Quasistationarity is ubiquitous in complex dynamical systems. In brain dy-namics there is ample evidence that event-related potentials reflect such qua-sistationary states. In order to detect them from time series, several segmen-tation techniques have been proposed. In this study we elaborate a recentapproach for detecting quasistationary states as recurrence domains by meansof recurrence analysis and subsequent symbolisation methods. As a result,recurrence domains are obtained as partition cells that can be further alignedand unified for different realisations. We address two pertinent problems ofcontemporary recurrence analysis and present possible solutions for them.