Wavelet-Detected Changes in Nocturnal Brain Electrical Activity in Patients with Non-Motor Disorders Indicative of Parkinson's Disease.

Background/Objectives-Parkinson's disease (PD) is the second most common neurodegenerative disorder caused by the destruction of neurons in the substantia nigra of the brain. Clinical diagnosis of this disease, based on monitoring motor symptoms, often leads to a delayed start of PD therapy and control, where over 60% of dopaminergic nerve cells are damaged in the brain substantia nigra. The search for simple and stable characteristics of EEG recordings is a promising direction in the development of methods for diagnosing PD and methods for diagnosing the preclinical stage of PD development.

Compensatory mechanisms of reduced interhemispheric EEG connectivity during sleep in patients with apnea.

We performed a mathematical analysis of functional connectivity in electroencephalography (EEG) of patients with obstructive sleep apnea (OSA) (N = 10; age: 52.8 ± 13 years; median age: 49 years; male/female ratio: 7/3), compared with a group of apparently healthy participants (N = 15; age: 51.5 ± 29.

The Objective Assessment of Event-Related Potentials: An Influence of Chronic Pain on ERP Parameters.

The article presents an original method for the automatic assessment of the quality of event-related potentials (ERPs), based on the calculation of the coefficient ε, which describes the compliance of recorded ERPs with some statistically significant parameters. This method was used to analyze the neuropsychological EEG monitoring of patients suffering from migraines. The frequency of migraine attacks was correlated with the spatial distribution of the coefficients ε, calculated for EEG channels.

Examining time-frequency mechanisms of full-fledged deep sleep development in newborns of different gestational age in the first days of their postnatal development.

Early age-related changes in EEG time-frequency characteristics during the restful sleep of newborns of different gestational ages result in the development of conventional EEG signs of deep sleep already during the first postnatal week of their life. Allocating newborns to different groups based on their gestational age and duration of postnatal period allowed demonstrating substantial intergroup differences in brain activity during sleep and wakefulness, along with significant variability in the time-frequency characteristics of brain activity. The process of conventional deep sleep development in infants born prior to the week 35 of gestation is associated with an increase in the power of alpha activity in the sensorimotor cortex of the brain.

Spike-Wave Seizures, NREM Sleep and Micro-Arousals in WAG/Rij Rats with Genetic Predisposition to Absence Epilepsy: Developmental Aspects.

The current study was done in Wistar Albino Glaxo Rijswijk (WAG/Rij) rats, which are genetically prone to develop spontaneous spike-wave discharges (SWDs) and are widely used as a genetic model of absence epilepsy. Here, we examined functional links between sleep and spike-wave epilepsy in aging WAG/Rij rats using advanced techniques of EEG analysis. SWDs, periods of NREM sleep and micro-arousals were automatically detected in three-channel epidural EEG recorded in freely moving WAG/Rij rats consequently at the age 5, 7 and 9 months.

Synchronization of the Processes of Autonomic Control of Blood Circulation in Humans Is Different in the Awake State and in Sleep Stages.

The influence of higher nervous activity on the processes of autonomic control of the cardiovascular system and baroreflex regulation is of considerable interest, both for understanding the fundamental laws of the functioning of the human body and for developing methods for diagnostics and treatment of pathologies. The complexity of the analyzed systems limits the possibilities of research in this area and requires the development of new tools. Earlier we propose a method for studying the collective dynamics of the processes of autonomic control of blood circulation in the awake state and in different stages of sleep.

Modification of Joint Recurrence Quantification Analysis (JRQA) for assessing individual characteristics from short EEG time series.

This article proposes a modification of joint recurrence quantification analysis for identifying individual characteristics applied to human electroencephalography (EEG) using short time series. Statistical analysis of EEG characteristics facilitated the clarification of the spatial localization of identified individual characteristics. The method can be adapted for use as a stage of a rapid automatic configuration of brain-computer interface devices, which is especially relevant when working with children, due to limited opportunities for their long-term monitoring.

Modified wavelet analysis of ECoG-pattern as promising tool for detection of the blood-brain barrier leakage.

A new approach for detection oscillatory patterns and estimation of their dynamics based by a modified CWT skeleton method is presented. The method opens up additional perspectives for the analysis of subtle changes in the oscillatory activity of complex nonstationary signals. The method was applied to analyze unique experimental signals obtained in usual conditions and after the non-invasive increase in the blood-brain barrier (BBB) permeability in 10 male Wistar rats.

Wavelet skeletons in sleep EEG-monitoring as biomarkers of early diagnostics of mild cognitive impairment.

Many neuro-degenerative diseases are difficult to diagnose in their early stages. For example, early diagnosis of Mild Cognitive Impairment (MCI) requires a wide variety of tests to distinguish MCI symptoms and normal consequences of aging. In this article, we use the wavelet-skeleton approach to find some characteristic patterns in the electroencephalograms (EEGs) of healthy adult patients and patients with cognitive dysfunctions.

Changes in EEG Alpha Activity during Attention Control in Patients: Association with Sleep Disorders.

We aimed to assess which quantitative EEG changes during daytime testing in patients with sleep disorder (primary insomnia and excessive daytime sleepiness groups). All experimental study participants were subjected to a long-term test for maintaining attention to sound stimuli, and their EEGs were recorded and then processed, using wavelet analysis, in order to estimate the power and frequency structure of alpha activity. In healthy subjects, the maximum increase in the alpha rhythm occurred near 9 Hz.

Automatic wavelet-based assessment of behavioral sleep using multichannel electrocorticography in rats.

Purpose: During the last decade, the reported prevalence of sleep-disordered breathing in adults has been rapidly increasing. Therefore, automatic methods of sleep assessment are of particular interest. In a framework of translational neuroscience, this study introduces a reliable automatic detection system of behavioral sleep in laboratory rats based on the signal recorded at the cortical surface without requiring electromyography.

Percept-related EEG classification using machine learning approach and features of functional brain connectivity.

Machine learning is a promising approach for electroencephalographic (EEG) trials classification. Its efficiency is largely determined by the feature extraction and selection techniques reducing the dimensionality of input data. Dimensionality reduction is usually implemented via the mathematical approaches (e.

Classifying the Perceptual Interpretations of a Bistable Image Using EEG and Artificial Neural Networks.

In order to classify different human brain states related to visual perception of ambiguous images, we use an artificial neural network (ANN) to analyze multichannel EEG. The classifier built on the basis of a multilayer perceptron achieves up to 95% accuracy in classifying EEG patterns corresponding to two different interpretations of the Necker cube. The important feature of our classifier is that trained on one subject it can be used for the classification of EEG traces of other subjects.