Information compression in the visual brain (Redundancy masking)

Our environment is filled with vast amounts of visual information. Processing all the information available in a typical visual scene would quickly overwhelm the human brain. To cope with the available information, a number of mechanisms, such as attentional prioritization and ensemble coding, protect the visual brain by filtering out nonessential information. In this project, we will investigate a recently discovered phenomenon (‘redundancy masking’ - RM) which likewise seems to function as a means to prevent information overload. In RM, information is compressed in repeating patterns that contain redundant information. In this project, using methods of psychophysics and EEG frequency tagging, we will further characterize RM, investigate its relations to other visual phenomena, and aim to pinpoint its role in the larger cognitive architecture. The overarching goal is to better understand how the visual brain selects, discards, and prioritizes information.
Requirements:
- Interest and motivation to empirically work on questions such as how the mind works  
- Programming (e.g., MATLAB and Python) 
- Running participants (including preparing/clearing EEG equipment, debriefing participants, etc.) several times per week