Das Problem bei der Diagnose ADHS ist vorwiegend durch das Fehlen von Objektivität definiert. Das Beiziehen von Biomarkern und das Verstehen derselben unter dem Aspekt von Handeln, Denken und Fühlen und auf dem Hintergrund des Lebensfeldes und der Lebensgeschichte löst das Problem weitgehend. Elektrophysiologische Biomarker (Quantitative Analyse des EEGs und ereigniskorrelierte Potentiale) eignen sich ausgezeichnet für das Verstehen der neuronalen Dynamik, für die Diagnosestellung und zuer Festlegung der Intervention im Sinne der personalisierte Medizin. Untersuchungen bekegen eine Hohe Validität der ereigniskorrelierten Potenziale}

The purpose of the present study was to determine if the theta/beta ratio, and theta and beta separately, correlate with behavioral parameters, and if these measures discriminate between children and adolescents with ADHD and normal gender- and age-matched controls. Sixty-two patients and 39 controls participated in the study. A continuous performance test (CPT), a GO/NOGO test and two rating scales were used to measure behavior in the patient group. EEG spectra were analyzed in eyes-closed and eyes-opened conditions, and in a GO/NOGO task in both groups. Neither the theta/beta ratio at CZ, nor theta and beta separately discriminated significantly between patients and controls. When each person was compared with the database significant elevations of theta were found in 25.8% of the patients and in only one control subject (2.6%). In the ADHD group, theta at CZ was positively correlated with inattention and executive problems and negatively correlated with hyperactivity/impulsivity. Beta correlated with good attention level in the control group, but with ADHD symptoms in the patients. Omission errors in the GO/NOGO test discriminated between patients and controls with an accuracy of 85%. For theta at CZ, the accuracy was 62%. Significantly elevated theta characterized a subgroup of ADHD and correlated with inattention and executive problems.

Background: There are numerous event-related potential (ERP) studies in relation to attention-deficit hyperactivity disorder (ADHD), and a substantial number of ERP correlates of the disorder have been identified. However, most of the studies are limited to group differences in children. Independent component analysis (ICA) separates a set of mixed event-related potentials into a corresponding set of statistically independent source signals, which are likely to represent different functional processes. Using a support vector machine (SVM), a classification method originating from machine learning, this study aimed at investigating the use of such independent ERP components in differentiating adult ADHD patients from non-clinical controls by selecting a most informative feature set. A second aim was to validate the predictive power of the SVM classifier by means of an independent ADHD sample recruited at a different laboratory. Methods: Two groups of age-matched adults (75 ADHD, 75 controls) performed a visual two stimulus go/no-go task. ERP responses were decomposed into independent components, and a selected set of independent ERP component features was used for SVM classification. Results: Using a 10-fold cross-validation approach, classification accuracy was 91%. Predictive power of the SVM classifier was verified on the basis of the independent ADHD sample (17 ADHD patients), resulting in a classification accuracy of 94%. The latency and amplitude measures which in combination differentiated best between ADHD patients and non-clinical subjects primarily originated from independent components associated with inhibitory and other executive operations. Conclusions: This study shows that ERPs can substantially contribute to the diagnosis of ADHD when combined with up-to-date methods.

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 anterior N2 and P3 waves of event related potentials (ERPs) in the GO/NOGO paradigm in trials related to preparatory set violations in previous studies were inconsistently associated either with action inhibition or conflict monitoring operations. In the present study a paired stimulus GO/NOGO design was used in order to experimentally control the preparatory sets. Three variants of the same stimulus task manipulated sensory mismatch, action inhibition and conflict monitoring operations by varying stimulus-response associations. The anterior N2 and P3 waves were decomposed into components by means of independent component analysis (ICA). The ICA was performed on collection of 114 individual ERPs in the three experimental conditions. Three of the independent components were selectively affected by the task manipulations indicating association of these components with sensory mismatch, action inhibition and conflict monitoring operations. According to sLORETA the sensory mismatch component was generated in the left and right temporal areas, the action suppression component was generated in the supplementary motor cortex, and the conflict monitoring component was generated in the anterior cingulate cortex.

Background: In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects. Methods: Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine. Results: The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%. Conclusions: This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.

Introduction: Chinese acupuncture therapy has been practiced for more than 3000 years. According to neuroimaging studies, electroacupuncture has been demonstrated to be effective via control of the frequency parameter of stimulation, based on the theory of frequency modulation of brain function. Aims: To investigate the following: (1) possible sustained effects of acustimulation in improving perceptual sensitivity in attention by comparing before, during, and 5 min following stimulation; (2) relations between commission errors and the motor inhibition event-related potential (ERP) component measured with independent component analysis (ICA); (3) whether habituation would be demonstrated in the sham control group and would be militated by acustimulation in the experimental groups. Results: Twenty-seven subjects were divided into three groups (n = 9). d-Prime (d) derived from signal detection theory was used as an index of perceptual sensitivity in the visual continuous performance attention test. Increased d was found during both alternating frequency (AE) and low frequency (LE) stimulation, but with no change in the sham control group (SE). However, only following AE was there a sustained poststimulation effect. Spatial filtration-based independent components (ICs) in the AE group revealed significantly decreased amplitudes of the motor inhibition ICs both during and poststimulation. There was a significant habituation effect from task repetition in the sham group with decreased amplitudes of ICs as follows: the visual comparison component difference between go (correct response) and nogo cues (correct withheld response), the P400 action monitoring and the working memory component in the nogo condition, and the passive auditory component on control trials. Conclusion: The results showed associations between acustimulation and improved perceptual sensitivity with sustained improvements following AE, but not LE stimulation. Improvements in commission errors in the AE group were related to the motor inhibition IC. The activational effects of acustimulation apparently attenuated the acrosstask habituation that characterized the control group.