This paper presents the results of the practical use of artificial neural networks in the field of EEG analysis. It describes the general methodology of application as well as a case study of a discrimination of depressive and psychotic patients using 16-channel long-term EEG data prepared by classical pre-processing (spectral decomposition). This study shows advantages and current limits concerning different levels of generalisation capabilities using a representative application example.