Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

• We present a new method to evaluate synchronization between time series.
• Using time-varying graphs with synchronization methods, we evaluate EEG networks.
• Brain functional networks was able to differentiate affective processing in subjects.

The major aim of this work was to propose a new association method known as Motif-Synchronization. This method was developed to provide information about the synchronization degree and direction between two nodes of a network by counting the number of occurrences of some patterns between any two time series. The second objective of this work was to present a new methodology for the analysis of dynamic brain networks, by combining the Time-Varying Graph (TVG) method with a directional association method. We further applied the new algorithms to a set of human electroencephalogram (EEG) signals to perform a dynamic analysis of the brain functional networks (BFN).