Enhancing the Signal of Corticomuscular Coherence

The availability of multichannel neuroimaging techniques, such as MEG and EEG, provides us with detailed topographical information of the recorded magnetic and electric signals and therefore gives us a good overview on the concomitant signals generated in the brain. To assess the location and the temporal dynamics of neuronal sources with noninvasive recordings, reconstruction tools such as beamformers have been shown to be useful. In the current study, we are in particular interested in cortical motor control involved in the isometric contraction of finger muscles. To this end we are measuring the interaction between the dynamics of brain signals and the electrical activity of hand muscles. We were interested to find out whether in addition to the well-known correlated activity between contralateral primary motor cortex and the hand muscles, additional functional connections can be demonstrated. We adopted coherence as a functional index and propose a so-called nulling beamformer method which is computationally efficient and addresses the localization of multiple correlated sources. In simulations of cortico-motor coherence, the proposed method was able to correctly localize secondary sources. The application of the approach on real electromyographic and magnetoencephalographic data collected during an isometric contraction and rest revealed an additional activity in the hemisphere ipsilateral to the hand involved in the task

Effects of Noise Electrical Stimulation on Proprioception, Force Control, and Corticomuscular Functional Connectivity

Sensory afferent inputs play an important role in neuromuscular functions. Subsensory level noise electrical stimulation enhances the sensitivity of peripheral sensory system and improves lower extremity motor function. The current study aimed to investigate the immediate effects of noise electrical stimulation on proprioceptive senses and grip force control, and whether there are associated neural activities in the central nervous system. Fourteen healthy adults participated in 2 experiments on 2 different days. In day 1, participants performed grip force and joint proprioceptive tasks with and without (sham) noise electrical stimulation. In day 2, participants performed grip force steady hold task before and after 30-min noise electrical stimulation. Noise stimulation was applied with surface electrodes secured along the course of the median nerve and proximal to the coronoid fossa EEG power spectrum density of bilateral sensorimotor cortex and coherence between EEG and finger flexor EMG were calculated and compared. Wilcoxon Signed-Rank Tests were used to compare the differences of proprioception, force control, EEG power spectrum density and EEG-EMG coherence between noise electrical stimulation and sham conditions. The significance level (alpha) was set at 0.05. Our study found that noise stimulation with optimal intensity could improve both force and joint proprioceptive senses. Furthermore, individuals with higher gamma coherence showed better force proprioceptive sense improvement with 30-min noise electrical stimulation. These observations indicate the potential clinical benefits of noise stimulation on individuals with impaired proprioceptive senses and the characteristics of individuals who might benefit from noise stimulation

State-dependent modulation of cortico-spinal networks

Beta-band rhythm (13-30 Hz) is a dominant oscillatory activity in the sensorimotor system. Numerous studies reported on links between motor performance and the cortical and cortico-spinal beta rhythm. However, these studies report divergent beta-band frequencies and are, additionally, based on differently performed motor-tasks (e.g., motor imagination, muscle contraction, reach, grasp, and attention). This diversity blurs the role of beta in the sensorimotor system. It consequently challenges the development of beta-band activity-dependent stimulation protocols in the sensorimotor system. In this vein, we studied the functional role of beta-band cortico-cortical and cortico-spinal networks during a motor learning task. We studied how the contribution of cortical and spinal beta changes in the course of learning, and how this modulation is affected by afferent feedback to the sensorimotor system. We furthermore researched the relationship to motor performance. Consider that we made our study in the absence of any residual movement to allow our findings to be translated into rehabilitation programs for severely affected stroke patients. This thesis, at first, investigates evoked responses after transcranial magnetic stimulation (TMS). This revealed two different beta-band networks, i.e., in the low and high beta-band reflecting cortical and cortico-spinal activity. We, then, used a broader frequency range in the beta-band to trigger passive opening of the hand (peripheral feedback) or cortical stimulation (cortical feedback). While a unilateral hemispheric increase in cortico-spinal synchronization was observed in the group with peripheral feedback, a bilateral hemispheric increase in cortico-cortical and cortico-spinal synchronization was observed for the group with cortical feedback. An improvement in motor performance was found in the peripheral group only. Additionally, an enhancement in the directed cortico-spinal synchronization from cortex to periphery was observed for the peripheral group. Similar neurophysiological and behavioral changes were observed for stroke patients receiving peripheral feedback. The results 6 suggest two different mechanisms for beta-band activity-dependent protocols depending on the feedback modality. While the peripheral feedback appears to increase the synchronization among neural groups, cortical stimulation appears to recruit dormant neurons and to extend the involved motor network. These findings may provide insights regarding the mechanism behind novel activity-dependent protocols. It also highlights the importance of afferent feedback for motor restoration in beta-band activity-dependent rehabilitation programs

Corticomuscular co-activation based hybrid brain-computer interface for motor recovery monitoring

The effect of corticomuscular coactivation based hybrid brain-computer interface (h-BCI) on post-stroke neurorehabilitation has not been explored yet. A major challenge in this area is to find an appropriate corticomuscular feature which can not only drive an h-BCI but also serve as a biomarker for motor recovery monitoring. Our previous study established the feasibility of a new method of measuring corticomuscular co-activation called correlation of band-limited power time-courses (CBPT) of EEG and EMG signals, outperforming the traditional EEG-EMG coherence in terms of accurately controlling a robotic hand exoskeleton device by the stroke patients. In this paper, we have evaluated the neurophysiological significance of CBPT for motor recovery monitoring by conducting a 5-week long longitudinal pilot trial on 4 chronic hemiparetic stroke patients. Results show that the CBPT variations correlated significantly (p-value< 0.05) with the dynamic changes in motor outcome measures during the therapy for all the patients. As the bandpower based biomarkers are popular in literature, a comparison with such biomarkers has also been made to cross-verify whether the changes in CBPT are indeed neurophysiological. Thus the study concludes that CBPT can serve as a biomarker for motor recovery monitoring while serving as a corticomuscular co-activation feature for h-BCI based neurorehabilitation. Despite an observed significant positive change between pre- and post-intervention motor outcomes, the question of the clinical effectiveness of CBPT is subject to further controlled trial on a larger cohort

Normalized compression distance to measure cortico-muscular synchronization

The neuronal functional connectivity is a complex and non-stationary phenomenon creating dynamic networks synchronization determining the brain states and needed to produce tasks. Here, as a measure that quantifies the synchronization between the neuronal electrical activity of two brain regions, we used the normalized compression distance (NCD), which is the length of the compressed file constituted by the concatenated two signals, normalized by the length of the two compressed files including each single signal. To test the NCD sensitivity to physiological properties, we used NCD to measure the cortico-muscular synchronization, a well-known mechanism to control movements, in 15 healthy volunteers during a weak handgrip. Independently of NCD compressor (Huffman or Lempel Ziv), we found out that the resulting measure is sensitive to the dominant-non dominant asymmetry when novelty management is required (p = 0.011; p = 0.007, respectively) and depends on the level of novelty when moving the nondominant hand (p = 0.012; p = 0.024). Showing lower synchronization levels for less dexterous networks, NCD seems to be a measure able to enrich the estimate of functional two-node connectivity within the neuronal networks that control the body

Cortico-muscular coherence in sensorimotor synchronisation

This thesis sets out to investigate the neuro-muscular control mechanisms underlying the ubiquitous phenomenon of sensorimotor synchronisation (SMS). SMS is the coordination of movement to external rhythms, and is commonly observed in everyday life. A large body of research addresses the processes underlying SMS at the levels of behaviour and brain. Comparatively, little is known about the coupling between neural and behavioural processes, i.e. neuro-muscular processes. Here, the neuro-muscular processes underlying SMS were investigated in the form of cortico-muscular coherence measured based on Electroencephalography (EEG) and Electromyography (EMG) recorded in human healthy participants. These neuro-muscular processes were investigated at three levels of engagement: passive listening and observation of rhythms in the environment, imagined SMS, and executed SMS, which resulted in the testing of three hypotheses: (i) Rhythms in the environment, such as music, spontaneously modulate cortico-muscular coupling, (ii) Movement intention modulates cortico-muscular coupling, and (iii) Cortico-muscular coupling is dynamically modulated during SMS time-locked to the stimulus rhythm. These three hypotheses were tested through two studies that used Electroencephalography (EEG) and Electromyography (EMG) recordings to measure Cortico-muscular coherence (CMC). First, CMC was tested during passive music listening, to test whether temporal and spectral properties of music stimuli known to induce groove, i.e., the subjective experience of wanting to move, can spontaneously modulate the overall strength of the communication between the brain and the muscles. Second, imagined and executed movement synchronisation was used to investigate the role of movement intention and dynamics on CMC. The two studies indicate that both top-down, and somatosensory and/or proprioceptive processes modulate CMC during SMS tasks. Although CMC dynamics might be linked to movement dynamics, no direct correlation between movement performance and CMC was found. Furthermore, purely passive auditory or visual rhythmic stimulation did not affect CMC. Together, these findings thus indicate that movement intention and active engagement with rhythms in the environment might be critical in modulating CMC. Further investigations of the mechanisms and function of CMC are necessary, as they could have important implications for clinical and elderly populations, as well as athletes, where optimisation of motor control is necessary to compensate for impaired movement or to achieve elite performance

Neuromechanical Biomarkers for Robotic Neurorehabilitation

: One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the "biomarkers" that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the "Rehabilomics" has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective

Improving Precision Force Control With Low-Frequency Error Amplification Feedback: Behavioral and Neurophysiological Mechanisms

Although error amplification (EA) feedback has been shown to improve performance on visuomotor tasks, the challenge of EA is that it concurrently magnifies task-irrelevant information that may impair visuomotor control. The purpose of this study was to improve the force control in a static task by preclusion of high-oscillatory components in EA feedback that cannot be timely used for error correction by the visuomotor system. Along with motor unit behaviors and corticomuscular coherence, force fluctuations (Fc) were modeled with non-linear SDA to contrast the reliance of the feedback process and underlying neurophysiological mechanisms by using real feedback, EA, and low-frequency error amplification (LF-EA). During the static force task in the experiment, the EA feedback virtually potentiated the size of visual error, whereas the LF-EA did not channel high-frequency errors above 0.8 Hz into the amplification process. The results showed that task accuracy was greater with the LF-EA than with the real and EA feedback modes, and that LF-EA led to smaller and more complex Fc. LF-EA generally led to smaller SDA variables of Fc (critical time points, critical point of Fc, the short-term effective diffusion coefficient, and short-term exponent scaling) than did real feedback and EA. The use of LF-EA feedback increased the irregularity of the ISIs of MUs but decreased the RMS of the mean discharge rate, estimated with pooled MU spike trains. Beta-range EEG–EMG coherence spectra (13–35 Hz) in the LF-EA condition were the greatest among the three feedback conditions. In summary, amplification of low-frequency errors improves force control by shifting the relative significances of the feedforward and feedback processes. The functional benefit arises from the increase in the common descending drive to promote a stable state of MU discharges