Generation of Oscillatory Synthetic Signal Simulating Brain Network Dynamics

In this paper, generation of oscillatory synthetic signal simulating brain network dynamics is proposed. The methods follows the expectations of brain network connectivity, which include expressed phase angle differences and signal mixture. We have generated thirty-two signals simulating two groups of sixteen electrodes. Each signal is a mixture of two signal components. The first signal component is synchronized within a group of electrodes but delayed to obtain different phase angles, while the second signal component is unique to each electrode. This simulation give us possibility to present that all brain regions or sources are not connected with each other and that the phase difference between connected oscillators (sources or channels) is not necessary close to zero and could be arbitrary. Phase locking value (PLV) and phase lag index (PLI) measures of connectivity have been calculated on the synthetic signals.