Conscious access and complexity of visual features

Imagine you are in your car driving to meet a friend at a restaurant you have never been to before. As an experienced driver, you don’t need to deliberately direct your gaze. Instead, your attention is automatically drawn to crossings far off in the distance, other moving vehicles, and relevant road signs. Without having to assert effort, your brain suppresses details in your immediate surroundings to enhance relevant information. When you arrive at the restaurant, you swiftly search through the crowd of strangers, assessing whether everyone is your friend within a fraction of a second. Your brain effortlessly evaluates each person with templates in your memory, first on crude features such as hair colour or height, and for anyone who fits these criteria, assessment is carried out on finer facial features. With our ability to use logical inferences based on experience we build templates of a target, which we use to efficiently scan through our environment. Regardless of how mundane this everyday task might seem; its completion requires several fundamental computational problems to be overcome. When driving a car and when searching a crowded room, you need to selectively enhance and suppress visual information, as processing all information equally is an inefficient use of resources. It can take several hundred milliseconds to fully process a complex natural scene (Kar et al., 2019), meaning that the processing of several visual objects must be happening in parallel. To add to this complexity, humans are continuously updating their goals (first, search for the bar across the whole room, then search for a person at the bar) based on information we are gaining within each moment. In this dissertation, I will address how the brain organizes information into categories, how items that are processed in parallel can interfere with each other, and at what levels of processing these interferences occur