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

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

Neurobehavioral Strategies of Skill Acquisition in Left and Right Hand Dominant Individuals

The brain consists of vast networks of connected pathways communicating through synchronized electrochemical activity propagated along fiber tracts. The current understanding is that the brain has a modular organization where regions of specialized processes are dynamically coupled through long-range projections of dense axonal networks connecting spatially distinct regions enabling signal transfer necessary for all complex thought and behavior, including regulation of movement. The central objective of the dissertation was to understand how sensorimotor information is integrated, allowing for adaptable motor behavior and skill acquisition in the left-and right-hand dominant populations. To this end participants, of both left- and right-hand dominance, repeatedly completed a visually guided, force matching task while neurobiological and neurobehavioral outcome measurements were continuously recorded via EEG and EMG. Functional connectivity and graph theoretical measurements were derived from EEG. Cortico-cortical coherence patterns were used to infer neurostrategic discrepancies employed in the execution of a motor task for each population. EEG activity was also correlated with neuromuscular activity from EMG to calculate cortico-muscular connectivity. Neurological patterns and corresponding behavioral changes were used to express how hand dominance influenced the developing motor plan, thereby increasing understanding of the sensorimotor integration process. The cumulative findings indicated fundamental differences in how left- and right-hand dominant populations interact with the world. The right-hand dominant group was found to rely on visual information to inform motor behavior where the left-hand dominant group used visual information to update motor behavior. The left-hand group was found to have a more versatile motor plan, adaptable to both dominant, nondominant, and bimanual tasks. Compared to the right-hand group it might be said that they were more successful in encoding the task, however behaviorally they performed the same. The implications of the findings are relevant to both clinical and performance applications providing insight as to potential alternative methods of information integration. The inclusion of the left-hand dominant population in the growing conceptualization of the brain will generate a more complete, stable, and accurate understanding of our complex biology

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke

Examining Lower Extremity Motor Activity Using Magnetoencephalography

The role of the cortex during locomotion remains unclear, but recent advances in neural imaging technologies have aided in developing ways to measure brain activity during motor tasks. One method is by measuring activations produced by neural oscillations which have been associated with a variety of human behaviors, from sleep and rest to cognitive actions and movement. The physiological and functional methods in which oscillations contribute to cortical control are still largely unknown. In this study, we aim to expand that knowledge by examining human cortical activity in the sensory and motor cortices during pedaling using magnetoencephalography (MEG). We hypothesized that, if the sensory and motor cortices are important for controlling locomotion, then the MEG signal would differ during pedaling as compared to rest and would be modulated with the phase of the pedaling cycle. Moreover, if locomotor-related brain activity is solely caused by sensory feedback, then the MEG signal would be the same during active and passive pedaling. We scanned eight healthy subjects using MEG while they pedaled a custom-made pedaling device. The subjects’ magnetocortical activity was measured in two minute recordings during rest, continuous, self-paced active pedaling, and passive pedaling. The passive condition consisted of the subject relaxing their leg muscles while the experimenter pedaled the device for them at a velocity matching that subject’s active pedaling bout. Task-dependent magnetocortical activity was examined in the primary sensorimotor cortex (M1 and S1), supplemental motor area (SMA), and premotor area (PMA). The power spectrum of the MEG signal during the different tasks was extracted using a Welch periodogram to examine the frequency content throughout each task. The power in the alpha and beta bands of all regions of interest decreased significantly during active and passive pedaling as compared to rest. No significant difference was found between any of the tasks in the gamma band. The temporal pattern of the beta frequency band was also examined across the pedaling cycle by performing a time-frequency decomposition using a Morlet wavelet. Both pedaling conditions demonstrated modulation of the beta band at twice the pedaling frequency. These fluctuations were not found in the rest condition. Our results showed that the brain becomes engaged during pedaling as compared to rest. The magnetocortical activity is different across the movement cycle, suggesting that the brain has input into the regulation of locomotor-like movement. There is also a strong sensory component during movement since the active and passive pedaling conditions are similar

Arm swing in healthy and Parkinsonian gait:explorations on brain, muscle and movement level

Human bipedal gait exhibits a coherent four-limb movement pattern comparable to that observed in quadrupedal gait, with upper limbs swinging in anti-phase with both opposite upper and ipsilateral lower limbs. Although the role of these upper limb movements in bipedal gait is not as obvious as in quadrupedal gait, one proposed advantage concerns the modulation of neural control to maintain the cyclic gait pattern. This dissertation broadens the knowledge on this supporting role of arm swing in gait control in healthy participants and patients with Parkinson’s Disease (PD), a neurodegenerative disease that affects both lower-limb gait and gait-related arm swing. We used a multi-level approach including electroencephalography, electromyography and gait analyses to explore how this is organized within and between brain, muscle and movement level, respectively. We demonstrated that arm swing can drive and shape lower limb muscle activity via subcortical and cortical pathways, in which the supplementary motor area plays a central role. As a result of this neural interlimb coupling, we found that disturbed upper and lower limb movements in PD gait are correlated. These findings provide neural support for the observed facilitating effect of arm swing instructions on gait initiation and continued gait in PD patients. Overall, this dissertation supports that arm swing instructions or exercises could potentially be used as an effective non-invasive gait rehabilitation method in PD patients

Исследование электрической активности мозга, связанной с движениями: обзор

Робота присвячена розгляду проблем, що виникають при дослідженні діяльності мозку, пов'язаної з рухами. Зміни в корі головного мозку під час виконання руху, а також його уявлення, відображають нейронні мережі, сформовані для планування і реалізації конкретного руху. Наведено огляд методів первинної обробки зареєстрованої активності головного мозку, які можуть бути використані для підвищення значимості виділених ознак. Описано закономірності, які мають місце до початку руху і після нього. Представлені методи, які підходять для оцінки зв'язку як між активністю мозку і активністю м'язів, так і між активністю областей головного мозку. Крім того, розглянута можливість класифікації та прогнозування рухів разом з реконструкцією кінематичних властивостей.The work is devoted to consideration of different problems which arise in studying of the movement-related brain activity. Changes in the cortex activity during performing of the movement both real and imagery represent neural networks formed for planning and performing of the particular motion. The review of possible preprocessing methods of the registered brain activity for increasing significance of extracted features are shown. Regularities and patterns which take place before and after movement onset are described. The methods that suitable for connectivity estimations in case of cortico-muscular relationships and in case of evaluations between brain regions are shown. In addition, possibility of movement classification and prediction together with reconstruction of kinematics features of the motion are considered.Работа посвящена рассмотрению проблем, возникающих при изучении деятельности мозга, связанной с движениями. Изменения в коре головного мозга во время выполнения движения, а также его представления, отображают нейронные сети, сформированные для планирования и реализации конкретного движения. Приведен обзор методов первичной обработки зарегистрированной активности головного мозга, которые могут быть использованы для повышения значимости выделенных признаков. Описаны закономерности, которые имеют место до начала движения и после него. Представлены методы, подходящие для оценки связи как между активностью мозга и активностью мышц, так и между активностью областей головного мозга. Кроме того, рассмотрена возможность классификации и прогнозирования движений вместе с реконструкцией кинематических свойств

Cortical beta oscillations are associated with motor performance following visuomotor learning

© 2019 The Authors People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45–60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session. Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes

Upregulation of cortico-cerebellar functional connectivity after motor learning

Interactions between the cerebellum and primary motor cortex are crucial for the acquisition of new motor skills. Recent neuroimaging studies indicate that learning motor skills is associated with subsequent modulation of resting-state functional connectivity in the cerebellar and cerebral cortices. The neuronal processes underlying the motor-learning-induced plasticity are not well understood. Here, we investigate changes in functional connectivity in source-reconstructed electroencephalography (EEG) following the performance of a single session of a dynamic force task in twenty young adults. Source activity was reconstructed in 112 regions of interest (ROIs) and the functional connectivity between all ROIs was estimated using the imaginary part of coherence. Significant changes in resting-state connectivity were assessed using partial least squares (PLS). We found that subjects adapted their motor performance during the training session and showed improved accuracy but with slower movement times. A number of connections were significantly upregulated after motor training, principally involving connections within the cerebellum and between the cerebellum and motor cortex. Increased connectivity was confined to specific frequency ranges in the mu- and beta-bands. Post hoc analysis of the phase spectra of these cerebellar and cortico-cerebellar connections revealed an increased phase lag between motor cortical and cerebellar activity following motor practice. These findings show a reorganization of intrinsic cortico-cerebellar connectivity related to motor adaptation and demonstrate the potential of EEG connectivity analysis in source space to reveal the neuronal processes that underpin neural plasticity