The P300 wave is decomposed into components reflecting response selection and automatic reactivation of stimulus-response links.

The parietal P300 wave of event-related potentials (ERPs) has been associated with various psychological operations in numerous laboratory tasks. This study aims to decompose the P3 wave of ERPs into subcomponents and link them with behavioral parameters, such as the strength of stimulus-response (S-R) links and GO/NOGO responses. EEGs (31 channels), referenced to linked ears, were recorded from 172 healthy adults (107 women) who participated in two cued GO/NOGO tasks, where the strength of S-R links was manipulated through instructions. P300 waves were observed in active conditions in response to cues, GO/NOGO stimuli, and in passive conditions when no manual response was required. Utilizing a combination of current source density transformation and blind source separation methods, we decomposed the P300 wave into two distinct components, purportedly originating from different parts of the parietal lobules. The amplitude of the parietal midline component (with current sources around Pz) closely mirrored the strength of the S-R link across proactive, reactive, and passive conditions. The amplitude of the lateral parietal component (with current sources around P3 and P4) resembled the push-pull activity of the output nuclei of the basal ganglia in action selection-inhibition operations. These findings provide insights into the neural mechanisms underlying action selection processes and the reactivation of S-R links.

Event-related EEG synchronization and desynchronization in patients with obsessive-compulsive disorder.

Symptoms in patients with obsessive-compulsive disorder (OCD) are associated with impairment in cognitive control, attention, and action inhibition. We investigated OCD group differences relative to healthy subjects in terms of event-related alpha and beta range synchronization (ERS) and desynchronization (ERD) during a visually cued Go/NoGo task. Subjects were 62 OCD patients and 296 healthy controls (HC). The OCD group in comparison with HC, showed a changed value of alpha/beta oscillatory power over the central cortex, in particular, an increase in the alpha/beta ERD over the central-parietal cortex during the interstimulus interval (Cue condition) as well as changes in the postmovement beta synchronization topography and frequency. Over the frontal cortex, the OCD group showed an increase in magnitude of the beta ERS in NoGo condition. Within the parietal-occipital ERS/ERD modulations, the OCD group showed an increase in the alpha/beta ERD over the parietal cortex after the presentation of the visual stimuli as well as a decrease in the beta ERD over the occipital cortex after the presentation of the Cue and Go stimuli. The specific properties in the ERS/ERD patterns observed in the OCD group may reflect high involvement of the frontal and central cortex in action preparation and action inhibition processes and, possibly, in maintaining the motor program, which might be a result of the dysfunction of the cortico-striato-thalamo-cortical circuits involving prefrontal cortex. The data about enhanced involvement of the parietal cortex in the evaluation of the visual stimuli are in line with the assumption about overfocused attention in OCD.

Application of Machine Learning to Diagnostics of Schizophrenia Patients Based on Event-Related Potentials.

Schizophrenia is a major psychiatric disorder that significantly reduces the quality of life. Early treatment is extremely important in order to mitigate the long-term negative effects. In this paper, a machine learning based diagnostics of schizophrenia was designed. Classification models were applied to the event-related potentials (ERPs) of patients and healthy subjects performing the visual cued Go/NoGo task. The sample consisted of 200 adult individuals ranging in age from 18 to 50 years. In order to apply the machine learning models, various features were extracted from the ERPs. The process of feature extraction was parametrized through a special procedure and the parameters of this procedure were selected through a grid-search technique along with the model hyperparameters. Feature extraction was followed by sequential feature selection transformation in order to prevent overfitting and reduce the computational complexity. Various models were trained on the resulting feature set. The best model was support vector machines with a sensitivity and specificity of 91% and 90.8%, respectively.

Latent ERP components of cognitive dysfunctions in ADHD and schizophrenia.

OBJECTIVE: The main goal was to assess common and specific deficits of cognitive control in (Attention Deficit Hyperactivity Disorder) ADHD and schizophrenia (SZ) using event-related potentials (ERPs). METHOD: Behavioral and EEG data in cued GO/NOGO task were recorded in 132 healthy controls (HC) and age, gender and education matched 63 ADHD adults, and 68 SZ patients. RESULTS: N2d wave in NOGO-GO contrast of ERPs did not differ between the groups while the P3d wave discriminated SZ group from two other groups. Latent components of ERPs were extracted by blind source separation method based on second-order statistics Kropotov et al. (2017) and compared between the groups. A counterpart of N2d wave of a frontally distributed latent component was smaller in SZ indicating a specific frontal dysfunction of conflict detection in SZ. Two centrally distributed P3 sub-components were reduced in both groups indicating a non-specific dysfunction of action inhibition operations in ADHD and SZ. CONCLUSION: A pattern of specific and common dysfunctions in terms of latent ERP components shows a more complex picture of functional impairment in schizophrenia and ADHD in comparison to conventional N2/P3 ERP description. SIGNIFICANCE: The latent component approach shows a functionally different pattern of cognitive control impairment in comparison to the conventional ERP analysis.

Functional indexes of reactive cognitive control: ERPs in cued go/no-go tasks.

We aimed to determine the functional meaning of latent (hidden) components decomposed from ERPs, in the context of a go/no-go paradigm. To accomplish this, we used a new group blind source separation method, based on joint diagonalization of covariance matrices of ERPs. Four variants of a frequently used go/no-go paradigm were designed, in which operations of reactive cognitive control, such as conflict detection and action inhibition, were independently manipulated. The results showed that a latent component, generated in the anterior cingulate cortex, induced N2/P3 fluctuation only in conditions in which the prepotent model was violated, and thus can be associated with conflict detection operations. In contrast, the two latent components generated in the vicinity of the central sulcus induced P3-like fluctuations in conditions in which the prepared action was suppressed, and thus can be associated with action inhibition operations. The advantages and limitations of the new blind source separation method in relation to ERP research are also discussed.

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.

Identification of infectious agents in onychomycoses by PCR-terminal restriction fragment length polymorphism.

A fast and reliable assay for the identification of dermatophyte fungi and nondermatophyte fungi (NDF) in onychomycosis is essential, since NDF are especially difficult to cure using standard treatment. Diagnosis is usually based on both direct microscopic examination of nail scrapings and macroscopic and microscopic identification of the infectious fungus in culture assays. In the last decade, PCR assays have been developed for the direct detection of fungi in nail samples. In this study, we describe a PCR-terminal restriction fragment length polymorphism (TRFLP) assay to directly and routinely identify the infecting fungi in nails. Fungal DNA was easily extracted using a commercial kit after dissolving nail fragments in an Na(2)S solution. Trichophyton spp., as well as 12 NDF, could be unambiguously identified by the specific restriction fragment size of 5'-end-labeled amplified 28S DNA. This assay enables the distinction of different fungal infectious agents and their identification in mixed infections. Infectious agents could be identified in 74% (162/219) of cases in which the culture results were negative. The PCR-TRFLP assay described here is simple and reliable. Furthermore, it has the possibility to be automated and thus routinely applied to the rapid diagnosis of a large number of clinical specimens in dermatology laboratories.