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 beha...
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We consider two small-world networks of Hodgkin-Huxley neurons interacting via inhibitory coupling. We found that synchronization indices (SI) in both networks oscillate periodically in time, so that time intervals of...
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In this paper, we consider applying computer vision algorithms for the classification problem one faces in neuroscience during EEG data analysis. Our approach is to apply a combination of computer vision and neural ne...
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In this paper, we analyze the brain activity during the execution by the subject of simple cognitive tasks associated with visual attention and symbol perception. We obtain biomarkers of brain activity in the process ...
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To model the picture of the external environment, the brain uses data coming from the sensory system. However, it is believed that the brain’s representation of the external environment is formed not only by sensory ...
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This paper discusses the three distinct types of motor activity, namely quasi, real, and imagery. Quasi-motion is voluntary movements that are minimized to the point that finally become undetectable by objective measu...
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In this paper, we discovered the increase in EEG power in the theta frequency range in the occipital cortex during a visual analysis of new information and the power decrease in the alpha range in the temporal lobe du...
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With this review we summarize the current state of scientific studies in the field of MI (motor imagery) and ME (motor execution). We composed brain map and description which correlate different brain areas with type ...
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In the present paper, we introduce an extended machine-learning-based approach to detect inter-areal functional connectivity based on an artificial neural network (ANN). Using the concept of generalized synchronizatio...
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This paper aims to present a comprehensive view on a new control method for legged robot: data-driven ground reaction predictor-based control. The idea of the method is to use machine learning tools to build a reliabl...
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