A detailed description of an effective connectivity measure applied to the analysis of epileptogenic networks is presented. Signals from an intracraneal electroencephalography (iEEG) are analyzed. These signals come from 9 deep electrodes. Two spontaneous seizures from one patient of the Ramos Mejia Hospital (RMH) were analysed. A statistical approach based in two thresholding steps allows the comparison of the connectivity between seizures and the non ictal periods. As an example, the method is used for the analysis of one seizure. To meassure the epileptogenic networks connectivity makes the epileptogenic zone (EZ) identification easier, which is of vital importance in a possible resective surgery. Therefore this could imply a better quality of life of post-surgical patients.