  Several methods have been developed to extract information from
electroencephalograms (EEG). One of them is Phase-Amplitude Coupling (PAC)
which is a type of Cross-Frequency Coupling (CFC) method, consisting in measure
the synchronization of phase and amplitude for the different EEG bands and
electrodes. This provides information regarding brain areas that are
synchronously activated, and eventually, a marker of functional connectivity
between these areas. In this work, intra and inter electrode PAC is computed
obtaining the relationship among different electrodes used in EEG. The
connectivity information is then treated as a graph in which the different
nodes are the electrodes and the edges PAC values between them. These
structures are embedded to create a feature vector that can be further used to
classify multichannel EEG samples. The proposed method has been applied to
classified EEG samples acquired using specific auditory stimuli in a task
designed for dyslexia disorder diagnosis in seven years old children EEG's. The
proposed method provides AUC values up to 0.73 and allows selecting the most
discriminant electrodes and EEG bands.
