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Ушаков, Вадим Леонидович

Организационные подразделения

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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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Basic Cognitive Architecture, Systemic Inflammation, and Immune Dysfunction in Schizophrenia
(2019) Ushakov, V. L.; Malashenkova, I. K.; Krynskiy, S. A.; Kartashov, S. I.; Ушаков, Вадим Леонидович
The aims of the project were to study the architecture of the brain's neural networks in the process of perceiving individual stimuli that are personally significant, to evaluate the main parameters of immunity and systemic inflammation, and to relate those to brain damage markers and patterns of cognitive-affective disorders in patients with schizophrenia. Materials and Methods. The study involved 35 patients with paranoid schizophrenia and 17 people without cognitive impairment. Clinical information about patients was obtained from the database created in the Alekseev Psychiatric Clinical Hospital No.1, Moscow Department of Health. The immunological arm of the study included the determination of key cytokines, neurotrophic factors, circulating immune complexes, C-reactive protein, cortisol, and immunoglobulins in the blood serum of patients. To study the cognitive functions, original methods of selecting the stimuli and recording the vegetative reactions were used; those allowed for identifying the architecture of neural networks involved in the pathogenesis of schizophrenia. Results. In this study, for the first time, changes in humoral immunity and parameters of systemic inflammation were found in patients with schizophrenia. Those changes included an increase in the levels of cytokines IL-6, IL-8, and interferon y, persisted regardless of the duration and nature of the antipsychotic therapy. Moreover, the immunological deviations were associated with the phase of the disease, it indicating their endogenous nature and connection with the pathogenesis of schizophrenia. Our pilot neuroimaging studies showed the feasibility of using MRI-compatible polygraphy for creating a group of fMRI images suitable for statistical analysis thus providing an objective assessment of physiological reactions to the presentation of personally-significant stimuli (based on keywords and images from the patient's anamnesis). By using this approach, we were able to detect the activation of neural networks in the associative zones of the left cuneus and precuneus and the ventrolateral prefrontal cortex of both hemispheres, i.e., the areas responsible for the working memory and processes of consciousness. Conclusion. Important novel data have been obtained on the relations between neurophysiological parameters, the cytokine profile and the immune status in schizophrenia.
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fmri and tractographic studies of cognitive systems in the human brain at the norm and the paranoid schizophrenia
(2019) Orlov, V. A.; Malakhov, D. G.; Maslennikova, A. V.; Arkhipov, A. Y.; Ushakov, V. L.; Kartashov, S. I.; Ушаков, Вадим Леонидович
© Springer Nature Switzerland AG 2019. This study is aimed at a systematic study of the work of neural networks of the human brain and their architecture in norm and in schizophrenia. To obtain the neurophysiological data, a unique complex of experimental equipment for world-class neurocognitive studies was used. The data obtained showed a significant decrease in the structural connectivity relationships for the rich club coefficient for a group of schizophrenic patients compared with the norm. Perception of emotionally negative visual and audio stimuli related to delusions in patients with schizophrenia does not lead to a significant decrease in BOLD signal as compared with the norm in Calcarine_L, Cerebelum_4_5_R, ParaHippocampal_LR, Precuneus_L, Temporal_Sup_R areas. The differences found in the structural and functional patterns of cognitive-affective disorders can serve as prognostic biomarkers in patients with schizophrenia and will make a significant contribution to the development of high-tech diagnostics in the early stages of mental illness.
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Contrasting human brain responses to literature descriptions of nature and to technical instructions
(2019) Orlov, V. A.; Malakhov, D. G.; Skiteva, L. I.; Zaidelman, L. Y.; Ushakov, V. L.; Kartashov, S. I.; Korosteleva, A. N.; Ушаков, Вадим Леонидович
© Springer Nature Switzerland AG 2019. The problem of semantic mapping of the brain is one of the urgent problems in human neurocognitive studies. At the present time there are only few studies reported in the world literature, all of which are made on the material and with the participation of English language native speakers. Russian language can thus become the second language for which this kind of research will be carried out, namely, finding out a correspondence between the semantic classes of the Russian vocabulary and the cortical areas responsible for processing these semantic classes when the text is orally presented. To solve this problem, it is necessary to develop techniques that allow us to investigate cognitive and neurolinguistic mechanisms of perception and understanding of the continuous text segments in natural language. In this paper, we present data on the comparative mapping of the human brain structures involved in the perception of meaningful texts containing technical instructions and literature descriptions of nature.
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Dear readers!
(2019) Velichkovsky, B. M.; Ushakov, V. L.; Ушаков, Вадим Леонидович
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Architecture of a wheelchair control system for disabled people: Towards multifunctional robotic solution with neurobiological interfaces
(2019) Karpov, V. E.; Malakhov, D. G.; Moscowsky, A. D.; Rovbo, M. A.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2019, Privolzhsky Research Medical University. All rights reserved.The aim of the study was to develop a control system for a robotic wheelchair with an extensive user interface that is able to support users with different impairments. Different concepts for a robotic wheelchair design for disabled people are discussed. The selected approach is based on a cognitive multimodal user interface to maximize autonomy of the wheelchair user and to allow him or her to communicate intentions by high-level instructions. Manual, voice, eye tracking, and BCI (brain–computer interface) signals can be used for strategic control whereas an intelligent autonomous system can perform low-level control. A semiotic model of the world processes sensory data and plans actions as a sequence of high-level tasks or behaviors for the control system. A software and hardware architecture for the robotic wheelchair and its multimodal user interface was proposed. This architecture supports several feedback types for the user including voice messages, screen output, as well as various light indications and tactile signals. The paper describes novel solutions that have been tested on real robotic devices. The prototype of the wheelchair uses a wide range of sensors such as a camera, range finders, and encoders to allow operator to move safely and provide object and scene recognition capabilities for the wheelchair. Dangerous behavior of the robot is interrupted by low-level reflexes. Additional high-level safety procedures can be implemented for the planning subsystem. The developed architecture allows utilizing user interfaces with a considerable time lag that are usually not suitable for traditional automated wheelchair control. This is achieved by increasing time allocated for processing of the interface modules, which is known to increase the accuracy of such interfaces as voice, eye tracking, and BCI. The increased latency of commands is mitigated by the increased automation of the wheelchair since high-level tasks can be given less frequently than manual control. The prospective solutions use a number of technologies based on registration of parameters of human physiological systems, including brain neural networks, in relation to the task of indirect control and interaction with mobile technical systems.
Только метаданные
Research of Neurocognitive Mechanisms of Revealing of the Information Concealing by the Person
(2019) Malakhov, D. G.; Orlov, V. A.; Kartashov, S. I.; Kholodny, Y. I.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2019, Springer Nature Switzerland AG. This work is related to the creation of an MR-compatible polygraph and the development of methods for detecting the hierarchy of neural networks of the cognitive organization of hidden memory markers. At the moment, there is practically no scientific work on lie detection, in which both the classical polygraph and the MRI scanner were simultaneously used. Combining these methods will help increase the probability of recognizing the facts of hiding important information and carry out an objective assessment of the truthfulness of the reported information. This method can also be used to detect the level of resistance of operators for emotional stress, assess the perception of emotional stimuli by subjects in neurocognitive tasks.
Только метаданные
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.
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Assessment of Cortical Travelling Waves Parameters Using Radially Symmetric Solutions to Neural Field Equations with Microstructure
(2021) Burlakov, E.; Verkhlyutov, V.; Malkov, I.; Ushakov, V. L.; Ушаков, Вадим Леонидович
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.We model cortical travelling waves by radially symmetric solutions to planar neural field equations with periodic spatial heterogeneity, which capture e.g. the microstructure observed in the primary visual cortex. We investigate the so-called bump-solutions that correspond to generation of local excitation in the brain tissue and an early stage of radially symmetric spread of cortical waves. We study how the neural medium heterogeneity and other biophysical parameters such as neuron activation threshold, the lengths and the strengths of neuronal connections affect cortical waves mathematically represented in terms of radially symmetric solutions to neural field equations with microstructure.