A5012263110- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Neural Networks and Applications
- Technology and Human Factors in Education and Health
- Heart Rate Variability and Autonomic Control
- Visual perception and processing mechanisms
- Sleep and Wakefulness Research
- stochastic dynamics and bifurcation
- Complex Systems and Time Series Analysis
- Nonlinear Dynamics and Pattern Formation
- Fractal and DNA sequence analysis
- Advanced Scientific Research Methods
- Blind Source Separation Techniques
- Obstructive Sleep Apnea Research
- Neuroscience of respiration and sleep
- Neural and Behavioral Psychology Studies
- Sleep and related disorders
- Cognitive Science and Mapping
- Muscle activation and electromyography studies
- Cognitive Science and Education Research
- Neuroscience and Neural Engineering
- Non-Invasive Vital Sign Monitoring
- Neuroscience and Neuropharmacology Research
- Time Series Analysis and Forecasting
Saratov State University
2013-2024
Saratov State Medical University
2019-2024
Institute of Physics
2021-2024
National Research Center for Preventive Medicine
2022-2024
Institute of Cardiology
2020-2022
Yuri Gagarin State Technical University of Saratov
2013-2020
Innopolis University
2019
We apply artificial neural network (ANN) for recognition and classification of electroencephalographic (EEG) patterns associated with motor imagery in untrained subjects. Classification accuracy is optimized by reducing complexity input experimental data. From multichannel EEG recorded the set 31 electrodes arranged according to extended international 10‐10 system, we select an appropriate type ANN which reaches 80 ± 10% single trial classification. Then, reduce number channels obtain...
In order to classify different human brain states related visual perception of ambiguous images, we use an artificial neural network (ANN) analyze multichannel EEG. The classifier built on the basis a multilayer perceptron achieves up 95% accuracy in classifying EEG patterns corresponding two interpretations Necker cube. important feature our is that trained one subject it can be used for classification traces other subjects. This result suggests existence common features structure...
The influence of motivation and alertness on brain activity associated with visual perception was studied experimentally using the Necker cube, which ambiguity controlled by contrast its ribs. wavelet analysis recorded multichannel electroencephalograms (EEG) allowed us to distinguish two different scenarios while processed ambiguous stimulus. first scenario is characterized a particular destruction alpha rhythm (8–12 Hz) simultaneous increase in beta-wave (20–30 Hz), whereas second...
In this paper we study the structural properties of a functional network human brain during evaluation mental tasks using concept betweenness centrality. We carry out experiments involving alternating trials task with simultaneous registration electroencephalographic (EEG) data. Using wavelet phase coherence reconstruct multiplex considering different typical frequency bands EEG activity as interconnected layers. reveal that transition from resting state to cognitive leads strong outflow...
We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of network from measurements processing macroscopic signals. Starting model Kuramoto phase oscillators, which evolve adaptively according to homophilic homeostatic adaptive principles, we give evidence that increase synchronization within groups nodes (and corresponding formation synchronous clusters) causes also defragmentation wavelet energy...
Brain-computer interfaces (BCIs) attract a lot of attention because their ability to improve the brain's efficiency in performing complex tasks using computer. Furthermore, BCIs can increase human's performance not only due human-machine interactions, but also thanks an optimal distribution cognitive load among all members group working on common task, i.e., human-human interaction. The latter is particular importance when sustained and alertness are required. In every day practice, this...
Abstract Neuronal brain network is a distributed computing system, whose architecture dynamically adjusted to provide optimal performance of sensory processing. A small amount visual information needed effortlessly be processed, activates neural activity in occipital and parietal areas. Conversely, task which requires sustained attention process large information, involves set long-distance connections between frontal areas coordinating the these distant regions. We demonstrate that while...
Behavioral experiments evidence that attention is not maintained at a constant level, but fluctuates with time. Recent studies associate such fluctuations dynamics of attention-related cortical networks, however the exact mechanism remains unclear. To address this issue, we consider functional neuronal interactions during accomplishment reaction time (RT) task which requires sustained attention. The participants are subjected to binary classification large number presented ambiguous visual...
Stimulus-related brain activity is considered using wavelet-based analysis of neural interactions between occipital and parietal areas in alpha (8--12 Hz) beta (15--30 frequency bands. We show that human sensory processing related to the visual stimuli perception induces response resulted different ways parieto-occipital these In band neuronal network characterized by homogeneous increase interaction all interconnected both within lobes them. lobe starts play a leading role dynamics...
The reliable and objective assessment of intelligence personality has been a topic increasing interest contemporary neuroscience psychology. It is known that can be measured by estimating the mental speed or velocity information processing. This usually as reaction time during elementary cognitive task processing, while often assessed means questionnaires. On other hand, human affects way subject accomplishes tasks and, therefore, some features define intelligence. expected these features,...
We study the synchronization of infra-slow oscillations in human scalp electroencephalogram signal with respiratory signal. For cases paced respiration a fixed frequency and linearly increasing frequency, we reveal phase locking brain potentials by respiration. It is shown that for different areas, can exhibit synchronous regimes orders.
Machine learning is a promising approach for electroencephalographic (EEG) trials classification. Its efficiency largely determined by the feature extraction and selection techniques reducing dimensionality of input data. Dimensionality reduction usually implemented via mathematical approaches (e.g., principal component analysis, linear discriminant etc.) regardless origin analyzed We hypothesize that since EEG features are certain neurophysiological processes, they should have distinctive...
A new approach for detection oscillatory patterns and estimation of their dynamics based by a modified CWT skeleton method is presented. The opens up additional perspectives the analysis subtle changes in activity complex nonstationary signals. was applied to analyze unique experimental signals obtained usual conditions after non-invasive increase blood-brain barrier (BBB) permeability 10 male Wistar rats. results wavelet-analysis electrocorticography (ECoG) recorded normal physiological...
The lymphatic drainage system of the brain (LDSB) is removal metabolites and wastes from its tissues. A dysfunction LDSB an important sign aging, oncology, Alzheimer's Parkinson's diseases. development new strategies for diagnosis injuries can improve prevention age-related cerebral amyloid angiopathy, neurodegenerative cerebrovascular There are two conditions, such as deep sleep opening blood-brain-barrier (OBBB) associated with activation. promising candidate measurement could be...
Many neuro-degenerative diseases are difficult to diagnose in their early stages. For example, diagnosis of Mild Cognitive Impairment (MCI) requires a wide variety tests distinguish MCI symptoms and normal consequences aging. In this article, we use the wavelet–skeleton approach find some characteristic patterns electroencephalograms (EEGs) healthy adult patients with cognitive dysfunctions. We analyze EEG activity recorded during natural sleep 11 elderly aged between 60 75, six whom have...
Abstract We performed a mathematical analysis of functional connectivity in electroencephalography (EEG) patients with obstructive sleep apnea (OSA) (N = 10; age: 52.8 ± 13 years; median 49 male/female ratio: 7/3), compared group apparently healthy participants 15; 51.5 29.5 42 8/7), based on the calculation wavelet bicoherence from nighttime polysomnograms. Having observed previously known phenomenon interhemispheric synchronization deterioration, we demonstrated compensatory increase...
We aimed to assess which quantitative EEG changes during daytime testing in patients with sleep disorder (primary insomnia and excessive sleepiness groups). All experimental study participants were subjected a long-term test for maintaining attention sound stimuli, their EEGs recorded then processed, using wavelet analysis, order estimate the power frequency structure of alpha activity. In healthy subjects, maximum increase rhythm occurred near 9 Hz. Patients primary characterized by an...