Sensorimotor Rhythm Research Articles

Functional Electrical Stimulation Controlled by Motor Imagery Brain-Computer Interface for Rehabilitation.

Sensorimotor rhythm (SMR)-based brain–computer interface (BCI) controlled Functional Electrical Stimulation (FES) has gained importance in recent years for the rehabilitation of motor deficits. However, there still remain many research questions to be addressed, such as unstructured Motor Imagery (MI) training procedures; a lack of methods to classify different MI tasks in a single hand, such as grasping and opening; and difficulty in decoding voluntary MI-evoked SMRs compared to FES-driven passive-movement-evoked SMRs. To address these issues, a study that is composed of two phases was conducted to develop and validate an SMR-based BCI-FES system with 2-class MI tasks in a single hand (Phase 1), and investigate the feasibility of the system with stroke and traumatic brain injury (TBI) patients (Phase 2). The results of Phase 1 showed that the accuracy of classifying 2-class MIs (approximately 71.25%) was significantly higher than the true chance level, while that of distinguishing voluntary and passive SMRs was not. In Phase 2, where the patients performed goal-oriented tasks in a semi-asynchronous mode, the effects of the FES existence type and adaptive learning on task performance were evaluated. The results showed that adaptive learning significantly increased the accuracy, and the accuracy after applying adaptive learning under the No-FES condition (61.9%) was significantly higher than the true chance level. The outcomes of the present research would provide insight into SMR-based BCI-controlled FES systems that can connect those with motor disabilities (e.g., stroke and TBI patients) to other people by greatly improving their quality of life. Recommendations for future work with a larger sample size and kinesthetic MI were also presented.

Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain-Computer Interface Experiments.

In this study, the sources of EEG activity in motor imagery brain–computer interface (BCI) control experiments were investigated. Sixteen linear decomposition methods for EEG source separation were compared according to different criteria. The criteria were mutual information reduction between the source activities and physiological plausibility. The latter was tested by estimating the dipolarity of the source topographic maps, i.e., the accuracy of approximating the map by potential distribution from a single current dipole, as well as by the specificity of the source activity for different motor imagery tasks. The decomposition methods were also compared according to the number of shared components found. The results indicate that most of the dipolar components are found by the Independent Component Analysis Methods AMICA and PWCICA, which also provided the highest information reduction. These two methods also found the most task-specific EEG patterns of the blind source separation algorithms used. They are outperformed only by non-blind Common Spatial Pattern methods in terms of pattern specificity. The components found by all of the methods were clustered using the Attractor Neural Network with Increasing Activity. The results of the cluster analysis revealed the most frequent patterns of electrical activity occurring in the experiments. The patterns reflect blinking, eye movements, sensorimotor rhythm suppression during the motor imagery, and activations in the precuneus, supplementary motor area, and premotor areas of both hemispheres. Overall, multi-method decomposition with subsequent clustering and task-specificity estimation is a viable and informative procedure for processing the recordings of electrophysiological experiments.

The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response

BackgroundStroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The “Promotoer” study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements.MethodsThis longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures.DiscussionWe expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice.Trial registrationName of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer).Trial registration number: NCT04353297; registration date on the ClinicalTrial.gov platform: April, 15/2020.

How Much Do Strategy Reports Tell About the Outcomes of Neurofeedback Training? A Study on the Voluntary Up-Regulation of the Sensorimotor Rhythm.

The core learning mechanisms of neurofeedback (NF) training are associative, implicit, and, consequently, largely impervious to consciousness. Many other aspects of training that determine training outcomes, however, are accessible to conscious processing. The outcomes of sensorimotor rhythm (SMR) up-regulation training are related to the strategies reported by participants. The classification methods of individual strategies employed hitherto were possibly under influence of the idiosyncratic interpretation of the rater. To measure and possibly overcome this limitation, we employed independent raters to analyze strategies reported during SMR up-regulation training. Sixty-two healthy young participants took part in a single session of SMR up-regulation training. After completing six blocks of training, in which they received either simple visual feedback or a gamified version thereof, participants were required to report the strategies employed. Their individual learning outcomes were computed as well. Results point out that individual strategies as well as NF learning outcomes were not particularly sensitive to the presence of gamified elements in training the SMR up-regulation. A high degree of consistency across independent raters classifying strategy reports was observed. Some strategies were more typical of responders while other ones were more common among non-responders. In summary, we demonstrate a more objective and transparent way to analyze individual mental strategies to shed more light on the differences between NF responders and non-responders.

Reduce brain computer interface inefficiency by combining sensory motor rhythm and movement-related cortical potential features

Objective. Brain Computer Interface (BCI) inefficiency indicates that there would be 10% to 50% of users are unable to operate Motor-Imagery-based BCI systems. Importantly, the almost all previous studieds on BCI inefficiency were based on tests of Sensory Motor Rhythm (SMR) feature. In this work, we assessed the occurrence of BCI inefficiency with SMR and Movement-Related Cortical Potential (MRCP) features. Approach. A pool of datasets of resting state and movements related EEG signals was recorded with 93 subjects during 2 sessions in separated days. Two methods, Common Spatial Pattern (CSP) and template matching, were used for SMR and MRCP feature extraction, and a winner-take-all strategy was applied to assess pattern recognition with posterior probabilities from Linear Discriminant Analysis to combine SMR and MRCP features. Main results. The results showed that the two types of features showed high complementarity, in line with their weak intercorrelation. In the subject group with poor accuracies (< 70%) by SMR feature in the two-class problem (right foot vs. right hand), the combination of SMR and MRCP features improved the averaged accuracy from 62% to 79%. Importantly, accuracies obtained by feature combination exceeded the inefficiency threshold. Significance. The feature combination of SMR and MRCP is not new in BCI decoding, but the large scale and repeatable study on BCI inefficiency assessment by using SMR and MRCP features is novel. MRCP feature provides the similar classification accuracies on the two subject groups with poor (< 70%) and good (> 90%) accuracies by SMR feature. These results suggest that the combination of SMR and MRCP features may be a practical approach to reduce BCI inefficiency. While, ‘BCI inefficiency’ might be more aptly called ‘SMR inefficiency’ after this study.

A Comparison of Non-negative Tucker Decomposition and Parallel Factor Analysis for Identification and Measurement of Human EEG Rhythms

Abstract Analysis of changes in the brain neural electrical activity measured by the electroencephalogram (EEG) plays a crucial role in the area of brain disorder diagnostics. The elementary latent sources of the brain neural activity can be extracted by a tensor decomposition of continuously recorded multichannel EEG. Parallel factor analysis (PARAFAC) is a powerful approach for this purpose. However, the assumption of the same number of factors in each dimension of the PARAFAC model may be restrictive when applied to EEG data. In this article we discuss the potential benefits of an alternative tensor decomposition method – the Tucker model. We analyze situations, where in comparison to the PARAFAC solution, the Tucker model provides a more parsimonious representation of the EEG data decomposition. We show that this more parsimonious representation of EEG is achieved without reducing the ability to explain variance. We analyze EEG records of two patients after ischemic stroke and we focus on the extraction of specific sensorimotor oscillatory sources associated with motor imagery during neurorehabilitation training. Both models provided consistent results. The advantage of the Tucker model was a compact structure with only two spatial signatures reflecting the expected lateralized activation of the detected subject-specific sensorimotor rhythms.

In Quest of Pathognomonic/Endophenotypic Markers of Attention Deficit Hyperactivity Disorder (ADHD): Potential of EEG-Based Frequency Analysis and ERPs to Better Detect, Prevent and Manage ADHD.

Attention deficit hyperactivity disorder (ADHD) is a chronic heritable developmental delay psychiatric disorder requiring chronic management, characterized by inattention, hyperactivity, hyperkinectivity and impulsivity. Subjective clinical evaluation still remains crucial in its diagnosis. Discussed are two key aspects in the “characterizing ADHD” and on the quest for objective “pathognomonic/endophenotypic diagnostic markers of ADHD”. The first aspect briefly revolves around issues related to identification of pathognomonic/endophenotypic diagnostic markers in ADHD. Issues discussed include changes in ADHD definition, remission/persistence and overlapping-symptoms cum shared-heritability with its co-morbid cross-border mental disorders. The second aspect discussed is neurobiological and EEG-based studies on ADHD. Given the neurobiological and temporal aspects of ADHD symptoms the electroencephalograph (EEG) like NeuralScan by Medeia appears as an appropriate tool. The EEGs appropriateness is further enhanced when coupled with suitable behavior/cognitive/motor/psychological tasks/paradigms yielding EEG-based markers like event-related-potential (ERPs like P3 amplitudes and latency), reaction time variability (RTV), Theta:Beta ratio (TBR) and sensorimotor rhythm (SMR). At present, these markers could potentially help in the neurobiological characterization of ADHD and either help in identifying or lay the groundwork for identifying pathognomonic and/or endophenotypic EEG-based markers enabling its diagnosis, treatment and management.

Neurofeedback en fibromialgia para el tratamiento de la depresión y la ansiedad.

Este trabajo versa sobre neurofeedback en pacientes con fibromialgia. Este síndrome aglutina una gran cantidad de síntomas diversos, que abarcan desde el dolor crónico, fatiga y cansancio crónico, problemas atencionales, de memoria y de sueño. A pesar de que es un síndrome idiopático múltiples estudios apuntan a que su origen está relacionado con el Síndrome de Sensibilización Central (SSC). Como intervención realizamos un entrenamiento mediante neurofeedback cuyo propósito es mejorar las variables ansiedad y depresión en fibromialgia. Utilizamos un protocolo estandarizado de ritmos sensoriomotores (SMR) ya que el entrenamiento de estas ondas repercute en el sistema dopaminérgico que a su vez está relacionado con la facilitación de las emociones positivas. Los resultados muestran que el neurofeedback mejora los trastornos de depresión y ansiedad en fibromialgia.

On the (in)efficacy of motor imagery training without feedback and event-related desynchronizations considerations

Motor imagery (MI) constitutes a recurrent strategy for signals generation in brain-computer interfaces (BCIs) - systems that aim to control external devices by directly associating brain responses to distinct commands. Although great improvement has been achieved in MI-BCIs performance over recent years, they still suffer from inter- and intra-subject variability issues. As an attempt to cope with this, some studies have suggested that MI training should aid users to appropriately modulate their response for BCI usage: generally, this training is performed based on the sensorimotor rhythms’ modulation over the primary sensorimotor cortex (PMC), with the signal being feedbacked to the user. Nonetheless, recent studies have revisited the actual involvement of the PMC into MI, and little to no attention has been devoted to understanding the participation of other cortical areas into training protocols. Therefore, in this work, our aim was to analyze the response induced by hands MI of 10 healthy subjects in the form of event-related desynchronizations (ERDs) and to assess whether features from beyond the PMC might be useful for hands MI classification. We investigated how this response occurs for distinct frequency intervals between 7–30 Hz, and ex0plored changes in their evocation pattern across 12 MI training sessions without feedback. Overall, we found that ERD patterns occur differently for the frequencies encompassed by the μ and β bands, with its evocation being favored for the first band. Over time, the no-feedback approach was inefficient to aid in enhancing ERD evocation (EO). Moreover, to some extent, EO tends to decrease over blocks within a given run, and runs within an MI session, but remains stable within an MI block. We also found that the C3/C4 pair is not necessarily optimal for data classification, and both spectral and spatial subjects’ specificities should be considered when designing training protocols.

Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting

Event-related desynchronization and synchronization (ERD/S) and movement-related cortical potential (MRCP) play an important role in brain-computer interfaces (BCI) for lower limb rehabilitation, particularly in standing and sitting. However, little is known about the differences in the cortical activation between standing and sitting, especially how the brain's intention modulates the pre-movement sensorimotor rhythm as they do for switching movements. In this study, we aim to investigate the decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for the actions of standing and sitting. We developed a behavioral task in which participants were instructed to perform both AO and MI/ME in regard to the transitioning actions of sit-to-stand and stand-to-sit. Our results demonstrated that the ERD was prominent during AO, whereas ERS was typical during MI at the alpha band across the sensorimotor area. A combination of the filter bank common spatial pattern (FBCSP) and support vector machine (SVM) for classification was used for both offline and classifier testing analyses. The offline analysis indicated the classification of AO and MI providing the highest mean accuracy at 82.73$\pm$2.54\% in the stand-to-sit transition. By applying the classifier testing analysis, we demonstrated the higher performance of decoding neural intentions from the MI paradigm in comparison to the ME paradigm. These observations led us to the promising aspect of using our developed tasks based on the integration of both AO and MI to build future exoskeleton-based rehabilitation systems.

BCI-based sensorimotor rhythm training can affect individuated finger movements

ABSTRACT Brain-computer interface (BCI) technology can restore communication and control to people who are severely paralyzed. BCI technology might also be able to enhance rehabilitation of motor function. We have previously shown that pre-movement sensorimotor rhythm (SMR) amplitude affects reaction time and performance on a joystick-based cursor movement task. The present study explores in adults without motor impairment the possibility that pre-movement SMR amplitude affects performance of individuated finger movements. In Phase 1, 8 individuals performed a finger flexion task that was monitored by an exoskeleton. During a 1-sec preparatory period, two colored targets on a video monitor cued flexion of the index finger, middle finger, both fingers, or neither finger; sudden color change then triggered the movement (or non-movement). SMR features (i.e. EEG amplitudes in specific frequency bands at specific scalp locations) in the pre-movement EEG that correlated with movement versus no movement were identified. In Phase 2, the participants learned to increase or decrease these SMR features to control a two-target BCI task. Finally, in Phase 3, they were asked to increase or decrease the SMR features to initiate the finger flexion task of Phase 1 and the impact on finger flexion performance was assessed. After BCI training, pre-movement SMR feature amplitude affected performance in a subset of individuals: lower amplitude was associated with shorter movement onset. In a subset of individuals, the beneficial effect on performance of lower SMR amplitude was greater when both fingers were flexed than when one was flexed and the other remained extended; thus, the impact of SMR amplitude modulation depended on the specificity of the subsequent motor task. These results indicate that BCI-based training of SMR activity in the pre-movement preparatory period can affect finger movements in a subset of individuals. They encourage studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful hand function.

Реактивность μ-ритма ЭЭГ у детей при имитации движений визуальных образов биологического и небиологического происхождения

The development of brain-computer interfaces based on the use of EEG sensorimotor rhythms reactivity parameters and designed for the rehabilitation of people (including children) with impaired motor functions is currently relevant. The study was aimed to analyse the EEG μ-rhythm in the individual frequency range in children during imitation of biological and non-biological motion. EEG was recorded at frontal, central and parietal cortical regions in 136 normally developing right-handed children aged 4–15, at rest and during the execution and imitation of movements using the computer mouse. When the children moved the computer mouse on their own (F1, 132 = 31.17; p &lt; 0.001) and executed the concentric moving of the coloured circle (F1, 132 = 90.34; p &lt; 0.001), the μ-rhythm desynchronization developed in the frontal, central and parietal neocortical regions. The μ-rhythm synchronization was detected during the non-biologocal motion imitation (F1, 132 = 12.65; p &lt; 0.001), compared to the task on the autonomous movement execution. The μ-rhythm desynchronization was observed during the biologocal motion imitation in relation to autonomous movement execution (F1, 132 = 9.58; p = 0.002). The described effects had their own features in the groups of children aged 4–6, 7–9, 10–12 and 13–15. The study results demonstrate the desirability of taking into account the μ-rhythm reactivity age-related features and the visual stimuli nature when developing software for the brain-computer interfaces.

Efficacy, Trainability, and Neuroplasticity of SMR vs. Alpha Rhythm Shooting Performance Neurofeedback Training.

Previous literature on shooting performance neurofeedback training (SP-NFT) to enhance performance usually focused on changes in behavioral indicators, but research on the physiological features of SP-NFT is lacking. To explore the effects of SP-NFT on trainability and neuroplasticity, we conducted a study in which 45 healthy participants were randomly divided into three groups: based on sensory-motor rhythm of C3, Cz and C4 (SMR group), based on alpha rhythm of T3 and T4 (Alpha group), and no NFT (control group). The training was performed for six sessions for 3 weeks. Before and after the SP-NFT, we evaluated changes in shooting performance and resting electroencephalography (EEG) frequency power, participant’s subjective task appraisal, neurofeedback trainability score, and EEG feature. Statistical analysis showed that the shooting performance of the participants in the SMR group improved significantly, the participants in the Alpha group decreased, and that of participants in the control group have no change. Meanwhile, the resting EEG power features of the two NFT groups changed specifically after training. The training process data showed that the training difficulty was significantly lower in the SMR group than in the Alpha group. Both NFT groups could improve the neurofeedback trainability scores and change the feedback features by means of their mind strategy. These results may provide evidence of trainability and neuroplasticity for SP-NFT, suggesting that the SP-NFT is effective in brain regulation and thus provide a potential method to improve shooting performance.

Self-Regulation of SMR Power Led to an Enhancement of Functional Connectivity of Somatomotor Cortices in Fibromyalgia Patients.

Neuroimaging studies have demonstrated that altered activity in somatosensory and motor cortices play a key role in pain chronification. Neurofeedback training of sensorimotor rhythm (SMR) is a tool which allow individuals to self-modulate their brain activity and to produce significant changes over somatomotor brain areas. Several studies have further shown that neurofeedback training may reduce pain and other pain-related symptoms in chronic pain patients. The goal of the present study was to analyze changes in SMR power and brain functional connectivity of the somatosensory and motor cortices elicited by neurofeedback task designed to both synchronize and desynchronize the SMR power over motor and somatosensory areas in fibromyalgia patients. Seventeen patients were randomly assigned to the SMR training (n = 9) or to a sham protocol (n = 8). All participants were trained during 6 sessions, and fMRI and EEG power elicited by synchronization and desynchronization trials were analyzed. In the SMR training group, four patients achieved the objective of SMR modulation in more than 70% of the trials from the second training session (good responders), while five patients performed the task at the chance level (bad responders). Good responders to the neurofeedback training significantly reduced pain and increased both SMR power modulation and functional connectivity of motor and somatosensory related areas during the last neurofeedback training session, whereas no changes in brain activity or pain were observed in bad responders or participants in the sham group. In addition, we observed that good responders were characterized by reduced impact of fibromyalgia and pain symptoms, as well as by increased levels of health-related quality of life during the pre-training sessions. In summary, the present study revealed that neurofeedback training of SMR elicited significant brain changes in somatomotor areas leading to a significant reduction of pain in fibromyalgia patients. In this sense, our research provide evidence that neurofeedback training is a promising tool for a better understanding of brain mechanisms involved in pain chronification.

Train Your Brain? Can We Really Selectively Train Specific EEG Frequencies With Neurofeedback Training.

Neurofeedback (NFB) is an operant conditioning procedure whereby an individual learns to self-regulate the electrical activity of his/her brain. Initially developed as a treatment intervention for pathologies with underlying EEG dysfunctions, NFB is also used as a training tool to enhance specific cognitive states required in high-performance situations. The original idea behind the NFB training effect is that the changes should only be circumscribed to the trained EEG frequencies. The EEG frequencies which are not used as feedback frequencies should be independent and not affected by the neurofeedback training. Despite the success of sensorimotor rhythm NFB training in cognitive performance enhancement, it remains unclear whether all participants can intentionally modify the power densities of specifically selected electroencephalographic (EEG) frequencies. In the present study, participants were randomly assigned to either a control heart rate variability (HRV) biofeedback (HRV) training group or a combination of HRV biofeedback and neurofeedback (HRV/NFB) training group. This randomized mixed design experiment consisted of two introductory theoretical lessons and a training period of 6 weeks. We investigated the evolution of the different EEG frequency bands of our two experimental groups across and within session. All the participants exhibited EEG changes across and within session. However, within the HRV/NFB training group, untrained EEG frequencies have been significantly modified, unlike some of the trained frequencies. Moreover, EEG activity was modified in both the HRV group and the HRV/NFB groups. Hence, the EEG changes were not only circumscribed to the trained frequency bands or to the training modality.

Intraoperative real-time stress in degenerative lumbar spine surgery: simultaneous analysis of electroencephalography signals and heart rate variability: a pilot study

BACKGROUND CONTEXTInterest in intraoperative stress has increased due to its potentially detrimental impact on surgical performance and burnout among spine surgeons. PURPOSEThe purpose of this study was to analyze intraoperative stress in real time in terms of electroencephalography signals and heart rate variability using a wearable device during spine surgery. STUDY DESIGNProspective observational study. PATIENT SAMPLEFive orthopedic spine surgeons with experience ranging from 1 to 30 years were included. OUTCOME MEASURESThe outcome measures included stress levels among the spine surgeons and differences in stress parameters between novice and expert surgeons and between assistants and operators. METHODSFrom June 2018 to November 2018, 179 consecutive records of intraoperative stress measures, including intraoperative electroencephalography signals and heart rate variability, comprising beats per minute (BPM) and low frequency/high frequency ratio, for the orthopedic spine surgeons were prospectively gathered, compared, and analyzed. RESULTSAmong all measures, sensory-motor rhythm (SMR) waves, gamma waves, and BPM differed significantly during surgery (analysis of variance; p=.040, .013, .002, respectively). Surgery duration and intraoperative bleeding were positively correlated with stress parameters, including gamma waves and tension. For operators, surgeon experience was negatively correlated with concentration, tension, and SMR, gamma, M-beta, and H-beta waves (Pearson correlation, p<.05). However, for assistants, surgeon experience was positively correlated with concentration, tension, BPM, and SMR, M-beta, H-beta, and gamma waves. Bleeding amounts were correlated positively with gamma waves and tension for both operators and assistants (Pearson correlation, p<.05). Stress among operators was higher than that among assistants in terms of low frequency/high frequency ratio. CONCLUSIONSOperators and surgeons with low experience exhibited higher stress levels during surgery, which should be addressed when scheduling elective surgery to ensure optimal conditions among spine surgeons.

The effects of handedness on sensorimotor rhythm desynchronization and motor-imagery BCI control

Brain–computer interfaces (BCIs) allow control of various applications or external devices solely by brain activity, e.g., measured by electroencephalography during motor imagery. Many users are unable to modulate their brain activity sufficiently in order to control a BCI. Most of the studies have been focusing on improving the accuracy of BCI control through advances in signal processing and BCI protocol modification. However, some research suggests that motor skills and physiological factors may affect BCI performance as well. Previous studies have indicated that there is differential lateralization of hand movements’ neural representation in right- and left-handed individuals. However, the effects of handedness on sensorimotor rhythm (SMR) distribution and BCI control have not been investigated in detail yet. Our study aims to fill this gap, by comparing the SMR patterns during motor imagery and real-feedback BCI control in right- (N = 20) and left-handers (N = 20). The results of our study show that the lateralization of SMR during a motor imagery task differs according to handedness. Left-handers present lower accuracy during BCI performance (single session) and weaker SMR suppression in the alpha band (8–13 Hz) during mental simulation of left-hand movements. Consequently, to improve BCI control, the user’s training should take into account individual differences in hand dominance.

Relieving peripheral neuropathic pain by increasing the power-ratio of low-β over high-β activities in the central cortical region with EEG-based neurofeedback: Study protocol for a controlled pilot trial (SMRPain study)

Chronic neuropathic pain associated with peripheral neuropathies cannot be attributed solely to lesions of peripheral sensory axons and likely involves alteration in the processing of nociceptive information in the central nervous system in most patients. Few data are available regarding EEG correlates of chronic neuropathic pain. The fact is that effective cortical neuromodulation strategies to treat neuropathic pain target the precentral cortical region, i.e. a cortical area corresponding to the motor cortex. It is not known how these strategies might modulate brain rhythms in the central cortical region, but it can be speculated that sensorimotor rhythms (SMRs) are modified. Another potent way of modulating cortical rhythms is to use EEG-based neurofeedback (NFB). Rare studies previously aimed at relieving neuropathic pain using EEG-NFB training. The objective of this single-centre, single-blinded, randomized controlled pilot study is to assess the value of an EEG-NFB procedure to relieve chronic neuropathic pain in patients with painful peripheral neuropathy. A series of 32 patients will be randomly assigned to one of the two following EEG-NFB protocols, aimed at increasing either the low-β(SMR)/high-β ratio (n=16) or the α(μ)/θ ratio (n=16) at central (rolandic) cortical level. Various clinical outcome measures will be collected before and one week after 12 EEG-NFB sessions performed over 4weeks. Resting-state EEG will also be recorded immediately before and after each NFB session. The primary endpoint will be the change in the impact of pain on patient's daily functioning, as assessed on the Interference Scale of the short form of the Brief Pain Inventory. The value of EEG-NFB procedures to relieve neuropathic pain has been rarely studied. This pilot study will attempt to show the value of endogenous modulation of brain rhythms in the central (rolandic) region in the frequency band corresponding to the frequency of stimulation currently used by therapeutic motor cortex stimulation. In the case of significant clinical benefit produced by the low-β(SMR)/high-β ratio increasing strategy, this work could pave the way for using EEG-NFB training within the armamentarium of neuropathic pain therapy.

Understanding and Controlling Cortical Activity for Superior Performance

Previous studies have revealed that several cortical signatures are associated with superior motor performance in sports, particularly precision sports. This review examined the strength of the evidence from these studies so that a clear conclusion could be drawn and a concrete direction for future efforts revealed. A total of 26 articles assessing the relationship between cortical activity and precision motor performance were extracted from databases. This review concluded that among the electroencephalographic components examined, only sensorimotor rhythm demonstrated a consistent and causal relationship with superior precision motor performance, whereas findings related to the left temporal alpha and frontal theta and alpha rhythms were not consistent and lacked the evidence needed to draw a causal inference for a role in superior precision motor performance. Future studies would benefit from methodological improvements including larger sample sizes, narrower skill-gap comparisons, evidenced-based and refined neurofeedback-training protocols, and consideration of ecological validity.

The Effect of an Integrated Neurofeedback and Biofeedback Training Intervention on Ice Hockey Shooting Performance.

The purpose of this study was to investigate the effectiveness of a sensorimotor rhythm (SMR) neurofeedback training (NFT) and biofeedback training (BFT) intervention on ice hockey shooting performance. Specifically, the purpose was to examine (a)whether an NFT/BFT program could improve ice hockey shooting performance, (b)whether the implementation of an SMR-NFT intervention leads to neurological adaptations during performance, and (c)whether such neurological changes account for improvement in shooting performance. Using a longitudinal stratified random control design, results demonstrated that while both SMR-NFT/BFT and control groups improved performance, the rate of improvement for the SMR-NFT/BFT group was significantly higher than the control. Participants in the SMR-NFT/BFT group demonstrated the ability to significantly increase SMR power from pre- to postintervention in the lab. However, no significant changes in SMR power were found during shooting performance. This result may be suggestive of differing cortical activity present during motor-skill preparation.