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The neural mechanisms underlying motor preparation have attracted much attention, particularly because of the assertion that they are similar to the mechanisms of motor imagery (MI), a technique widely used in motor rehabilitation and brain-computer interfaces (BCIs). Here we clarified the process of visuomotor transformation for the real and imagined movements by analyzing EEG responses that were time locked to the appearance of visual targets and movement onsets. The experimental task required responding to target stimuli with button presses or imagined button presses while ignoring distractors. We examined how different components of movement-related potentials (MRPs) varied depending on the reaction time (RT) and interpreted the findings in terms of the motor noise accumulation hypothesis. Furthermore, we compared MRPs and event-related desynchronization (ERD) for overt motor actions versus motor imagery. For the MRPs, we distinguished lateralized readiness potentials (LRPs) and reafferent potentials (RAPs). While MRPs were similar for the real and imagined movements, imagery-related potentials were not lateralized. The amplitude of the late potentials that developed during motor imagery at the same time RAPs occurred during real movements was correlated with the amplitude of β-ERD. As such they could have represented sensorimotor activation triggered by the imagery. LRPs that occurred during real movements lasted longer for longer RTs, which is consistent with activity accumulation in the motor cortex prior to overt action onset. LRPs occurred for non-target stimuli, as well, but they were small and short lived. We interpret these results in terms of a visuomotor transformation, where information flows from visual to motor areas and results in a movement, a decision not to move and/or a mental image of a movement. The amplitude of the late positive peak that developed during MI was correlated with the amplitude of the β-ERD. Since the latency of this component was consistent with the timing of RAP, we suggest that it is a non-lateralized RAP-like component associated with sensorimotor activation during kinesthetic MI.

It is well known that both the movement of the hand itself and the mental representation of it lead to event-related desynchronization (ERD) of EEG recorded over the corresponding motor areas of the cerebral cortex. Similarly, in somatosensory cortical areas, ERD occurs upon tactile stimulation of the hand, but whether this effect is caused by mental representation of sensations from tactile stimulation remains poorly understood. In the present study, the effects on the EEG of imaginary vibrotactile sensations on the right hand were compared with the effects of real vibrotactile stimulation. Both actual vibrotactile stimulation and mental representation of it have been found to elicit contralateral ERD patterns, particularly prominent in theμ-band and most pronounced in the C3 region. The paper discusses tactile imagery as a part of the complex sensorimotor mental image and its prospects for using EEG patterns of imagery-induced tactile sensations as control signals in BCI circuits independently and when combined with ERD based on movement imagination to improve the efficiency of neurointerface technologies in rehabilitation medicine, in particular, to restore movements after a stroke and neurotrauma.

Sharing, as a system of social practices, arises in the context of the digital economy. The latter requires a change in the basic ownership model. Classical idea of unlimited private property does not meet the new conditions for the production and consumption of goods and services. Sharing platforms that provide individuals with mutual access to private resources through digital technologies are a result of targeted programming and regulation of social relations. A feature of «joint consumption» is the contradiction between the non-commercial nature of access to private resources and their consumption and the commercial nature of the platform organization. In the regulatory sphere, this contradiction is expressed in the fact that the platforms commercially regulate social relations, while simultaneously solving the tasks of ensuring the non-commercial nature of interaction between users, protecting their interests and legitimizing their regulatory activities in the eyes of users. The development perspective is associated with the evolution of trust systems towards in the blockchain type.

Brain Computer Interface (BCIs) strive to provide a communication channel between the human brain and the environment without using overt actions. To achieve this goal, BCIs convert recordings of neural activity into commands to an external device. One of the most common BCI methods is based on matching of spectral characteristics of EEG sensorimotor rhythms (SMR) to motor imagery attempts. While such motor-imagery BCI have been extensively studied, little is known about the possibility of using tactile imagery as a BCI component. Here we studied EEG modulations associated with tactile imagery and obtained results suggesting that this approach could improve BCI operations.METHODS. 12 healthy naïve volunteers participated in the study. After vibrotactile stimulation was applied several times to the right hand, participants imagined the same sensations in the absence of actual vibration. During this tactile imagery task, 30 channels of EEG were recorded. The effects of tactile imagery were assessed as changes of the SMR in mu and beta bands, which were quantified using EEG desynchronization/synchronization (ERD/S) ratios. An offline classification was conducted for three states: resting, tactile imagery of the right hand, and tactile imagery of the left hand. The classification was based on common spatial pattern (CSP) filtering and linear discriminant analysis.RESULTS. The participants exhibited consistent contralateral ERD patterns over sensorimotor areas during tactile imagery of each hand. Statistically significant differences (p

In this work, the EEG mu-rhythm desynchronization was studied during motor imagery (MI) combined with functional electrical stimulation (FES) of an imaginary hand. The aim of the study is to estimate the effect of (FES) on mu-rhythm event related desynchronization/synchronization (ERD/ERDS) patterns during and after motor imagery. The study involved 13 healthy participants, which were asked to imagine the right hand grasping while EEG was recorded. Evaluation of the cortical activation was performed by mu-rhythm ERD/ERDS estimation. ERD/ERDS was assessed in experimental conditions before, during and after FES. Statistically significant changes (Friedman test) in the central mu-rhythm ERD during MI+FES comparing “before” condition was obtained. Our results suggest a direct effect of the peripheral electric stimulation on the cortical activation level, which is especially expressed in combination with the motor imagery.

Movement observation (MO) modulates activity of brain regions involved in motor control. It is mentioned that this phenomenon is evoked by the mirror neurons system activity and reflects processes of action understanding, action recognition and covert imitation of observed movements. Desynchronization of sensorimotor EEG oscillations and increase in corticospinal excitability assessed by transcranial magnetic stimulation (TMS) are invasive markers of motor and somatosensory cortices activation. Despite the fact that numerous studies show sensitivity of these markers to movements observation, little is known about the dynamics of the EEG activity and corticospinal excitability during evaluating the anatomically correctness of observed actions. We designed a TMS-EEG experiment with passive observation of simple aimless movements, in which subjects observed natural and unnatural flexions of fingers. Spatially separated sensorimotor EEG oscillations and TMS evoked myographic potentials were studied. The results revealed sensitivity of mu/beta oscillations to the anatomical correctness of movement. No correlations between mu/beta desynchronization and motor evoked potentials (MEPs) were found, but a weak link between beta synchronization and MEPs was shown. It might be proposed that ERD reflects activity of rather somatosensory but not motor cortex. Our findings demonstrate that activity of the sensorimotor cortex is modulated by action observation and action recognition, whereas EEG activity from different frequency ranges is modulated in different ways. Importantly, no significant changes in MEPs amplitude during MO was found. This result is discussed with regard to the impact of experimental instructions and participant's mental state during the MO task.

Motor imagery training is commonly used for sport and neurorehabilitation, improving human motor performance. In our previous works we have shown that motor imagery can be an effective way to reach higher performance in some sensorimotor tasks, technically related to esports. In this work reaction time of 10 participants was measured in the mouse aim task before and after motor imagery training session, while EEG was recorded. Statistically significant decrease in reaction time between before and after motor imagery training was obtained, while stable contralateral central ERD patterns during motor imagery were presented. A high correlation between baseline reactions’ time of participants and their levels of progress was observed. We believe that motor imagery training associated with sensorimotor rhythms desynchronization in EEG has great potential for esports training programs.

18 Healthy volunteers were involved and the effect of functional neuromuscular electrical stimulation, which causes flexion of the hand on the corticospinal excitability during motor imaging and resting state, was investigated in this study. It was shown that the combined action of functional electrical stimulation and the kinesthetic motor imagery leads to an increase of the amplitude of motor evoked potentials, caused by a single-pulse transcranial magnetic stimulation. At the same time, in the state of motor rest, this effect was not obtained. Since a change in corticospinal excitability at the cortical level may affect the processes of plastic reorganization necessary for the restoration of motor functions after strokes and other neurotraumas, the results of this work have a direct practical potential. In particular, the possibility of creating effective training complexes for the motor recovery based on motor imagery brain-computer interfaces with functional neuromuscular stimulation as a sensorimotor feedback is discussed. Rehabilitation with the use of such training complexes will help to elucidate the mechanisms of motor recovery, which are based on the phenomena of neuroplasticity due to changes in the excitability of neurons of the sensorimotor cortex.

Despite 50 years of research, there is still no common understanding of neurophysiological processes underlying meditation practice since the data obtained are often quite contradictory. For overcoming these difficulties, the literature suggests paying more attention to describing the type of meditation, practitioners’ experience, and other subjective factors (for example, discomfort from electrophysiological equipment or presented stimuli) that can influence the meditation process. In this article, we tried to consider these methodological recommendations and developed a special structured interview to take these factors into account. The results showed that neither field studies (investigation of meditation in conditions as close to natural as possible), nor the study of monks of the same tradition, from the same monasteries, having the same experience in meditation, does not guarantee that sufficiently homogeneous groups of subjects can be formed. A detailed analysis of the proposed structured interview may be necessary to research meditation’s influence on brain mechanisms.

Motor imagery (MI) training can improve motor performance which is widely used in sport training. BCI based on MI can demonstrate the quality of mental efforts via neurofeedback based on sensorimotor activation. Despite numerous studies of MI in context of classical sport, there are no studies aimed at improvement for e-athletes performance. The aim of the study is to evaluate the effect of MI-training on reaction time and velocity in gaming mouse control tasks. The study involved 14 healthy naive volunteers, divided into two subgroups. Experimental subgroup (N = 8) was trained with kinesthetic MI with BCI-visual feedback. The control subgroup (N = 6) had no BCI-feedback. In the speed selection task participants had to click on the correct mouse button. In the fast-clicking task participants should click as fast as they can for one minute. Each task was before (pretest) and after (posttest) MI training. During the training participants imagined finger movements used in actual task executions. During the task executions reaction time was recorded and EEG was recorded during MI training. Performed statistical analysis on a group level included paired comparisons between pretest and posttest (Wilcoxon signed-rank tests). Statistically significant changes (p < 0.05) in the reaction time in speed selection task and reaction velocity in fast clicking task after MI-training in experimental subgroup. Everyone in experimental subgroup had stable ERD during motor imagery, while there were neither differences in reaction time nor in reaction velocity in control group. The obtained results confirm the previously shown effects of motor imagery on sensorimotor performance.

Brain–computer interfaces (BCI) based on motor imagery allow people to use mental motor images recognized from the electroencephalogram (EEG) as control commands. With the aim of providing the most effective channel for interactions, interfaces of this type are under active development and modifi cation, though all currently require use of the visual modality in the control loop. We have proposed an interaction scheme using such BCI employing the vibrotactile channel – without use of visual control elements. The interface described here was tested in 11 healthy subjects who were presented with the task of learning motor imagery and using it in the BCI control loop, guided by stimuli delivered in the tactile modality – using vibration stimulators attached to the body. This paradigm provides for assessment of the effectiveness of motor imagery training with the eyes closed. During the study, which lasted seven experimental days, all subjects successfully acquired the motor imagery skill. Thus, users were found to be able to learn to operate in the BCI control loop without using the visual channel, when stimuli to carry out commands and feedback are delivered via the vibrational modality. The characteristics of EEG activity, corticospinal excitability, session-by-session dynamics, and the accuracy of BCI use in this approach were at least no different from those in the classical scheme with visual delivery of stimuli and feedback, and for some users the new mode had advantages in terms of a number of measures. The BCI paradigm proposed here opens up the potential for use by people with poor vision and widens the range of practical applications of BCI.

Motor imagery (MI) is considered to be a promising cognitive tool for improving motor skills as well as for rehabilitation therapy of movement disorders. It is believed that MI training efficiency could be improved by using the brain-computer interface (BCI) technology providing real-time feedback on person's mental attempts. While BCI is indeed a convenient and motivating tool for practicing MI, it is not clear whether it could be used for predicting or measuring potential positive impact of the training. In this study, we are trying to establish whether the proficiency in BCI control is associated with any of the neurophysiological or psychological correlates of motor imagery, as well as to determine possible interrelations among them. For that purpose, we studied motor imagery in a group of 19 healthy BCI-trained volunteers and performed a correlation analysis across various quantitative assessment metrics. We examined subjects' sensorimotor event-related EEG events, corticospinal excitability changes estimated with single-pulse transcranial magnetic stimulation (TMS), BCI accuracy and self-assessment reports obtained with specially designed questionnaires and interview routine. Our results showed, expectedly, that BCI performance is dependent on the subject's capability to suppress EEG sensorimotor rhythms, which in turn is correlated with the idle state amplitude of those oscillations. Neither BCI accuracy nor the EEG features associated with MI were found to correlate with the level of corticospinal excitability increase during motor imagery, and with assessed imagery vividness. Finally, a significant correlation was found between the level of corticospinal excitability increase and kinesthetic vividness of imagery (KVIQ-20 questionnaire). Our results suggest that two distinct neurophysiological mechanisms might mediate possible effects of motor imagery: the non-specific cortical sensorimotor disinhibition and the focal corticospinal excitability increase. Acquired data suggests that BCI-based approach is unreliable in assessing motor imagery due to its high dependence on subject's innate EEG features (e.g. resting mu-rhythm amplitude). Therefore, employment of additional assessment protocols, such as TMS and psychological testing, is required for more comprehensive evaluation of the subject's motor imagery training efficiency.

Nowadays, there is a growing number of studies suggesting that coupled with the brain-computer interface BCI the motor imagery practice could be a helpful tool in neurorehabilitation therapy, but the actual neurophysiological correlates of such exercise are poorly understood. In this study we examined two of the most notable neurophysiological effects of motor imagery --- the EEG mu-rhythm desynchronization and the increase in cortical excitability assessed with transcranial magnetic stimulation TMS. We have found that subjects' BCI performance was highly correlated with mu-rhythm features and was not associated with the cortical excitability increase. Subjects with the lowest accuracy in BCI all had a statically significant excitability raise during motor imagery and did not differ from better performers. Our results suggest that poor BCI performers with weak EEG response still could benefit from the motor imagery training, and in that case cortex excitability level had to be considered for the control measurement.