A resective neurosurgical intervention can allow a successful treatment of therapy refractory patients. For the exact localization of the epileptic focus, EEG data are presurgically recorded and visually analyzed by neurologists. The analysis of these data is extremely difficult and time-intensive. The planned research project proposes an automated focus detection and seizure propagation analysis for epileptic seizures for the aforementioned presurgical monitoring by means of time series analysis methodology. Based on invasive and scalp EEG data, spatial and temporal dependencies of brain areas shall be determined and analyzed during epileptic seizures. We want to aid physicians in the difficult interpretation of these EEG signals. The planned research project comprises the following parts: 1. In a first step the temporal structure of the EEG recordings, which are highly instationary bio signals, shall be studied. Hereby, dynamic segmentation and methods for the detection of local stationarity are employed. 2. Based on these results, algorithms for reduction of the used input channels shall be developed. Methods like the An algorithm, which perform a dynamic channel selection, could be appropriate. Furthermore, by means of dynamic factor models we intend to model the fact that electrical signals originating from one source are recorded by several electrodes. 3. By means of graphical modeling and appropriate dependency measures coupling effects between the different electrodes shall be analyzed. The evolution of the obtained dependencies shall give a hint for the localization of the focus and the propagation of the seizure. Neurophysical informations shall be involved in the modeling. 4. We want to investigate the circumstances where scalp EEG data is sufficient for our analysis, and when invasive EEG data really yields relevant new information. Furthermore we want to compare the results of the EEG analysis with other investigation methods.