Responses to interocular disparity correlation in the human cerebral cortex

Purpose: Perceiving binocular depth relies on the ability of our visual system to precisely match corresponding features in the left and right eyes. Yet how the human brain extracts interocular disparity correlation is poorly understood. Methods: We used functional magnetic resonance imaging (fMRI) to characterize brain regions involved in processing interocular disparity correlation. By varying the amount of interocular correlation of a disparity-defined random-dot-stereogram, we concomitantly controlled the perception of binocular depth and measured the percent Blood-Oxygenation-Level-Dependent (%BOLD)-signal in multiple regions-of-interest in the human occipital cortex and along the intraparietal sulcus. Results: A linear support vector machine classification analysis applied to cortical responses showed patterns of activation that represented different disparity correlation levels within regions-of-interest in the visual cortex. These also revealed a positive trend between the difference in disparity correlation and classification accuracy in V1, V3 and lateral occipital cortex. Classifier performance was significantly related to behavioural performance in dorsal visual area V3. Cortical responses to random-dot-stereogram stimuli were greater in the right compared to the left hemisphere. Conclusions: Our results show that multiple regions in the cerebral cortex are sensitive to changes in interocular disparity correlation, and that dorsal area V3 may play an important role in the early transformation of binocular disparity to depth perception

Effects of visual attention on stereoscopic depth perception in the human visual cortex

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Mapping the visual world to the human brain

The visual maps measured non-invasively in the brain of human and non-human primates reliably reflect the underlying neuronal responses recorded with invasive electrodes

Effects of Spatial and Feature Attention on Disparity-Rendered Structure-From-Motion Stimuli in the Human Visual Cortex

<div><p>An important advance in the study of visual attention has been the identification of a non-spatial component of attention that enhances the response to similar features or objects across the visual field. Here we test whether this non-spatial component can co-select individual features that are perceptually bound into a coherent object. We combined human psychophysics and functional magnetic resonance imaging (fMRI) to demonstrate the ability to co-select individual features from perceptually coherent objects. Our study used binocular disparity and visual motion to define disparity structure-from-motion (dSFM) stimuli. Although the spatial attention system induced strong modulations of the fMRI response in visual regions, the non-spatial system’s ability to co-select features of the dSFM stimulus was less pronounced and variable across subjects. Our results demonstrate that feature and global feature attention effects are variable across participants, suggesting that the feature attention system may be limited in its ability to automatically select features within the attended object. Careful comparison of the task design suggests that even minor differences in the perceptual task may be critical in revealing the presence of global feature attention.</p></div

Cortical responses to cylinders.

<p>A: Cortical responses to cylinders disambiguated by disparity under attended (open) and unattended (filled) conditions compared to a baseline of static dots with zero-disparity. B: Average BOLD response to attended cylinders disambiguated by disparity under clockwise (light gray) and counter-clockwise (dark gray) conditions compared to a baseline of static dots with zero-disparity. C: Average BOLD response to unattended cylinder when rotating in the same (light gray) or different (dark gray) directions to the attended cylinder compared to the baseline. All errors are ± s.e.m. averaged across left and right hemispheres and two scans within participant sessions.</p

Spatial attention increased BOLD response to cylinders.

<p>Icons on the top show a schematic view of the stimulus screen from the perspective of the participant. Left half of figure shows responses to two cylinders compared to a baseline composed of two fields of static zero-disparity dots, with attention directed to the left cylinder. The right half of the figure shows the same conditions with attention directed to the right cylinder. Borders of visual areas (white lines) were defined using standard retinotopic mapping. All data were fully cluster-corrected at p<0.05. The color bar indicates significance levels of activation maps with a z-statistic ranging from 2.3–12. The key gives the orientation of the flat patch in relation to the dorsal, ventral and medial axis. Light gray areas mark gyri, dark gray areas sulci.</p

Mean classification accuracy to cylinders.

<p>A: Mean classification accuracy to a cylinder (in left or right visual field) in the 100 most activated voxels V1 and other retinotopic visual areas (B–G). The white bars show the classification based on attended or unattended condition. Light gray bars indicate the classification of an attended cylinder rotating in a clockwise or counter-clockwise direction. Dark gray bars show the classification of the unattended cylinder rotating in the same or different direction as the attended cylinder. The black line at 0.5 indicates chance performance. Black error bars indicate Bonferroni-corrected 95% confidence intervals obtained by iterating the classification 10000 times. Red lines indicate Bonferroni-corrected 95% confidence intervals of the empirical null distribution obtained by iterating the classification with permuted labels 10000 times. Asterices indicate significant classification accuracy.</p

Stimuli and experimental paradigm.

<p>A: Structure-from-motion cylinders disambiguated by binocular disparity are perceived as rotating counter-clockwise (bottom left) or clockwise (bottom right) as controlled by the disparity of the right and left-wards moving surfaces (adapted from Dodd et al., 2001). B: Schematic diagram of the behavioral task used in the MRI-scanner, illustrating an example trial where attention is cued to the right side. For cued cylinders, participants reported whether the speed of rotation in the 1^st and 2^nd interval was different, while uncued cylinders were ignored.</p