Simultaneous EEG 10 Hz desynchronization and 40 Hz synchronization during finger movements

Determining the effects of transcranial alternating current stimulation on corticomotor excitability and motor performance: A sham-controlled comparison of four frequencies

Transcranial alternating current stimulation (tACS) modulates brain oscillations and corticomotor plasticity. We examined the effects of four tACS frequencies (20 Hz, 40 Hz, 60 Hz, and 80 Hz) on motor cortex (M1) excitability and motor performance. In a randomised crossover design, 12 adults received 20-minute tACS sessions, with Sham as control. Corticomotor and intracortical excitability was measured up to 60-minutes post-tACS. Motor performance was evaluated using the Grooved Pegboard Test (GPT) and sensorimotor assessments. Our findings demonstrated frequency-dependent modulation of corticomotor excitability based on MEP amplitude. 20 Hz and 40 Hz tACS reduced MEPs, while 60 Hz and 80 Hz increased MEPs. Inhibition (cortical silent period, SP) was reduced across all tACS frequencies compared to Sham, with 20 Hz and 40 Hz showing consistent reductions, 60 Hz showing effects at post-0 and post-30, and 80 Hz at post-60. Furthermore, 60 Hz tACS decreased intracortical inhibition at post-0, while intracortical facilitation increased with 20 Hz and 60 Hz at post-0, and 40 Hz at post-60. Motor performance remained unaffected across frequencies. Regression analyses revealed that shorter SP at 60 min post 60 Hz tACS predicted faster reaction times, while greater MEP amplitudes at 60 min following 80 Hz tACS predicted improved hand dexterity. Overall, beta and gamma tACS frequencies modulate M1 excitability, with consistent effects on SP, suggesting potential use in conditions involving SP elongation, such as stroke and Huntington's disease. These findings highlight 60 Hz tACS as a potential tool for motor rehabilitation therapies.

Older Individuals Do Not Show Task Specific Variations in EEG Band Power and Finger Force Coordination

OBJECTIVE

Controlling and coordinating finger force is crucial for performing everyday tasks and maintaining functional independence. Aging naturally weakens neural, muscular, and musculoskeletal systems, leading to compromised hand motor function. This decline reduces cortical activity, finger force control and coordination in older adults.

OBJECTIVE

To investigate independently the EEG band power and finger force coordination in older individuals and compare the results with young healthy adults.

METHODS

Twenty healthy young adults aged 20-30 (26.96 ± 2.68) and fourteen older adults aged 58-72 (62.57 ± 3.58) participated in this study. Participants held the instrumented handle gently for five seconds then lifted and held it for an additional five seconds in the two conditions: fixed (thumb platform secured) and free condition (thumb platform may slide on slider).

RESULTS

In the older individuals there was no difference observed in the finger force synergy indices, and EEG beta band power between the two task conditions. However, in the young group synergy indices and EEG beta band power were less in free condition compared to fixed condition. Additionally, in the fixed condition, older adults showed a reduced synergy indices and reduced EEG beta band power than the young adults.

CONCLUSION

Older participants exhibited consistent synergy indices and beta band power across conditions, while young adults adjusted strategies based on tasks. Task-dependent finger force synergy indices were observed in young adults, contrasting with older individuals Additionally, it is suggested that EEG band power and synergy indices may be related, indicating potential associations between EEG activity and finger force coordination.

Effectiveness and brain mechanism of multi-target transcranial alternating current stimulation (tACS) on motor learning in stroke patients: study protocol for a randomized controlled trial

BACKGROUND

Transcranial alternating current stimulation (tACS) has proven to be an effective treatment for improving cognition, a crucial factor in motor learning. However, current studies are predominantly focused on the motor cortex, and the potential brain mechanisms responsible for the therapeutic effects are still unclear. Given the interconnected nature of motor learning within the brain network, we have proposed a novel approach known as multi-target tACS. This study aims to ascertain whether multi-target tACS is more effective than single-target stimulation in stroke patients and to further explore the potential underlying brain mechanisms by using techniques such as transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI).

METHODS

This study employs a double-blind, sham-controlled, randomized controlled trial design with a 2-week intervention period. Both participants and outcome assessors will remain unaware of treatment allocation throughout the study. Thirty-nine stroke patients will be recruited and randomized into three distinct groups, including the sham tACS group (SS group), the single-target tACS group (ST group), and the multi-target tACS group (MT group), at a 1:1:1 ratio. The primary outcomes are series reaction time tests (SRTTs) combined with electroencephalograms (EEGs). The secondary outcomes include motor evoked potential (MEP), central motor conduction time (CMCT), short interval intracortical inhibition (SICI), intracortical facilitation (ICF), magnetic resonance imaging (MRI), Box and Block Test (BBT), and blood sample RNA sequencing. The tACS interventions for all three groups will be administered over a 2-week period, with outcome assessments conducted at baseline (T0) and 1 day (T1), 7 days (T2), and 14 days (T3) of the intervention phase.

DISCUSSION

The study's findings will determine the potential of 40-Hz tACS to improve motor learning in stroke patients. Additionally, it will compare the effectiveness of multi-target and single-target approaches, shedding light on their respective improvement effects. Through the utilization of techniques such as TMS and MRI, the study aims to uncover the underlying brain mechanisms responsible for the therapeutic impact. Furthermore, the intervention has the potential to facilitate motor learning efficiency, thereby contributing to the advancement of future stroke rehabilitation treatment.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2300073465. Registered on 11 July 2023.

Movement-related ERS and connectivity in the gamma frequency decrease with practice

Previous work showed that movements are accompanied by modulation of electroencephalographic (EEG) activity in both beta (13-30 Hz) and gamma (>30 Hz) ranges. The amplitude of beta event-related synchronization (ERS) is not linked to movement characteristics, but progressively increases with motor practice, returning to baseline after a period of rest. Conversely, movement-related gamma ERS amplitude is proportional to movement distance and velocity. Here, high-density EEG was recorded in 51 healthy subjects to investigate whether i) three-hour practice in two learning tasks, one with a motor component and one without, affects gamma ERS amplitude and connectivity during a motor reaching test, and ii) 90-minutes of either sleep or quiet rest have an effect on gamma oscillatory activity. We found that, while gamma ERS was appropriately scaled to the target extent at all testing points, its amplitude decreased after practice, independently of the type of interposed learning, and after both quiet wake and nap, with partial correlations with subjective fatigue scores. During movement execution, connectivity patterns within fronto-parieto-occipital electrodes, over areas associated with attentional networks, decreased after both practice and after 90-minute rest. While confirming the prokinetic nature of movement-related gamma ERS, these findings demonstrated the preservation of gamma ERS scaling to movement velocity with practice, despite constant amplitude reduction. We thus speculate that such decreases, differently from the practice-related increases of beta ERS, are related to reduced attention or working memory mechanisms due to fatigue or a switch of strategy toward automatization of movement execution and do not specifically reflect plasticity phenomena.

Cortical facilitation of tactile afferents during the preparation of a body weight transfer when standing on a biomimetic surface

Self-generated movement shapes tactile perception, but few studies have investigated the brain mechanisms involved in the processing of the mechanical signals related to the static and transient skin deformations generated by forces and pressures exerted between the foot skin and the standing surface. We recently found that standing on a biomimetic surface (i.e., inspired by the characteristics of mechanoreceptors and skin dermatoglyphics), that magnified skin-surface interaction, increased the sensory flow to the somatosensory cortex and improved balance control compared to standing on control (e.g., smooth) surfaces. In this study, we tested whether the well-known sensory suppression that occurs during movements is alleviated when the tactile afferent signal becomes relevant with the use of a biomimetic surface. Eyes-closed participants (n = 25) self-stimulated their foot cutaneous receptors by shifting their body weight toward one of their legs while standing on either a biomimetic or a control (smooth) surface. In a control task, similar forces were exerted on the surfaces (i.e., similar skin-surface interaction) by passive translations of the surfaces. Sensory gating was assessed by measuring the amplitude of the somatosensory-evoked potential over the vertex (SEP, recorded by EEG). Significantly larger and shorter SEPs were found when participants stood on the biomimetic surface. This was observed whether the forces exerted on the surface were self-generated or passively generated. Contrary to our prediction, we found that the sensory attenuation related to the self-generated movement did not significantly differ between the biomimetic and control surfaces. However, we observed an increase in gamma activity (30-50 Hz) over centroparietal regions during the preparation phase of the weight shift only when participants stood on the biomimetic surface. This result might suggest that gamma-band oscillations play an important functional role in processing behaviorally relevant stimuli during the early stages of body weight transfer.

The Control of Movements via Motor Gamma Oscillations

The ability to perform movements is vital for our daily life. Our actions are embedded in a complex environment where we need to deal efficiently in the face of unforeseen events. Neural oscillations play an important role in basic sensorimotor processes related to the execution and preparation of movements. In this review, I will describe the state of the art regarding the role of motor gamma oscillations in the control of movements. Experimental evidence from electrophysiological studies has shown that motor gamma oscillations accomplish a range of functions in motor control beyond merely signaling the execution of movements. However, these additional aspects associated with motor gamma oscillation remain to be fully clarified. Future work on different spatial, temporal and spectral scales is required to further understand the implications of gamma oscillations in motor control.

Long-term stability of the chronic epidural wireless recorder WIMAGINE in tetraplegic patients

Objective.The evaluation of the long-term stability of ElectroCorticoGram (ECoG) signals is an important scientific question as new implantable recording devices can be used for medical purposes such as Brain-Computer Interface (BCI) or brain monitoring.Approach.The long-term clinical validation of wireless implantable multi-channel acquisition system for generic interface with neurons (WIMAGINE), a wireless 64-channel epidural ECoG recorder was investigated. The WIMAGINE device was implanted in two quadriplegic patients within the context of a BCI protocol. This study focused on the ECoG signal stability in two patients bilaterally implanted in June 2017 (P1) and in November 2019 (P2).Methods. The ECoG signal was recorded at rest prior to each BCI session resulting in a 32 month and in a 14 month follow-up for P1 and P2 respectively. State-of-the-art signal evaluation metrics such as root mean square (RMS), the band power (BP), the signal to noise ratio (SNR), the effective bandwidth (EBW) and the spectral edge frequency (SEF) were used to evaluate stability of signal over the implantation time course. The time-frequency maps obtained from task-related motor activations were also studied to investigate the long-term selectivity of the electrodes.Mainresults.Based on temporal linear regressions, we report a limited decrease of the signal average level (RMS), spectral distribution (BP) and SNR, and a remarkable steadiness of the EBW and SEF. Time-frequency maps obtained during motor imagery, showed a high level of discrimination 1 month after surgery and also after 2 years.Conclusions.The WIMAGINE epidural device showed high stability over time. The signal evaluation metrics of two quadriplegic patients during 32 months and 14 months respectively provide strong evidence that this wireless implant is well-suited for long-term ECoG recording.Significance.These findings are relevant for the future of implantable BCIs, and could benefit other patients with spinal cord injury, amyotrophic lateral sclerosis, neuromuscular diseases or drug-resistant epilepsy.

Short-term changes in cortical physiological arousal measured by electroencephalography during thalamic centromedian deep brain stimulation

OBJECTIVE

The intralaminar thalamus is well implicated in the processes of arousal and attention. Stimulation of the intralaminar thalamus has been used therapeutically to improve level of alertness in minimally conscious individuals and to reduce seizures in refractory epilepsy, both presumably through modulation of thalamocortical function. Little work exists that directly measures the effects of intralaminar thalamic stimulation on cortical physiological arousal in humans. Therefore, our goal was to quantify cortical physiological arousal in individuals with epilepsy receiving thalamic intralaminar deep brain stimulation.

METHODS

We recorded scalp electroencephalogram (EEG) during thalamic intralaminar centromedian (CM) nucleus stimulation in 11 patients with medically refractory epilepsy. Participants underwent stimulation at 130 Hz and 300 µs for periods of 5 min alternating with 5 min of rest while stimulus voltage was titrated upward from 1 to 5 V. EEG signal power was analyzed in different frequency ranges in relation to stimulus strength and time.

RESULTS

We found a progressive increase in broadband gamma (25-100 Hz) cortical EEG power (F = 7.64, p < .05) and decrease in alpha (8-13 Hz) power (F = 4.37, p < .05) with thalamic CM stimulation. Topographic maps showed these changes to be widely distributed across the cortical surface rather than localized to one region.

SIGNIFICANCE

Previous work has shown that broadband increases in gamma frequency power and decreases in alpha frequency power are generally associated with states of cortical activation and increased arousal/attention. Our observed changes therefore support the possible role of cortical activation and increased physiological arousal in therapeutic effects of intralaminar thalamic stimulation for improving both epilepsy and attention. Further investigations with this approach may lead to methods for determining optimal deep brain stimulation parameters to improve clinical outcome in these disorders.

The Feasibility of Longitudinal Upper Extremity Motor Function Assessment Using EEG

Motor function assessment is crucial in quantifying motor recovery following stroke. In the rehabilitation field, motor function is usually assessed using questionnaire-based assessments, which are not completely objective and require prior training for the examiners. Some research groups have reported that electroencephalography (EEG) data have the potential to be a good indicator of motor function. However, those motor function scores based on EEG data were not evaluated in a longitudinal paradigm. The ability of the motor function scores from EEG data to track the motor function changes in long-term clinical applications is still unclear. In order to investigate the feasibility of using EEG to score motor function in a longitudinal paradigm, a convolutional neural network (CNN) EEG model and a residual neural network (ResNet) EEG model were previously generated to translate EEG data into motor function scores. To validate applications in monitoring rehabilitation following stroke, the pre-established models were evaluated using an initial small sample of individuals in an active 14-week rehabilitation program. Longitudinal performances of CNN and ResNet were evaluated through comparison with standard Fugl-Meyer Assessment (FMA) scores of upper extremity collected in the assessment sessions. The results showed good accuracy and robustness with both proposed networks (average difference: 1.22 points for CNN, 1.03 points for ResNet), providing preliminary evidence for the proposed method in objective evaluation of motor function of upper extremity in long-term clinical applications.

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis

The purpose of this paper is to record and analyze induced gamma-band activity (GBA) (30-60 Hz) in cerebral motor areas during imaginary movement and to compare it quantitatively with activity recorded in the same areas during actual movement using a simplified electroencephalogram (EEG). Brain activity (basal activity, imaginary motor task and actual motor task) is obtained from 12 healthy volunteer subjects using an EEG (Cz channel). GBA is analyzed using the mean power spectral density (PSD) value. Event-related synchronization (ERS) is calculated from the PSD values of the basal GBA (GBAb), the GBA of the imaginary movement (GBAim) and the GBA of the actual movement (GBAac). The mean GBAim and GBAac values for the right and left hands are significantly higher than the GBAb value (p = 0.007). No significant difference is detected between mean GBA values during the imaginary and actual movement (p = 0.242). The mean ERS values for the imaginary movement (ERSimM (%) = 23.52) and for the actual movement (ERSacM = 27.47) do not present any significant difference (p = 0.117). We demonstrated that ERS could provide a useful way of indirectly checking the function of neuronal motor circuits activated by voluntary movement, both imaginary and actual. These results, as a proof of concept, could be applied to physiology studies, brain-computer interfaces, and diagnosis of cognitive or motor pathologies.

Potential of on-scalp MEG: Robust detection of human visual gamma-band responses

Electrophysiological signals recorded intracranially show rich frequency content spanning from near‐DC to hundreds of hertz. Noninvasive electromagnetic signals measured with electroencephalography (EEG) or magnetoencephalography (MEG) typically contain less signal power in high frequencies than invasive recordings. Particularly, noninvasive detection of gamma‐band activity (>30 Hz) is challenging since coherently active source areas are small at such frequencies and the available imaging methods have limited spatial resolution. Compared to EEG and conventional SQUID‐based MEG, on‐scalp MEG should provide substantially improved spatial resolution, making it an attractive method for detecting gamma‐band activity. Using an on‐scalp array comprised of eight optically pumped magnetometers (OPMs) and a conventional whole‐head SQUID array, we measured responses to a dynamic visual stimulus known to elicit strong gamma‐band responses. OPMs had substantially higher signal power than SQUIDs, and had a slightly larger relative gamma‐power increase over the baseline. With only eight OPMs, we could obtain gamma‐activity source estimates comparable to those of SQUIDs at the group level. Our results show the feasibility of OPMs to measure gamma‐band activity. To further facilitate the noninvasive detection of gamma‐band activity, the on‐scalp OPM arrays should be optimized with respect to sensor noise, the number of sensors and intersensor spacing.

Corticomuscular Coherence for Upper Arm Flexor and Extensor Muscles During Isometric Exercise and Cyclically Isokinetic Movement

Cortical-muscular functional coupling reflects the interaction between the cerebral cortex and the muscle activities. Corticomuscular coherence (CMC) has been extensively revealed in sustained contractions of various upper- and lower-limb muscles during static and dynamic force outputs. However, it is not well-understood that the CMC modulation mechanisms, i.e., the relation between a cerebral hemisphere and dynamic motor controlling limbs at constant speeds, such as isokinetic movement. In this paper, we explore the CMC between upper arm flexors/extensors movement and motor cortex during isometric exercise and cyclically isokinetic movement. We also provide further insights of frequency-shift and the neural pathway mechanisms in isokinetic movement by evaluating the coherence between motor cortex and agonistic or antagonistic muscles. This study is the first to investigate the relationship between cortical-muscular functional connections in elbow flexion-extension movement with constant speeds. The result shows that gamma-range coherence for isokinetic movement is greatly increased compared with isometric exercise, and significant CMC is observed in the entire flexion-extension stage regardless the nature of muscles contraction, although dominant synchronization of cortical oscillation and muscular activity resonated in sustained contraction stage principally. Besides, the CMC for extensors and flexors are explicitly consistent in contraction stage during cyclically isokinetic elbow movement. It is concluded that cortical-muscular coherence can be dynamically modulated as well as selective by cognitive demands of the body, and the time-varying mechanisms of the synchronous motor oscillation exist in healthy individuals during dynamic movement.

Modulations in Oscillatory Activity of Globus Pallidus Internus Neurons During a Directed Hand Movement Task-A Primary Mechanism for Motor Planning

Globus pallidus internus (GPi) neurons in the basal ganglia are traditionally thought to play a significant role in the promotion and suppression of movement via a change in firing rates. Here, we hypothesize that a primary mechanism of movement control by GPi neurons is through specific modulations in their oscillatory patterns. We analyzed neuronal spiking activity of 83 GPi neurons recorded from two healthy nonhuman primates executing a radial center-out motor task. We found that, in directionally tuned neurons, the power in the gamma band is significantly (p < 0.05) greater than that in the beta band (a "cross-over" effect), during the planning stages of movements in their preferred direction. This cross-over effect is not observed in the non-directionally tuned neurons. These data suggest that, during movement planning, information encoding by GPi neurons may be governed by a sudden emergence and suppression of oscillatory activities, rather than simply by a change in average firing rates.

Corticomuscular Coherence and Its Applications: A Review

Corticomuscular coherence (CMC) is an index utilized to indicate coherence between brain motor cortex and associated body muscles, conventionally. As an index of functional connections between the cortex and muscles, CMC research is the focus of neurophysiology in recent years. Although CMC has been extensively studied in healthy subjects and sports disorders, the purpose of its applications is still ambiguous, and the magnitude of CMC varies among individuals. Here, we aim to investigate factors that modulate the variation of CMC amplitude and compare significant CMC between these factors to find a well-developed research prospect. In the present review, we discuss the mechanism of CMC and propose a general definition of CMC. Factors affecting CMC are also summarized as follows: experimental design, band frequencies and force levels, age correlation, and difference between healthy controls and patients. In addition, we provide a detailed overview of the current CMC applications for various motor disorders. Further recognition of the factors affecting CMC amplitude can clarify the physiological mechanism and is beneficial to the implementation of CMC clinical methods.

EEG coherence as a diagnostic tool to measure the initial stages of Parkinson Disease

Although Parkinson Disease was described a long time ago by James Parkinson and several biomarkers were used to predict the symptoms of PD, there is no accepted tool to distinguish the initial stages of this pathology. The present hypothesis discusses the Coherence Function, an Electroencephalography measure which could be used as a simple, and low-cost tool to describe the onset of cardinal signals of PD. Our hypothesis is based on three factors: beta frequency related to movement, motor action over particular cortical regions, and cortical coupling between cortical areas involved in the execution of voluntary movement. We believe that these factors support our hypothesis pointing out coherence function as an interesting measure to detect initial stages of PD.

Neural Oscillations and the Initiation of Voluntary Movement

The brain processes involved in the planning and initiation of voluntary action are of great interest for understanding the relationship between conscious awareness of decisions and the neural control of movement. Voluntary motor behavior has generally been considered to occur when conscious decisions trigger movements. However, several studies now provide compelling evidence that brain states indicative of forthcoming movements take place before a person becomes aware of a conscious decision to act. While such studies have created much debate over the nature of ‘free will,’ at the very least they suggest that unconscious brain processes are predictive of forthcoming movements. Recent studies suggest that slow changes in neuroelectric potentials may play a role in the timing of movement onset by pushing brain activity above a threshold to trigger the initiation of action. Indeed, recent studies have shown relationships between the phase of low frequency oscillatory activity of the brain and the onset of voluntary action. Such studies, however, cannot determine whether this underlying neural activity plays a causal role in the initiation of movement or is only associated with the intentional behavior. Non-invasive transcranial alternating current brain stimulation can entrain neural activity at particular frequencies in order to assess whether underlying brain processes are causally related to associated behaviors. In this review, we examine the evidence for neural coding of action as well as the brain states prior to action initiation and discuss whether low frequency alternating current brain stimulation could influence the timing of a persons’ decision to act.

The effects of transcranial alternating current stimulation (tACS) at individual alpha peak frequency (iAPF) on motor cortex excitability in young and elderly adults

Transcranial alternating current stimulation (tACS) can modulate brain oscillations, cortical excitability and behaviour. In aging, the decrease in EEG alpha activity (8–12 Hz) in the parieto-occipital and mu rhythm in the motor cortex are correlated with the decline in cognitive and motor functions, respectively. Increasing alpha activity using tACS might therefore improve cognitive and motor function in the elderly. The present study explored the influence of tACS on cortical excitability in young and old healthy adults. We applied tACS at individual alpha peak frequency for 10 min (1.5 mA) to the left motor cortex. Transcranial magnetic stimulation was used to assess the changes in cortical excitability as measured by motor-evoked potentials at rest, before and after stimulation. TACS increased cortical excitability in both groups. However, our results also suggest that the mechanism behind the effects was different, as we observed an increase and decrease in intracortical inhibition in the old group and young group, respectively. Our results indicate that both groups profited similarly from the stimulation. There was no indication that tACS was more effective in conditions of low alpha power, that is, in the elderly.

The Effects of Fluency Enhancing Conditions on Sensorimotor Control of Speech in Typically Fluent Speakers: An EEG Mu Rhythm Study

Objective: To determine whether changes in sensorimotor control resulting from speaking conditions that induce fluency in people who stutter (PWS) can be measured using electroencephalographic (EEG) mu rhythms in neurotypical speakers.

Methods: Non-stuttering (NS) adults spoke in one control condition (solo speaking) and four experimental conditions (choral speech, delayed auditory feedback (DAF), prolonged speech and pseudostuttering). Independent component analysis (ICA) was used to identify sensorimotor μ components from EEG recordings. Time-frequency analyses measured μ-alpha (8–13 Hz) and μ-beta (15–25 Hz) event-related synchronization (ERS) and desynchronization (ERD) during each speech condition.

Results: 19/24 participants contributed μ components. Relative to the control condition, the choral and DAF conditions elicited increases in μ-alpha ERD in the right hemisphere. In the pseudostuttering condition, increases in μ-beta ERD were observed in the left hemisphere. No differences were present between the prolonged speech and control conditions.

Conclusions: Differences observed in the experimental conditions are thought to reflect sensorimotor control changes. Increases in right hemisphere μ-alpha ERD likely reflect increased reliance on auditory information, including auditory feedback, during the choral and DAF conditions. In the left hemisphere, increases in μ-beta ERD during pseudostuttering may have resulted from the different movement characteristics of this task compared with the solo speaking task. Relationships to findings in stuttering are discussed.

Significance: Changes in sensorimotor control related feedforward and feedback control in fluency-enhancing speech manipulations can be measured using time-frequency decompositions of EEG μ rhythms in neurotypical speakers. This quiet, non-invasive, and temporally sensitive technique may be applied to learn more about normal sensorimotor control and fluency enhancement in PWS.

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

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

Instantaneous voltage as an alternative to power- and phase-based interpretation of oscillatory brain activity

For decades, oscillatory brain activity has been characterized primarily by measurements of power and phase. While many studies have linked those measurements to cortical excitability, their relationship to each other and to the physiological underpinnings of excitability is unclear. The recently proposed Function-through-Biased-Oscillations (FBO) hypothesis (Schalk, 2015) addressed these issues by suggesting that the voltage potential at the cortical surface directly reflects the excitability of cortical populations, that this voltage is rhythmically driven away from a low resting potential (associated with depolarized cortical populations) towards positivity (associated with hyperpolarized cortical populations). This view explains how oscillatory power and phase together influence the instantaneous voltage potential that directly regulates cortical excitability. This implies that the alternative measurement of instantaneous voltage of oscillatory activity should better predict cortical excitability compared to either of the more traditional measurements of power or phase. Using electrocorticographic (ECoG) data from 28 human subjects, the results of our study confirm this prediction: compared to oscillatory power and phase, the instantaneous voltage explained 20% and 31% more of the variance in broadband gamma, respectively, and power and phase together did not produce better predictions than the instantaneous voltage. These results synthesize the previously separate power- and phase-based interpretations and associate oscillatory activity directly with a physiological interpretation of cortical excitability. This alternative view has implications for the interpretation of studies of oscillatory activity and for current theories of cortical information transmission.

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial

BACKGROUND

Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations.

METHODS

Twenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention.

RESULTS

As compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and β bands and larger fronto-central cortical activations in the affected hemisphere.

CONCLUSIONS

The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance.

TRIAL REGISTRATION

Retrospectively registered in Clinical Trials on 21-11-2016, n. NCT02971371 .

Alpha power indexes task-related networks on large and small scales: A multimodal ECoG study in humans and a non-human primate

Performing different tasks, such as generating motor movements or processing sensory input, requires the recruitment of specific networks of neuronal populations. Previous studies suggested that power variations in the alpha band (8-12Hz) may implement such recruitment of task-specific populations by increasing cortical excitability in task-related areas while inhibiting population-level cortical activity in task-unrelated areas (Klimesch et al., 2007; Jensen and Mazaheri, 2010). However, the precise temporal and spatial relationships between the modulatory function implemented by alpha oscillations and population-level cortical activity remained undefined. Furthermore, while several studies suggested that alpha power indexes task-related populations across large and spatially separated cortical areas, it was largely unclear whether alpha power also differentially indexes smaller networks of task-related neuronal populations. Here we addressed these questions by investigating the temporal and spatial relationships of electrocorticographic (ECoG) power modulations in the alpha band and in the broadband gamma range (70-170Hz, indexing population-level activity) during auditory and motor tasks in five human subjects and one macaque monkey. In line with previous research, our results confirm that broadband gamma power accurately tracks task-related behavior and that alpha power decreases in task-related areas. More importantly, they demonstrate that alpha power suppression lags population-level activity in auditory areas during the auditory task, but precedes it in motor areas during the motor task. This suppression of alpha power in task-related areas was accompanied by an increase in areas not related to the task. In addition, we show for the first time that these differential modulations of alpha power could be observed not only across widely distributed systems (e.g., motor vs. auditory system), but also within the auditory system. Specifically, alpha power was suppressed in the locations within the auditory system that most robustly responded to particular sound stimuli. Altogether, our results provide experimental evidence for a mechanism that preferentially recruits task-related neuronal populations by increasing cortical excitability in task-related cortical areas and decreasing cortical excitability in task-unrelated areas. This mechanism is implemented by variations in alpha power and is common to humans and the non-human primate under study. These results contribute to an increasingly refined understanding of the mechanisms underlying the selection of the specific neuronal populations required for task execution.

Interfacing brain with computer to improve communication and rehabilitation after brain damage

Communication and control of the external environment can be provided via brain-computer interfaces (BCIs) to replace a lost function in persons with severe diseases and little or no chance of recovery of motor abilities (ie, amyotrophic lateral sclerosis, brainstem stroke). BCIs allow to intentionally modulate brain activity, to train specific brain functions, and to control prosthetic devices, and thus, this technology can also improve the outcome of rehabilitation programs in persons who have suffered from a central nervous system injury (ie, stroke leading to motor or cognitive impairment). Overall, the BCI researcher is challenged to interact with people with severe disabilities and professionals in the field of neurorehabilitation. This implies a deep understanding of the disabled condition on the one hand, and it requires extensive knowledge on the physiology and function of the human brain on the other. For these reasons, a multidisciplinary approach and the continuous involvement of BCI users in the design, development, and testing of new systems are desirable. In this chapter, we will focus on noninvasive EEG-based systems and their clinical applications, highlighting crucial issues to foster BCI translation outside laboratories to eventually become a technology usable in real-life realm.

Assessing human mirror activity with EEG mu rhythm: A meta-analysis

A fundamental issue in cognitive neuroscience is how the brain encodes others' actions and intentions. In recent years, a potential advance in our knowledge on this issue is the discovery of mirror neurons in the motor cortex of the nonhuman primate. These neurons fire to both execution and observation of specific types of actions. Researchers use this evidence to fuel investigations of a human mirror system, suggesting a common neural code for perceptual and motor processes. Among the methods used for inferring mirror system activity in humans are changes in a particular frequency band in the electroencephalogram (EEG) called the mu rhythm. Mu frequency appears to decrease in amplitude (reflecting cortical activity) during both action execution and action observation. The current meta-analysis reviewed 85 studies (1,707 participants) of mu that infer human mirror system activity. Results demonstrated significant effect sizes for mu during execution (Cohen's d = 0.46, N = 701) as well as observation of action (Cohen's d = 0.31, N = 1,508), confirming a mirroring property in the EEG. A number of moderators were examined to determine the specificity of these effects. We frame these meta-analytic findings within the current discussion about the development and functions of a human mirror system, and conclude that changes in EEG mu activity provide a valid means for the study of human neural mirroring. Suggestions for improving the experimental and methodological approaches in using mu to study the human mirror system are offered.

The Neurophysiologist Perspective into MS Plasticity

Multiple sclerosis (MS) is a frequent, highly debilitating inflammatory demyelinating disease, starting to manifest in early adulthood and presenting a wide variety of symptoms, which are often resistant to pharmacological treatments. Cortical dysfunctions have been demonstrated to be key components of MS condition, and plasticity of the corticospinal motor system is highly involved in major MS symptoms, such as fatigue, spasticity, or pain. Cortical dysfunction in MS can be studied with neurophysiological tools, such as electroencephalography (EEG) and related techniques (evoked potentials) or transcranial magnetic stimulation (TMS). These techniques are now widely used to provide essential elements of MS diagnosis and can also be used to modulate plasticity. Indeed, the recent development of non-invasive brain stimulation techniques able to induce cortical plasticity, such as repetitive TMS or transcranial direct current stimulation, has brought promising results as add-on treatments. In this review, we will focus on the use of these tools (EEG and TMS) to study plasticity in MS and on the major techniques used to modulate plasticity in MS.

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

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

Neurophysiologic correlates of sonication treatment in patients with essential tremor

Transcranial magnetic resonance imaging-guided high-intensity focused ultrasound (MRgHIFU) is gaining attention as a potent substitute for surgical intervention in the treatment of neurologic disorders. To discern the neurophysiologic correlates of its therapeutic effects, we applied MRgHIFU to an intractable neurologic disorder, essential tremor, while measuring magnetoencephalogram mu rhythms from the motor cortex. Focused ultrasound sonication destroyed tissues by focusing a high-energy beam on the ventralis intermedius nucleus of the thalamus. The post-treatment effectiveness was also evaluated using the clinical rating scale for tremors. Thalamic MRgHIFU had substantial therapeutic effects on patients, based on MRgHIFU-mediated improvements in movement control and significant changes in brain mu rhythms. Ultrasonic thalamotomy may reduce hyper-excitable activity in the motor cortex, resulting in normalized behavioral activity after sonication treatment. Thus, non-invasive and spatially accurate MRgHIFU technology can serve as a potent therapeutic tool with broad clinical applications.

Eye closure causes widespread low-frequency power increase and focal gamma attenuation in the human electrocorticogram

OBJECTIVE

We sought to characterize the effects of eye closure on EEG power using electrocorticography (ECoG). Specifically, we sought to elucidate the anatomical areas demonstrating an eye closure effect, and at which frequencies this effect occurs.

METHODS

ECoG was recorded from 32 patients undergoing invasive monitoring for seizure focus localization. Patients were instructed to close and open their eyes repeatedly. ECoG power was compared in the epochs following eye closure and opening, for various frequency bands and brain regions.

RESULTS

We found that at low frequencies, eye closure causes widespread power increases involving all lobes of the brain. This effect was significant not only in the α (8-12 Hz) band but in the δ (2-4 Hz), θ (4-8 Hz), and β (15-30 Hz) bands as well. At high frequencies, eye closure causes comparatively focal power decreases over occipital cortex and frontal Brodmann areas 8 and 9.

CONCLUSIONS

Eye closure (1) affects a broad range of frequencies outside the α band and (2) involves a distributed network of neural activity in anatomical areas outside visual cortex.

SIGNIFICANCE

This study constitutes the first large-scale, systematic application of ECoG to study eye closure, which is shown to influence a broad range of frequencies and brain regions.

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide “entry points” to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits.

It's how you get there: walking down a virtual alley activates premotor and parietal areas

Voluntary drive is crucial for motor learning, therefore we are interested in the role that motor planning plays in gait movements. In this study we examined the impact of an interactive Virtual Environment (VE) feedback task on the EEG patterns during robot assisted walking. We compared walking in the VE modality to two control conditions: walking with a visual attention paradigm, in which visual stimuli were unrelated to the motor task; and walking with mirror feedback, in which participants observed their own movements. Eleven healthy participants were considered. Application of independent component analysis to the EEG revealed three independent component clusters in premotor and parietal areas showing increased activity during walking with the adaptive VE training paradigm compared to the control conditions. During the interactive VE walking task spectral power in frequency ranges 8-12, 15-20, and 23-40 Hz was significantly (p ≤ 0.05) decreased. This power decrease is interpreted as a correlate of an active cortical area. Furthermore activity in the premotor cortex revealed gait cycle related modulations significantly different (p ≤ 0.05) from baseline in the frequency range 23-40 Hz during walking. These modulations were significantly (p ≤ 0.05) reduced depending on gait cycle phases in the interactive VE walking task compared to the control conditions. We demonstrate that premotor and parietal areas show increased activity during walking with the adaptive VE training paradigm, when compared to walking with mirror- and movement unrelated feedback. Previous research has related a premotor-parietal network to motor planning and motor intention. We argue that movement related interactive feedback enhances motor planning and motor intention. We hypothesize that this might improve gait recovery during rehabilitation.

Event-related desynchronization and synchronization quantification in motor-related EEG by Kolmogorov entropy

OBJECTIVE

Various approaches have been applied for the quantification of event-related desynchronization/synchronization (ERD/ERS) in EEG/MEG data analysis, but most of them are based on band power analysis. In this paper, we sought a novel method using a nonlinear measurement to quantify the ERD/ERS time course of motor-related EEG.

APPROACH

We applied Kolmogorov entropy to quantify the ERD/ERS time course of motor-related EEG in relation to hand movement imagination and execution for the first time. To further test the validity of the Kolmogorov entropy measure, we tested it on five human subjects for feature extraction to classify the left and right hand motor tasks.

MAIN RESULTS

The results show that the relative increase and decrease of Kolmogorov entropy indicates the ERD and ERS respectively. An average classification accuracy of 87.3% was obtained for five subjects.

SIGNIFICANCE

The results prove that Kolmogorov entropy can effectively quantify the dynamic process of event-related EEG, and it also provides a novel method of classifying motor imagery tasks from scalp EEG by Kolmogorov entropy measurement with promising classification accuracy.

A novel method for reducing the effect of tonic muscle activity on the gamma band of the scalp EEG

Neural oscillations in the gamma band are of increasing interest, but separating them from myogenic electrical activity has proved difficult. A novel algorithm has been developed to reduce the effect of tonic scalp and neck muscle activity on the gamma band of the EEG. This uses mathematical modelling to fit individual muscle spikes and then subtracts them from the data. The method was applied to the detection of motor associated gamma in two separate groups of eight subjects using different sampling rates. A reproducible increase in high gamma (65-85 Hz) magnitude occurred immediately after the motor action in the left central area (p = 0.02 and p = 0.0002 for the two cohorts with individually optimized algorithm parameters, compared to p = 0.03 and p = 0.16 before correction). Whilst the magnitude of this event-related gamma synchronisation was not reduced by the application of the EMG reduction algorithm, the baseline left central gamma magnitude was significantly reduced by an average of 23 % with a faster sampling rate (p < 0.05). In comparison, at left and right temporo-parietal locations the gamma amplitude was reduced by 60 and 54 % respectively (p < 0.05). The reduction of EMG contamination by fitting and subtraction of individual spikes shows promise as a method of improving the signal to noise ratio of high frequency neural oscillations in scalp EEG.

Basal ganglia activity patterns in parkinsonism and computational modeling of their downstream effects

The availability of suitable animal models and the opportunity to record electrophysiologic data in movement disorder patients undergoing neurosurgical procedures has allowed researchers to investigate parkinsonism-related changes in neuronal firing patterns in the basal ganglia and associated areas of the thalamus and cortex. These studies have shown that parkinsonism is associated with increased activity in the basal ganglia output nuclei, along with increases in burst discharges, oscillatory firing and synchronous firing patterns throughout the basal ganglia. Computational approaches have the potential to play an important role in the interpretation of these data. Such efforts can provide a formalized view of neuronal interactions in the network of connections between the basal ganglia, thalamus, and cortex, allow for the exploration of possible contributions of particular network components to parkinsonism, and potentially result in new conceptual frameworks and hypotheses that can be subjected to biological testing. It has proven very difficult, however, to integrate the wealth of the experimental findings into coherent models of the disease. In this review, we provide an overview of the abnormalities in neuronal activity that have been associated with parkinsonism. Subsequently, we discuss some particular efforts to model the pathophysiologic mechanisms that may link abnormal basal ganglia activity to the cardinal parkinsonian motor signs and may help to explain the mechanisms underlying the therapeutic efficacy of deep brain stimulation for Parkinson's disease. We emphasize the logical structure of these computational studies, making clear the assumptions from which they proceed and the consequences and predictions that follow from these assumptions.

Interactions between visual and motor areas during the recognition of plausible actions as revealed by magnetoencephalography

Several studies have shown activation of the mirror neuron system (MNS), comprising the temporal, posterior parietal, and sensorimotor areas when observing plausible actions, but far less is known on how these cortical areas interact during the recognition of a plausible action. Here, we recorded neural activity with magnetoencephalography while subjects viewed point-light displays of biologically plausible and scrambled versions of actions. We were interested in modulations of oscillatory activity and, specifically, in coupling of oscillatory activity between visual and motor areas. Both plausible and scrambled actions elicited modulations of θ (5-7 Hz), α (7-13 Hz), β (13-35 Hz), and γ (55-100 Hz) power within visual and motor areas. When comparing between the two actions, we observed sequential and spatially distinct increases of γ (∼65 Hz), β (∼25 Hz), and α (∼11 Hz) power between 0.5 and 1.3 s in parieto-occipital, sensorimotor, and left temporal areas. In addition, significant clusters of γ (∼65 Hz) and α/β (∼15 Hz) power decrease were observed in right temporal and parieto-occipital areas between 1.3 and 2.0 s. We found β-power in sensorimotor areas to be positively correlated on a trial-by-trial basis with parieto-occipital γ and left temporal α-power for the plausible but not for the scrambled condition. These results provide new insights in the neuronal oscillatory activity of the areas involved in the recognition of plausible action movements and their interaction. The power correlations between specific areas underscore the importance of interactions between visual and motor areas of the MNS during the recognition of a plausible action.

Differential Go/NoGo activity in both contingent negative variation and spectral power

We investigated whether both the contingent negative variation (CNV), an event-related potential index of preparatory brain activity, and event-related oscillatory EEG activity differentiated Go and NoGo trials in a delayed response task. CNV and spectral power (4-100 Hz) were calculated from EEG activity in the preparatory interval in 16 healthy adult participants. As previously reported, CNV amplitudes were higher in Go compared to NoGo trials. In addition, event-related spectral power of the Go condition was reduced in the theta to low gamma range compared to the NoGo condition, confirming that preparing to respond is associated with modulation of event-related spectral activity as well as the CNV. Altogether, the impact of the experimental manipulation on both slow event-related potentials and oscillatory EEG activity may reflect coordinated dynamic changes in the excitability of distributed neural networks involved in preparation.

Action-related semantic content and negation polarity modulate motor areas during sentence reading: an event-related desynchronization study

Our study evaluated motor cortex involvement during silent reading of sentences referring to hand actions. We aimed at defining whether sentential polarity (affirmative vs. negative) would modulate motor cortex activation using the event-related desynchronization (ERD) analysis of the mu rhythm. Eleven healthy volunteers performed a reading task involving 160 sentences (80 affirmative: 40 hand-related, 40 abstract; 80 negative: 40 hand-related, 40 abstract). After reading each sentence, subjects had to decide whether the verb was high or low frequency in Italian. Electroencephalographic (EEG) activity was recorded with 32 surface electrodes and mu ERD analyses were performed for each subject. Hand-action related sentences induced a greater mu ERD over the left premotor and motor hand areas compared to abstract sentences. Mu ERD was greater and temporally delayed when the hand-related verbs were presented in the negative versus affirmative form. As predicted by the "embodied semantic" theory of language understanding, motor areas were activated during sentences referring to hand actions. In addition, motor cortex activation was larger for negative than affirmative motor sentences, a finding compatible with the hypothesis that comprehension is more demanding in the specific case of motor content negation.

Neural synchrony within the motor system: what have we learned so far?

Synchronization of neural activity is considered essential for information processing in the nervous system. Both local and inter-regional synchronization are omnipresent in different frequency regimes and relate to a variety of behavioral and cognitive functions. Over the years, many studies have sought to elucidate the question how alpha/mu, beta, and gamma synchronization contribute to motor control. Here, we review these studies with the purpose to delineate what they have added to our understanding of the neural control of movement. We highlight important findings regarding oscillations in primary motor cortex, synchronization between cortex and spinal cord, synchronization between cortical regions, as well as abnormal synchronization patterns in a selection of motor dysfunctions. The interpretation of synchronization patterns benefits from combining results of invasive and non-invasive recordings, different data analysis tools, and modeling work. Importantly, although synchronization is deemed to play a vital role, it is not the only mechanism for neural communication. Spike timing and rate coding act together during motor control and should therefore both be accounted for when interpreting movement-related activity.

Level of participation in robotic-assisted treadmill walking modulates midline sensorimotor EEG rhythms in able-bodied subjects

In robot assisted gait training, a pattern of human locomotion is executed repetitively with the intention to restore the motor programs associated with walking. Several studies showed that active contribution to the movement is critical for the encoding of motor memory. We propose to use brain monitoring techniques during gait training to encourage active participation in the movement. We investigated the spectral patterns in the electroencephalogram (EEG) that are related to active and passive robot assisted gait. Fourteen healthy participants were considered. Infomax independent component analysis separated the EEG into independent components representing brain, muscle, and eye movement activity, as well as other artifacts. An equivalent current dipole was calculated for each independent component. Independent components were clustered across participants based on their anatomical position and frequency spectra. Four clusters were identified in the sensorimotor cortices that accounted for differences between active and passive walking or showed activity related to the gait cycle. We show that in central midline areas the mu (8-12 Hz) and beta (18-21 Hz) rhythms are suppressed during active compared to passive walking. These changes are statistically significant: mu (F(1, 13)=11.2 p ≤ 0.01) and beta (F(1, 13)=7.7, p ≤ 0.05). We also show that these differences depend on the gait cycle phases. We provide first evidence of modulations of the gamma rhythm in the band 25 to 40 Hz, localized in central midline areas related to the phases of the gait cycle. We observed a trend (F(1, 8)=11.03, p ≤ 0.06) for suppressed low gamma rhythm when comparing active and passive walking. Additionally we found significant suppressions of the mu (F(1, 11)=20.1 p ≤ 0.01), beta (F(1, 11)=11.3 p ≤ 0.05) and gamma (F(1, 11)=4.9 p ≤ 0.05) rhythms near C3 (in the right hand area of the primary motor cortex) during phases of active vs. passive robot assisted walking. To our knowledge this is the first study showing EEG analysis during robot assisted walking. We provide evidence for significant differences in cortical activation between active and passive robot assisted gait. Our findings may help to define appropriate features for single trial detection of active participation in gait training. This work is a further step toward the evaluation of brain monitoring techniques and brain-computer interface technologies for improving gait rehabilitation therapies in a top-down approach.

Eye-gaze independent EEG-based brain-computer interfaces for communication

The present review systematically examines the literature reporting gaze independent interaction modalities in non-invasive brain-computer interfaces (BCIs) for communication. BCIs measure signals related to specific brain activity and translate them into device control signals. This technology can be used to provide users with severe motor disability (e.g. late stage amyotrophic lateral sclerosis (ALS); acquired brain injury) with an assistive device that does not rely on muscular contraction. Most of the studies on BCIs explored mental tasks and paradigms using visual modality. Considering that in ALS patients the oculomotor control can deteriorate and also other potential users could have impaired visual function, tactile and auditory modalities have been investigated over the past years to seek alternative BCI systems which are independent from vision. In addition, various attentional mechanisms, such as covert attention and feature-directed attention, have been investigated to develop gaze independent visual-based BCI paradigms. Three areas of research were considered in the present review: (i) auditory BCIs, (ii) tactile BCIs and (iii) independent visual BCIs. Out of a total of 130 search results, 34 articles were selected on the basis of pre-defined exclusion criteria. Thirteen articles dealt with independent visual BCIs, 15 reported on auditory BCIs and the last six on tactile BCIs, respectively. From the review of the available literature, it can be concluded that a crucial point is represented by the trade-off between BCI systems/paradigms with high accuracy and speed, but highly demanding in terms of attention and memory load, and systems requiring lower cognitive effort but with a limited amount of communicable information. These issues should be considered as priorities to be explored in future studies to meet users' requirements in a real-life scenario.

A K-means multivariate approach for clustering independent components from magnetoencephalographic data

Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are confirmed by a comparison with a MEG tailored version of the self-organizing group ICA, which is largely used for fMRI IC clustering.

Reduced movement-related β desynchronisation in juvenile myoclonic epilepsy: a MEG study of task specific cortical modulation

OBJECTIVE

We investigated differences in task induced responses in occipital and sensorimotor cortex between patients with juvenile myclonic epilepsy (JME) and healthy controls .

METHODS

Twelve patients with JME and 12 age-matched non-epilepsy volunteers performed visual and motor tasks during MEG. We used synthetic aperture magnetometry to localise areas of task-related oscillatory modulations, performed time-frequency analyses on the locations of peak task related power changes and compared power and frequency modulation at these locations between patients and controls.

RESULTS

Patients with JME had significantly reduced pre-movement beta event-related desynchronisation in the motor task compared to controls. No significant differences were seen in other motor-related responses, or visual oscillatory responses.

CONCLUSIONS

Altered beta event-related desynchronisation may represent network specific dysfunction in JME possibly through GABAergic dysfunction.

SIGNIFICANCE

Characterising task specific cortical responses in epilepsy offers the potential to understand the patho-physiological basis of seizures and provide a window on disease and treatment effects.