In this work we present the development process of a wireless portable module. It is developed to record various characteristics during sport shooting, such as automatic detection of the moment of shot and barrel movement during aiming, taking into account the peculiarities of its use in neurophysiological research. We propose an approach allowing to synchronize devices in a wireless local network with high accuracy (synchronization accuracy was 2 ms), as well as a method of logging the recorded data at a sampling rate of up to 2 kHz on an onboard flash drive.
In this paper, we present an analysis of the dynamics of functional connectivity of the cerebral cortical network using near-infrared spectroscopy during human solutions to simple cognitive tasks. A task-based on the Sternberg paradigm was chosen to provide a cognitive load. We identified statistically significant changes in the communication forces obtained on the basis of the analysis of oxyhemoglobin signals during the experiment. We found that in the course of the experiment, there is a restructuring of the functional network, which is accompanied by a decrease in the average connectivity strength between the cortical areas under study. We showed that there is a correlation between the subjective evaluation of fatigue degree and the characteristics of the identified functional neural network.
In this paper, we investigated the fatigue-related processes of reconfiguring the human brain functional network while solving the cognitive task. We analyzed the correlations between the psychophysiological state of the subject with the characteristics of neural activity. We found that the subject’s fatigue positively correlates with the average degree of functional connectivities between neural ensembles in the beta and alpha frequency ranges. The obtained results indicate the increase in the integrative processes of a functional neural network. We revealed that the increasing fatigue during the experiment does not decrease the efficiency of the task completion: the speed and correctness of responses do not change. This suggests that functional integration may reflect the optimization of the brain’s neural network during the experiment.
The main goal of this project was to identify the patterns of muscular activity of a person in the process of his interaction with the environment, as well as to identify mechanisms that make it possible to adapt behavior in response to changing external conditions. For this, we conducted a series of experiments with subjects placed in an unstable state. We carried out statistical analysis for the received signals of muscle activity. Based on the results of the analysis of behavioral characteristics, we revealed positive dynamics when subjects were reaching a state of balance and a pattern associated with training.
We provided a combined analysis of electroencephalogram and functional near-infrared spectroscopy signals in order to investigate the process of prolonged visual perception. We investigated perception and decision-making processing during long-term and intense cognitive load. We found characteristic changes in electrical and hemodynamic activities during the neurophysiological experiment. The relationship was found between the EEG characteristics and the ΔO2Hb oscillation registered with the help of functional near-infrared spectroscopy.
Experimental design for recording of EEG and fNIRS during performance of real and imaginary movement was proposed. Set of experiments was conducted in accordance with this design and obtained EEG and fNIRS dataset was analyzed. Analysis allowed to introduce certain features in time-frequency domain that can be used to separate real motor activity from motor imagery.
KEYWORDS: Electroencephalography, Wavelets, Control systems, Electrodes, Information visualization, Visualization, Astatine, Signal analyzers, Bandpass filters, Linear filtering
We have recorded multichannel EEG signals from subjects maintaining the body balance on the balance board. Having synchronized the board oscillations and the recordings we have revealed and described specific features of the cortical activity that relate to balance maintaining and reaching an equilibrium state. We have found that the increase of the equilibrium state duration is accompanied by the change of the EEG spectral amplitude in the β frequency band.
We have proposed brain-computer interface (BCI) for the estimation of the brain response on the presented visual tasks. Proposed BCI is based on the EEG recorder Encephalan-EEGR-19/26 (Medicom MTD, Russia) supplemented by a special home-made developed acquisition software. BCI is tested during experimental session while subject is perceiving the bistable visual stimuli and classifying them according to the interpretation. We have subjected the participant to the different external conditions and observed the significant decrease in the response, associated with the perceiving the bistable visual stimuli, during the presence of distraction. Based on the obtained results we have proposed possibility to use of BCI for estimation of the human alertness during solving the tasks required substantial visual attention.
In this paper we suggest the new approach of powerful sub-THz signal generation based on intense electron beams containing oscillating virtual cathode. Suggested compact microwave source complies with a number of biomedical applications such as imaging, preventive healthcare, etc. In this work we discuss the results of numerical simulation and optimization of the novel device called “nanovircator” that have been carried out. The results of the numerical study show the possibility of “nanovircator” operation at 0.1-0.4 THz frequency range.
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