Contrast Invariant Orientation Tuning And Efficient Selection In Human Visual Cortex

Contrast-invariant Orientation Tuning and Efficient Selection in Human Visual Cortex

The visual system is a complex network of structures that work together to process and make sense of visual information derived from the surrounding environment. This dissertation explores the challenges faced by the visual system, both externally and internally, in achieving its goal of providing a coherent perception of the visual world. Chapter 2 focuses on contrast-invariant orientation tuning, a remarkable ability of the visual system to maintain stable perception regardless of changes in stimulus contrasts. While extensively studied in non-human primates, the existence of contrast-invariant orientation tuning in human visual cortex has been uncertain. I present evidence that orientation tuning in human visual cortex remains invariant to changes in stimulus contrast. Chapter 3 investigates the neural mechanism of selective attention and its impact on contrast-discrimination behavior. By employing different task designs with varying numbers of targets, the association between the number of targets and different attention mechanisms is examined. It is demonstrated that the efficient selection mechanism is utilized when multiple targets are present, while both the efficient selection and response gain mechanisms are associated with fewer targets. Also, the efficient selection model proves to be effective in explaining the behavior in attention tasks. In investigating these mechanisms, I utilize the steady-state visual evoked potential (SSVEP) frequency tagging technique involving multiple input stimuli, which is an effective tool for studying both sensory and cognitive processes. This dissertation contributes to our understanding of how the human visual system adapts to external changes and internal demands, shedding light on the mechanisms of contrast-invariant orientation tuning and selective attention.

Cumulated Index Medicus

Advanced Computing in Industrial Mathematics

This book gathers the peer-reviewed proceedings of the 13th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'18, held in Sofia, Bulgaria. The general theme of BGSIAM'18 was industrial and applied mathematics with particular focus on: mathematical physics, numerical analysis, high performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, biomedical and engineering applications.