Illusions of visual orientation: comparisons between perceptual and visuo-motor tasks

The Milner and Goodale (1995) model of dual cortical visual systems suggests that, in the primate cortex, separate neural substrates dominate the tasks of visual perception and visuo-motor control. This model derives from a number of independent sources of evidence: anatomical, physiological and behavioural. Neuropsychological evidence in humans suggests that visual perception and visuo-motor control can be selectively impaired through damage to the ventral and dorsal visual streams respectively. Evidence has emerged that in the healthy human visual cortex, differentiable effects of visual illusions can be found between the two measures of perception and visuo- motor control. This evidence has been cited to support the Milner and Goodale (1995) model. The series of studies reported in this dissertation used a similar, but methodologically revised application of the illusion paradigm in the novel domain of orientation. Using two types of visual illusions, the simultaneous tilt illusion (STI) and the rod-and-frame illusion (RFI), a series of studies found patterns of association, dissociation and interaction that strongly support the Mihier and Goodale model. The critical issue, in terms of predicting the pattern of effects across perception and visuo-motor control tasks, was found to be the siting of the causal mechanisms underlying the illusion employed

The neurobiological basis of inter-individual variability in visual perception

Visual perception is the conscious experience that is unique to each individual. However, conventional neuroscience studies tend to focus on the commonality in visual perception across different individuals and fail to address the key properties of any conscious experience - its individuality and subjectivity. In my thesis, I investigated the neurobiological basis of perceptual variability across healthy human adults, through a combined approach of psychophysics, in-vivo MR imaging, in-vitro histological imaging, and computational modeling. I found that perception of local and global visual features, as assessed respectively from visual discrimination of local feature details and visual illusion induced by global feature contexts, exhibits a ten-fold inter-individual variability that correlates with the morphology of primary visual cortex. Specifically, an increase in the surface area of primary visual cortex is associated with a shift in the scope of visual feature perception from global-context-oriented to local-detail-oriented, where individuals with smaller visual cortical surface area experience stronger visual illusion and individuals with larger visual cortical surface area perform more accurate visual discrimination. Intriguingly, an increase in the thickness of primary visual cortex has the opposite impact, where visual discrimination is less accurate at visual field locations corresponding to thicker parts of primary visual cortex. The functional impact that visual cortical anatomy exerts on visual feature perception is recapitulated in visual neural selectivity. I found that in individuals with larger surface area of primary visual cortex, visual cortical neurons exhibit higher selectivity and respond to a smaller, localised visual field range. By contrast, at thicker parts of primary visual cortex, visual cortical neurons exhibit lower selectivity and respond to a larger, globalised visual field range. The opposite functional impacts exhibited by the two morphological dimensions, the surface area and the thickness, of primary visual cortex can nonetheless be unified under the framework of intracortical scaling. I found that the scaling of intracortical connectivity with visual cortical morphology shifts the scope of both visual feature perception and visual neural selectivity between global- and local-oriented. Together these findings revealed that the individuality in visual feature perception arises neurobiologically from the variability in visual cortical morphology, through the mediation of intracortical connectivity and visual neural selectivity

The Impact of Affect on Neural Mechanisms Underlying Orientation Perception

The underlying mechanisms used to process 2D visual information to form a unified 3D percept of the world remain largely unknown. Previous work in our lab has shown that accurate 3D perception of textured surfaces depends on the presence of specific patterns of orientation flows in the retinal image. Recent research has shown that affective state may influence the visual perception of oriented patterns. Relative to neutral face stimuli, fearful face stimuli have been shown to increase sensitivity to orientation of low spatial frequency patterns and decrease sensitivity to orientation of high spatial frequency patterns. How affective state influences the perception of orientation as used in more complex patterns and in patterns that convey 3D shape, which is processed higher in the visual pathway, is currently not known. Using the Radboud face database, we examined the effects of affective fear versus neutral face primes on orientation sensitivity using grating and plaid stimuli of low (2cpd) and high (4cpd) spatial frequency, and on 3D curvature sensitivity using images of 3D surfaces textured with 2cpd and 4cpd gratings. In Experiment One, we examined the role of fear on 2D orientation sensitivity of tilted gratings and plaid stimuli at both low and high spatial frequencies. Results replicated previous research showing increased orientation sensitivity to low frequency patterns and decreased orientation sensitivity to high frequency patterns; however, our results limit this finding as orientation-specific to vertically oriented stimuli only. Therefore, differences in tilt thresholds for spatial frequency were shown to be dependent on orientation information contained within the pattern. In Experiment Two, we investigated the role of fear on 3D shape perception for surfaces slanted and corrugated in depth patterned with low and high frequency gratings. Results indicate that differences in the affective influence of orientation sensitivity for each spatial frequency were specific to processing area along the visual pathway. For 2D images conveying 3D shape, fear diminished, rather than increased, sensitivity for the low spatial frequency condition. However, for slanted surfaces, results indicated affective influence per spatial frequency for direction of slant. For corrugated surfaces, affective influence was found to be orientation specific for vertically corrugated stimuli patterned with horizontal gratings but was not found to have differential effects on spatial frequency. Therefore, affect may differentially influence visual processing of spatial frequency on orientation at multiple areas along the pathway. In Experiment Three, we assessed the contributions of the presence of a face prime, paradigm, and ordering effects on our results from Experiment One. Results confirm the robust nature of the affective influence of fear on the relationship between spatial frequency and orientation, as differences were not shown to be a result of no face primes, paradigm differences, or ordering effects. Taken together, our results indicate that the top-down modulation of affect differentially influences the saliency of spatial frequency information for orientation processing differently along multiple areas of the visual pathway

Computational Neural Models of Spatial Integration in Perceptual Grouping

Recent developments in the neural computational modeling of perceptual grouping are described with reference to a newly proposed taxonomy to formalize mechanisms of spatial integration. This notational framework and nomenclature is introduced in or-der to clarify key properties common to all or most models, while permitting unique attributes of each approach to be independently examined. The strength of spatial integration in the models that are considered is always some function of the distances and relative alignments in perceptual space of the centers of units representing orien-tational features or energy in a visual scene. We discuss the signicance of variations of the constituents of an activation function for spatial integration, and also consider the larger modeling framework in which this function is applied in each approach. We also discuss the relationship of feedforward and feedback mechanisms and the issues of self-organization as core principles underlying the establishment of spatial integra-tion mechanisms. The relationship of the grouping models to models of other visual competencies is considered with respect to prospects for future research. 354 From Fragments to Object

Activity in area V3A predicts positions of moving objects

No description supplie