A Population Search Algorithm for Clustered Multivariate Solutions: Application to EEG Connectivity

There is a need to efficiently identify time, frequency and spatial locations between which connectivity occurs within the brain. Therefore, a novel, population based, search algorithm is proposed based upon the behaviour of foraging animals. The method is evaluated on a simple grid search problem and on the identification of time-frequency locations of statistically significant phase synchronisation in both synthetic and real EEG. The method is shown to be comparable to a state-of-the-art phase synchronisation identification algorithm in terms of speed while identifying a large proportion of available solutions.