People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant) for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

Subjects (N=6) were asked to push a key (button) and time an interval after they listening to a sequence of sound (two buzzers) at one interval from a side (left or right) of headphone speakers. The time between the onset of the last buzzer and that of the key tap was defined as an anticipation time. The coefficient of determination between the interval and the anticipation time was calculated to evaluate accuracy of the anticipation. As a result, there was no laterality in the anticipation accuracy. However, when auditory masking was added to either side of headphone speakers, only the left side masking significantly reduced the anticipation accuracy. Thus, auditory masking caused disturbances with laterality to interval memory. These results suggest that the auditory interval memory, i.e. a working memory for the time perception is lateralized.