Human performance in complex mental tasks relies on elementary cognitive abilities, e.g., information processing speed and working memory capacity. These elementary functions can be measured on a behavioral level usin...
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In the present study we aim to find specific characteristic based on brain activity, that can be used to evaluate attention and, thus, can be used in brain-computer interface. We propose an approach to collaborative B...
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In this paper, we analyze the functional connectivity between changes in the concentration of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin, recorded by various leads of fNIRS from the frontal and parietal cort...
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In this paper, we present an analysis of modern tools for processing brain neuronal connectivity graphs-feed-forward artificial neural network. Different configurations of multilayer perceptron were considered and tes...
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This work is devoted to the study of one of the fundamental properties of the beam, namely, space-charge-limited current in a cylindrical drift tube located in an external magnetic field of various intensities. The va...
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A promising task is the analysis of the different rhythms of the brain cortical activity when performing cognitive tasks. Studying this issue allows to advance in the development of brain-computer interfaces. Some bra...
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In present paper, we introduce a database containing multichannel experimental data of brain electrical activity (M/EEG signals) supplemented by necessary experimental protocols and additional characteristics of the s...
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We developed noninvasive brain-to-brain interface for dynamical redistribution of cognitive load between subjects according to their current performances during shared cognitive task. As a result, a participant who ex...
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作者：
Andreev, AndreyInnopolis University
Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia
We investigate the dynamics of complex network of Hodgkin-Huxley neurons. It consists of 3 sub-networks. The first small network receives external signal which is transferred into a spike sequence. Then it is transmit...
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In this study, we examined reservoir computing (RC)as a tool for predicting the macroscopic dynamics of a subset of oscillators in a network based on the macroscopic dynamics of other parts of it. As a model network, ...
In this study, we examined reservoir computing (RC)as a tool for predicting the macroscopic dynamics of a subset of oscillators in a network based on the macroscopic dynamics of other parts of it. As a model network, we utilized a network of 300 Kuramoto oscillators with adaptation. Our results demonstrate that reservoir computing effectively addresses this task. Additionally, a similar reservoir computing model was applied to experimental neurovisualization data and exhibited high accuracy in reconstructing damaged EEG channels compared to classical methods like spatial interpolation.
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