Brain oscillatory activity during motor imagery in EEG-fMRI coregistration

Handedness effects on imagery of dominant- versus non-dominant-hand movements: An electroencephalographic investigation

Mental representations of our bodies are thought to influence how we interact with our surroundings. We can examine these mental representations through motor imagery, the imagination of movement using scalp EEG recordings. The visual modality of motor imagery emphasises 'seeing' the imagined movement and is associated with increased activity in the alpha rhythm (8-14 Hz) measured over the occipital regions. The kinaesthetic modality emphasises 'feeling' the movement and is associated with decreased activity in the mu rhythm (8-14 Hz) measured over the sensorimotor cortices. These two modalities can be engaged in isolation or together. We recorded EEG activity while 37 participants (17 left-hand dominant) completed an objective hand motor imagery task. Left-handers exhibited significant activity differences between occipital and motor regions only during imagery of right-hand (non-dominant-hand) movements. This difference was primarily driven by less oscillatory activity in the mu rhythm, which may reflect a shift in imagery strategy wherein participants placed more effort into generating the kinaesthetic sensations of non-dominant-hand imagery. Spatial features of 8-14 Hz activity generated from principal component analysis (PCA) provide further support for a strategy shift. Right-handers also exhibited significant differences between alpha and mu activity during imagery of non-dominant movements. However, this difference was not primarily driven by either rhythm, and no differences were observed in the group's PCA results. Together, these findings indicate that individuals imagine movement differently when it involves their dominant versus non-dominant hand, and left-handers may be more flexible in their motor imagery strategies.

Functional Connectivity and Feature Fusion Enhance Multiclass Motor-Imagery Brain-Computer Interface Performance

(1) Background: in the field of motor-imagery brain-computer interfaces (MI-BCIs), obtaining discriminative features among multiple MI tasks poses a significant challenge. Typically, features are extracted from single electroencephalography (EEG) channels, neglecting their interconnections, which leads to limited results. To address this limitation, there has been growing interest in leveraging functional brain connectivity (FC) as a feature in MI-BCIs. However, the high inter- and intra-subject variability has so far limited its effectiveness in this domain. (2) Methods: we propose a novel signal processing framework that addresses this challenge. We extracted translation-invariant features (TIFs) obtained from a scattering convolution network (SCN) and brain connectivity features (BCFs). Through a feature fusion approach, we combined features extracted from selected channels and functional connectivity features, capitalizing on the strength of each component. Moreover, we employed a multiclass support vector machine (SVM) model to classify the extracted features. (3) Results: using a public dataset (IIa of the BCI Competition IV), we demonstrated that the feature fusion approach outperformed existing state-of-the-art methods. Notably, we found that the best results were achieved by merging TIFs with BCFs, rather than considering TIFs alone. (4) Conclusions: our proposed framework could be the key for improving the performance of a multiclass MI-BCI system.

Simultaneous real-time EEG-fMRI neurofeedback: A systematic review

Neurofeedback (NF) is a biofeedback technique that teaches individuals self-control of brain functions by measuring brain activations and providing an online feedback signal to modify emotional, cognitive, and behavioral functions. NF approaches typically rely on a single modality, such as electroencephalography (EEG-NF) or a brain imaging technique, such as functional magnetic resonance imaging (fMRI-NF). The introduction of simultaneous EEG-fMRI tools has opened up the possibility of combining the high temporal resolution of EEG with the high spatial resolution of fMRI, thereby increasing the accuracy of NF. However, only a few studies have actively combined both techniques. In this study, we conducted a systematic review of EEG-fMRI-NF studies (N = 17) to identify the potential and effectiveness of this non-invasive treatment for neurological conditions. The systematic review revealed a lack of homogeneity among the studies, including sample sizes, acquisition methods in terms of simultaneity of the two procedures (unimodal EEG-NF and fMRI-NF), therapeutic targets field, and the number of sessions. Indeed, because most studies are based on a single session of NF, it is difficult to draw any conclusions regarding the therapeutic efficacy of NF. Therefore, further research is needed to fully understand non-clinical and clinical potential of EEG-fMRI-NF.

Contribution of the sensorimotor beta oscillations and the cortico-basal ganglia-thalamic circuitry during value-based decision making: A simultaneous EEG-fMRI investigation

In decision neuroscience, the motor system has primarily been considered to be involved in executing choice actions. However, a competing perspective suggests its engagement in the evaluation of options, traditionally considered to be performed by the brain's valuation system. Here, we investigate the role of the motor system in value-based decision making by determining the neural circuitries associated with the sensorimotor beta oscillations previously identified to encode decision options. In a simultaneous EEG-fMRI study, participants evaluated reward and risk associated with a forthcoming action. A significant sensorimotor beta desynchronization was identified prior to and independent of response. The level of beta desynchronization showed evidence of encoding the reward levels. This beta desynchronization covaried, on a trial-by-trial level, with BOLD activity in the cortico-basal ganglia-thalamic circuitry. In contrast, there was only a weak covariation within the valuation network, despite significant modulation of its BOLD activity by reward levels. These results suggest that the way in which decision variables are processed differs in the valuation network and in the cortico-basal ganglia-thalamic circuitry. We propose that sensorimotor beta oscillations indicate incentive motivational drive towards a choice action computed from the decision variables even prior to making a response, and it arises from the cortico-basal ganglia-thalamic circuitry.

Mu oscillations and motor imagery performance: A reflection of intra-individual success, not inter-individual ability

Mu oscillations (8-13 Hz), recorded over the human motor cortex, have been shown to consistently suppress during both the imagination and performance of movements; however, its functional significance in the imagery process is currently unclear. Here we examined human electroencephalographic (EEG) oscillations in the context of motor imagery performance as measured by imagery success within participants and imagery ability between participants. We recorded continuous EEG activity while participants performed the Test of Ability in Movement Imagery (TAMI), an objective test of motor imagery task. Results demonstrated that mu oscillatory activity significantly decreased during successful as compared to unsuccessful imagery trials. However, the extent of reduction in mu oscillations did not correlate with overall imagery ability as measured by the total TAMI score. These findings provide further support for the involvement of mu oscillations in indexing motor imagery performance and suggest that mu oscillations may reflect important processes related to imagery accuracy, processes likely related to those underlying overt motor production and motor understanding.

Neurophysiological evidence of motor imagery training in Parkinson’s disease: a case series study

Background:

Motor imagery (MI) has become an increasingly popular rehabilitation tool for individuals with motor impairments. However, it has been proposed that individuals with Parkinson’s Disease (PKD) may not benefit from MI due to impairments in motor learning.

Objective:

This case series study investigated the effects of a 4-week MI training protocol on MI ability in three male individuals with PKD, with an emphasis on examining changes in brain responses.

Methods:

Training was completed primarily at home, via audio recordings, and emphasized the imagination of functional tasks. MI ability was assessed pre and post-training using subjective and objective imagery questionnaires, alongside an electroencephalographic (EEG) recording of a functional MI task. EEG analysis focused on the mu rhythm, as it has been proposed that suppression in the mu rhythm may reflect MI success and motor learning. Previous research has indicated that mu suppression is impaired in individuals with PKD, and may contribute to the disease’s associated deficits in motor learning.

Results:

Following training, all three participants improved in MI accuracy, but reported no notable improvements in MI vividness. Greater suppression in the mu rhythm was also exhibited by all three participants post-training.

Conclusion:

These results suggest the participants learned from the training protocol and that individuals with PKD are responsive to MI training. Further research on a larger scale is needed to verify the findings and determine if this learning translates to improvements in motor function.

Neurophysiological adaptations to spaceflight and simulated microgravity

Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well.

On the Better Performance of Pianists with Motor Imagery-Based Brain-Computer Interface Systems

Motor imagery (MI)-based brain-computer interface (BCI) systems detect electrical brain activity patterns through electroencephalogram (EEG) signals to forecast user intention while performing movement imagination tasks. As the microscopic details of individuals' brains are directly shaped by their rich experiences, musicians can develop certain neurological characteristics, such as improved brain plasticity, following extensive musical training. Specifically, the advanced bimanual motor coordination that pianists exhibit means that they may interact more effectively with BCI systems than their non-musically trained counterparts; this could lead to personalized BCI strategies according to the users' previously detected skills. This work assessed the performance of pianists as they interacted with an MI-based BCI system and compared it with that of a control group. The Common Spatial Patterns (CSP) and Linear Discriminant Analysis (LDA) machine learning algorithms were applied to the EEG signals for feature extraction and classification, respectively. The results revealed that the pianists achieved a higher level of BCI control by means of MI during the final trial (74.69%) compared to the control group (63.13%). The outcome indicates that musical training could enhance the performance of individuals using BCI systems.

The Effect of Expertise on Kinesthetic Motor Imagery of Complex Actions

The ability to mentally simulate an action by recalling the body sensations relative to the real execution is referred to as kinesthetic motor imagery (MI). Frontal and parietal motor-related brain regions are generally engaged during MI. The present study aimed to investigate the time course and neural correlates of complex action imagery and possible effects of expertise on the underlying action representation processes. Professional ballet dancers and controls were presented with effortful and effortless ballet steps and instructed to mentally reproduce each movement during EEG recording. Time-locked MI was associated with an Anterior Negativity (AN) component (400-550 ms) that was larger in dancers relative to controls. The AN was differentially modulated by the motor content (effort) as a function of ballet expertise. It was more negative in response to effortful (than effortless) movements in control participants only. This effect also had a frontal distribution in controls and a centro-parietal distribution in dancers, as shown by the topographic maps of the scalp voltage. The source reconstruction (swLORETA) of the recorded potentials in the AN time-window showed enhanced engagement of prefrontal regions in controls (BA 10/47) relative to dancers, and occipitotemporal (BA 20) and bilateral sensorimotor areas in dancers (BA6/40) compared with controls. This evidence seems to suggest that kinesthetic MI of complex action relied on visuomotor simulation processes in participants with acquired dance expertise. Simultaneously, increased cognitive demands occurred in participants lacking in motor knowledge with the specific action. Hence, professional dance training may lead to refined action representation processes.

Influence of focal vibration over Achilles tendon on the activation of sensorimotor cortex in healthy subjects and subacute stroke patients

The modulation of cerebral activity could induce plastic changes in the cerebral cortex and contribute to motor rehabilitation. Focal vibration over lower-extremity muscles has therapeutic effects on the impaired motor function for stroke patients, but the modulatory effects of focal vibration on brain activity are less known. To explore this problem, this experiment was designed and conducted, in which focal vibration (75 Hz) was applied over the right Achilles tendon of 14 healthy subjects and the affected Achilles tendon of seven subacute stroke patients. Electroencephalography was recorded in the following phases: resting-state and three focal vibration sessions. Electroencephalographical analysis showed a significantly desynchronized power of contralateral primary sensorimotor cortex (S1-M1) in beta1 band (13-18 Hz) following all focal vibration sessions occurred in healthy subjects compared to resting-state, whereas a significantly desynchronized power of bilateral S1-M1 in the beta1 and beta2 band (18-21 Hz) was observed in stroke patients compared to resting-state. Besides, event-related power desynchronization of bilateral S1-M1 in stroke patients was significantly lower than healthy subjects in the beta2 and beta3 band (21-30 Hz) during focal vibration sessions. These results demonstrated that focal vibration over Achilles tendon could activate bilateral S1-M1 in stroke patients, which was different in healthy subjects. These indications contribute to a better understanding of the underlying mechanism of focal vibration on stroke rehabilitation.

Study of the activation in sensorimotor cortex and topological properties of functional brain network following focal vibration on healthy subjects and subacute stroke patients: An EEG study

Modulation on cerebral cortex and cerebral networks can induce reorganization of the brain, which contributes to rehabilitation. Previous studies have proved that focal vibration (FV) on limb muscles can modulate the activities of sensorimotor cortex in healthy subjects (HS). The objective of this paper is to study the modulatory effects of FV on the sensorimotor cortex and cerebral network in HS and subacute stroke patients (SP). An experiment was designed and conducted, during which FV of 75 Hz was applied over biceps muscle of right limb of 10 HS and 10 SP with right hemiplegia. Electroencephalography (EEG) was recorded in the following phases: before FV, control condition and three sessions of FV. EEG analysis showed a significant decrease in motor-related power desynchronization (MRPD) of contralesional primary sensorimotor cortex (contralesional S1-M1) in the beta2 band (18-21 Hz) for SP during FV sessions, as well as in MRPD of bilateral S1-M1 in the beta1 (13-18 Hz) and the beta2 band for HS. Moreover, MRPD of contralesional S1-M1 was significantly lower than MRPD of ipsilesional S1-M1 during FV. Besides, a significant increase of global efficiency (E) and decrease of characteristic path length (L) were identified in the beta1 band for SP, whereas a significant increase of L was identified for HS. The results indicated that FV could enhance the excitability of contralesional S1-M1 and alter topological properties of functional brain network for SP, which was different in HS. This indication can contribute to understanding the modulatory effects of FV on cerebral cortex and cerebral network.

Effects of Focal Vibration over Upper Limb Muscles on the Activation of Sensorimotor Cortex Network: An EEG Study

Studying the therapeutic effects of focal vibration (FV) in neurorehabilitation is the focus of current research. However, it is still not fully understood how FV on upper limb muscles affects the sensorimotor cortex in healthy subjects. To explore this problem, this experiment was designed and conducted, in which FV was applied to the muscle belly of biceps brachii in the left arm. During the experiment, electroencephalography (EEG) was recorded in the following three phases: before FV, during FV, and two minutes after FV. During FV, a significant lower relative power at C3 and C4 electrodes and a significant higher connection strength between five channel pairs (Cz-FC1, Cz-C3, Cz-CP6, C4-FC6, and FC6-CP2) in the alpha band were observed compared to those before FV. After FV, the relative power at C4 in the beta band showed a significant increase compared to its value before FV. The changes of the relative power at C4 in the alpha band had a negative correlation with the relative power of the beta band during FV and with that after FV. The results showed that FV on upper limb muscles could activate the bilateral primary somatosensory cortex and strengthen functional connectivity of the ipsilateral central area (FC1, C3, and Cz) and contralateral central area (CP2, Cz, C4, FC6, and CP6). These results contribute to understanding the effect of FV over upper limb muscles on the brain cortical network.

Sex differences in early sensorimotor processing for speech discrimination

Sensorimotor activity in speech perception tasks varies as a function of context, cognitive load, and cognitive ability. This study investigated listener sex as an additional variable. Raw EEG data were collected as 21 males and 21 females discriminated /ba/ and /da/ in quiet and noisy backgrounds. Independent component analyses of data from accurately discriminated trials identified sensorimotor mu components with characteristic alpha and beta peaks from 16 members of each sex. Time-frequency decompositions showed that in quiet discrimination, females displayed stronger early mu-alpha synchronization, whereas males showed stronger mu-beta desynchronization. Findings indicate that early attentional mechanisms for speech discrimination were characterized by sensorimotor inhibition in females and predictive sensorimotor activation in males. Both sexes showed stronger early sensorimotor inhibition in noisy discrimination conditions versus in quiet, suggesting sensory gating of the noise. However, the difference in neural activation between quiet and noisy conditions was greater in males than females. Though sex differences appear unrelated to behavioral accuracy, they suggest that males and females exhibit early sensorimotor processing for speech discrimination that is fundamentally different, yet similarly adaptable to adverse conditions. Findings have implications for understanding variability in neuroimaging data and the male prevalence in various neurodevelopmental disorders with inhibitory dysfunction.

Effects and Dose-Response Relationships of Motor Imagery Practice on Strength Development in Healthy Adult Populations: a Systematic Review and Meta-analysis

BACKGROUND

Motor imagery (MI), a mental simulation of a movement without overt muscle contraction, has been largely used to improve general motor tasks. However, the effects of MI practice on maximal voluntary strength (MVS) remain equivocal.

OBJECTIVES

The aims of this meta-analysis were to (1) estimate whether MI practice intervention can meaningfully improve MVS in healthy adults; (2) compare the effects of MI practice on MVS with its combination with physical practice (MI-C), and with physical practice (PP) training alone; and (3) investigate the dose-response relationships of MI practice.

DATA SOURCES AND STUDY ELIGIBILITY

Seven electronic databases were searched up to April 2017. Initially 717 studies were identified; however, after evaluation of the study characteristics, data from 13 articles involving 370 participants were extracted. The meta-analysis was completed on MVS as the primary parameter. In addition, parameters associated with training volume, training intensity, and time spent training were used to investigate dose-response relationships.

RESULTS

MI practice moderately improved MVS. When compared to conventional PP, effects were of small benefit in favour of PP. MI-C when compared to PP showed unclear effects. MI practice produced moderate effects in both upper and lower extremities on MVS. The cortical representation area of the involved muscles did not modify the effects. Meta-regression analysis revealed that (a) a training period of 4 weeks, (b) a frequency of three times per week, (c) two to three sets per single session, (d) 25 repetitions per single set, and (e) single session duration of 15 min were associated with enhanced improvements in muscle strength following MI practice. Similar dose-response relationships were observed following MI and PP.

CONCLUSIONS

The present meta-analysis demonstrates that compared to a no-exercise control group of healthy adults, MI practice increases MVS, but less than PP. These findings suggest that MI practice could be considered as a substitute or additional training tool to preserve muscle function when athletes are not exposed to maximal training intensities.

EEG Hyperconnectivity Study on Saxophone Quartet Playing in Ensemble

A professional quartet of saxophonists playing in ensemble provides a perfect scenario to study the eventual occurrence of synchronous oscillatory brain activity across subjects. Here, we applied hyperscanning methodologies for simultaneously recordings of electroencephalographic (EEG) signals from four professional saxophonists while they observ an audiovideo recording of their own previous musical performance. An ad-hoc musical composition was written for the study. At debriefing, the subjects were asked to answer two questionnaires to assess their empathy trait and the musical leadership. In order to estimate the hyperconnectivity of each musician we proposed a measure which combines phase synchronization index of brain oscillations and graph theory framework. The inter-connectivity level of each musician was statistically compared. Statistical results revealed a significant lower hyperconnectivity in the left Brodmann area 44 for the Soprano with respect to the other three members. Recent theories attributed this brain region (Broca's area) to music generation, empathy processes and communication. We hypothesize a relationship between brain-to-brain connectivity level and the musical role within the quartet.

Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm

BACKGROUND

Physical motor exercise aided by an electroencephalogram (EEG)-based brain-computer interface (BCI) is known to improve motor recovery in patients with stroke. In such a BCI paradigm, event-related desynchronization (ERD) in the alpha and beta bands extracted from EEG recorded over the primary sensorimotor area (SM1) is often used, since ERD has been suggested to be associated with an increase of corticospinal excitability. Recently, we demonstrated a novel online lock-in amplifier (LIA) algorithm to estimate the amplitude modulation of motor-related SM1 ERD. With this algorithm, the delay time, accuracy, and stability to estimate motor-related SM1 ERD were significantly improved compared with the conventional fast Fourier transformation (FFT) algorithm. These technical improvements to extract an ERD trace imply a potential advantage for a better trace of the excitatory status of the SM1 in a BCI context. Therefore, the aim of this study was to assess the precision of LIA-based ERD tracking for estimation of corticospinal excitability using a transcranial magnetic stimulation (TMS) paradigm.

METHODS

The motor evoked potentials (MEPs) induced by single-pulse TMS over the primary motor cortex depending on the magnitudes of SM1 ERD (i.e., 35% and 70%) extracted by the online LIA or FFT algorithm were monitored during a motor imagery task of wrist extension in 17 healthy participants. Then, the peak-to-peak amplitudes of MEPs and their variabilities were assessed to investigate the precision of the algorithms.

RESULTS

We found greater MEP amplitude evoked by single-pulse TMS triggered by motor imagery-related alpha SM1 ERD than at rest. This enhancement was associated with the magnitude of ERD in both FFT and LIA algorithms. Moreover, we found that the variabilities of peak-to-peak MEP amplitudes at 35% and 70% ERDs calculated by the novel online LIA algorithm were smaller than those extracted using the conventional FFT algorithm.

CONCLUSIONS

The present study demonstrated that the calculation of motor imagery-related SM1 ERDs using the novel online LIA algorithm led to a more precise estimation of corticospinal excitability than when the ordinary FFT-based algorithm was used.

Subjective Vividness of Kinesthetic Motor Imagery Is Associated With the Similarity in Magnitude of Sensorimotor Event-Related Desynchronization Between Motor Execution and Motor Imagery

In the field of psychology, it has been well established that there are two types of motor imagery such as kinesthetic motor imagery (KMI) and visual motor imagery (VMI), and the subjective evaluation for vividness of motor imagery each differs across individuals. This study aimed to examine how the motor imagery ability assessed by the psychological scores is associated with the physiological measure using electroencephalogram (EEG) sensorimotor rhythm during KMI task. First, 20 healthy young individuals evaluated subjectively how vividly they can perform each of KMI and VMI by using the Kinesthetic and Visual Imagery Questionnaire (KVIQ). We assessed their motor imagery abilities by summing each of KMI and VMI scores in KVIQ (KMI_total and VMI_total). Second, in physiological experiments, they repeated two strengths (10 and 40% of maximal effort) of isometric voluntary wrist-dorsiflexion. Right after each contraction, they also performed its KMI. The scalp EEGs over the sensorimotor cortex were recorded during the tasks. The EEG power is known to decrease in the alpha-and-beta band (7–35 Hz) from resting state to performing state of voluntary contraction (VC) or motor imagery. This phenomenon is referred to as event-related desynchronization (ERD). For each strength of the tasks, we calculated the maximal peak of ERD during VC, and that during its KMI, and measured the degree of similarity (ERD_sim) between them. The results showed significant negative correlations between KMI_total and ERD_sim for both strengths (p < 0.05) (i.e., the higher the KMI_total, the smaller the ERD_sim). These findings suggest that in healthy individuals with higher motor imagery ability from a first-person perspective, KMI efficiently engages the shared cortical circuits corresponding with motor execution, including the sensorimotor cortex, with high compliance.

Quantification of Upper Limb Motor Recovery and EEG Power Changes after Robot-Assisted Bilateral Arm Training in Chronic Stroke Patients: A Prospective Pilot Study

Background

Bilateral arm training (BAT) has shown promise in expediting progress toward upper limb recovery in chronic stroke patients, but its neural correlates are poorly understood.

Objective

To evaluate changes in upper limb function and EEG power after a robot-assisted BAT in chronic stroke patients.

Methods

In a within-subject design, seven right-handed chronic stroke patients with upper limb paresis received 21 sessions (3 days/week) of the robot-assisted BAT. The outcomes were changes in score on the upper limb section of the Fugl-Meyer assessment (FM), Motricity Index (MI), and Modified Ashworth Scale (MAS) evaluated at the baseline (T₀), posttraining (T₁), and 1-month follow-up (T₂). Event-related desynchronization/synchronization were calculated in the upper alpha and the beta frequency ranges.

Results

Significant improvement in all outcomes was measured over the course of the study. Changes in FM were significant at T₂, and in MAS at T₁ and T₂. After training, desynchronization on the ipsilesional sensorimotor areas increased during passive and active movement, as compared with T₀.

Conclusions

A repetitive robotic-assisted BAT program may improve upper limb motor function and reduce spasticity in the chronically impaired paretic arm. Effects on spasticity were associated with EEG changes over the ipsilesional sensorimotor network.

Experience modulates motor imagery-based brain activity

Whether or not brain activation during motor imagery (MI), the mental rehearsal of movement, is modulated by experience (i.e. skilled performance, achieved through long-term practice) remains unclear. Specifically, MI is generally associated with diffuse activation patterns that closely resemble novice physical performance, which may be attributable to a lack of experience with the task being imagined vs. being a distinguishing feature of MI. We sought to examine how experience modulates brain activity driven via MI, implementing a within- and between-group design to manipulate experience across tasks as well as expertise of the participants. Two groups of 'experts' (basketball/volleyball athletes) and 'novices' (recreational controls) underwent magnetoencephalography (MEG) while performing MI of four multi-articular tasks, selected to ensure that the degree of experience that participants had with each task varied. Source-level analysis was applied to MEG data and linear mixed effects modelling was conducted to examine task-related changes in activity. Within- and between-group comparisons were completed post hoc and difference maps were plotted. Brain activation patterns observed during MI of tasks for which participants had a low degree of experience were more widespread and bilateral (i.e. within-groups), with limited differences observed during MI of tasks for which participants had similar experience (i.e. between-groups). Thus, we show that brain activity during MI is modulated by experience; specifically, that novice performance is associated with the additional recruitment of regions across both hemispheres. Future investigations of the neural correlates of MI should consider prior experience when selecting the task to be performed.

Event-related desynchronization of mu and beta oscillations during the processing of novel tool names

According to the embodied cognition framework, the formation of conceptual representations integrates the type of experience during learning. In this electroencephalographic study, we applied a linguistic variant of a training paradigm, in which participants learned to associate novel names to novel tools while either manipulating or visually exploring them. The analysis focused on event-related desynchronization (ERD) of oscillations in the mu and beta frequency range, which reflects activation of sensorimotor brain areas. After three training sessions, processing names of manipulated tools elicited a stronger ERD of the beta (18-25 Hz, 140-260 ms) and the lower mu rhythm (8-10 Hz, 320-440 ms) than processing names of visually explored tools, reflecting a possible reactivation of experiential sensorimotor information. Given the unexpected result that familiarized pseudo-words elicited an ERD comparable to names of manipulated tools, our findings could reflect a suppression of sensorimotor activity during the processing of objects with exclusively visual features.

Non-linear Relationship between BOLD Activation and Amplitude of Beta Oscillations in the Supplementary Motor Area during Rhythmic Finger Tapping and Internal Timing

Functional imaging studies using BOLD contrasts have consistently reported activation of the supplementary motor area (SMA) both during motor and internal timing tasks. Opposing findings, however, have been shown for the modulation of beta oscillations in the SMA. While movement suppresses beta oscillations in the SMA, motor and non-motor tasks that rely on internal timing increase the amplitude of beta oscillations in the SMA. These independent observations suggest that the relationship between beta oscillations and BOLD activation is more complex than previously thought. Here we set out to investigate this rapport by examining beta oscillations in the SMA during movement with varying degrees of internal timing demands. In a simultaneous EEG-fMRI experiment, 20 healthy right-handed subjects performed an auditory-paced finger-tapping task. Internal timing was operationalized by including conditions with taps on every fourth auditory beat, which necessitates generation of a slow internal rhythm, while tapping to every auditory beat reflected simple auditory-motor synchronization. In the SMA, BOLD activity increased and power in both the low and the high beta band decreased expectedly during each condition compared to baseline. Internal timing was associated with a reduced desynchronization of low beta oscillations compared to conditions without internal timing demands. In parallel with this relative beta power increase, internal timing activated the SMA more strongly in terms of BOLD. This documents a task-dependent non-linear relationship between BOLD and beta-oscillations in the SMA. We discuss different roles of beta synchronization and desynchronization in active processing within the same cortical region.

Role of medial premotor areas in action language processing in relation to motor skills

The literature reports that the supplementary motor area (SMA) and pre-supplementary motor area (pre-SMA) are involved in motor planning and execution, and in motor-related cognitive functions such as motor imagery. However, their specific role in action language processing remains unclear. In the present study, we investigated the impact of repetitive transcranial magnetic stimulation (rTMS) over SMA and pre-SMA during an action semantic analogy task (SAT) in relation with fine motor skills (i.e., manual dexterity) and motor imagery abilities in healthy non-expert adults. The impact of rTMS over SMA (but not pre-SMA) on reaction times (RT) during SAT was correlated with manual dexterity. Specifically, results show that rTMS over SMA modulated RT for those with lower dexterity skills. Our results therefore demonstrate a causal involvement of SMA in action language processing, as well as the existence of inter-individual differences in this involvement. We discuss these findings in light of neurolinguistic theories of language processing.

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D). Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

Modulation of motor cortex inhibition during motor imagery

Motor imagery (MI) is similar to overt movement, engaging common neural substrates and facilitating the corticomotor pathway; however, it does not result in excitatory descending motor output. Transcranial magnetic stimulation (TMS) can be used to assess inhibitory networks in the primary motor cortex via measures of 1-ms short-interval intracortical inhibition (SICI), long-interval intracortical inhibition (LICI), and late cortical disinhibition (LCD). These measures are thought to reflect extrasynaptic GABA_A tonic inhibition, postsynaptic GABA_B inhibition, and presynaptic GABA_B disinhibition, respectively. The behavior of 1-ms SICI, LICI, and LCD during MI has not yet been explored. This study aimed to investigate how 1-ms SICI, LICI, and LCD are modulated during MI and voluntary relaxation (VR) of a target muscle. Twenty-five healthy young adults participated. TMS was used to assess nonconditioned motor evoked potential (MEP) amplitude, 1-ms SICI, 100- (LICI₁₀₀) and 150-ms LICI, and LCD in the right abductor pollicis brevis (APB) and right abductor digiti minimi during rest, MI, and VR of the hand. Compared with rest, MEP amplitudes were facilitated in APB during MI. SICI was not affected by task or muscle. LICI₁₀₀ decreased in both muscles during VR but not MI, whereas LCD was recruited in both muscles during both tasks. This indicates that VR modulates postsynaptic GABA_B inhibition, whereas both tasks modulate presynaptic GABA_B inhibition in a non-muscle-specific way. This study highlights further neurophysiological parallels between actual and imagined movement, which may extend to voluntary relaxation.NEW & NOTEWORTHY This is the first study to investigate how 1-ms short-interval intracortical inhibition, long-interval intracortical inhibition, and late cortical disinhibition are modulated during motor imagery and voluntary muscle relaxation. We present novel findings of decreased 100-ms long-interval intracortical inhibition during voluntary muscle relaxation and increased late cortical disinhibition during both motor imagery and voluntary muscle relaxation.

Quantitative EEG Evaluation During Robot-Assisted Foot Movement

Passiveand imagined limbmovements induce changes in cerebral oscillatory activity. Central modulatory effects play a role in plastic changes, and are of uttermost importance in rehabilitation. This has extensively been studied for upper limb, but less is known for lower limb. The aim of this study is to investigate the topographical distribution of event-related desynchronization/synchronization(ERD/ERS) and task-relatedcoherence during a robot-assisted and a motor imagery task of lower limb in healthy subjects to inform rehabilitation paradigms. 32-channels electroencephalogram (EEG) was recorded in twenty-one healthy right footed and handed subjects during a robot-assisted single-joint cyclic right ankle movement performed by the BTS ANYMOV robotic hospital bed. Data were acquired with a block protocol for passive and imagined movement at a frequency of 0.2 Hz. ERD/ERS and task related coherence were calculated in alpha1 (8-10 Hz), alpha2 (10.5-12.5 Hz) and beta (13-30 Hz) frequency ranges. During passive movement, alpha2 rhythm desynchronized overC3 and ipsilateral frontal areas (F4, FC2, FC6); betaERD was detected over the bilateral motor areas (Cz, C3, C4). During motor imagery, a significant desynchronization was evident for alpha1 over contralateral sensorimotor cortex (C3), for alpha2 over bilateral motor areas (C3 and C4), and for beta over central scalp areas. Task-related coherence decreased during passive movement in alpha2 band between contralateral central area (C3, CP5, CP1, P3) and ipsilateral frontal area (F8, FC6, T8); beta band coherence decreased between C3-C4 electrodes, and increased between C3-Cz. These data contribute to the understanding of oscillatory activity and functional neuronal interactions during lower limb robot-assisted motor performance. The final output of this line of research is to inform the design and development of neurorehabilitation protocols.

Brain-machine interfaces for rehabilitation of poststroke hemiplegia

Noninvasive brain-machine interfaces (BMIs) are typically associated with neuroprosthetic applications or communication aids developed to assist in daily life after loss of motor function, eg, in severe paralysis. However, BMI technology has recently been found to be a powerful tool to promote neural plasticity facilitating motor recovery after brain damage, eg, due to stroke or trauma. In such BMI paradigms, motor cortical output and input are simultaneously activated, for instance by translating motor cortical activity associated with the attempt to move the paralyzed fingers into actual exoskeleton-driven finger movements, resulting in contingent visual and somatosensory feedback. Here, we describe the rationale and basic principles underlying such BMI motor rehabilitation paradigms and review recent studies that provide new insights into BMI-related neural plasticity and reorganization. Current challenges in clinical implementation and the broader use of BMI technology in stroke neurorehabilitation are discussed.

Using Actual and Imagined Walking Related Desynchronization Features in a BCI

Recently, brain-computer interface (BCI) research has extended to investigate its possible use in motor rehabilitation. Most of these investigations have focused on the upper body. Only few studies consider gait because of the difficulty of recording EEG during gross movements. However, for stroke patients the rehabilitation of gait is of crucial importance. Therefore, this study investigates if a BCI can be based on walking related desynchronization features. Furthermore, the influence of complexity of the walking movements on the classification performance is investigated. Two BCI experiments were conducted in which healthy subjects performed a cued walking task, a more complex walking task (backward or adaptive walking), and imagination of the same tasks. EEG data during these tasks was classified into walking and no-walking. The results from both experiments show that despite the automaticity of walking and recording difficulties, brain signals related to walking could be classified rapidly and reliably. Classification performance was higher for actual walking movements than for imagined walking movements. There was no significant increase in classification performance for both the backward and adaptive walking tasks compared with the cued walking tasks. These results are promising for developing a BCI for the rehabilitation of gait.

Brain-computer interfaces for patients with disorders of consciousness

The disorders of consciousness refer to clinical conditions that follow a severe head injury. Patients diagnosed as in a vegetative state lack awareness, while patients diagnosed as in a minimally conscious state retain fluctuating awareness. However, it is a challenge to accurately diagnose these disorders with clinical assessments of behavior. To improve diagnostic accuracy, neuroimaging-based approaches have been developed to detect the presence or absence of awareness in patients who lack overt responsiveness. For the small subset of patients who retain awareness, brain-computer interfaces could serve as tools for communication and environmental control. Here we review the existing literature concerning the sensory and cognitive abilities of patients with disorders of consciousness with respect to existing brain-computer interface designs. We highlight the challenges of device development for this special population and address some of the most promising approaches for future investigations.

A validation study of the use of near-infrared spectroscopy imaging in primary and secondary motor areas of the human brain

The electroencephalographically measured Bereitschafts (readiness)-potential in the supplementary motor area (SMA) serves as a signature of the preparation of motor activity. Using a multichannel, noninvasive near-infrared spectroscopy (NIRS) imager, we studied the vascular correlate of the readiness potential. Sixteen healthy subjects performed a self-paced or externally triggered motor task in a single or repetitive pattern, while NIRS simultaneously recorded the task-related responses of deoxygenated hemoglobin (HbR) in the primary motor area (M1) and the SMA. Right-hand movements in the repetitive sequence trial elicited a significantly greater HbR response in both the SMA and the left M1 compared to left-hand movements. During the single sequence condition, the HbR response in the SMA, but not in the M1, was significantly greater for self-paced than for externally cued movements. Nonetheless, an unequivocal temporal delay was not found between the SMA and M1. Near-infrared spectroscopy is a promising, noninvasive bedside tool for the neuromonitoring of epileptic seizures or cortical spreading depolarizations (CSDs) in patients with epilepsy, stroke, or brain trauma because these pathological events are associated with typical spatial and temporal changes in HbR. Propagation is a characteristic feature of these events which importantly supports their identification and characterization in invasive recordings. Unfortunately, the present noninvasive study failed to show a temporal delay during self-paced movements between the SMA and M1 as a vascular correlate of the readiness potential. Although this result does not exclude, in principle, the possibility that scalp-NIRS can detect a temporal delay between different regions during epileptic seizures or CSDs, it strongly suggests that further technological development of NIRS should focus on both improved spatial and temporal resolution. This article is part of a Special Issue entitled Status Epilepticus.

Is event-related desynchronization a biomarker representing corticospinal excitability?

Brain computer interfaces (BCIs) using event-related desynchronization (ERD) of the electroencephalogram (EEG), which is believed to represent increased activation of the sensorimotor cortex, have attracted attention as tools for rehabilitation of upper limb motor functions in hemiplegic stroke patients. However, it remains unclear whether the corticospinal excitability is actually correlated with ERD. The purpose of this study was to assess the association between the ERD magnitude and the excitability of primary motor cortex (M1) and spinal motoneurons. M1 excitability was tested by motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) using transcranial magnetic stimulation, and spinal motoneuronal excitability was tested by F-waves using peripheral nerve stimulation. Results showed that large ERD during motor imagery was associated with significantly increased F-wave persistence and reduced SICI, but no significant changes in ICF and the response average of F-wave amplitudes. Our findings suggest that ERD magnitude during motor imagery represents the instantaneous excitability of both M1 and spinal motoneurons. This study provides electrophysiological evidence that ERD-based BCI with motor imagery task increases corticospinal excitability as changes accompanying actual movements.

Beta oscillations reveal ethnicity ingroup bias in sensorimotor resonance to pain of others

People evaluate members of their own social group more favorably and empathize more strongly with their ingroup members. Using electroencephalography (EEG), we explored whether resonant responses of sensorimotor cortex to the pain of others are modulated by the ethnicity of these others. White participants watched video clips of ethnic ingroup and outgroup hands, being either penetrated by a needle syringe or touched by a cotton swab, while EEG was recorded. Time-frequency analysis was applied to Laplacian-transformed signals from the sensors overlying sensorimotor cortex in order to assess event-related desynchronization and synchronization (ERD/ERS) of sensorimotor mu (7-12 Hz) and beta (13-30 Hz) rhythms. When watching needle injections, beta ERD was significantly stronger for ingroup compared with outgroup hands. This ethnicity bias was restricted to painful actions, as beta ERD for ingroup and outgroup hands neither differed when observing no-pain videos, nor during presentation of the hands without any treatment. Such vicarious sensorimotor activation could play a role in social interaction by enhancing the understanding of the feelings and reactions of others and hence facilitating behavioral coordination among group members.

Electroencephalography as a post-stroke assessment method: An updated review

Given that stroke is currently a serious problem in the population, employing more reliable and objective techniques for determining diagnosis and prognosis is necessary in order to enable effective clinical decision-making. EEG is a simple, low-cost, non-invasive tool that can provide information about the changes occurring in the cerebral cortex during the recovery process after stroke. EEG provides data on the evolution of cortical activation patterns which can be used to establish a prognosis geared toward harnessing each patient's full potential. This strategy can be used to prevent compensation and maladaptive plasticity, redirect treatments, and develop new interventions that will let stroke patients reach their new maximum motor levels.

Grasping hand verbs: oscillatory beta and alpha correlates of action-word processing

The grounded cognition framework proposes that sensorimotor brain areas, which are typically involved in perception and action, also play a role in linguistic processing. We assessed oscillatory modulation during visual presentation of single verbs and localized cortical motor regions by means of isometric contraction of hand and foot muscles. Analogously to oscillatory activation patterns accompanying voluntary movements, we expected a somatotopically distributed suppression of beta and alpha frequencies in the motor cortex during processing of body-related action verbs. Magnetoencephalographic data were collected during presentation of verbs that express actions performed using the hands (H) or feet (F). Verbs denoting no bodily movement (N) were used as a control. Between 150 and 500 msec after visual word onset, beta rhythms were suppressed in H and F in comparison with N in the left hemisphere. Similarly, alpha oscillations showed left-lateralized power suppression in the H-N contrast, although at a later stage. The cortical oscillatory activity that typically occurs during voluntary movements is therefore found to somatotopically accompany the processing of body-related verbs. The combination of a localizer task with the oscillatory investigation applied to verb reading as in the present study provides further methodological possibilities of tracking language processing in the brain.

Motor imagery-based brain activity parallels that of motor execution: evidence from magnetic source imaging of cortical oscillations

Motor imagery (MI) is a form of practice in which an individual mentally performs a motor task. Previous research suggests that skill acquisition via MI is facilitated by repetitive activation of brain regions in the sensorimotor network similar to that of motor execution, however this evidence is conflicting. Further, many studies do not control for overt muscle activity and thus the activation patterns reported for MI may be driven in part by actual movement. The purpose of the current research is to further establish MI as a secondary modality of skill acquisition by providing electrophysiological evidence of an overlap between brain areas recruited for motor execution and imagery. Non-disabled participants (N=18; 24.7±3.8 years) performed both execution and imagery of a unilateral sequence button-press task. Magnetoencephalography (MEG) was utilized to capture neural activity, while electromyography used to rigorously monitor muscle activity. Event-related synchronization/desynchronization (ERS/ERD) analysis was conducted in the beta frequency band (15-30 Hz). Whole head dual-state beamformer analysis was applied to MEG data and 3D t-tests were conducted after Talairach normalization. Source-level analysis showed that MI has similar patterns of spatial activity as ME, including activation of contralateral primary motor and somatosensory cortices. However, this activation is significantly less intense during MI (p<0.05). As well, activation during ME was more lateralized (i.e., within the contralateral hemisphere). These results confirm that ME and MI have similar spatial activation patterns. Thus, the current research provides direct electrophysiological evidence to further establish MI as a secondary form of skill acquisition.

Discriminative Learning of Propagation and Spatial Pattern for Motor Imagery EEG Analysis

Effective learning and recovery of relevant source brain activity patterns is a major challenge to brain-computer interface using scalp EEG. Various spatial filtering solutions have been developed. Most current methods estimate an instantaneous demixing with the assumption of uncorrelatedness of the source signals. However, recent evidence in neuroscience suggests that multiple brain regions cooperate, especially during motor imagery, a major modality of brain activity for brain-computer interface. In this sense, methods that assume uncorrelatedness of the sources become inaccurate. Therefore, we are promoting a new methodology that considers both volume conduction effect and signal propagation between multiple brain regions. Specifically, we propose a novel discriminative algorithm for joint learning of propagation and spatial pattern with an iterative optimization solution. To validate the new methodology, we conduct experiments involving 16 healthy subjects and perform numerical analysis of the proposed algorithm for EEG classification in motor imagery brain-computer interface. Results from extensive analysis validate the effectiveness of the new methodology with high statistical significance.

Event-related desynchronization reflects downregulation of intracortical inhibition in human primary motor cortex

There is increasing interest in electroencephalogram (EEG)-based brain-computer interface (BCI) as a tool for rehabilitation of upper limb motor functions in hemiplegic stroke patients. This type of BCI often exploits mu and beta oscillations in EEG recorded over the sensorimotor areas, and their event-related desynchronization (ERD) following motor imagery is believed to represent increased sensorimotor cortex excitability. However, it remains unclear whether the sensorimotor cortex excitability is actually correlated with ERD. Thus we assessed the association of ERD with primary motor cortex (M1) excitability during motor imagery of right wrist movement. M1 excitability was tested by motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI), and intracortical facilitation (ICF) with transcranial magnetic stimulation (TMS). Twenty healthy participants were recruited. The participants performed 7 s of rest followed by 5 s of motor imagery and received online visual feedback of the ERD magnitude of the contralateral hand M1 while performing the motor imagery task. TMS was applied to the right hand M1 when ERD exceeded predetermined thresholds during motor imagery. MEP amplitudes, SICI, and ICF were recorded from the agonist muscle of the imagined hand movement. Results showed that the large ERD during wrist motor imagery was associated with significantly increased MEP amplitudes and reduced SICI but no significant changes in ICF. Thus ERD magnitude during wrist motor imagery represents M1 excitability. This study provides electrophysiological evidence that a motor imagery task involving ERD may induce changes in corticospinal excitability similar to changes accompanying actual movements.

Bayesian learning for spatial filtering in an EEG-based brain-computer interface

Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

Modulation of event-related desynchronization in robot-assisted hand performance: brain oscillatory changes in active, passive and imagined movements

Background

Robot-assisted therapy in patients with neurological disease is an attempt to improve function in a moderate to severe hemiparetic arm. A better understanding of cortical modifications after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Modifications of cortical activity in healthy subjects were evaluated during voluntary active movement, passive robot-assisted motor movement, and motor imagery tasks performed under unimanual and bimanual protocols.

Methods

Twenty-one channel electroencephalography (EEG) was recorded with a video EEG system in 8 subjects. The subjects performed robot-assisted tasks using the Bi-Manu Track robot-assisted arm trainer. The motor paradigm was executed during one-day experimental sessions under eleven unimanual and bimanual protocols of active, passive and imaged movements. The event-related-synchronization/desynchronization (ERS/ERD) approach to the EEG data was applied to investigate where movement-related decreases in alpha and beta power were localized.

Results

Voluntary active unilateral hand movement was observed to significantly activate the contralateral side; however, bilateral activation was noted in all subjects on both the unilateral and bilateral active tasks, as well as desynchronization of alpha and beta brain oscillations during the passive robot-assisted motor tasks. During active-passive movement when the right hand drove the left one, there was predominant activation in the contralateral side. Conversely, when the left hand drove the right one, activation was bilateral, especially in the alpha range. Finally, significant contralateral EEG desynchronization was observed during the unilateral task and bilateral ERD during the bimanual task.

Conclusions

This study suggests new perspectives for the assessment of patients with neurological disease. The findings may be relevant for defining a baseline for future studies investigating the neural correlates of behavioral changes after robot-assisted training in stroke patients.