Identification of time-varying cortico-cortical and cortico-muscular coherence during motor tasks with multivariate autoregressive models

Neural populations coordinate at fast subsecond time-scales during rest and task execution. As a result, functional brain connectivity assessed with different neuroimaging modalities (EEG, MEG, fMRI) may also change over different time scales. In addition to the more commonly used sliding window techniques, the General Linear Kalman Filter (GLFK) approach has been proposed to estimate time-varying brain connectivity. In the present work, we propose a modification of the GLFK approach to model time-varying connectivity. We also propose a systematic method to select the hyper-parameters of the model. We evaluate the performance of the method using MEG and EMG data collected from 12 young subjects performing two motor tasks (unimanual and bimanual hand grips), by quantifying time-varying cortico-cortical and cortico-muscular coherence (CCC and CMC). The CMC results revealed patterns in accordance with earlier findings, as well as an improvement in both time and frequency resolution compared to sliding window approaches. These results suggest that the proposed methodology is able to unveil accurate time-varying connectivity patterns with an excellent time resolution

Corticomuscular interactions during different movement periods in a multi-joint compound movement

While much is known about motor control during simple movements, corticomuscular communication profiles during compound movement control remain largely unexplored. Here, we aimed at examining frequency band related interactions between brain and muscles during different movement periods of a bipedal squat (BpS) task utilizing regression corticomuscular coherence (rCMC), as well as partial directed coherence (PDC) analyses. Participants performed 40 squats, divided into three successive movement periods (Eccentric (ECC), Isometric (ISO) and Concentric (CON)) in a standardized manner. EEG was recorded from 32 channels specifically-tailored to cover bilateral sensorimotor areas while bilateral EMG was recorded from four main muscles of BpS. We found both significant CMC and PDC (in beta and gamma bands) during BpS execution, where CMC was significantly elevated during ECC and CON when compared to ISO. Further, the dominant direction of information flow (DIF) was most prominent in EEG-EMG direction for CON and EMG-EEG direction for ECC. Collectively, we provide novel evidence that motor control during BpS is potentially achieved through central motor commands driven by a combination of directed inputs spanning across multiple frequency bands. These results serve as an important step toward a better understanding of brain-muscle relationships during multi joint compound movements.V.V.N was supported by the HSE Basic Research Program and the Russian Academic Excellence Project '5–100'. This study was supported by the Max-Planck Society

Sensorimotor Mapping With MEG: An Update on the Current State of Clinical Research and Practice With Considerations for Clinical Practice Guidelines

Published: November 2020In this article, we present the clinical indications and advances in the use of magnetoencephalography to map the primary sensorimotor (SM1) cortex in neurosurgical patients noninvasively. We emphasize the advantages of magnetoencephalography over sensorimotor mapping using functional magnetic resonance imaging. Recommendations to the referring physicians and the clinical magnetoencephalographers to achieve appropriate sensorimotor cortex mapping using magnetoencephalography are proposed. We finally provide some practical advice for the use of corticomuscular coherence, corticokinematic coherence, and mu rhythm suppression in this indication. Magnetoencephalography should now be considered as a method of reference for presurgical functional mapping of the sensorimotor cortex.X. De Ti ege is Post-doctorate Clinical Master Specialist at the Fonds de la Recherche Scientifique (FRS-FNRS, Brussels, Belgium). M. Bourguignon has been supported by the program Attract of Innoviris (Grant 2015-BB2B-10), by the Spanish Ministry of Economy and Competitiveness (Grant PSI2016- 77175-P), and by the Marie Sk1odowska-Curie Action of the European Commission (Grant 743562). H. Piitulainen has been supported by the Academy of Finland (Grants #266133 and #296240), the Jane and Aatos Erkko Foundation, and the Emil Aaltonen Foundation. The authors thank Professor Riitta Hari for her support in most of the research works published by the authors and presented in this article. The MEG project at the CUB H^opital Erasme is financially supported by the Fonds Erasme (Research convention “Les Voies du Savoir,” Fonds Erasme, Brussels, Belgium)

Design and validation of a wireless Body Sensor Network for integrated EEG and HD-sEMG acquisitions

Sensorimotor integration is the process through which the human brain plans the motor program execution according to external sources. Within this context, corticomuscular and corticokinematic coherence analyses are common methods to investigate the mechanism underlying the central control of muscle activation. This requires the synchronous acquisition of several physiological signals, including EEG and sEMG. Nevertheless, physical constraints of the current, mostly wired, technologies limit their application in dynamic and naturalistic contexts. In fact, although many efforts were made in the development of biomedical instrumentation for EEG and HD-sEMG signal acquisition, the need for an integrated wireless system is emerging. We hereby describe the design and validation of a new fully wireless body sensor network for the integrated acquisition of EEG and HD-sEMG signals. This Body Sensor Network is composed of wireless bio-signal acquisition modules, named sensor units, and a set of synchronization modules used as a general-purpose system for time-locked recordings. The system was characterized in terms of accuracy of the synchronization and quality of the collected signals. An in-depth characterization of the entire system and an end-to-end comparison of the wireless EEG sensor unit with a wired benchmark EEG device were performed. The proposed device represents an advancement of the State-of-the-Art technology allowing the integrated acquisition of EEG and HD-sEMG signals for the study of sensorimotor integration

NON INVASIVE INVESTIGATION OF SENSORIMOTOR CONTROL FOR FUTURE DEVELOPMENT OF BRAIN-MACHINE-INTERFACE (BMI)

My thesis focuses on describing novel functional connectivity properties of the sensorimotor system that are of potential interest in the field of brain-machine interface. In particular, I have investigated how the connectivity changes as a consequence of either pathologic conditions or spontaneous fluctuations of the brain's internal state. An ad-hoc electronic device has been developed to implement the appropriate experimental settings. First, the functional communication among sensorimotor primary nodes was investigated in multiple sclerosis patients afflicted by persistent fatigue. I selected this condition, for which there is no effective pharmacological treatment, since existing literature links this type of fatigue to the motor control system. In this study, electroencephalographic (EEG) and electromyographic (EMG) traces were acquired together with the pressure exerted on a bulb during an isometric hand grip. The results showed a higher frequency connection between central and peripheral nervous systems (CMC) and an overcorrection of the exerted movement in fatigued multiple sclerosis patients. In fact, even though any fatigue-dependent brain and muscular oscillatory activity alterations were absent, their connectivity worked at higher frequencies as fatigue increased, explaining 67% of the fatigue scale (MFIS) variance (p=.002). In other terms, the functional communication within the central-peripheral nervous systems, namely involving primary sensorimotor areas, was sensitive to tiny alterations in neural connectivity leading to fatigue, well before the appearance of impairments in single nodes of the network. The second study was about connectivity intended as propagation of information and studied in dependence on spontaneous fluctuations of the sensorimotor system triggered by an external stimulus. Knowledge of the propagation mechanisms and of their changes is essential to extract significant information from single trials. The EEG traces were acquired during transcranial magnetic stimulation (TMS) to yield to a deeper knowledge about the response to an external stimulation while the cortico-spinal system passes through different states. The results showed that spontaneous increases of the excitation of the node originating the transmission within the hand control network gave rise to dynamic recruitment patterns with opposite behaviors, weaker in homotopic and parietal circuits, stronger in frontal ones. As probed by TMS, this behavior indicates that the effective connectivity within bilateral circuits orchestrating hand control are dynamically modulated in time even in resting state. The third investigation assessed the plastic changes in the sensorimotor system after stroke induced by 3 months of robotic rehabilitation in chronic phase. A functional source extraction procedure was applied on the acquired EEG data, enabling the investigation of the functional connectivity between homologous areas in the resting state. The most significant result was that the clinical ameliorations were associated to a ‘normalization’ of the functional connectivity between homologous areas. In fact, the brain connectivity did not necessarily increase or decrease, but it settled within a ‘physiological’ range of connectivity. These studies strengthen our knowledge about the behavioral role of the functional connectivity among neuronal networks’ nodes, which will be essential in future developments of enhanced rehabilitative interventions, including brain-machine interfaces. The presented research also moves the definition of new indices of clinical state evaluation relevant for compensating interventions, a step forward

EEG Characterization of Sensorimotor Networks: Implications in Stroke

The purpose of this dissertation was to use electroencephalography (EEG) to characterize sensorimotor networks and examine the effects of stroke on sensorimotor networks. Sensorimotor networks play an essential role in completion of everyday tasks, and when damaged, as in stroke survivors, the successful completion of seemingly simple motor tasks becomes fantasy. When sensorimotor networks are impaired as a result of stroke, varying degrees of sensorimotor deficits emerge, most often including loss of sensation and difficulty generating upper extremity movements. Although sensory therapies, such as the application of tendon vibration, have been shown to reduce the sensorimotor deficits after stroke, the underlying sensorimotor mechanisms associated with such improvements are unknown. While sensorimotor networks have been studied extensively, unanswered questions still surround their role in basic control paradigms and how their role changes after stroke. EEG provides a way to probe the high-speed temporal dynamics of sensorimotor networks that other more common imaging modalities lack. Sensorimotor network function was examined in controls during a task designed to differentiate potential mechanisms of arm stabilization and determine to what degree the sensorimotor network is involved. After sensorimotor network function was characterized in controls, we examined the effect of stroke on the sensorimotor network during rest and described the reorganization that occurs. Lastly, we explored tendon vibration as a sensory therapy for stroke survivors and determined if sensorimotor network mechanisms underlie improvements in arm tracking performance due to wrist tendon vibration. We observed cortical activity and connectivity that suggests sensorimotor networks are involved in the control of arm stability, cortical networks reorganize to more asymmetric, local networks after stroke, and tendon vibration normalizes sensorimotor network activity and connectivity during motor control after stroke. This dissertation was among the first studies using EEG to characterize the high-speed temporal dynamics of sensorimotor networks following stroke. This new knowledge has led to a better understanding of how sensorimotor networks function under ordinary circumstances as well as extreme situations such as stroke and revealed previously unknown mechanisms by which tendon vibration improves motor control in stroke survivors, which will lead to better therapeutic approaches

A neurophysiological examination of voluntary isometric contractions: modulations in sensorimotor oscillatory dynamics with contraction force and physical fatigue, and peripheral contributions to maximal force production

Human motor control is a complex process involving both central and peripheral components of the nervous system. Type Ia afferent input contributes to both motor unit recruitment and firing frequency, however, whether maximal force production is dependent on this input is unclear. Therefore, chapter 2 examined maximal and explosive force production of the knee extensors following prolonged infrapatellar tendon vibration; designed to attenuate the efficacy of the homonymous Ia afferent-α-motoneuron pathway. Despite a marked decrease in H-reflex amplitude, indicating an attenuated efficacy of the Ia afferent-α-motoneuron pathway, both maximal and explosive force production were unaffected after vibration. This suggested that maximal and explosive isometric quadriceps force production was not dependent upon Ia afferent input to the homonymous motor unit pool. Voluntary movements are linked with various modulations in ongoing neural oscillations within the supraspinal sensorimotor system. Despite considerable interest in the oscillatory responses to movements per se, the influence of the motor parameters that define these movements is poorly understood. Subsequently, chapters 3 and 4 investigated how the motor parameters of voluntary contractions modulated the oscillatory amplitude. Chapter 3 recorded electroencephalography from the leg area of the primary sensorimotor cortex in order to investigate the oscillatory responses to isometric unilateral contractions of the knee-extensors at four torque levels (15, 30, 45 and 60% max.). An increase in movement-related gamma (30-50 Hz) activity was observed with increments in knee-extension torque, whereas oscillatory power within the delta (0.5-3 Hz), theta (3-7 Hz), alpha (7-13 Hz) and beta (13-30 Hz) bands were unaffected. Chapter 4 examined the link between the motor parameters of voluntary contraction and modulations in beta (15-30 Hz) oscillations; specifically, movement-related beta decrease (MRBD) and post-movement beta rebound (PMBR). Magnetoencephalography (MEG) was recorded during isometric ramp and constant-force wrist-flexor contractions at distinct rates of force development (10.4, 28.9 and 86.7% max./s) and force output (5, 15, 35 and 60%max.), respectively. MRBD was unaffected by RFD or force output, whereas systematic modulation of PMBR by both contraction force and RFD was identified for the first time. Specifically, increments in isometric contraction force increased PMBR amplitude, and increments in RFD increased PMBR amplitude but decreased PMBR duration. Physical fatigue arises not only from peripheral processes within the active skeletal muscles but also from supraspinal mechanisms within the brain. However, exactly how cortical activity is modulated during fatigue has received a paucity of attention. Chapter 5 investigated whether oscillatory activity within the primary sensorimotor cortex was modulated when contractions were performed in a state of physical fatigue. MEG was recorded during submaximal isometric contractions of the wrist-flexors performed both before and after a fatiguing series of isometric wrist-flexions or a time matched control intervention. Physical fatigue offset the attenuation in MRBD observed during the control trial, whereas PMBR was increased when submaximal contractions were performed in a fatigued state

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

Changes in the location of cortico-muscular coherence following stroke

Stroke results in reorganization of residual brain networks. The functional role of brain regions within these networks remains unclear, particularly those in the contralesional hemisphere. We studied 25 stroke patients with a range of motor impairment and 23 healthy age-matched controls using magnetoencephalography (MEG) and electromyography (EMG) to measure oscillatory signals from the brain and affected muscles simultaneously during a simple isometric hand grip, from which cortico-muscular coherence (CMC) was calculated. Peaks of cortico-muscular coherence in both the beta and gamma bands were found in the contralateral sensorimotor cortex in all healthy controls, but were more widespread in stroke patients, including some peaks found in the contralesional hemisphere (7 patients for beta coherence and 5 for gamma coherence). Neither the coherence value nor the distance of the coherence peak from the mean of controls correlated with impairment. Peak CMC in the contralesional hemisphere was found not only in some highly impaired patients, but also in some patients with good functional recovery. Our results provide evidence that a wide range of cortical brain regions, including some in the contralesional hemisphere, may have influence over EMG activity in the affected muscles after stroke thereby supporting functional recovery