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Using Brain-Computer Interface for Measuring Indicators of Cognitive Processes (A Case of Doing Educational Reading)
Ch. 9088759. P. 484–487.
Varnavsky A.N., Romanova I.I.
Students’ cognitive processes while their learning activities strongly influence the effectiveness of education. The indicators of such processes can be determined using an electroencephalogram analysis and, as a consequence, the success of educational process as a whole can be predicted. For this analysis, alpha and beta rhythms are traditionally used. It may be of interest to use complex indicators, characterizing several rhythms, and alternative types of rhythm, for example, theta rhythm, to improve measurement accuracy. To make it possible to use theta rhythm and to assess the level of understanding and interest of the text viewed, the preliminary experiment was carried out. The results of the experiment demonstrate that the maximum value of the dominant frequency of theta rhythm was observed in case of uninteresting or unfamiliar reading. The effect of font size on the performance of cognitive processes was also studied.
Исаев М. Р., Бобров П. Д., 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
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
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
Сизикова Т. Э., Леонов С. В., Polikanova I., Российский психологический журнал 2024 Т. 21 № 3 С. 172–189
Introduction. High levels of anxiety are often associated with abnormal activity in the brain areas involved in emotional processing, cognitive control, and reduced connectivity in the default mode network (DMN). Studies also show that the activation of the DMN increases during self-reflection processes, especially positive self-reference, suggesting the possibility of using self-reflection to reduce anxiety. ...
Added: November 2, 2024
Makarova A., Volkova K., Lebedev M. et al., , in: 2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2021. 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 ...
Added: December 9, 2022
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
Чадова И. Н., Водолажская М. Г., В кн.: Тезисы докладов седьмого международного конгресса «Нейронаука для медицины и психологии».: ООО «Макс Пресс», 2011. С. 114–115.
The subcortical-cortical integration with their relatively small genetic and phenotypic variation
(Shepovalnikov, Tsitseroshin, 2007) have a sexual dimorphism, studied in ontogenesis in less detailed compared
to the inner – and interhemispheric cortical zones interactions (Panasevizch, 2010). In this regard the general
differences research of the most informative EEG-parameters – the full amplitude spectrum (FAS) a wide
frequency range of ...
Added: December 3, 2019
Lebedev M., Proceedings of the National Academy of Sciences of the United States of America 2019 Vol. 116 No. 43 P. 21821–21827
Intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1) can produce percepts that mimic somatic sensation and, thus, has potential as an approach to sensorize prosthetic limbs. However, it is not known whether ICMS could recreate active texture exploration-the ability to infer information about object texture by using one's fingertips to scan a surface. Here, we show that ...
Added: November 1, 2019
Lebedev M., Frontiers in Neuroscience 2019 Vol. 13 P. 1–24
The Internet comprises a decentralized global system that serves humanity's collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a "human brain/cloud interface" ("B/CI"), ...
Added: November 1, 2019
Lebedev M., Neural Computation 2019 Vol. 31 No. 6 P. 1085–1113
Although many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications over the years, an optimal, consensual approach remains elusive. Recent advances in deep learning algorithms provide new opportunities for improving the design of BMI decoders, including the use of recurrent artificial neural networks to decode neuronal ensemble activity in real time. Here, we developed a long-short term memory (LSTM) decoder ...
Added: November 1, 2019
Smetanin N., Volkova K., Zabodaev S. et al., Frontiers in Neuroinformatics 2018 Vol. 12 No. 100 P. 1–18
Neurofeedback (NFB) is a real-time paradigm, where subjects learn to volitionally modulate their own brain activity recorded with electroencephalographic (EEG), magnetoencephalographic (MEG) or other functional brain imaging techniques and presented to them via one of sensory modalities: visual, auditory or tactile. NFB has been proposed as an approach to treat neurological conditions and augment brain ...
Added: December 13, 2018
Mirabella G., Lebedev M., Journal of Neurophysiology 2017 Vol. 117 No. 3 P. 1305–1319
It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject's motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) ...
Added: December 11, 2018
Lebedev M., Frontiers in Neuroscience 2017 Vol. 11 No. 642 P. 1–4
This highly cited paper by Ganguly and Carmena (2009) reported a case of neuroplasticity associated with the operation of a brain-machine interface (BMI). Neuroplasticity is of great interest to BMI developers because of its causal role in the embodiment of neural prostheses (Lebedev and Nicolelis, 2006; Dobkin, 2007; Koralek et al., 2012; Shenoy and Carmena, ...
Added: December 11, 2018
Lebedev M., Yin A., Tseng P. H. et al., Scientific Reports 2018 Vol. 8 No. 9184 P. 1–17
Primary motor (M1), primary somatosensory (S1) and dorsal premotor (PMd) cortical areas of rhesus monkeys previously have been associated only with sensorimotor control of limb movements. Here we show that a signifcant number of neurons in these areas also represent body position and orientation in space. Two rhesus monkeys (K and M) used a wheelchair ...
Added: December 11, 2018