[Analysis of independent components for event-related potentials from patients with an established diagnosis of schizophrenia, obsessive-compulsive and depressive disorders].

We investigated the possibility to classify data from patients with different psychiatric disorders on the base of physiological measures of the brain activity. Event-related potentials during the execution of GO/NOGO task were recorded from age matched groups of patients with schizophrenia, major depression and obsessive-compulsive disorder. Separation of independent components for event-related potentials was performed by applying Independent Component Analysis method. Picked out components were used in the method of discriminant analysis to classify the data according to clinical diagnosis. Discriminant analysis of components for event-related potentials allows classifying the data of patients with a suitable amount of matches with an established diagnosis.

[Brain structures and functional pecularities in children with mental disorders and transcranial direct current stimulation].

This research represents MRI and EEG-investigation in children with mental disorders perinatal genesis during tDCS. In 70% cases brain structures damages don't found or were minimal. On the contrary, in 77% cases α-rhythm of EEG in parietal-occipital areas was non-regular. Functional insufficiency can as a basis of high efficiency tDCS by children. In cases with autism spectrum disorders the Subscales of Woodcock-Jonson were used for the quantitative estimation of efficiency of the course of treatment with tDCS. Positive changes after the course of tDCS were revealed in psychic state, speech comprehension, communication, practical and speech experience, fine motor skills and social integration.

[Local EEG characteristics of the children with psychic abnormalities, examined by independent components analysis (ICA)].

The method of independent components within the range of 3-13 Hz was used for the analysis of EEG of the children with psychic abnormalities of perinatal origin. The research was undertaken while children were keeping awake with open eyes. In cases of harder developmental delay it was revealed a significant rise of θ-range power spectrum in frontal-temporal cortex areas of left hemisphere and temporal areas of right hemisphere. This fact make it possible to regard these areas as hypothetic sources of slow activity and a damage/immaturity marker of frontal-thalamic area and the temporal areas, responsible for auditory analysis and verbal synthesis, audio & visual data integration.

[Functional biomarkers in the diagnostics of mental disorders: cognitive event-related potentials].

The article is devoted to recent researches in the field of fundamental knowledge about the mechanisms of information processing in human brain for the diagnosis of mental disorders performed in the laboratory of neurobiology for action programming of the Bechtereva Institute of Human Brain, RAS. These researches were connected with analysis of functional components for cognitive ERPs obtained in diverse behavioral conditions. The main goal of this fundamental approach is the decomposition of multi-channel ERPs into functionally different components. These components are generated in various cortical areas have different temporal dynamics and reflect a variety of mental operations. The main methodology we used is the independent component analysis, applied to a large set of ERPs (from hundreds of people) obtained by varying of functional conditions in one psychological test. In particular, components related to psychological processes such as the comparison of sensory signals with the trace in working memory, inhibition of current activity, monitoring of the conflict were identified in the GO/NOGO test. In the framework of European project normative database was constructed for the components described above and this allowed comparing the data obtained from large groups of patients (including patients with attention deficit disorder, schizophrenia, obsessive disorders, depression, autism, dyslexia, brain trauma and dementia) with the healthy subjects. This article presents data from patients with a diagnosis of attention deficit disorder and schizophrenia.

[Power spectra of the main EEG rhythms in children with different types of attention deficit hyperactivity disorder].

We investigated a group of children aged 9-12 years with attention deficit hyperactivity disorder (ADHD) combined type, have divided into two variants of the clinical picture of ADHD: residual-organic variant (ADH D RO) and idiopathic variant (ADHD RI). We studied the power spectral analysis in the main frequency bands in background EEG eyes closed and are open. The significant differences between both groups observed in the theta frequency band in the fronto-central and occipital leads. In the fronto-central leads of the cortex were the maximum values in the group of children ADHD RO, whereas in children with ADHD IR, the largest values of power spectra were in the occipital leads. Statistically significant differences in spectral power in the alpha range between healthy subjects and groups children with ADHD had not been received. Thus, our studies have shown that these two variants of ADHD have some neurophysiological differences that must be considered when choosing a treatment.

[Improving source localization of ERPs in the GO/NOGO task by modeling of their cross-covariance structure].

We studied 19-channel event-related potentials (ERPs) during the GO/NOGO task in 517 healthy subjects. Decomposition of multi-channel ERP into independent components was performed with a method based on modeling the cross-covariance structure of the transient response. The results show that this method allows us to obtain low-correlated components with acceptable reliability. The identified components have been associated with psychological processes such as the attended sensory mismatch operation, the decision-making on the subsequent action, the action inhibition operation, the conflict monitoring operation and others. In conclusion, the separation of the ERP recording into independent components and the use of the sLORETA helps localizing sources of ERPs more accurately than the conventional analysis of the ERP.

[Possibility of using biofeedback for amplitude training of ERP's independent components].

The aim of this study was to investigate the possibility of voluntary training for independent component of event-related potentials in modified two-stimuli Go/NoGo test by the method of biofeedback. Subjects were 10 healthy people which were asked to increase amplitude of P3b component of event-related potentials from Go stimulus. This component is generated in parietal area and is thought to be connected with action engagement. The study consisted of three sessions including tuning (determining of mean amplitude), training and placebo. Amplitude of P3b component did not change significantly during training and placebo sessions comparing to tuning session while amplitude of SPD component significantly decreased in both sessions. This component is separated in event-related potentials from Go stimulus and its source according to "sLORETA" is localized in parahippocampus. Obtained results allow determining further approaches to research the possibility of using biofeedback for correction of ERPs' components.

[Analysis of EEG characteristic at early stages of depression using method of independent components].

Independent Component Analysis (ICA) was used for 19-channel resting EEG analysis 111 patients at early stages of depressive disorder and 526 age-matched healthy subjects. Comparison of independent components power spectra in depressed patients and healthy subjects in two states: Eyes closed and Eyes open, has revealed significant differences between groups for three frequency bands: Theta (4-7.5 Hz), Alpha (7.5-14 Hz), and Beta (14-20 Hz). Increased power of alpha and theta activity in depressed patients at parietal and occipital sites may be caused by decreased cortical activation of these regions. Diffuse enhancement of beta activity level can correlate with anxiety symptoms which take an important place in clinical picture of depressive disorder at early stages. Using of ICA method for comparison of spectral characteristics of EEG in groups of patients with different brain pathology and healthy subjects gives a possibility to localize more precisely the discovered differences as compare to traditional analysis of EEG spectra.

[The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury].

The comparison of three different clustering methods of 19-channels EEG independent components in 518 healthy subjects and 87 patients with post concussion syndrome after traumatic brain injury was performed to define more exact the location of sources of pathologic brain activity. Following methods of grouping were used: clustering of independent components topographies, clustering of coordinates of equivalent dipole sources corresponding to independent components topographies and sorting of independent components using extremes of equivalent source current density computed by Standardized Low Resolution Electromagnetic Tomography (sLORETA).The comparison of power spectra of independent components revealed statically significant increase of EEG power located in frontal and temporal brain areas in delta, theta and alpha frequency bands in patients with post concussion syndrome after traumatic brain injury. The method of clustering of independent components topographies seems to be most sensitive in comparison with other two methods.

[Normative EEG spectral characteristics in healthy subjects from 7 to 89 years].

EEGs were recorded at 885 healthy subjects of both sexes with age from 7 to 89 years in "eyes closed" and "eyes opened" conditions. Both average EEG power spectra and EEG independent component power spectra were computed for 20 age groups of subjects separately, and corresponding confidence intervals of average power were estimated for four frequency bands: delta, theta, alpha and beta. These quantitative data can be useful as objective criteria for diagnostics of brain dysfunctions.