Bülent YILMAZ, Fatih ALTINDİŞ, Cengiz GAZELOĞLU

Prediction of preference and effect of music on preference: a preliminary study on electroencephalography from young women

Neuromarketing is the application of the neuroscientific approaches to analyze and understand economicallyrelevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated.The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic,loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density(PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect of music was investigatedby comparing the mean differences between music and no music groups using independent two-sample t-test. In thepreference prediction part sequential forward selection, k-nearest neighbors (k-NN) and the support vector machines(SVM), and 5-fold cross-validation approaches were used. It is found that music did not affect like decision in any ofthe power bands, on the contrary, music affected dislike decisions for all bands with no exceptions. Furthermore, theaccuracies obtained in preference prediction study were between 77.5 and 82.5% for k-NN and SVM techniques. Theresults of the study showed the feasibility of using EEG signals in the investigation of the music effect on purchasingbehavior and the prediction of preference of an individual.

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