M.: Detection of transient synchronization in multivariate brain signals, application to event-related potentials. Chaos and Complexity Letters 3(1), 1–24 (2007) of phase synchronization 15

The present work introduces an analysis framework for the detec-tion of transient synchronized states in multivariate time series. In case of linear data these states exhibit a dramatic increase and subsequent decrease of time scale in the signal, whereas the corresponding instanta-neous phases show transient mutual phase synchronization. We propose a single segmentation algorithm for both data types, which considers the space-time structure of the data. Applications to linear and phasic simulated signals illustrate the method. Further applications to event-related brain potentials obtained from an auditory oddball experiment while real car-driving reveal the lack of the cognitive component P300 in an experimental condition. Further the obtained results indicate at-tention effects in the event-related component N100 and shows dramatic latency jitters between single datasets. A comparison of the proposed method to a conventional index of mutual phase synchronization demon-strates the superiority of considering space-time data structures. 2