Dimensional complexity analysis of human EEG in visual processing

To assess nonlinear human electroencephalogram (EEG) activities in the visual processing, we estimate the dimensional complexity (DCx) of the human EEGs. A similarity index is built to precisely detect dynamic changes in the EEG patterns. Significantly lower DCx values are observed at most channels when subjects are performing visual recognition and categorization tasks. This decrease in DCx values may be produced by the neural synchronization of cortical field activities caused by the visual processing. Our results may be helpful to understand the nonlinear human EEG activities in the visual processing.