Narrow Results

Evaluation of the correlation of the activities of various organs is an important area of research in physiology. In this paper, we evaluated the correlation among the brain and facial muscles’ reactions to various auditory stimuli. We played three different music (relaxing, pop, and rock music) to 13 subjects and accordingly analyzed the changes in complexities of EEG and EMG signals by calculating their fractal exponent and sample entropy. Based on the results, EEG and EMG signals experienced more significant changes by presenting relaxing, pop, and rock music, respectively. A strong correlation was observed among the alterations of the complexities of EMG and EEG signals, which indicates the coupling of the activities of facial muscles and brain. This method could be further applied to investigate the coupling of the activities of the brain and other organs of the human body.

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.

In this research, for the first time, we analyze the relationship between facial muscles and brain activities when human receives different dynamic visual stimuli. We present different moving visual stimuli to the subjects and accordingly analyze the complex structure of electromyography (EMG) signal versus the complex structure of electroencephalography (EEG) signal using fractal theory. Based on the obtained results from analysis, presenting the stimulus with greater complexity causes greater change in the complexity of EMG and EEG signals. Statistical analysis also supported the results of analysis and showed that visual stimulus with greater complexity has greater effect on the complexity of EEG and EMG signals. Therefore, we showed the relationship between facial muscles and brain activities in this paper. The method of analysis in this research can be further employed to investigate the relationship between other human organs’ activities and brain activity.