EEG-Based Classification of Olfactory Response to Pleasant Stimuli

Olfactory perception involves complex processing distributed along several cortical and sub-cortical regions in the brain. Although several studies have shown that the power spectra of the electroencephalography (EEG) contain information that can be used to differentiate between pleasant and unpleasant stimuli, there are still no studies which investigate whether EEG can be used to differentiate between the neural responses to olfactory stimuli of different levels of pleasantness. For this purpose, in the present study, local brain information within established frequency bands (θ, α and γ) has been used to devise discriminative features in a classification approach. A comparative study of four widely used classifiers is presented and SVM gives the best performance (accuracy = 75.71%). The results reveal that is it possible to objectively discriminate using EEG spectral features between fine levels of perceived pleasantness using the SVM-based classifier within a cross-validation procedure.