Recently, many researches of the extraction of personal comfort and preference have been studied. Personal comfort and preference depend on a person, therefore the index is needed for the measurement. Then, we aim to understand personal comfort and preference by using the EEG as an index. The purpose of this study is to make the EEG map that makes visual the relationship between the EEG and external stimuli. We think that analyzing the distribution in the EEG map leads to the extraction of personal preference. First of all, we measure EEG patterns in 3 conditions; neutral which is the state relaxing without external stimuli, listening to favorite music, and smelling favorite fragrance. Then, we make the data matrix from the obtain data. Then, we extract features from the matrix by using neural networks. Finally, we make the EEG map to clarify the location of each EEG feature. In order to show the effectiveness of the proposed method, we demonstrate the simulation examples.