Sarshar Dorosti - Tehran University of Art, Tehran, Iran
Seyed Hasan Soltani - Tehran University of Art, Tehran, Iran
Reza Khosrowabadi - Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran

Background and Aim : Many studies have investigated brain mechanism involved in process of various features of visual stimuli such as color, light, contrast and so on. Among them, fractal animation as a genre of computer and digital art implies the mathematically beauty of self-similarities and fractals to create a new media art in texture and landscape generation, and plant growth simulation. Nevertheless, it is still questionable that how the brain process and conceive the fractal animations. In this study, we hypothesized that fractals must convey their self-similarity effect on the brain signals as well.Methods : we produced some 2D and 3D fractal animations and 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) were recruited and their brain activities were recorded with a 32-channels while they were exposed to the 2D/3D fractal animations. 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 channels (Pz- Cpz- Cp3) showed correlation with FDs of 2D animations. In addition, frequency-band specific analysis also showed significant correlation at the (P3-Pz-Cp3-Cpz-C3) in alpha band, and (Cz-Cpz-Pz-Cp4) in beta band. The results indicated that EEG signals at the parietal regions have more complex pattern while 2D animations with higher FDs were presented.Conclusion : Despite the difference in the similarity of different bands, results indicate significant similarity between the self-similarities in the 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 and has a great potential to be used in brain-computer interface applications.

fractal animations; fractal dimensions; box-counting; Katz, Electroencephalography (EEG)