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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 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 visual stimuli. For this purpose, we chose two types of visual stimuli, namely, living and non-living visual stimuli. We demonstrate that the fractal structure of human EEG signal changes significantly between living versus non-living visual stimuli. 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.

Analysis of eye movement due to different visual stimuli always has been one of the major research areas in vision science. An important category of works belongs to decoding of eye movement due to variations of color of visual stimuli. In this research, for the first time, we employ fractal analysis in order to investigate the variations of complex structure of eye movement time series in response to variations of color of visual stimuli. For this purpose, we applied two different images in three different colors (red, green, blue) to subjects. The result of our analysis showed that eye movement has the greatest complexity in case of green visual stimulus. On the other hand, the lowest complexity of eye movement was observed in case of red stimulus. In addition, the results showed that except for red visual stimulus, applying the visual stimulus with greater complexity causes the lower complexity in eye movements. The employed methodology in this research can be further applied to analyze the influence of other variations of visual stimuli on human eye movement.

An important category of studies in vision science is related to the analysis of the influence of environmental changes on human eye movement. In this way, scientists analyze human eye movement in different conditions using different methods. An important category of works is devoted to the decoding of eye reaction to color tonality. In this research for the first time, we examined the application of fractal theory for decoding of eye reaction to variations in color intensity of visual stimuli. Three green visual stimuli with different color intensities have been applied to subjects and accordingly the fractal dimension of their eye movements has been analyzed. We also tested the eye movement in non-stimulation condition (rest). Based on the obtained results, increasing the color intensity of visual stimuli caused a lower complexity in subject’s eye movement. We also observed that eye movement is less complex in case of non-stimulation compared to different stimulation conditions. The application of fractal theory in analysis of eye movement can be extended to analyze the effect of other stimulation conditions on eye movement to investigate about the decoding behavior of human eye, which is very important in vision science.

This paper analyzed the coupling among the reactions of eyes and brain in response to visual stimuli. Since eye movements and electroencephalography (EEG) signals as the features of eye and brain activities have complex patterns, we utilized fractal theory and sample entropy to decode the correlation between them. In the experiment, subjects looked at a dot that moved on different random paths (dynamic visual stimuli) on the screen of a computer in front of them while we recorded their EEG signals and eye movements simultaneously. The results indicated that the changes in the complexity of eye movements and EEG signals are coupled ($r=-0.8043$ in case of fractal dimension and $r=-0.9259$ in case of sample entropy), which reflects the coupling between the brain and eye activities. This analysis could be extended to evaluate the correlation between the activities of other organs versus the brain.

Analysis of the brain activity to external stimulation is an important area of research in biomedical engineering. In this paper, for the first time, we analyzed the brain reaction to visual stimuli with different frequencies using three complexity methods. For this purpose, we utilized fractal theory, sample entropy, and approximate entropy to study the variations of the complexity EEG signals while subjects received visual stimuli at 7, 9, 11, and 13 Hz. The results showed that, in general, by moving from 9 Hz to 13 Hz stimuli, the complexity of EEG signals increases, except in the case of 11 Hz stimulus. The statistical analysis also supported the results of the analysis. The conducted analysis in this research can be performed in the case of other types of external stimuli to study how the brain reacts in different conditions.

Analysis of the influence of external stimuli on human eye movements is an important challenge in vision research. In this paper, we investigate the influence of applied visual stimuli on variations of eye movements. For this purpose, we employ information theory, which provides us with tools such as Shannon entropy as the indicator of information content of process. This study for the first time reveals the relation between the information content of eye movements and the information content of visual stimuli. Based on the performed analysis, the information content of eye movements time series shifts toward the information content of applied visual stimuli, where the greater variation in Shannon entropy of visual stimuli causes the greater variation in the Shannon entropy of eye movements time series. The observed behavior is explained through nervous system. As a rehabilitation purpose, the employed methodology in this research can be investigated in case of patients with vision problems, with the aim of improving patients’ vision.

Human eye movement is a key concept in the field of vision science. It has already been established that human eye movement responds to external stimuli. Hence, investigating the reaction of the human eye movement to various types of external stimuli is important in this field. There have been many researches on human eye movement that were previously done, but this is the first study to show a relation between the complex structure of human eye movement and the complex structure of static visual stimulus. Fractal theory was implemented and we showed that the fractal dynamics of the human eye movement is related to the fractal structure of visual target as stimulus. The outcome of this research provides new platforms to scientists to further investigate on the relation between eye movement and other applied stimuli.

Analysis of the correlation among the activities of the eyes and brain is an important research area in physiological science. In this paper, we analyzed the correlation between the reactions of eyes and the brain during rest and while watching different visual stimuli. Since every external stimulus transfers information to the human brain, and on the other hand, eye movements and EEG signals contain information, we utilized Shannon entropy to evaluate the coupling between them. In the experiment, 10 subjects looked at 4 images with different information contents while we recorded their EEG signals and eye movements simultaneously. According to the results, the information contents of eye fluctuations, EEG signals, and visual stimuli are coupled, which reflect the coupling between the brain and eye activities. Similar analyses could be performed to evaluate the correlation among the activities of other organs versus the brain.

In this paper, we study the potential involvement of monkey amygdala in the evaluation of value encoding of visual and auditive stimuli associated with reward or no reward. We recorded the activity of 93 extracellular neurons from the monkey right amygdala, while performing a multisensory operant task. The activity of 78 task-related neurons was studied. Of these, 13 neurons (16%) responded to the value of visual stimuli, 22 neurons (28%) responded after the presentation of visual stimuli, 22 neurons (28%) showed an inhibition around the lever-pressing and were classified as action related neurons and 22 neurons (28%) responded after reward delivery. These findings suggest that neurons in the amygdala play a role in encoding value and processing visual information, participate in motor regulation and are sensitive to reward. The activity of these neurons did not change in the evaluation of auditive stimuli. These data support the hypothesis that amygdala neurons are specific to each sensory modality and that different groups of amygdala neurons process visual and auditive information.