Task-related coherence and task-related spectral power changes during sequential finger movements

Post-Movement Beta Synchronization Induced by Speed Effects IHI from Ipsilateral to Contralateral Motor Cortex

Beta event-related spectral perturbation (ERSP), including bilateral movement-related beta desynchronization (MRBD) and post-movement beta synchronization (PMBS), can be evoked by unilateral speed movement. A potential correlation might exist between power (de)synchronization and interhemispheric coherence during movement execution. However, during the PMBS phase, the existence of interhemispheric coupling and the effect of speed on it are largely undiscovered. This study aimed to answer this question. In the present study, we investigated eight healthy, right-handed volunteers using a combination of electroencephalography (EEG), transcranial magnetic stimulation (TMS), and electromyography (EMG). We explored interhemispheric (directed) coherence during isotonic right index finger abduction movements at two speeds: ballistic and self-paced. We discovered that: (i) Compared to the MRBD period, interhemispheric coherence was greater during the PMBS period. Furthermore, ballistic movement induced a larger coherence during the PMBS period, but not during the MRBD period. (ii) In the MRBD phase, directed coherence from the contralateral motor cortex (CM1) to the ipsilateral motor cortex (IM1) was larger, with a reverse tendency observed during the PMBS period. Additionally, in ballistic movement, directed coherence from IM1 to CM1 was stronger and positively correlated with coherence, with no effect of speed on directed coherence detected in the MRBD phase. To advance the understanding of neural mechanisms and the causality of interhemispheric coherence during the PMBS period, we investigated the interhemispheric inhibition (IHI) from IM1 to CM1 at different speeds. A stronger IHI from IM1 to CM1 at PMBS peak time was demonstrated, which was enhanced during ballistic movement. Additionally, IHI was negatively correlated with PMBS, and movement speed was positively associated with interhemispheric coupling during the PMBS period and IHI from IM1 to CM1.Significance Statement The present study explored interhemispheric (directed)coherence during isotonic right index finger abduction movements at two speeds: ballistic and self-paced. We discovered a dominance of interhemispheric coherence during the PMBS period of ballistic movement. Furthermore, directed coherence from the CM1 to the IM1 was more predominant in the MRBD phase, with a reverse tendency observed during the PMBS period. Additionally, directed coherence from IM1 to CM1 was stronger and positively correlated with coherence in ballistic movement. Advanced exploration revealed a stronger IHI from IM1 to CM1 at PMBS peak time, which was enhanced during ballistic movement. Additionally, IHI was negatively correlated with PMBS, and movement speed was positively associated with interhemispheric coupling during the PMBS period and IHI.

The polarity of high-definition transcranial direct current stimulation affects the planning and execution of movement sequences

Noninvasive brain stimulation of the primary motor cortex has been shown to alter therapeutic outcomes in stroke and other neurological conditions, but the precise mechanisms remain poorly understood. Determining the impact of such neurostimulation on the neural processing supporting motor control is a critical step toward further harnessing its therapeutic potential in multiple neurological conditions affecting the motor system. Herein, we leverage the excellent spatio-temporal precision of magnetoencephalographic (MEG) imaging to identify the spectral, spatial, and temporal effects of high-definition transcranial direct current stimulation (HD-tDCS) on the neural responses supporting motor control. Participants (N = 67) completed three HD-tDCS visits (anode, cathode, sham), with each involving 20 min of left primary motor cortex stimulation and performance of a simple/complex motor sequencing task during MEG. Whole-brain statistical analyses of beta oscillatory responses revealed stimulation-by-task interaction effects in the left primary motor cortex, right occipitotemporal, and the right dorsolateral prefrontal cortices. Broadly, anodal stimulation induced significantly stronger beta oscillatory responses in these regions during simple movement sequences, while neural responses to complex sequences were not affected by stimulation. En masse, these data suggest that the beta oscillations serving motor planning (i.e., pre-movement) are particularly sensitive to the polarity of noninvasive stimulation and that the impact varies based on the difficulty of the movement sequence.

Long-term motor learning in focal hand dystonia

OBJECTIVE

Because focal hand dystonia usually occurs in the over-learned stage, it would be valuable to know long-term motor learning characteristics and underlying pathophysiological features that might predispose to dystonia.

METHODS

We conducted a case-control exploratory study of 15 visits over 12 weeks in the non-affected hand of a 4-finger sequence of 8 key presses in eight patients with FHD compared with eight age- and sex-matched, healthy volunteers (HVs). We studied the behavioral data and the physiological changes of the brain, including motor cortical excitability and cortical oscillations.

RESULTS

There was no significant difference in the time to reach 100 % accuracy between FHD and HV during the 80-day follow-up period. There was a statistically significant difference in the accuracy of sequential finger movement tasks between patients with FHD compared with HVs over 12 weeks, but post-hoc analysis with multiple comparion correction did not show difference. There were no significant differences in recruitment curve changes and task-related power changes of alpha and beta bands.

CONCLUSION

Over 12 weeks, FHD have motor learning capacity comparable to HVs and do not show pathophysiological abnormalities.

SIGNIFICANCE

Further studies would be valuable with more patients, more extended periods of practice, and more detailed electrophysiological explorations.

A Visuo-Haptic System for Nodule Detection Training: Insights From EEG and Behavioral Analysis

Medical palpation is a key skill for clinicians. It is typically trained using animal and synthetic models, which however raise ethical concerns and produce high volumes of consumables. An alternative could be visuo-haptic simulations, despite their training efficacy has not been proved yet. The assessment of palpatory skills requires objective methods, that can be achieved by combining performance metrics with electroencephalography (EEG). The goals of this study were to: (i) develop a visuo-haptic system to train nodule detection, combining a Geomagic Touch haptic device with a visuo-haptic simulation of a skin patch and a nodule, implemented using SOFA framework; (ii) assess whether this system could be used for training and evaluation. To do so, we collected performance and EEG data of 19 subjects performing multiple repetitions of a nodule detection task. Results revealed that participants could be divided in low and high performers; the former applied a greater pressure when looking for the nodule and showed a higher EEG alpha (8.5 - 13 ) peak at rest; The latter explored the skin remaining on its surface and were characterized by low alpha power. Furthermore, alpha power positively correlated with error and negatively with palpation depth. Altogether, these results suggest that alpha power might be an indicator of performance, denoting an increase in vigilance, attention, information processing, cognitive processes, and engagement, ultimately affecting strategy and performance. Also, the combination of EEG with performance data can provide an objective measure of the user's palpation ability.

Cross-hemispheric recruitment during action planning with increasing task demand

The recruitment of cross-hemispheric counterparts of lateralized prefrontal brain regions with increasing processing demand is thought to increase memory performance despite cognitive aging, but was recently reported to be present also in young adults working at their capacity limit. Here we ask if cross-hemispheric recruitment is a general strategy of the adult brain in that executive task demand would modulate bilateral activation beyond prefrontal cortex and across cognitive tasks. We analyzed data sets from two fMRI experiments investigating retrospective working memory maintenance and prospective action planning. We confirmed a cross-hemispheric recruitment of prefrontal cortex across tasks and experiments. Changes in lateralization due to planning further surfaced in the cerebellum, dorsal premotor and posterior parietal cortex. Parietal cortex thereby exhibited cross-hemispheric recruitment also during spatial but not verbal working memory maintenance. Our results confirm a domain-general role of prefrontal cortex in cross-hemispheric recruitment. They further suggest that other task-specific brain regions also recruit their idling cross-hemispheric counterparts to relocate executive processing power.

Characteristics of EEG power spectra involved in the proficiency of motor learning

Neuromodulation techniques for modulating brain activity can affect performance in a variety of behaviors. Techniques including transcranial alternating current stimulation and random noise stimulation can modulate neural oscillations. However, the intervention effect of neuromodulation approaches on motor learning is poor, partly because the electroencephalography (EEG) power spectra associated with the motor learning process has not yet been fully elucidated. Therefore, we investigated the characteristics of EEG power spectra in the process of motor learning in 15 right-handed healthy participants (5 females; mean age = 22.8 ± 3.0 years). The motor task was a ball-rotation task in which participants rotated two balls in the palm of their left hand. Participants performed a pre-test, the motor learning tasks, and a post-test. In the motor learning tasks, twenty 60 s trials were performed in the clockwise (CW) direction. Before and after the motor learning tasks, CW and counterclockwise (CCW; control condition) tasks were performed for 60 s each as pre- and post-tests. Therefore, CW direction was set as a motor learning task, while CCW was a test-only control task. EEG was recorded during the tests and tasks, and the power spectra in the alpha, beta, and gamma oscillations were calculated and compared between pre- and post-tests. The results showed that in the CW post-test, the power of the gamma band in the left parietal areas and the right frontal area was significantly higher than in the pre-test. In the CCW, there was no significant difference in each band at each area between the pre- and post-tests. Our findings reveal the characteristics of the EEG spectra related to the motor learning process. These results may help to establish more effective neuromodulation approaches to modifying neural oscillations in motor learning, including in rehabilitation fields.

Investigating the Application of Graph Theory Features in Hand Movement Directions Decoding using EEG Signals

In recent years, functional analysis of brain networks based on graph theory properties has attracted considerable attention. This approach has usually been exploited for structural and functional brain analysis, while its potential in motor decoding tasks has remained unexplored. This study aimed to investigate the feasibility of using graph-based features in hand direction decoding in movement execution and preparation intervals. Hence, EEG signals were recorded from nine healthy subjects while performing a four-target center-out reaching task. The functional brain network was calculated based on the magnitude squared coherence (MSC) at six frequency bands. Then, the features based on eight graph theory metrics were extracted from brain networks. The classification was performed with a support vector machine classifier. The results revealed that in four-class direction discrimination, the mean accuracy of the graph-based method surpassed 63% and 53% on movement and pre-movement data, respectively. Additionally, a feature fusion approach that combines the graph theory features with power features was proposed. The fusion method raised the classification accuracy to 70.8% and 61.2% for movement and pre-movement intervals, respectively. This work has verified the feasibility of using graph theory properties and their superiority over band power features in a hand movement decoding task.

Differential Effects of Transcranial Static Magnetic Stimulation Over Left and Right Dorsolateral Prefrontal Cortex on Brain Oscillatory Responses During a Working Memory Task

Transcranial static magnetic stimulation (tSMS) is known to influence behavioral and neural activities. However, although the left and right dorsolateral prefrontal cortex (DLPFC) are associated with different cognitive functions, there remains a lack of knowledge on a difference in the effects of tSMS on cognitive performance and related brain activity between left and right DLPFC stimulations. To address this knowledge gap, we examined how differently tSMS over the left and right DLPFC altered working memory performance and electroencephalographic oscillatory responses using a 2-back task, in which subjects monitor a sequence of stimuli and decide whether a presented stimulus matches the stimulus presented two trials previously. Fourteen healthy adults (five females) performed the 2-back task before, during (20 min after the start of stimulation), immediately after, and 15 min after three different stimulation conditions: tSMS over the left DLPFC, tSMS over the right DLPFC, and sham stimulation. Our preliminary results revealed that while tSMS over the left and right DLPFC impaired working memory performance to a similar extent, the impacts of tSMS on brain oscillatory responses were different between the left and right DLPFC stimulations. Specifically, tSMS over the left DLPFC increased the event-related synchronization in beta band whereas tSMS over the right DLPFC did not show such an effect. These findings support evidence that the left and right DLPFC play different roles in working memory and suggest that the neural mechanism underlying the impairment of working memory by tSMS can be different between left and right DLPFC stimulations.

Bilateral Sensorimotor Cortical Communication Modulated by Multiple Hand Training in Stroke Participants: A Single Training Session Pilot Study

Bi-manual therapy (BT), mirror therapy (MT), and robot-assisted rehabilitation have been conducted in hand training in a wide range of stages in stroke patients; however, the mechanisms of action during training remain unclear. In the present study, participants performed hand tasks under different intervention conditions to study bilateral sensorimotor cortical communication, and EEG was recorded. A multifactorial design of the experiment was used with the factors of manipulating objects (O), robot-assisted bimanual training (RT), and MT. The sum of spectral coherence was applied to analyze the C3 and C4 signals to measure the level of bilateral corticocortical communication. We included stroke patients with onset <6 months (n = 6), between 6 months and 1 year (n = 14), and onset >1 year (n = 20), and their Brunnstrom recovery stage ranged from 2 to 4. The results showed that stroke duration might influence the effects of hand rehabilitation in bilateral cortical corticocortical communication with significant main effects under different conditions in the alpha and beta bands. Therefore, stroke duration may influence the effects of hand rehabilitation on interhemispheric coherence.

Continuous Decoding of Hand Movement From EEG Signals Using Phase-Based Connectivity Features

The principal goal of the brain-computer interface (BCI) is to translate brain signals into meaningful commands to control external devices or neuroprostheses to restore lost functions of patients with severe motor disabilities. The invasive recording of brain signals involves numerous health issues. Therefore, BCIs based on non-invasive recording modalities such as electroencephalography (EEG) are safer and more comfortable for the patients. The BCI requires reconstructing continuous movement parameters such as position or velocity for practical application of neuroprostheses. The BCI studies in continuous decoding have extensively relied on extracting features from the amplitude of brain signals, whereas the brain connectivity features have rarely been explored. This study aims to investigate the feasibility of using phase-based connectivity features in decoding continuous hand movements from EEG signals. To this end, the EEG data were collected from seven healthy subjects performing a 2D center-out hand movement task in four orthogonal directions. The phase-locking value (PLV) and magnitude-squared coherence (MSC) are exploited as connectivity features along with multiple linear regression (MLR) for decoding hand positions. A brute-force search approach is employed to find the best channel pairs for extracting features related to hand movements. The results reveal that the regression models based on PLV and MSC features achieve the average Pearson correlations of 0.43 ± 0.03 and 0.42 ± 0.06, respectively, between predicted and actual trajectories over all subjects. The delta and alpha band features have the most contribution in regression analysis. The results also demonstrate that both PLV and MSC decoding models lead to superior results on our data compared to two recently proposed feature extraction methods solely based on the amplitude or phase of recording signals (p < 0.05). This study verifies the ability of PLV and MSC features in the continuous decoding of hand movements with linear regression. Thus, our findings suggest that extracting features based on brain connectivity can improve the accuracy of trajectory decoder BCIs.

The Prognostic Utility of Electroencephalography in Stroke Recovery: A Systematic Review and Meta-Analysis

BACKGROUND

Improved ability to predict patient recovery would guide post-stroke care by helping clinicians personalize treatment and maximize outcomes. Electroencephalography (EEG) provides a direct measure of the functional neuroelectric activity in the brain that forms the basis for neuroplasticity and recovery, and thus may increase prognostic ability.

OBJECTIVE

To examine evidence for the prognostic utility of EEG in stroke recovery via systematic review/meta-analysis.

METHODS

Peer-reviewed journal articles that examined the relationship between EEG and subsequent clinical outcome(s) in stroke were searched using electronic databases. Two independent researchers extracted data for synthesis. Linear meta-regressions were performed across subsets of papers with common outcome measures to quantify the association between EEG and outcome.

RESULTS

75 papers were included. Association between EEG and clinical outcomes was seen not only early post-stroke, but more than 6 months post-stroke. The most studied prognostic potential of EEG was in predicting independence and stroke severity in the standard acute stroke care setting. The meta-analysis showed that EEG was associated with subsequent clinical outcomes measured by the Modified Rankin Scale, National Institutes of Health Stroke Scale, and Fugl-Meyer Upper Extremity Assessment (r = .72, .70, and .53 from 8, 13, and 12 papers, respectively). EEG improved prognostic abilities beyond prediction afforded by standard clinical assessments. However, the EEG variables examined were highly variable across studies and did not converge.

CONCLUSIONS

EEG shows potential to predict post-stroke recovery outcomes. However, evidence is largely explorative, primarily due to the lack of a definitive set of EEG measures to be used for prognosis.

Unimanual sensorimotor learning-A simultaneous EEG-fMRI aging study

Sensorimotor coordination requires orchestrated network activity in the brain, mediated by inter‐ and intra‐hemispheric interactions that may be affected by aging‐related changes. We adopted a theoretical model, according to which intra‐hemispheric inhibition from premotor to primary motor cortex is mandatory to compensate for inter‐hemispheric excitation through the corpus callosum. To test this as a function of age we acquired electroencephalography (EEG) simultaneously with functional magnetic resonance imaging (fMRI) in two groups of healthy adults (younger N = 13: 20–25 year and older N = 14: 59–70 year) while learning a unimanual motor task. On average, quality of performance of older participants stayed significantly below that of the younger ones. Accompanying decreases in motor‐event‐related EEG β‐activity were lateralized toward contralateral motor regions, albeit more so in younger participants. In this younger group, the mean β‐power during motor task execution was significantly higher in bilateral premotor areas compared to the older adults. In both groups, fMRI blood oxygen level dependent (BOLD) signals were positively correlated with source‐reconstructed β‐amplitudes: positive in primary motor and negative in premotor cortex. This suggests that β‐amplitude modulation is associated with primary motor cortex “activation” (positive BOLD response) and premotor “deactivation” (negative BOLD response). Although the latter results did not discriminate between age groups, they underscore that enhanced modulation in primary motor cortex may be explained by a β‐associated excitatory crosstalk between hemispheres.

EEG as a marker of brain plasticity in clinical applications

Neural networks are dynamic, and the brain has the capacity to reorganize itself. This capacity is named neuroplasticity and is fundamental for many processes ranging from learning and adaptation to new environments to the response to brain injuries. Measures of brain plasticity involve several techniques, including neuroimaging and neurophysiology. Electroencephalography, often used together with other techniques, is a common tool for prognostic and diagnostic purposes, and cortical reorganization is reflected by EEG measurements. Changes of power bands in different cortical areas occur with fatigue and in response to training stimuli leading to learning processes. Sleep has a fundamental role in brain plasticity, restoring EEG bands alterations and promoting consolidation of learning. Exercise and physical inactivity have been extensively studied as both strongly impact brain plasticity. Indeed, EEG studies showed the importance of the physical activity to promote learning and the effects of inactivity or microgravity on cortical reorganization to cope with absent or altered sensorimotor stimuli. Finally, this chapter will describe some of the EEG changes as markers of neural plasticity in neurologic conditions, focusing on cerebrovascular and neurodegenerative diseases. In conclusion, neuroplasticity is the fundamental mechanism necessary to ensure adaptation to new stimuli and situations, as part of the dynamicity of life.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.

A Single Bout of High-Intensity Cardiovascular Exercise Does Not Enhance Motor Performance and Learning of a Visuomotor Force Modulation Task, but Triggers Ipsilateral Task-Related EEG Activity

Acute cardiovascular exercise (aCE) seems to be a promising strategy to improve motor performance and learning. However, results are heterogeneous, and the related neurophysiological mechanisms are not well understood. Oscillatory brain activitiy, such as task-related power (TRPow) in the alpha and beta frequencies, are known neural signatures of motor activity. Here, we tested the effects of aCE on motor performance and learning, along with corresponding modulations in EEG TRPow over the sensorimotor cortex. Forty-five right-handed participants (aged 18-34 years) practiced a visuomotor force-matching (FM) task after either high-intensity (HEG), low-intensity (LEG), or no exercise (control group, CG). Motor performance was assessed immediately, 15 min, 30 min, and 24 h after aCE/control. EEG was measured during the FM task. Results of frequentist and Bayesian statistics revealed that high- and low-intensity aCE had no effect at the behavioral level, adding to the previous mixed results. Interestingly, EEG analyses showed an effect of aCE on the ipsilateral sensorimotor cortex, with a stronger decrease in β-TRPow 15 min after exercise in both groups compared to the CG. Overall, aCE applied before motor practice increased ipsilateral sensorimotor activity, while motor learning was not affected; it remains to be seen whether aCE might affect motor learning in the long run.

Ageing and the Ipsilateral M1 BOLD Response: A Connectivity Study

Young people exhibit a negative BOLD response in ipsilateral primary motor cortex (M1) when making unilateral movements, such as button presses. This negative BOLD response becomes more positive as people age. In this study, we investigated why this occurs, in terms of the underlying effective connectivity and haemodynamics. We applied dynamic causal modeling (DCM) to task fMRI data from 635 participants aged 18-88 from the Cam-CAN dataset, who performed a cued button pressing task with their right hand. We found that connectivity from contralateral supplementary motor area (SMA) and dorsal premotor cortex (PMd) to ipsilateral M1 became more positive with age, explaining 44% of the variability across people in ipsilateral M1 responses. In contrast, connectivity from contralateral M1 to ipsilateral M1 was weaker and did not correlate with individual differences in rM1 BOLD. Neurovascular and haemodynamic parameters in the model were not able to explain the age-related shift to positive BOLD. Our results add to a body of evidence implicating neural, rather than vascular factors as the predominant cause of negative BOLD-while emphasising the importance of inter-hemispheric connectivity. This study provides a foundation for investigating the clinical and lifestyle factors that determine the sign and amplitude of the M1 BOLD response in ageing, which could serve as a proxy for neural and vascular health, via the underlying neurovascular mechanisms.

Complexity-Dependent Modulations of Beta Oscillations for Verbal and Nonverbal Movements

Purpose The planning and execution of motor behaviors require coordination of neurons that are established through synchronization of neural activity. Movements are typically preceded by event-related desynchronization (ERD) in the beta range (15-30 Hz) primarily localized in the motor cortex, while movement onset is associated with event-related synchronization (ERS). It is hypothesized that ERD is important for movement preparation and execution, and ERS serves to inhibit movement and update the motor plan. The primary objective of this study was to determine to what extent movement-related oscillatory brain patterns (ERD and ERS) during verbal and nonverbal tasks may be affected differentially by variations in task complexity. Method Seventeen right-handed adult participants (nine women, eight men; M _age = 25.8 years, SD = 5.13) completed a sequential button press and verbal task. The final analyses included data for 15 participants for the nonverbal task and 13 for the verbal task. Both tasks consisted of two complexity levels: simple and complex sequences. Magnetoencephalography was used to record modulations in beta band brain oscillations during task performance. Results Both the verbal and button press tasks were characterized by significant premovement ERD and postmovement ERS. However, only simple sequences showed a distinct transient synchronization during the premovement phase of the task. Differences between the two tasks were reflected in both latency and peak amplitude of ERD and ERS, as well as in lateralization of oscillations. Conclusions Both verbal and nonverbal movements showed a significant desynchronization of beta oscillations during the movement preparation and holding phase and a resynchronization upon movement termination. Importantly, the premovement phase for simple but not complex tasks was characterized by a transient partial synchronization. In addition, the data revealed significant differences between the two tasks in terms of lateralization of oscillatory modulations. Our findings suggest that, while data from the general motor control research can inform our understanding of speech motor control, significant differences exist between the two motor systems that caution against overgeneralization of underlying neural control processes.

Alpha and beta neural oscillations differentially reflect age-related differences in bilateral coordination

Bilateral in-phase (IP) and anti-phase (AP) movements represent two fundamental modes of bilateral coordination that are essential for daily living. Although previous studies have shown that aging is behaviorally associated with decline in bilateral coordination, especially in AP movements, the underlying neural mechanisms remain unclear. Here, we use kinematic measurements and electroencephalography to compare motor performance of young and older adults executing bilateral IP and AP hand movements. On the behavioral level, inter-limb synchronization was reduced during AP movements compared to IP and this reduction was stronger in the older adults. On the neural level, we found interactions between group and condition for task-related power change in different frequency bands. The interaction was driven by smaller alpha power decreases over the non-dominant cortical motor area in young adults during IP movements and larger beta power decreases over the midline region in older adults during AP movements. In addition, the decrease in inter-limb synchronization during AP movements was predicted by stronger directional connectivity in the beta-band: an effect more pronounced in older adults. Our results therefore show that age-related differences in the two bilateral coordination modes are reflected on the neural level by differences in alpha and beta oscillatory power as well as interhemispheric directional connectivity.

Neural Correlates of Motor Skill Learning Are Dependent on Both Age and Task Difficulty

Although a general age-related decline in neural plasticity is evident, the effects of age on neural plasticity after motor practice are inconclusive. Inconsistencies in the literature may be related to between-study differences in task difficulty. Therefore, we aimed to determine the effects of age and task difficulty on motor learning and associated brain activity. We used task-related electroencephalography (EEG) power in the alpha (8–12 Hz) and beta (13–30 Hz) frequency bands to assess neural plasticity before, immediately after, and 24-h after practice of a mirror star tracing task at one of three difficulty levels in healthy younger (19–24 yr) and older (65–86 yr) adults. Results showed an age-related deterioration in motor performance that was more pronounced with increasing task difficulty and was accompanied by a more bilateral activity pattern for older vs. younger adults. Task difficulty affected motor skill retention and neural plasticity specifically in older adults. Older adults that practiced at the low or medium, but not the high, difficulty levels were able to maintain improvements in accuracy at retention and showed modulation of alpha TR-Power after practice. Together, these data indicate that both age and task difficulty affect motor learning, as well as the associated neural plasticity.

Electrical Brain Activity and Its Functional Connectivity in the Physical Execution of Modern Jazz Dance

Besides the pure pleasure of watching a dance performance, dance as a whole-body movement is becoming increasingly popular for health-related interventions. However, the science-based evidence for improvements in health or well-being through dance is still ambiguous and little is known about the underlying neurophysiological mechanisms. This may be partly related to the fact that previous studies mostly examined the neurophysiological effects of imagination and observation of dance rather than the physical execution itself. The objective of this pilot study was to investigate acute effects of a physically executed dance with its different components (recalling the choreography and physical activity to music) on the electrical brain activity and its functional connectivity using electroencephalographic (EEG) analysis. Eleven dance-inexperienced female participants first learned a Modern Jazz Dance (MJD) choreography over three weeks (1 h sessions per week). Afterwards, the acute effects on the EEG brain activity were compared between four different test conditions: physically executing the MJD choreography with music, physically executing the choreography without music, imaging the choreography with music, and imaging the choreography without music. Every participant passed each test condition in a randomized order within a single day. EEG rest-measurements were conducted before and after each test condition. Considering time effects the physically executed dance without music revealed in brain activity analysis most increases in alpha frequency and in functional connectivity analysis in all frequency bands. In comparison, physically executed dance with music as well as imagined dance with music led to fewer increases and imagined dance without music provoked noteworthy brain activity and connectivity decreases at all frequency bands. Differences between the test conditions were found in alpha and beta frequency between the physically executed dance and the imagined dance without music as well as between the physically executed dance with and without music in the alpha frequency. The study highlights different effects of a physically executed dance compared to an imagined dance on many brain areas for all measured frequency bands. These findings provide first insights into the still widely unexplored field of neurological effects of dance and encourages further research in this direction.

Menstrual Cycle Modulates Motor Learning and Memory Consolidation in Humans

Numerous studies have noted that sex and/or menstrual phase influences cognitive performance (in particular, declarative memory), but the effects on motor learning (ML) and procedural memory/consolidation remain unclear. In order to test the hypothesis that ML differs across menstrual cycle phases, initial ML, overlearning, consolidation, and final performance were assessed in women in the follicular, preovulation and luteal phases. Primary motor cortex (M1) oscillations were assessed neuro-physiologically, and premenstrual syndrome and interoceptive awareness scores were assessed psychologically. We found not only poorer performance gain through initial ML but also lower final performance after overlearning a day and a week later in the luteal group than in the ovulation group. This behavioral difference could be explained by particular premenstrual syndrome symptoms and associated failure of normal M1 excitability in the luteal group. In contrast, the offline effects, i.e., early and late consolidation, did not differ across menstrual cycle phases. These results provide information regarding the best time in which to start learning new sensorimotor skills to achieve expected gains.

Comparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation

Modulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli. Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants. Both tactile and proprioceptive stimulus produced a clear suppression at 300-350 ​ms followed by a subsequent rebound at 700-900 ​ms after stimulus onset, detected at similar latencies both with MEG and EEG. The relative amplitudes of suppression and rebound correlated strongly between MEG and EEG recordings. However, the relative strength of suppression and rebound in the contralateral hemisphere (with respect to the stimulated hand) was significantly stronger in MEG than in EEG recordings. Our results indicate that MEG recordings produced signals with higher signal-to-noise ratio than EEG, favoring MEG as an optimal tool for studies evaluating sensorimotor cortical functions. However, the strong correlation between MEG and EEG results encourages the use of EEG when translating studies to clinical practice. The clear advantage of EEG is the availability of the method in hospitals and bed-side measurements at the acute phase.

Task-Modulated Corticocortical Synchrony in the Cognitive-Motor Network Supporting Handwriting

Both motor and cognitive aspects of behavior depend on dynamic, accurately timed neural processes in large-scale brain networks. Here, we studied synchronous interplay between cortical regions during production of cognitive-motor sequences in humans. Specifically, variants of handwriting that differed in motor variability, linguistic content, and memorization of movement cues were contrasted to unveil functional sensitivity of corticocortical connections. Data-driven magnetoencephalography mapping (n = 10) uncovered modulation of mostly left-hemispheric corticocortical interactions, as quantified by relative changes in phase synchronization. At low frequencies (~2–13 Hz), enhanced frontoparietal synchrony was related to regular handwriting, whereas premotor cortical regions synchronized for simple loop production and temporo-occipital areas for a writing task substituting normal script with loop patterns. At the beta-to-gamma band (~13–45 Hz), enhanced synchrony was observed for regular handwriting in the central and frontoparietal regions, including connections between the sensorimotor and supplementary motor cortices and between the parietal and dorsal premotor/precentral cortices. Interpreted within a modular framework, these modulations of synchrony mainly highlighted interactions of the putative pericentral subsystem of hand coordination and the frontoparietal subsystem mediating working memory operations. As part of cortical dynamics, interregional phase synchrony varies depending on task demands in production of cognitive-motor sequences.

Neurophysiological Correlates of Adaptation and Interference during Asymmetrical Bimanual Movements

In this study, we investigated brain dynamics during interference between hands during bimanual movements. Participants performed a bimanual center-out reaching task in which a visuomotor rotation was applied to the right hand while the left hand did not receive visual feedback of its movements. This manipulation resulted in interference from the adapting right hand to the kinesthetically guided left hand. Electroencephalography (EEG) recordings during the task showed that spectral power in the high and low beta frequency bands was elevated early in exposure, but decreased throughout learning. This may be representative of error-based updating of internal models of movement. Additionally, coherence, a measure of neural functional connectivity, was elevated both within and between hemispheres in the beta frequencies during the initial presentation of the visuomotor rotation, and then decreased throughout adaptation. This suggests that beta oscillatory neural activity may be marker for transmission of conflicting motor information between hemispheres, which manifests in interference between the hands during asymmetrical bimanual movements.

Task-specific interhemispheric hypoconnectivity in writer's cramp - An EEG study

OBJECTIVE

Writer's cramp (WC) is a focal task-specific dystonia characterized by abnormal posturing of the hand muscles during handwriting, but not during other tasks that involve the same set of muscles and objects such as sharpening a pencil. Our objective was to investigate the pathophysiology underlying the task specificity of this disorder using EEG. We hypothesized that premotor-parietal connectivity will be lower in WC patients specifically during handwriting and motor imagery of handwriting.

METHODS

We recruited 15 WC patients and 15 healthy controls. EEG was recorded while participants performed 4 tasks - writing with a pencil, sharpening a pencil, imagining writing and imagining sharpening. We determined the connectivity changes between relevant brain regions during these tasks.

RESULTS

We found reduced interhemispheric alpha coherence in the sensorimotor areas in WC patients exclusively during handwriting. WC patients also showed less reduction of task-related beta spectral power and a trend for reduced premotor-parietal coherence during motor tasks.

CONCLUSION

We could not confirm an abnormality in premotor-parietal connectivity specific to handwriting by this method. However, there was a task-specific reduction in interhemispheric alpha connectivity in WC patients, whose behavioral correlate remains unknown.

SIGNIFICANCE

Interhemispheric alpha connectivity can be a potential interventional target in WC.

Cerebral hemodynamic changes during motor imagery and passive robot-assisted movement of the lower limbs

BACKGROUND

Neurovascular Coupling is the cerebral mechanism responsible for linking neuronal activity, cerebral metabolism and regional cerebral blood flow (CBF). The direct relation between functional brain activity during active, passive and motor imagery paradigms and changes in CBF has been widely investigated using different techniques. However, CBF changes have not been investigated beat by beat during robot assisted passive movement (PM) and motor imagery (MI) of lower limb, yet.

MATERIALS AND METHODS

We investigated beat-to-beat hemodynamic changes in 8 healthy subjects using TCD during MI and robot-assisted PM of lower limb.

RESULTS

The results showed that MI and PM induce a significant CBFv increase and that PM and MI lead to similar hemodynamic changes in healthy subjects.

CONCLUSIONS

The findings may be useful to better understand the variation of CBFv in brain pathology and to develop more specific and efficient rehabilitation therapy protocols in neurological diseases, such as stroke.

Human motor cortical beta bursts relate to movement planning and response errors

Motor cortical beta activity (13-30 Hz) is a hallmark signature of healthy and pathological movement, but its behavioural relevance remains unclear. Using high-precision magnetoencephalography (MEG), we show that during the classical event-related desynchronisation (ERD) and event-related synchronisation (ERS) periods, motor cortical beta activity in individual trials (n > 12,000) is dominated by high amplitude, transient, and infrequent bursts. Beta burst probability closely matched the trial-averaged beta amplitude in both the pre- and post-movement periods, but individual bursts were spatially more focal than the classical ERS peak. Furthermore, prior to movement (ERD period), beta burst timing was related to the degree of motor preparation, with later bursts resulting in delayed response times. Following movement (ERS period), the first beta burst was delayed by approximately 100 milliseconds when an incorrect response was made. Overall, beta burst timing was a stronger predictor of single trial behaviour than beta burst rate or single trial beta amplitude. This transient nature of motor cortical beta provides new constraints for theories of its role in information processing within and across cortical circuits, and its functional relevance for behaviour in both healthy and pathological movement.

Individual-Specific Classification of Mental Workload Levels Via an Ensemble Heterogeneous Extreme Learning Machine for EEG Modeling

In a human–machine cooperation system, assessing the mental workload (MW) of the human operator is quite crucial to maintaining safe operation conditions. Among various MW indicators, electroencephalography (EEG) signals are particularly attractive because of their high temporal resolution and sensitivity to the occupation of working memory. However, the individual difference of the EEG feature distribution may impair the machine-learning based MW classifier. In this paper, we employed a fast-training neural network, extreme learning machine (ELM), as the basis to build an individual-specific classifier ensemble to recognize binary MW. To improve the diversity of the classification committee, heterogeneous member classifiers were adopted by fusing multiple ELMs and Bayesian models. Specifically, a deep network structure was applied in each weak model aiming at finding informative EEG feature representations. The structure of hyper-parameters of the proposed heterogeneous ensemble ELM (HE-ELM) was then identified and then its performance was compared against several competitive MW classifiers. We found that the HE-ELM model was superior for improving the individual-specific accuracy of MW assessments.

The functional role of beta-oscillations in the supplementary motor area during reaching and grasping after stroke: A question of structural damage to the corticospinal tract

Hand motor function is often severely affected in stroke patients. Non-satisfying recovery limits reintegration into normal daily life. Understanding stroke-related network changes and identifying common principles that might underlie recovered motor function is a prerequisite for the development of interventional therapies to support recovery. Here, we combine the evaluation of functional activity (multichannel electroencephalography) and structural integrity (diffusion tensor imaging) in order to explain the degree of residual motor function in chronic stroke patients. By recording neural activity during a reaching and grasping task that mimics activities of daily living, the study focuses on deficit-related neural activation patterns. The study showed that the functional role of movement-related beta desynchronization in the supplementary motor area (SMA) for residual hand motor function in stroke patients depends on the microstructural integrity of the corticospinal tract (CST). In particular, in patients with damaged CST, stronger task-related activity in the SMA was associated with worse residual motor function. Neither CST damage nor functional brain activity alone sufficiently explained residual hand motor function. The findings suggest a central role of the SMA in the motor network during reaching and grasping in stroke patients, the degree of functional relevance of the SMA is depending on CST integrity.

Walking to your right music: a randomized controlled trial on the novel use of treadmill plus music in Parkinson's disease

BACKGROUND

Rhythmic Auditory Stimulation (RAS) can compensate for the loss of automatic and rhythmic movements in patients with idiopathic Parkinson's disease (PD). However, the neurophysiological mechanisms underlying the effects of RAS are still poorly understood. We aimed at identifying which mechanisms sustain gait improvement in a cohort of patients with PD who practiced RAS gait training.

METHODS

We enrolled 50 patients with PD who were randomly assigned to two different modalities of treadmill gait training using GaitTrainer3 with and without RAS (non_RAS) during an 8-week training program. We measured clinical, kinematic, and electrophysiological effects of both the gait trainings.

RESULTS

We found a greater improvement in Functional Gait Assessment (p < 0.001), Tinetti Falls Efficacy Scale (p < 0.001), Unified Parkinson Disease Rating Scale (p = 0.001), and overall gait quality index (p < 0.001) following RAS than non_RAS training. In addition, the RAS gait training induced a stronger EEG power increase within the sensorimotor rhythms related to specific periods of the gait cycle, and a greater improvement of fronto-centroparietal/temporal electrode connectivity than the non_RAS gait training.

CONCLUSIONS

The findings of our study suggest that the usefulness of cueing strategies during gait training consists of a reshape of sensorimotor rhythms and fronto-centroparietal/temporal connectivity. Restoring the internal timing mechanisms that generate and control motor rhythmicity, thus improving gait performance, likely depends on a contribution of the cerebellum. Finally, identifying these mechanisms is crucial to create patient-tailored, RAS-based rehabilitative approaches in PD.

TRIAL REGISTRATION

NCT03434496 . Registered 15 February 2018, retrospectively registered.

Transcranial Alternating Current Stimulation Has Frequency-Dependent Effects on Motor Learning in Healthy Humans

It is well established that the primary motor cortex (M1) plays a significant role in motor learning in healthy humans. It is unclear, however, whether mechanisms of motor learning include M1 oscillatory activity. In this study, we aimed to test whether M1 oscillations, entrained by transcranial Alternating Current Stimulation (tACS) at motor resonant frequencies, have any effect on motor acquisition and retention during a rapid learning task, as assessed by kinematic analysis. We also tested whether the stimulation influenced the corticospinal excitability changes after motor learning. Sixteen healthy subjects were enrolled in the study. Participants performed the motor learning task in three experimental conditions: sham-tACS (baseline), β-tACS and γ-tACS. Corticospinal excitability was assessed with single-pulse TMS before the motor learning task and 5, 15, and 30 min thereafter. Motor retention was tested 30 min after the motor learning task. During training, acceleration of the practiced movement improved in the baseline condition and the enhanced performance was retained when tested 30 min later. The β-tACS delivered during training inhibited the acquisition of the motor learning task. Conversely, the γ-tACS slightly improved the acceleration of the practiced movement during training but it reduced motor retention. At the end of training, corticospinal excitability had similarly increased in the three sessions. The results are compatible with the hypothesis that entrainment of the two major motor resonant rhythms through tACS over M1 has different effects on motor learning in healthy humans. The effects, however, were unrelated to corticospinal excitability changes.

Modulation of brain alpha rhythm and heart rate variability by attention-related mechanisms

According to recent evidence, oscillations in the alpha-band (8–14 Hz) play an active role in attention via allocation of cortical resources: decrease in alpha activity enhances neural processes in task-relevant regions, while increase in alpha activity reduces processing in task-irrelevant regions. Here, we analyzed changes in alpha-band power of 13-channel electroencephalogram (EEG) acquired from 30 subjects while performing four tasks that differently engaged visual, computational and motor attentional components. The complete (visual + computational + motor) task required to read and solve an arithmetical operation and provide a motor response; three simplified tasks involved a subset of these components (visual + computational task, visual task, motor task). Task-related changes in alpha power were quantified by aggregating electrodes into two main regions (fronto-central and parieto-occipital), to test regional specificity of alpha modulation depending on the involved attentional aspects. Independent Component Analysis (ICA) was applied to discover the main independent processes accounting for alpha power over the two scalp regions. Furthermore, we performed analysis of Heart Rate Variability (HRV) from one electrocardiogram signal acquired simultaneously with EEG, to test autonomic reaction to attentional loads. Results showed that alpha power modulation over the two scalp regions not only reflected the number of involved attentional components (the larger their number the larger the alpha power suppression) but was also fine-tuned by the nature of the recruited mechanisms (visual, computational, motor) relative to the functional specification of the regions. ICA revealed topologically dissimilar and differently attention-regulated processes of alpha power over the two regions. HRV indexes were less sensitive to different attentional aspects compared to alpha power, with vagal activity index presenting larger changes. This study contributes to improve our understanding of the electroencephalographic and autonomic correlates of attention and may have practical implications in neurofeedback, brain-computer interfaces, neuroergonomics as well as in clinical practice and neuroscience research exploring attention-deficit disorders.

Correlation Structure in Micro-ECoG Recordings is Described by Spatially Coherent Components

Electrocorticography (ECoG) is becoming more prevalent due to improvements in fabrication and recording technology as well as its ease of implantation compared to intracortical electrophysiology, larger cortical coverage, and potential advantages for use in long term chronic implantation. Given the flexibility in the design of ECoG grids, which is only increasing, it remains an open question what geometry of the electrodes is optimal for an application. Conductive polymer, PEDOT:PSS, coated microelectrodes have an advantage that they can be made very small without losing low impedance. This makes them suitable for evaluating the required granularity of ECoG recording in humans and experimental animals. We used two-dimensional (2D) micro-ECoG grids to record intra-operatively in humans and during acute implantations in mouse with separation distance between neighboring electrodes (i.e., pitch) of 0.4 mm and 0.2/0.25 mm respectively. To assess the spatial properties of the signals, we used the average correlation between electrodes as a function of the pitch. In agreement with prior studies, we find a strong frequency dependence in the spatial scale of correlation. By applying independent component analysis (ICA), we find that the spatial pattern of correlation is largely due to contributions from multiple spatially extended, time-locked sources present at any given time. Our analysis indicates the presence of spatially structured activity down to the sub-millimeter spatial scale in ECoG despite the effects of volume conduction, justifying the use of dense micro-ECoG grids.

Electrocorticography (ECoG) is a type of electrophysiological monitoring that uses electrodes placed directly on the exposed surface of the brain. ECoG is a promising technique for studying the brain, and EcoG signals can be used to control brain-computer interfaces. Advances have made it possible to record simultaneously with an increasing number of smaller, and more closely spaced electrodes. However, a property of electrical recording from outside the brain is that common signals appear on different electrodes at different locations, and this affects decisions about how to best distribute a limited number of electrodes to maximize the information that can be gathered. Large spacing of electrodes around one centimeter apart on the brain’s surface has proven useful for clinical and research use, but how much benefit there is to recording from more locations in a smaller area remains to be answered. We found that we can explain the commonality between the different locations as the combination of different patterns of brain activity that are present at multiple electrode locations, and that signals recorded from very closely spaced electrodes, around a millimeter or less apart, are able to identify patterns that are at this small scale.

Unilateral, 3D Arm Movement Kinematics Are Encoded in Ipsilateral Human Cortex

There is increasing evidence that the hemisphere ipsilateral to a moving limb plays a role in planning and executing movements. However, the exact relationship between cortical activity and ipsilateral limb movements is uncertain. We sought to determine whether 3D arm movement kinematics (speed, velocity, and position) could be decoded from cortical signals recorded from the hemisphere ipsilateral to the moving limb. By having invasively monitored patients perform unilateral reaches with each arm, we also compared the encoding of contralateral and ipsilateral limb kinematics from a single cortical hemisphere. In four motor-intact human patients (three male, one female) implanted with electrocorticography electrodes for localization of their epileptic foci, we decoded 3D movement kinematics of both arms with accuracies above chance. Surprisingly, the spatial and spectral encoding of contralateral and ipsilateral limb kinematics was similar, enabling cross-prediction of kinematics between arms. These results clarify our understanding that the ipsilateral hemisphere robustly contributes to motor execution and supports that the information of complex movements is more bihemispherically represented in humans than has been previously understood.SIGNIFICANCE STATEMENT Although limb movements are traditionally understood to be driven by the cortical hemisphere contralateral to a moving limb, movement-related neural activity has also been found in the ipsilateral hemisphere. This study provides the first demonstration that 3D arm movement kinematics can be decoded from human electrocorticographic signals ipsilateral to the moving limb. Surprisingly, the spatial and spectral encoding of contralateral and ipsilateral limb kinematics was similar. The finding that specific kinematics are encoded in the ipsilateral hemisphere demonstrates that the ipsilateral hemisphere contributes to the execution of unilateral limb movements, improving our understanding of motor control. Additionally, the bihemisheric representation of voluntary movements has implications for the development of neuroprosthetic systems for reaching and for neurorehabilitation strategies following cortical injuries.

Altered task-related modulation of long-range connectivity in children with autism

Functional connectivity differences between children with autism spectrum disorder (ASD) and typically developing children have been described in multiple datasets. However, few studies examine the task-related changes in connectivity in disorder-relevant behavioral paradigms. In this paper, we examined the task-related changes in functional connectivity using EEG and a movement-based paradigm that has behavioral relevance to ASD. Resting-state studies motivated our hypothesis that children with ASD would show a decreased magnitude of functional connectivity during the performance of a motor-control task. Contrary to our initial hypothesis, however, we observed that task-related modulation of functional connectivity in children with ASD was in the direction opposite to that of TDs. The task-related connectivity changes were correlated with clinical symptom scores. Our results suggest that children with ASD may have differences in cortical segregation/integration during the performance of a task, and that part of the differences in connectivity modulation may serve as a compensatory mechanism. Autism Res 2018, 11: 245-257. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

Decreased connectivity between brain regions is thought to cause the symptoms of autism. Because most of our knowledge comes from data in which children are at rest, we do not know how connectivity changes directly lead to autistic behaviors, such as impaired gestures. When typically developing children produced complex movements, connectivity decreased between brain regions. In children with autism, connectivity increased. It may be that behavior-related changes in brain connectivity are more important than absolute differences in connectivity in autism.

Association between stimulus-evoked somatosensory inhibition and movement-related sensorimotor oscillation: A magnetoencephalographic study

The interaction between the somatosensory and motor cortices is understood; however, their functional relationship remains elusive. To elucidate the association between somatosensory and sensorimotor functions, this study investigated the correlation between somatosensory activities in response to paired-pulse stimulation and sensorimotor oscillations during self-paced finger movement in 18 healthy male subjects by using a magnetoencephalographic recording. The main finding was that stimulus-evoked somatosensory gating activities were significantly correlated with movement-related sensorimotor oscillatory responses. Specifically, the gating ratios of somatosensory N20m were related to the power changes of sensorimotor beta event-related desynchronization (ERD) (p=0.003) and event-related synchronization (ERS) (p=0.05). In conclusion, we confirmed that the inhibition of stimulus-evoked somatosensory responses is associated with the oscillatory characteristics of movement-related sensorimotor activities.

Musical training increases functional connectivity, but does not enhance mu suppression

Musical training provides an ideal platform for investigating action representation for sound. Learning to play an instrument requires integration of sensory and motor perception-action processes. Functional neuroimaging studies have indicated that listening to trained music can result in the activity in premotor areas, even after a short period of training. These studies suggest that action representation systems are heavily dependent on specific sensorimotor experience. However, others suggest that because humans naturally move to music, sensorimotor training is not necessary and there is a more general action representation for music. We previously demonstrated that EEG mu suppression, commonly implemented to demonstrate mirror-neuron-like action representation while observing movements, can also index action representations for sounds in pianists. The current study extends these findings to a group of non-musicians who learned to play randomised sequences on a piano, in order to acquire specific sound-action mappings for the five fingers of their right hand. We investigated training-related changes in neural dynamics as indexed by mu suppression and task-related coherence measures. To test the specificity of training effects, we included sounds similar to those encountered in the training and additionally rhythm sequences. We found no effect of training on mu suppression between pre- and post-training EEG recordings. However, task-related coherence indexing functional connectivity between electrodes over audiomotor areas increased after training. These results suggest that long-term training in musicians and short-term training in novices may be associated with different stages of audiomotor integration that can be reflected in different EEG measures. Furthermore, the changes in functional connectivity were specifically found for piano tones, and were not apparent when participants listened to rhythms, indicating some degree of specificity related to training.

Group and individual analyses of pre-, peri-, and post-movement related alpha and beta oscillations during a single continuous monitoring task

Band power linked to lower and upper alpha (i.e. 8-10Hz; 10-12Hz) and lower and upper beta (i.e. 12-20Hz; 20-30Hz) were examined during response related stages, including anticipation, response execution (RE), response inhibition (RI) and post response recovery (PRR). Group and individual data from 34 participants were considered. The participant's objective was to press a response key immediately following 4 non-repeating, single integer odd digits. These were presented amongst a continuous stream of digits and Xs. Electroencephalogram (EEG) signals were recorded from 32 electrodes (pooled to 12 regions). In the group analyses, participant EEG response was compared to baseline revealing that upper alpha desynchronised during anticipation, RE and RI; lower beta during anticipation and RE; and upper beta just RE. Upper alpha desynchronisation during rapid, unplanned RI is novel. Also, upper alpha and lower/upper beta synchronised during PRR. For upper alpha, we speculate this indexes brief cortical deactivation; for beta we propose this indexes response set maintenance. Lastly, lower alpha fluctuations correlated negatively with RT, indexing neural efficiency. Individual analyses involved calculation of the proportion of individuals displaying the typical RE and PRR trends; these were not reflected by all participants. The former was displayed individually by the largest proportion in upper alpha recorded left fronto-centrally; the latter was most reliably displayed individually in lower beta recorded mid centro-parietally. Therefore, group analyses identified typical alpha and beta synchronisation/desynchronisation trends, whilst individual analyses identified their degree of representation in single participants. Attention is drawn to the clinical relevance of this issue.

Quantitative EEG Evaluation During Robot-Assisted Foot Movement

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

Brain Network Connectivity and Topological Analysis During Voluntary Arm Movements

Functional connectivity estimates the temporal synchrony among functionally homogeneous brain regions based on the assessment of the dynamics of topologically localized neurophysiological responses. The aim of this study was to investigate task-related changes in brain activity and functional connectivity by applying different methods namely event-related desynchronization (ERD), coherence, and graph-theoretical analysis to electroencephalographic (EEG) recordings, for comparing their respective descriptive power and complementarity. As it is well known, ERD provides an estimate of differences in power spectral densities between active (or task) and rest conditions, functional connectivity allows assessing the level of synchronization between the signals recorded at different scalp locations and graph analysis enables the estimation of the functional network features and topology. EEG activity was recorded on 10 subjects during left/right arm movements. The theta, alpha, and beta bands were considered. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex during the left arm movement and in beta band during the right arm movement, besides identifying the regions involved in the task, as it was expected. On the other hand, connectivity assessment highlighted that stronger connections are those that involved the motor regions for which graph analysis revealed reduced accessibility and an increased centrality during the movement. Jointly, the last two methods allow identifying the cortical areas that are functionally related in the active condition as well as the topological organization of the functional network. Results support the hypothesis that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced functional connectivity and could be profitably exploited in clinical contexts.