title: Cepstral Analysis of EEG During Visual Perception and Mental Imagery Reveals the Influence of Artistic Expertise.
abstract: In this article, multichannel electroencephalogram (EEG) signals of artists and nonartists were analyzed during the performances of visual perception and mental imagery of paintings using cepstrum coefficients. Each of the calculated cepstrum coefficients and their parameters such as energy, average, standard deviation and entropy were separately used for distinguishing the two groups. It was found that a distinguishing coefficient might exist among the cepstrum coefficients, which could separate the two groups despite electrode placement. It was also observed that the two groups were distinguishable during the three states using the cepstrum coefficient parameters. However, separating the two groups was dependent on channel selection in this regard. The cepstrum coefficient parameters were found significantly lower for artists as compared to nonartists during the visual perception and the mental imagery, indicating a decreased average energy of EEG for artists. In addition, a similar significant decreasing trend in the cepstrum coefficient parameters was observed from occipital to frontal brain regions during the performances of the two cognitive tasks for the two groups, suggesting that visual perception and its mental imagery overlap in neuronal resources. The two groups were also classified using a neural gas classifier and a support vector machine classifier. The obtained average classification accuracies during the visual perception, the mental imagery, and at rest in the case of using the best selected distinguishable cepstrum coefficients were 76.87%, 77.5%, and 97.5%, respectively; however, a decrease in average recognition accuracy was found for classifying the two groups using the cepstrum coefficient parameters.
authors.affiliation: Faculty of Technology and Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
authors.forename: Nasrin
authors.initials: N
authors.lastname: Shourie
keywords: Brain; cognition; electrodes; electroencephalography; entropy; paintings; support vector machine; visual perception