Functional significance of the mu rhythm of human cortex: an electrophysiologic study with subdural electrodes

Modulation of stimulus-induced 20-Hz activity for the tongue and hard palate during tongue movement in humans

OBJECTIVE

Modulation of 20-Hz activity in the primary sensorimotor cortex (SM1) may be important for oral functions. Here, we show that 20-Hz event-related desynchronization/synchronization (20-Hz ERD/ERS) is modulated by sensory input and motor output in the oral region.

METHODS

Magnetic 20-Hz activity was recorded following right-sided tongue stimulation during rest (Rest) and self-paced repetitive tongue movement (Move). To exclude proprioception effects, 20-Hz activity induced by right-sided hard palate stimulation was also recorded. The 20-Hz activity in the two conditions was compared via temporal spectral evolution analyses.

RESULTS

20-Hz ERD/ERS was detected over bilateral temporoparietal areas in the Rest condition for both regions. Moreover, 20-Hz ERS was significantly suppressed in the Move condition for both regions.

CONCLUSIONS

Detection of 20-Hz ERD/ERS during the Rest condition for both regions suggests that the SM1 functional state may be modulated by oral stimulation, with or without proprioceptive effects. Moreover, the suppression of 20-Hz ERS for the hard palate during the Move condition suggests that the stimulation-induced functional state of SM1 may have been modulated by the movement, even though the movement and stimulation areas were different.

SIGNIFICANCE

Sensorimotor function of the general oral region may be finely coordinated through 20-Hz cortical oscillation.

Neural dynamics in motor preparation: From phase-mediated global computation to amplitude-mediated local computation

Oscillatory activity plays a critical role in the brain. Here, we illustrate the dynamics of neural oscillations in the motor system of the brain. We used a non-directional cue to instruct participants to prepare a motor response with either the left or the right hand and recorded electroencephalography during the preparation of the response. Consistent with previous findings, the amplitude of alpha-band (8-14Hz) oscillations significantly decreased over the motor region contralateral to the hand prepared for the response. Prior to this decrease, there were a number of inter-regional phase synchronies at lower frequencies (2-4Hz; delta band). Cross-frequency coupling was quantified to further explore the direct link between alpha amplitudes and delta synchrony. The cross-frequency coupling of showed response-specific modulation, whereby the motor region contralateral to the preparation hand exhibited an increase in coupling relative to the baseline. The amplitude of alpha oscillations had an unpreferred and a preferred delta phase, in which the amplitude was modulated negatively and positively, respectively. Given the amplitude of alpha-band oscillations decreased over the analyzed period, the alpha amplitude might be down-regulated by the phase-amplitude coupling, although we do not have direct evidence for that. Taken together, these results show global-to-local computation in the motor system, which started from inter-regional delta phase synchrony and ended at an effector-specific decrease in the amplitude of alpha-band oscillations, with phase-amplitude coupling connecting both computations.

Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept

A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute post-stroke patients. The system permits synchronized cortical and kinematic measures by integrating high-resolution EEG, passive robotic device and Virtual Reality. The brain functional re-organization was monitored in association with motor patterns replicating activities of daily living (ADL). Patients underwent 13 rehabilitation sessions. At sessions 1, 7 and 13, clinical tests were administered to assess the level of motor impairment, and EEG was recorded during rehabilitation task execution. For each session and rehabilitation task, four kinematic indices of motor performance were calculated and compared with the outcome of clinical tests. Functional source maps were obtained from EEG data and projected on the real patients' anatomy (MRI data). Laterality indices were calculated for hemispheric dominance assessment. All patients showed increased participation in the rehabilitation process. Cortical activation changes during recovery were detected in relation to different motor patterns, hence verifying the system's suitability to add quantitative measures of motor performance and neural recovery to classical tests. We conclude that this system seems a promising tool for novel robot-based rehabilitation paradigms tailored to individual needs and neuro-motor responses of the patients.

EEG-guided meditation: A personalized approach

The therapeutic potential of meditation for physical and mental well-being is well documented, however the possibility of adverse effects warrants further discussion of the suitability of any particular meditation practice for every given participant. This concern highlights the need for a personalized approach in the meditation practice adjusted for a concrete individual. This can be done by using an objective screening procedure that detects the weak and strong cognitive skills in brain function, thus helping design a tailored meditation training protocol. Quantitative electroencephalogram (qEEG) is a suitable tool that allows identification of individual neurophysiological types. Using qEEG screening can aid developing a meditation training program that maximizes results and minimizes risk of potential negative effects. This brief theoretical-conceptual review provides a discussion of the problem and presents some illustrative results on the usage of qEEG screening for the guidance of mediation personalization.

Transcranial direct current stimulation enhances mu rhythm desynchronization during motor imagery that depends on handedness

Transcranial direct current stimulation (tDCS) can modulate the amplitude of event-related desynchronization (ERD) that appears on the electroencephalogram (EEG) during motor imagery. To study the effect of handedness on the modulating effect of tDCS, we compared the difference in tDCS-boosted ERD during dominant and non-dominant hand motor imagery. EEGs were recorded over the left sensorimotor cortex of seven healthy right-handed volunteers, and we measured ERD induced either by dominant or non-dominant hand motor imagery. Ten minutes of anodal tDCS was then used to increase the cortical excitability of the contralateral primary motor cortex (M1), and ERD was measured again. With anodal tDCS, we observed only a small increase in ERD during non-dominant hand motor imagery, whereas the same stimulation induced a prominent increase in ERD during dominant hand motor imagery. This trend was most obvious in the participants who used their dominant hand more frequently. Although our study is preliminary because of a small sample size, these results suggest that the increase in ERD by applying anodal tDCS was stronger on the dominant side than on the non-dominant side. The background excitability of M1 may determine the strength of the effect of anodal tDCS on ERD by hand motor imagery.

Neurofeedback training of alpha-band coherence enhances motor performance

OBJECTIVE

Neurofeedback training of motor cortex activations with brain-computer interface systems can enhance recovery in stroke patients. Here we propose a new approach which trains resting-state functional connectivity associated with motor performance instead of activations related to movements.

METHODS

Ten healthy subjects and one stroke patient trained alpha-band coherence between their hand motor area and the rest of the brain using neurofeedback with source functional connectivity analysis and visual feedback.

RESULTS

Seven out of ten healthy subjects were able to increase alpha-band coherence between the hand motor cortex and the rest of the brain in a single session. The patient with chronic stroke learned to enhance alpha-band coherence of his affected primary motor cortex in 7 neurofeedback sessions applied over one month. Coherence increased specifically in the targeted motor cortex and in alpha frequencies. This increase was associated with clinically meaningful and lasting improvement of motor function after stroke.

CONCLUSIONS

These results provide proof of concept that neurofeedback training of alpha-band coherence is feasible and behaviorally useful.

SIGNIFICANCE

The study presents evidence for a role of alpha-band coherence in motor learning and may lead to new strategies for rehabilitation.

Functional cortical network in alpha band correlates with social bargaining

Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals' alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts.

Alpha-band desynchronization in human parietal area during reach planning

OBJECTIVE

The symptoms with optic ataxia suggest that simple and visually guided hand movements are controlled by 2 different neural substrates. To assess the differential frequency-coded posterior parietal cortex (PPC) role in planning visuo-motor goal-directed tasks, we studied the action specificity of event-related desynchronization (ERD) in this area.

METHODS

We investigated cortical activity by electroencephalography, while 16 healthy subjects performed self-paced reaching or wrist extension (control) movements. Time-frequency representations were calculated for each movement during the preparatory period.

RESULTS

ERD dynamics in upper alpha-band indicated that preparing a goal-directed action activates contralateral PPC to the moving hand around 1.2s before starting the movement, while this activation is later (around 0.7s) in preparing a not-goal-directed action. The posterior dominant rhythm had peak frequency of lower alpha-band at bilateral parietal.

CONCLUSIONS

Posterior parietal cortex encodes goal-directed movement preparation through upper alpha-band activity, whereas general attention is processed via lower alpha-band oscillations.

SIGNIFICANCE

Preparing to reach an object engages posterior parietal cortex earlier than a not-goal directed movement.

Frequency and topography in monkey electroencephalogram during action observation: possible neural correlates of the mirror neuron system

The observation of actions executed by others results in desynchronization of electroencephalogram (EEG) in the alpha and beta frequency bands recorded from the central regions in humans. On the other hand, mirror neurons, which are thought to be responsible for this effect, have been studied only in macaque monkeys, using single-cell recordings. Here, as a first step in a research programme aimed at understanding the parallels between human and monkey mirror neuron systems (MNS), we recorded EEG from the scalp of two monkeys during action observation. The monkeys were trained to fixate on the face of a human agent and subsequently to fixate on a target upon which the agent performed a grasping action. We found that action observation produced desynchronization in the 19-25 Hz band that was strongest over anterior and central electrodes. These results are in line with human data showing that specific frequency bands within the power spectrum of the ongoing EEG may be modulated by observation of actions and therefore might be a specific marker of MNS activity.

Neural mirroring mechanisms and imitation in human infants

Studying human infants will increase our understanding of the nature, origins and function of neural mirroring mechanisms. Human infants are prolific imitators. Infant imitation indicates observation-execution linkages in the brain prior to language and protracted learning. Investigations of neural aspects of these linkages in human infants have focused on the sensorimotor mu rhythm in the electroencephalogram, which occurs in the alpha frequency range over central electrode sites. Recent results show that the infant mu rhythm is desynchronized during action execution as well as action observation. Current work is elucidating properties of the infant mu rhythm and how it may relate to prelinguistic action processing and social understanding. Here, we consider this neuroscience research in relation to developmental psychological theory, particularly the 'Like-Me' framework, which holds that one of the chief cognitive tasks of the human infant is to map the similarity between self and other. We elucidate the value of integrating neuroscience findings with behavioural studies of infant imitation, and the reciprocal benefit of examining mirroring mechanisms from an ontogenetic perspective.

EEG mu rhythm in typical and atypical development

Electroencephalography (EEG) is an effective, efficient, and noninvasive method of assessing and recording brain activity. Given the excellent temporal resolution, EEG can be used to examine the neural response related to specific behaviors, states, or external stimuli. An example of this utility is the assessment of the mirror neuron system (MNS) in humans through the examination of the EEG mu rhythm. The EEG mu rhythm, oscillatory activity in the 8-12 Hz frequency range recorded from centrally located electrodes, is suppressed when an individual executes, or simply observes, goal directed actions. As such, it has been proposed to reflect activity of the MNS. It has been theorized that dysfunction in the mirror neuron system (MNS) plays a contributing role in the social deficits of autism spectrum disorder (ASD). The MNS can then be noninvasively examined in clinical populations by using EEG mu rhythm attenuation as an index for its activity. The described protocol provides an avenue to examine social cognitive functions theoretically linked to the MNS in individuals with typical and atypical development, such as ASD. 

Kinesthetic and vestibular information modulate alpha activity during spatial navigation: a mobile EEG study

In everyday life, spatial navigation involving locomotion provides congruent visual, vestibular, and kinesthetic information that need to be integrated. Yet, previous studies on human brain activity during navigation focus on stationary setups, neglecting vestibular and kinesthetic feedback. The aim of our work is to uncover the influence of those sensory modalities on cortical processing. We developed a fully immersive virtual reality setup combined with high-density mobile electroencephalography (EEG). Participants traversed one leg of a triangle, turned on the spot, continued along the second leg, and finally indicated the location of their starting position. Vestibular and kinesthetic information was provided either in combination, as isolated sources of information, or not at all within a 2 × 2 full factorial intra-subjects design. EEG data were processed by clustering independent components, and time-frequency spectrograms were calculated. In parietal, occipital, and temporal clusters, we detected alpha suppression during the turning movement, which is associated with a heightened demand of visuo-attentional processing and closely resembles results reported in previous stationary studies. This decrease is present in all conditions and therefore seems to generalize to more natural settings. Yet, in incongruent conditions, when different sensory modalities did not match, the decrease is significantly stronger. Additionally, in more anterior areas we found that providing only vestibular but no kinesthetic information results in alpha increase. These observations demonstrate that stationary experiments omit important aspects of sensory feedback. Therefore, it is important to develop more natural experimental settings in order to capture a more complete picture of neural correlates of spatial navigation.

An evidence-based combining classifier for brain signal analysis

Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems.

Neurophysiological substrates of stroke patients with motor imagery-based Brain-Computer Interface training

We investigated the efficacy of motor imagery-based Brain Computer Interface (MI-based BCI) training for eight stroke patients with severe upper extremity paralysis using longitudinal clinical assessments. The results were compared with those of a control group (n = 7) that only received FES (Functional Electrical Stimulation) treatment besides conventional therapies. During rehabilitation training, changes in the motor function of the upper extremity and in the neurophysiologic electroencephalographic (EEG) were observed for two groups. After 8 weeks of training, a significant improvement in the motor function of the upper extremity for the BCI group was confirmed (p < 0.05 for ARAT), simultaneously with the activation of bilateral cerebral hemispheres. Additionally, event-related desynchronization (ERD) of the affected sensorimotor cortexes (SMCs) was significantly enhanced when compared to the pretraining course, which was only observed in the BCI group (p < 0.05). Furthermore, the activation of affected SMC and parietal lobe were determined to contribute to motor function recovery (p < 0.05). In brief, our findings demonstrate that MI-based BCI training can enhance the motor function of the upper extremity for stroke patients by inducing the optimal cerebral motor functional reorganization.

Somatosensory experiences with action modulate alpha and beta power during subsequent action observation

How does prior experience with action change how we perceive a similar action performed by someone else? Previous research has examined the role of sensorimotor and visual experiences in action mirroring during subsequent observation, but the contribution of somatosensory experiences to this effect has not been adequately examined. The current study tests whether prior somatosensory stimulation experienced during action production modulates brain activity during observation of similar actions being performed by others. Specifically, changes in alpha- and beta-range oscillations in the electroencephalogram (EEG) during observation of reaching actions were examined in relation to the observer's own prior experience of somatosensory stimulation while carrying out similar actions. Analyses revealed that alpha power over central electrodes was significantly decreased during observation of an action expected to result in somatosensory stimulation. Conversely, beta power was increased when an observed action was expected to result in somatosensory stimulation. These results suggest that somatosensory experiences may uniquely contribute to the way in which we process other people's actions.

Influence of spiking activity on cortical local field potentials

The intra-cortical local field potential (LFP) reflects a variety of electrophysiological processes including synaptic inputs to neurons and their spiking activity. It is still a common assumption that removing high frequencies, often above 300 Hz, is sufficient to exclude spiking activity from LFP activity prior to analysis. Conclusions based on such supposedly spike-free LFPs can result in false interpretations of neurophysiological processes and erroneous correlations between LFPs and behaviour or spiking activity. Such findings might simply arise from spike contamination rather than from genuine changes in synaptic input activity. Although the subject of recent studies, the extent of LFP contamination by spikes is unclear, and the fundamental problem remains. Using spikes recorded in the motor cortex of the awake monkey, we investigated how different factors, including spike amplitude, duration and firing rate, together with the noise statistic, can determine the extent to which spikes contaminate intra-cortical LFPs. We demonstrate that such contamination is realistic for LFPs with a frequency down to ∼10 Hz. For LFP activity below ∼10 Hz, such as movement-related potential, contamination is theoretically possible but unlikely in real situations. Importantly, LFP frequencies up to the (high-) gamma band can remain unaffected. This study shows that spike–LFP crosstalk in intra-cortical recordings should be assessed for each individual dataset to ensure that conclusions based on LFP analysis are valid. To this end, we introduce a method to detect and to visualise spike contamination, and provide a systematic guide to assess spike contamination of intra-cortical LFPs.

Importance of baseline in event-related desynchronization during a combination task of motor imagery and motor observation

OBJECTIVE

Event-related desynchronization (ERD) or synchronization (ERS) refers to the modulation of any EEG rhythm in response to a particular event. It is typically quantified as the ratio between a baseline and a task condition (the event). Here, we focused on the sensorimotor mu-rhythm. We explored the effects of different baselines on mu-power and ERD of the mu-rhythm during a motor imagery task.

METHODS

Eighteen healthy subjects performed motor imagery tasks while EEGs were recorded. Five different baseline movies were shown. For the imagery task a right-hand opening/closing movie was shown. Power and ERD of the mu-rhythm recorded over C3 and C4 for the different baselines were estimated.

MAIN RESULTS

50% of the subjects showed relatively high mu-power for specific baselines only, and ERDs of these subjects were strongly dependent on the baseline used. In 17% of the subjects no preference was found. Contralateral ERD of the mu-rhythm was found in about 67% of the healthy volunteers, with a significant baseline preference in about 75% of that subgroup.

SIGNIFICANCE

The sensorimotor ERD quantifies activity of the brain during motor imagery tasks. Selection of the optimal baseline increases ERD.

Bridging a yawning chasm: EEG investigations into the debate concerning the role of the human mirror neuron system in contagious yawning

Ongoing debate in the literature concerns whether there is a link between contagious yawning and the human mirror neuron system (hMNS). One way of examining this issue is with the use of the electroencephalogram (EEG) to measure changes in mu activation during the observation of yawns. Mu oscillations are seen in the alpha bandwidth of the EEG (8-12 Hz) over sensorimotor areas. Previous work has shown that mu suppression is a useful index of hMNS activation and is sensitive to individual differences in empathy. In two experiments, we presented participants with videos of either people yawning or control stimuli. We found greater mu suppression for yawns than for controls over right motor and premotor areas, particularly for those scoring higher on traits of empathy. In a third experiment, auditory recordings of yawns were compared against electronically scrambled versions of the same yawns. We observed greater mu suppression for yawns than for the controls over right lateral premotor areas. Again, these findings were driven by those scoring highly on empathy. The results from these experiments support the notion that the hMNS is involved in contagious yawning, emphasise the link between contagious yawning and empathy, and stress the importance of good control stimuli.

EEG alpha activity reflects motor preparation rather than the mode of action selection

Alpha-band activity (8–13 Hz) is not only suppressed by sensory stimulation and movements, but also modulated by attention, working memory and mental tasks, and could be sensitive to higher motor control functions. The aim of the present study was to examine alpha oscillatory activity during the preparation of simple left or right finger movements, contrasting the external and internal mode of action selection. Three preparation conditions were examined using a precueing paradigm with S1 as the preparatory and S2 as the imperative cue: Full, laterality instructed by S1; Free, laterality freely selected and None, laterality instructed by S2. Time-frequency (TF) analysis was performed in the alpha frequency range during the S1–S2 interval, and alpha motor-related amplitude asymmetries (MRAA) were also calculated. The significant MRAA during the Full and Free conditions indicated effective external and internal motor response preparation. In the absence of specific motor preparation (None), a posterior alpha event-related desynchronization (ERD) dominated, reflecting the main engagement of attentional resources. In Full and Free motor preparation, posterior alpha ERD was accompanied by a midparietal alpha event-related synchronization (ERS), suggesting a concomitant inhibition of task-irrelevant visual activity. In both Full and Free motor preparation, analysis of alpha power according to MRAA amplitude revealed two types of functional activation patterns: (1) a motor alpha pattern, with predominantly midparietal alpha ERS and large MRAA corresponding to lateralized motor activation/visual inhibition and (2) an attentional alpha pattern, with dominating right posterior alpha ERD and small MRAA reflecting visuospatial attention. The present results suggest that alpha oscillatory patterns do not resolve the selection mode of action, but rather distinguish separate functional strategies of motor preparation.

Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor Imagery Protocols

Introduction. Sensorimotor cortex is activated similarly during motor execution and motor imagery. The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas.Materials and Methods. Seven healthy subjects performed 4 motor tasks (real foot, imaginary foot, real hand, and imaginary hand movements), while electroencephalography was recorded over the sensorimotor cortex. Event-Related Desynchronization/Synchronization (ERD/ERS) of the mu-rhythm was used to evaluate MI performance. Source detection and FCNs were studied with eConnectome.Results and Discussion. Four subjects produced similar ERD/ERS patterns between motor execution and imagery during both hand and foot tasks, 2 subjects only during hand tasks, and 1 subject only during foot tasks. All subjects showed the expected brain activation in well-performed MI tasks, facilitating cortical source estimation. Preliminary functional connectivity analysis shows formation of networks on the sensorimotor cortex during motor imagery and execution.Conclusions. Cortex activation maps depict sensorimotor cortex activation, while similar functional connectivity networks are formed in the sensorimotor cortex both during actual and imaginary movements. eConnectome is demonstrated as an effective tool for the study of cortex activation and FCN. The implementation of FCN in motor imagery could induce promising advancements in Brain Computer Interfaces.

Performance evaluation of a motor-imagery-based EEG-Brain computer interface using a combined cue with heterogeneous training data in BCI-Naive subjects

BACKGROUND

The subjects in EEG-Brain computer interface (BCI) system experience difficulties when attempting to obtain the consistent performance of the actual movement by motor imagery alone. It is necessary to find the optimal conditions and stimuli combinations that affect the performance factors of the EEG-BCI system to guarantee equipment safety and trust through the performance evaluation of using motor imagery characteristics that can be utilized in the EEG-BCI testing environment.

METHODS

The experiment was carried out with 10 experienced subjects and 32 naive subjects on an EEG-BCI system. There were 3 experiments: The experienced homogeneous experiment, the naive homogeneous experiment and the naive heterogeneous experiment. Each experiment was compared in terms of the six audio-visual cue combinations and consisted of 50 trials. The EEG data was classified using the least square linear classifier in case of the naive subjects through the common spatial pattern filter. The accuracy was calculated using the training and test data set. The p-value of the accuracy was obtained through the statistical significance test.

RESULTS

In the case in which a naive subject was trained by a heterogeneous combined cue and tested by a visual cue, the result was not only the highest accuracy (p < 0.05) but also stable performance in all experiments.

CONCLUSIONS

We propose the use of this measuring methodology of a heterogeneous combined cue for training data and a visual cue for test data by the typical EEG-BCI algorithm on the EEG-BCI system to achieve effectiveness in terms of consistence, stability, cost, time, and resources management without the need for a trial and error process.

Electrophysiological signatures of intentional social coordination in the 10-12 Hz range

This study sought to investigate the effects of manipulating social coordination on brain synchronization/de-synchronization in the mu band. Mu activation is associated with understanding and coordinating motor acts and may play a key role in mediating social interaction. Members of a dyad were required to interact with one another in a rhythmic finger movement coordination task under various instructions: intrinsic where each member of the dyad was instructed to maintain their own and ignore their partner's movement; in-phase where they were asked to synchronize with their partner's movement; and anti-phase where they were instructed to syncopate with their partner's movement. EEG and movement data were recorded simultaneously from both subjects during all three tasks and a control condition. Log power ratios of EEG activity in the active conditions versus control were used to assess the effect of task context on synchronization/de-synchronization in the mu spectral domain. Results showed clear and systematic modulation of mu band activity in the 10-12 Hz range as a function of coordination context. In the left hemisphere general levels of alpha-mu suppression increased progressively as one moved from intrinsic through in-phase to anti-phase contexts but with no specific central-parietal focus. In contrast the right hemisphere displayed context-specific changes in the central-parietal region. The intrinsic condition showed a right synchronization which disappeared with the in-phase context even as de-synchronization remained greater in the left hemisphere. Anti-phase was associated with larger mu suppression in the right in comparison with left at central-parietal region. Such asymmetrical changes were highly correlated with changing behavioral dynamics. These specific patterns of activation and deactivation of mu activity suggest that localized neural circuitry in right central-parietal regions mediates how individuals interpret the movements of others in the context of their own actions. A right sided mechanism in the 10-12 Hz range appears to be involved in integrating the mutual information among the members of a dyad that enables the dynamics of social interaction to unfold in time.

Decoding intention: a neuroergonomic perspective

Decoding the intentions of other people based on non-linguistic cues such as their body movement is a major requirement of many jobs. Whether it is maintaining security at an airport or negotiating with locals in a foreign country, there is a need to maximize the effectiveness of training or real-time performance in this decoding process. This review considers the potential utility of neuroergonomic solutions, and in particular, of electroencephalographic (EEG) methods for augmenting action understanding. Focus is given to body movements and hand-object interactions, where there is a rapid growth in relevant science. The interpretation of EEG-based signals is reinforced by a consideration of functional magnetic resonance imaging experiments demonstrating underlying brain mechanisms that support goal oriented action. While no EEG method is currently implemented as a practical application for enhancing the understanding of unspoken intentions, there are a number of promising approaches that merit further development.

Neural correlates of action observation and execution in 14-month-old infants: an event-related EEG desynchronization study

There is increasing interest in neurobiological methods for investigating the shared representation of action perception and production in early development. We explored the extent and regional specificity of EEG desynchronization in the infant alpha frequency range (6-9 Hz) during action observation and execution in 14-month-old infants. Desynchronization during execution was restricted to central electrode sites, while action observation was associated with a broader desynchronization across frontal, central, and parietal regions. The finding of regional specificity in the overlap between EEG responses to action execution and observation suggests that the rhythm seen in the 6-9 Hz range over central sites in infancy shares certain properties with the adult mu rhythm. The magnitude of EEG desynchronization to action perception and production appears to be smaller for infants than for adults and older children, suggesting developmental change in this measure.

Utility of independent component analysis for interpretation of intracranial EEG

Electrode arrays are sometimes implanted in the brains of patients with intractable epilepsy to better localize seizure foci before epilepsy surgery. Analysis of intracranial EEG (iEEG) recordings is typically performed in the electrode channel domain without explicit separation of the sources that generate the signals. However, intracranial EEG signals, like scalp EEG signals, could be linear mixtures of local activity and volume-conducted activity arising in multiple source areas. Independent component analysis (ICA) has recently been applied to scalp EEG data, and shown to separate the signal mixtures into independently generated brain and non-brain source signals. Here, we applied ICA to unmix source signals from intracranial EEG recordings from four epilepsy patients during a visually cued finger movement task in the presence of background pathological brain activity. This ICA decomposition demonstrated that the iEEG recordings were not maximally independent, but rather are linear mixtures of activity from multiple sources. Many of the independent component (IC) projections to the iEEG recording grid were consistent with sources from single brain regions, including components exhibiting classic movement-related dynamics. Notably, the largest IC projection to each channel accounted for no more than 20–80% of the channel signal variance, implying that in general intracranial recordings cannot be accurately interpreted as recordings of independent brain sources. These results suggest that ICA can be used to identify and monitor major field sources of local and distributed functional networks generating iEEG data. ICA decomposition methods are useful for improving the fidelity of source signals of interest, likely including distinguishing the sources of pathological brain activity.

Subdural electrodes

Subdural electrodes are frequently used to aid in the neurophysiological assessment of patients with intractable seizures. We review the indications for these, their uses for localizing epileptogenic regions and for localizing cortical regions supporting movement, sensation, and language.

Topographical organization of mu and Beta band activity associated with hand and foot movements in patients with perirolandic lesions

To study the topographical organization of mu and beta band event-related desynchronization (ERD) associated with voluntary hand and foot movements, we used magnetoencephalographic (MEG) recordings from 19 patients with perirolandic lesions. Synthetic aperture magnetometry (SAM) was used to detect and localize changes in the mu (7 - 11 Hz) and beta (13 - 30 Hz) frequency bands associated with repetitive movements of the hand and foot and overlaid on individual coregistered magnetic resonance (MR) images. Hand movements showed homotopic and contralateral ERD at the sensorimotor (S/M) cortex in the majority of cases for mu and to a lesser extent for beta rhythms. Foot movements showed an increased heterotopic distribution with bilateral and ipsilateral ERD compared to hand movements. No systematic topographical segregation between mu and beta ERD could be observed. In patients with perirolandic lesions, the mu and beta band spatial characteristics associated with hand movements retain the expected functional-anatomical boundaries to a large extent. Foot movements have altered patterns of mu and beta band ERD, which may give more insight into the differential functional role of oscillatory activity in different voluntary movements.

Modulation of mu rhythm desynchronization during motor imagery by transcranial direct current stimulation

Background

The mu event-related desynchronization (ERD) is supposed to reflect motor preparation and appear during motor imagery. The aim of this study is to examine the modulation of ERD with transcranial direct current stimulation (tDCS).

Methods

Six healthy subjects were asked to imagine their right hand grasping something after receiving a visual cue. Electroencephalograms (EEGs) were recorded near the left M1. ERD of the mu rhythm (mu ERD) by right hand motor imagery was measured. tDCS (10 min, 1 mA) was used to modulate the cortical excitability of M1. Anodal, cathodal, and sham tDCS were tested in each subject with a randomized sequence on different days. Each condition was separated from the preceding one by more than 1 week in the same subject. Before and after tDCS, mu ERD was assessed. The motor thresholds (MT) of the left M1 were also measured with transcranial magnetic stimulation.

Results

Mu ERD significantly increased after anodal stimulation, whereas it significantly decreased after cathodal stimulation. There was a significant correlation between mu ERD and MT.

Conclusions

Opposing effects on mu ERD based on the orientation of the stimulation suggest that mu ERD is affected by cortical excitability.

A review on directional information in neural signals for brain-machine interfaces

Brain-machine interfaces (BMIs) can be characterized by the technique used to measure brain activity and by the way different brain signals are translated into commands that control an effector. We give an overview of different approaches and focus on a particular BMI approach: the movement of an artificial effector (e.g. arm prosthesis to the right) by those motor cortical signals that control the equivalent movement of a corresponding body part (e.g. arm movement to the right). This approach has been successfully applied in monkeys and humans by accurately extracting parameters of movements from the spiking activity of multiple single-units. Here, we review recent findings showing that analog neuronal population signals, ranging from intracortical local field potentials over epicortical ECoG to non-invasive EEG and MEG, can also be used to decode movement direction and continuous movement trajectories. Therefore, these signals might provide additional or alternative control for this BMI approach, with possible advantages due to reduced invasiveness.

Oscillatory brain states interact with late cognitive components of the somatosensory evoked potential

The question of interaction between ongoing neuronal activity and evoked responses has been addressed for different species, sensory systems and measurement modalities. Among other findings, there is converging evidence for an interaction of occipital alpha-rhythm amplitude with the visual evoked potential. Here, we test the hypothesis that the modulatory role of an ongoing rhythm might not be confined to the visual system and the occipital alpha rhythm, but instead may be generalized to other sensory systems. Using an online EEG analysis approach, we investigated the influence of the Rolandic alpha-rhythm on the somatosensory evoked potential (SEP). We triggered vibrotactile stimulation during periods of high Rolandic alpha-rhythm amplitude. Analysis revealed significant effects of pre-stimulus Rolandic alpha amplitude on the amplitude of the N140 and P260 components of the SEP, known to be linked to cognitive processing, but not on early sensory components. The N140-P260 complex shows a different focus in topography than the early sensory components and the pre-stimulus Rolandic alpha rhythm. These results indicate an involvement of Rolandic alpha-rhythm in higher cognitive processing. In more general terms--and in the context of similar studies in the visual system--our findings suggest that modulation of late EP components by ongoing rhythms might be a characteristic and possibly universal feature of sensory systems.

Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex

Similar to the posterior alpha rhythm, pericentral (Rolandic) EEG rhythms in the alpha and beta frequency range are referred to as "idle rhythms" indicating a "resting state" of the respective system. The precise function of these rhythms is not clear. We used simultaneous EEG-fMRI during a bimanual motor task to localize brain areas involved in Rolandic alpha and beta EEG rhythms. The identification of these rhythms in the MR environment was achieved by a blind source separation algorithm. Rhythm "strength", i.e. spectral power determined by wavelet analysis, inversely correlated most strongly with the fMRI-BOLD signal in the postcentral cortex for the Rolandic alpha (mu) rhythm and in the precentral cortex for the Rolandic beta rhythm. FMRI correlates of Rolandic alpha and beta rhythms were distinct from those associated with the posterior "classical" alpha rhythm, which correlated inversely with the BOLD signal in the occipital cortex. An inverse correlation with the BOLD signal in the respective sensory area seems to be a general feature of "idle rhythms".

Electrocorticographic spectral changes associated with ipsilateral individual finger and whole hand movement

The study of the human sensorimotor (SM) cortex activations associated with hand motor movement is central to the design of efficient and clinically useful brain-computer interfaces. Whereas the electrocorticographic (ECoG) signatures of contralateral hand movement have been studied in detail, those of ipsilateral hand and individual finger movements have not been characterized. We studied the low (8-32 Hz) and high-frequency (76-100 Hz) SM cortical ECoG spectral changes associated with contralateral and ipsilateral whole hand and individual finger movement and assessed their discriminability. We find that ipsilateral movement is associated with widespread decreases in the low-frequency band (LFB) and more focal increases in the high-frequency band (HFB). The HFB component discriminates between ipsilateral and contralateral movement-associated activations, in contrast to the LFB. The HFB also discriminates between thumb and index finger movement-associated activations, for both the contralateral and the ipsilateral case, whereas the LFB does not. This is the first published report of a discriminable ipsilateral motor signal, with important implications in the use of brain-computer interfaces in hemiplegic patients.

Decoupling the cortical power spectrum reveals real-time representation of individual finger movements in humans

During active movement the electric potentials measured from the surface of the motor cortex exhibit consistent modulation, revealing two distinguishable processes in the power spectrum. At frequencies <40 Hz, narrow-band power decreases occur with movement over widely distributed cortical areas, while at higher frequencies there are spatially more focal power increases. These high-frequency changes have commonly been assumed to reflect synchronous rhythms, analogous to lower-frequency phenomena, but it has recently been proposed that they reflect a broad-band spectral change across the entire spectrum, which could be obscured by synchronous rhythms at low frequencies. In 10 human subjects performing a finger movement task, we demonstrate that a principal component type of decomposition can naively separate low-frequency narrow-band rhythms from an asynchronous, broad-spectral, change at all frequencies between 5 and 200 Hz. This broad-spectral change exhibited spatially discrete representation for individual fingers and reproduced the temporal movement trajectories of different individual fingers.

Hand movement direction decoded from MEG and EEG

Brain activity can be used as a control signal for brain-machine interfaces (BMIs). A powerful and widely acknowledged BMI approach, so far only applied in invasive recording techniques, uses neuronal signals related to limb movements for equivalent, multidimensional control of an external effector. Here, we investigated whether this approach is also applicable for noninvasive recording techniques. To this end, we recorded whole-head MEG during center-out movements with the hand and found significant power modulation of MEG activity between rest and movement in three frequency bands: an increase for < or = 7 Hz (low-frequency band) and 62-87 Hz (high-gamma band) and a decrease for 10-30 Hz (beta band) during movement. Movement directions could be inferred on a single-trial basis from the low-pass filtered MEG activity as well as from power modulations in the low-frequency band, but not from the beta and high-gamma bands. Using sensors above the motor area, we obtained a surprisingly high decoding accuracy of 67% on average across subjects. Decoding accuracy started to rise significantly above chance level before movement onset. Based on simultaneous MEG and EEG recordings, we show that the inference of movement direction works equally well for both recording techniques. In summary, our results show that neuronal activity associated with different movements of the same effector can be distinguished by means of noninvasive recordings and might, thus, be used to drive a noninvasive BMI.

Golf putt outcomes are predicted by sensorimotor cerebral EEG rhythms

It is not known whether frontal cerebral rhythms of the two hemispheres are implicated in fine motor control and balance. To address this issue, electroencephalographic (EEG) and stabilometric recordings were simultaneously performed in 12 right-handed expert golfers. The subjects were asked to stand upright on a stabilometric force platform placed at a golf green simulator while playing about 100 golf putts. Balance during the putts was indexed by body sway area. Cortical activity was indexed by the power reduction in spatially enhanced alpha (8-12 Hz) and beta (13-30 Hz) rhythms during movement, referred to as the pre-movement period. It was found that the body sway area displayed similar values in the successful and unsuccessful putts. In contrast, the high-frequency alpha power (about 10-12 Hz) was smaller in amplitude in the successful than in the unsuccessful putts over the frontal midline and the arm and hand region of the right primary sensorimotor area; the stronger the reduction of the alpha power, the smaller the error of the unsuccessful putts (i.e. distance from the hole). These results indicate that high-frequency alpha rhythms over associative, premotor and non-dominant primary sensorimotor areas subserve motor control and are predictive of the golfer's performance.

EEG mu rhythm and imitation impairments in individuals with autism spectrum disorder

Imitation ability has consistently been shown to be impaired in individuals with autism. A dysfunctional execution/observation matching system has been proposed to account for this impairment. The EEG mu rhythm is believed to reflect an underlying execution/observation matching system. This study investigated evidence of differential mu rhythm attenuation during the observation, execution, and imitation of movements and examined its relation to behaviorally assessed imitation abilities. Fourteen high-functioning adults with autism spectrum disorder (ASD) and 15 IQ- and age-matched typical adults participated. On the behavioral imitation task, adults with ASD demonstrated significantly poorer performance compared to typical adults in all domains of imitation ability. On the EEG task, both groups demonstrated significant attenuation of the mu rhythm when executing an action. However, when observing movement, the individuals with ASD showed significantly reduced attenuation of the mu wave. Behaviorally assessed imitation skills were correlated with degree of mu wave attenuation during observation of movement. These findings suggest that there is execution/observation matching system dysfunction in individuals with autism and that this matching system is related to degree of impairment in imitation abilities.

Composition of brain oscillations and their functions in the maintenance of auditory, visual and audio–visual speech percepts: an exploratory study

In the present exploratory study based on 7 subjects, we examined the composition of magnetoencephalographic (MEG) brain oscillations induced by the presentation of an auditory, visual, and audio-visual stimulus (a talking face) using an oddball paradigm. The composition of brain oscillations were assessed here by analyzing the probability-classification of short-term MEG spectral patterns. The probability index for particular brain oscillations being elicited was dependent on the type and the modality of the sensory percept. The maintenance of the integrated audio-visual percept was accompanied by the unique composition of distributed brain oscillations typical of auditory and visual modality, and the contribution of brain oscillations characteristic for visual modality was dominant. Oscillations around 20 Hz were characteristic for the maintenance of integrated audio-visual percept. Identifying the actual composition of brain oscillations allowed us (1) to distinguish two subjectively/consciously identical mental percepts, and (2) to characterize the types of brain functions involved in the maintenance of the multi-sensory percept.