Functional connectivity from EEG signals during perceiving pleasant and unpleasant odors
The olfactory sense is strongly related to memory and emotional processes. Studies on the effects of odor perception from brain activity have been conducted by using different neuro-imaging techniques. In this paper, we analyse electroencephalography (EEG) of 23 subjects during perceiving pleasant and unpleasant odor stimuli. We describe the construction of brain functional connectivity networks measured by most commonly used models. We discuss the network-based features of functional connectivity, and design classifiers by applying different functional connectivity network features. Finally, we show that pleasant and unpleasant emotions from olfactory perceptions can be better classified if we see the brain as a nonlinear small-world network. By extracting appropriate features from functional connectivity networks, we manage to classify pleasant and unpleasant olfactory perceptions with an average Kappa value of 0.11 ± 0.17, which is significantly non-random.