Event-related Desynchronization Patterns Research Articles

Avatar embodiment prior to motor imagery training in VR does not affect the induced event-related desynchronization: a pilot study

Motor-imagery brain-computer interfaces (MI-BCIs) have the potential to improve motor function in individuals with neurological disorders. Their effectiveness relies on patients’ ability to generate reliable MI-related electroencephalography (EEG) patterns, which can be influenced by the quality of neurofeedback. Virtual Reality (VR) has emerged as a promising tool for enhancing proprioceptive feedback due to its ability to induce a sense of embodiment (SoE), where individuals perceive a virtual body as their own. Although prior research has highlighted the importance of SoE in enhancing MI skills and BCI performance, to date, no study has successfully isolated nor manipulated the SoE in VR before MI training, creating a gap in our understanding of the precise role of the priming effect of embodiment in MI-BCIs. In this study, we aimed to examine whether the virtual SoE when induced, as priming of avatar embodiment, and assessed before MI training, could enhance MI-induced EEG patterns. To achieve this, we divided 26 healthy participants into two groups: the embodied group, which experienced SoE with an avatar before undergoing VR-based MI training, and the non-embodied group, which underwent the same MI training without a prior embodiment phase, serving as a control. We analyzed subjective measures of embodiment, the event-related desynchronization (ERD) power of the sensorimotor rhythms, lateralization of ERD, and offline classification BCI accuracy. Although the embodiment phase effectively induced SoE in the embodied group, both groups exhibited similar MI-induced ERD patterns and BCI classification accuracy. This suggests that the induction of SoE prior to MI training may not significantly influence the training outcomes. Instead, it appears that the integration of embodied VR feedback during MI training itself is sufficient to induce appropriate ERD, as evidenced by previous research.

Cortical activation and BCI performance during brief tactile imagery: A comparative study with motor imagery

Brain-computer interfaces (BCIs) rely heavily on motor imagery (MI) for operation, yet tactile imagery (TI) presents a novel approach that may be advantageous in situations where visual feedback is impractical. The current study aimed to compare the cortical activity and digit classification performance induced by TI and MI to assess the viability of TI for use in BCIs. Twelve right-handed participants engaged in trials of TI and MI, focusing on their left and right index digits. Event-related desynchronization (ERD) in the mu and beta bands was analyzed, and classification accuracy was determined through an artificial neural network (ANN). Comparable ERD patterns were observed in both TI and MI, with significant decreases in ERD during imagery tasks. The ANN demonstrated high classification accuracy, with TI achieving a mean±SD of 79.30 ± 3.91 % and MI achieving 81.10 ± 2.96 %, with no significant difference between the two (p = 0.11). The study found that TI induces substantial ERD comparable to MI and maintains high classification accuracy, supporting its potential as an effective mental strategy for BCIs. This suggests that TI could be a valuable alternative in BCI applications, particularly for individuals unable to rely on visual cues.

Event-Related Desynchronization induced by Tactile Imagery: an EEG Study.

It is well-known that both hand movements and mental representations of movement lead to event-related desynchronization (ERD) of the electroencephalogram (EEG) recorded over the corresponding cortical motor areas. However, the relationship between ERD in somatosensory cortical areas and mental representations of tactile sensations is not well-understood. In this study, we employed EEG recordings in healthy humans to compare the effects of real and imagined vibrotactile stimulation of the right hand. Both real and imagined sensations produced contralateral ERD patterns, particularly in the μ-band and most significantly in the C3 region. Building on these results and the previous literature, we discuss the role of tactile imagery as part of the complex body image and the potential for using EEG patterns induced by tactile imagery as control signals in brain-computer interfaces (BCIs). Combining this approach with motor imagery could improve the performance of BCIs intended for rehabilitation of sensorimotor function after stroke and neural trauma.Significance StatementIn this study, we address the issue of mental representations in the somatosensory domain. By assessing the dynamics of sensorimotor EEG rhythms and the distribution of topographical EEG patterns, we demonstrate that tactile imagery produces event-related desynchronization in the contralateral EEG, even in the absence of physical stimulation. Our results clarify the neurophysiological mechanisms underlying the occurrence of ERD in the mu rhythm and its relationship to somatosensory cortical processing.

Motor-Related Mu/Beta Rhythm in Older Adults: A Comprehensive Review.

Mu rhythm, also known as the mu wave, occurs on sensorimotor cortex activity at rest, and the frequency range is defined as 8-13Hz, the same frequency as the alpha band. Mu rhythm is a cortical oscillation that can be recorded from the scalp over the primary sensorimotor cortex by electroencephalogram (EEG) and magnetoencephalography (MEG). The subjects of previous mu/beta rhythm studies ranged widely from infants to young and older adults. Furthermore, these subjects were not only healthy people but also patients with various neurological and psychiatric diseases. However, very few studies have referred to the effect of mu/beta rhythm with aging, and there was no literature review about this theme. It is important to review the details of the characteristics of mu/beta rhythm activity in older adults compared with young adults, focusing on age-related mu rhythm changes. By comprehensive review, we found that, compared with young adults, older adults showed mu/beta activity change in four characteristics during voluntary movement, increased event-related desynchronization (ERD), earlier beginning and later end, symmetric pattern of ERD and increased recruitment of cortical areas, and substantially reduced beta event-related desynchronization (ERS). It was also found that mu/beta rhythm patterns of action observation were changing with aging. Future work is needed in order to investigate not only the localization but also the network of mu/beta rhythm in older adults.

Audiovisual incongruence differentially impacts left and right hemisphere sensorimotor oscillations: Potential applications to production.

Speech production gives rise to distinct auditory and somatosensory feedback signals which are dynamically integrated to enable online monitoring and error correction, though it remains unclear how the sensorimotor system supports the integration of these multimodal signals. Capitalizing on the parity of sensorimotor processes supporting perception and production, the current study employed the McGurk paradigm to induce multimodal sensory congruence/incongruence. EEG data from a cohort of 39 typical speakers were decomposed with independent component analysis to identify bilateral mu rhythms; indices of sensorimotor activity. Subsequent time-frequency analyses revealed bilateral patterns of event related desynchronization (ERD) across alpha and beta frequency ranges over the time course of perceptual events. Right mu activity was characterized by reduced ERD during all cases of audiovisual incongruence, while left mu activity was attenuated and protracted in McGurk trials eliciting sensory fusion. Results were interpreted to suggest distinct hemispheric contributions, with right hemisphere mu activity supporting a coarse incongruence detection process and left hemisphere mu activity reflecting a more granular level of analysis including phonological identification and incongruence resolution. Findings are also considered in regard to incongruence detection and resolution processes during production.

Does Real-Time Feedback Affect Sensorimotor EEG Patterns in Routine Motor Imagery Practice?

Background. Motor imagery engages much of the same neural circuits as an overt movement. Therefore, the mental rehearsal of movements is often used to supplement physical training and might aid motor neurorehabilitation after stroke. One attempt to capture the brain’s involvement in imagery involves the use, as a marker, of the depression or event-related desynchronization (ERD) of thalamocortical sensorimotor rhythms found in a human electroencephalogram (EEG). Using fast real-time processing, it is possible to make the subject aware of their own brain reactions or—even better—to turn them into actions through a technology called the brain–computer interface (BCI). However, it remains unclear whether BCI-enabled imagery facilitates a stronger or qualitatively different brain response compared to the open-loop training. Methods. Seven healthy volunteers who were experienced in both closed and open-loop motor imagery took part in six experimental sessions over a period of 4.5 months, in which they performed kinesthetic imagery of a previously known set of finger and arm movements with simultaneous 30-channel EEG acquisition. The first and the last session mostly consisted of feedback trials in which the subjects were presented with the classification results of the EEG patterns in real time; during the other sessions, no feedback was provided. Spatiotemporal and amplitude features of the ERD patterns concomitant with imagery were compared across experimental days and between feedback conditions using linear mixed-effects modeling. Results. The main spatial sources of ERD appeared to be highly stable across the six experimental days, remaining nearly identical in five of seven subjects (Pearson’s ρ > 0.94). Only in one subject did the spatial pattern of activation statistically significantly differ (p = 0.009) between the feedback and no-feedback conditions. Real-time visual feedback delivered through the BCI did not significantly increase the ERD strength. Conclusion. The results imply that the potential benefits of MI could be yielded by well-habituated subjects with a simplified open-loop setup, e.g., through at-home self-practice.

Investigating the effect of losses and gains on effortful engagement during an incentivized Go/NoGo task through anticipatory cortical oscillatory changes.

Losses usually have greater subjective value (SV) than gains of equal nominal value but often cause a relative deterioration in effortful performance. Since losses and gains induce differing approach/avoidance behavioral tendencies, we explored whether incentive type interacted with approach/avoidance motor-sets. Alpha- and beta-band event-related desynchronization (ERD) was hypothesized to be weakest when participants expected a loss and prepared an inhibitory motor-set, and strongest when participants expected a gain and prepared an active motor-set. It was also hypothesized that effort would modulate reward and motor-set-related cortical activation patterns. Participants completed a cued Go/NoGo task while expecting a reward (+10p), avoiding a loss (-10p), or receiving no incentive (0p); and while expecting a NoGo cue with a probability of either .75 or .25. Pre-movement alpha- and beta-band EEG power was analyzed using the ERD method, and the SV of effort was evaluated using a cognitive effort discounting task. Gains incentivized faster RTs and stronger preparatory alpha band ERD compared to loss and no incentive conditions, while inhibitory motor-sets resulted in significantly weaker alpha-band ERD. However, there was no interaction between incentive and motor-sets. Participants were more willing to expend effort in losses compared to gain trials, although the SV of effort was not associated with ERD patterns or RTs. Results suggest that incentive and approach/avoidance motor tendencies modulate cortical activations prior to a speeded RT movement independently, and are not associated with the economic value of effort. The present results favor attentional explanations of the effect of incentive modality on effort.

Brain Patterns During Single- and Dual-Task Leg Movements

The brain is able to engage in dual tasks such as motor imagery (MI) and action observation (AO) or motor execution (ME) with action observation. In this study, we have quantitatively compared event-related desynchronization (ERD) patterns during tasks of pure MI, MI with AO (O-MI), ME, and ME with AO (O-ME) of the leg to investigate the underlying neuronal mechanisms using EEG. Subjects were instructed to imagine or perform rhythmical actions while watching a video of leg movements during O-MI and O-ME tasks; In contrast, subjects imagined and performed the leg movements without observing any video during pure MI and ME tasks. We noticed that the amplitude of ERDs from MI, O-MI, ME and O-ME sequentially increases in central regions of the brain. These quantified ERD patterns in EEG were used to study the differences of brain oscillatory changes among the four tasks. We found that ERDs in motor area were more distinct in O-MI, compared with pure MI. These results suggest that O-MI produced stronger motor activations than MI. Plus, O-ME showed significantly greater activations than ME in the beta band. O-ME has produced stronger neurophysiological effects than MI, and stronger behavioral effects than ME. These empirical results do provide convincing evidence of the dual tasks such combined MI or ME with action observation on brain pattern changes. The video of the goal-directed leg movements is most likely able to improve the ability of performing or imagining movements. O-MI and O-ME may get better and closer therapeutic effects in leg rehabilitation and motor skill training. Furthermore, the extent analysis of ERD may provide the basis for evaluating the ability of O-MI and O-ME in leg rehabilitation and motor skill training.

Cortical Activations and BCI Performances at Different Speeds of Visual and Proprioceptive Stimulation.

Motor imagery based brain-computer interface (MI-BCI) is one of the most common paradigms utilized in neurofeedback training (NFT) for rehabilitation engineering. Specifically, finding an appropriate feedback protocol is significantly important to improve the effectiveness of the motor training system. To this end, we investigated the electroencephalography(EEG) oscillatory patterns measured by event-related desynchronization (ERD) when sixteen participants accepted the visual and proprioceptive stimulation achieving the kinematic hand grasping movements at three different speeds (i.e. 1/3 Hz, 2/3 Hz and 1 Hz). The EEG results indicated that the ERD patterns showed no significant difference in sensorimotor cortex (i.e. C3 and FC3 channels) by comparing the three conditions. Nevertheless, the 2/3 Hz stimulation speed could achieve a significantly better classification performance than the other two conditions across all participants. Therefore, the visual and proprioceptive electrical stimulation achieving the kinematic hand grasping at 2/3 Hz speed might provide an available approach for the online MI-BCI system based NFT system in the future.

EEG time-frequency analysis provides arguments for arm swing support in human gait control

Background: Human gait benefits from arm swing, which requires four-limb co-ordination. The Supplementary Motor Area (SMA) is involved in multi-limb coordination. With its location anterior to the leg motor cortex and the pattern of its connections, this suggests a distinct role in gait control.Research question: Is the SMA functionally implicated in gait-related arm swing?Methods: Ambulant electroencephalography (EEG) was employed during walking with and without arm swing in twenty healthy subjects (mean age: 64.9yrs, SD 7.2). Power changes across the EEG frequency spectrum were assessed by Event Related Spectral Perturbation (ERSP) analysis over both the putative SMA at electrode position Fz and additional sensorimotor regions.Results: During walking with arm swing, midline electrodes Fz and Cz showed a step-related pattern of Event Related Desynchronization (ERD) followed by Event Related Synchronization (ERS). Walking without arm swing was associated with significant ERD-ERS power reduction in the high-beta/low-gamma band over Fz and a power increase over Cz. Electrodes C3 and C4 revealed a pattern of ERD during contralateral- and ERS during ipsilateral leg swing. This ERD power decreased in gait without arm swing (low-frequency band). The ERSP pattern during walking with arm swing was similar at CP1 and CP2: ERD was seen during double support and the initial swing phase of the right leg, while a strong ERS emerged during the second half of the left leg’s swing. Walking without arm swing showed a significant power reduction of this ERD-ERS pattern over CP2, while over CP1, ERS during left leg’s swing turned into ERD.Conclusion: The relation between arm swing in walking and a step-related ERD-ERS pattern in the high-beta/low-gamma band over the putative SMA, points at an SMA contribution to integrated cyclic anti-phase movements of upper- and lower limbs. This supports a cortical underpinning of arm swing support in gait control.

Multiple-command single-frequency SSVEP-based BCI system using flickering action video

BackgroundThe number of commands in a brain–computer interface (BCI) system is important. This study proposes a new BCI technique to increase the number of commands in a single BCI system without loss of accuracy. New methodWe expected that a flickering action video with left and right elbow movements could simultaneously activate the different pattern of event-related desynchronization (ERD) according to the video contents (e.g., left or right) and steady-state visually evoked potential (SSVEP). The classification accuracy to discriminate left, right, and rest states was compared under the three following feature combinations: SSVEP power (19–21 Hz), Mu power (8–13 Hz), and simultaneous SSVEP and Mu power. ResultsThe SSVEP feature could discriminate the stimulus condition, regardless of left or right, from the rest condition, while the Mu feature discriminated left or right, but was relatively poor in discriminating stimulus from rest. However, combining the SSVEP and Mu features, which were evoked by the stimulus with a single frequency, showed superior performance for discriminating all the stimuli among rest, left, or right. Comparison with the existing methodThe video contents could activate the ERD differently, and the flickering component increased its accuracy, such that it revealed a better performance to discriminate when considering together. ConclusionsThis paradigm showed possibility of increasing performance in terms of accuracy and number of commands with a single frequency by applying flickering action video paradigm and applicability to rehabilitation systems used by patients to facilitate their mirror neuron systems while training.

Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity.

Motor imagery is often used inducing changes in electroencephalographic (EEG) signals for imagery-based brain-computer interfacing (BCI). A BCI is a device translating brain signals into control signals providing severely motor-impaired persons with an additional, non-muscular channel for communication and control. In the last years, there is increasing interest using BCIs also for healthy people in terms of enhancement or gaming. Most studies focusing on improving signal processing feature extraction and classification methods, but the performance of a BCI can also be improved by optimizing the user’s control strategies, e.g., using more vivid and engaging mental tasks for control. We used multichannel EEG to investigate neural correlates of a sports imagery task (playing tennis) compared to a simple motor imagery task (squeezing a ball). To enhance the vividness of both tasks participants performed a short physical exercise between two imagery sessions. EEG was recorded from 60 closely spaced electrodes placed over frontal, central, and parietal areas of 30 healthy volunteers divided in two groups. Whereas Group 1 (EG) performed a physical exercise between the two imagery sessions, Group 2 (CG) watched a landscape movie without physical activity. Spatiotemporal event-related desynchronization (ERD) and event-related synchronization (ERS) patterns during motor imagery (MI) tasks were evaluated. The results of the EG showed significant stronger ERD patterns in the alpha frequency band (8–13 Hz) during MI of tennis after training. Our results are in evidence with previous findings that MI in combination with motor execution has beneficial effects. We conclude that sports MI combined with an interactive game environment could be a future promising task in motor learning and rehabilitation improving motor functions in late therapy processes or support neuroplasticity.

A mathematical model to mimic the shape of event related desynchronization/synchronization

Rhythmic oscillatory activities of the sensory cortex have been observed after a presentation of a stimulus. This activity first drops dramatically and then increases considerably that are respectively named event-related desynchronization (ERD) and event-related synchronization (ERS). There are several effective factors that can alter the ERD and ERS pattern. In this study, a mathematical model was presented that produced ERD and ERS pattern in response to a stimulus. This model works based on the synchronization concepts. The proposed model provided different suggestions about the reason behind the relationship between the encoding of incoming sensory information and the oscillatory activities, effective factors on the characteristics of neuronal units, and how may these factors affect the amplitude and latency of the ERD and ERS.

Sensory Feedback Interferes with Mu Rhythm Based Detection of Motor Commands from Electroencephalographic Signals.

Background: Electroencephalogram (EEG)-based brain-computer interfaces (BCI) represent a promising component of restorative motor therapies in individuals with partial paralysis. However, in those patients, sensory functions such as proprioception are at least partly preserved. The aim of this study was to investigate whether afferent feedback interferes with the BCI-based detection of efferent motor commands during execution of movements.Methods: Brain activity of 13 able-bodied subjects (age: 29.1 ± 4.8 years; 11 males) was compared between a motor task (MT) consisting of an isometric, isotonic grip and a somatosensory electrical stimulation (SS) of the fingertips. Modulation of the mu rhythm (8–13 Hz) was investigated to identify changes specifically related to the generation of efferent commands. A linear discriminant analysis (LDA) was used to investigate the activation pattern on a single-trial basis. Classifiers were trained with MT vs. REST (periods without MT/SS) and tested with SS and vice versa to quantify the impact of afferent feedback on the classification results.Results: Few differences in the spatial pattern between MT and SS were found in the modulation of the mu rhythm. All were characterized by event-related desynchronization (ERD) peaks at electrodes C3, C4, and CP3. Execution of the MT was associated with a significantly stronger ERD in the majority of sensorimotor electrodes [C3 (p < 0.01); CP3 (p < 0.05); C4 (p < 0.01)]. Classification accuracy of MT vs. REST was significantly higher than SS vs. REST (77% and 63%; p < 10-8). Classifiers trained on MT vs. REST were able to classify SS trials significantly above chance even though no motor commands were present during SS. Classifiers trained on SS performed better in classifying MT instead of SS.Conclusion: Our results challenge the notion that the modulation of the mu rhythm is a robust phenomenon for detecting efferent commands when afferent feedback is present. Instead, they indicate that the mu ERD caused by the processing of afferent feedback generates ERD patterns in the sensorimotor cortex that are masking the ERD patterns caused by the generation of efferent commands. Thus, processing of afferent feedback represents a considerable source of false positives when the mu rhythm is used for the detection of efferent commands.

Ipsilateral EEG mu rhythm reflects the excitability of uncrossed pathways projecting to shoulder muscles

BackgroundMotor planning, imagery or execution is associated with event-related desynchronization (ERD) of mu rhythm oscillations (8-13 Hz) recordable over sensorimotor areas using electroencephalography (EEG). It was shown that motor imagery involving distal muscles, e.g. finger movements, results in contralateral ERD correlating with increased excitability of the contralateral corticospinal tract (c-CST). Following the rationale that purposefully increasing c-CST excitability might facilitate motor recovery after stroke, ERD recently became an attractive target for brain-computer interface (BCI)-based neurorehabilitation training. It was unclear, however, whether ERD would also reflect excitability of the ipsilateral corticospinal tract (i-CST) that mainly innervates proximal muscles involved in e.g. shoulder movements. Such knowledge would be important to optimize and extend ERD-based BCI neurorehabilitation protocols, e.g. to restore shoulder movements after stroke. Here we used single-pulse transcranial magnetic stimulation (TMS) targeting the ipsilateral primary motor cortex to elicit motor evoked potentials (MEPs) of the trapezius muscle. To assess whether ERD reflects excitability of the i-CST, a correlation analysis between between MEP amplitudes and ipsilateral ERD was performed.MethodsExperiment 1 consisted of a motor execution task during which 10 healthy volunteers performed elevations of the shoulder girdle or finger pinching while a 128-channel EEG was recorded. Experiment 2 consisted of a motor imagery task during which 16 healthy volunteers imagined shoulder girdle elevations or finger pinching while an EEG was recorded; the participants simultaneously received randomly timed, single-pulse TMS to the ipsilateral primary motor cortex. The spatial pattern and amplitude of ERD and the amplitude of the agonist muscle’s TMS-induced MEPs were analyzed.ResultsERDs occurred bilaterally during both execution and imagery of shoulder girdle elevations, but were lateralized to the contralateral hemisphere during finger pinching. We found that trapezius MEPs increased during motor imagery of shoulder elevations and correlated with ipsilateral ERD amplitudes.ConclusionsIpsilateral ERD during execution and imagery of shoulder girdle elevations appears to reflect the excitability of uncrossed pathways projecting to the shoulder muscles. As such, ipsilateral ERD could be used for neurofeedback training of shoulder movement, aiming at reanimation of the i-CST.

EEG Analysis During Active and Assisted Repetitive Movements: Evidence for Differences in Neural Engagement.

Two key ingredients of a successful neuro-rehabilitative intervention have been identified as intensive and repetitive training and subject's active participation, which can be coupled in an active robot-assisted training. To exploit these two elements, we recorded electroencephalography, electromyography and kinematics signals from nine healthy subjects performing a 2×2 factorial design protocol, with subject's volitional intention and robotic glove assistance as factors. We quantitatively evaluated primary sensorimotor, premotor and supplementary motor areas activation during movement execution by computing event-related desynchronization (ERD) patterns associated to mu and beta rhythms. ERD patterns showed a similar behavior for all investigated regions: statistically significant ERDs began earlier in conditions requiring subject's volitional contribution; ERDs were prolonged towards the end of movement in conditions in which the robotic assistance was present. Our study suggests that the combination between subject volitional contribution and movement assistance provided by the robotic device (i.e., active robot-assisted modality) is able to provide early brain activation (i.e., earlier ERD) associated with stronger proprioceptive feedback (i.e., longer ERD). This finding might be particularly important for neurological patients, where movement cannot be completed autonomously and passive/active robot-assisted modalities are the only possibilities of execution.

Improving the discrimination of hand motor imagery via virtual reality based visual guidance

While research on the brain–computer interface (BCI) has been active in recent years, how to get high-quality electrical brain signals to accurately recognize human intentions for reliable communication and interaction is still a challenging task. The evidence has shown that visually guided motor imagery (MI) can modulate sensorimotor electroencephalographic (EEG) rhythms in humans, but how to design and implement efficient visual guidance during MI in order to produce better event-related desynchronization (ERD) patterns is still unclear. The aim of this paper is to investigate the effect of using object-oriented movements in a virtual environment as visual guidance on the modulation of sensorimotor EEG rhythms generated by hand MI. To improve the classification accuracy on MI, we further propose an algorithm to automatically extract subject-specific optimal frequency and time bands for the discrimination of ERD patterns produced by left and right hand MI. The experimental results show that the average classification accuracy of object-directed scenarios is much better than that of non-object-directed scenarios (76.87% vs. 69.66%). The result of the t-test measuring the difference between them is statistically significant (p = 0.0207). When compared to algorithms based on fixed frequency and time bands, contralateral dominant ERD patterns can be enhanced by using the subject-specific optimal frequency and the time bands obtained by our proposed algorithm. These findings have the potential to improve the efficacy and robustness of MI-based BCI applications.

3D visualization of movements can amplify motor cortex activation during subsequent motor imagery.

A repetitive movement practice by motor imagery (MI) can influence motor cortical excitability in the electroencephalogram (EEG). This study investigated if a realistic visualization in 3D of upper and lower limb movements can amplify motor related potentials during subsequent MI. We hypothesized that a richer sensory visualization might be more effective during instrumental conditioning, resulting in a more pronounced event related desynchronization (ERD) of the upper alpha band (10–12 Hz) over the sensorimotor cortices thereby potentially improving MI based brain-computer interface (BCI) protocols for motor rehabilitation. The results show a strong increase of the characteristic patterns of ERD of the upper alpha band components for left and right limb MI present over the sensorimotor areas in both visualization conditions. Overall, significant differences were observed as a function of visualization modality (VM; 2D vs. 3D). The largest upper alpha band power decrease was obtained during MI after a 3-dimensional visualization. In total in 12 out of 20 tasks the end-user of the 3D visualization group showed an enhanced upper alpha ERD relative to 2D VM group, with statistical significance in nine tasks.With a realistic visualization of the limb movements, we tried to increase motor cortex activation during subsequent MI. The feedback and the feedback environment should be inherently motivating and relevant for the learner and should have an appeal of novelty, real-world relevance or aesthetic value (Ryan and Deci, 2000; Merrill, 2007). Realistic visual feedback, consistent with the participant’s MI, might be helpful for accomplishing successful MI and the use of such feedback may assist in making BCI a more natural interface for MI based BCI rehabilitation.

Event-related mu-rhythm desynchronization during movement observation is impaired in Parkinson’s disease

ObjectivePatients with Parkinson’s disease often experience difficulties in adapting movements and learning alternative movements to compensate for symptoms. Since observation of movement has been demonstrated to lead to the formation of a lasting specific motor memory that resembled that elicited by physical training we hypothesize that mu-rhythm desynchronization in response to movement observation is impaired in Parkinson’s disease. MethodIn a pilot study with nine patients with Parkinson’s disease at a Hoehn and Yahr stage of I or II and eleven age-matched controls, we tested this hypothesis by comparing the event related desynchronization (ERD) patterns from the EEG recorded during the observation of hand action and baseline videos. ResultsHealthy subjects showed normal bilateral ERD of the mu-rhythm. In patients with Parkinson’s disease this distinct ERD pattern was lacking. ConclusionThe results of this study suggest that event-related mu-rhythm desynchronization is impaired in Parkinson’s disease, even at early stages of the disease. SignificanceStudying event-related mu-rhythm desynchronization dysfunction in Parkinson’s disease patients may enhance our understanding of symptoms as impaired motor learning.

Performance of Motor Imagery Brain-Computer Interface Based on Anodal Transcranial Direct Current Stimulation Modulation

Voluntarily modulating neural activity plays a key role in brain-computer interface (BCI). In general, the self-regulated neural activation patterns are used in the current BCI systems involving the repetitive trainings with feedback for an attempt to achieve a high-quality control performance. With the limitation posed by the training procedure in most BCI studies, the present work aims to investigate whether directly modulating the neural activity by using an external method could facilitate the BCI control. We designed an experimental paradigm that combines anodal transcranial direct current stimulation (tDCS) with a motor imagery (MI)-based feedback EEG BCI system. Thirty-two young and healthy human subjects were randomly assigned to the real and sham stimulation groups to evaluate the effect of tDCS-induced EEG pattern changes on BCI classification accuracy. Results showed that the anodal tDCS obviously induces sensorimotor rhythm (SMR)-related event-related desynchronization (ERD) pattern changes in the upper-mu (10-14 Hz) and beta (14-26 Hz) rhythm components. Both the online and offline BCI classification results demonstrate that the enhancing ERD patterns could conditionally improve BCI performance. This pilot study suggests that the tDCS is a promising method to help the users to develop reliable BCI control strategy in a relatively short time.