Measuring Integration Processes in Visual Symmetry with Frequency-Tagged EEG.

Symmetry is a highly salient feature of the natural world which requires integration of visual features over space. The aim of the current work is to isolate dynamic neural correlates of symmetry-specific integration processes. We measured steady-state visual evoked potentials (SSVEP) as participants viewed symmetric patterns comprised of distinct spatial regions presented at two different frequencies (f and f). We measured intermodulation components, shown to reflect non-linear processing at the neural level, indicating integration of spatially separated parts of the pattern. We generated a wallpaper pattern containing two reflection symmetry axes by tiling the plane with a two-fold reflection symmetric unit-pattern and split each unit-pattern diagonally into separate parts which could be presented at different frequencies. We compared SSVEPs measured for wallpapers and control patterns for which both images were equal in terms of translation and rotation symmetry but reflection symmetry could only emerge for the wallpaper pattern through integration of the image-pairs. We found that low-frequency intermodulation components differed between the wallpaper and control stimuli, indicating the presence of integration mechanisms specific to reflection symmetry. These results showed that spatial integration specific to symmetry perception can be isolated through a combination of stimulus design and the frequency tagging approach.