MEG studies of motor cortex gamma oscillations: evidence for a gamma "fingerprint" in the brain?

Neural interactions in the human frontal cortex dissociate reward and punishment learning

How human prefrontal and insular regions interact while maximizing rewards and minimizing punishments is unknown. Capitalizing on human intracranial recordings, we demonstrate that the functional specificity toward reward or punishment learning is better disentangled by interactions compared to local representations. Prefrontal and insular cortices display non-selective neural populations to rewards and punishments. Non-selective responses, however, give rise to context-specific interareal interactions. We identify a reward subsystem with redundant interactions between the orbitofrontal and ventromedial prefrontal cortices, with a driving role of the latter. In addition, we find a punishment subsystem with redundant interactions between the insular and dorsolateral cortices, with a driving role of the insula. Finally, switching between reward and punishment learning is mediated by synergistic interactions between the two subsystems. These results provide a unifying explanation of distributed cortical representations and interactions supporting reward and punishment learning.

Automatic detection of ALS from single-trial MEG signals during speech tasks: a pilot study

Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal, and fast-progressive neurodegenerative disease characterized by the degeneration of motor neurons. ALS patients often experience an initial misdiagnosis or a diagnostic delay due to the current unavailability of an efficient biomarker. Since impaired speech is typical in ALS, we hypothesized that functional differences between healthy and ALS participants during speech tasks can be explained by cortical pattern changes, thereby leading to the identification of a neural biomarker for ALS. In this pilot study, we collected magnetoencephalography (MEG) recordings from three early-diagnosed patients with ALS and three healthy controls during imagined (covert) and overt speech tasks. First, we computed sensor correlations, which showed greater correlations for speakers with ALS than healthy controls. Second, we compared the power of the MEG signals in canonical bands between the two groups, which showed greater dissimilarity in the beta band for ALS participants. Third, we assessed differences in functional connectivity, which showed greater beta band connectivity for ALS than healthy controls. Finally, we performed single-trial classification, which resulted in highest performance with beta band features (∼ 98%). These findings were consistent across trials, phrases, and participants for both imagined and overt speech tasks. Our preliminary results indicate that speech-evoked beta oscillations could be a potential neural biomarker for diagnosing ALS. To our knowledge, this is the first demonstration of the detection of ALS from single-trial neural signals.

The Effect of Intranasal Plus Transcranial Photobiomodulation on Neuromuscular Control in Individuals with Repetitive Head Acceleration Events

Objective: This proof-of-concept study was to investigate the relationship between photobiomodulation (PBM) and neuromuscular control. Background: The effects of concussion and repetitive head acceleration events (RHAEs) are associated with decreased motor control and balance. Simultaneous intranasal and transcranial PBM (itPBM) is emerging as a possible treatment for cognitive and psychological sequelae of brain injury with evidence of remote effects on other body systems. Methods: In total, 43 (39 male) participants, age 18-69 years (mean, 49.5; SD, 14.45), with a self-reported history of concussive and/or RHAE and complaints of their related effects (e.g., mood dysregulation, impaired cognition, and poor sleep quality), completed baseline and posttreatment motor assessments including clinical reaction time, grip strength, grooved pegboard, and the Mini Balance Evaluation Systems Test (MiniBEST). In the 8-week interim, participants self-administered itPBM treatments by wearing a headset comprising four near-infrared light-emitting diodes (LED) and a near-infrared LED nasal clip. Results: Posttreatment group averages in reaction time, MiniBEST reactive control subscores, and bilateral grip strength significantly improved with effect sizes of g = 0.75, g = 0.63, g = 0.22 (dominant hand), and g = 0.34 (nondominant hand), respectively. Conclusion: This study provides a framework for more robust studies and suggests that itPBM may serve as a noninvasive solution for improved neuromuscular health.

Adults with cerebral palsy exhibit uncharacteristic cortical oscillations during an adaptive sensorimotor control task

Prior research has shown that the sensorimotor cortical oscillations are uncharacteristic in persons with cerebral palsy (CP); however, it is unknown if these altered cortical oscillations have an impact on adaptive sensorimotor control. This investigation evaluated the cortical dynamics when the motor action needs to be changed "on-the-fly". Adults with CP and neurotypical controls completed a sensorimotor task that required either proactive or reactive control while undergoing magnetoencephalography (MEG). When compared with the controls, the adults with CP had a weaker beta (18-24 Hz) event-related desynchronization (ERD), post-movement beta rebound (PMBR, 16-20 Hz) and theta (4-6 Hz) event-related synchronization (ERS) in the sensorimotor cortices. In agreement with normative work, the controls exhibited differences in the strength of the sensorimotor gamma (66-84 Hz) ERS during proactive compared to reactive trials, but similar condition-wise changes were not seen in adults with CP. Lastly, the adults with CP who had a stronger theta ERS tended to have better hand dexterity, as indicated by the Box and Blocks Test and Purdue Pegboard Test. These results may suggest that alterations in the theta and gamma cortical oscillations play a role in the altered hand dexterity and uncharacteristic adaptive sensorimotor control noted in adults with CP.

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Introduction

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies.

Methods

Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements. Data were collected from 10 healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances/ipa/ and /api/, produced at normal and faster rates.

Results

The results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8-12 Hz) and beta band (13-30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques.

Discussion

These results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.

Beta bursts question the ruling power for brain-computer interfaces

Objective: Current efforts to build reliable brain-computer interfaces (BCI) span multiple axes from hardware, to software, to more sophisticated experimental protocols, and personalized approaches. However, despite these abundant efforts, there is still room for significant improvement. We argue that a rather overlooked direction lies in linking BCI protocols with recent advances in fundamental neuroscience.Approach: In light of these advances, and particularly the characterization of the burst-like nature of beta frequency band activity and the diversity of beta bursts, we revisit the role of beta activity in 'left vs. right hand' motor imagery (MI) tasks. Current decoding approaches for such tasks take advantage of the fact that MI generates time-locked changes in induced power in the sensorimotor cortex and rely on band-passed power changes in single or multiple channels. Although little is known about the dynamics of beta burst activity during MI, we hypothesized that beta bursts should be modulated in a way analogous to their activity during performance of real upper limb movements.Main results and Significance: We show that classification features based on patterns of beta burst modulations yield decoding results that are equivalent to or better than typically used beta power across multiple open electroencephalography datasets, thus providing insights into the specificity of these bio-markers.

Disruption of Sensorimotor Cortical Oscillations by Visual Interference Predicts the Altered Motor Performance of Persons with Cerebral Palsy

Emerging evidence indicates that aberrations in sensorimotor cortical oscillations likely play a key role in uncharacteristic motor actions seen in cerebral palsy. This interpretation is largely centered on the assumption that the aberrant cortical oscillations primarily reflect the motor aspects, with less consideration of possible higher-order cognitive connections. To directly probe this view, we examined the impact of cognitive interference on the sensorimotor cortical oscillations seen in persons with cerebral palsy using magnetoencephalography. Persons with cerebral palsy (N = 26, 9-47 years old) and controls (N = 46, 11-49 years) underwent magnetoencephalographic imaging while completing an arrow-based version of the Eriksen flanker task. Structural equation modeling was used to evaluate the relationship between the extent of interference generated by the flanker task and the strength of the sensorimotor cortical oscillations and motor performance. Our results indicated that the impact of cognitive interference on beta and gamma oscillations moderated the interference effect on reaction times in persons with cerebral palsy, above and beyond that seen in controls. Overall, these findings suggest that alterations in sensorimotor oscillatory activity in those with cerebral palsy at least partly reflects top-down control influences on the motor system. Thus, suppression of distracting stimuli should be a consideration when evaluating altered motor actions in cerebral palsy.

Movement-related ERS and connectivity in the gamma frequency decrease with practice

Previous work showed that movements are accompanied by modulation of electroencephalographic (EEG) activity in both beta (13-30 Hz) and gamma (>30 Hz) ranges. The amplitude of beta event-related synchronization (ERS) is not linked to movement characteristics, but progressively increases with motor practice, returning to baseline after a period of rest. Conversely, movement-related gamma ERS amplitude is proportional to movement distance and velocity. Here, high-density EEG was recorded in 51 healthy subjects to investigate whether i) three-hour practice in two learning tasks, one with a motor component and one without, affects gamma ERS amplitude and connectivity during a motor reaching test, and ii) 90-minutes of either sleep or quiet rest have an effect on gamma oscillatory activity. We found that, while gamma ERS was appropriately scaled to the target extent at all testing points, its amplitude decreased after practice, independently of the type of interposed learning, and after both quiet wake and nap, with partial correlations with subjective fatigue scores. During movement execution, connectivity patterns within fronto-parieto-occipital electrodes, over areas associated with attentional networks, decreased after both practice and after 90-minute rest. While confirming the prokinetic nature of movement-related gamma ERS, these findings demonstrated the preservation of gamma ERS scaling to movement velocity with practice, despite constant amplitude reduction. We thus speculate that such decreases, differently from the practice-related increases of beta ERS, are related to reduced attention or working memory mechanisms due to fatigue or a switch of strategy toward automatization of movement execution and do not specifically reflect plasticity phenomena.

Low-Field Magnetic Stimulation Alleviates MPTP-Induced Alterations in Motor Function and Dopaminergic Neurons in Male Mice

Recent studies show that repetitive transcranial magnetic stimulation (rTMS) improves cognitive and motor functions in patients with Parkinson's Disease (PD). Gamma rhythm low-field magnetic stimulation (LFMS) is a new non-invasive rTMS technique that generates diffused and low-intensity magnetic stimulation to the deep cortical and subcortical areas. To investigate the potential therapeutic effects of LFMS in PD, we subjected an experimental mouse model to LFMS (as an early treatment). We examined the LFMS effect on motor functions as well as neuronal and glial activities in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated male C57BL/6J mice. Mice received MPTP injection (30 mg/kg, i.p., once daily for 5 days) followed by LFMS treatment, 20 min each day for 7 days. LFMS treatment improved motor functions compared with the sham-treated MPTP mice. Further, LFMS significantly improved tyrosine hydroxylase (TH) and decreased glial fibrillary acidic protein (GFAP) levels in substantia nigra pars compacta (SNpc) and non-significantly in striatal (ST) regions. LFMS treatment improved neuronal nuclei (NeuN) levels in SNpc. Our findings suggest that early LFMS treatment improves neuronal survival and, in turn, motor functions in MPTP-treated mice. Further investigation is required to clearly define the molecular mechanisms by which LFMS improves motor and cognitive function in PD patients.

Stereoptic serious games as a visual rehabilitation tool for individuals with a residual amblyopia (AMBER trial): a protocol for a crossover randomized controlled trial

BACKGROUND

Amblyopia is the most common developmental vision disorder in children. The initial treatment consists of refractive correction. When insufficient, occlusion therapy may further improve visual acuity. However, the challenges and compliance issues associated with occlusion therapy may result in treatment failure and residual amblyopia. Virtual reality (VR) games developed to improve visual function have shown positive preliminary results. The aim of this study is to determine the efficacy of these games to improve vision, attention, and motor skills in patients with residual amblyopia and identify brain-related changes. We hypothesize that a VR-based training with the suggested ingredients (3D cues and rich feedback), combined with increasing the difficulty level and the use of various games in a home-based environment is crucial for treatment efficacy of vision recovery, and may be particularly effective in children.

METHODS

The AMBER study is a randomized, cross-over, controlled trial designed to assess the effect of binocular stimulation (VR-based stereoptic serious games) in individuals with residual amblyopia (n = 30, 6-35 years of age), compared to refractive correction on vision, selective attention and motor control skills. Additionally, they will be compared to a control group of age-matched healthy individuals (n = 30) to account for the unique benefit of VR-based serious games. All participants will play serious games 30 min per day, 5 days per week, for 8 weeks. The games are delivered with the Vivid Vision Home software. The amblyopic cohort will receive both treatments in a randomized order according to the type of amblyopia, while the control group will only receive the VR-based stereoscopic serious games. The primary outcome is visual acuity in the amblyopic eye. Secondary outcomes include stereoacuity, functional vision, cortical visual responses, selective attention, and motor control. The outcomes will be measured before and after each treatment with 8-week follow-up.

DISCUSSION

The VR-based games used in this study have been conceived to deliver binocular visual stimulation tailored to the individual visual needs of the patient, which will potentially result in improved basic and functional vision skills as well as visual attention and motor control skills.

TRIAL REGISTRATION

This protocol is registered on ClinicalTrials.gov (identifier: NCT05114252) and in the Swiss National Clinical Trials Portal (identifier: SNCTP000005024).

Individual/Peak Gamma Frequency: What Do We Know?

In recent years, the concept of individualized measures of electroencephalographic (EEG) activity has emerged. Gamma-band activity plays an important role in many sensory and cognitive processes. Thus, peak frequency in the gamma range has received considerable attention. However, peak or individual gamma frequency (IGF) is rarely used as a primary measure of interest; consequently, little is known about its nature and functional significance. With this review, we attempt to comprehensively overview available information on the functional properties of peak gamma frequency, addressing its relationship with certain processes and/or modulation by various factors. Here, we show that IGFs seem to be related to various endogenous and exogenous factors. Broad functional aspects that are related to IGF might point to the differences in underlying mechanisms. Therefore, research utilizing different types of stimulation for IGF estimation and covering several functional aspects in the same population is required. Moreover, IGFs span a wide range of frequencies (30-100 Hz). This could be partly due to the variability of methods used to extract the measures of IGF. In order to overcome this issue, further studies aiming at the optimization of IGF extraction would be greatly beneficial.

Modulation of cortical beta oscillations influences motor vigor: A rhythmic TMS-EEG study

Previous electro- or magnetoencephalography (Electro/Magneto EncephaloGraphic; E/MEG) studies using a correlative approach have shown that β (13-30 Hz) oscillations emerging in the primary motor cortex (M1) are implicated in regulating motor response vigor and associated with an anti-kinetic role, that is, slowness of movement. However, the functional role of M1 β oscillations in regulation of motor responses remains unclear. To address this gap, we combined EEG with rhythmic TMS (rhTMS) delivered to M1 at the β (20 Hz) frequency shortly before subjects performed an isometric ramp-and-hold finger force production task at three force levels. rhTMS is a novel approach that can modulate rhythmic patterns of neural activity. β-rhTMS over M1 induced a modulation of neural oscillations to β frequency in the sensorimotor area and reduced peak force rate during the ramp-up period relative to sham and catch trials. Interestingly, this rhTMS effect occurred only in the large force production condition. To distinguish whether the effects of rhTMS on EEG and behavior stemmed from phase-resetting by each magnetic pulse or neural entrainment by the periodicity of rhTMS, we performed a control experiment using arrhythmic TMS (arTMS). arTMS did not induce changes in EEG oscillations nor peak force rate during the rump-up period. Our results provide novel evidence that β neural oscillations emerging the sensorimotor area influence the regulation of motor response vigor. Furthermore, our findings further demonstrate that rhTMS is a promising tool for tuning neural oscillations to the target frequency.

Movement-related beta ERD and ERS abnormalities in neuropsychiatric disorders

Movement-related oscillations in the beta range (from 13 to 30 Hz) have been observed over sensorimotor areas with power decrease (i.e., event-related desynchronization, ERD) during motor planning and execution followed by an increase (i.e., event-related synchronization, ERS) after the movement's end. These phenomena occur during active, passive, imaged, and observed movements. Several electrophysiology studies have used beta ERD and ERS as functional indices of sensorimotor integrity, primarily in diseases affecting the motor system. Recent literature also highlights other characteristics of beta ERD and ERS, implying their role in processes not strictly related to motor function. Here we review studies about movement-related ERD and ERS in diseases characterized by motor dysfunction, including Parkinson's disease, dystonia, stroke, amyotrophic lateral sclerosis, cerebral palsy, and multiple sclerosis. We also review changes of beta ERD and ERS reported in physiological aging, Alzheimer's disease, and schizophrenia, three conditions without overt motor symptoms. The review of these works shows that ERD and ERS abnormalities are present across the spectrum of the examined pathologies as well as development and aging. They further suggest that cognition and movement are tightly related processes that may share common mechanisms regulated by beta modulation. Future studies with a multimodal approach are warranted to understand not only the specific topographical dynamics of movement-related beta modulation but also the general meaning of beta frequency changes occurring in relation to movement and cognitive processes at large. Such an approach will provide the foundation to devise and implement novel therapeutic approaches to neuropsychiatric disorders.

Brainprints: identifying individuals from magnetoencephalograms

Magnetoencephalography (MEG) is used to study a wide variety of cognitive processes. Increasingly, researchers are adopting principles of open science and releasing their MEG data. While essential for reproducibility, sharing MEG data has unforeseen privacy risks. Individual differences may make a participant identifiable from their anonymized recordings. However, our ability to identify individuals based on these individual differences has not yet been assessed. Here, we propose interpretable MEG features to characterize individual difference. We term these features brainprints (brain fingerprints). We show through several datasets that brainprints accurately identify individuals across days, tasks, and even between MEG and Electroencephalography (EEG). Furthermore, we identify consistent brainprint components that are important for identification. We study the dependence of identifiability on the amount of data available. We also relate identifiability to the level of preprocessing and the experimental task. Our findings reveal specific aspects of individual variability in MEG. They also raise concerns about unregulated sharing of brain data, even if anonymized.

Normalizing the brain connectome for communication through synchronization

Networks in neuroscience determine how brain function unfolds, and their perturbations lead to psychiatric disorders and brain disease. Brain networks are characterized by their connectomes, which comprise the totality of all connections, and are commonly described by graph theory. This approach is deeply rooted in a particle view of information processing, based on the quantification of informational bits such as firing rates. Oscillations and brain rhythms demand, however, a wave perspective of information processing based on synchronization. We extend traditional graph theory to a dual, particle-wave, perspective, integrate time delays due to finite transmission speeds, and derive a normalization of the connectome. When applied to the database of the Human Connectome Project, it explains the emergence of frequency-specific network cores including the visual and default mode networks. These findings are robust across human subjects (N = 100) and are a fundamental network property within the wave picture. The normalized connectome comprises the particle view in the limit of infinite transmission speeds and opens the applicability of graph theory to a wide range of novel network phenomena, including physiological and pathological brain rhythms. These two perspectives are orthogonal, but not incommensurable, when understood within the novel, here-proposed, generalized framework of structural connectivity.

Finely-tuned gamma oscillations: Spectral characteristics and links to dyskinesia

Gamma oscillations comprise a loosely defined, heterogeneous group of functionally different activities between 30 and 100 Hz in the cortical and subcortical local field potential (LFP) of the motor network. Two distinct patterns seem to emerge which are easily conflated: Finely-tuned gamma (FTG) oscillations - a narrowband activity with peaks between 60 and 90 Hz - have been observed in multiple movement disorders and are induced by dopaminergic medication or deep brain stimulation (DBS). FTG has been linked with levodopa or DBS-induced dyskinesias, which makes it a putative biomarker for adaptive DBS. On the other hand, gamma activity can also present as a broad phenomenon (30-100 Hz) in the context of motor activation and dynamic processing. Here, we contrast FTG, either levodopa-induced or DBS-induced, from movement-related broadband gamma synchronisation and further elaborate on the functional role of FTG and its potential implications for adaptive DBS. Given the unclear distinction of FTG and broad gamma in literature, we appeal for more careful separation of the two. To better characterise cortical and subcortical FTG as biomarkers for dyskinesia, their sensitivity and specificity need to be investigated in a large clinical trial.

Connectivity in Large-Scale Resting-State Brain Networks Is Related to Motor Learning: A High-Density EEG Study

Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG), we addressed this question from a brain network perspective. Specifically, we examined frequency-dependent functional connectivity in resting-state networks from twenty-nine young healthy participants before and after they were trained on a motor sequence learning task. Consolidation was assessed with an overnight retest on the motor task. Our results showed training-related decreases in gamma-band connectivity within the motor network, and between the motor and functionally distinct resting-state networks including the attentional network. Brain-behavior correlation analyses revealed that baseline beta, delta, and theta rsFC were related to subsequent motor learning and memory consolidation such that lower connectivity within the motor network and between the motor and several distinct resting-state networks was correlated with better learning and overnight consolidation. Lastly, training-related increases in beta-band connectivity between the motor and the visual networks were related to greater consolidation. Altogether, our results indicate that connectivity in large-scale resting-state brain networks is related to—and modulated by—motor learning and memory consolidation processes. These finding corroborate previous seed-based connectivity research and provide evidence that frequency-dependent functional connectivity in resting-state networks is critically linked to motor learning and memory consolidation.

Modulation of Gamma Spectral Amplitude and Connectivity During Reaching Predicts Peak Velocity and Movement Duration

Modulation of gamma oscillations recorded from the human motor cortex and basal ganglia appears to play a key role in movement execution. However, there are still major questions to be answered about the specific role of cortical gamma activity in both the planning and execution of movement features such as the scaling of peak velocity and movement time. In this study, we characterized movement-related gamma oscillatory dynamics and its relationship with kinematic parameters based on 256-channels EEG recordings in 64 healthy subjects while performing fast and uncorrected reaching movements to targets located at three distances. In keeping with previous studies, we found that movement-related gamma synchronization occurred during movement execution. As a new finding, we showed that gamma synchronization occurred also before movement onset, with planning and execution phases involving different gamma peak frequencies and topographies. Importantly, the amplitude of gamma synchronization in both planning and execution increased with target distance and predicted peak velocity and movement time. Additional analysis of phase coherence revealed a gamma-coordinated long-range network involving occipital, frontal and central regions during movement execution that was positively related to kinematic features. This is the first evidence in humans supporting the notion that gamma synchronization amplitude and phase coherence pattern can reliably predict peak velocity amplitude and movement time. Therefore, these findings suggest that cortical gamma oscillations have a crucial role for the selection, implementation and control of the appropriate kinematic parameters of goal-directed reaching movements.

Serotonin 1A receptor agonist modulation of motor deficits and cortical oscillations by NMDA receptor interaction in parkinsonian rats

Although serotonin 1A (5-HT1A) receptor agonists are widely used as the additive compound to reduce l-dopa-induced dyskinesia in Parkinson's disease (PD), few studies focused on the effect and mechanism of 5-HT1A receptor agonist on the motor symptoms of PD. Unilateral 6-hydroxydopamine (6-OHDA)-lesioned rats were used and implantation of electrodes was performed in the motor cortex of these rats. So the effect of 5-HT1A receptor agonist 8-OH-DPAT on motor behaviors and oscillatory activities were evaluated. In addition, 8-OH-DPAT combined with D2 receptor antagonist raclopride, NMDA receptor antagonist MK-801, or its agonist d-cycloserine (DCS) were co-administrated. 8-OH-DPAT administration significantly improved spontaneous locomotor activity and asymmetric forepaw function in 6-OHDA-lesioned rats. Meanwhile, 8-OH-DPAT identified selective modulation of the abnormal high beta oscillations (25-40 Hz) in the motor cortex of 6-OHDA-lesioned rats, without inducing pathological finely tuned gamma around 80 Hz. Different from 8-OH-DPAT, l-dopa treatment produced a prolonged improvement on motor performances and differential regulation of high beta and gamma oscillations. However, dopamine D2 receptor antagonist had no influence on the 8-OH-DPAT-mediated-motor behaviors and beta oscillations in 6-OHDA-lesioned rats. In contrast, subthreshold NMDA receptor antagonist MK-801 obviously elevated the 8-OH-DPAT-mediated-motor behaviors, while NMDA receptor agonist DCS partially impaired the 8-OH-DPAT-mediated symptoms in 6-OHDA-lesioned rats. This study suggests that 5-HT1A receptor agonist 8-OH-DPAT improves motor activity and modulates the oscillations in the motor cortex of parkinsonian rats. Different from l-dopa, 8-OH-DPAT administration ameliorates motor symptoms of PD through glutamatergic rather than the dopaminergic pathway.

The Control of Movements via Motor Gamma Oscillations

The ability to perform movements is vital for our daily life. Our actions are embedded in a complex environment where we need to deal efficiently in the face of unforeseen events. Neural oscillations play an important role in basic sensorimotor processes related to the execution and preparation of movements. In this review, I will describe the state of the art regarding the role of motor gamma oscillations in the control of movements. Experimental evidence from electrophysiological studies has shown that motor gamma oscillations accomplish a range of functions in motor control beyond merely signaling the execution of movements. However, these additional aspects associated with motor gamma oscillation remain to be fully clarified. Future work on different spatial, temporal and spectral scales is required to further understand the implications of gamma oscillations in motor control.

An Impending Paradigm Shift in Motor Imagery Based Brain-Computer Interfaces

The development of reliable assistive devices for patients that suffer from motor impairments following central nervous system lesions remains a major challenge in the field of non-invasive Brain-Computer Interfaces (BCIs). These approaches are predominated by electroencephalography and rely on advanced signal processing and machine learning methods to extract neural correlates of motor activity. However, despite tremendous and still ongoing efforts, their value as effective clinical tools remains limited. We advocate that a rather overlooked research avenue lies in efforts to question neurophysiological markers traditionally targeted in non-invasive motor BCIs. We propose an alternative approach grounded by recent fundamental advances in non-invasive neurophysiology, specifically subject-specific feature extraction of sensorimotor bursts of activity recorded via (possibly magnetoencephalography-optimized) electroencephalography. This path holds promise in overcoming a significant proportion of existing limitations, and could foster the wider adoption of online BCIs in rehabilitation protocols.

Detection and Analysis of Cortical Beta Bursts in Developmental EEG Data

Developmental EEG research often involves analyzing signals within various frequency bands, based on the assumption that these signals represent oscillatory neural activity. However, growing evidence suggests that certain frequency bands are dominated by transient burst events in single trials rather than sustained oscillations. This is especially true for the beta band, with adult ‘beta burst’ timing a better predictor of motor behavior than slow changes in average beta amplitude. No developmental research thus far has looked at beta bursts, with techniques used to investigate frequency-specific activity structure rarely even applied to such data. Therefore, we aimed to: i) provide a tutorial for developmental EEG researchers on the application of methods for evaluating the rhythmic versus transient nature of frequency-specific activity; and ii) use these techniques to investigate the existence of sensorimotor beta bursts in infants. We found that beta activity in 12-month-olds did occur in bursts, however differences were also revealed in terms of duration, amplitude, and rate during grasping compared to adults. Application of the techniques illustrated here will be critical for clarifying the functional roles of frequency-specific activity across early development, including the role of beta activity in motor processing and its contribution to differing developmental motor trajectories.

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Transient bursts rather than oscillations dominate sensorimotor beta activity

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Lagged coherence indicates the rhythmicity of a signal

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The p-episode method can be used to identify beta bursts in developmental EEG data

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Infant sensorimotor beta has a lower peak frequency than adults and consists of longer duration, higher amplitude bursts

Simultaneously recorded subthalamic and cortical LFPs reveal different lexicality effects during reading aloud

Many language functions are traditionally assigned to cortical brain areas, leaving the contributions of subcortical structures to language processing largely unspecified. The present study examines a potential role of the subthalamic nucleus (STN) in lexical processing, specifically, reading aloud of words (e.g., 'fate') and pseudowords (e.g., 'fape'). We recorded local field potentials simultaneously from the STN and the cortex (precentral, postcentral, and superior temporal gyri) of 13 people with Parkinson's disease undergoing awake deep brain stimulation and compared STN's lexicality-related neural activity with that of the cortex. Both STN and cortical activity demonstrated significant task-related modulations, but the lexicality effects were different in the two brain structures. In the STN, an increase in gamma band activity (31-70 Hz) was present in pseudoword trials compared to word trials during subjects' spoken response. In the cortex, a greater decrease in beta band activity (12-30 Hz) was observed for pseudowords in the precentral gyrus. Additionally, 11 individual cortical sites showed lexicality effects with varying temporal and topographic characteristics in the alpha and beta frequency bands. These findings suggest that the STN and the sampled cortical regions are involved differently in the processing of lexical distinctions.

The Influence of Frequency Bands and Brain Region on ECoG-Based BMI Learning Performance

Numerous brain–machine interface (BMI) studies have shown that various frequency bands (alpha, beta, and gamma bands) can be utilized in BMI experiments and modulated as neural information for machine control after several BMI learning trial sessions. In addition to frequency range as a neural feature, various areas of the brain, such as the motor cortex or parietal cortex, have been selected as BMI target brain regions. However, although the selection of target frequency and brain region appears to be crucial in obtaining optimal BMI performance, the direct comparison of BMI learning performance as it relates to various brain regions and frequency bands has not been examined in detail. In this study, ECoG-based BMI learning performances were compared using alpha, beta, and gamma bands, respectively, in a single rodent model. Brain area dependence of learning performance was also evaluated in the frontal cortex, the motor cortex, and the parietal cortex. The findings indicated that BMI learning performance was best in the case of the gamma frequency band and worst in the alpha band (one-way ANOVA, F = 4.41, p < 0.05). In brain area dependence experiments, better BMI learning performance appears to be shown in the primary motor cortex (one-way ANOVA, F = 4.36, p < 0.05). In the frontal cortex, two out of four animals failed to learn the feeding tube control even after a maximum of 10 sessions. In conclusion, the findings reported in this study suggest that the selection of target frequency and brain region should be carefully considered when planning BMI protocols and for performing optimized BMI.

Stuttering: A Disorder of Energy Supply to Neurons?

Stuttering is a disorder characterized by intermittent loss of volitional control of speech movements. This hypothesis and theory article focuses on the proposal that stuttering may be related to an impairment of the energy supply to neurons. Findings from electroencephalography (EEG), brain imaging, genetics, and biochemistry are reviewed: (1) Analyses of the EEG spectra at rest have repeatedly reported reduced power in the beta band, which is compatible with indications of reduced metabolism. (2) Studies of the absolute level of regional cerebral blood flow (rCBF) show conflicting findings, with two studies reporting reduced rCBF in the frontal lobe, and two studies, based on a different method, reporting no group differences. This contradiction has not yet been resolved. (3) The pattern of reduction in the studies reporting reduced rCBF corresponds to the regional pattern of the glycolytic index (GI; Vaishnavi et al., 2010). High regional GI indicates high reliance on non-oxidative metabolism, i.e., glycolysis. (4) Variants of the gene ARNT2 have been associated with stuttering. This gene is primarily expressed in the brain, with a pattern roughly corresponding to the pattern of regional GI. A central function of the ARNT2 protein is to act as one part of a sensor system indicating low levels of oxygen in brain tissue and to activate appropriate responses, including activation of glycolysis. (5) It has been established that genes related to the functions of the lysosomes are implicated in some cases of stuttering. It is possible that these gene variants result in a reduced peak rate of energy supply to neurons. (6) Lastly, there are indications of interactions between the metabolic system and the dopamine system: for example, it is known that acute hypoxia results in an elevated tonic level of dopamine in the synapses. Will mild chronic limitations of energy supply also result in elevated levels of dopamine? The indications of such interaction effects suggest that the metabolic theory of stuttering should be explored in parallel with the exploration of the dopaminergic theory.

Gamma-Band Frequency Analysis and Motor Development in Music-Trained Children: A Cross-Sectional Study

Background: The aim of this study was to analyze the gamma-band frequency and motor performance of children with and without music training.Methods: This cross-sectional study included 31 right-handed children, 6-11 years old, who were allocated to two groups: 1) the music group (MG), including children who attended preschool and musical training (n = 16), and 2) the no-music group (NMG), including children who attended preschool but received no additional music training (n = 15). The outcomes were gamma-band frequency measured by electroencephalography, manual dexterity, aim-and-catch, and static and dynamic balance abilities measured by the Movement Assessment Battery for Children, and fine motor skills, overall motor skills, balance, corporal body scheme, spatial organization, temporal orientation, and general motor quotient (GMQ) by a Brazilian scale for motor development.Results: There 1was a significant difference between groups in the peak frequency (p = 0.0195) and median frequency (p = 0.0070) in the F3-F4 regions. Static and dynamic balance (p = 0.03), temporal orientation (p < 0.01), and GMQ (p < 0.03) were higher in MG than in NMG.Conclusion: The musically trained children had increased gamma-peak frequency in the frontal region and greater temporal orientation, balance, and the overall motor quotient.

Movement-Related Gamma Synchrony Differentially Predicts Behavior in the Presence of Visual Interference Across the Lifespan

The ability to allocate neural resources to task-relevant stimuli, while inhibiting distracting information in the surrounding environment (i.e., selective attention) is critical for high-level cognitive function, and declines in this ability have been linked to functional deficits in later life. Studies of age-related declines in selective attention have focused on frontal circuitry, with almost no work evaluating the contribution of motor cortical dynamics to successful task performance. Herein, we examined 69 healthy adults (23-72 years old) who completed a flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain using a beamformer to evaluate the contribution of motor cortical dynamics to age-related increases in behavioral interference effects. Our results showed that gamma oscillations in the contralateral motor cortex (M1) were a robust predictor of reaction time, regardless of interference level. Additionally, we observed condition-wise differences in gamma-by-age interactions, such that in younger adults, increases in M1 gamma power were predictive of faster reaction times during incongruent trials, while older adults did not receive this same behavioral benefit. Importantly, these data indicate that M1 gamma oscillations are differentially predictive of behavior in the presence, but not absence of visual interference, resulting in exhausted compensatory strategies with age.

Data-driven beamforming technique to attenuate ballistocardiogram artefacts in electroencephalography-functional magnetic resonance imaging without detecting cardiac pulses in electrocardiography recordings

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a very promising non‐invasive neuroimaging technique. However, EEG data obtained from the simultaneous EEG–fMRI are strongly influenced by MRI‐related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. When compared to the GA correction, the BCG correction is more challenging to remove due to its inherent variabilities and dynamic changes over time. The standard BCG correction (i.e., average artefact subtraction [AAS]), require detecting cardiac pulses from simultaneous electrocardiography (ECG) recording. However, ECG signals are also distorted and will become problematic for detecting reliable cardiac peaks. In this study, we focused on a beamforming spatial filtering technique to attenuate all unwanted source activities outside of the brain. Specifically, we applied the beamforming technique to attenuate the BCG artefact in EEG–fMRI, and also to recover meaningful task‐based neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond accurately. We analysed EEG–fMRI data in 20 healthy participants during the ANT, and compared four different BCG corrections (non‐BCG corrected, AAS BCG corrected, beamforming + AAS BCG corrected, beamforming BCG corrected). We demonstrated that the beamforming approach did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task‐based brain activity when compared to the standard AAS correction. This data‐driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG–fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI‐related artefacts.

Mechanisms of Network Interactions for Flexible Cortico-Basal Ganglia-Mediated Action Control

In humans, finely tuned γ synchronization (60-90 Hz) rapidly appears at movement onset in a motor control network involving primary motor cortex, the basal ganglia and motor thalamus. Yet the functional consequences of brief movement-related synchronization are still unclear. Distinct synchronization phenomena have also been linked to different forms of motor inhibition, including relaxing antagonist muscles, rapid movement interruption and stabilizing network dynamics for sustained contractions. Here, I will introduce detailed hypotheses about how intrasite and intersite synchronization could interact with firing rate changes in different parts of the network to enable flexible action control. The here proposed cause-and-effect relationships shine a spotlight on potential key mechanisms of cortico-basal ganglia-thalamo-cortical (CBGTC) communication. Confirming or revising these hypotheses will be critical in understanding the neuronal basis of flexible movement initiation, invigoration and inhibition. Ultimately, the study of more complex cognitive phenomena will also become more tractable once we understand the neuronal mechanisms underlying behavioral readouts.

Circuit Mechanisms of L-DOPA-Induced Dyskinesia (LID)

L-DOPA is the criterion standard of treatment for Parkinson disease. Although it alleviates some of the Parkinsonian symptoms, long-term treatment induces L-DOPA–induced dyskinesia (LID). Several theoretical models including the firing rate model, the firing pattern model, and the ensemble model are proposed to explain the mechanisms of LID. The “firing rate model” proposes that decreasing the mean firing rates of the output nuclei of basal ganglia (BG) including the globus pallidus internal segment and substantia nigra reticulata, along the BG pathways, induces dyskinesia. The “firing pattern model” claimed that abnormal firing pattern of a single unit activity and local field potentials may disturb the information processing in the BG, resulting in dyskinesia. The “ensemble model” described that dyskinesia symptoms might represent a distributed impairment involving many brain regions, but the number of activated neurons in the striatum correlated most strongly with dyskinesia severity. Extensive evidence for circuit mechanisms in driving LID symptoms has also been presented. LID is a multisystem disease that affects wide areas of the brain. Brain regions including the striatum, the pallidal–subthalamic network, the motor cortex, the thalamus, and the cerebellum are all involved in the pathophysiology of LID. In addition, although both amantadine and deep brain stimulation help reduce LID, these approaches have complications that limit their wide use, and a novel antidyskinetic drug is strongly needed; these require us to understand the circuit mechanism of LID more deeply.

Aberrant brain oscillatory coupling from the primary motor cortex in children with autism spectrum disorders

Autism spectrum disorder (ASD) often involves dysfunction in general motor control and motor coordination, in addition to core symptoms. However, the neural mechanisms underlying motor dysfunction in ASD are poorly understood. To elucidate this issue, we focused on brain oscillations and their coupling in the primary motor cortex (M1). We recorded magnetoencephalography in 18 children with ASD, aged 5 to 7 years, and 19 age- and IQ-matched typically-developing children while they pressed a button during a video-game-like motor task. The motor-related gamma (70 to 90 Hz) and pre-movement beta oscillations (15 to 25 Hz) were analyzed in the primary motor cortex using an inverse method. To determine the coupling between beta and gamma oscillations, we applied phase-amplitude coupling to calculate the statistical dependence between the amplitude of fast oscillations and the phase of slow oscillations. We observed a motor-related gamma increase and a pre-movement beta decrease in both groups. The ASD group exhibited a reduced motor-related gamma increase and enhanced pre-movement beta decrease in the ipsilateral primary motor cortex. We found phase-amplitude coupling, in which high-gamma activity was modulated by the beta rhythm in the primary motor cortex. Phase-amplitude coupling in the ipsilateral primary motor cortex was reduced in the ASD group compared with the control group. Using oscillatory changes and their couplings, linear discriminant analysis classified the ASD and control groups with high accuracy (area under the receiver operating characteristic curve: 97.1%). The current findings revealed alterations in oscillations and oscillatory coupling, reflecting the dysregulation of motor gating mechanisms in ASD. These results may be helpful for elucidating the neural mechanisms underlying motor dysfunction in ASD, suggesting the possibility of developing a biomarker for ASD diagnosis.

Response certainty during bimanual movements reduces gamma oscillations in primary motor cortex

Even when movement outputs are identical, the neural responses supporting them might differ substantially in order to adapt to changing environmental contexts. Despite the essential nature of this adaptive capacity of the human motor system, little is known regarding the effects of contextual response (un)certainty on the neural dynamics known to serve motor processing. In this study, we use a novel bimanual motor task and neuroimaging with magnetoencephalography (MEG) to examine the effects of contextual response certainty on the dynamic neural responses that are important for proper movement. Significant neural responses were identified in the time-frequency domain at the sensor-level and imaged to the cortex using a spectrally resolved beamformer. Combined frequentist and Bayesian statistical testing between neural motor responses under certain and uncertain conditions indicated evidence for no conditional effect on the peri-movement beta desynchronization (18 - 28 Hz; -100 to 300 ms). In contrast, the movement-related gamma synchronization (MRGS; 66 - 86 Hz; -50 to 150 ms) exhibited a robust effect of motor certainty, such that increased contextual response certainty reduced the amplitude of this response. Interestingly, the peak frequency of the MRGS was unaffected by response certainty. These findings both advance our understanding of the neural processes required to adapt our movements under altered environmental contexts, and support the growing conceptualization of the MRGS as being reflective of ongoing higher cognitive processes during movement execution.

Age-related trends in neuromagnetic transient beta burst characteristics during a sensorimotor task and rest in the Cam-CAN open-access dataset

Non-invasive neurophysiological recordings, such as those measured by magnetoencelography (MEG), provide insight into the behaviour of neural networks and how these networks change with factors such as task performance, disease state, and age. Recently, there has been a trend in describing neurophysiological recordings as a series of transient bursts of neural activity rather than averaged sustained oscillations as burst characteristics may be more directly correlated with the neurological generators of brain activity. In this work, we investigate how beta burst characteristics change with age in a large open access dataset. The objectives are (1) to detect and characterize transient beta bursts over the ipsilateral and contralateral primary sensorimotor cortices during a unilateral motor task performance and during wakeful resting, and (2) to identify age-related changes in beta burst characteristics, in the context of earlier reports of age-related changes in beta suppression and the post-movement beta rebound. MEG data, acquired at the Cambridge Centre for Ageing and Neuroscience, of roughly 600 participants with a nearly uniform distribution of ages between 18 and 88 years old was used for analysis. We found that burst rate is the predominant factor related to age-related changes in the amplitude of the induced beta rhythm responses associated with a button press task. Furthermore, we present a cross-validation of burst parameters detected at the sensor- (peak sensor and sensor ROI) and source-level (beamformer spatial filter). This work is as an important step in characterizing transient bursts in neuromagnetic signals in the temporal domain, towards a better understanding of the healthy aging human brain.

Structural correlates of atypical visual and motor cortical oscillations in pediatric-onset multiple sclerosis

We have previously demonstrated that pediatric‐onset multiple sclerosis (POMS) negatively impacts the visual pathway as well as motor processing speed. Relationships between MS‐related diffuse structural damage of gray and white matter (WM) tissue and cortical responses to visual and motor stimuli remain poorly understood. We used magnetoencephalography in 14 POMS patients and 15 age‐ and sex‐matched healthy controls to assess visual gamma (30–80 Hz), motor gamma (60–90 Hz), and motor beta (15–30 Hz) cortical oscillatory responses to a visual‐motor task. Then, 3T MRI was used to: (a) calculate fractional anisotropy (FA) of the posterior visual and corticospinal motor WM pathways and (b) quantify volume and thickness of the cuneus and primary motor cortex. Visual gamma band power was reduced in POMS and was associated with reduced FA of the optic radiations but not with loss of cuneus volume or thickness. Activity in the primary motor cortex, as measured by postmovement beta rebound amplitude associated with peak latency, was decreased in POMS, although this reduction was not predicted by structural metrics. Our findings implicate loss of WM integrity as a contributor to reduced electrical responses in the visual cortex in POMS. Future work in larger cohorts will inform on the cognitive implications of this finding in terms of visual processing function and will determine whether the progressive loss of brain volume known to occur in POMS ultimately contributes to both progressive dysfunction in such tasks as well as progressive reduction in cortical electrical responses in the visual cortex.

Significance and Translational Value of High-Frequency Cortico-Basal Ganglia Oscillations in Parkinson's Disease

The mechanisms and significance of basal ganglia oscillations is a fundamental research question engaging both clinical and basic investigators. In Parkinson’s disease (PD), neural activity in basal ganglia nuclei is characterized by oscillatory patterns that are believed to disrupt the dynamic processing of movement-related information and thus generate motor symptoms. Beta-band oscillations associated with hypokinetic states have been reviewed in several excellent previous articles. Here we focus on faster oscillatory phenomena that have been reported in association with a diverse range of motor states. We review the occurrence of different types of fast oscillations and the evidence supporting their pathophysiological role. We also provide a general discussion on the definition, possible mechanisms, and translational value of synchronized oscillations of different frequencies in cortico-basal ganglia structures. Revealing how oscillatory phenomena are caused and spread in cortico-basal ganglia-thalamocortical networks will offer a key to unlock the neural codes of both motor and non-motor symptoms in PD. In preclinical therapeutic research, recording of oscillatory neural activities holds the promise to unravel mechanisms of action of current and future treatments.

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.

Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals

Speech production is a hierarchical mechanism involving the synchronization of the brain and the oral articulators, where the intention of linguistic concepts is transformed into meaningful sounds. Individuals with locked-in syndrome (fully paralyzed but aware) lose their motor ability completely including articulation and even eyeball movement. The neural pathway may be the only option to resume a certain level of communication for these patients. Current brain-computer interfaces (BCIs) use patients' visual and attentional correlates to build communication, resulting in a slow communication rate (a few words per minute). Direct decoding of imagined speech from the neural signals (and then driving a speech synthesizer) has the potential for a higher communication rate. In this study, we investigated the decoding of five imagined and spoken phrases from single-trial, non-invasive magnetoencephalography (MEG) signals collected from eight adult subjects. Two machine learning algorithms were used. One was an artificial neural network (ANN) with statistical features as the baseline approach. The other was convolutional neural networks (CNNs) applied on the spatial, spectral and temporal features extracted from the MEG signals. Experimental results indicated the possibility to decode imagined and spoken phrases directly from neuromagnetic signals. CNNs were found to be highly effective with an average decoding accuracy of up to 93% for the imagined and 96% for the spoken phrases.

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

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

Task-Modulated Corticocortical Synchrony in the Cognitive-Motor Network Supporting Handwriting

Both motor and cognitive aspects of behavior depend on dynamic, accurately timed neural processes in large-scale brain networks. Here, we studied synchronous interplay between cortical regions during production of cognitive-motor sequences in humans. Specifically, variants of handwriting that differed in motor variability, linguistic content, and memorization of movement cues were contrasted to unveil functional sensitivity of corticocortical connections. Data-driven magnetoencephalography mapping (n = 10) uncovered modulation of mostly left-hemispheric corticocortical interactions, as quantified by relative changes in phase synchronization. At low frequencies (~2–13 Hz), enhanced frontoparietal synchrony was related to regular handwriting, whereas premotor cortical regions synchronized for simple loop production and temporo-occipital areas for a writing task substituting normal script with loop patterns. At the beta-to-gamma band (~13–45 Hz), enhanced synchrony was observed for regular handwriting in the central and frontoparietal regions, including connections between the sensorimotor and supplementary motor cortices and between the parietal and dorsal premotor/precentral cortices. Interpreted within a modular framework, these modulations of synchrony mainly highlighted interactions of the putative pericentral subsystem of hand coordination and the frontoparietal subsystem mediating working memory operations. As part of cortical dynamics, interregional phase synchrony varies depending on task demands in production of cognitive-motor sequences.

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis

The purpose of this paper is to record and analyze induced gamma-band activity (GBA) (30-60 Hz) in cerebral motor areas during imaginary movement and to compare it quantitatively with activity recorded in the same areas during actual movement using a simplified electroencephalogram (EEG). Brain activity (basal activity, imaginary motor task and actual motor task) is obtained from 12 healthy volunteer subjects using an EEG (Cz channel). GBA is analyzed using the mean power spectral density (PSD) value. Event-related synchronization (ERS) is calculated from the PSD values of the basal GBA (GBAb), the GBA of the imaginary movement (GBAim) and the GBA of the actual movement (GBAac). The mean GBAim and GBAac values for the right and left hands are significantly higher than the GBAb value (p = 0.007). No significant difference is detected between mean GBA values during the imaginary and actual movement (p = 0.242). The mean ERS values for the imaginary movement (ERSimM (%) = 23.52) and for the actual movement (ERSacM = 27.47) do not present any significant difference (p = 0.117). We demonstrated that ERS could provide a useful way of indirectly checking the function of neuronal motor circuits activated by voluntary movement, both imaginary and actual. These results, as a proof of concept, could be applied to physiology studies, brain-computer interfaces, and diagnosis of cognitive or motor pathologies.

Gamma frequency band shift of contralateral corticomuscular synchronous oscillations with force strength for hand movement tasks

Bilateral voluntary contractions involve functional changes in both primary motor cortices. However how the unilateral voluntary contraction of hand muscles influences the contralateral corticomuscular synchronous oscillations mechanisms remains unclear. In the bimanual tasks, nine healthy subjects were instructed to generate force by abducting their left-hand index finger against a force sensor and simultaneously the right-hand precise pinch task with visual feedback. They were divided into four conditions according to the two contraction force levels of the left-hand muscles 5% and 50% maximal isometric voluntary contraction (MVC) and with/without visual feedback for the right hand. Corticomuscular synchronization of the right hand in the beta band was revealed when the subjects performed the bimanual exercise with 5% MVC of left-hand muscles, which is consistent with previous studies. As the contraction strength of the left-hand muscle increased to 50% MVC, the corticomuscular coherence (CMC) frequency of the right hand shifted to gamma band, and the CMC in beta band decreased significantly (P < 0.05) in the electroencephalography→electromyography direction. This phenomenon suggests that the corticomuscular synchronous oscillation will shift from beta band to higher frequencies (principally gamma) as the contraction force of the contralateral hand increases, which may be due to the changes in the subject's attention and more frequent synchronization of neuromuscular motor neurons oscillations. These findings will be helpful to explore the hand motion control and feedback mechanisms, and further provide a basis for the application of neuromuscular coupling in clinical rehabilitation evaluation.Video abstract: http://links.lww.com/WNR/A571.

Individual differences in motor development during early childhood: An MEG study

In a previous study, we reported the first measurements of pre-movement and sensorimotor cortex activity in preschool age children (ages 3-5 years) using a customized pediatric magnetoencephalographic system. Movement-related activity in the sensorimotor cortex differed from that typically observed in adults, suggesting that maturation of cortical motor networks was still incomplete by late preschool age. Here we compare these earlier results to a group of school age children (ages 6-8 years) including seven children from the original study measured again two years later, and a group of adults (mean age 31.1 years) performing the same task. Differences in movement-related brain activity were observed both longitudinally within children in which repeated measurements were made, and cross-sectionally between preschool age children, school age children, and adults. Movement-related mu (8-12 Hz) and beta (15-30 Hz) oscillations demonstrated linear increases in amplitude and mean frequency with age. In contrast, movement-evoked gamma synchronization demonstrated a step-like transition from low (30-50 Hz) to high (70-90 Hz) narrow-band oscillations, and this occurred at different ages in different children. Notably, pre-movement activity ('readiness fields') observed in adults was absent in even the oldest children. These are the first direct observations of brain activity accompanying motor responses throughout early childhood, confirming that maturation of this activity is still incomplete by mid-childhood. In addition, individual children demonstrated markedly different developmental trajectories in movement-related brain activity, suggesting that individual differences need to be taken into account when studying motor development across age groups.

Determining the Optimal Number of MEG Trials: A Machine Learning and Speech Decoding Perspective

Advancing the knowledge about neural speech mechanisms is critical for developing next-generation, faster brain computer interface to assist in speech communication for the patients with severe neurological conditions (e.g., locked-in syndrome). Among current neuroimaging techniques, Magnetoencephalography (MEG) provides direct representation for the large-scale neural dynamics of underlying cognitive processes based on its optimal spatiotemporal resolution. However, the MEG measured neural signals are smaller in magnitude compared to the background noise and hence, MEG usually suffers from a low signal-to-noise ratio (SNR) at the single-trial level. To overcome this limitation, it is common to record many trials of the same event-task and use the time-locked average signal for analysis, which can be very time consuming. In this study, we investigated the effect of the number of MEG recording trials required for speech decoding using a machine learning algorithm. We used a wavelet filter for generating the denoised neural features to train an Artificial Neural Network (ANN) for speech decoding. We found that wavelet based denoising increased the SNR of the neural signal prior to analysis and facilitated accurate speech decoding performance using as few as 40 single-trials. This study may open up the possibility of limiting MEG trials for other task evoked studies as well.

Quantitative Evaluation in Estimating Sources Underlying Brain Oscillations Using Current Source Density Methods and Beamformer Approaches

Brain oscillations from EEG and MEG shed light on neurophysiological mechanisms of human behavior. However, to extract information on cortical processing, researchers have to rely on source localization methods that can be very broadly classified into current density estimates such as exact low-resolution brain electromagnetic tomography (eLORETA), minimum norm estimates (MNE), and beamformers such as dynamic imaging of coherent sources (DICS) and linearly constrained minimum variance (LCMV). These algorithms produce a distributed map of brain activity underlying sustained and transient responses during neuroimaging studies of behavior. On the other hand, there are very few comparative analyses that evaluates the “ground truth detection” capabilities of these methods. The current article evaluates the reliability in estimation of sources of spectral event generators in the cortex using a two-pronged approach. First, simulated EEG data with point dipoles and distributed dipoles are used to validate the accuracy and sensitivity of each one of these methods of source localization. The abilities of the techniques were tested by comparing the localization error, focal width, false positive (FP) ratios while detecting already known location of neural activity generators under varying signal-to-noise ratios (SNRs). Second, empirical EEG data during auditory steady state responses (ASSRs) in human participants were used to compare the distributed nature of source localization. All methods were successful in recovery of point sources in favorable signal to noise scenarios and could achieve high hit rates if FPs are ignored. Interestingly, focal activation map is generated by LCMV and DICS when compared to eLORETA while control of FPs is much superior in eLORETA. Subsequently drawbacks and strengths of each method are highlighted with a detailed discussion on how to choose a technique based on empirical requirements.

Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions

Cortico-basal ganglia circuits are thought to play a crucial role in the selection and control of motor behaviors and have also been implicated in the processing of motivational content and in higher cognitive functions. During the last two decades, electrophysiological recordings in basal ganglia circuits have shown that several disease conditions are associated with specific changes in the temporal patterns of neuronal activity. In particular, synchronized oscillations have been a frequent finding suggesting that excessive synchronization of neuronal activity may be a pathophysiological mechanism involved in a wide range of neurologic and psychiatric conditions. We here review the experimental support for this hypothesis primarily in relation to Parkinson’s disease but also in relation to dystonia, essential tremor, epilepsy, and psychosis/schizophrenia.

Dynamic Activation Patterns of the Motor Brain Revealed by Diffuse Optical Tomography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019;2019:6028-6031. [PMID: 31947220 DOI: 10.1109/embc.2019.8857370]

Diffuse optical tomography (DOT), a subset of functional near-infrared spectroscopy (fNIRS), is a noninvasive functional imaging modality for studying the human brain in normal and diseased conditions. It measures changes in concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) in the blood vasculature of the brain. In contrast to functional magnetic resonance imaging (fMRI), the gold standard in human brain imaging, DOT offers the advantage of higher temporal resolution, portability, lower cost, multiple contrasts and usability for persons who cannot otherwise utilize MRI-based imaging modalities, including bedridden patients and infants, etc. The goal of the present study was to evaluate performance of a DOT method in studying dynamic patterns of brain activations involving motor control. CW-fNIRS data were acquired in four sessions from a healthy male participant when he performed a motor task in a block-design experiment. Results from experimental data showed pronounced activity in the primary motor cortex (M1), contralateral to the clenching hand. It was further observed that the M1 activity was consistent over four sessions. Furthermore, temporal dynamics of motor activity at each session further revealed well-sequenced activation patterns among M1, premotor cortex (PMC), and supplementary motor area (SMA). Timed ipsilateral motor activity suppression was also observed several seconds after the onset of contralateral M1 activity. More importantly, these temporal dynamics were similarly observed in all four sessions. These preliminary results suggest that the DOT method has the sensitivity, reliability, and spatio-temporal resolutions to study activities originated from the motor cortices. A full-scope evaluation and validation in more participants on the motor system can establish it as a promising neuroimaging tool to study, such as, infants at the risk of cerebral palsy or elders with Parkinson's due to its portability and usability in clinical environments.

The functional role of beta-oscillations in the supplementary motor area during reaching and grasping after stroke: A question of structural damage to the corticospinal tract

Hand motor function is often severely affected in stroke patients. Non-satisfying recovery limits reintegration into normal daily life. Understanding stroke-related network changes and identifying common principles that might underlie recovered motor function is a prerequisite for the development of interventional therapies to support recovery. Here, we combine the evaluation of functional activity (multichannel electroencephalography) and structural integrity (diffusion tensor imaging) in order to explain the degree of residual motor function in chronic stroke patients. By recording neural activity during a reaching and grasping task that mimics activities of daily living, the study focuses on deficit-related neural activation patterns. The study showed that the functional role of movement-related beta desynchronization in the supplementary motor area (SMA) for residual hand motor function in stroke patients depends on the microstructural integrity of the corticospinal tract (CST). In particular, in patients with damaged CST, stronger task-related activity in the SMA was associated with worse residual motor function. Neither CST damage nor functional brain activity alone sufficiently explained residual hand motor function. The findings suggest a central role of the SMA in the motor network during reaching and grasping in stroke patients, the degree of functional relevance of the SMA is depending on CST integrity.