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Exploration of Cortical Dynamics in the Center-Out with Stylus Paradigm
P. 64–66.
This study aims to identify correlations between the directions of the hand movements and the brain signals recorded from the brain surface using electrocorticography (ECoG). We suppose that the coding of the hand movement direction occurs in the motor cortex and could be detected with ECoG. Using representational similarity analysis (RSA) and the cosine tuning assumption we confirmed that indeed, there is a significant concordance between the brain signals and the hand movement directions. And the main areas of the brain responsible for this have been identified.
Исаев М. Р., Bobrov P., Журнал высшей нервной деятельности им. И.П. Павлова 2022 Т. 72 № 5 С. 728–738
The paper proposes methods for brain–computer interface, based on the hemodynamic activity registration using near–infrared spectroscopy (NIRS) and adapted for using in the movement disorders rehabilitation. Methods include a filtration adapted to the instructions frequency, step by step classification of the rest state and active tasks, as well as training of the interface classifier on ...
Added: March 18, 2026
Люкманов Р. Х., Исаев М. Р., Mokienko O. et al., Анналы клинической и экспериментальной неврологии 2023 Т. 17 № 4 С. 82–88
Introduction. Non-invasive brain–computer interfaces (BCIs) enable feedback motor imagery [MI] training in neurological patients to support their motor rehabilitation. Nowadays, the use of BCIs based on functional near-infrared spectroscopy (fNIRS) for motor rehabilitation is yet to be investigated. Objective: To evaluate the potential fNIRS BCI use in hand MI training for comprehensive post-stroke rehabilitation. Materials ...
Added: March 18, 2026
Лабор В. В., Mokienko O., Черкасова А. Н. et al., Журнал неврологии и психиатрии им. С.С. Корсакова 2025 Т. 125 № 11 С. 27–35
В статье представлен обзор исследований, посвященных применению тренировок представления движения и интерфейсов мозг-компьютер (ИМК) для когнитивной реабилитации пациентов с неврологическими заболеваниями. На основе анализа исследований, опубликованных с 2004 по 2025 г., проведена оценка эффективности данных методов в восстановлении когнитивных функций у пациентов с инсультом (13 исследований), болезнью Паркинсона (4) и рассеянным склерозом (2). Большинство исследований демонстрирует положительное влияние тренировок представления движения на когнитивные функции пациентов с неврологическими заболеваниями и когнитивным дефицитом средней ...
Added: March 18, 2026
Решетникова В. В., Боброва Е. В., Гришин А. А. et al., Журнал высшей нервной деятельности им. И.П. Павлова 2025 Т. 75 № 3 С. 313–326
Neurorehabilitation of motor functions using a neurointerface (BCI) with feedback is a modern promising area of research. However, there is very little data on muscle activity during the motor imagery of lower limb – an important aspect of rehabilitation. The EMG activity of the lower limb muscles was studied in 42 healthy participants which control ...
Added: March 11, 2026
Mokienko O., Chervyakov A., Kulikova S. et al., Frontiers in Computational Neuroscience 2013 No. 7 Article 168
Background: Motor imagery (MI) is the mental performance of movement without muscle activity. It is generally accepted that MI and motor performance have similar physiological mechanisms.
Purpose: To investigate the activity and excitability of cortical motor areas during MI in subjects who were previously trained with an MI-based brain-computer interface (BCI).
Subjects and Methods: Eleven healthy volunteers ...
Added: March 9, 2026
Frolov A., Mokienko O., Lyukmanov R. et al., Frontiers in Neuroscience 2017 Vol. 11 Article 400
Repeated use of brain-computer interfaces (BCIs) providing contingent sensory feedback of brain activity was recently proposed as a rehabilitation approach to restore motor function after stroke or spinal cord lesions. However, there are only a few clinical studies that investigate feasibility and effectiveness of such an approach. Here we report on a placebo-controlled, multicenter clinical ...
Added: March 9, 2026
Isaev M., Pavel Bobrov, Olesya Mokienko et al., Sensors 2025 Vol. 25 No. 16 Article 5040
Understanding patterns of interhemispheric asymmetry is crucial for monitoring neuroplastic changes during post-stroke motor rehabilitation. However, conventional laterality indices often pose computational challenges when applied to functional near-infrared spectroscopy (fNIRS) data due to the bidirectional hemodynamic responses. In this study, we analyze fNIRS recordings from 15 post-stroke patients undergoing motor imagery brain-computer interface training across ...
Added: March 6, 2026
Gavrilenko Y., Saada D., Ilyushin E. et al., Advances in Intelligent Systems and Computing 2021 Vol. 1310 P. 97–105
The internal speech recognition is a promising technology, which could find its use in brain-computer interfaces development and greatly help those who suffer from neurodegenerative diseases. The research in this area is in its early stages and is associated with practical value, which makes it relevant. It is known that internal pronunciation can be restored ...
Added: October 2, 2025
Fedosov N., Medvedeva D., Shevtsov O. et al., Journal of Neural Engineering 2025 No. 22 Article 046031
Objective. Recent advances in biomagnetic sensing have led to the development of compact, wearable devices capable of detecting weak magnetic fields generated by biological activity. Optically pumped magnetometers (OPMs) have shown significant promise in functional neuroimaging. Brain rhythms play a crucial role in diagnostics, cognitive research, and neurointerfaces. Here we demonstrate that a small number of ...
Added: September 5, 2025
Asker A. Nagoev, Rusak A., Truskova A., , in: Big Data and Artificial Intelligence for Decision-Making in the Smart EconomyVol. 168.: Switzerland: Springer, 2025. Ch. 41 P. 389–396.
Added: August 27, 2025
Aksiotis V., Alexei Ossadtchi, , in: 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN) Kaliningrad, 14-16 Sept. 2022.: IEEE, 2022. P. 6–9.
In the present study, a fast and adaptive technique for the presentation of stimuli based on ongoing brain rhythm is described. Sensorimotor cortical mu rhythm (divided by two components: alpha (mu) and beta) was used as target for assessment of prestimulus rhythm’s power influence on the consequent reaction time. The final sample consisted of 15 ...
Added: December 16, 2022
Makarova A., Volkova K., Ossadtchi A. et al., , in: 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN) Kaliningrad, 14-16 Sept. 2022.: IEEE, 2022. P. 86–89.
Brain-computer interfaces (BCIs) based on electrocorticographic (ECoG) activity has become relatively popular due to sensitivity of ECoG to specific details of actual and imagined actions. It has been shown that significant differences in the brain activity while performing hand movements in different directions can be found in relation to cosine tuning theory. This research seeks ...
Added: December 16, 2022
Dimitri Bredikhin, Agranovich O., Ulanov M. et al., Clinical Neurophysiology 2023 Vol. 145 P. 11–21
Objective
Obstetric brachial plexus palsy (OBPP) and amyoplasia, the classical type of arthrogryposis multiplex congenita, manifest themselves as highly limited mobility of the upper limb. At the same time, according to the embodiment cognition theories, the motor impairments might lead to the alteration of cognitive functions in OBPP/amyoplasia patients. In the current study, we examined whether ...
Added: November 16, 2022
Petrosyan A., Синкин М. В., Lebedev M. et al., Journal of Neural Engineering 2021 Vol. 18 Article 026019
Abstract
Objective. Brain–computer interfaces (BCIs) decode information from neural activity and send it to external devices. The use of Deep Learning approaches for decoding allows for automatic feature engineering within the specific decoding task. Physiologically plausible interpretation of the network parameters ensures the robustness of the learned decision rules and opens the exciting opportunity for automatic knowledge ...
Added: January 24, 2022
Fedosov N., Shevtsov O., Ossadtchi A., , in: 2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2021. P. 16–18.
Added: December 8, 2021
Fedosov N., Levadniy I., Dmitriev A. et al., , in: Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020.: IEEE, 2020. P. 69–72.
Added: December 8, 2021
Vidaurre C., Jorajuría T., Ramos-Murguialday A. et al., Journal of Neural Engineering 2021 Vol. 18 No. 4 Article 0460b1
Objective.Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other ...
Added: September 8, 2021
Lebedev M., Ossadtchi A., Okorokova L. et al., , in: Brain–Computer Interface Research. A State-of-the-Art Summary 8.: Springer, 2020. P. 11–23.
Handwriting is an advanced motor skill and one of the key developments in human culture. Here we show that handwriting can be decoded—offline and online—from electromyographic (EMG) signals recorded from multiple hand and forearm muscles. We convert EMGs into continuous handwriting traces and into discretely decoded font characters. For this purpose, we use Wiener and ...
Added: February 4, 2021
Kardonov Y., Инновации и инвестиции 2020 № 8 С. 191–193
Neurotechnologies are used in various areas of the real economy. The article analyzes the solutions of companies in the field of neurotechnology to identify the main areas of commercial application of such solutions. The classification of these solutions is given for such areas of application as assessment and development of skills using neurotechnology, neuromarketing, neurocontrol, ...
Added: January 9, 2021