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Analyzing the influence of external stimuli on human eye movements is an important challenge in vision research. In this paper, we investigate the plasticity of eye movements due to the applied auditory stimuli (music). For this purpose, we use fractal theory, which provides us with tools such as fractal dimension as an indicator of process complexity. This study, for the first time, reveals the correlation between fractal dynamics of eye movements and fractal dynamics of auditory stimuli. Based on the performed analysis, the fractal structure of the eye movements shifts toward the fractal structure of the applied auditory stimuli, where the greater variation in fractal dynamics of auditory stimuli causes greater variation in the fractal dynamics of eye movements. The observed behavior is explained through the nervous system. As a rehabilitation purpose, the employed methodology in this research can be investigated in case of patients with vision problems, where the applied music could potentially improve their vision.

Analysis of human behavior is one of the major research topics in neuroscience. It is known that human behavior is related to his brain activity. In this way, the analysis of human brain activity is the root for analysis of his behavior. Electroencephalography (EEG) as one of the most famous methods for measuring of the brain activity generates a chaotic signal, which has fractal characteristic. This study reveals the relation between the fractal structure (complexity) of human EEG signal and the applied auditory stimuli. For this purpose, we chose a range of auditory stimuli with different rhythmic patterns. We demonstrated that the fractal structure of human EEG signal changes significantly based on different rhythmic patterns. The capability observed in this research can be applied to other kinds of stimuli in order to classify the brain response based on the types of stimuli.

Our facial muscles react due to exposure to various stimuli. For example, when we sniff an odor, our facial muscles react. Since the brain controls the activities of muscles, therefore, a coupling should exist between their activities. This paper studies the coupling between the activations of the brain and facial muscles in auditory stimulation by the complexity-based analysis of Electroencephalogram (EEG) and Electromyogram (EMG) signals. Three pieces of music were chosen according to the differences in their complexities. We calculated the fractal dimension and sample entropy of EEG and EMG signals for 13 subjects in rest and response to different music. The results showed strong couplings among the alterations of the complexities of these signals and music, which indicate the correlation between brain and facial muscle activities. This complexity-based analysis could be further extended to the case of other physiological signals to decode the correlation between the responses of different organs and the brain.