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Ушаков, Вадим Леонидович

Организационные подразделения

Организационная единица

Институт интеллектуальных кибернетических систем

Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.

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Ушаков

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Вадим Леонидович

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Теперь показываю 1 - 10 из 67

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Neurophysiological Correlators of Semantic Features
(2020) Orlov, V.; Stroganova, T.; Velichkovskiy, B.; Korosteleva, A.; Ushakov, V.; Ушаков, Вадим Леонидович
© 2020, Springer Nature Switzerland AG.The article presents the result of fMRI data processing - a map and characteristics of brain activity in the process of monitoring human speech activity. Experimental data calculated by 8 subjects. The main goal of the work was to localize the spatial and temporal dynamics of the neural networks of the cortex, which is responsible for the mechanism of verbal control. The secondary goal of the work was to recognize and remove noise components from the fMRI signal, which are related to human physiology and a feature of the test items.
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A Review of Method and Approaches for Resting State fMRI Analyses
(2020) Orlov, V. A.; Kozlov, S. O.; Enyagina, I. M.; Poyda, A. A.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2020, Springer Nature Switzerland AG.Resting-state functional Magnetic Resonance Imaging (R-fMRI) measures spontaneous low-frequency oscillations of the BOLD signal in order to identify the functional architecture of the human brain. The analysis of such data allowed to identify resting state networks (RSN) and other areas of the brain that operate synchronously in time. Over the past few years, the interest of both scientists and clinicians to various methods of R-fMRI data analysis has greatly increased. In this article, we present a review and comparison of various methods and algorithms for analyzing the functional connectivity of the human brain in resting state, developed in the world, based on an analysis of the literature.
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Application of Registration of Human Vegetative Reactions in the Process of Functional Magnetic Resonance Imaging
(2020) Orlov, V. A.; Kholodny, Y. I.; Kartashov, S. I.; Malakhov, D. G.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2020, Springer Nature Switzerland AG.This paper presents the first results of experiments on the joint use of MRI and MRI compatible polygraph in the study of neurocognitive processes, in particular - related to revealing of concealed information in humans. Experiments have shown the feasibility of using an MRI compatible polygraph in the process of fMRI studies. In the course of the study, the criterion for classifying subjects according to the dynamics of their vegetative reactions was discovered: the criterion allows for a more focused approach to the study of neurocognitive processes and may contribute to improving the quality of fMRI research for various purposes.
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Neuro-Correlates of the eBICA Model
(2020) Orlov, V. A.; Shigeev, S. V.; Ushakov, V. L.; Kartashov, S. I.; Samsonovich, A. V.; Ушаков, Вадим Леонидович; Самсонович, Алексей Владимир
© 2020, Springer Nature Switzerland AG.The article presents a new approach to building semantic maps based on the use of the eBICA model and the calculation of neurophysiological correlates of behavioral motives based on fMRI data. In this study, a social videogame paradigm was used in combination with fMRI and other recording tools. The obtained data show the complex neural network dynamics of behavioral motives distributed on the cortical and subcortical regions of the brain, related to the interaction of a person with the collaborative non-player character powered by the eBICA cognitive architecture.
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Dynamic Parameters of the Diffusion in Human Brain White Matter During Cognitive Tasks
(2020) Orlov, V.; Kartashov, S.; Ushakov, V.; Ушаков, Вадим Леонидович
© 2020, Springer Nature Switzerland AG.The aim of this work was to develop and analyze the MRI sequence for the functional tractography protocol. Also, a method of combining structural MRI, fMRI, tractography and functional tractography was developed to study the effect of changes in the diffusion of human CSF during performing the simplest cognitive tasks - motor stimulation and visual perception. Curves of these dynamic changes were obtained. A number of additional studies conducted show that described effect does not depend on the nearby large vessels.
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The role of brain stem structures in the vegetative reactions based on fMRI analysis
(2020) Orlov, V. A.; Kholodny, Y. I.; Malakhov, D. G.; Kovalchuk, M. V.; Ushakov, V. L.; Kartashov, S. I.; Ушаков, Вадим Леонидович
© Springer Nature Switzerland AG 2020.This work was aimed at studying the role of brain stem structures in vegetative responses upon presentation of self significant stimuli (personal name) using the functional MRI method. The subjects, based on the data of the MRI compatible polygraph, were divided into three groups with different degree of vegetative reactions to personality-related stimuli: with strong galvanic skin reactions (GSR) only—7 subjects; with medium GSR and cardiovascular response (CR)—6 subjects; and with low reactivity of GSR and CR—5 subjects. The obtained statistical maps of brain neural network activities showed high activation of the brain stem structures upon presentation of personality-related stimuli in the second group (medium GSR and CR); low activation of the stem structures in the first group (strong GSR); and complete absence of activation of the stem structures in subjects of the third group (with low reactivity of the GSR and CR). It was shown that the use of MRI compatible polygraph for selection of fMRI data to subsequent statistical analysis is effective.
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Lateralization in Neurosemantics: Are Some Lexical Clusters More Equal Than Others?
(2021) Nosovets, Z.; Velichkovsky, B. M.; Zaidelman, L.; Orlov, V.; Ushakov, V.; Ушаков, Вадим Леонидович
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.In this study, we have implemented neurosemantic analysis to identify brain’s voxel-wise representations of words in Russian spoken narratives and their asymmetries in the brain. 25 subjects listen to five stories, first person narratives of dramatic events, while their brain activation was registered by 3T functional magnetic resonance imaging (fMRI). Seven best subjects in terms of their engagement and objective control of brain reaction were selected for further analysis. Twelve lexical clusters were found, with different semantics – from time-and-space concepts to human actions and mental states. Clusters “experience” and “threat” were ones that on average demonstrated a symmetrical localization. For other clusters, brain localization has a left-sided bias. Our results support the view of non-modular and widely distributed nature of semantic representations, not limited to the activity of structures in the temporal and frontal lobes. These results also demonstrate that the right hemisphere can be involved in representation of mental lexicon. Our findings were broadly consistent with those reported for the English language, which points to the universality of the factors governing brain’s lexical representations.
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Neurophysiological Features of Neutral and Threatening Visual Stimuli Perception in Patients with Schizophrenia
(2021) Kartashov, S. I.; Orlov, V. A.; Maslennikova, A. V.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.The authors of this work set a goal to study the features of visual perception of threatening stimulus associated with personal experience in patients with schizophrenia. As a target group were taken patients with a paranoid-hallucinatory syndrome. Healthy volunteers without mental disorders and neurological diseases were used as controls. During fMRI studies, threatening and neutral images were presented. The experiment was built on the principle of a block paradigm. As a result, statistical parametric maps were constructed for two groups of subjects and the results were compared among themselves. According to the obtained results, patients with schizophrenia show a decrease in the overall level of activation in all regions of the brain compared with healthy volunteers. This is most evident in Middle Temporal Gyrus (temporooccipital part Right), Inferior Temporal Gyrus (temporooccipital part Left and Right), Lateral Occipital Cortex (inferior division Left and Right), Temporal Occipital Fusiform Cortex Left and Right and Frontal Pole Left and Right.
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The Solution to the Problem of Classifying High-Dimension fMRI Data Based on the Spark Platform
(2021) Efitorov, A.; Orlov, V.; Dolenko, S.; Shiroky, V.; Ushakov, V. L.; Широкий, Владимир Романович; Ушаков, Вадим Леонидович
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.This paper compares approaches to solving the classification problem based on fMRI data of the original dimension using the big data platform Spark. The original data is 4D fMRI time series with time resolution (TR) = 0.5 s for one sample recording. Participants have to solve 6 tasks, requiring activating various types of thinking, during 30 min session. A large number of subjects and a short time resolution generated the dataset with more than 86 000 samples, which allowed applying machine learning methods to solve this problem, instead of classical statistical maps. The random forest model was used to solve the binary classification problem. The paper analyzes model performance dependence upon time during the problem solving sessions. Evidence has been obtained that there is some limited time required for solving the same type of problems, and if more time is spent, this is due to the fact that the brain does not instantly get involved in the work on the proposed task, but it is still staying at resting state for some time.
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Mirror Neurons in the Interpretation of Action and Intentions
(2021) Bushov, Y. V.; Svetlik, M. V.; Kartashov, S. I.; Orlov, V. A.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.The aim of the research was the studying the activity of mirror neurons in humans during the observation and reproduction of rhythm. As markers of mirror neuron activity, we used depression of the EEG mu-rhythm in the alpha and beta frequency ranges, cortical interactions at the frequency of this rhythm, as well as the results of fMRI brain mapping. The research involved volunteers men and women aged from 18 to 27 year (University students). Research has shown that monitoring the reproduction of a five-second rhythm is accompanied by activation of not only those areas of the cortex where the «motor» mirror neurons are located, but also other cortex areas, as well as the basal ganglia and cerebellum. This findings suggest that mirror neurons themselves do not provide an understanding of actions and intentions, although they are involved in these processes. It is assumed that these neurons provide interaction between the prefrontal, sensory and motor areas of the cortex, as well as places where motor programs are stored in the brain. The result of the interaction of these structures is an understanding of the actions and intentions of other people.