Modeling Magnification and Anisotropy in the Primate Foveal Confluence

A basic organizational principle of the primate visual system is that it maps the visual environment repeatedly and retinotopically onto cortex. Simple algebraic models can be used to describe the projection from visual space to cortical space not only for V1, but also for the complex of areas V1, V2 and V3. Typically a conformal (angle-preserving) projection ensuring local isotropy is regarded as ideal and primate visual cortex is often regarded as an approximation of this ideal. However, empirical data show systematic deviations from this ideal that are especially relevant in the foveal projection. The aims of this study were to map the nature of anisotropy predicted by existing models, to investigate the optimization targets faced by different types of retino-cortical maps, and finally to propose a novel map that better models empirical data than other candidates. The retino-cortical map can be optimized towards a space-conserving homogenous representation or a quasi-conformal mapping. The latter would require a significantly enlarged representation of specific parts of the cortical maps. In particular it would require significant enlargement of parafoveal V2 and V3 which is not supported by empirical data. Further, the recently published principal layout of the foveal singularity cannot be explained by existing models. We suggest a new model that accurately describes foveal data, minimizing cortical surface area in the periphery but suggesting that local isotropy dominates the most foveal part at the expense of additional cortical surface. The foveal confluence is an important example of the detailed trade-offs between the compromises required for the mapping of environmental space to a complex of neighboring cortical areas. Our models demonstrate that the organization follows clear morphogenetic principles that are essential for our understanding of foveal vision in daily life

Cloverleaf Clusters: A Common Macrostructural Organization across Human Visual and Auditory Cortex

One of the fundamental properties of mammalian brains is that sensory regions of cortex are organized into multiple, functionally specialized cortical field maps (CFMs). An individual CFM is composed of two orthogonal topographical representations, reflecting two essential aspects of a sensory feature space. Each CFM is thought to subserve a specific computation or set of computations that underlie particular perceptual behaviors by enabling the comparison and combination of the information carried by the various specialized neuronal populations within this cortical region. Multiple adjacent CFMs, in turn, have now been shown by multiple laboratories to be organized in visual and auditory cortex into a macrostructural pattern called the cloverleaf cluster. CFMs within cloverleaf clusters tend to share properties such as receptive field distribution, cortical magnification, and processing specialization. This chapter will review the evidence for CFM and cloverleaf cluster organization across human visual and auditory cortex and will discuss the utility of these measurements for determining cortical structure and function and for investigating what changes occur in sensory cortex following various types of trauma or disease

Changes in Visual Cortex in Healthy Aging and Dementia

This chapter reviews the differences in specific structural and functional characteristics of human visual cortex among young adults, healthy aging adults, and patients with dementia, with a primary focus on those with Alzheimer’s disease (AD). Such visual cortex changes have been shown to underlie many of the behavioral deficits that develop in healthy aging and AD. Measurements of disordered visual cortex in dementia patients may be possible early in the course of neurodegeneration and thus may be useful for improving early diagnosis of these devastating diseases

Near-optimal combination of disparity across a log-polar scaled visual field

The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment

Form in Darkness: Linking Visual Cortex Structure With Spontaneous Neural Function

Spontaneous neural activity within visual cortex is synchronized at varying spatial scales, from the cytoarchitecural level of individual neurons to the coarse scale of whole regions. The neural basis of this synchronicity remains ambiguous. In this thesis, we focus on the role visual experience plays in organizing the spontaneous activity within the visual system. We start in Chapter 2 by creating a means by which to analyze homologous patches of cortex between sighted and blind individuals, as lack of vision precludes the use of traditional stimulus-driven mapping techniques. We find that anatomy alone could indeed predict the retinotopic organization of an individual\u27s striate cortex with an accuracy equivalent to the length of a typical mapping experiment. Chapter 3 applies this approach to analyze the organization of spontaneous signals within the striate cortex of blind and sighted subjects. We find that lack of visual experience produces a subtle change in the pattern of corticocortico correlations only between the hemispheres, and that these correlations are best modeled as function of cortical distance, not retinotopy. Chapter 4 expands our analysis to include areas V2 and V3. Here, we find that persistent visual experience supports network-level neural synchrony between spatially distributed cortical visual areas at both a coarse (regional) and fine (topographic) scale. Together, these results allow us model the organization of spontaneous activity in visual cortex as a combination of network signals linked to visual function and intrinsic signals coupled to structural connections. In the final chapter, we examine possible top-down mediators that may further modulate this network-level correlation. Minimal change in synchronicity is observed in a subject with a corpus callosotomy, suggesting the preeminence of bottom-up inputs. Taken together, this work advances our understanding of the origins of coherent spontaneous neural activity within visual cortex

Peripheral vision and pattern recognition:a review

We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding