Fractal dimension of EEG signal senses complexity of fractal animations

Fractal and self-similar patterns are ubiquitous in nature and have been the subject of extensive research in recent years. These patterns manifest across various spatial and temporal scales, yet the neural mechanisms underlying their perception remain poorly understood. We hypothesized that the complexity of visual stimuli directly influences the complexity of brain information processing, such that changes in the fractal dimension of visual animations would correspond to changes in the fractal pattern of EEG signals. To test this, EEG data were recorded from fifteen healthy participants as they viewed a series of 2D fractal animations. The fractal dimension of each animation frame was calculated using the box-counting method, while the fractal dimensions of 32 EEG channels were computed in a frequency-specific manner. Pearson’s correlation analysis was then used to assess the relationship between the fractal dimension patterns of the animations and the EEG signals. Results revealed that the complexity of fractal animations is primarily reflected in changes in the fractal dimension of EEG signals in the centro-parietal and parietal regions. This suggests that as visual stimulus complexity increases, the brain enhances the complexity of its information processing to better perceive and interpret the stimuli.