Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

OBJECTIVE: To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. METHODS: Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. RESULTS: Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. CONCLUSIONS: Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. SIGNIFICANCE: Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults.

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.

EEG power spectra at early stages of depressive disorders.

In previous quantitative EEG studies of depression, mostly patients with a lifetime history of depressive disorders were reported. This study examined quantitative EEG parameters obtained in the early stages of depression in comparison with age-matched healthy controls. EEG was recorded using two different montages in eyes closed and eyes open resting states. A significant increase in spectrum power in theta (4-7.5 Hz), alpha (7.5-14 Hz), and beta (14-20 Hz) frequency bands was found in depressed patients at parietal and occipital sites, both in eyes closed and eyes open conditions. These results suggest that an increase in slow (theta and alpha) activity in the EEG pattern may reflect a decreased cortical activation in these brain regions. Enhancement of beta power may correlate with anxiety symptoms that most likely play an important role on the onset of depressive disorder.

ERPs correlates of EEG relative beta training in ADHD children.

Eighty-six children (ages 9-14) with attention deficit hyperactivity disorder (ADHD) participated in this study. Event-related potentials (ERPs) were recorded in auditory GO/NOGO task before and after 15-22 sessions of EEG biofeedback. Each session consisted of 20 min of enhancing the ratio of the EEG power in 15-18 Hz band to the EEG power in the rest of spectrum, and 7-10 min of enhancing of the ratio of the EEG power in 12-15 Hz to the EEG power in the rest of spectrum with C3-Fz electrodes' placements for the first protocol and C4-Pz for the second protocol. On the basis of quality of performance during training sessions, the patients were divided into two groups: good performers and bad performers. ERPs of good performers to GO and NOGO cues gained positive components evoked within 180-420 ms latency. At the same time, no statistically significant differences between pre- and post-training ERPs were observed for bad performers. The ERP differences between post- and pretreatment conditions for good performers were distributed over frontal-central areas and appear to reflect an activation of frontal cortical areas associated with beta training.