The neural basis of intermittent motor control in humans

The central nervous system adjusts muscle synergy structure and tightly controls rollator-supported transitions between sitting and standing

BACKGROUND

Older individuals are at risk of falling. Assistive devices like rollators help to reduce that risk, especially by compensating for decreased leg muscle strength and balance problems. Paradoxically, rollators have been found to be a fall risk as well as being difficult to use. To investigate the causes, this study examines how different levels of rollator support (no assistance, light touch, and full support) and balance demands (standard lab floor, balance pads) affect movement coordination during standing up and sitting down movements.

METHODS

Twenty young participants stood up and sat down while full-body kinematics and muscle activity (30 channels) were recorded. Participants stood up and sat down using different movement strategies (e.g., forward leaning, hybrid, and vertical rise standing up movement strategies). For each movement strategy, spatial and temporal muscle synergies were extracted from the muscle activity patterns. Temporal muscle synergies provided a more compact, low-dimensional representation than spatial muscle synergies, so they were subsequently clustered with k-means++. The activation duration of the temporal muscle synergies was assessed with full-width at half-maximum at the main peak. Multivariate linear mixed models were used to investigate if the muscle weightings associated with the temporal muscle synergies differed across the support conditions.

RESULTS

The timings of the temporal muscle synergy activations, but not the shape, differed across the movement strategies for both types of movement. Across all tasks, temporal muscle synergies showed a narrower width of activation around the time of seat-off and seat-on than at the movement start and end. No support-specific temporal muscle synergies were found, but lower limb muscle weightings decreased while upper-limb muscle weightings increased with increased support.

CONCLUSION

The narrow shape of the temporal synergy activation profiles suggests that the central nervous system controls the movements tightly, especially around seat-off and seat-on and in challenging conditions with increased balance demands. Furthermore, rollator support increases the weightings of upper body and decreases the weightings of lower limb muscles, especially around seat-off and seat-on. Future studies may further investigate how the loss of tight movement control may cause falls in older individuals.

A novel method for estimating functional connectivity from EEG coherence potentials

Analysis of functional connectivity can provide insights into how the brain performs various cognitive and behavioral tasks as well as the neural mechanisms underlying several pathologies. In this work, we describe a novel approach to estimate functional connectivity from electroencephalography (EEG) data using the concept of coherence potentials (CPs), which are defined as clusters of high-amplitude deflections with similar waveform shapes. We define connectivity measures based on features of CPs, including the time intervals between CP peaks and their co-occurrence on different electrodes or channels. We used EEG data from 25 healthy subjects performing three tasks - resting state (eyes closed and eyes open), working memory and pattern completion tasks to investigate the ability of CP based connectivity measures to distinguish between these tasks. When compared with traditional connectivity measures including several spectral-based measures and mutual information, our results showed that CP based connectivity measures more robustly and significantly distinguished between all the tasks both at group-level and subject-level. In conclusion, CP based EEG connectivity measures provide a reliable way to distinguish between different cognitive task conditions and could pave way in the early detection of neurological disorders such as Alzheimer's disease that affect various cognitive tasks.

Recognition of brain activities via graph-based long short-term memory-convolutional neural network

Introduction

Human brain activities are always difficult to recognize due to its diversity and susceptibility to disturbance. With its unique capability of measuring brain activities, magnetoencephalography (MEG), as a high temporal and spatial resolution neuroimaging technique, has been used to identify multi-task brain activities. Accurately and robustly classifying motor imagery (MI) and cognitive imagery (CI) from MEG signals is a significant challenge in the field of brain-computer interface (BCI).

Methods

In this study, a graph-based long short-term memory-convolutional neural network (GLCNet) is proposed to classify the brain activities in MI and CI tasks. It was characterized by implementing three modules of graph convolutional network (GCN), spatial convolution and long short-term memory (LSTM) to effectively extract time-frequency-spatial features simultaneously. For performance evaluation, our method was compared with six benchmark algorithms of FBCSP, FBCNet, EEGNet, DeepConvNets, Shallow ConvNet and MEGNet on two public datasets of MEG-BCI and BCI competition IV dataset 3.

Results

The results demonstrated that the proposed GLCNet outperformed other models with the average accuracies of 78.65% and 65.8% for two classification and four classification on the MEG-BCI dataset, respectively.

Discussion

It was concluded that the GLCNet enhanced the model's adaptability in handling individual variability with robust performance. This would contribute to the exploration of brain activates in neuroscience.

Neural signatures of temporal anticipation in human cortex represent event probability density

Temporal prediction is a fundamental function of neural systems. Recent results show that humans anticipate future events by calculating probability density functions, rather than hazard rates. However, direct neural evidence for this hypothesized mechanism is lacking. We recorded neural activity using magnetoencephalography as participants anticipated auditory and visual events distributed in time. We show that temporal anticipation, measured as reaction times, approximates the event probability density function, but not hazard rate. Temporal anticipation manifests as spatiotemporally patterned activity in three anatomically and functionally distinct parieto-temporal and sensorimotor cortical areas. Each of these areas revealed a marked neural signature of anticipation: Prior to sensory cues, activity in a specific frequency range of neural oscillations, spanning alpha and beta ranges, encodes the event probability density function. These neural signals predicted reaction times to imminent sensory cues. These results demonstrate that supra-modal representations of probability density across cortex underlie the anticipation of future events.

Correlation analysis of upper limb muscle activation in the frequency domain in wheelchair fencers

Background

The study includes a correlation analysis of EMG signals of upper limb muscle activity in wheelchair fencers. The aim of the study was to investigate neuromuscular conduction in wheelchair fencers using the EMG signal from their upper limb muscles.

Methods

Wavelet transform analysis was used to examine the biosignals. The recorded EMG signals were subjected to time-frequency transformations. The scalograms were determined using the continuous wavelet transform. Based on the analysis, time-frequency coherence maps were extracted to determine validation in the frequency bands: 2-16 Hz, 17-30 Hz, and 31-60 Hz. The study participants were 16 wheelchair fencers, members of the Polish Paralympic Team, in two disability categories: 7 in category A and 9 in category B. Coherence was calculated for frequencies up to 60 Hz.

Results

The analysis revealed the individual time-dependent coherence between two signals for different frequencies during the work cycle of the antagonist muscles of the arm (biceps/triceps) and forearm (flexor/extensor carpi radialis). A significant difference in alpha coherence (2-16 Hz) occurred in the group of forearm muscles in the frequency band of 2-16 Hz, both for G (p = 0.042) and M (p = 0.031) parameters (G: A - 0.08 Hz, B - 0.04 Hz; M: A - 0.51 and B - 0.42). Its peaks were observed during the fencing action cycle. Some differences in gamma coherence were also found in the EMG signals of the forearm muscles in the 31-60 Hz frequency band were statistically significant (p = 0.031): 0.43 in group A and 0.36 in group B.

Conclusion

The results showed the neuromuscular conduction, where alpha coherence reflects the reticulospinal tract responsible for the excitation of the distal muscles of the wrist and hand, while gamma coherence results from cortical signals. It is related to efferent conduction and reflects corticomuscular coupling. Frequency domain coherence analysis determines the strength of intermuscular synchronization, allowing a comprehensive investigation of the neural mechanisms underlying motor recovery. It maps separate neural pathways for arm and hand control.

Right-left sEMG burst synchronization of the lumbar erector spinae muscles of seated violin players

Burst-like activation of postural muscles has been previously described and plays a crucial role in elucidating the strategies for postural control adopted by the central nervous system (CNS). A spatio-temporal descriptor of surface electromyographic (sEMG) bursts (STB) is proposed and applied to statistically quantify the burst-like activity of the right and left (R-L) lumbar erector spinae muscle of nine seated violinists playing for two hours. The STB signal is the number of pixels of the high density sEMG (HDsEMG) maps simultaneously showing sEMG amplitude above a given threshold. Burst activity was present in all nine subjects. Four of them met four stringent criteria allowing analysis of frequency, duration, and synchronization between the R-L bursts after 0, 15, 30, 60, 120 min of playing. Mean square coherence between STBs of the two muscles was > 0.75 within ⁓1 Hz bandwidth between 2.2 Hz and 4.5 Hz depending on subject. Non-parametric statistics was applied to compare, in time and space, the R-L features of the bursts. The mean STB width was significantly associated primarily to side and secondarily to time and ranged from 100 to 250 ms. The right STB signals led the left (p < 0.02) by 0 - 160 ms.The inverted pendulum composed by the upper body of a seated violinist is controlled in an intermittent way. The erector spinae of the selected subjects were active, on average, for less than 50% of the time. These findings demonstrate a CNS strategy of intermittent back muscle activation presumably aimed to reducing fatigue during hours of playing in seated violinists.

Mobile EEG for the study of cognitive-motor interference during swimming?

Research on brain function in natural environments has become a new interest in cognitive science. In this study, we aim to advance mobile electroencephalography (EEG) participant and device mobility. We investigated the feasibility of measuring human brain activity using mobile EEG during a full-body motion task as swimming, by the example of cognitive-motor interference (CMI). Eleven participants were given an auditory oddball task while sitting and swimming, with mobile EEG recording ongoing brain activity. Measures of interest were event-related potentials (ERPs) elicited by experimental stimuli. While the auditory N100 was measured to verify signal quality, the P300 to task-relevant stimuli served as a marker of CMI effects. Analyzes were first performed within subjects, while binomial tests assessed the proportion of significant effects. Event-related changes in the time-frequency domain around turns during swimming were analyzed in an exploratory fashion. The successful recording of the N100 in all conditions shows that the setup was functional throughout the experiment. Regarding CMI, we did not find reliable changes in P300 amplitude in different motor settings in all subjects. However, we found plausible modulations in the alpha/mu and beta bands before and after turns. This study shows that it is generally feasible to measure mobile EEG in the time and time-frequency domain in an aquatic environment while subjects are freely moving. We see promising potential in the use of mobile EEG in extreme settings, advancing toward the application of mobile EEG in more real-life situations.

Detection of Threshold-Level Stimuli Modulated by Temporal Predictions of the Cerebellum

The cerebellum has the reputation of being a primitive part of the brain that mostly is involved in motor coordination and motor control. Older lesion studies and more recent electrophysiological studies have, however, indicated that it is involved in temporal perception and temporal expectation building. An outstanding question is whether this temporal expectation building cerebellar activity has functional relevance. In this study, we collected magnetoencephalographic data from 30 healthy participants performing a detection task on at-threshold stimulation that was presented at the end of a sequence of temporally regular or irregular above-threshold stimulation. We found that behavioral detection rates depended on the degree of irregularity in the sequence preceding it. We also found cerebellar responses evoked by above-threshold and at-threshold stimulation. The evoked responses to at-threshold stimulation differed significantly, depending on whether it was preceded by a regular or an irregular sequence. Finally, we found that detection performance across participants correlated significantly with the differences in cerebellar evoked responses to the at-threshold stimulation, demonstrating the functional relevance of cerebellar activity in sensory expectation building. We furthermore found evidence of thalamic involvement, as indicated by responses in the beta band (14-30 Hz) and by significant modulations of cerebello-thalamic connectivity by the regularity of the sequence and the kind of stimulation terminating the sequence. These results provide evidence that the temporal expectation building mechanism of the cerebellum, what we and others have called an internal clock, shows functional relevance by regulating behavior and performance in sensory action that requires acting and integrating evidence over precise timescales.

Reduced Cerebellar Brain Inhibition and Vibrotactile Perception in Response to Mechanical Hand Stimulation at Flutter Frequency

The cerebellum is traditionally considered a movement control structure because of its established afferent and efferent anatomical and functional connections with the motor cortex. In the last decade, studies also proposed its involvement in perception, particularly somatosensory acquisition and prediction of the sensory consequences of movement. However, compared to its role in motor control, the cerebellum's specific role or modulatory influence on other brain areas involved in sensory perception, specifically the primary sensorimotor cortex, is less clear. In the present study, we explored whether peripherally applied vibrotactile stimuli at flutter frequency affect functional cerebello-cortical connections. In 17 healthy volunteers, changes in cerebellar brain inhibition (CBI) and vibration perception threshold (VPT) were measured before and after a 20-min right hand mechanical stimulation at 25 Hz. 5 Hz mechanical stimulation of the right foot served as an active control condition. Performance in a Grooved Pegboard test (GPT) was also measured to assess stimulation's impact on motor performance. Hand stimulation caused a reduction in CBI (13.16%) and increased VPT but had no specific effect on GPT performance, while foot stimulation had no significant effect on all measures. The result added evidence to the functional connections between the cerebellum and primary motor cortex, as shown by CBI reduction. Meanwhile, the parallel increase in VPT indirectly suggests that the cerebellum influences the processing of vibrotactile stimulus through motor-sensory interactions.

Scale-invariant changes in corticospinal excitability reflect multiplexed oscillations in the motor output

In the absence of disease, humans produce smooth and accurate movement trajectories. Despite such 'macroscopic' aspect, the 'microscopic' structure of movements reveals recurrent (quasi-rhythmic) discontinuities. To date, it is unclear how the sensorimotor system contributes to the macroscopic and microscopic architecture of movement. Here, we investigated how corticospinal excitability changes in relation to microscopic fluctuations that are naturally embedded within larger macroscopic variations in motor output. Participants performed a visuomotor tracking task. In addition to the 0.25 Hz modulation that is required for task fulfilment (macroscopic scale), the motor output shows tiny but systematic fluctuations at ∼2 and 8 Hz (microscopic scales). We show that motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) during task performance are consistently modulated at all (time) scales. Surprisingly, MEP modulation covers a similar range at both micro- and macroscopic scales, even though the motor output differs by several orders of magnitude. Thus, corticospinal excitability finely maps the multiscale temporal patterning of the motor output, but it does so according to a principle of scale invariance. These results suggest that corticospinal excitability indexes a relatively abstract level of movement encoding that may reflect the hierarchical organisation of sensorimotor processes. KEY POINTS: Motor behaviour is organised on multiple (time)scales. Small but systematic ('microscopic') fluctuations are engrained in larger and slower ('macroscopic') variations in motor output, which are instrumental in deploying the desired motor plan. Corticospinal excitability is modulated in relation to motor fluctuations on both macroscopic and microscopic (time)scales. Corticospinal excitability obeys a principle of scale invariance, that is, it is modulated similarly at all (time)scales, possibly reflecting hierarchical mechanisms that optimise motor encoding.

Frontal cortex activity during the production of diverse social communication calls in marmoset monkeys

Vocal communication is essential for social behaviors in humans and non-human primates. While the frontal cortex is crucial to human speech production, its role in vocal production in non-human primates has long been questioned. It is unclear whether activities in the frontal cortex represent diverse vocal signals used in non-human primate communication. Here we studied single neuron activities and local field potentials (LFP) in the frontal cortex of male marmoset monkeys while the animal engaged in vocal exchanges with conspecifics in a social environment. We found that both single neuron activities and LFP were modulated by the production of each of the four major call types. Moreover, neural activities showed distinct patterns for different call types and theta-band LFP oscillations showed phase-locking to the phrases of twitter calls, suggesting a neural representation of vocalization features. Our results suggest important functions of the marmoset frontal cortex in supporting the production of diverse vocalizations in communication.

Electrophysiological evidence of discontinuities in the propagation of lexical decision processes across the motor hierarchy

This research assessed the propagation of decisional effects across multiple electrophysiological indexes related to motor-response implementation within a lexical decision task, a paradigmatic case of a 2-alternative choice task on linguistic stimuli. By co-registering electroencephalographic and electromyographic data, we focused on the lexicality effect (i.e., the difference between responses to words and nonwords), and we tracked its influence across indexes of motor-response planning (indexed by effector-selective lateralization of beta-frequency desynchronizations), programming (indexed by the lateralized readiness potential) and execution (indexed by the chronometric durations of muscular responses). In addition, we explored corticomuscular coherence as the potential physiological underpinning of a continuous mapping of information between stimulus evaluation and response channels. The results revealed lexicality effects only on indexes of motor planning and execution, with no reliable involvement of the other measures. This pattern is discussed with reference to the hypothesis of multiple decisional components exerting different influences across the motor-hierarchy.

M1 transcranial direct current stimulation augments laparoscopic surgical skill acquisition

The acquisition of basic surgical skills is a key component of medical education and trainees in laparoscopic surgery typically begin developing their skills using simulation box trainers. However, despite the advantages of simulation surgical training, access can be difficult for many trainees. One technique that has shown promise to enhance the deliberate practice of motor skills is transcranial electric stimulation (tES). The purpose of this study was to assess the impact of transcranial direct current stimulation (tDCS) on training induced improvements and retention of traditional time and kinematic based laparoscopic surgical skill metrics. Forty-nine medical students were randomly allocated to a neurostimulation or sham group and completed 5 training sessions of a bead transfer and threading laparoscopic task. Participants in both the sham and stimulation groups significantly improved their time and kinematic performance on both tasks following training. Although we did find that participants who received M1 tDCS saw greater performance benefits in response to training on a bead transfer task compared to those receiving sham stimulation no effect of neurostimulation was found for the threading task. This finding raises new questions regarding the effect that motor task complexity has on the efficacy of neurostimulation to augment training induced improvement and contributes to a growing body of research investigating the effects of neurostimulation on the sensory-motor performance of laparoscopic surgical skill.

Another Way to Confuse Motor Control: Manual Technique Supposed to Shorten Muscle Spindles Reduces the Muscular Holding Stability in the Sense of Adaptive Force in Male Soccer Players

Sensorimotor control can be impaired by slacked muscle spindles. This was shown for reflex responses and, recently, also for muscular stability in the sense of Adaptive Force (AF). The slack in muscle spindles was generated by contracting the lengthened muscle followed by passive shortening. AF was suggested to specifically reflect sensorimotor control since it requires tension-length control in adaptation to an increasing load. This study investigated AF parameters in reaction to another, manually performed slack procedure in a preselected sample (n = 13). The AF of 11 elbow and 12 hip flexors was assessed by an objectified manual muscle test (MMT) using a handheld device. Maximal isometric AF was significantly reduced after manual spindle technique vs. regular MMT. Muscle lengthening started at 64.93 ± 12.46% of maximal voluntary isometric contraction (MVIC). During regular MMT, muscle length could be maintained stable until 92.53 ± 10.12% of MVIC. Hence, muscular stability measured by AF was impaired after spindle manipulation. Force oscillations arose at a significantly lower level for regular vs. spindle. This supports the assumption that they are a prerequisite for stable adaptation. Reduced muscular stability in reaction to slack procedures is considered physiological since sensory information is misled. It is proposed to use slack procedures to test the functionality of the neuromuscular system, which is relevant for clinical practice.

Spatiotemporal dynamics characterise spectral connectivity profiles of continuous speaking and listening

Speech production and perception are fundamental processes of human cognition that both rely on intricate processing mechanisms that are still poorly understood. Here, we study these processes by using magnetoencephalography (MEG) to comprehensively map connectivity of regional brain activity within the brain and to the speech envelope during continuous speaking and listening. Our results reveal not only a partly shared neural substrate for both processes but also a dissociation in space, delay, and frequency. Neural activity in motor and frontal areas is coupled to succeeding speech in delta band (1 to 3 Hz), whereas coupling in the theta range follows speech in temporal areas during speaking. Neural connectivity results showed a separation of bottom-up and top-down signalling in distinct frequency bands during speaking. Here, we show that frequency-specific connectivity channels for bottom-up and top-down signalling support continuous speaking and listening. These findings further shed light on the complex interplay between different brain regions involved in speech production and perception.

How the conception of control influences our understanding of actions

Wilful movement requires neural control. Commonly, neural computations are thought to generate motor commands that bring the musculoskeletal system - that is, the plant - from its current physical state into a desired physical state. The current state can be estimated from past motor commands and from sensory information. Modelling movement on the basis of this concept of plant control strives to explain behaviour by identifying the computational principles for control signals that can reproduce the observed features of movements. From an alternative perspective, movements emerge in a dynamically coupled agent-environment system from the pursuit of subjective perceptual goals. Modelling movement on the basis of this concept of perceptual control aims to identify the controlled percepts and their coupling rules that can give rise to the observed characteristics of behaviour. In this Perspective, we discuss a broad spectrum of approaches to modelling human motor control and their notions of control signals, internal models, handling of sensory feedback delays and learning. We focus on the influence that the plant control and the perceptual control perspective may have on decisions when modelling empirical data, which may in turn shape our understanding of actions.

Spatial and Temporal Muscle Synergies Provide a Dual Characterization of Low-dimensional and Intermittent Control of Upper-limb Movements

Muscle synergy analysis investigates the neurophysiological mechanisms that the central nervous system employs to coordinate muscles. Several models have been developed to decompose electromyographic (EMG) signals into spatial and temporal synergies. However, using multiple approaches can complicate the interpretation of results. Spatial synergies represent invariant muscle weights modulated with variant temporal coefficients; temporal synergies are invariant temporal profiles that coordinate variant muscle weights. While non-negative matrix factorization allows to extract both spatial and temporal synergies, the comparison between the two approaches was rarely investigated targeting a large set of multi-joint upper-limb movements. Spatial and temporal synergies were extracted from two datasets with proximal (16 subjects, 10M, 6F) and distal upper-limb movements (30 subjects, 21M, 9F), focusing on their differences in reconstruction accuracy and inter-individual variability. We showed the existence of both spatial and temporal structure in the EMG data, comparing synergies with those from a surrogate dataset in which the phases were shuffled preserving the frequency content of the original data. The two models provide a compact characterization of motor coordination at the spatial or temporal level, respectively. However, a lower number of temporal synergies are needed to achieve the same reconstruction R²: spatial and temporal synergies may capture different hierarchical levels of motor control and are dual approaches to the characterization of low-dimensional coordination of the upper-limb. Last, a detailed characterization of the structure of the temporal synergies suggested that they can be related to intermittent control of the movement, allowing high flexibility and dexterity. These results improve neurophysiology understanding in several fields such as motor control, rehabilitation, and prosthetics.

Modulation of lower limb muscles and trajectory correction in the bipedal stance during visual perturbation

The ability to actively track posture using visual targets as indicators is important for improving impairments in whole-body coordination, and accurate visual feedback on tasks is considered effective in promoting sensory-motor integration and behavioral success. In the present study, we examined inter- and intramuscular modulation between the two lower limbs in response to visual perturbation. Sixteen healthy young subjects (age: 21.3 ± 0.7 years) were asked to move their weight back and forth while tracking a visual target displayed on a monitor in front of them for 30 s. Three types of target movements were examined: a sinusoidal wave (i.e., a predictable pattern), more complex patterns (random), and no movement (stationary). Electromyography (EMG) was used to assess intra- and intermuscular coherence modulation of the plantar flexor muscles (right and left soleus and right and left medial gastrocnemius). The ability to adjust posture to follow the target signal was assessed using a stabilometer. Inter- and intramuscular coherence increased during the visual perturbation task compared to the stationary task. In addition, left-right differences in lower limb modulation were observed during the visual perturbation task. Furthermore, interlimb coherence was related to the motor accuracy of tracking. The muscles of both lower limbs cooperated in response to visual perturbation, suggesting that these muscles control visually induced anteroposterior postural sway. Since such visual perturbations promote coordination between both lower extremities, this relationship may indicate the potential for rehabilitation training to help individuals acquire and improve the motor functions necessary to efficiently and stably perform activities of daily living.

Case report: Individualized pulsed electromagnetic field therapy in a Long COVID patient using the Adaptive Force as biomarker

The increasing prevalence of Long COVID is an imminent public health disaster, and established approaches have not provided adequate diagnostics or treatments. Recently, anesthetic blockade of the stellate ganglion was reported to improve Long COVID symptoms in a small case series, purportedly by "rebooting" the autonomic nervous system. Here, we present a novel diagnostic approach based on the Adaptive Force (AF), and report sustained positive outcome for one severely affected Long COVID patient using individualized pulsed electromagnetic field (PEMF) at the area C7/T1. AF reflects the capacity of the neuromuscular system to adapt adequately to external forces in an isometric holding manner. In case, maximal isometric AF (AFisomax) is exceeded, the muscle merges into eccentric muscle action. Thereby, the force usually increases further until maximal AF (AFmax) is reached. In case adaptation is optimal, AFisomax is ~99-100% of AFmax. This holding capacity (AFisomax) was found to be vulnerable to disruption by unpleasant stimulus and, hence, was regarded as functional parameter. AF was assessed by an objectified manual muscle test using a handheld device. Prior to treatment, AFisomax was considerably lower than AFmax for hip flexors (62 N = ~28% AFmax) and elbow flexors (71 N = ~44% AFmax); i.e., maximal holding capacity was significantly reduced, indicating dysfunctional motor control. We tested PEMF at C7/T1, identified a frequency that improved neuromuscular function, and applied it for ~15 min. Immediately post-treatment, AFisomax increased to ~210 N (~100% AFmax) at hip and 184 N (~100% AFmax) at elbow. Subjective Long COVID symptoms resolved the following day. At 4 weeks post-treatment, maximal holding capacity was still on a similarly high level as for immediately post-treatment (~100% AFmax) and patient was symptom-free. At 6 months the patient's Long COVID symptoms have not returned. This case report suggests (1) AF could be a promising diagnostic for post-infectious illness, (2) AF can be used to test effective treatments for post-infectious illness, and (3) individualized PEMF may resolve post-infectious symptoms.

Asynchronous Intermittent Regulation of Human Arm Movement with Markovian Jumping Parameters

In this paper, the regulation stability problem of the human arm continuous movement is investigated based on Markovian jumping parameters. In particular, the intermittent control mechanism is adopted in the arm movement regulation procedure to model the human intermittent motor control strategy. Furthermore, by taking into account the Markovian jumping parameters with different modes, the asynchronous regulation issue is proposed to model mode mismatch between the motor control and arm movement. On the basis of model transformation, sufficient stability conditions are established during the arm movements, and the desired regulation gain can be obtained by the convex optimization method. In the end, an illustrative example is presented to show the applicability and effectiveness of our developed model and optimized regulation approach.

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.

EEG Oscillations in Specific Frequency Bands Are Differently Coupled with Angular Joint Angle Kinematics during Rhythmic Passive Elbow Movement

Rhythmic passive movements are often used during rehabilitation to improve physical functions. Previous studies have explored oscillatory activities in the sensorimotor cortex during active movements; however, the relationship between movement rhythms and oscillatory activities during passive movements has not been substantially tested. Therefore, we aimed to quantitatively identify changes in cortical oscillations during rhythmic passive movements. Twenty healthy young adults participated in our study. We placed electroencephalography electrodes over a nine-position grid; the center was oriented on the transcranial magnetic stimulation hotspot of the biceps brachii muscle. Passive movements included elbow flexion and extension; the participants were instructed to perform rhythmic elbow flexion and extension in response to the blinking of 0.67 Hz light-emitting diode lamps. The coherence between high-beta and low-gamma oscillations near the hotspot of the biceps brachii muscle and passive movement rhythms was higher than that between alpha oscillation and passive movement rhythm. These results imply that alpha, beta, and gamma oscillations of the primary motor cortex are differently related to passive movement rhythm.

Interpersonal synchronization of movement intermittency

Most animal species group together and coordinate their behavior in quite sophisticated manners for mating, hunting, or defense purposes. In humans, coordination at a macroscopic level (the pacing of movements) is evident both in daily life (e.g., walking) and skilled (e.g., music and dance) behaviors. By examining the fine structure of movement, we here show that interpersonal coordination is established also at a microscopic – submovement – level. Natural movements appear as marked by recurrent (2–3 Hz) speed breaks, i.e., submovements, that are traditionally considered the result of intermittency in (visuo)motor feedback-based control. In a series of interpersonal coordination tasks, we show that submovements produced by interacting partners are not independent but alternate tightly over time, reflecting online mutual adaptation. These findings unveil a potential core mechanism for behavioral coordination that is based on between-persons synchronization of the intrinsic dynamics of action-perception cycles.

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Movements show intermittent speed pulses occurring at 2–3 Hz, called submovements

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Submovements are actively coordinated in counter-phase by interacting partners

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Submovements coordination depends on spatial alignment but not movement congruency

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Behavioral coordination occurs both at macro- and microscopic movement scales

Enhancement of functional corticomuscular coupling after transcranial ultrasound stimulation in mice

OBJECTIVE

Transcranial ultrasound stimulation (TUS), a large penetration depth and high spatial resolution technology, has developed rapidly in recent years. This study aimed to explore and evaluate the neuromodulation effects of TUS on mouse motor neural circuits under different parameters.

APPROACH

Our study used functional corticomuscular coupling (FCMC) as an index to explore the modulation mechanism for movement control under different TUS parameters (intensity [Isppa] and stimulation duration [SD]). We collected local field potential (LFP) and tail electromyographic (EMG) data under TUS in healthy mice and then introduced the time-frequency coherence method to analyze the FCMC before and after TUS in the time-frequency domain. After that, we defined the relative coherence area (RCA) to quantify the coherence between LFP and EMG under TUS.

MAIN RESULTS

The FCMC at theta, alpha, beta, and gamma bands was enhanced after TUS, and the neuromodulation efficacy mainly occurred in the lower frequency band (theta and alpha band). After TUS with different parameters, the FCMC in all selected frequency bands showed a tendency of increasing first and then decreasing. Further analysis showed that the maximum coupling value of theta band appeared from 0.2 to 0.4 s, and that the maximum coupling value in alpha and gamma band appeared from 0 to 0.2 s.

SIGNIFICANCE

The aforementioned results demonstrate that FCMC in the motor cortex could be modulated by TUS. We provide a theoretical basis for further exploring the modulation mechanism of TUS parameters and clinical application.

Sports-Related Motor Processing at Different Rates of Force Development

How does our brain manage to process vast quantities of sensory information that define movement performance? By extracting the required movement parameters for which brain dynamics are, inter alia, assumed to be functionally related to, we used electroencephalography to investigate motor-related brain oscillations. Visually guided movement (i.e., motor) tasks at explosive, medium and slow rates of force development (RFD) revealed increased broad-band activity at explosive RFD, whereas decreasing activity could be observed during both intermediate and slow RFD. Moreover, a continuously decreasing activity pattern from faster to slower RFD and a return to baseline activity after full muscle relaxation was found. We suggest oscillatory activity to desynchronize in sensorimotor demanding tasks, whereas task-specific synchronization mirrors movement acceleration. The pre/post-stimulus activity steady state may indicate an inhibitory baseline that provides attentional focus and timing.

A network information theoretic framework to characterise muscle synergies in space and time

Objective Current approaches to muscle synergy extraction rely on linear dimensionality reduction algorithms that make specific assumptions on the underlying signals. However, to capture nonlinear time varying, large-scale but also muscle-specific interactions, a more generalised approach is required. Approach Here we developed a novel framework for muscle synergy extraction that relaxes model assumptions by using a combination of information- and network theory and dimensionality reduction. We first quantify informational dynamics between muscles, time-samples or muscle-time pairings using a novel mutual information formulation. We then model these pairwise interactions as multiplex networks and identify modules representing the network architecture. We employ this modularity criterion as the input parameter for dimensionality reduction, which verifiably extracts the identified modules, and also to characterise salient structures within each module. Main results This novel framework captures spatial, temporal and spatiotemporal interactions across two benchmark datasets of reaching movements, producing distinct spatial groupings and both tonic and phasic temporal patterns. Readily interpretable muscle synergies spanning multiple spatial and temporal scales were identified, demonstrating significant task dependence, ability to capture trial-to-trial fluctuations and concordance across participants. Furthermore, our framework identifies submodular structures that represent the distributed networks of co-occurring signal interactions across scales. Significance The capabilities of this framework are illustrated through the concomitant continuity with previous research and novelty of the insights gained. Several previous limitations are circumvented including the extraction of functionally meaningful and multiplexed pairwise muscle couplings under relaxed model assumptions. The extracted synergies provide a holistic view of the movement while important details of task performance are readily interpretable. The identified muscle groupings transcend biomechanical constraints and the temporal patterns reveal characteristics of fundamental motor control mechanisms. We conclude that this framework opens new opportunities for muscle synergy research and can constitute a bridge between existing models and recent network-theoretic endeavours.

Nonequivalent After-Effects of Alternating Current Stimulation on Motor Cortex Oscillation and Inhibition: Simulation and Experimental Study

The effects of transcranial alternating current stimulation (tACS) frequency on brain oscillations and cortical excitability are still controversial. Therefore, this study investigated how different tACS frequencies differentially modulate cortical oscillation and inhibition. To do so, we first determined the optimal positioning of tACS electrodes through an electric field simulation constructed from magnetic resonance images. Seven electrode configurations were tested on the electric field of the precentral gyrus (hand motor area). We determined that the Cz-CP1 configuration was optimal, as it resulted in higher electric field values and minimized the intra-individual differences in the electric field. Therefore, tACS was delivered to the hand motor area through this arrangement at a fixed frequency of 10 Hz (alpha-tACS) or 20 Hz (beta-tACS) with a peak-to-peak amplitude of 0.6 mA for 20 min. We found that alpha- and beta-tACS resulted in larger alpha and beta oscillations, respectively, compared with the oscillations observed after sham-tACS. In addition, alpha- and beta-tACS decreased the amplitudes of conditioned motor evoked potentials and increased alpha and beta activity, respectively. Correspondingly, alpha- and beta-tACSs enhanced cortical inhibition. These results show that tACS frequency differentially affects motor cortex oscillation and inhibition.

Brain rhythms define distinct interaction networks with differential dependence on anatomy

Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent. Thus, the rhythms defined distinct interaction networks. Importantly, networks of coherence and GC were not explained by the spatial distributions of the strengths of the rhythms. Those networks, particularly the GC networks, contained clear modules, with typically one dominant rhythm per module. To understand how this distinctiveness and modularity arises on a common anatomical backbone, we correlated, across 91 area pairs, the metrics of functional interaction with those of anatomical projection strength. Anatomy was primarily related to coherence and GC, with the largest effect sizes for GC. The correlation differed markedly between rhythms, being less pronounced for the beta and strongest for the gamma rhythm.

Temporally resolved neural dynamics underlying handwriting

How do the temporal dynamics of neural activity encode highly coordinated visual-motor behaviour? To capture the millisecond-resolved neural activations associated with fine visual-motor skills, we devised a co-registration system to simultaneously record electroencephalogram and handwriting kinematics while participants were performing four handwriting tasks (writing in Chinese/English scripts with their dominant/non-dominant hand). The neural activation associated with each stroke was clearly identified with a well-structured and reliable pattern. The functional significance of this pattern was validated by its significant associations with language, hand and the cognitive stages and kinematics of handwriting. Furthermore, the handwriting rhythmicity was found to be synchronised to the brain's ongoing theta oscillation, and the synchronisation was associated with the factor of language and hand. These major findings imply an implication between motor skill formation and the interplay between the rhythms in the brain and the peripheral systems.

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Essential tremor, a common, debilitating motor disorder, is thought to be caused by cerebellar malfunction. It has been shown that rhythmic Purkinje cell firing is both necessary and sufficient to induce body tremor. During tremor, cerebellar nuclei (CN) cells also display oscillatory activity. This study examined whether rhythmic activity in the CN characterizes the occurrence of body tremor, or alternatively, whether aberrant bursting activity underlies body tremor. Cerebellar nuclei activity was chronically recorded and analyzed in freely moving and in harmaline treated rats. CN neurons displayed rhythmic activity in both conditions, but the number of oscillatory neurons and the relative oscillation time were significantly higher under harmaline. The dominant frequencies of the oscillations were broadly distributed under harmaline and the likelihood that two simultaneously recorded neurons would co-oscillate and their oscillation coherence were significantly lower. It is argued that these alterations rather than neuronal rhythmicity per se underlie harmaline-induced body tremor.

Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease

OBJECTIVE

Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson's disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia.

METHODS

Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures.

RESULTS

Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side.

DISCUSSION

Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.

Disgusting odours affect the characteristics of the Adaptive Force in contrast to neutral and pleasant odours

The olfactomotor system is especially investigated by examining the sniffing in reaction to olfactory stimuli. The motor output of respiratory-independent muscles was seldomly considered regarding possible influences of smells. The Adaptive Force (AF) characterizes the capability of the neuromuscular system to adapt to external forces in a holding manner and was suggested to be more vulnerable to possible interfering stimuli due to the underlying complex control processes. The aim of this pilot study was to measure the effects of olfactory inputs on the AF of the hip and elbow flexors, respectively. The AF of 10 subjects was examined manually by experienced testers while smelling at sniffing sticks with neutral, pleasant or disgusting odours. The reaction force and the limb position were recorded by a handheld device. The results show, inter alia, a significantly lower maximal isometric AF and a significantly higher AF at the onset of oscillations by perceiving disgusting odours compared to pleasant or neutral odours (p < 0.001). The adaptive holding capacity seems to reflect the functionality of the neuromuscular control, which can be impaired by disgusting olfactory inputs. An undisturbed functioning neuromuscular system appears to be characterized by a proper length tension control and by an earlier onset of mutual oscillations during an external force increase. This highlights the strong connection of olfaction and motor control also regarding respiratory-independent muscles.

Adaptive Force and emotionally related imaginations - preliminary results suggest a reduction of the maximal holding capacity as reaction to disgusting food imagination

The link between emotions and motor control has been discussed for years. The measurement of the Adaptive Force (AF) provides the possibility to get insights into the adaptive control of the neuromuscular system in reaction to external forces. It was hypothesized that the holding isometric AF is especially vulnerable to disturbing inputs. Here, the behavior of the AF under the influence of positive (tasty) vs. negative (disgusting) food imaginations was investigated. The AF was examined in n = 12 cases using an objectified manual muscle test of the hip flexors, elbow flexors or pectoralis major muscle, performed by one of two experienced testers while the participants imagined their most tasty or most disgusting food. The reaction force and the limb position were measured by a handheld device. While the slope of force rises and the maximal AF did not differ significantly between tasty and disgusting imaginations (p > 0.05), the maximal isometric AF was significantly lower and the AF at the onset of oscillations was significantly higher under disgusting vs. tasty imaginations (both p = 0.001). A proper length tension control of muscles seems to be a crucial functional parameter of the neuromuscular system which can be impaired instantaneously by emotionally related negative imaginations. This might be a potential approach to evaluate somatic reactions to emotions.

A neural circuit state change underlying skilled movements

In motor neuroscience, state changes are hypothesized to time-lock neural assemblies coordinating complex movements, but evidence for this remains slender. We tested whether a discrete change from more autonomous to coherent spiking underlies skilled movement by imaging cerebellar Purkinje neuron complex spikes in mice making targeted forelimb-reaches. As mice learned the task, millimeter-scale spatiotemporally coherent spiking emerged ipsilateral to the reaching forelimb, and consistent neural synchronization became predictive of kinematic stereotypy. Before reach onset, spiking switched from more disordered to internally time-locked concerted spiking and silence. Optogenetic manipulations of cerebellar feedback to the inferior olive bi-directionally modulated neural synchronization and reaching direction. A simple model explained the reorganization of spiking during reaching as reflecting a discrete bifurcation in olivary network dynamics. These findings argue that to prepare learned movements, olivo-cerebellar circuits enter a self-regulated, synchronized state promoting motor coordination. State changes facilitating behavioral transitions may generalize across neural systems.

Temporal control of muscle synergies is linked with alpha-band neural drive

KEY POINTS

It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies.

ABSTRACT

During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.

Master-Slave Synchronization of Delayed Neural Networks With Time-Varying Control

This brief investigates the master-slave synchronization problem of delayed neural networks with general time-varying control. Assuming a linear feedback controller with time-varying control gain, the synchronization problem is recast into the stability problem of a delayed system with a time-varying coefficient. The main theorem is established in terms of the time average of the control gain by using the Lyapunov-Razumikhin theorem. Moreover, the proposed framework encompasses some general intermittent control schemes, such as the switched control gain with external disturbance and intermittent control with pulse-modulated gain function, while some useful corollaries are consequently deduced. Interestingly, our theorem also provides a solution for regaining stability under control failure. The validity of the theorem and corollaries is further demonstrated with numerical examples.

Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis

Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.

Force variability is mostly not motor noise: Theoretical implications for motor control

Variability in muscle force is a hallmark of healthy and pathological human behavior. Predominant theories of sensorimotor control assume 'motor noise' leads to force variability and its 'signal dependence' (variability in muscle force whose amplitude increases with intensity of neural drive). Here, we demonstrate that the two proposed mechanisms for motor noise (i.e. the stochastic nature of motor unit discharge and unfused tetanic contraction) cannot account for the majority of force variability nor for its signal dependence. We do so by considering three previously underappreciated but physiologically important features of a population of motor units: 1) fusion of motor unit twitches, 2) coupling among motoneuron discharge rate, cross-bridge dynamics, and muscle mechanics, and 3) a series-elastic element to account for the aponeurosis and tendon. These results argue strongly against the idea that force variability and the resulting kinematic variability are generated primarily by 'motor noise.' Rather, they underscore the importance of variability arising from properties of control strategies embodied through distributed sensorimotor systems. As such, our study provides a critical path toward developing theories and models of sensorimotor control that provide a physiologically valid and clinically useful understanding of healthy and pathologic force variability.

Circadian rhythms and the HPA axis: A systems view

The circadian timing system comprises a network of time-keeping clocks distributed across a living host whose responsibility is to allocate resources and distribute functions temporally to optimize fitness. The molecular structures generating these rhythms have evolved to accommodate the rotation of the earth in an attempt to primarily match the light/dark periods during the 24-hr day. To maintain synchrony of timing across and within tissues, information from the central clock, located in the suprachiasmatic nucleus, is conveyed using systemic signals. Leading among those signals are endocrine hormones, and while the hypothalamic-pituitary-adrenal axis through the release of glucocorticoids is a major pacesetter. Interestingly, the fundamental units at the molecular and physiological scales that generate local and systemic signals share critical structural properties. These properties enable time-keeping systems to generate rhythmic signals and allow them to adopt specific properties as they interact with each other and the external environment. The purpose of this review is to provide a broad overview of these structures, discuss their functional characteristics, and describe some of their fundamental properties as these related to health and disease. This article is categorized under: Immune System Diseases > Computational Models Immune System Diseases > Biomedical Engineering.

Visual detection is locked to the internal dynamics of cortico-motor control

Movements overtly sample sensory information, making sensory analysis an active-sensing process. In this study, we show that visual information sampling is not just locked to the (overt) movement dynamics but to the internal (covert) dynamics of cortico-motor control. We asked human participants to perform continuous isometric contraction while detecting unrelated and unpredictable near-threshold visual stimuli. The motor output (force) shows zero-lag coherence with brain activity (recorded via electroencephalography) in the beta-band, as previously reported. In contrast, cortical rhythms in the alpha-band systematically forerun the motor output by 200 milliseconds. Importantly, visual detection is facilitated when cortico-motor alpha (not beta) synchronization is enhanced immediately before stimulus onset, namely, at the optimal phase relationship for sensorimotor communication. These findings demonstrate an ongoing coupling between visual sampling and motor control, suggesting the operation of an internal and alpha-cycling visuomotor loop.

Intermuscular coherence between homologous muscles during dynamic and static movement periods of bipedal squatting

Coordination of functionally coupled muscles is a key aspect of movement execution. Demands on coordinative control increase with the number of involved muscles and joints, as well as with differing movement periods within a given motor sequence. While previous research has provided evidence concerning inter- and intramuscular synchrony in isolated movements, compound movements remain largely unexplored. With this study, we aimed to uncover neural mechanisms of bilateral coordination through intermuscular coherence (IMC) analyses between principal homologous muscles during bipedal squatting (BpS) at multiple frequency bands (alpha, beta, and gamma). For this purpose, participants performed bipedal squats without additional load, which were divided into three distinct movement periods (eccentric, isometric, and concentric). Surface electromyography (EMG) was recorded from four homologous muscle pairs representing prime movers during bipedal squatting. We provide novel evidence that IMC magnitudes differ between movement periods in beta and gamma bands, as well as between homologous muscle pairs across all frequency bands. IMC was greater in the muscle pairs involved in postural and bipedal stability compared with those involved in muscular force during BpS. Furthermore, beta and gamma IMC magnitudes were highest during eccentric movement periods, whereas we did not find movement-related modulations for alpha IMC magnitudes. This finding thus indicates increased integration of afferent information during eccentric movement periods. Collectively, our results shed light on intermuscular synchronization during bipedal squatting, as we provide evidence that central nervous processing of bilateral intermuscular functioning is achieved through task-dependent modulations of common neural input to homologous muscles.

NEW & NOTEWORTHY It is largely unexplored how the central nervous system achieves coordination of homologous muscles of the upper and lower body within a compound whole body movement, and to what extent this neural drive is modulated between different movement periods and muscles. Using intermuscular coherence analysis, we show that homologous muscle functions are mediated through common oscillatory input that extends over alpha, beta, and gamma frequencies with different synchronization patterns at different movement periods.

Beta-Range Corticomuscular Coupling Reflects Asymmetries in Hand Movement

Hand movement in humans is verified as asymmetries and lateralization, and two hemispheres make some distinct but complementary contributions in the control of hand movement. However, little research has been done on whether the information transfer of the motor system is different between left and right hand movement. Considering the importance of functional corticomuscular coupling (FCMC) between the motor cortex and contralateral muscle in movement assessment, this study aimed to explore the differences between left and right hand by investigating the interaction between muscle and brain activity. Here, we applied the transfer spectral entropy (TSE) algorithm to quantize the connection between electroencephalogram (EEG) over the brain scalp and electromyogram (EMG) from extensor digitorum (ED) and flexor digitorum superficialis (FDS) muscles recorded simultaneously during a gripping task. Eight healthy subjects were enrolled in this study. Results showed that left hand yielded narrower and lower beta synchronization compared to the right. Further analysis indicated coupling strength in EEG-EMG(FDS) combination was higher at beta band than that in EEG-EMG(ED) combination, and exhibited distinct differences between descending (EEG to EMG direction) and ascending (EMG to EEG direction) direction. This study presents the distinctions of beta-range FCMC between left and right hand, and confirms the importance of beta synchronization in understanding the mechanism of motor stability control. The cortex-muscle FCMC might be used as an evaluation approach to explore the difference between left and right movement system.

Theta Synchronization of Phonatory and Articulatory Systems in Marmoset Monkey Vocal Production

Human speech shares a 3-8-Hz theta rhythm across all languages [1-3]. According to the frame/content theory of speech evolution, this rhythm corresponds to syllabic rates derived from natural mandibular-associated oscillations [4]. The underlying pattern originates from oscillatory movements of articulatory muscles [4, 5] tightly linked to periodic vocal fold vibrations [4, 6, 7]. Such phono-articulatory rhythms have been proposed as one of the crucial preadaptations for human speech evolution [3, 8, 9]. However, the evolutionary link in phono-articulatory rhythmicity between vertebrate vocalization and human speech remains unclear. From the phonatory perspective, theta oscillations might be phylogenetically preserved throughout all vertebrate clades [10-12]. From the articulatory perspective, theta oscillations are present in non-vocal lip smacking [1, 13, 14], teeth chattering [15], vocal lip smacking [16], and clicks and faux-speech [17] in non-human primates, potential evolutionary precursors for speech rhythmicity [1, 13]. Notably, a universal phono-articulatory rhythmicity similar to that in human speech is considered to be absent in non-human primate vocalizations, typically produced with sound modulations lacking concomitant articulatory movements [1, 9, 18]. Here, we challenge this view by investigating the coupling of phonatory and articulatory systems in marmoset vocalizations. Using quantitative measures of acoustic call structure, e.g., amplitude envelope, and call-associated articulatory movements, i.e., inter-lip distance, we show that marmosets display speech-like bi-motor rhythmicity. These oscillations are synchronized and phase locked at theta rhythms. Our findings suggest that oscillatory rhythms underlying speech production evolved early in the primate lineage, identifying marmosets as a suitable animal model to decipher the evolutionary and neural basis of coupled phono-articulatory movements.

A New Unifying Account of the Roles of Neuronal Entrainment

Rhythms are a fundamental and defining feature of neuronal activity in animals including humans. This rhythmic brain activity interacts in complex ways with rhythms in the internal and external environment through the phenomenon of 'neuronal entrainment', which is attracting increasing attention due to its suggested role in a multitude of sensory and cognitive processes. Some senses, such as touch and vision, sample the environment rhythmically, while others, like audition, are faced with mostly rhythmic inputs. Entrainment couples rhythmic brain activity to external and internal rhythmic events, serving fine-grained routing and modulation of external and internal signals across multiple spatial and temporal hierarchies. This interaction between a brain and its environment can be experimentally investigated and even modified by rhythmic sensory stimuli or invasive and non-invasive neuromodulation techniques. We provide a comprehensive overview of the topic and propose a theoretical framework of how neuronal entrainment dynamically structures information from incoming neuronal, bodily and environmental sources. We discuss the different types of neuronal entrainment, the conceptual advances in the field, and converging evidence for general principles.

Can EEG and MEG detect signals from the human cerebellum?

The cerebellum plays a key role in the regulation of motor learning, coordination and timing, and has been implicated in sensory and cognitive processes as well. However, our current knowledge of its electrophysiological mechanisms comes primarily from direct recordings in animals, as investigations into cerebellar function in humans have instead predominantly relied on lesion, haemodynamic and metabolic imaging studies. While the latter provide fundamental insights into the contribution of the cerebellum to various cerebellar-cortical pathways mediating behaviour, they remain limited in terms of temporal and spectral resolution. In principle, this shortcoming could be overcome by monitoring the cerebellum's electrophysiological signals. Non-invasive assessment of cerebellar electrophysiology in humans, however, is hampered by the limited spatial resolution of electroencephalography (EEG) and magnetoencephalography (MEG) in subcortical structures, i.e., deep sources. Furthermore, it has been argued that the anatomical configuration of the cerebellum leads to signal cancellation in MEG and EEG. Yet, claims that MEG and EEG are unable to detect cerebellar activity have been challenged by an increasing number of studies over the last decade. Here we address this controversy and survey reports in which electrophysiological signals were successfully recorded from the human cerebellum. We argue that the detection of cerebellum activity non-invasively with MEG and EEG is indeed possible and can be enhanced with appropriate methods, in particular using connectivity analysis in source space. We provide illustrative examples of cerebellar activity detected with MEG and EEG. Furthermore, we propose practical guidelines to optimize the detection of cerebellar activity with MEG and EEG. Finally, we discuss MEG and EEG signal contamination that may lead to localizing spurious sources in the cerebellum and suggest ways of handling such artefacts. This review is to be read as a perspective review that highlights that it is indeed possible to measure cerebellum with MEG and EEG and encourages MEG and EEG researchers to do so. Its added value beyond highlighting and encouraging is that it offers useful advice for researchers aspiring to investigate the cerebellum with MEG and EEG.

A bang-bang control model predicts the triphasic muscles activity during hand reaching

There are numerous ways to reach for an apple hanging from a tree. Yet, our motor system uses a specific muscle activity pattern that features activity bursts and silent periods. We suggest that these bursts are an evidence against the common view that the brain controls the commands to the muscles in a smooth continuous manner. Instead, we propose a model in which a motor plan is transformed into a piecewise-constant control signal that is low-pass filtered and transmitted to the muscles with different muscle-specific delays. We use a Markov chain Monte Carlo (MCMC) method to identify transitions in the state of the muscles following initial activation and show that fitting a bang-bang control model to the kinematics of movement predicts these transitions in the state of the muscles. Such a bang-bang controller suggests that the brain reduces the complexity of the problem of ballistic movements control by sending commands to the muscles at sparse times. Identifying this bang-bang controller can be useful to develop efficient controllers for neuroprostheses and other physical human-robot interaction systems.NEW & NOTEWORTHY While ballistic hand reaching movements are characterized by smooth position and velocity signals, the activity of the muscles exhibits bursts and silent periods. Here, we propose that a model based on bang-bang control provides the link between the abrupt changes in the muscle activity and the smooth reaching trajectory. Using bang-bang control instead of continuous control may simplify the design of prostheses and other physical human-robot interaction systems.

Oscillations in the auditory system and their possible role

GOURÉVITCH, B., C. Martin, O. Postal, J.J. Eggermont. Oscillations in the auditory system, their possible role. NEUROSCI BIOBEHAV REV XXX XXX-XXX, 2020. - Neural oscillations are thought to have various roles in brain processing such as, attention modulation, neuronal communication, motor coordination, memory consolidation, decision-making, or feature binding. The role of oscillations in the auditory system is less clear, especially due to the large discrepancy between human and animal studies. Here we describe many methodological issues that confound the results of oscillation studies in the auditory field. Moreover, we discuss the relationship between neural entrainment and oscillations that remains unclear. Finally, we aim to identify which kind of oscillations could be specific or salient to the auditory areas and their processing. We suggest that the role of oscillations might dramatically differ between the primary auditory cortex and the more associative auditory areas. Despite the moderate presence of intrinsic low frequency oscillations in the primary auditory cortex, rhythmic components in the input seem crucial for auditory processing. This allows the phase entrainment between the oscillatory phase and rhythmic input, which is an integral part of stimulus selection within the auditory system.