Synchronization of parietal and premotor areas during preparation and execution of praxis hand movements

Connectivity of neural signals to the primary motor area during preparatory periods for movement following external and internal cues

PURPOSE

We investigated the connectivity of neural signals from movement-related cortical areas to the primary motor area (M1) in the hemisphere contralateral to the movement side during the period of movement-related magnetic fields before movement.

MATERIALS AND METHODS

Participants were 13 healthy adults, and nerual signals were recorded using magnetoencephalography. Spontaneous extension of the right wrist was performed at the participant's own pace and following a visual cue in internal (IC) and external (EC) cue tasks. The connectivity of neural signals to M1 from each movement-related motor area was assessed by Granger causality analysis (GCA). The GCA was performed on the neural activity elicited in a frequency band between 7.8 and 46.9 Hz during the pre-movement periods, which occurred durng the readiness field (RF) and the negative slope prime (NSp). F-values, as connectivity values obtained by GCA, were compared between the EC and IC cue tasks.

RESULTS

For NSp periods, the connectivity of neural signals from the left superior frontal area (SF-L) to M1 was dominant in the IC task, whereas that from the left superior parietal area (SP-L) to M1 was dominant in the EC task. The F value in the GCA from SP-L to M1 was greater in the EC task during RF than in the IC task during equivalent periods.

CONSLUSIONS

In the present study, there were differences in the connectivity of neural signals to M1 between IC and EC tasks. The present results suggested that the pattern of pre-movement neural activity that resulted in a movement was not uniform but differed between movement tasks just before the movement.

Dynamic networks of cortico-muscular interactions in sleep and neurodegenerative disorders

The brain plays central role in regulating physiological systems, including the skeleto-muscular and locomotor system. Studies of cortico-muscular coordination have primarily focused on associations between movement tasks and dynamics of specific brain waves. However, the brain-muscle functional networks of synchronous coordination among brain waves and muscle activity rhythms that underlie locomotor control remain unknown. Here we address the following fundamental questions: what are the structure and dynamics of cortico-muscular networks; whether specific brain waves are main network mediators in locomotor control; how the hierarchical network organization relates to distinct physiological states under autonomic regulation such as wake, sleep, sleep stages; and how network dynamics are altered with neurodegenerative disorders. We study the interactions between all physiologically relevant brain waves across cortical locations with distinct rhythms in leg and chin muscle activity in healthy and Parkinson's disease (PD) subjects. Utilizing Network Physiology framework and time delay stability approach, we find that 1) each physiological state is characterized by a unique network of cortico-muscular interactions with specific hierarchical organization and profile of links strength; 2) particular brain waves play role as main mediators in cortico-muscular interactions during each state; 3) PD leads to muscle-specific breakdown of cortico-muscular networks, altering the sleep-stage stratification pattern in network connectivity and links strength. In healthy subjects cortico-muscular networks exhibit a pronounced stratification with stronger links during wake and light sleep, and weaker links during REM and deep sleep. In contrast, network interactions reorganize in PD with decline in connectivity and links strength during wake and non-REM sleep, and increase during REM, leading to markedly different stratification with gradual decline in network links strength from wake to REM, light and deep sleep. Further, we find that wake and sleep stages are characterized by specific links strength profiles, which are altered with PD, indicating disruption in the synchronous activity and network communication among brain waves and muscle rhythms. Our findings demonstrate the presence of previously unrecognized functional networks and basic principles of brain control of locomotion, with potential clinical implications for novel network-based biomarkers for early detection of Parkinson's and neurodegenerative disorders, movement, and sleep disorders.

Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements

Planning goal-directed movements towards different targets is at the basis of common daily activities (e.g., reaching), involving visual, visuomotor, and sensorimotor brain areas. Alpha (8-13 Hz) and beta (13-30 Hz) oscillations are modulated during movement preparation and are implicated in correct motor functioning. However, how brain regions activate and interact during reaching tasks and how brain rhythms are functionally involved in these interactions is still limitedly explored. Here, alpha and beta brain activity and connectivity during reaching preparation are investigated at EEG-source level, considering a network of task-related cortical areas. Sixty-channel EEG was recorded from 20 healthy participants during a delayed center-out reaching task and projected to the cortex to extract the activity of 8 cortical regions per hemisphere (2 occipital, 2 parietal, 3 peri-central, 1 frontal). Then, we analyzed event-related spectral perturbations and directed connectivity, computed via spectral Granger causality and summarized using graph theory centrality indices (in degree, out degree). Results suggest that alpha and beta oscillations are functionally involved in the preparation of reaching in different ways, with the former mediating the inhibition of the ipsilateral sensorimotor areas and disinhibition of visual areas, and the latter coordinating disinhibition of the contralateral sensorimotor and visuomotor areas.

Motor networks in children with autism spectrum disorder: a systematic review on EEG studies

Motor disturbance and altered motor networks are commonly reported in individuals with autism spectrum disorder (ASD). It has been suggested that electroencephalogram (EEG) can be used to provide exquisite temporal resolution for understanding motor control processes in ASD. However, the variability of study design and EEG approaches can impact our interpretation. Here, we conducted a systematic review on recent 11 EEG studies that involve motor observation and/or execution tasks and evaluated how these findings help us understand motor difficulties in ASD. Three behavior paradigms with different EEG analytic methods were demonstrated. The main findings were quite mixed: children with ASD did not always show disrupted neuronal activity during motor observation. Additionally, they might have intact ability for movement execution but have more difficulties in neuronal modulation during movement preparation. We would like to promote discussions on how methodological selections of behavioral tasks and data analytic approaches impact our interpretation of motor deficits in ASD. Future EEG research addressing the inconsistency across methodological approaches is necessary to help us understand neurophysiological mechanism of motor abnormalities in ASD.

Neuroplasticity after upper-extremity rehabilitation therapy with sensory stimulation in chronic stroke survivors

This study investigated the effect of using subthreshold vibration as a peripheral sensory stimulation during therapy on cortical activity. Secondary analysis of a pilot triple-blinded randomized controlled trial. Twelve chronic stroke survivors underwent 2-week upper-extremity task-practice therapy. Half received subthreshold vibratory stimulation on their paretic wrist (treatment group) and the other half did not (control). EEG connectivity and event-related de-/resynchronization for the sensorimotor network during hand grip were examined at pre-intervention, post-intervention and follow-up. Statistically significant group by time interactions were observed for both connectivity and event-related spectral perturbation. For the treatment group, connectivity increased at post-intervention and decreased at follow-up. Event-related desynchronization decreased and event-related resynchronization increased at post-intervention, which was maintained at follow-up. The control group had the opposite trend for connectivity and no change in event-related spectral perturbation. The stimulation altered cortical sensorimotor activity. The findings complement the clinical results of the trial in which the treatment group significantly improved gross manual dexterity while the control group did not. Increased connectivity in the treatment group may indicate neuroplasticity for motor learning, while reduced event-related desynchronization and increased event-related resynchronization may indicate lessened effort for grip and improved inhibitory control. EEG may improve understanding of neural processes underlying motor recovery.

Alpha-band activity in parietofrontal cortex predicts future availability of vibrotactile feedback in prosthesis use

Prosthesis disuse and abandonment is an ongoing issue in upper-limb amputation. In addition to lost structural and motor function, amputation also results in decreased task-specific sensory information. One proposed remedy is augmenting somatosensory information using vibrotactile feedback to provide tactile feedback of grasping objects. While the role of frontal and parietal areas in motor tasks is well established, the neural and kinematic effects of this augmented vibrotactile feedback remain in question. In this study, we sought to understand the neurobehavioral effects of providing augmented feedback during a reach-grasp-transport task. Ten persons with sound limbs performed a motor task while wearing a prosthesis simulator with and without vibrotactile feedback. We hypothesized that providing vibrotactile feedback during prosthesis use would increase activity in frontal and parietal areas and improve grasp-related behavior. Results show that anticipation of upcoming vibrotactile feedback may be encoded in motor and parietal areas during the reach-to-grasp phase of the task. While grasp aperture is unaffected by vibrotactile feedback, the availability of vibrotactile feedback does lead to a reduction in velocity during object transport. These results help shed light on how engineered feedback is utilized by prostheses users and provide methodologies for further assessment in advanced prosthetics research.

Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Predicting upper extremity motor improvement following therapy using EEG-based connectivity in chronic stroke

BACKGROUND

Uncertain prognosis presents a challenge for therapists in determining the most efficient course of rehabilitation treatment for individual patients. Cortical Sensorimotor network connectivity may have prognostic utility for upper extremity motor improvement because the integrity of the communication within the sensorimotor network forms the basis for neuroplasticity and recovery.

OBJECTIVE

To investigate if pre-intervention sensorimotor connectivity predicts post-stroke upper extremity motor improvement following therapy.

METHODS

Secondary analysis of a pilot triple-blind randomized controlled trial. Twelve chronic stroke survivors underwent 2-week task-practice therapy, while receiving vibratory stimulation for the treatment group and no stimulation for the control group. EEG connectivity was obtained pre-intervention. Motor improvement was quantified as change in the Box and Block Test from pre to post-therapy. The association between ipsilesional sensorimotor connectivity and motor improvement was examined using regression, controlling for group. For negative control, contralesional/interhemispheric connectivity and conventional predictors (initial clinical motor score, age, time post-stroke, lesion volume) were examined.

RESULTS

Greater ipsilesional sensorimotor alpha connectivity was associated with greater upper extremity motor improvement following therapy for both groups (p < 0.05). Other factors were not significant.

CONCLUSION

EEG connectivity may have a prognostic utility for individual patients' upper extremity motor improvement following therapy in chronic stroke.

The Influence of Different EEG References on Scalp EEG Functional Network Analysis During Hand Movement Tasks

Although scalp EEG functional networks have been applied to the study of motor tasks using electroencephalography (EEG), the selection of a suitable reference electrode has not been sufficiently researched. To investigate the effects of the original reference (REF-CZ), the common average reference (CAR), and the reference electrode standardization technique (REST) on scalp EEG functional network analysis during hand movement tasks, EEGs of 17 right-handed subjects performing self-paced hand movements were collected, and scalp functional networks [coherence (COH), phase-locking value (PLV), phase lag index (PLI)] with different references were constructed. Compared with the REF-CZ reference, the networks with CAR and REST references exhibited more significant increases in connectivity during the left-/right-hand movement preparation (MP) and movement execution (ME) stages. The node degree of the channel near the reference electrode was significantly reduced by the REF-CZ reference. CAR and REST both decreased this reference effect, REST more so than CAR. We confirmed that the choice of reference would affect the analysis of the functional network during hand movement tasks, and the REST reference can greatly reduce the effects of the online recording reference on the analysis of EEG connectivity.

Evaluation of synchronization measures for capturing the lagged synchronization between EEG channels: A cognitive task recognition approach

During cognitive, perceptual and sensory tasks, connectivity profile changes across different regions of the brain. Variations of such connectivity patterns between different cognitive tasks can be evaluated using pairwise synchronization measures applied to electrophysiological signals, such as electroencephalography (EEG). However, connectivity-based task recognition approaches achieving viable recognition performance have been lacking from the literature. By using several synchronization measures, we identify time lags between channel pairs during different cognitive tasks. We employed mutual information, cross correntropy, cross correlation, phase locking value, cosine similarity and nonlinear interdependence measures. In the training phase, for each type of cognitive task, we identify the time lags that maximize the average synchronization between channel pairs. These lags are used to calculate pairwise synchronization values with which we construct the train and test feature vectors for recognition of the cognitive task carried out using Fisher's linear discriminant (FLD) analysis. We tested our framework in a motor imagery activity recognition scenario on PhysioNet Motor Movement/Imagery and BCI Competition-III Ⅳa datasets. For PhysioNet dataset, average performance results ranging between % 51 and % 61 across 20 subjects. For BCI Competition-Ⅲ dataset, we achieve an average recognition performance of % 76 which is above the minimum reliable communication rate (% 70). We achieved an average accuracy over the minimum reliable communication rate on the BCI Competition-Ⅲ dataset. Performance levels were lower on the PhysioNet dataset. These results indicate that a viable task recognition system is achievable using pairwise synchronization measures evaluated at the proper task specific lags.

Robust EEG/MEG Based Functional Connectivity with the Envelope of the Imaginary Coherence: Sensor Space Analysis

The brain's functional connectivity (FC) estimated at sensor level from electromagnetic (EEG/MEG) signals can provide quick and useful information towards understanding cognition and brain disorders. Volume conduction (VC) is a fundamental issue in FC analysis due to the effects of instantaneous correlations. FC methods based on the imaginary part of the coherence (iCOH) of any two signals are readily robust to VC effects, but neglecting the real part of the coherence leads to negligible FC when the processes are truly connected but with zero or π-phase (modulus 2π) interaction. We ameliorate this issue by proposing a novel method that implements an envelope of the imaginary coherence (EIC) to approximate the coherence estimate of supposedly active underlying sources. We compare EIC with state-of-the-art FC measures that included lagged coherence, iCOH, phase lag index (PLI) and weighted PLI (wPLI), using bivariate autoregressive and stochastic neural mass models. Additionally, we create realistic simulations where three and five regions were mapped on a template cortical surface and synthetic MEG signals were obtained after computing the electromagnetic leadfield. With this simulation and comparison study, we also demonstrate the feasibility of sensor FC analysis using receiver operating curve analysis whilst varying the signal's noise level. However, these results should be interpreted with caution given the known limitations of the sensor-based FC approach. Overall, we found that EIC and iCOH demonstrate superior results with most accurate FC maps. As they complement each other in different scenarios, that will be important to study normal and diseased brain activity.

Temporal recalibration of motor and visual potentials in lag adaptation in voluntary movement

Adaptively recalibrating motor-sensory asynchrony is critical for animals to perceive self-produced action consequences. It is controversial whether motor- or sensory-related neural circuits recalibrate this asynchrony. By combining magnetoencephalography (MEG) and functional MRI (fMRI), we investigate the temporal changes in brain activities caused by repeated exposure to a 150-ms delay inserted between a button-press action and a subsequent flash. We found that readiness potentials significantly shift later in the motor system, especially in parietal regions (average: 219.9 ms), while visually evoked potentials significantly shift earlier in occipital regions (average: 49.7 ms) in the delay condition compared to the no-delay condition. Moreover, the shift in readiness potentials, but not in visually evoked potentials, was significantly correlated with the psychophysical measure of motor-sensory adaptation. These results suggest that although both motor and sensory processes contribute to the recalibration, the motor process plays the major role, given the magnitudes of shift and the correlation with the psychophysical measure.

Central neuronal motor behaviour in skilled and less skilled novices - Approaching sports-specific movement techniques

Research on motor behavioural processes preceding voluntary movements often refers to analysing the readiness potential (RP). For this, decades of studies used laboratory setups with controlled sports-related actions. Further, recent applied approaches focus on athlete-non-athlete comparisons, omitting possible effects of training history on RP. However, RP preceding real sport-specific movements in accordance to skill acquisition remains to be elucidated. Therefore, after familiarization 16 right-handed males with no experience in archery volunteered to perform repeated sports-specific movements, i.e. 40 arrow-releasing shots at 60s rest on a 15m distant standard target. Continuous, synchronised EEG and right limb EMG recordings during arrow-releasing served to detect movement onsets for RP analyses over distinct cortical motor areas. Based on attained scores on target, archery novices were, a posteriori, subdivided into a skilled and less skilled group. EMG results for mean values revealed no significant changes (all p>0.05), whereas RP amplitudes and onsets differed between groups but not between motor areas. Arrow-releasing preceded larger RP amplitudes (p<0.05) and later RP onsets (p<0.05) in skilled compared to less skilled novices. We suggest this to reflect attentional orienting and greater effort that accompanies central neuronal preparatory states of a sports-specific movement.

Apraxia: Review and Update

Praxis, the ability to perform skilled or learned movements is essential for daily living. Inability to perform such praxis movements is defined as apraxia. Apraxia can be further classified into subtypes such as ideomotor, ideational and limb-kinetic apraxia. Relevant brain regions have been found to include the motor, premotor, temporal and parietal cortices. Apraxia is found in a variety of highly prevalent neurological disorders including dementia, stroke and Parkinsonism. Furthermore, apraxia has been shown to negatively affect quality of life. Therefore, recognition and treatment of this disorder is critical. This article provides an overview of apraxia and highlights studies dealing with the neurophysiology of this disorder, opening up novel perspectives for the use of motor training and noninvasive brain stimulation as treatment.

An Integrated Approach for the Monitoring of Brain and Autonomic Response of Children with Autism Spectrum Disorders during Treatment by Wearable Technologies

Autism Spectrum Disorders (ASD) are associated with physiological abnormalities, which are likely to contribute to the core symptoms of the condition. Wearable technologies can provide data in a semi-naturalistic setting, overcoming the limitations given by the constrained situations in which physiological signals are usually acquired. In this study an integrated system based on wearable technologies for the acquisition and analysis of neurophysiological and autonomic parameters during treatment is proposed and an application on five children with ASD is presented. Signals were acquired during a therapeutic session based on an imitation protocol in ASD children. Data were analyzed with the aim of extracting quantitative EEG (QEEG) features from EEG signals as well as heart rate and heart rate variability (HRV) from ECG. The system allowed evidencing changes in neurophysiological and autonomic response from the state of disengagement to the state of engagement of the children, evidencing a cognitive involvement in the children in the tasks proposed. The high grade of acceptability of the monitoring platform is promising for further development and implementation of the tool. In particular if the results of this feasibility study would be confirmed in a larger sample of subjects, the system proposed could be adopted in more naturalistic paradigms that allow real world stimuli to be incorporated into EEG/psychophysiological studies for the monitoring of the effect of the treatment and for the implementation of more individualized therapeutic programs.

Influence of Perspective of Action Observation Training on Residual Limb Control in Naïve Prosthesis Usage

Prior work in amputees and partial limb immobilization have shown improved neural and behavioral outcomes in using their residual limb with prosthesis when undergoing observation-based training with a prosthesis-using actor compared to an intact limb. It was posited that these improvements are due to an alignment of user with the actor. It may be affected by visual angles that allow emphasis of critical joint actions which may promote behavioral changes. The purpose of this study was to examine how viewing perspective of observation-based training effects prosthesis adaptation in naïve device users. Twenty nonamputated prosthesis users learned how to use an upper extremity prosthetic device while viewing a training video from either a sagittal or coronal perspective. These views were chosen as they place visual emphasis on different aspects of task performance to the device. The authors found that perspective of actions has a significant role in adaptation of the residual limb while using upper limb prostheses. Perspectives that demonstrate elbow adaptations to prosthesis usage may enhance the functional motor outcomes of action observation therapy. This work has potential implications on how prosthetic device operation is conveyed to persons adapting to prostheses through action observation based therapy.

Decreased Modulation of EEG Oscillations in High-Functioning Autism during a Motor Control Task

Autism spectrum disorders (ASD) are thought to result in part from altered cortical excitatory-inhibitory balance; this pathophysiology may impact the generation of oscillations on electroencephalogram (EEG). We investigated premotor-parietal cortical physiology associated with praxis, which has strong theoretical and empirical associations with ASD symptomatology. Twenty five children with high-functioning ASD (HFA) and 33 controls performed a praxis task involving the pantomiming of tool use, while EEG was recorded. We assessed task-related modulation of signal power in alpha and beta frequency bands. Compared with controls, subjects with HFA showed 27% less left central (motor/premotor) beta (18–22 Hz) event-related desynchronization (ERD; p = 0.030), as well as 24% less left parietal alpha (7–13 Hz) ERD (p = 0.046). Within the HFA group, blunting of central ERD attenuation was associated with impairments in clinical measures of praxis imitation (r = −0.4; p = 0.04) and increased autism severity (r = 0.48; p = 0.016). The modulation of central beta activity is associated, among other things, with motor imagery, which may be necessary for imitation. Impaired imitation has been associated with core features of ASD. Altered modulation of oscillatory activity may be mechanistically involved in those aspects of motor network function that relate to the core symptoms of ASD.

Practicing Novel, Praxis-Like Movements: Physiological Effects of Repetition

Our primary goal was to develop and validate a task that could provide evidence about how humans learn praxis gestures, such as those involving the use of tools. To that end, we created a video-based task in which subjects view a model performing novel, meaningless one-handed actions with kinematics similar to praxis gestures. Subjects then imitated the movements with their right hand. Trials were repeated six times to examine practice effects. EEG was recorded during the task. As a control, subjects watched videos of a model performing a well-established (over learned) tool-use gesture. These gestures were also imitated six times. Demonstrating convergent validity, EEG measures of task-related cortical activation were similar in topography and frequency between the novel gesture task and the overlearned, praxis gesture task. As in studies assessing motor skill learning with simpler tasks, cortical activation during novel gesture learning decreased as the same gestures were repeated. In the control condition, repetition of overlearned tool-use gestures were also associated with reductions in activation, though to a lesser degree. Given that even overlearned, praxis gestures show constriction of EEG activity with repetition, it is possible that that attentional effects drive some of the repetition effects seen in EEG measures of activation during novel gesture repetition.

EEG oscillatory patterns and classification of sequential compound limb motor imagery

Background

A number of studies have been done on movement imagination of motor sequences with a single limb. However, brain oscillatory patterns induced by movement imagination of motor sequences involving multiple limbs have not been reported in recent years. The goal of the present study was to verify the feasibility of application of motor sequences involving multiple limbs to brain-computer interface (BCI) systems based on motor imagery (MI). The changes of EEG patterns and the inter-influence between movements associated with the imagination of motor sequences were also investigated.

Methods

The experiment, where 12 healthy subjects participated, involved one motor sequence with a single limb and three kinds of motor sequences with two or three limbs. The activity involved mental simulation, imagining playing drums with two conditions (60 and 30 beats per minute for the first and second conditions, respectively).

Results

Movement imagination of different limbs in the sequence contributed to time-variant event-related desynchronization (ERD) patterns within both mu and beta rhythms, which was more obvious for the second condition compared with the first condition. The ERD values of left/right hand imagery with prior hand imagery were significantly larger than those with prior foot imagery, while the phase locking values (PLVs) between central electrodes and the mesial frontocentral electrode of non-initial movement were significantly larger than those of the initial movement during imagination of motor sequences for both conditions. Classification results showed that the power spectral density (PSD) based method outperformed the multi-class common spatial patterns (multi-CSP) based method: The highest accuracies were 82.86 % and 91.43 %, and the mean values were 65 % and 74.14 % for the first and second conditions, respectively.

Conclusions

This work implies that motor sequences involving multiple limbs can be utilized to build a multimodal classification paradigm in MI-based BCI systems, and that prior movement imagination can result in the changes of neural activities in motor areas during subsequent movement imagination in the process of limb switching.

A Link between the Increase in Electroencephalographic Coherence and Performance Improvement in Operating a Brain-Computer Interface

We study the relationship between electroencephalographic (EEG) coherence and accuracy in operating a brain-computer interface (BCI). In our case, the BCI is controlled through motor imagery. Hence, a number of volunteers were trained using different training paradigms: classical visual feedback, auditory stimulation, and functional electrical stimulation (FES). After each training session, the volunteers' accuracy in operating the BCI was assessed, and the event-related coherence (ErCoh) was calculated for all possible combinations of pairs of EEG sensors. After at least four training sessions, we searched for significant differences in accuracy and ErCoh using one-way analysis of variance (ANOVA) and multiple comparison tests. Our results show that there exists a high correlation between an increase in ErCoh and performance improvement, and this effect is mainly localized in the centrofrontal and centroparietal brain regions for the case of our motor imagery task. This result has a direct implication with the development of new techniques to evaluate BCI performance and the process of selecting a feedback modality that better enhances the volunteer's capacity to operate a BCI system.

Dynamics of functional and effective connectivity within human cortical motor control networks

OBJECTIVE

Praxis, the performance of complex motor gestures, is crucial to the development of motor and social/communicative capacities. Praxis relies on a network consisting of inferior parietal and premotor regions, particularly on the left, and is thought to require transformation of spatio-temporal representations (parietal) into movement sequences (premotor).

METHOD

We examined praxis network dynamics by measuring EEG effective connectivity while healthy subjects performed a praxis task.

RESULTS

Propagation from parietal to frontal regions was not statistically greater on the left than the right. However, propagation from left parietal regions to all other regions was significantly greater during gesture preparation than execution. Moreover, during gesture preparation only, propagation from the left parietal region to bilateral frontal regions was greater than reciprocal propagations to the left parietal region. This directional specificity was not observed for the right parietal region.

CONCLUSIONS

These findings represent direct electrophysiological evidence for directionally predominant propagation in left frontal-parietal networks during praxis behavior, which may reflect neural mechanisms by which representations in the human brain select appropriate motor sequences for subsequent execution.

SIGNIFICANCE

In addition to bolstering the classic view of praxis network function, these results also demonstrate the relevance of additional information provided by directed connectivity measures.

Graph theoretical analysis indicates cognitive impairment in MS stems from neural disconnection

BACKGROUND

The mechanisms underlying cognitive impairment in MS are still poorly understood. However, due to the specific pathology of MS, one can expect alterations in connectivity leading to physical and cognitive impairment.

AIM

In this study we aimed at assessing connectivity differences in EEG between cognitively impaired (CI) and cognitively preserved (CP) MS patients. We also investigated the influence of the measures used to construct networks.

METHODS

We included 308 MS patients and divided them into two groups based on their cognitive score. Graph theoretical network analyses were conducted based on networks constructed using different connectivity measures, i.e. correlation, correlation in the frequency domain, coherence, partial correlation, the phase lag index and the imaginary part of coherency. The most commonly encountered network parameters were calculated and compared between the two groups using Wilcoxon's rank test. Clustering coefficients and path lengths were normalized to a randomized mean clustering coefficient and path length for each patient. False discovery rate was used to correct for the multiple comparisons and Cohen's d effect sizes are reported.

RESULTS

Coherence analysis suggests that theta and delta connectivity is significantly smaller in cognitively impaired patients. Small-worldness differences are found in networks based on correlation, theta and delta coherence and correlation in the frequency domain. Modularity was related to age but not to cognition.

CONCLUSION

Cognitive deterioration in MS is a symptom that seems to be caused by neural disconnections, probably the white matter tracts connecting both hemispheres, and leads to a wide range in network differences which can be assessed by applying GTA to EEG data. In the future, these results may lead to cheaper and more objective assessments of cognitive impairment in MS.

Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique that utilizes magnetic fluxes to alter cortical activity. Continuous theta-burst repetitive TMS (cTBS) results in long-lasting decreases in indices of cortical excitability, and alterations in performance of behavioral tasks. We investigated the effects of cTBS on cortical function via functional connectivity and graph theoretical analysis of EEG data. Thirty-one channel resting-state EEG recordings were obtained before and after 40 s of cTBS stimulation to the left primary motor cortex. Functional connectivity between nodes was assessed in multiple frequency bands using lagged max-covariance, and subsequently thresholded to construct undirected graphs. After cTBS, we find widespread decreases in functional connectivity in the alpha band. There are also simultaneous increases in functional connectivity in the high-beta bands, especially amongst anterior and interhemispheric connections. The analysis of the undirected graphs reveals that interhemispheric and interregional connections are more likely to be modulated after cTBS than local connections. There is also a shift in the topology of network connectivity, with an increase in the clustering coefficient after cTBS in the beta bands, and a decrease in clustering and increase in path length in the alpha band, with the alpha-band connectivity primarily decreased near the site of stimulation. cTBS produces widespread alterations in cortical functional connectivity, with resulting shifts in cortical network topology.

Acupuncture induces divergent alterations of functional connectivity within conventional frequency bands: evidence from MEG recordings

As an ancient Chinese healing modality which has gained increasing popularity in modern society, acupuncture involves stimulation with fine needles inserted into acupoints. Both traditional literature and clinical data indicated that modulation effects largely depend on specific designated acupoints. However, scientific representations of acupoint specificity remain controversial. In the present study, considering the new findings on the sustained effects of acupuncture and its time-varied temporal characteristics, we employed an electrophysiological imaging modality namely magnetoencephalography with a temporal resolution on the order of milliseconds. Taken into account the differential band-limited signal modulations induced by acupuncture, we sought to explore whether or not stimulation at Stomach Meridian 36 (ST36) and a nearby non-meridian point (NAP) would evoke divergent functional connectivity alterations within delta, theta, alpha, beta and gamma bands. Whole-head scanning was performed on 28 healthy participants during an eyes-closed no-task condition both preceding and following acupuncture. Data analysis involved calculation of band-limited power (BLP) followed by pair-wise BLP correlations. Further averaging was conducted to obtain local and remote connectivity. Statistical analyses revealed the increased connection degree of the left temporal cortex within delta (0.5-4 Hz), beta (13-30 Hz) and gamma (30-48 Hz) bands following verum acupuncture. Moreover, we not only validated the closer linkage of the left temporal cortex with the prefrontal and frontal cortices, but further pinpointed that such patterns were more extensively distributed in the ST36 group in the delta and beta bands compared to the restriction only to the delta band for NAP. Psychophysical results for significant pain threshold elevation further confirmed the analgesic effect of acupuncture at ST36. In conclusion, our findings may provide a new perspective to lend support for the specificity of neural expression underlying acupuncture.

Inferring functional neural connectivity with phase synchronization analysis: a review of methodology

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals.

Volume conduction effects in brain network inference from electroencephalographic recordings using phase lag index

In this paper, we test the performance of a synchronicity estimator widely applied in Neuroscience, phase lag index (PLI), for brain network inference in EEG. We implement the four sphere head model to simulate the volume conduction problem present in EEG recordings and measure the activity at the scalp of surrogate sources located at the brain level. Then, networks are estimated under the null hypothesis (independent sources) using PLI, coherence (R) and phase coherence (PC) for the volume conduction and no volume conduction (NVC) cases. It is known that R and PC are highly influenced by volume conduction, leading to the inference of clustered grid networks. PLI was designed to solve this problem. Our simulations show that PLI is partially invariant to volume conduction. The networks found by PLI show small-worldness, with a clustering coefficient higher than random networks. On the contrary, PLI-NVC obtains networks whose distribution is closer to random networks indicating that the high clustering shown by PLI networks are caused by volume conduction. The influence of volume conduction in PLI might lead to biased results in brain network inference from EEG if this behaviour is ignored.

Forming Tool Use Representations: A Neurophysiological Investigation into Tool Exposure

Prior work has identified a common left parietofrontal network for storage of tool-related information for various tasks. How these representations become established within this network on the basis of different modes of exposure is unclear. Here, healthy subjects engaged in physical practice (direct exposure) with familiar and unfamiliar tools. A separate group of subjects engaged in video-based observation (indirect exposure) of the same tools to understand how these learning strategies create representations. To assess neural mechanisms engaged for pantomime after different modes of exposure, a pantomime task was performed for both tools while recording neural activation with high-density EEG. Motor planning–related neural activation was evaluated using beta band (13–22 Hz) event-related desynchronization. Hemispheric dominance was assessed, and activation maps were generated to understand topography of activations. Comparison of conditions (effects of tool familiarity and tool exposure) was performed with standardized low-resolution brain electromagnetic tomography. Novel tool pantomime following direct exposure resulted in greater activations of bilateral parietofrontal regions. Activations following indirect training varied by tool familiarity; pantomime of the familiar tool showed greater activations in left parietofrontal areas, whereas the novel tool showed greater activations at right temporoparieto-occipital areas. These findings have relevance to the mechanisms for understanding motor-related behaviors involved in new tools that we have little or no experience with and can extend into advancing theories of tool use motor learning.

Parieto-frontal network in humans studied by cortico-cortical evoked potential

Parieto-frontal network is essential for sensorimotor integration in various complex behaviors, and its disruption is associated with pathophysiology of apraxia and visuo-spatial disorders. Despite advances in knowledge regarding specialized cortical areas for various sensorimotor transformations, little is known about the underlying cortico-cortical connectivity in humans. We investigated inter-areal connections of the lateral parieto-frontal network in vivo by means of cortico-cortical evoked potentials (CCEPs). Six patients with epilepsy and one with brain tumor were studied. With the use of subdural electrodes implanted for presurgical evaluation, network configuration was investigated by tracking the connections from the parietal stimulus site to the frontal site where the maximum CCEP was recorded. It was characterized by (i) a near-to-near and distant-to-distant, mirror symmetric configuration across the central sulcus, (ii) preserved dorso-ventral organization (the inferior parietal lobule to the ventral premotor area and the superior parietal lobule to the dorsal premotor area), and (iii) projections to more than one frontal cortical sites in 56% of explored connections. These findings were also confirmed by the standardized parieto-frontal CCEP connectivity map constructed in reference to the Jülich cytoarchitectonic atlas in the MNI standard space. The present CCEP study provided an anatomical blueprint underlying the lateral parieto-frontal network and demonstrated a connectivity pattern similar to non-human primates in the newly developed inferior parietal lobule in humans.

Cortical activities associated with voluntary movements and involuntary movements

Recent advance in non-invasive techniques including electrophysiology and functional neuroimaging has enabled investigation of control mechanism of voluntary movements and pathophysiology of involuntary movements in human. Epicortical recording with subdural electrodes in epilepsy patients complemented the findings obtained by the non-invasive techniques. Before self-initiated simple movement, activation occurs first in the pre-supplementary motor area (pre-SMA) and SMA proper bilaterally with some somatotopic organisation, and the lateral premotor area (PMA) and primary motor cortex (M1) mainly contralateral to the movement with precise somatotopic organisation. Functional connectivity among cortical areas has been disclosed by cortico-cortical coherence, cortico-cortical evoked potential, and functional MRI. Cortical activities associated with involuntary movements have been studied by jerk-locked back averaging and cortico-muscular coherence. Application of transcranial magnetic stimulation helped clarifying the state of excitability and inhibition in M1. The sensorimotor cortex (S1-M1) was shown to play an important role in generation of cortical myoclonus, essential tremor, Parkinson tremor and focal dystonia. Cortical myoclonus is actively driven by S1-M1 while essential tremor and Parkinson tremor are mediated by S1-M1. 'Negative motor areas' at PMA and pre-SMA and 'inhibitory motor areas' at peri-rolandic cortex might be involved in the control of voluntary movement and generation of negative involuntary movements, respectively.

Altered connectivity and action model formation in autism is autism

Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others' actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function.

Basal ganglia shapes predict social, communication, and motor dysfunctions in boys with autism spectrum disorder

OBJECTIVE

Basal ganglia abnormalities have been suggested as contributing to motor, social, and communicative impairments in autism spectrum disorder (ASD). Volumetric analyses offer limited ability to detect localized differences in basal ganglia structure. Our objective was to investigate basal ganglia shape abnormalities and their association with behavioral features of ASD, which may involve multiple frontal-subcortical circuits.

METHOD

Basal ganglia were manually delineated from MR images of 32 boys with ASD and 45 typically developing (TD) boys. Large deformation diffeomorphic metric mapping (LDDMM) was used to assess between-group differences in basal ganglia shape and to examine associations with motor, praxis, and reciprocal social and communicative impairments in ASD.

RESULTS

Boys with ASD showed changes in right basal ganglia shape as compared with TD boys; surface deformation was present in the caudate, putamen, and globus pallidus but did not stand up to correction for multiple comparisons. Brain-behavior correlation findings were more robust; analyses accounting for multiple comparisons revealed, in boys with ASD, surface inward deformation of the right posterior putamen predicted poorer motor skill, whereas surface inward deformation of the bilateral anterior and posterior putamen predicted poorer praxis. Surface outward deformation in the bilateral medial caudate head predicted greater reciprocal social and communicative impairment.

CONCLUSIONS

Motor, social, and communicative impairments in boys with ASD are associated with shape abnormalities in the basal ganglia. The findings suggest abnormalities within parallel frontal-subcortical circuits are differentially associated with impaired acquisition of motor and reciprocal social and communicative skills in ASD.

Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis

Transient episodes of synchronisation of neuronal activity in particular frequency ranges are thought to underlie cognition. Empirical mode decomposition phase locking (EMDPL) analysis is a method for determining the frequency and timing of phase synchrony that is adaptive to intrinsic oscillations within data, alleviating the need for arbitrary bandpass filter cut-off selection. It is extended here to address the choice of reference electrode and removal of spurious synchrony resulting from volume conduction. Spline Laplacian transformation and independent component analysis (ICA) are performed as pre-processing steps, and preservation of phase synchrony between synthetic signals, combined using a simple forward model, is demonstrated. The method is contrasted with use of bandpass filtering following the same pre-processing steps, and filter cut-offs are shown to influence synchrony detection markedly. Furthermore, an approach to the assessment of multiple EEG trials using the method is introduced, and the assessment of statistical significance of phase locking episodes is extended to render it adaptive to local phase synchrony levels. EMDPL is validated in the analysis of real EEG data, during finger tapping. The time course of event-related (de)synchronisation (ERD/ERS) is shown to differ from that of longer range phase locking episodes, implying different roles for these different types of synchronisation. It is suggested that the increase in phase locking which occurs just prior to movement, coinciding with a reduction in power (or ERD) may result from selection of the neural assembly relevant to the particular movement.

Movement gating of beta/gamma oscillations involved in the N30 somatosensory evoked potential

Evoked potential modulation allows the study of dynamic brain processing. The mechanism of movement gating of the frontal N30 component of somatosensory evoked potentials (SEP) produced by the stimulation of the median nerve at wrist remains to be elucidated. At rest, a power enhancement and a significant phase-locking of the electroencephalographic (EEG) oscillation in the beta/gamma range (25-35 Hz) are related to the emergence of the N30. The latter was also perfectly identified in presence of pure phase-locking situation. Here, we investigated the contribution of these rhythmic activities to the specific gating of the N30 component during movement. We demonstrated that concomitant execution of finger movement of the stimulated hand impinges such temporal concentration of the ongoing beta/gamma EEG oscillations and abolishes the N30 component throughout their large topographical extent on the scalp. This also proves that the phase-locking phenomenon is one of the main actors for the N30 generation. These findings could be explained by the involvement of neuronal populations of the sensorimotor cortex and other related areas, which are unable to respond to the phasic sensory activation and to phase-lock their firing discharges to the external sensory input during the movement. This new insight into the contribution of phase-locked oscillation in the emergence of the N30 and in its gating behavior calls for a reappraisal of fundamental and clinical interpretation of the frontal N30 component.

Left parietal activation related to planning, executing and suppressing praxis hand movements

OBJECTIVE

We sought to investigate the activity of bilateral parietal and premotor areas during a Go/No Go paradigm involving praxis movements of the dominant hand.

METHODS

A sentence was presented which instructed subjects on what movement to make (S1; for example, "Show me how to use a hammer."). After an 8-s delay, "Go" or "No Go" (S2) was presented. If Go, they were instructed to make the movement described in the S1 instruction sentence as quickly as possible, and continuously until the "Rest" cue was presented 3 s later. If No Go, subjects were to simply relax until the next instruction sentence. Event-related potentials (ERP) and event-related desynchronization (ERD) in the beta band (18-22 Hz) were evaluated for three time bins: after S1, after S2, and from -2.5 to -1.5 s before the S2 period.

RESULTS

Bilateral premotor ERP was greater than bilateral parietal ERP after the S2 Go compared with the No Go. Additionally, left premotor ERP was greater than that from the right premotor area. There was predominant left parietal ERD immediately after S1 for both Go and No Go, which was sustained for the duration of the interval between S1 and S2. For both S2 stimuli, predominant left parietal ERD was again seen when compared to that from the left premotor or right parietal area. However, the left parietal ERD was greater for Go than No Go.

CONCLUSION

The results suggest a dominant role in the left parietal cortex for planning, executing, and suppressing praxis movements. The ERP and ERD show different patterns of activation and may reflect distinct neural movement-related activities.

SIGNIFICANCE

The data can guide further studies to determine the neurophysiological changes occurring in apraxia patients and help explain the unique error profiles seen in patients with left parietal damage.

Update on apraxia

Apraxia is classically defined as difficulty performing learned, skilled gestures. In this review, we describe the range of motor impairments classified as apraxia, focusing on ideomotor limb apraxia. We present several prominent models of praxis to explain the variety of difficulties seen in patients with apraxia. We also discuss the large-scale frontal-parietal-basal ganglia network thought to underlie praxis. In this context, we highlight the common occurrence of limb apraxia in corticobasal degeneration, a neurodegenerative condition characterized by frontal, parietal, and basal ganglia disease.

Gesture subtype-dependent left lateralization of praxis planning: an event-related fMRI study

Ideomotor apraxia is a disorder mainly of praxis planning, and the deficit is typically more evident in pantomiming transitive (tool related) than intransitive (communicative) gestures. The goal of the present study was to assess differential hemispheric lateralization of praxis production using event-related functional magnetic resonance imaging. Voxel-based analysis demonstrated significant activations in posterior parietal cortex (PPC) and premotor cortex (PMC) association areas, which were predominantly left hemispheric, regardless of whether planning occurred for right or left hand transitive or intransitive pantomimes. Furthermore, region of interest-based calculation of mean laterality index (LI) revealed a significantly stronger left lateralization in PPC/PMC clusters for planning intransitive (LI = -0.49 + 0.10, mean + standard deviation [SD]) than transitive gestures (-0.37 + 0.08, P = 0.02, paired t-tests) irrespective of the hand involved. This differential left lateralization for planning remained significant in PMC (LI = -0.47 + 0.14 and -0.36 + 0.13, mean + SD, P = 0.04), but not in PPC (-0.56 + 0.11 and -0.45 + 0.12, P = 0.11), when both regions were analyzed separately. In conclusion, the findings point to a left-hemispheric specialization for praxis planning, being more pronounced for intransitive gestures in PMC, possibly due to their communicative nature.

Cortico-cortical networks in patients with ideomotor apraxia as revealed by EEG coherence analysis

We sought to determine whether coherent networks which circumvent lesioned cortex are seen in patients with ideomotor apraxia (IMA) while performing tool-use pantomimes. Five normal subjects and five patients with IMA (three patients with corticobasal degeneration and two with left hemisphere stroke) underwent 64-channel EEG recording while performing three tool-use pantomimes with their left hand in a self-paced manner. Beta band (20-22 Hz) coherence indicates that normal subjects have a dominant left hemisphere network responsible for praxis preparation, which was absent in patients. Corticobasal degeneration patients showed significant coherence increase between left parietal-right premotor areas. Left hemisphere stroke patients showed significant coherence increases in a right parietofrontal network. The right hemisphere appears to store useable praxis representations in IMA patients with left hemisphere damage.

Human brain mapping: hemodynamic response and electrophysiology

In view of the recent advance in functional neuroimaging, the current status of non-invasive techniques applied for human brain mapping was reviewed by integrating two principles: hemodynamic and electrophysiological, from the viewpoint of clinical neurophysiology. The currently available functional neuroimaging techniques based on hemodynamic principles are functional magnetic resonance imaging (fMRI), positron emission tomography (PET) or single-photon emission computed tomography (SPECT), and near-infrared spectroscopy (NIRS). Electrophysiological techniques include electroencephalography (EEG), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS). As for the coupling between hemodynamic response and neuronal activity (neurovascular coupling), experimental studies suggest that the hemodynamic response is significantly correlated to neuronal activity, especially local field potential (synaptic activity) rather than spiking activity, within a certain range. The hemodynamic response tends to be more widespread in space and lasts longer in time as compared with the neuronal activity. Since each technique has its own characteristic features especially in terms of spatial and temporal resolution, it is important to adopt the most appropriate technique for solving each specific question, and it is useful to combine two techniques either simultaneously or in separate sessions. As for the multi-modal approach, the combined use of EEG and MEG, EEG and PET, or EEG and fMRI is applied for the simultaneous studies, and for the separate use of two different techniques, the information obtained from fMRI is used for estimating the generator source from EEG or MEG data (fMRI-constrained source estimation). Functional connectivity among different brain areas can be studied by using a single technique such as the EEG coherence or the correlation analysis of fMRI or PET data, or by combining the stimulation technique such as TMS with neuroimaging. Further advance of each technology and improvement in the analysis method will promote the understanding of precise functional specialization and inter-areal coupling, and will contribute to the increased efficacy of rapidly developing physiological treatments of neurological and psychiatric disorders.

Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources

OBJECTIVE

To address the problem of volume conduction and active reference electrodes in the assessment of functional connectivity, we propose a novel measure to quantify phase synchronization, the phase lag index (PLI), and compare its performance to the well-known phase coherence (PC), and to the imaginary component of coherency (IC).

METHODS

The PLI is a measure of the asymmetry of the distribution of phase differences between two signals. The performance of PLI, PC, and IC was examined in (i) a model of 64 globally coupled oscillators, (ii) an EEG with an absence seizure, (iii) an EEG data set of 15 Alzheimer patients and 13 control subjects, and (iv) two MEG data sets.

RESULTS

PLI and PC were more sensitive than IC to increasing levels of true synchronization in the model. PC and IC were influenced stronger than PLI by spurious correlations because of common sources. All measures detected changes in synchronization during the absence seizure. In contrast to PC, PLI and IC were barely changed by the choice of different montages. PLI and IC were superior to PC in detecting changes in beta band connectivity in AD patients. Finally, PLI and IC revealed a different spatial pattern of functional connectivity in MEG data than PC.

CONCLUSION

The PLI performed at least as well as the PC in detecting true changes in synchronization in model and real data but, at the same token and like-wise the IC, it was much less affected by the influence of common sources and active reference electrodes.

Contribution of exploratory methods to the investigation of extended large-scale brain networks in functional MRI: methodologies, results, and challenges

A large-scale brain network can be defined as a set of segregated and integrated regions, that is, distant regions that share strong anatomical connections and functional interactions. Data-driven investigation of such networks has recently received a great deal of attention in blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). We here review the rationale for such an investigation, the methods used, the results obtained, and also discuss some issues that have to be faced for an efficient exploration.

Preparatory band specific premotor cortical activity differentiates upper and lower extremity movement

Event related desynchronization (ERD) allows evaluation of brain signals in multiple frequency dimensions. The purpose of this study was to determine left hemispheric non-primary motor cortex differences at varying frequencies of premovement ERD for similar movements by end-effectors of the upper and lower extremities. We recorded 32-channel electroencephalography (EEG) while subjects performed self-paced right ankle dorsiflexion and wrist extension. Electromyography (EMG) was recorded over the tibialis anterior and extensor carpi ulnaris. EEG was analyzed for premovement ERD within the alpha (8-12 Hz), low beta (13-18 Hz) and high beta (18-22 Hz) frequencies over the premotor, motor, and sensory areas of the left and mesial cortex from -1.5 to 0 s before movement. Within the alpha and high beta bands, wrist movements showed limited topography, but greater ERD over posterior premotor cortex areas. Alpha ERD was also significantly greater over the lateral motor cortex for wrist movements. In the low beta band, wrist movements provided extensive ERD differences to include the left motor and mesial/lateral premotor areas, whereas ankle movements showed only limited ERD activity. Overall, alpha and high beta activity demonstrated distinctions that are consistent with mapping of wrist and ankle representations over the sensorimotor strip, whereas the low beta representation demonstrated the clearest distinctions between the limbs over widespread brain areas, particularly the lateral premotor cortex. This suggests limited leg premovement activity at the dorsolateral premotor cortex. Low beta ERD may be reflect joint or limb specific preparatory activity in the premotor area. Further work is required to better evaluate the extent of this low beta activity for multiple comparative joints.