DECREASE OF COMPLEXITY IN EEG AS A SYMPTOM OF DEPRESSION

NONLINEAR dynamic analysis provides new methods for the processing of the electroencephalogram (EEG). We demonstrate here that the EEG dynam ics of major depressive subjects is more predictable, that is less com plex, than that of control subjects. Moreover, the consequence of trea tment upon the EEG dynamics seems to be dependent on the appearance of the illness. Although the specificity of this dynamic signature for d ifferent stages of depression is to be confirmed, the assumption of a strong link between a healthy system and a high level of complexity in dynamics is further supported.