. The tapetal reflection technique was used to monitor residual eye movements and to provide a map, for each eye, of the retinal blood vessels which could later be compared with retinal wholemounts stained with cresyl violet to reveal the area centralis. The receptive-field disparities of cells recorded from areas 17 and 19 were compared with each other and with reference to the visual axes defined by the area centralis of each eye. Cells of area 19 (receiving W-type input) had horizontal receptive-field disparities that were significantly more divergent than those of the cells in area 17 and 17–18 ‘border region’. Referred to the area centralis, the mean horizontal receptive-field disparity in area 19 was –0.5°( ± 0.8°). The mean horizontal receptive-field disparity of area 17 (receiving X-, Y- and W-type input) was convergent with respect to the visual axis at +2° (± 0.5°). Finally, the mean horizontal receptive-field disparity of the cells in the 17–18 border region (which receive mainly Y -type input) was even more convergent (2.6° ± 1.5°) than that of area 17. Binocular interactions of cortical neurons were tested with the Risley biprism technique. Area 19 cells had maximal responses to binocular stimulation when the receptive-field disparities were either close to zero or slightly divergent. In contrast, area 17 cells tended to respond optimally to disparities that were either slightly or strongly convergent. At the level of the lateral geniculate nucleus there were significant differences between the receptive-field disparities inferred from the comparison of receptive-field positions of adjacent neurons recorded on either side of the border between the A and A1 geniculate laminae and those inferred from a similar comparison at the C1–C2 border. The mean horizontal disparities inferred from the interlaminar comparison at the A–A1 border were +2.1° (±0.3°); those inferred from the interlaminar comparison at the C1–C2 border –0.2 (± 0.2°) were more divergent. This difference is consistent with the idea that there is a subclass of W-type ganglion cells projecting to area 19 via the C-laminae which codes more divergent disparities than the X-type cell pathway projecting through the A-laminae to area 17. Our results support Levick’s (1977) hypothesis that the X- and Y- systems play different roles in the processing of binocular disparity information; the Y-system (areas 17 and 18) coding for convergent disparities, the X-system (area 17) coding for the binocular information in the fixation plane. Furthermore, the data are consistent with our extension of Levick’s hypothesis that the W-subsystem projection to area 19 processes divergent disparities beyond the fixation plane.

A Coarse-to-Fine Disparity Energy Model with Both Phase-Shift and Position-Shift Receptive Field Mechanisms

2004 ◽  
Vol 16 (8) ◽  
pp. 1545-1577 ◽  
Author(s):  
Yuzhi Chen ◽  
Ning Qian
Keyword(s):  
Phase Shift ◽  
Receptive Field ◽  
Tuning Curve ◽  
Energy Model ◽  
Disparity Estimation ◽  
Population Response ◽  
Large Stimulus ◽  
Wide Range ◽  
Position Shift ◽  
Coarse To Fine

Numerous studies suggest that the visual system uses both phase-and position-shift receptive field (RF) mechanisms for the processing of binocular disparity. Although the difference between these two mechanisms has been analyzed before, previous work mainly focused on disparity tuning curves instead of population responses. However, tuning curve and population response can exhibit different characteristics, and it is the latter that determines disparity estimation. Here we demonstrate, in the framework of the disparity energy model, that for relatively small disparities, the population response generated by the phase-shift mechanism is more reliable than that generated by the position-shift mechanism. This is true over a wide range of parameters, including the RF orientation. Since the phase model has its own drawbacks of underestimating large stimulus disparity and covering only a restricted range of disparity at a given scale, we propose a coarse-to-fine algorithm for disparity computation with a hybrid of phase-shift and position-shift components. In this algorithm, disparity at each scale is always estimated by the phase-shift mechanism to take advantage of its higher reliability. Since the phase-based estimation is most accurate at the smallest scale when the disparity is correspondingly small, the algorithm iteratively reduces the input disparity from coarse to fine scales by introducing a constant position-shift component to all cells for a given location in order to offset the stimulus disparity at that location. The model also incorporates orientation pooling and spatial pooling to further enhance reliability. We have tested the algorithm on both synthetic and natural stereo images and found that it often performs better than a simple scale-averaging procedure.

Computing Stereo Disparity and Motion with Known Binocular Cell Properties

1994 ◽  
Vol 6 (3) ◽  
pp. 390-404 ◽  
Author(s):  
Ning Qian
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Stereo Vision ◽  
Motion Detection ◽  
Binocular Disparity ◽  
Stereo Disparity ◽  
Random Dot Stereograms ◽  
Disparity Maps ◽  
Physiological Studies

Many models for stereo disparity computation have been proposed, but few can be said to be truly biological. There is also a rich literature devoted to physiological studies of stereopsis. Cells sensitive to binocular disparity have been found in the visual cortex, but it is not clear whether these cells could be used to compute disparity maps from stereograms. Here we propose a model for biological stereo vision based on known receptive field profiles of binocular cells in the visual cortex and provide the first demonstration that these cells could effectively solve random dot stereograms. Our model also allows a natural integration of stereo vision and motion detection. This may help explain the existence of units tuned to both disparity and motion in the visual cortex.

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