Discriminating imagined and non-imagined tasks in the motor cortex area: entropy-complexity plane with a wavelet decomposition

Abstract

Electroencephalograms reflect the electrical activity of the brain, which can be considered ruled by a chaotic nonlinear dynamics. We consider human electroencephalogram recordings during different motor type activities, and when imagining that they perform this activity. We characterize the different dynamics of the cortex according to distinct motor and imagined movement tasks using an information theory approach and a wavelet decomposition. More specifically, we use the entropy-complexity plane H × C in combination with the wavelet decomposition to precisely quantify the dynamics of the neuronal activity showing that the current theoretical framework allows us to distinguish realized and imagined tasks within the cortex.