Complexity-based decoding of brain-skin relation in response to olfactory stimuli. (February 2020)

• Record Type: Journal Article
• Authors: Omam, Shafiul; Babini, Mohammad Hossein; Sim, Sue; Tee, Rui; Nathan, Visvamba; Namazi, Hamidreza
• Is Part Of: Computer methods and programs in biomedicine. Volume 184(2020)
• Publication Date: 2020-02
• Subjects: Skin -- Brain -- Galvanic skin response (GSR) -- Electroencephalography (EEG) signals -- Fractal theory -- Complexity; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2019.105293
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Brain controls the reaction of skin through the nervous system and therefore there should be relation between their activities. We have used complexity analysis to make a relation between skin reaction (GSR signal), bran reaction (EEG signal) and olfactory stimuli. The results of analysis showed that the greater variation in the complexity of odors (as olfactory stimuli) causes greater variation in the complexity of EEG and GSR signal, and therefore we conclude that activity of skin is linked to the activity of the brain. Abstract: Background and Objective: Human body is covered with skin in different parts. In fact, skin reacts to different changes around human. For instance, when the surrounding temperature changes, human skin will react differently. It is known that the activity of skin is regulated by human brain. In this research, for the first time we investigate the relation between the activities of human skin and brain by mathematical analysis of Galvanic Skin Response (GSR) and Electroencephalography (EEG) signals. Method: For this purpose, we employ fractal theory and analyze the variations of fractal dimension of GSR and EEG signals when subjects are exposed to different olfactory stimuli in the form of pleasant odors. Results: Based on the obtained results, the complexity of GSR signal changes with the complexity of EEG signal in case of different stimuli, where by increasing the molecular complexity of olfactory stimuli, the complexity of EEG and GSR signals increases. The results of statistical analysis showed the significant effect of stimulation on variations of complexity of GSR signal. In addition, based on effect size analysis, fourth odor with greatest molecular complexity had the greatest effect on variations of complexity of EEG and GSR signals. Conclusion: Therefore, it can be said that human skin reaction changes with the variations in the activity of human brain. The result of analysis in this research can be further used to make a model between the activities of human skin and brain that will enable us to predict skin reaction to different stimuli.