Measures of brain connectivity through permutation entropy in epileptic disorders

Most of the scientist assume that epileptic seizures are triggered by an abnormal electrical activity of groups of neural populations that yields to dynamic changes in the properties of Electroencephalography (EEG) signals. To understand the pathogenesis of the epileptic seizures, it is useful detect them by using a tool able to identify the dynamic changes in EEG recordings. In the last years, many measures in the complex network theory have been developed. The aim of this paper is the use of Permutation Entropy (PE) with the addition of a threshold method to create links between the different electrodes placed over the scalp, in order to simulate the network phenomena that occur in the brain. This technique was tested over two EEG recordings: a healthy subject and an epileptic subject affected by absence seizures.