An EEG study to analyze the rain responses to fractal animation

Introduction: Visual sense has an important role in shaping human understanding of the natural world. Many studies have been done on the types of visual stimuli. In fact, there are different techniques to investigate different characteristics of EEG signals. For instance, fractal analysis and approximate entropy talk about randomness and complexity of EEG signals. Fractals are infinitely complex patterns that are self-similar across different scales. The fractal dimension can describe the inherent irregularity and complexity of natural objects. In this study, association between fractal dimensions of visual stimuli (fractal animation) and scaling properties of the EEG signal is investigated. Objectives: In this study, we aim to describe how the complexity of visual stimuli influences the complexity of information processing in the brain. To the best our knowledge, it is the first time that brain mechanism in response to 2D or 3D fractal animations have been investigated. We hypothesized that complexity of visual stimuli explained by fractal dimension of 2D or 3D animations could be directly transferred to the complexity of brain signal explained by FD of EEG. Methods: We produced twenty 2D and 3D fractal animations. After video processing, we extracted the fractal dimension of each frames by box counting method. Subsequently, a group of 15 healthy young adults (age: 20-30, all male, right hand) were recruited. The subjects were exposed to the 2D/3D fractal animations and their brain responses to the stimuli were recorded using a 32-channels EEG recorder. Then, fractal dimensions of the cleaned EEG data were calculated using Katz’s method in a frequency band-specific manner. Finally, association between the fractal dimensions of animations and fractal dimensions of the brain signals were calculated using the Pearson's correlation algorithm. Results: FDs of EEG signals mainly at the parietal regions showed correlation with FDs of 2D animations. The results were frequency-band specific and significant correlations were observed at the (P3, Pz, CP3, CPz, C3) in alpha band, and (Cz, CPz, Pz, CP4) in beta band. These results indicate importance of alpha and beta complexities at the parietal regions while a subject perceives a fractal animation. Conclusion: The results indicate a significant relationship between the self-similarities in fractal animations and self-similarities of the brain signals. It means when the complexity of visual stimuli increases the mechanism of information processing in the brain also enhance its complexity to better attend and comprehend the stimuli. Such a finding could help us to pave the way to better understand the brain behavior in process of visual stimuli and has a great potential to be used in brain-computer interface applications.