Search

Introduction: The olfactory system in chronic animal experiments is studied according to the records of bioelectric activity recorded with microelectrode arrays located on the dorsal surface of the olfactory bulb. It is believed that the response of the olfactory bulb bioelectric activity to the odorant presentation is associated with fluctuations synchronized by respiration and belonging to the range of so-called gamma rhythms. Purpose: To develop a method of automatic search for time boundaries of odor-induced gamma rhythm patterns in the bioelectric activity of an olfactory bulb. Results: The complexity of automatic search for odor-induced patterns are due to masking them by spontaneous oscillations of gamma rhythms unrelated to the olfactory system activity. Besides, the modal frequency of the patterns is a priori unknown and changes dynamically during an experiment on an anesthetized animal. The Hausdorff distance is used as a cost function of the search. In order to increase its sensitivity, an adaptive band-pass filter was synthesized based on a multichannel singular spectrum analysis. Its passband in the analyzed time sample corresponds best to the spectrum of the required patterns. The results of experiments on rats are presented. The use of band-pass filters based on the Fourier transform with parameters unchanged during the experiment due to the non-stationary nature of the frequency characteristics of the desired patterns does not ensure their effective search. In particular, when using the Butterworth band-pass filter in the search algorithm, significant errors were observed in determining the time boundaries of the epochs of patterns, and omissions of patterns. But the use of a synthesized adaptive band-pass filter provided reliable automatic search for patterns and determination of their time boundaries with a high accuracy. Algorithm failures in this case were observed only in rat motion artifacts. Practical relevance: The developed method extends the existing tools used to study the olfactory system of a living organism.

We propose a method for finding a priori undefined structures of unknown temporal fluctuations for frequency oscillators of various intensities as part of the output signals of synchronized dynamical systems. Unlike traditional approaches, the developed method is based on the continuous wavelet transform of the observed signal and is efficient in cases when frequency characteristics of the desired pattern are close to the noise characteristics of the output signal.

The study was aimed at developing a new automatic search technique for specific invariant patterns associated with the execution of voluntary motor activity (Readiness potentials, RP) reflected in multidimensional electroencephalogram (EEG) signals. The Hausdorff metric was used as a criterion function for searching specific movement-related EEG patterns in brain activity. To increase the metric sensitivity, an adaptive low-pass filter was synthesized with the multivariate singular spectrum analysis (SSA). It has been experimentally demonstrated that significant temporal characteristics of the brain potentials preceding movement execution in the frontal, central and parietal areas of the cerebral cortex, on average, were 240±90 ms. It is shown that the synthesized adaptive filter has provided a reliable automatic search for induced pre-movement EEG patterns and the correct determination of their time boundaries (accuracy up to 96%). The developed method expands the existing tools to improve the functionality and reliability of various Brain-computer interfaces including those based on randomly generated, user-induced patterns of brain activity associated with voluntary motor activity.

Although a significant number of studies have been devoted to the investigation of the electrographic correlates and neurophysiological mechanisms of spoken and inner (imagined) speech, there is a question on which EEG characteristics reflect its content. Considering that speech is a complex cognitive process which requires coordinated activity of a number of cortical structures of the large hemispheres, the EEG coherence values were studied. The values were recorded from 14 channels of 10 young men in the process of real verbalization (spoken speech) and during pronunciation of imagined words designating directions in space (up, down, right, left, forward, backward). It was shown that the level of EEG coherence is generally higher for real verbalization, most significantly at gamma-2-rhythm frequencies (55–70 Hz). Spatial coherence patterns specific to a number of words are formed in the left cerebral hemisphere during imagined utterance of words at gamma-2 frequencies. The application of machine learning and neural network classification has demonstrated a significant similarity of the generated spatial coherent patterns of spoken and inner (imagined) speech. The Multi-layer Perceptron (MLP) neural network classification method has shown the accuracy of word detection in the imagined speech according to brain activity patterns up to 49–61% for 3 classes and 33–40% for 7 classes, with a random recognition rate of 33,3 and 14,2% respectively. The latter indicates a promising application of coherence values and imagined speech denoting directions in space for the development of Brain-computer interfaces (BCIs).

Statement of the problem: the article looks into a class of problems which require identification of hidden regularities in adjustment of the bioelectrical activity of living organisms registered against various stimuli, through search and temporal localization of patterns in noised electrograms containing useful information. One of the approaches to solving such problems is based on an analysis of the Shannon entropy calculated based on the components of the power spectrum and called the spectral entropy function. It is found that under the conditions providing that the patterns in question pertain to high-frequency rhythms, and the boundaries of their energy spectra are a priori unknown, the criterial functions of spectral entropy are of low sensitivity. Purpose of the research: to develop cost functions of entropy analysis which are sufficiently sensitive for searching for high-frequency patterns with a priori unknown parameters in noised electrograms. Results: development of a cost function that makes it possible to find the frequency sub-band where the spectral components of the patterns in question maximally contribute to the total spectrum power. The subsequent computation of the spectral entropy in the identified frequency sub-band provides a solution to the problem of search for the response patterns in noised electrograms under the above conditions. Practical significance: the results confirm the effectiveness of the developed functions whose use is limited by the requirement that the electrogram should be recorded on more than one lead.

This paper describes tightly coupled algorithms of measurements by coarse microelectromechanical sensors with data generated by GPS/GLONASS mobile onboard satellite navigation receivers. The synthesized algorithm ensures a highly accurate and high-frequency recording of linear and angular car parameters when the visible satellite constellation degrades and the accuracy of satellite-aided measurements decreases. The terrestrial vehicle is supposed only to travel along the highway with coordinates recorded in digital navigation maps.

The integration of inertial and satellite navigation systems based on optimal linear stochastic filtration is characterized by considerable computational costs of synthesized algorithms. The proposed algorithm requires minimum computational effort and enables the efficient use of integrated navigation systems in automotive vehicles.

Tight integration of satellite and strapdown inertial navigation systems is used for automotive vehicles and complicated by the necessity to design adequate models of the object of research. A universal stochastic model adequately reflecting the processes of arbitrary motion of a ground vehicle is synthesized in a canonical form. The model can be used for realization of tightly coupled inertialsatellite navigation systems. The results of simulation modelling are given, which confirm the efficiency of the synthesized model.