title: Like/dislike analysis using EEG: determination of most discriminative channels and frequencies.
abstract: In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer products, (ii) timing characteristic of "like" decisions during such mental processes. For this purpose, we have obtained multichannel EEG recordings from 15 subjects, during total of 16 epochs of 10 s long, while they were presented with some shoe photographs. When they liked a specific shoe, they pressed on a button and marked the time of this activity and the particular epoch was labeled as a LIKE case. No button press meant that the subject did not like the particular shoe that was displayed and corresponding epoch designated as a DISLIKE case. After preprocessing, power spectral density (PSD) of EEG data was estimated at different frequencies (4, 5, …, 40 Hz) using the Burg method, for each epoch corresponding to one shoe presentation. Each subject's data consisted of normalized PSD values (NPVs) from all LIKE and DISLIKE cases/epochs coming from all 19 EEG channels. In order to determine the most discriminative frequencies and channels, we have utilized logistic regression, where LIKE/DISLIKE status was used as a categorical (binary) response variable and corresponding NPVs were the continuously valued input variables or predictors. We observed that when all the NPVs (total of 37) are used as predictors, the regression problem was becoming ill-posed due to large number of predictors (compared to the number of samples) and high correlation among predictors. To circumvent this issue, we have divided the frequency band into low frequency (LF) 4-19 Hz and high frequency (HF) 20-40 Hz bands and analyzed the influence of the NPV in these bands separately. Then, using the p-values that indicate how significantly estimated predictor weights are different than zero, we have determined the NPVs and channels that are more influential in determining the outcome, i.e., like/dislike decision. In the LF band, 4 and 5 Hz were found to be the most discriminative frequencies (MDFs). In the HF band, none of the frequencies seemed offer significant information. When both male and female data was used, in the LF band, a frontal channel on the left (F7-A1) and a temporal channel on the right (T6-A2) were found to be the most discriminative channels (MDCs). In the HF band, MDCs were central (Cz-A1) and occipital on the left (O1-A1) channels. The results of like timings suggest that male and female behavior for this set of stimulant images were similar.
authors: Electrical and Electronics Engineering Department, Abdullah Gül University, Kayseri, Turkey. Electronic address: bulent.yilmaz@agu.edu.tr.
authors: Bülent
authors: B
authors: Yılmaz
authors: Biomedical Engineering Department, Erciyes University, Kayseri, Turkey.
authors: Sümeyye
authors: S
authors: Korkmaz
authors: Biomedical Engineering Department, Erciyes University, Kayseri, Turkey.
authors: Dilek Betül
authors: DB
authors: Arslan
authors: Biomedical Engineering Department, Erciyes University, Kayseri, Turkey.
authors: Evrim
authors: E
authors: Güngör
authors: Electrical and Electronics Engineering Department, Antalya International University, Antalya, Turkey.
authors: Musa H
authors: MH
authors: Asyalı
mesh_terms: D000328:Adult; D003657:Decision Making; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D055815:Young Adult
keywords: Burg method; EEG; Logistic; Neuromarketing; Partiality; Power spectral density; Regression