Independent component approach to the analysis of EEG recordings at early stages of depressive disorders.

OBJECTIVE: A modern approach for blind source separation of electrical activity represented by Independent Components Analysis (ICA) was used for QEEG analysis in depression.

METHODS: The spectral characteristics of the resting EEG in 111 adults in the early stages of depression and 526 non-depressed subjects were compared between groups of patients and healthy controls using a combination of ICA and sLORETA methods.

RESULTS: Comparison of the power of independent components in depressed patients and healthy controls have revealed significant differences between groups for three frequency bands: theta (4-7.5Hz), alpha (7.5-14Hz), and beta (14-20Hz) both in Eyes closed and Eyes open conditions. An increase in slow (theta and alpha) activity in depressed patients at parietal and occipital sites may reflect a decreased cortical activation in these brain regions, and a diffuse enhancement of beta power may correlate with anxiety symptoms playing an important role on the onset of depressive disorder.

CONCLUSIONS: ICA approach used in the present study allowed us to localize the EEG spectra differences between the two groups.

SIGNIFICANCE: A relatively rare approach which uses the ICA spectra for comparison of the quantitative parameters of EEG in different groups of patients/subjects allows to improve an accuracy of measurement.