Cognitive modeling using multivariate multiscale entropy analysis of EEG: entropy changes according to auditory inputs and the level of attention

Multivariate multiscale entropy (MMSE) is one measure to measure the amount of information in a random signal. The amount of information contained in electroencephalogram (EEG) signals that vary depending on auditory input and state was measured using MMSE in this study. As a result, the MMSE value rises not only when rehearsal of a given sentence is performed, but also when a non-semantic sentence is given, and appropriate noise is mixed in with the input sentence. As a result of these findings, this study proposes a method for quantitatively analyzing various cognitive models.