Neuronal network coherent with hand kinematics during fast repetitive hand movements

Interpersonal motor synchrony in autism: a systematic review and meta-analysis

Introduction

Interpersonal motor synchrony (IMS) is the spontaneous, voluntary, or instructed coordination of movements between interacting partners. Throughout the life cycle, it shapes social exchanges and interplays with intra- and inter-individual characteristics that may diverge in Autism Spectrum Disorder (ASD). Here we perform a systematic review and meta-analysis to summarize the extant literature and quantify the evidence about reduced IMS in dyads including at least one participant with a diagnosis of ASD.

Methods

Empirical evidence from sixteen experimental studies was systematically reviewed, encompassing spontaneous and instructed paradigms as well as a paucity of measures used to assess IMS. Of these, thirteen studies (n = 512 dyads) contributed measures of IMS with an in situ neurotypical partner (TD) for ASD and control groups, which could be used for meta-analyses.

Results

Reduced synchronization in ASD-TD dyads emerged from both the systematic review and meta-analyses, although both small and large effect sizes (i.e., Hedge's g) in favor of the control group are consistent with the data (Hedge's g = .85, p < 0.001, 95% CI[.35, 1.35], 95% PI[-.89, 2.60]).

Discussion

Uncertainty is discussed relative to the type of task, measures, and age range considered in each study. We further discuss that sharing similar experiences of the world might help to synchronize with one another. Future studies should not only assess whether reduced IMS is consistently observed in ASD-TD dyads and how this shapes social exchanges, but also explore whether and how ASD-ASD dyads synchronize during interpersonal exchanges.

Brain and muscle activity during fatiguing maximum-speed knee movement

Although the underlying mechanisms behind upper limb (e.g., finger) motor slowing during movements performed at the maximum voluntary rate have been explored, the same cannot be said for the lower limb. This is especially relevant considering the lower limb's larger joints and different functional patterns. Despite the similar motor control base, previously found differences in movement patterns and segment inertia may lead to distinct central and peripheral manifestations of fatigue in larger joint movement. Therefore, we aimed to explore these manifestations in a fatiguing knee maximum movement rate task by measuring brain and muscle activity, as well as brain-muscle coupling using corticomuscular coherence, during this task. A significant decrease in knee movement rate up to half the task duration was observed. After an early peak, brain activity showed a generalized decrease during the first half of the task, followed by a plateau, whereas knee flexor muscle activity showed a continuous decline. A similar decline was also seen in corticomuscular coherence but for both flexor and extensor muscles. The electrophysiological manifestations associated with knee motor slowing therefore showed some common and some distinct aspects compared with smaller joint tasks. Both central and peripheral manifestations of fatigue were observed; the changes seen in both EEG and electromyographic (EMG) variables suggest that multiple mechanisms were involved in exercise regulation and fatigue development.NEW & NOTEWORTHY The loss of knee movement rate with acute fatigue induced by high-speed movement is associated with both central and peripheral electrophysiological changes, such as a decrease in EEG power, increased agonist-antagonist cocontraction, and impaired brain-muscle coupling. These findings had not previously been reported for the knee joint, which shows functional and physiological differences compared with the existing findings for smaller upper limb joints.

Afferents to Action: Cortical Proprioceptive Processing Assessed with Corticokinematic Coherence Specifically Relates to Gross Motor Skills

Voluntary motor control is thought to be predicated on the ability to efficiently integrate and process somatosensory afferent information. However, current approaches in the field of motor control have not factored in objective markers of how the brain tracks incoming somatosensory information. Here, we asked whether motor performance relates to such markers obtained with an analysis of the coupling between peripheral kinematics and cortical oscillations during continuous movements, best known as corticokinematic coherence (CKC). Motor performance was evaluated by measuring both gross and fine motor skills using the Box and Blocks Test (BBT) and the Purdue Pegboard Test (PPT), respectively, and with a biomechanics measure of coordination. A total of 61 participants completed the BBT, while equipped with electroencephalography and electromyography, and the PPT. We evaluated CKC, from the signals collected during the BBT, as the coherence between movement rhythmicity and brain activity, and coordination as the cross-correlation between muscle activity. CKC at movements' first harmonic was positively associated with BBT scores (r = 0.41, p = 0.001), and alone showed no relationship with PPT scores (r = 0.07, p = 0.60), but in synergy with BBT scores, participants with lower PPT scores had higher CKC than expected based on their BBT score. Coordination was not associated with motor performance or CKC (p > 0.05). These findings demonstrate that cortical somatosensory processing in the form of strengthened brain-peripheral coupling is specifically associated with better gross motor skills and thus may be considered as a valuable addition to classical tests of proprioception acuity.

Volitional muscle activation intensifies neuronal processing of proprioceptive afference in the primary sensorimotor cortex: an EEG study

Proprioception refers to the ability to perceive the position and movement of body segments in space. The cortical aspects of the proprioceptive afference from the body can be investigated using corticokinematic coherence (CKC). CKC accurately quantifies the degree of coupling between cortical activity and limb kinematics, especially if precise proprioceptive stimulation of evoked movements is used. However, there is no evidence on how volitional muscle activation during proprioceptive stimulation affects CKC strength. Twenty-five healthy volunteers (28.8 ± 7 yr, 11 females) participated in the experiment, which included electroencephalographic (EEG), electromyographic (EMG), and kinematic recordings. Ankle-joint rotations (2-Hz) were elicited through a movement actuator in two conditions: passive condition with relaxed ankle and active condition with constant 5-Nm plantar flexion exerted during the stimulation. In total, 6 min of data were recorded per condition. CKC strength was defined as the maximum coherence value among all the EEG channels at the 2-Hz movement frequency for each condition separately. Both conditions resulted in significant CKC peaking at the Cz electrode over the foot area of the primary sensorimotor (SM1) cortex. Stronger CKC was found for the active (0.13 ± 0.14) than the passive (0.03 ± 0.04) condition (P < 0.01). The results indicated that volitional activation of the muscles intensifies the neuronal proprioceptive processing in the SM1 cortex. This finding could be explained both by peripheral sensitization of the ankle joint proprioceptors and central modulation of the neuronal proprioceptive processing at the spinal and cortical levels.NEW & NOTEWORTHY The current study is the first to investigate the effect of volitional muscle activation on CKC-based assessment of cortical proprioception of the ankle joint. Results show that the motor efference intensifies the neuronal processing of proprioceptive afference of the ankle joint. This is a significant finding as it may extend the use of CKC method during active tasks to further evaluate the motor efference-proprioceptive afference relationship and the related adaptations to exercise, rehabilitation, and disease.

Decoding movement frequencies and limbs based on steady-state movement-related rhythms from noninvasive EEG

Objective.Decoding different types of movements noninvasively from electroencephalography (EEG) is an essential topic in neural engineering, especially in brain-computer interface. Although the widely used sensorimotor rhythm (SMR) is efficient in limb decoding, it lacks efficacy in decoding movement frequencies. Accumulating evidence supports the notion that the movement frequency is encoded in the steady-state movement-related rhythm (SSMRR). Our study has two primary objectives: firstly, to investigate the spatial-spectral representation of SSMRR in EEG during voluntary movements; secondly, to assess whether movement frequencies and limbs can be effectively decoded based on SSMRR.Approach.To comprehensively examine the representation of SSMRR, we investigated the frequency characteristics and spatial patterns associated with various rhythmic finger movements. Coherence analysis was performed between the sensor or source domain EEG and finger movements recorded by data gloves. A fusion model based on spectral SNR features and filter-bank common spatial pattern features was utilized to decode movement frequencies and limbs.Main results.At the group-level, sensor domain, and source domain coherence maps demonstrated that the accurate movement frequency (f0) and its first harmonic (f1) were encoded in the contralateral motor cortex. For the four-class classification, including two movement frequencies for both hands, the decoding accuracies for externally paced and internally paced movements were 73.14 ± 15.86% and 66.30 ± 17.26% (averaged across ten subjects, chance levels at 31.05% and 30.96%). Notably, the average results of five subjects with the highest decoding accuracies reached 87.21 ± 7.44% and 80.44 ± 7.99%.Significance.Our results verified the EEG representation of SSMRR and proved that the movement frequency and limb could be effectively decoded based on spatial-spectral features extracted from SSMRR. We suggest that SSMRR can serve as a complement to SMR to expand the range of decodable movement types and the approaches of limb decoding.

Proprioceptive response strength in the primary sensorimotor cortex is invariant to the range of finger movement

Proprioception is the sense of body position and movement that relies on afference from the proprioceptors in muscles and joints. Proprioceptive responses in the primary sensorimotor (SM1) cortex can be elicited by stimulating the proprioceptors using evoked (passive) limb movements. In magnetoencephalography (MEG), proprioceptive processing can be quantified by recording the movement evoked fields (MEFs) and movement-induced beta power modulations or by computing corticokinematic coherence (CKC) between the limb kinematics and cortical activity. We examined whether cortical proprioceptive processing quantified with MEF peak strength, relative beta suppression and rebound power and CKC strength is affected by the movement range of the finger. MEG activity was measured from 16 right-handed healthy volunteers while movements were applied to their right-index finger metacarpophalangeal joint with an actuator. Movements were either intermittent, every 3000 ± 250 ms, to estimate MEF or continuous, at 3 Hz, to estimate CKC. In both cases, 4 different ranges of motion of the stimuli were investigated: 15, 18, 22 and 26 mm for MEF and 6, 7, 9 and 13 mm for CKC. MEF amplitude, relative beta suppression and rebound as well as peak CKC strength at the movement frequency were compared between the movement ranges in the source space. Inter-individual variation was also compared between the MEF and CKC strengths. As expected, MEF and CKC responses peaked at the contralateral SM1 cortex. MEF peak, beta suppression and rebound and CKC strengths were similar across all movement ranges. Furthermore, CKC strength showed a lower degree of inter-individual variation compared with MEF strength. Our result of absent modulation by movement range in cortical responses to passive movements of the finger indicates that variability in movement range should not hinder comparability between different studies or participants. Furthermore, our data indicates that CKC is less prone to inter-individual variability than MEFs, and thus more advantageous in what pertains to statistical power.

Proprioception: A New Era Set in Motion by Emerging Genetic and Bionic Strategies?

The generation of an internal body model and its continuous update is essential in sensorimotor control. Although known to rely on proprioceptive sensory feedback, the underlying mechanism that transforms this sensory feedback into a dynamic body percept remains poorly understood. However, advances in the development of genetic tools for proprioceptive circuit elements, including the sensory receptors, are beginning to offer new and unprecedented leverage to dissect the central pathways responsible for proprioceptive encoding. Simultaneously, new data derived through emerging bionic neural machine-interface technologies reveal clues regarding the relative importance of kinesthetic sensory feedback and insights into the functional proprioceptive substrates that underlie natural motor behaviors.

Identification of cerebral cortices processing acceleration, velocity, and position during directional reaching movement with deep neural network and explainable AI

Cerebral cortical representation of motor kinematics is crucial for understanding human motor behavior, potentially extending to efficient control of the brain-computer interface. Numerous single-neuron studies have found the existence of a relationship between neuronal activity and motor kinematics such as acceleration, velocity, and position. Despite differences between kinematic characteristics, it is hard to distinguish neural representations of these kinematic characteristics with macroscopic functional images such as electroencephalography (EEG) and magnetoencephalography (MEG). The reason might be because cortical signals are not sensitive enough to segregate kinematic characteristics due to their limited spatial and temporal resolution. Considering different roles of each cortical area in producing movement, there might be a specific cortical representation depending on characteristics of acceleration, velocity, and position. Recently, neural network modeling has been actively pursued in the field of decoding. We hypothesized that neural features of each kinematic parameter could be identified with a high-performing model for decoding with an explainable AI method. Time-series deep neural network (DNN) models were used to measure the relationship between cortical activity and motor kinematics during reaching movement. With DNN models, kinematic parameters of reaching movement in a 3D space were decoded based on cortical source activity obtained from MEG data. An explainable artificial intelligence (AI) method was then adopted to extract the map of cortical areas, which strongly contributed to decoding each kinematics from DNN models. We found that there existed differed as well as shared cortical areas for decoding each kinematic attribute. Shared areas included bilateral supramarginal gyri and superior parietal lobules known to be related to the goal of movement and sensory integration. On the other hand, dominant areas for each kinematic parameter (the contralateral motor cortex for acceleration, the contralateral parieto-frontal network for velocity, and bilateral visuomotor areas for position) were mutually exclusive. Regarding the visuomotor reaching movement, the motor cortex was found to control the muscle force, the parieto-frontal network encoded reaching movement from sensory information, and visuomotor areas computed limb and gaze coordination in the action space. To the best of our knowledge, this is the first study to discriminate kinematic cortical areas using DNN models and explainable AI.

From thinking fast to moving fast: motor control of fast limb movements in healthy individuals

The ability to produce high movement speeds is a crucial factor in human motor performance, from the skilled athlete to someone avoiding a fall. Despite this relevance, there remains a lack of both an integrative brain-to-behavior analysis of these movements and applied studies linking the known dependence on open-loop, central control mechanisms of these movements to their real-world implications, whether in the sports, performance arts, or occupational setting. In this review, we cover factors associated with the planning and performance of fast limb movements, from the generation of the motor command in the brain to the observed motor output. At each level (supraspinal, peripheral, and motor output), the influencing factors are presented and the changes brought by training and fatigue are discussed. The existing evidence of more applied studies relevant to practical aspects of human performance is also discussed. Inconsistencies in the existing literature both in the definitions and findings are highlighted, along with suggestions for further studies on the topic of fast limb movement control. The current heterogeneity in what is considered a fast movement and in experimental protocols makes it difficult to compare findings in the existing literature. We identified the role of the cerebellum in movement prediction and of surround inhibition in motor slowing, as well as the effects of fatigue and training on central motor control, as possible avenues for further research, especially in performance-driven populations.

Cortical networks show characteristic recruitment patterns after somatosensory stimulation by pneumatically evoked repetitive hand movements in newborn infants

Controlled assessment of functional cortical networks is an unmet need in the clinical research of noncooperative subjects, such as infants. We developed an automated, pneumatic stimulation method to actuate naturalistic movements of an infant’s hand, as well as an analysis pipeline for assessing the elicited electroencephalography (EEG) responses and related cortical networks. Twenty newborn infants with perinatal asphyxia were recruited, including 7 with mild-to-moderate hypoxic–ischemic encephalopathy (HIE). Statistically significant corticokinematic coherence (CKC) was observed between repetitive hand movements and EEG in all infants, peaking near the contralateral sensorimotor cortex. CKC was robust to common sources of recording artifacts and to changes in vigilance state. A wide recruitment of cortical networks was observed with directed phase transfer entropy, also including areas ipsilateral to the stimulation. The extent of such recruited cortical networks was quantified using a novel metric, Spreading Index, which showed a decrease in 4 (57%) of the infants with HIE. CKC measurement is noninvasive and easy to perform, even in noncooperative subjects. The stimulation and analysis pipeline can be fully automated, including the statistical evaluation of the cortical responses. Therefore, the CKC paradigm holds great promise as a scientific and clinical tool for controlled assessment of functional cortical networks.

Feature stability and setup minimization for EEG-EMG-enabled monitoring systems

Delivering health care at home emerged as a key advancement to reduce healthcare costs and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training applications, wearable and portable devices can be employed for movement recognition and monitoring of the associated brain signals. This is one of the contexts where it is essential to minimize the monitoring setup and the amount of data to collect, process, and share. In this paper, we address this challenge for a monitoring system that includes high-dimensional EEG and EMG data for the classification of a specific type of hand movement. We fuse EEG and EMG into the magnitude squared coherence (MSC) signal, from which we extracted features using different algorithms (one from the authors) to solve binary classification problems. Finally, we propose a mapping-and-aggregation strategy to increase the interpretability of the machine learning results. The proposed approach provides very low mis-classification errors ( < 0.1 ), with very few and stable MSC features ( < 10 % of the initial set of available features). Furthermore, we identified a common pattern across algorithms and classification problems, i.e., the activation of the centro-parietal brain areas and arm's muscles in 8-80 Hz frequency band, in line with previous literature. Thus, this study represents a step forward to the minimization of a reliable EEG-EMG setup to enable gesture recognition.

Temporally stable beta sensorimotor oscillations and cortico-muscular coupling underlie force steadiness

As humans, we seamlessly hold objects in our hands, and may even lose consciousness of these objects. This phenomenon raises the unsettled question of the involvement of the cerebral cortex, the core area for voluntary motor control, in dynamically maintaining steady muscle force. To address this issue, we measured magnetoencephalographic brain activity from healthy adults who maintained a steady pinch grip. Using a novel analysis approach, we uncovered fine-grained temporal modulations in the beta sensorimotor brain rhythm and its coupling with muscle activity, with respect to several aspects of muscle force (rate of increase/decrease or plateauing high/low). These modulations preceded changes in force features by ∼40 ms and possessed behavioral relevance, as less salient or absent modulation predicted a more stable force output. These findings have consequences for the existing theories regarding the functional role of cortico-muscular coupling, and suggest that steady muscle contractions are characterized by a stable rather than fluttering involvement of the sensorimotor cortex.

The role of reading experience in atypical cortical tracking of speech and speech-in-noise in dyslexia

Dyslexia is a frequent developmental disorder in which reading acquisition is delayed and that is usually associated with difficulties understanding speech in noise. At the neuronal level, children with dyslexia were reported to display abnormal cortical tracking of speech (CTS) at phrasal rate. Here, we aimed to determine if abnormal tracking relates to reduced reading experience, and if it is modulated by the severity of dyslexia or the presence of acoustic noise. We included 26 school-age children with dyslexia, 26 age-matched controls and 26 reading-level matched controls. All were native French speakers. Children's brain activity was recorded with magnetoencephalography while they listened to continuous speech in noiseless and multiple noise conditions. CTS values were compared between groups, conditions and hemispheres, and also within groups, between children with mild and severe dyslexia. Syllabic CTS was significantly reduced in the right superior temporal gyrus in children with dyslexia compared with controls matched for age but not for reading level. Severe dyslexia was characterized by lower rapid automatized naming (RAN) abilities compared with mild dyslexia, and phrasal CTS lateralized to the right hemisphere in children with mild dyslexia and all control groups but not in children with severe dyslexia. Finally, an alteration in phrasal CTS was uncovered in children with dyslexia compared with age-matched controls in babble noise conditions but not in other less challenging listening conditions (non-speech noise or noiseless conditions); no such effect was seen in comparison with reading-level matched controls. Overall, our results confirmed the finding of altered neuronal basis of speech perception in noiseless and babble noise conditions in dyslexia compared with age-matched peers. However, the absence of alteration in comparison with reading-level matched controls demonstrates that such alterations are associated with reduced reading level, suggesting they are merely driven by reduced reading experience rather than a cause of dyslexia. Finally, our result of altered hemispheric lateralization of phrasal CTS in relation with altered RAN abilities in severe dyslexia is in line with a temporal sampling deficit of speech at phrasal rate in dyslexia.

Oscillatory dynamics underlying noun and verb production in highly proficient bilinguals

Words representing objects (nouns) and words representing actions (verbs) are essential components of speech across languages. While there is evidence regarding the organizational principles governing neural representation of nouns and verbs in monolingual speakers, little is known about how this knowledge is represented in the bilingual brain. To address this gap, we recorded neuromagnetic signals while highly proficient Spanish-Basque bilinguals performed a picture-naming task and tracked the brain oscillatory dynamics underlying this process. We found theta (4-8 Hz) power increases and alpha-beta (8-25 Hz) power decreases irrespectively of the category and language at use in a time window classically associated to the controlled retrieval of lexico-semantic information. When comparing nouns and verbs within each language, we found theta power increases for verbs as compared to nouns in bilateral visual cortices and cognitive control areas including the left SMA and right middle temporal gyrus. In addition, stronger alpha-beta power decreases were observed for nouns as compared to verbs in visual cortices and semantic-related regions such as the left anterior temporal lobe and right premotor cortex. No differences were observed between categories across languages. Overall, our results suggest that noun and verb processing recruit partially different networks during speech production but that these category-based representations are similarly processed in the bilingual brain.

Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system

Corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. Here, we introduce a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC with deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1.

Reaching to inhibit a prepotent response: A wearable 3-axis accelerometer kinematic analysis

The present work explores the distinctive contribution of motor planning and control to human reaching movements. In particular, the movements were triggered by the selection of a prepotent response (Dominant) or, instead, by the inhibition of the prepotent response, which required the selection of an alternative one (Non-dominant). To this end, we adapted a Go/No-Go task to investigate both the dominant and non-dominant movements of a cohort of 19 adults, utilizing kinematic measures to discriminate between the planning and control components of the two actions. In this experiment, a low-cost, easy to use, 3-axis wrist-worn accelerometer was put to good use to obtain raw acceleration data and to compute and break down its velocity components. The values obtained with this task indicate that with the inhibition of a prepotent response, the selection and execution of the alternative one yields both a longer reaction time and movement duration. Moreover, the peak velocity occurred later in time in the non-dominant response with respect to the dominant response, revealing that participants tended to indulge more in motor planning than in adjusting their movement along the way. Finally, comparing such results to the findings obtained by other means in the literature, we discuss the feasibility of an accelerometer-based analysis to disentangle distinctive cognitive mechanisms of human movements.

Corticokinematic coherence is stronger to regular than irregular proprioceptive stimulation of the hand

Proprioceptive afference can be investigated using corticokinematic coherence (CKC), which indicates coupling between limb kinematics and cortical activity. CKC has been quantified using proprioceptive stimulation (movement actuators) with fixed interstimulus interval (ISI). However, it is unclear how regularity of the stimulus sequence (jitter) affects CKC strength. Eighteen healthy volunteers (16 right-handed, 27.8 ± 5.0 yr, 7 females) participated in magnetoencephalography (MEG) session in which their right index finger was continuously moved at ∼3 Hz with Constant 333 ms ISI or with 20% Jitter (ISI 333 ± 66 ms) using a pneumatic-movement actuator. Three minutes of data per condition were collected. Finger kinematics were recorded with a three-axis accelerometer. CKC strength was defined as the peak coherence value in the Rolandic MEG gradiometer pair contralateral to the movement at 3 Hz. Both conditions resulted in significant coherence peaking in the gradiometers over the primary sensorimotor cortex. Constant stimulation yielded stronger CKC at 3 Hz (0.78 ± 0.11 vs. 0.66 ± 0.13, P < 0.001) and its first harmonic (0.60 ± 0.19 vs. 0.27 ± 0.11, P < 0.001) than irregular stimulation. Similarly, the respective sustained-movement evoked field was also stronger for constant stimulation. The results emphasize the importance of temporal stability of the proprioceptive stimulation sequence when quantifying CKC strength. The weaker CKC during irregular stimulation can be explained with temporal and thus spectral scattering of the paired peripheral and cortical events beyond the mean stimulation frequency. This impairs the signal-to-noise ratio of respective MEG signal and thus CKC strength. When accurately estimating and following changes in CKC strength, we suggest using precise movement actuators with constant stimulation sequence.NEW & NOTEWORTHY Cortical proprioceptive processing can be investigated using corticokinematic coherence (CKC). The findings show that CKC method is sensitive to temporal stability in the stimulation sequence. Although both regular and irregular sequences resulted in robust coherence, the regular stimulation sequence with pneumatic movement actuator is recommended to maximize coherence strength and reproducibility to allow better comparability between groups or populations.

Pneumatic artificial muscle-based stimulator for passive functional magnetic resonance imaging sensorimotor mapping in patients with brain tumours

BACKGROUND

Two concerns with respect to pre-operative task-based motor functional magnetic resonance imaging (fMRI) in patients with brain tumours are inadequate performance due to patients' impaired motor function and head motion artefacts.

NEW METHOD

In the present study we validate the use of a stimulator based on a pneumatic artificial muscle (PAM) for fMRI mapping of the primary sensorimotor (SM1) cortex in twenty patients with rolandic or perirolandic brain tumours. All patients underwent both active and passive motor block-design fMRI paradigms, performing comparable active and passive PAM-induced flexion-extensions of the icontralesional index finger.

RESULTS

PAM-induced movements resulted in a significant BOLD signal increase in contralateral primary motor (M1) and somatosensory (S1) cortices in 18/20 and 19/20 (p<.05 FWE corrected in 16/18 and 18/19) patients, versus 18/20 and 16/20 (p<.05 FWE corrected) during active movements. The two patients in whom the PAM-based stimulator failed to induce any significant BOLD signal change in the contralateral M1 cortex differed from the two in whom active motion was conversely ineffective. At the group level, no significant difference in contrast magnitude was observed within the contralateral SM1 cortex when comparing active with passive movements. During passive movements, head motion was significantly reduced. Comparison with existing method(s) As compared to the several robotic devices for passive motion that were introduced in the past decades, our PAM-based stimulator appears smaller, handier, and easier to use.

CONCLUSION

The use of PAM-based stimulators should be included in routine pre-operative fMRI protocols along with active paradigms in such patients' population.

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

In 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, cortico-kinematic 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.

Feasibility and reproducibility of electroencephalography-based corticokinematic coherence

The most important message in this report is that the corticokinematic coherence (CKC) method is a feasible and reproducible tool to quantify, map, and follow cortical proprioceptive (“the movement sense”) processing using EEG that is more widely available for CKC recordings than previously used magnetoencephalographic designs, in basic research, but especially in clinical environments. We provide useful recommendations for optimal EEG derivations for cost-effective experimental designs, allowing large sample size studies.

Evidence for genetically determined degeneration of proprioceptive tracts in Friedreich ataxia

OBJECTIVE

To assess with magnetoencephalography the developmental vs progressive character of the impairment of spinocortical proprioceptive pathways in Friedreich ataxia (FRDA).

METHODS

Neuromagnetic signals were recorded from 16 right-handed patients with FRDA (9 female patients, mean age 27 years, mean Scale for the Assessment and Rating Of ataxia [SARA] score 22.25) and matched healthy controls while they performed right finger movements either actively or passively. The coupling between movement kinematics (i.e., acceleration) and neuromagnetic signals was assessed by the use of coherence at sensor and source levels. Such coupling, that is, the corticokinematic coherence (CKC), specifically indexes proprioceptive afferent inputs to the contralateral primary sensorimotor (cSM1) cortex. Nonparametric permutations and Spearman rank correlation test were used for statistics.

RESULTS

In both groups of participants and movement conditions, significant coupling peaked at the cSM1 cortex. Coherence levels were 70% to 75% lower in patients with FRDA than in healthy controls in both movement conditions. In patients with FRDA, coherence levels correlated with genotype alteration (i.e., the size of GAA1 triplet expansion) and the age at symptom onset but not with disease duration or SARA score.

CONCLUSION

This study provides electrophysiologic evidence demonstrating that proprioceptive impairment in FRDA is mostly genetically determined and scarcely progressive after symptom onset. It also positions CKC as a reliable, robust, specific marker of proprioceptive impairment in FRDA.

Localization of Sensorimotor Cortex Using Navigated Transcranial Magnetic Stimulation and Magnetoencephalography

The mapping of the sensorimotor cortex gives information about the cortical motor and sensory functions. Typical mapping methods are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG). The differences between these mapping methods are, however, not fully known. TMS center of gravities (CoGs), MEG somatosensory evoked fields (SEFs), corticomuscular coherence (CMC), and corticokinematic coherence (CKC) were mapped in ten healthy adults. TMS mapping was performed for first dorsal interosseous (FDI) and extensor carpi radialis (ECR) muscles. SEFs were induced by tactile stimulation of the index finger. CMC and CKC were determined as the coherence between MEG signals and the electromyography or accelerometer signals, respectively, during voluntary muscle activity. CMC was mapped during the activation of FDI and ECR muscles separately, whereas CKC was measured during the waving of the index finger at a rate of 3–4 Hz. The maximum CMC was found at beta frequency range, whereas maximum CKC was found at the movement frequency. The mean Euclidean distances between different localizations were within 20 mm. The smallest distance was found between TMS FDI and TMS ECR CoGs and longest between CMC FDI and CMC ECR sites. TMS-inferred localizations (CoGs) were less variable across participants than MEG-inferred localizations (CMC, CKC). On average, SEF locations were 8 mm lateral to the TMS CoGs (p < 0.01). No differences between hemispheres were found. Based on the results, TMS appears to be more viable than MEG in locating motor cortical areas.

Cortical Tracking of Speech-in-Noise Develops from Childhood to Adulthood

In multitalker backgrounds, the auditory cortex of adult humans tracks the attended speech stream rather than the global auditory scene. Still, it is unknown whether such preferential tracking also occurs in children whose speech-in-noise (SiN) abilities are typically lower compared with adults. We used magnetoencephalography (MEG) to investigate the frequency-specific cortical tracking of different elements of a cocktail party auditory scene in 20 children (age range, 6-9 years; 8 females) and 20 adults (age range, 21-40 years; 10 females). During MEG recordings, subjects attended to four different 5 min stories, mixed with different levels of multitalker background at four signal-to-noise ratios (SNRs; noiseless, +5, 0, and -5 dB). Coherence analysis quantified the coupling between the time courses of the MEG activity and attended speech stream, multitalker background, or global auditory scene, respectively. In adults, statistically significant coherence was observed between MEG signals originating from the auditory system and the attended stream at <1, 1-4, and 4-8 Hz in all SNR conditions. Children displayed similar coupling at <1 and 1-4 Hz, but increasing noise impaired the coupling more strongly than in adults. Also, children displayed drastically lower coherence at 4-8 Hz in all SNR conditions. These results suggest that children's difficulties to understand speech in noisy conditions are related to an immature selective cortical tracking of the attended speech streams. Our results also provide unprecedented evidence for an acquired cortical tracking of speech at syllable rate and argue for a progressive development of SiN abilities in humans.SIGNIFICANCE STATEMENT Behaviorally, children are less proficient than adults at understanding speech-in-noise. Here, neuromagnetic signals were recorded while healthy adults and typically developing 6- to 9-year-old children attended to a speech stream embedded in a multitalker background noise with varying intensity. Results demonstrate that auditory cortices of both children and adults selectively track the attended speaker's voice rather than the global acoustic input at phrasal and word rates. However, increments of noise compromised the tracking significantly more in children than in adults. Unexpectedly, children displayed limited tracking of both the attended voice and the global acoustic input at the 4-8 Hz syllable rhythm. Thus, both speech-in-noise abilities and cortical tracking of speech syllable repetition rate seem to mature later in adolescence.

Neuromagnetic Cerebellar Activity Entrains to the Kinematics of Executed Finger Movements

This magnetoencephalography (MEG) study aims at characterizing the coupling between cerebellar activity and the kinematics of repetitive self-paced finger movements. Neuromagnetic signals were recorded in 11 right-handed healthy adults while they performed repetitive flexion-extensions of right-hand fingers at three different movement rates: slow (~ 1 Hz), medium (~ 2 Hz), and fast (~ 3 Hz). Right index finger acceleration was monitored with an accelerometer. Coherence analysis was used to index the coupling between right index finger acceleration and neuromagnetic signals. Dynamic imaging of coherent sources was used to locate coherent sources. Coupling directionality between primary sensorimotor (SM1), cerebellar, and accelerometer signals was assessed with renormalized partial directed coherence. Permutation-based statistics coupled with maximum statistic over the entire brain volume or restricted to the cerebellum were used. At all movement rates, maximum coherence peaked at SM1 cortex contralateral to finger movements at movement frequency (F0) and its first harmonic (F1). Significant (statistics restricted to the cerebellum) coherence consistently peaked at the right posterior lobe of the cerebellum at F0 with no influence of movement rate. Coupling between Acc and cerebellar signals was significantly stronger in the afferent than in the efferent direction with no effective contribution of cortico-cerebellar or cerebello-cortical pathways. This study demonstrates the existence of significant coupling between finger movement kinematics and neuromagnetic activity at the posterior cerebellar lobe ipsilateral to finger movement at F0. This coupling is mainly driven by spinocerebellar, presumably proprioceptive, afferences.

Movement Kinematics Dynamically Modulates the Rolandic ~ 20-Hz Rhythm During Goal-Directed Executed and Observed Hand Actions

This study investigates whether movement kinematics modulates similarly the rolandic α and β rhythm amplitude during executed and observed goal-directed hand movements. It also assesses if this modulation relates to the corticokinematic coherence (CKC), which is the coupling observed between cortical activity and movement kinematics during such motor actions. Magnetoencephalography (MEG) signals were recorded from 11 right-handed healthy subjects while they performed or observed an actor performing the same repetitive hand pinching action. Subjects' and actor's forefinger movements were monitored with an accelerometer. Coherence was computed between acceleration signals and the amplitude of α (8-12 Hz) or β (15-25 Hz) oscillations. The coherence was also evaluated between source-projected MEG signals and their β amplitude. Coherence was mainly observed between acceleration and the amplitude of β oscillations at movement frequency within bilateral primary sensorimotor (SM1) cortex with no difference between executed and observed movements. Cross-correlation between the amplitude of β oscillations at the SM1 cortex and movement acceleration was maximal when acceleration was delayed by ~ 100 ms, both during movement execution and observation. Coherence between source-projected MEG signals and their β amplitude during movement observation and execution was not significantly different from that during rest. This study shows that observing others' actions engages in the viewer's brain similar dynamic modulations of SM1 cortex β rhythm as during action execution. Results support the view that different neural mechanisms might account for this modulation and CKC. These two kinematic-related phenomena might help humans to understand how observed motor actions are actually performed.

Contrasting functional imaging parametric maps: The mislocation problem and alternative solutions

In the field of neuroimaging, researchers often resort to contrasting parametric maps to identify differences between conditions or populations. Unfortunately, contrast patterns mix effects related to amplitude and location differences and tend to peak away from sources of genuine brain activity to an extent that scales with the smoothness of the maps. Here, we illustrate this mislocation problem on source maps reconstructed from magnetoencephalographic recordings and propose a novel, dedicated location-comparison method. In realistic simulations, contrast mislocation was on average ∼10 mm when genuine sources were placed at the same location, and was still above 5 mm when sources were 20 mm apart. The dedicated location-comparison method achieved a sensitivity of ∼90% when inter-source distance was 12 mm. Its benefit is also illustrated on real brain-speech entrainment data. In conclusion, contrasts of parametric maps provide precarious information for source location. To specifically address the question of location difference, one should turn to dedicated methods as the one proposed here.

MEG Insight into the Spectral Dynamics Underlying Steady Isometric Muscle Contraction

To gain fundamental knowledge on how the brain controls motor actions, we studied in detail the interplay between MEG signals from the primary sensorimotor (SM1) cortex and the contraction force of 17 healthy adult humans (7 females, 10 males). SM1 activity was coherent at ∼20 Hz with surface electromyogram (as already extensively reported) but also with contraction force. In both cases, the effective coupling was dominant in the efferent direction. Across subjects, the level of ∼20 Hz coherence between cortex and periphery positively correlated with the “burstiness” of ∼20 Hz SM1 (Pearson r ≈ 0.65) and peripheral fluctuations (r ≈ 0.9). Thus, ∼20 Hz coherence between cortex and periphery is tightly linked to the presence of ∼20 Hz bursts in SM1 and peripheral activity. However, the very high correlation with peripheral fluctuations suggests that the periphery is the limiting factor. At frequencies <3 Hz, both SM1 signals and ∼20 Hz SM1 envelope were coherent with both force and its absolute change rate. The effective coupling dominated in the efferent direction between (1) force and the ∼20 Hz SM1 envelope and (2) the absolute change rate of the force and SM1 signals. Together, our data favor the view that ∼20 Hz coherence between cortex and periphery during isometric contraction builds on the presence of ∼20 Hz SM1 oscillations and needs not rely on feedback from the periphery. They also suggest that effective cortical proprioceptive processing operates at <3 Hz frequencies, even during steady isometric contractions.

SIGNIFICANCE STATEMENT Accurate motor actions are made possible by continuous communication between the cortex and spinal motoneurons, but the neurophysiological basis of this communication is poorly understood. Using MEG recordings in humans maintaining steady isometric muscle contractions, we found evidence that the cortex sends population-level motor commands that tend to structure according to the ∼20 Hz sensorimotor rhythm, and that it dynamically adapts these commands based on the <3 Hz fluctuations of proprioceptive feedback. To our knowledge, this is the first report to give a comprehensive account of how the human brain dynamically handles the flow of proprioceptive information and converts it into appropriate motor command to keep the contraction force steady.

Investigation of the effects of transcranial alternating current stimulation (tACS) on self-paced rhythmic movements

Human rhythmic movements spontaneously entrain to external rhythmic stimuli. Such sensory-motor entrainment can attract movements to different tempi and enhance their efficiency, with potential clinical applications for motor rehabilitation. Here we investigate whether entrainment of self-paced rhythmic movements can be induced via transcranial alternating current stimulation (tACS), which uses alternating currents to entrain spontaneous brain oscillations at specific frequencies. Participants swung a handheld pendulum at their preferred tempo with the right hand while tACS was applied over their left or right primary motor cortex at frequencies equal to their preferred tempo (Experiment 1) or in the alpha (10Hz) and beta (20Hz) ranges (Experiment 2). Given that entrainment generally occurs only if the frequency difference between two rhythms is small, stimulations were delivered at frequencies equal to participants' preferred movement tempo (≈1Hz) and ±12.5% in Experiment 1, and at 10Hz and 20Hz, and ±12.5% in Experiment 2. The comparison of participants' movement frequency, amplitude, variability, and phase synchrony with and without tACS failed to reveal entrainment or movement modifications across the two experiments. However, significant differences in stimulation-related side effects reported by participants were found between the two experiments, with phosphenes and burning sensations principally occurring in Experiment 2, and metallic tastes reported marginally more often in Experiment 1. Although other stimulation protocols may be effective, our results suggest that rhythmic movements such as pendulum swinging or locomotion that are low in goal-directedness and/or strongly driven by peripheral and mechanical constraints may not be susceptible to modulation by tACS.

Left Superior Temporal Gyrus Is Coupled to Attended Speech in a Cocktail-Party Auditory Scene

Using a continuous listening task, we evaluated the coupling between the listener's cortical activity and the temporal envelopes of different sounds in a multitalker auditory scene using magnetoencephalography and corticovocal coherence analysis. Neuromagnetic signals were recorded from 20 right-handed healthy adult humans who listened to five different recorded stories (attended speech streams), one without any multitalker background (No noise) and four mixed with a "cocktail party" multitalker background noise at four signal-to-noise ratios (5, 0, -5, and -10 dB) to produce speech-in-noise mixtures, here referred to as Global scene. Coherence analysis revealed that the modulations of the attended speech stream, presented without multitalker background, were coupled at ∼0.5 Hz to the activity of both superior temporal gyri, whereas the modulations at 4-8 Hz were coupled to the activity of the right supratemporal auditory cortex. In cocktail party conditions, with the multitalker background noise, the coupling was at both frequencies stronger for the attended speech stream than for the unattended Multitalker background. The coupling strengths decreased as the Multitalker background increased. During the cocktail party conditions, the ∼0.5 Hz coupling became left-hemisphere dominant, compared with bilateral coupling without the multitalker background, whereas the 4-8 Hz coupling remained right-hemisphere lateralized in both conditions. The brain activity was not coupled to the multitalker background or to its individual talkers. The results highlight the key role of listener's left superior temporal gyri in extracting the slow ∼0.5 Hz modulations, likely reflecting the attended speech stream within a multitalker auditory scene.

SIGNIFICANCE STATEMENT

When people listen to one person in a "cocktail party," their auditory cortex mainly follows the attended speech stream rather than the entire auditory scene. However, how the brain extracts the attended speech stream from the whole auditory scene and how increasing background noise corrupts this process is still debated. In this magnetoencephalography study, subjects had to attend a speech stream with or without multitalker background noise. Results argue for frequency-dependent cortical tracking mechanisms for the attended speech stream. The left superior temporal gyrus tracked the ∼0.5 Hz modulations of the attended speech stream only when the speech was embedded in multitalker background, whereas the right supratemporal auditory cortex tracked 4-8 Hz modulations during both noiseless and cocktail-party conditions.

Neural signatures of hand kinematics in leaders vs. followers: A dual-MEG study

During joint actions, people typically adjust their own actions according to the ongoing actions of the partner, which implies that the interaction modulates the behavior of both participants. However, the neural substrates of such mutual adaptation are still poorly understood. Here, we set out to identify the kinematics-related brain activity of leaders and followers performing hand actions.

Sixteen participants as 8 pairs performed continuous, repetitive right-hand opening and closing actions with ~3-s cycles in a leader–follower task. Subjects played each role for 5 min. Magnetoencephalographic (MEG) brain signals were recorded simultaneously from both partners with a dual-MEG setup, and hand kinematics was monitored with accelerometers. Modulation index, a cross-frequency coupling measure, was computed between the hand acceleration and the MEG signals in the alpha (7–13 Hz) and beta (13–25 Hz) bands.

Regardless of the participants' role, the strongest alpha and beta modulations occurred bilaterally in the sensorimotor cortices. In the occipital region, beta modulation was stronger in followers than leaders; these oscillations originated, according to beamformer source reconstructions, in early visual cortices. Despite differences in the modulation indices, alpha and beta power did not differ between the conditions.

Our results indicate that the beta modulation in the early visual cortices depends on the subject's role as a follower or leader in a joint hand-action task. This finding could reflect the different strategies employed by leaders and followers in integrating kinematics-related visual information to control their own actions.

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Pairs of subjects performed hand movements as a leader and follower in a dual-MEG setup.

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Alpha and beta powers did not differ between followers and leaders.

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Alpha and beta modulation indices were strongest at bilateral sensorimotor cortices.

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Beta modulation was stronger in leaders than followers in the early visual cortex.

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The role might influence the integration of kinematics-related visual information to control one's own movements.

Phasic stabilization of motor output after auditory and visual distractors

To maintain steady motor output, distracting sensory stimuli need to be blocked. To study the effects of brief auditory and visual distractors on the human primary motor (M1) cortex, we monitored magnetoencephalographic (MEG) cortical rhythms, electromyogram (EMG) of finger flexors, and corticomuscular coherence (CMC) during right-hand pinch (force 5-7% of maximum) while 1-kHz tones and checkerboard patterns were presented for 100 ms once every 3.5-5 s. Twenty-one subjects (out of twenty-two) showed statistically significant ∼20-Hz CMC. Both distractors elicited a covert startle-like response evident in changes of force and EMG (∼50% of the background variation) but without any visible movement, followed by ∼1-s enhancement of CMC (auditory on average by 75%, P < 0.001; visual by 33%, P < 0.05) and rolandic ∼20-Hz rhythm (auditory by 14%, P < 0.05; visual by 11%, P < 0.01). Directional coupling of coherence from muscle to the M1 cortex (EMG→MEG) increased for ∼0.5 s at the onset of the CMC enhancement, but only after auditory distractor (by 105%; P < 0.05), likely reflecting startle-related proprioceptive afference. The 20-Hz enhancements occurred in the left M1 cortex and were for the auditory stimuli preceded by an early suppression (by 7%, P < 0.05). Task-unrelated distractors modulated corticospinal coupling at ∼20 Hz. We propose that the distractors triggered covert startle-like responses, resulting in proprioceptive afference to the cortex, and that they also transiently disengaged the subject's attention from the fine-motor task. As a result, the corticospinal output was readjusted to keep the contraction force stable.

A geometric correction scheme for spatial leakage effects in MEG/EEG seed-based functional connectivity mapping

Spatial leakage effects are particularly confounding for seed-based investigations of brain networks using source-level electroencephalography (EEG) or magnetoencephalography (MEG). Various methods designed to avoid this issue have been introduced but are limited to particular assumptions about its temporal characteristics. Here, we investigate the usefulness of a model-based geometric correction scheme (GCS) to suppress spatial leakage emanating from the seed location. We analyze its properties theoretically and then assess potential advantages and limitations with simulated and experimental MEG data (resting state and auditory-motor task). To do so, we apply Minimum Norm Estimation (MNE) for source reconstruction and use variation of error parameters, statistical gauging of spatial leakage correction and comparison with signal orthogonalization. Results show that the GCS has a local (i.e., near the seed) effect only, in line with the geometry of MNE spatial leakage, and is able to map spatially all types of brain interactions, including linear correlations eliminated after signal orthogonalization. Furthermore, it is robust against the introduction of forward model errors. On the other hand, the GCS can be affected by local overcorrection effects and seed mislocation. These issues arise with signal orthogonalization too, although significantly less extensively, so the two approaches complement each other. The GCS thus appears to be a valuable addition to the spatial leakage correction toolkits for seed-based FC analyses in source-projected MEG/EEG data.

Spatiotemporal oscillatory dynamics during the encoding and maintenance phases of a visual working memory task

Many electrophysiology studies have examined neural oscillatory activity during the encoding, maintenance, and/or retrieval phases of various working memory tasks. Together, these studies have helped illuminate the underlying neural dynamics, although much remains to be discovered and some findings have not replicated in subsequent work. In this study, we examined the oscillatory dynamics that serve visual working memory operations using high-density magnetoencephalography (MEG) and advanced time-frequency and beamforming methodology. Specifically, we recorded healthy adults while they performed a high-load, Sternberg-type working memory task, and focused on the encoding and maintenance phases. We found significant 9-16 Hz desynchronizations in the bilateral occipital cortices, left dorsolateral prefrontal cortex (DLPFC), and left superior temporal areas throughout the encoding phase. Our analysis of the dynamics showed that the left DLPFC and superior temporal desynchronization became stronger as a function of time during the encoding period, and was sustained throughout most of the maintenance phase until sharply decreasing in the milliseconds preceding retrieval. In contrast, desynchronization in occipital areas became weaker as a function of time during encoding and eventually evolved into a strong synchronization during the maintenance period, consistent with previous studies. These results provide clear evidence of dynamic network-level processes during the encoding and maintenance phases of working memory, and support the notion of a dynamic pattern of functionally-discrete subprocesses within each working memory phase. The presence of such dynamic oscillatory networks may be a potential source of inconsistent findings in this literature, as neural activity within these networks changes dramatically with time.

Exploring how musical rhythm entrains brain activity with electroencephalogram frequency-tagging

The ability to perceive a regular beat in music and synchronize to this beat is a widespread human skill. Fundamental to musical behaviour, beat and meter refer to the perception of periodicities while listening to musical rhythms and often involve spontaneous entrainment to move on these periodicities. Here, we present a novel experimental approach inspired by the frequency-tagging approach to understand the perception and production of rhythmic inputs. This approach is illustrated here by recording the human electroencephalogram responses at beat and meter frequencies elicited in various contexts: mental imagery of meter, spontaneous induction of a beat from rhythmic patterns, multisensory integration and sensorimotor synchronization. Collectively, our observations support the view that entrainment and resonance phenomena subtend the processing of musical rhythms in the human brain. More generally, they highlight the potential of this approach to help us understand the link between the phenomenology of musical beat and meter and the bias towards periodicities arising under certain circumstances in the nervous system. Entrainment to music provides a highly valuable framework to explore general entrainment mechanisms as embodied in the human brain.

Corticokinematic coherence mainly reflects movement-induced proprioceptive feedback

Corticokinematic coherence (CKC) reflects coupling between magnetoencephalographic (MEG) signals and hand kinematics, mainly occurring at hand movement frequency (F0) and its first harmonic (F1). Since CKC can be obtained for both active and passive movements, it has been suggested to mainly reflect proprioceptive feedback to the primary sensorimotor (SM1) cortex. However, the directionality of the brain-kinematics coupling has not been previously assessed and was thus quantified in the present study by means of renormalized partial directed coherence (rPDC). MEG data were obtained from 15 subjects who performed right index-finger movements and whose finger was, in another session, passively moved, with or without tactile input. Four additional subjects underwent the same task with slowly varying movement pace, spanning the 1-5 Hz frequency range. The coupling between SM1 activity recorded with MEG and finger kinematics was assessed with coherence and rPDC. In all conditions, the afferent rPDC spectrum, which resembled the coherence spectrum, displayed higher values than the efferent rPDC spectrum. The afferent rPDC was 37% higher when tactile input was present, and it was at highest at F1 of the passive conditions; the efferent rPDC level did not differ between conditions. The apparent latency for the afferent input, estimated within the framework of the rPDC analysis, was 50-100 ms. The higher directional coupling between hand kinematics and SM1 activity in afferent than efferent direction strongly supports the view that CKC mainly reflects movement-related somatosensory proprioceptive afferent input to the contralateral SM1 cortex.

Linking motor-related brain potentials and velocity profiles in multi-joint arm reaching movements

The study of the movement related brain potentials (MRPBs) needs accurate technical approaches to disentangle the specific patterns of bran activity during the preparation and execution of movements. During the last forty years, synchronizing the electromyographic activation (EMG) of the muscle with electrophysiological recordings (EEG) has been commonly ussed for these purposes. However, new clinical approaches in the study of motor diseases and rehabilitation suggest the demand of new paradigms that might go further into the study of the brain activity associated with the kinematics of movements. As a response to this call, we have used a 3-D hand-tracking system with the aim to record continuously the position of an ultrasonic sender attached to the hand during the performance of multi-joint self-paced movements. We synchronized time-series of position and velocity of the sender with the EEG recordings, obtaining specific patterns of brain activity as a function of the fluctuations of the kinematics during natural movement performance. Additionally, the distribution of the brain activity during the preparation and execution phases of movements was similar that reported previously using the EMG, suggesting the validity of our technique. We claim that this paradigm could be usable in patients because of its simplicity and the potential knowledge that can be extracted from clinical protocols.

Human primary motor cortex is both activated and stabilized during observation of other person's phasic motor actions

When your favourite athlete flops over the high-jump bar, you may twist your body in front of the TV screen. Such automatic motor facilitation, 'mirroring' or even overt imitation is not always appropriate. Here, we show, by monitoring motor-cortex brain rhythms with magnetoencephalography (MEG) in healthy adults, that viewing intermittent hand actions of another person, in addition to activation, phasically stabilizes the viewer's primary motor cortex, with the maximum of half a second after the onset of the seen movement. Such a stabilization was evident as enhanced cortex-muscle coherence at 16-20 Hz, despite signs of almost simultaneous suppression of rolandic rhythms of approximately 7 and 15 Hz as a sign of activation of the sensorimotor cortex. These findings suggest that inhibition suppresses motor output during viewing another person's actions, thereby withholding unintentional imitation.

Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration

Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI) in combination with structural equation modeling (SEM). This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

Preserved coupling between the reader's voice and the listener's cortical activity in autism spectrum disorders

Purpose

Investigating the steadiness of the phase-coupling between the time-course of the reader's voice and brain signals of subjects with autism spectrum disorder (ASD) passively listening to connected speech using magnetoencephalography (MEG). In typically developed subjects, such coupling occurs at the right posterior temporal sulcus (pSTS) for frequencies below 1 Hz, and reflects the neural processing of sentence-level rhythmic prosody at the prelexical level.

Methods

Cortical neuromagnetic signals were recorded with MEG (Elekta Oy, Finland) while seven right-handed and native French-speaking ASD subjects (six males, one female, range: 13–20 years) listened to live (Live) or recorded (Recorded) voices continuously reading a text in French for five minutes. Coherence was computed between the reader's voice time-course and ASD subjects' MEG signals. Coherent neural sources were subsequently reconstructed using a beamformer.

Key findings

Significant coupling was found at 0.5 Hz in all ASD subjects in Live and in six subjects in Recorded. Coherent sources were located close to the right pSTS in both conditions. No significant difference was found in coherence levels between Live and Recorded, and between ASD subjects and ten typically developed subjects (right-handed, native French-speaking adults, 5 males, 5 females, age range: 21–38 years) included in a previous study.

Significance

This study discloses a preserved coupling between the reader's voice and ASD subjects' cortical activity at the right pSTS. These findings support the existence of preserved neural processing of sentence-level rhythmic prosody in ASD. The preservation of early cortical processing of prosodic elements in verbal language might be exploited in therapeutic interventions in ASD.

Rate control and quality assurance during rhythmic force tracking

Movement characteristics can be coded in the single neurons or in the summed activity of neural populations. However, whether neural oscillations are conditional to the frequency demand and task quality of rhythmic force regulation is still unclear. This study was undertaken to investigate EEG dynamics and behavior correlates during force-tracking at different target rates. Fourteen healthy volunteers conducted load-varying isometric abduction of the index finger by coupling the force output to sinusoidal targets at 0.5 Hz, 1.0 Hz, and 2.0 Hz. Our results showed that frequency demand significantly affected EEG delta oscillation (1-4 Hz) in the C3, CP3, CPz, and CP4 electrodes, with the greatest delta power and lowest delta peak around 1.5 Hz for slower tracking at 0.5 Hz. Those who had superior tracking congruency also manifested enhanced alpha oscillation (8-12 Hz). Alpha rhythms of the skilled performers during slow tracking spread through the whole target cycle, except for the phase of direction changes. However, the alpha rhythms centered at the mid phase of a target cycle with increasing target rate. In conclusion, our findings clearly suggest two advanced roles of cortical oscillation in rhythmic force regulation. Rate-dependent delta oscillation involves a paradigm shift in force control under different time scales. Phasic organization of alpha rhythms during rhythmic force tracking is related to behavioral success underlying the selective use of bimodal controls (feedback and feedforward processes) and the timing of attentional focus on the target's peak velocity.