Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects

Jeunet, Camille; Glize, Bertrand; McGonigal, Aileen; Batail, Jean-Marie; Micoulaud‐Franchi, Jean‐Arthur

doi:10.1016/j.neucli.2018.10.068

Cited by 75 publications

(53 citation statements)

References 110 publications

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“…18.0 (IBM, Chicago, IL). We respectively, examined the effects of group, brain area, test condition, and time-phase on the ERD areas (%) in the mu band (8-12 Hz) and beta band (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25). Four-way repeated-measures analyses of variance (ANOVA) was used to assess the interactions and the main effects among four variables (group, brain area, condition, and time-phase).…”

Section: Statistical Analysesmentioning

confidence: 99%

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Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke

Chang

Chen

et al. 2019

Front. Neurol.

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Mirror therapy (MT) facilitates motor learning and induces cortical reorganization and motor recovery from stroke. We applied the new digital mirror therapy (DMT) system to compare the cortical activation under the three visual feedback conditions: (1) no mirror visual feedback (NoMVF), (2) bilateral synchronized task-based mirror visual feedback training (BMVF), and (3) reciprocal task-based mirror visual feedback training (RMVF). During DMT, EEG recordings, including time-dependent event-related desynchronization (ERD) signal amplitude in both mu and beta bands, were obtained from the standard C3 (ispilesional hemisphere, IH), C4 (contralesional hemisphere, CH), and Cz scalp sites (supplementary motor area, SMA). The entire ERD curve was separated into three time-phases: P0 (−2 to 0 s), P1 (0 to 2 s), and P2 (2 to 4 s). Four-way and subsequent repeated-measures analyses of variance were used to examine the effects of group (stroke vs. control group), test condition (NoMVF, BMVF, and RMVF), time-phase (P0, P1, and P2), and brain area (IH, CH, SMA) on the ERD areas (%) in mu and beta bands. For the mu band, generally, ERD areas (%) were larger in the control than in the stroke group. The ERD areas (%) were largest under the RMVF condition, followed by BMVF and NoMVF conditions. Similar results were found in the beta bands. The main effects of group, time-phase, and test condition on the ERD areas (%) were significant for the three brain areas, except the main effect of group in the SMA (Cz) and CH (C4) brain area. The ERD areas (%) were larger in the control than in the stroke group. The ERD area (%) was significantly larger during P1 than during P0 and P2 (ps < 0.02), and during P2 than during P0 (ps < 0.01). The ERD area (%) under the RMVF condition was significantly larger than that under the BMVF condition and NoMVF condition (ps < 0.05). The present study suggests that cortical activation particularly in the SMA (Cz) of the brain increases in the RMVF condition in both healthy subjects and stroke patients. This result supports the hypothesis that stroke patients may benefit from RMVF training.

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Section: Statistical Analysesmentioning

confidence: 99%

“…The study by Jeunet et al have developed an EEGbased (including mu and beta bands) brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills. Accordingly, mu and beta bands could be proper indices when examining the MT effectiveness (21).…”

Section: Introductionmentioning

confidence: 99%

Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke

Chang

Chen

et al. 2019

Front. Neurol.

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“…It is known well that during MI, the sensorimotor µ-rhythm power (8)(9)(10)(11)(12)(13) decreases noticeably relative to the baseline power for some time, and then rebounds and increases over the baseline power. These phenomena are referred to as event-related desynchronization (ERD) [11] and event-related synchronization (ERS) [12].…”

Section: Introductionmentioning

confidence: 98%

“…Reflecting Thompson's opinion, BCI's user-specific suitability, rather than BCI-illiteracy, has been addressed throughout this work. To enhance MI-BCI ability, many researchers have used neurofeedback [6][7][8] and sensory stimulation training [9,10] to help guide users. These strategies included evoked kinesthetic experiences and produced discriminative brain patterns among different classes.…”

Section: Introductionmentioning

confidence: 99%

Use of Both Eyes-Open and Eyes-Closed Resting States May Yield a More Robust Predictor of Motor Imagery BCI Performance

Kwon

Won

et al. 2020

Electronics

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Motor-imagery brain-computer interface (MI-BCI) is a technique that manipulates external machines using brain activities, and is highly useful to amyotrophic lateral sclerosis patients who cannot move their limbs. However, it is reported that approximately 15–30% of users cannot modulate their brain signals, which results in the inability to operate motor imagery BCI systems. Thus, advance prediction of BCI performance has drawn researchers’ attention, and some predictors have been proposed using the alpha band’s power, as well as other spectral bands’ powers, or spectral entropy from resting state electroencephalography (EEG). However, these predictors rely on a single state alone, such as the eyes-closed or eyes-open state; thus, they may often be less stable or unable to explain inter-/intra-subject variability. In this work, a modified predictor of MI-BCI performance that considered both brain states (eyes-open and eyes-closed resting states) was investigated with 41 online MI-BCI session datasets acquired from 15 subjects. The results showed that our proposed predictor and online MI-BCI classification accuracy were positively and highly significantly correlated (r = 0.71, p < 0.1 × 10 − 7 ), which indicates that the use of multiple brain states may yield a more robust predictor than the use of a single state alone.

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“…This is particularly relevant for neurofeedback studies targeting sensorimotor beta oscillations since beta activity can be reduced by motor imagery and attention (Pfurtscheller et al, 2001;Vukelić et al, 2019). A clear association between neurofeedback training and enhanced performance both in terms of self-regulation of EEG beta bursts and motor skills has yet to be established (Jeunet et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Neurofeedback-Linked Suppression of Cortical β Bursts Speeds Up Movement Initiation in Healthy Motor Control: A Double-Blind Sham-Controlled Study

Everest-Phillips

Clouter

et al. 2020

J. Neurosci.

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Abnormally increased beta bursts in cortical-basal ganglia-thalamic circuits are associated with rigidity and bradykinesia in patients with Parkinson's disease. Increased beta bursts detected in the motor cortex have also been associated with longer reaction times in healthy participants. Here we further hypothesize that suppressing beta bursts through neurofeedback training can improve motor performance in healthy subjects. We conducted a double-blind sham-controlled study on 20 human volunteers (10 females) using a sequential neurofeedback-behaviour task with the neurofeedback reflecting the occurrence of beta bursts over sensorimotor cortex quantified in real-time. The results show that neurofeedback training helps healthy participants learn to volitionally suppress beta bursts in the sensorimotor cortex, with training being accompanied by reduced reaction time in subsequent cued movements. These changes were only significant in the real feedback group but not in the sham group, confirming the effect of neurofeedback training over simple motor imagery. In addition, reaction times correlated with the rate and accumulated duration of beta bursts in the contralateral motor cortex before the Go cue, but not with averaged beta power. The reduced reaction times induced by neurofeedback training positively correlated with reduced beta bursts across all tested hemispheres. These results strengthen the link between the occurrence of beta bursts in the sensorimotor cortex before the Go cue and slowed movement initiation in healthy motor control. The results also highlight the potential benefit of neurofeedback training in facilitating voluntary suppression of beta bursts in order to speed up movement initiation. Significance This double-blind sham-controlled study suggested that neurofeedback training can facilitate volitional suppression of beta bursts in sensorimotor cortex in healthy motor control better 3 than sham feedback. The training was accompanied by reduced reaction time in subsequent cued movements, and the reduced reaction time positively correlated with the level of reduction in cortical beta bursts before the Go cue, but not with average beta power. These results provide further evidence of a causal link between sensorimotor beta bursts and movement initiation and suggest that neurofeedback training could potentially be used to train participants to speed up movement initiation.

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Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects

Cited by 75 publications

References 110 publications

Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke

Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke

Use of Both Eyes-Open and Eyes-Closed Resting States May Yield a More Robust Predictor of Motor Imagery BCI Performance

Neurofeedback-Linked Suppression of Cortical β Bursts Speeds Up Movement Initiation in Healthy Motor Control: A Double-Blind Sham-Controlled Study

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