Alpha, beta and gamma electrocorticographic rhythms in somatosensory, motor, premotor and prefrontal cortical areas differ in movement execution and observation in humans

Time synchronization between parietal-frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks

BACKGROUND

In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated.

METHODS

Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson's correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification.

RESULTS

Parietal-frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients.

CONCLUSIONS

In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation.

Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex

Social interactions in primates require social cognition abilities such as anticipating the partner's future choices as well as pure cognitive skills involving processing task-relevant information. The medial prefrontal cortex (mPFC) has been implicated in these cognitive processes. Here, we investigated the neural oscillations underlying the complex social behaviors involving the interplay of social roles (Actor vs. Observer) and interaction types (whether working with a "Good" or "Bad" partner). We found opposite power modulations of the beta and gamma bands by social roles, indicating dedicated processing for task-related information. Concurrently, the interaction type was conveyed by lower frequencies, which are commonly associated with neural circuits linked to performance and reward monitoring. Thus, the mPFC exhibits parallel coding of both "cold" processes (purely cognitive) and "hot" processes (reward and social-related). This allocation of neural resources gives the mPFC a key neural node, flexibly integrating multiple sources of information during social interactions.

Exploring empathic engagement in immersive media: An EEG study on mu rhythm suppression in VR

This study investigates the influence of immersive media, particularly Virtual Reality (VR), on empathic responses, in comparison to traditional television (TV), using electroencephalography (EEG). We employed mu rhythm suppression as a measurable neural marker to gauge empathic engagement, as its increase generally signifies heightened empathic responses. Our findings exhibit a greater mu rhythm suppression in VR conditions compared to TV conditions, suggesting a potential enhancement in empathic responses with VR. Furthermore, our results revealed that the strength of empathic responses was not confined to specific actions depicted in the video clips, underscoring the possibility of broader implications. This research contributes to the ongoing discourse on the effects of different media environments on empathic engagement, particularly emphasizing the unique role of immersive technologies such as VR. It invites further investigation into how such technologies can shape and potentially enhance the empathic experience.

Motor cortex activation during visuomotor transformations: evoked potentials during overt and imagined movements

Despite the prevalence of visuomotor transformations in our motor skills, their mechanisms remain incompletely understood, especially when imagery actions are considered such as mentally picking up a cup or pressing a button. Here, we used a stimulus-response task to directly compare the visuomotor transformation underlying overt and imagined button presses. Electroencephalographic activity was recorded while participants responded to highlights of the target button while ignoring the second, non-target button. Movement-related potentials (MRPs) and event-related desynchronization occurred for both overt movements and motor imagery (MI), with responses present even for non-target stimuli. Consistent with the activity accumulation model where visual stimuli are evaluated and transformed into the eventual motor response, the timing of MRPs matched the response time on individual trials. Activity-accumulation patterns were observed for MI, as well. Yet, unlike overt movements, MI-related MRPs were not lateralized, which appears to be a neural marker for the distinction between generating a mental image and transforming it into an overt action. Top-down response strategies governing this hemispheric specificity should be accounted for in future research on MI, including basic studies and medical practice.

Early modulations of neural oscillations during the processing of emotional body language

The processing of threat-related emotional body language (EBL) has been shown to engage sensorimotor cortical areas early on and induce freezing in the observers' motor system, particularly when observing fearful EBL. To provide insights into the interplay between somatosensory and motor areas during observation of EBL, here, we used high-density electroencephalography (hd-EEG) in healthy humans while they observed EBL stimuli involving fearful and neutral expressions. To capture early sensorimotor brain response, we focused on P100 fronto-central event-related potentials (ERPs) and event-related desynchronization/synchronization (ERD/ERS) in the mu-alpha (8-13 Hz) and lower beta (13-20 Hz) bands over the primary motor (M1) and somatosensory (S1) cortices. Source-level ERP and ERD/ERS analyses were conducted using eLORETA. Results revealed higher P100 amplitudes in motor and premotor channels for 'Neutral' compared with 'Fear'. Additionally, analysis of ERD/ERS showed increased beta band desynchronization in M1 for 'Neutral', and the opposite pattern in S1. Source-level estimation showed significant differences between conditions mainly observed in the beta band over sensorimotor areas. These findings provide high-temporal resolution evidence suggesting that seeing fearful EBL induces early activation of somatosensory areas, which in turn could suppress M1 activity. These findings highlight early dynamics within the observer's sensorimotor system and hint at a sensorimotor mechanism supporting freezing during the processing of EBL.

Changes in EEG alpha-band power during prehension indicates neural motor drive inhibition

Changes in alpha band activity (8-12 Hz) indicate the downregulation of brain regions during cognitive tasks, reflecting real-time cognitive load. Despite this, its feasibility to be used in a more dynamic environment with ongoing motor corrections has not been studied. This research used electroencephalography (EEG) to explore how different brain regions are engaged during a simple grasp and lift task where unexpected changes to the object's weight or surface friction are introduced. The results suggest that alpha activity changes related to motor error correction occur only in motor-related areas (i.e. central areas) but not in error processing areas (i.e., frontoparietal network) during unexpected weight changes. This suggests that oscillations over motor areas reflect the reduction of motor drive related to motor error correction, thus, being a potential cortical electrophysiological biomarker for the process and not solely as a proxy for cognitive demands. This observation is particularly relevant in scenarios where these signals are used to evaluate high cognitive demands co-occurring with high levels of motor errors and corrections, such as prosthesis use. The establishment of electrophysiological biomarkers of mental resource allocation during movement and cognition can help identify indicators of mental workload and motor drive, which may be useful for improving brain-machine interfaces.NEW & NOTEWORTHY We demonstrated that alpha suppression, an EEG phenomenon with high temporal resolution, occurs over the primary sensorimotor area during error correction during lift movements. Interpretations of alpha activity are often attributed to high cognitive demands, thus recognizing that it is also influenced by motor processes is important in situations where cognitive demands are paired with movement errors. This could further have application as a biomarker for error correction in human-machine interfaces, such as neuroprostheses.

Predictability alters information flow during action observation in human electrocorticographic activity

The action observation network (AON) has been extensively studied using short, isolated motor acts. How activity in the network is altered when these isolated acts are embedded in meaningful sequences of actions remains poorly understood. Here we utilized intracranial electrocorticography to characterize how the exchange of information across key nodes of the AON-the precentral, supramarginal, and visual cortices-is affected by such embedding and the resulting predictability. We found more top-down beta oscillation from precentral to supramarginal contacts during the observation of predictable actions in meaningful sequences compared to the same actions in randomized, and hence less predictable, order. In addition, we find that expectations enabled by the embedding lead to a suppression of bottom-up visual responses in the high-gamma range in visual areas. These results, in line with predictive coding, inform how nodes of the AON integrate information to process the actions of others.

Neural oscillations reveal disrupted functional connectivity associated with impaired speech auditory feedback control in post-stroke aphasia

The oscillatory brain activities reflect neuro-computational processes that are critical for speech production and sensorimotor control. In the present study, we used neural oscillations in left-hemisphere stroke survivors with aphasia as a model to investigate network-level functional connectivity deficits associated with disrupted speech auditory feedback control. Electroencephalography signals were recorded from 40 post-stroke aphasia and 39 neurologically intact control participants while they performed speech vowel production and listening tasks under pitch-shifted altered auditory feedback (AAF) conditions. Using weighted phase-lag index, we calculated broadband (1-70 Hz) functional neural connectivity between electrode pairs covering the frontal, pre- and post-central, and parietal regions. Results revealed reduced fronto-central delta and theta band and centro-parietal low-beta band connectivity in left-hemisphere electrodes associated with diminished speech AAF compensation responses in post-stroke aphasia compared with controls. Lesion-mapping analysis demonstrated that stroke-induced damage to multi-modal brain networks within the inferior frontal gyrus, Rolandic operculum, inferior parietal lobule, angular gyrus, and supramarginal gyrus predicted the reduced functional neural connectivity within the delta and low-beta bands during both tasks in aphasia. These results provide evidence that disrupted neural connectivity due to left-hemisphere brain damage can result in network-wide dysfunctions associated with impaired sensorimotor integration mechanisms for speech auditory feedback control.

Evaluation of abstract rule-based associations in the human premotor cortex during passive observation

Decision-making often manifests in behavior, typically yielding overt motor actions. This complex process requires the registration of sensory information with one's internal representation of the current context, before a categorical judgment of the most appropriate motor behavior can be issued. The construct concept of embodied decision-making encapsulates this sequence of complex processes, whereby behaviorally salient information from the environment is represented in an abstracted space of potential motor actions rather than only in an abstract cognitive "decision" space. Theoretical foundations and some empirical evidence account for support the involvement of premotor cortical circuits in embodied cognitive functions. Animal models show that premotor circuits participate in the registration and evaluation of actions performed by peers in social situations, that is, prior to controlling one's voluntary movements guided by arbitrary stimulus-response rules. However, such evidence from human data is currently limited. Here we used time-resolved magnetoencephalography imaging to characterize activations of the premotor cortex as human participants observed arbitrary, non-biological visual stimuli that either respected or violated a simple stimulus-response association rule. The participants had learned this rule previously, either actively, by performing a motor task (active learning), or passively, by observing a computer perform the same task (passive learning). We discovered that the human premotor cortex is activated during the passive observation of the correct execution of a sequence of events according to a rule learned previously. Premotor activation also differs when the subjects observe incorrect stimulus sequences. These premotor effects are present even when the observed events are of a non-motor, abstract nature, and even when the stimulus-response association rule was learned via passive observations of a computer agent performing the task, without requiring overt motor actions from the human participant. We found evidence of these phenomena by tracking cortical beta-band signaling in temporal alignment with the observation of task events and behavior. We conclude that premotor cortical circuits that are typically engaged during voluntary motor behavior are also involved in the interpretation of events of a non-ecological, unfamiliar nature but related to a learned abstract rule. As such, the present study provides the first evidence of neurophysiological processes of embodied decision-making in human premotor circuits when the observed events do not involve motor actions of a third party.

Aberrant modulation of broadband neural oscillations reflects vocal sensorimotor deficits in post-stroke aphasia

OBJECTIVE

The present study investigated the neural oscillatory correlates of impaired vocal sensorimotor control in left-hemisphere stroke.

METHODS

Electroencephalography (EEG) signals were recorded from 34 stroke and 46 control subjects during speech vowel vocalization and listening tasks under normal and pitch-shifted auditory feedback.

RESULTS

Time-frequency analyses revealed aberrantly decreased theta (4-8 Hz) and increased gamma band (30-80 Hz) power in frontal and posterior parieto-occipital regions as well as reduced alpha (8-13 Hz) and beta (13-30 Hz) desynchronization over sensorimotor areas before speech vowel vocalization in left-hemisphere stroke compared with controls. Subjects with the stroke also presented with aberrant modulation of broadband (4-80 Hz) neural oscillations over sensorimotor regions after speech vowel onset during vocalization and listening under normal and altered auditory feedback. We found that the atypical pattern of broadband neural oscillatory modulation was correlated with diminished vocal feedback error compensation behavior and the severity of co-existing language-related aphasia symptoms associated with left-hemisphere stroke.

CONCLUSIONS

These findings indicate complex interplays between the underlying mechanisms of speech and language and their deficits in post-stroke aphasia.

SIGNIFICANCE

Our data motivate the notion of studying neural oscillatory dynamics as a critical component for the examination of speech and language disorders in post-stroke aphasia.

Enhancing Visual-Guided Motor Imagery Performance via Sensory Threshold Somatosensory Electrical Stimulation Training

OBJECTIVE

Motor imagery (MI) based brain- computer interface (BCI) has been widely studied as an effective way to enhance motor learning and promote motor recovery. However, the accuracy of MI-BCI heavily depends on whether subjects can perform MI tasks correctly, which largely limits the general application of MI-BCI. To overcome this limitation, a training strategy based on the combination of MI and sensory threshold somatosensory electrical stimulation (MI+st-SES) is proposed in this study.

METHODS

Thirty healthy subjects were recruited and randomly divided into SES group and control group. Both groups performed left-hand and right-hand MI tasks in three consecutive blocks. The main difference between two groups lies in the second block, where subjects in SES group received the st-SES during MI tasks whereas the control group performed MI tasks only.

RESULTS

The results showed that the SES group had a significant improvement in event-related desynchronization (ERD) of alpha rhythm after the training session of MI+st-SES (left-hand: F(2,27) = 9.98, p<0.01; right-hand: F(2, 27) = 10.43, p<0.01). The classification accuracy between left- and right-hand MI in the SES group was also significantly improved following MI+st-SES training (F(2,27) = 6.46, p<0.01). In contrary, there was no significant difference between the first and third blocks in the control group (F(2,27) = 0.18, p = 0.84). The functional connectivity based on weighted pairwise phase consistency (wPPC) over the sensorimotor area also showed an increase after the MI+st-SES training.

CONCLUSION AND SIGNIFICANCE

Our findings indicate that training based on MI+st-SES is a promising way to foster MI performance and assist subjects in achieving efficient BCI control.

Combined EEG and immersive virtual reality unveil dopaminergic modulation of error monitoring in Parkinson's Disease

Detecting errors in your own and others' actions is associated with discrepancies between intended and expected outcomes. The processing of salient events is associated with dopamine release, the balance of which is altered in Parkinson's disease (PD). Errors in observed actions trigger various electrocortical indices (e.g. mid-frontal theta, error-related delta, and error positivity [oPe]). However, the impact of dopamine depletion to observed errors in the same individual remains unclear. Healthy controls (HCs) and PD patients observed ecological reach-to-grasp-a-glass actions performed by a virtual arm from a first-person perspective. PD patients were tested under their dopaminergic medication (on-condition) and after dopaminergic withdrawal (off-condition). Analyses of oPe, delta, and theta-power increases indicate that while the formers were elicited after incorrect vs. correct actions in all groups, the latter were observed in on-condition but altered in off-condition PD. Therefore, different EEG error signatures may index the activity of distinct mechanisms, and error-related theta power is selectively modulated by dopamine depletion. Our findings may facilitate discovering dopamine-related biomarkers for error-monitoring dysfunctions that may have crucial theoretical and clinical implications.

The Effects of Subthalamic Nucleus Deep Brain Stimulation and Retention Delay on Memory-Guided Reaching Performance in People with Parkinson's Disease

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN-DBS) improves intensive aspects of movement (velocity) in people with Parkinson's disease (PD) but impairs the more cognitively demanding coordinative aspects of movement (error). We extended these findings by evaluating STN-DBS induced changes in intensive and coordinative aspects of movement during a memory-guided reaching task with varying retention delays.

OBJECTIVE

We evaluated the effect of STN-DBS on motor control during a memory-guided reaching task with short and long retention delays in participants with PD and compared performance to healthy controls (HC).

METHODS

Eleven participants with PD completed the motor section of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) and performed a memory-guided reaching task under four different STN-DBS conditions (DBS-OFF, DBS-RIGHT, DBS-LEFT, and DBS-BOTH) and two retention delays (0.5 s and 5 s). An additional 13 HC completed the memory-guided reaching task.

RESULTS

Unilateral and bilateral STN-DBS improved the MDS-UPDRS III scores. In the memory-guided reaching task, both unilateral and bilateral STN-DBS increased the intensive aspects of movement (amplitude and velocity) in the direction toward HC but impaired coordinative aspects of movement (error) away from the HC. Furthermore, movement time was decreased but reaction time was unaffected by STN-DBS. Shorter retention delays increased amplitude and velocity, decreased movement times, and decreased error, but increased reaction times in the participants with PD. There were no interactions between STN-DBS condition and retention delay.

CONCLUSION

STN-DBS may affect cognitive-motor functioning by altering activity throughout cortico-basal ganglia networks and the oscillatory activity subserving them.

BCI-FES With Multimodal Feedback for Motor Recovery Poststroke

An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals-user-generated intent-to-move neural activity recorded from cerebral cortical motor areas-to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.

Impact of sport training on adaptations in neural functioning and behavioral performance: A scoping review with meta-analysis on EEG research

Background/objective

Investigating the neural mechanisms underlying sport performance has been a research focus in the field of sport science. The current review aims to identify distinct characteristics between athletes and non-athletes at behavioral and neural levels. Further analysis was conducted as to potential reasons that contributed to the differences.

Methods

Literature was searched through PubMed, ScienceDirect, Cochrane, EBSCO, and Web of Science for EEG studies that compared athletes with non-athletes or novices in behavioral performance and brain function.

Results

The process of literature search and selection identified 16 studies that satisfied the predetermined inclusion criteria. Theta, alpha, and beta frequency bands were employed as the primary EEG measures of cortical activities in the included studies. Athletes indicated significant advantages over controls in behavioral performance, Hedges′g=0.42,p=0.02, and brain function, Hedges′g=0.49,p=0.03. Moderator analysis on behavioral performance indicated a large effect size in sport-related performance, Hedges′g=0.90,p=0.01, but a small, non-significant effect size in general tasks, Hedges′g=0.14,p=0.44.

Conclusions

Superior performance in sport-related tasks mostly contributed to athletes’ significant advantage in behavioral performance. Additionally, favorable profiles of brain function associated with athletes included neural efficiency, increased cortical asymmetry, greater cognitive flexibility, and precise timing of cortical activation. Applying EEG technique to sport has shown promising directions in performance improvement and talent identification for young athletes.

Motivated for movement: Beta activation over the motor cortex resulting from intrinsic and extrinsic motivators

Past work on motivation has primarily studied dichotomous distinctions of motivation (e.g., extrinsic or intrinsic). However, focusing on the overall motivational intensity may be better at accentuating the unique differences within and between varying motivators as it pertains to the impetus to act. Specifically, motivational intensity influences neural patterns of beta band frequency (13-30 Hz) as measured by electroencephalography (EEG) that enable motor-action preparation, a neural correlate of motivated movement. The primary aim of across three experiments was to investigate neural motor-action preparation to modified flanker tasks within achievement (Experiment 1), autonomous (Experiment 2), and extrinsic vs. intrinsic (Experiment 3) motivational contexts. Experiment 1 revealed greater motor-action preparation for challenging trial cues and did not differ in behavioral attentional and performance measures across both trial types. Experiment 2 revealed no significant difference in motor-action preparation, did not differ in behavioral attentional narrowing and had worse behavioral performance in high autonomy relative to low autonomy trials. Experiment 3 revealed greater motor-action preparation for challenging trial cues, did not differ in behavioral attentional narrowing and had a faster performance for reward trials relative to high autonomy trials. These findings suggest motivators of the same category (i.e., intrinsic) may differ in motivational strength, as suggested by a neurophysiological measure of immediate motivated movement planning.

Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks

Cortical neural networks exhibit high internal variability in spontaneous dynamic activities and they can robustly and reliably respond to external stimuli with multilevel features–from microscopic irregular spiking of neurons to macroscopic oscillatory local field potential. A comprehensive study integrating these multilevel features in spontaneous and stimulus–evoked dynamics with seemingly distinct mechanisms is still lacking. Here, we study the stimulus–response dynamics of biologically plausible excitation–inhibition (E–I) balanced networks. We confirm that networks around critical synchronous transition states can maintain strong internal variability but are sensitive to external stimuli. In this dynamical region, applying a stimulus to the network can reduce the trial-to-trial variability and shift the network oscillatory frequency while preserving the dynamical criticality. These multilevel features widely observed in different experiments cannot simultaneously occur in non-critical dynamical states. Furthermore, the dynamical mechanisms underlying these multilevel features are revealed using a semi-analytical mean-field theory that derives the macroscopic network field equations from the microscopic neuronal networks, enabling the analysis by nonlinear dynamics theory and linear noise approximation. The generic dynamical principle revealed here contributes to a more integrative understanding of neural systems and brain functions and incorporates multimodal and multilevel experimental observations. The E–I balanced neural network in combination with the effective mean-field theory can serve as a mechanistic modeling framework to study the multilevel neural dynamics underlying neural information and cognitive processes.

The complexity and variability of brain dynamical activity range from neuronal spiking and neural avalanches to oscillatory local field potentials of local neural circuits in both spontaneous and stimulus-evoked states. Such multilevel variable brain dynamics are functionally and behaviorally relevant and are principal components of the underlying circuit organization. To more comprehensively clarify their neural mechanisms, we use a bottom-up approach to study the stimulus–response dynamics of neural circuits. Our model assumes the following key biologically plausible components: excitation–inhibition (E–I) neuronal interaction and chemical synaptic coupling. We show that the circuits with E–I balance have a special dynamic sub-region, the critical region. Circuits around this region could account for the emergence of multilevel brain response patterns, both ongoing and stimulus-induced, observed in different experiments, including the reduction of trial-to-trial variability, effective modulation of gamma frequency, and preservation of criticality in the presence of a stimulus. We further analyze the corresponding nonlinear dynamical principles using a novel and highly generalizable semi-analytical mean-field theory. Our computational and theoretical studies explain the cross-level brain dynamical organization of spontaneous and evoked states in a more integrative manner.

Action Intentions, Predictive Processing, and Mind Reading: Turning Goalkeepers Into Penalty Killers

The key to action control is one’s ability to adequately predict the consequences of one’s actions. Predictive processing theories assume that forward models enable rapid “preplay” to assess the match between predicted and intended action effects. Here we propose the novel hypothesis that “reading” another’s action intentions requires a rich forward model of that agent’s action. Such a forward model can be obtained and enriched through learning by either practice or simulation. Based on this notion, we ran a series of studies on soccer goalkeepers and novices, who predicted the intended direction of penalties being kicked at them in a computerized penalty-reading task. In line with hypotheses, extensive practice in penalty kicking improved performance in penalty reading among goalkeepers who had extensive prior experience in penalty blocking but not in penalty kicking. A robust benefit in penalty reading did not result from practice in kinesthetic motor imagery of penalty kicking in novice participants. To test whether goalkeepers actually use such penalty-kicking imagery in penalty reading, we trained a machine-learning classifier on multivariate fMRI activity patterns to distinguish motor-imagery-related from attention-related strategies during a penalty-imagery training task. We then applied that classifier to fMRI data related to a separate penalty-reading task and showed that 2/3 of all correctly read penalty kicks were classified as engaging the motor-imagery circuit rather than merely the attention circuit. This study provides initial evidence that, in order to read our opponent’s action intention, it helps to observe their action kinematics, and use our own forward model to predict the sensory consequences of “our” penalty kick if we were to produce these action kinematics ourselves. In sum, it takes practice as a penalty kicker to become a penalty killer.

A brief review of motor imagery and bimanual coordination

Motor imagery is increasingly being used in clinical settings, such as in neurorehabilitation and brain computer interface (BCI). In stroke, patients lose upper limb function and must re-learn bimanual coordination skills necessary for the activities of daily living. Physiotherapists integrate motor imagery with physical rehabilitation to accelerate recovery. In BCIs, users are often asked to imagine a movement, often with sparse instructions. The EEG pattern that coincides with this cognitive task is captured, then used to execute an external command, such as operating a neuroprosthetic device. As such, BCIs are dependent on the efficient and reliable interpretation of motor imagery. While motor imagery improves patient outcome and informs BCI research, the cognitive and neurophysiological mechanisms which underlie it are not clear. Certain types of motor imagery techniques are more effective than others. For instance, focusing on kinesthetic cues and adopting a first-person perspective are more effective than focusing on visual cues and adopting a third-person perspective. As motor imagery becomes more dominant in neurorehabilitation and BCIs, it is important to elucidate what makes these techniques effective. The purpose of this review is to examine the research to date that focuses on both motor imagery and bimanual coordination. An assessment of current research on these two themes may serve as a useful platform for scientists and clinicians seeking to use motor imagery to help improve bimanual coordination, either through augmenting physical therapy or developing more effective BCIs.

High-gamma mirror activity patterns in the human brain during reach-to-grasp movement observation, retention, and execution-An MEG study

While the existence of a human mirror neuron system is evident, the involved brain areas and their exact functional roles remain under scientific debate. A number of functionally different mirror neuron types, neurons that selectively respond to specific grasp phases and types for example, have been reported with single cell recordings in monkeys. In humans, spatially limited, intracranially recorded electrophysiological signals in the high-gamma (HG) range have been used to investigate the human mirror system, as they are associated with spiking activity in single neurons. Our goal here is to complement previous intracranial HG studies by using magnetoencephalography to record HG activity simultaneously from the whole head. Participants performed a natural reach-to-grasp movement observation and delayed imitation task with different everyday objects and grasp types. This allowed us to characterize the spatial organization of cortical areas that show HG-activation modulation during movement observation (mirroring), retention (mnemonic mirroring), and execution (motor control). Our results show mirroring related HG modulation patterns over bilateral occipito-parietal as well as sensorimotor areas. In addition, we found mnemonic mirroring related HG modulation over contra-lateral fronto-temporal areas. These results provide a foundation for further human mirror system research as well as possible target areas for brain-computer interface and neurorehabilitation approaches.

Altered Modulation of the Movement-Related Beta Desynchronization with Force in Stroke - a Pilot Study

Conventional therapy improves motor recovery after stroke. However, 50% of stroke survivors still suffer from a significant level of long-term upper extremity impairment. Identifying a specific biomarker whose magnitude scales with the level of force could help in the development of more effective, novel, highly targeted rehabilitation therapies such as brain stimulation or neurofeedback. Four chronic stroke participants were enrolled in this pilot study to find such a neural marker using an Independent Component Analysis (ICA)-based source analysis approach, and investigate how it has been affected by the injury. Beta band desynchronization in the ipsilesional primary motor cortex was found to be most robustly scaling with force. This activity modulation with force was found to be significantly reduced, and to plateau at higher force than that of the contralesional (unaffected) side. A rehabilitation therapy that would target such a neuromarker could have the potential to strengthen the brain-to-muscle drive and improve motor learning and recovery.Clinical Relevance- This study identifies a neural marker that scales with motor output and shows how this modulation has been affected by stroke.

Classifying subclinical depression using EEG spectral and connectivity measures

Detecting depression on its early stages helps preventing the onset of severe depressive episodes. In this study, we propose an automatic classification pipeline to detect subclinical depression (i.e., dysphoria) through the electroencephalography (EEG) signal. To this aim, we recorded the EEG signals in resting condition from 26 female participants with dysphoria and 38 female controls. The EEG signals were processed to extract several spectral and functional connectivity features to feed a nonlinear Support Vector Machine (SVM) classifier embedded with a Recursive Feature Elimination (RFE) algorithm. Our recognition pipeline obtained a maximum classification accuracy of 83.91% in recognizing dysphoria patients with a combination of connectivity and spectral measures. Moreover, an accuracy of 76.11% was achieved with only the 4 most informative functional connections, suggesting a central role of cortical connectivity in the theta band for early depression recognition. The present study can facilitate the diagnosis of subclinical conditions of depression and may provide reliable indicators of depression for the clinical community.

Motor Preparation and Execution for Performance Difficulty: Centroparietal Beta Activation during the Effort Expenditure for Rewards Task as a Function of Motivation

Debate exists as to the effects of anxiety in performance-based studies. However, no studies have examined the influence of motivation both in preparation of a motor movement and during movement performance. The present study measured beta activation in preparation for and during execution of the effort expenditure for rewards task (EEfRT), a button-pressing task consisting of easy and hard trials. Results indicated that motor preparation (i.e., reduced beta activation) was greater in preparation for hard trials than for easy trials. Additionally, motor preparation decreased (i.e., beta activation increased) over the course of hard trial execution. These results suggest that motor preparation is enhanced prior to more challenging tasks but that motor preparation declines as participants become closer to completing their goal in each challenging trial. These results provide insight into how beta activation facilitates effort expenditure for motor tasks varying in difficulty and motivation. The impact of these results on models of anxiety and performance is discussed.

20 Hz Transcranial Alternating Current Stimulation Inhibits Observation-Execution-Related Motor Cortex Excitability

The present study aimed to investigate the effect of transcranial alternating current stimulation (tACS) on the primary motor cortex (M1) during action observation, and subsequent action execution, on motor cortex excitability. The participants received tACS at 10 Hz or 20 Hz, or a sham stimulation over the left M1 for 10 min while they observed a video displaying a repeated button-tapping task using the right hand, and then performed an identical task with their right hand. Motor-evoked potential (MEP) amplitudes were measured before (T0) and after the action observation paired with tACS or a sham stimulation (T1), and after the performance of the action (T2). The results showed that MEPs were significantly reduced at time point T1 (p = 0.042, Cohen’s d = 0.611) and T2 (p = 0.0003, Cohen’s d = 0.852) in the 20 Hz tACS condition, in contrast with the sham stimulation. There was a significantly smaller MEP amplitude at time point T2 in the 20 Hz tACS condition, as compared to the 10 Hz tACS condition (p = 0.01, Cohen’s d = 0.622), but the MEP amplitude did not significantly change at time point T1 between the 20 Hz and 10 Hz tACS conditions (p = 0.136, Cohen’s d = 0.536). There were no significant differences at time point T1 and T2 between the 10 Hz tACS condition and the sham stimulation. We conclude that 20 Hz tACS during action observation inhibited motor cortex excitability and subsequently inhibited execution-related motor cortex excitability. The effects of tACS on task-related motor cortex excitability are frequency-dependent.

Associations of Hyperactivity and Inattention Scores with Theta and Beta Oscillatory Dynamics of EEG in Stop-Signal Task in Healthy Children 7-10 Years Old

Simple Summary

Most studies on ADHD have been focused on the comparisons between healthy subjects and clinical patients. The dimensional approaches propose that the main pathological behavioral domains are distributed in the normal population and not only in individual categories of people (as assumed in traditional schemes of comparisons between patients and controls). In the current study, we used a similar approach to identify potential markers of ADHD by studying the EEG dynamics of healthy children with a natural variability in hyperactivity and inattention scores during performance of the Stop-Signal task. We found that hyperactivity/inattention scores were positively associated with RT variability. Hyperactivity/inattention scores were negatively associated with an increase in beta spectral power in the first 200 ms and positively associated with an increase in theta rhythm at about 300 ms after presentation of the Go stimulus. It has been hypothesized that such results imply insufficient vigilance in the early stages of perception and subsequent compensatory enhancing of attention to the stimulus in children with higher hyperactivity and inattention scores.

Abstract

In the current study, we aimed to investigate the associations between the natural variability in hyperactivity and inattention scores, as well as their combination with EEG oscillatory responses in the Stop-Signal task in a sample of healthy children. During performance, the Stop-Signal task EEGs were recorded in 94 Caucasian children (40 girls) from 7 to 10 years. Hyperactivity/inattention and inattention scores positively correlated with RT variability. Hyperactivity/inattention and inattention scores negatively correlated with an increase in beta spectral power in the first 200 ms after presentation of the Go stimulus. Such results are in line with the lack of arousal model in ADHD children and can be associated with less sensory arousal in the early stages of perception in children with symptoms of inattention. The subsequent greater increase in theta rhythm at about 300 ms after presentation of the Go stimulus in children with higher inattention scores may be associated with increased attention processes and compensation for insufficient vigilance in the early stages of perception.

Neural correlates of speech and limb motor timing deficits revealed by aberrant beta band desynchronization in Parkinson's disease

OBJECTIVE

We used a classical motor reaction time paradigm to examine the effects of Parkinson's disease (PD) on the mechanisms of speech production and upper limb movement.

METHODS

Electro-encephalography (EEG) signals were recorded in PD and control groups during speech vowel production and button press tasks in response to temporally predictable and unpredictable visual stimuli.

RESULTS

Motor reaction times were slower in PD vs. control group independent of stimulus timing and movement modality. This effect was accompanied by stronger desynchronizations of low beta (13-18 Hz) and high beta (18-25 Hz) band neural oscillations in PD vs. control prior to the onset of speech and hand movement. In addition, pre-movement desynchronization of beta band oscillations were correlated with motor reaction time in control subjects with faster responses associated with weaker beta band desynchronizations during the planning phase of movement. However, no such effect was found in the PD group.

CONCLUSIONS

We suggest that the aberrant pattern of beta band desynchronization is a neural correlate of speech and upper limb motor timing deficits as a result of cortico-striatal pathology in PD.

SIGNIFICANCE

These findings motivate interventions targeted toward normalizing beta band activities for improving speech and upper limb movement timing in PD.

Sensorimotor contributions to working memory differ between the discrimination of Same and Different syllable pairs

Sensorimotor activity during speech perception is both pervasive and highly variable, changing as a function of the cognitive demands imposed by the task. The purpose of the current study was to evaluate whether the discrimination of Same (matched) and Different (unmatched) syllable pairs elicit different patterns of sensorimotor activity as stimuli are processed in working memory. Raw EEG data recorded from 42 participants were decomposed with independent component analysis to identify bilateral sensorimotor mu rhythms from 36 subjects. Time frequency decomposition of mu rhythms revealed concurrent event related desynchronization (ERD) in alpha and beta frequency bands across the peri- and post-stimulus time periods, which were interpreted as evidence of sensorimotor contributions to working memory encoding and maintenance. Left hemisphere alpha/beta ERD was stronger in Different trials than Same trials during the post-stimulus period, while right hemisphere alpha/beta ERD was stronger in Same trials than Different trials. A between-hemispheres contrast revealed no differences during Same trials, while post-stimulus alpha/beta ERD was stronger in the left hemisphere than the right during Different trials. Results were interpreted to suggest that predictive coding mechanisms lead to repetition suppression effects in Same trials. Mismatches arising from predictive coding mechanisms in Different trials shift subsequent working memory processing to the speech-dominant left hemisphere. Findings clarify how sensorimotor activity differentially supports working memory encoding and maintenance stages during speech discrimination tasks and have potential to inform sensorimotor models of speech perception and working memory.

Oscillatory Activity in Mouse Lemur Primary Motor Cortex During Natural Locomotor Behavior

In arboreal environments, substrate orientation determines the biomechanical strategy for postural maintenance and locomotion. In this study, we investigated possible neuronal correlates of these mechanisms in an ancestral primate model, the gray mouse lemur. We conducted telemetric recordings of electrocorticographic activity in left primary motor cortex of two mouse lemurs moving on a branch-like small-diameter pole, fixed horizontally, or vertically. Analysis of cortical oscillations in high β (25–35 Hz) and low γ (35–50 Hz) bands showed stronger resting power on horizontal than vertical substrate, potentially illustrating sensorimotor processes for postural maintenance. Locomotion on horizontal substrate was associated with stronger event-related desynchronization than vertical substrate, which could relate to locomotor adjustments and/or derive from differences in baseline activity. Spectrograms of cortical activity showed modulation throughout individual locomotor cycles, with higher values in the first than second half cycle. However, substrate orientation did not significantly influence these variations. Overall, these results confirm that specific cortical mechanisms are solicited during arboreal locomotion, whereby mouse lemurs adjust cortical activity to substrate orientation during static posture and locomotion, and modulate this activity throughout locomotor cycles.

Accurate Offline Asynchronous Detection of Individual Finger Movement From Intracranial Brain Signals Using a Novel Multiway Approach

Asynchronous motor Brain Computer Interfacing (BCI) is characterized by the continuous decoding of intended muscular activity from brain signals. Such applications have gained widespread interest for enabling users to issue commands volitionally. In conventional motor BCIs features extracted from brain signals are concatenated into vector- or matrix-based (or one-/two-way) representations. Nevertheless, when accounting for the original multimodal or multiway signal structure, decoding performance has been shown to improve jointly with result interpretability. However, as multiway decoders are notorious for the extensive computational cost to train them, conventional ones are still preferred. To curb this limitation, we introduce a novel multiway classifier, called Block-Term Tensor Classifier that inherits the improved accuracy of multiway methods while providing fast training. We show that it can outperform state-of-the-art multiway and two-way Linear Discriminant Analysis classifiers in asynchronous detection of individual finger movements from intracranial recordings, an essential feature to achieve a sense of dexterity with hand prosthetics and exoskeletons.

Movement-related changes in pallidocortical synchrony differentiate action execution and observation in humans

OBJECTIVE

Suppression of local and network alpha and beta oscillations in the human basal ganglia-thalamocortical (BGTC) circuit is a prominent feature of movement, including suppression of local alpha/beta power, cross-region beta phase coupling, and cortical and subcortical phase-amplitude coupling (PAC). We hypothesized that network-level coupling is more directly related to movement execution than local power changes, given the role of pathological network hypersynchrony in movement disorders such as Parkinson disease (PD). Understanding the specificity of these movement-related signals is important for designing novel therapeutics.

METHODS

We recorded globus pallidus internus (GPi) and motor cortical local field potentials during movement execution, passive movement observation and rest in 12 patients with PD undergoing deep brain stimulator implantation.

RESULTS

Local alpha/beta power is suppressed in the globus pallidus and motor cortex during both action execution and action observation, although less so during action observation. In contrast, pallidocortical phase synchrony and GPi and motor cortical alpha/beta-gamma PAC are suppressed only during action execution.

CONCLUSIONS

The functional dissociation across tasks in pallidocortical network activity suggests a particularly important role of network coupling in motor execution.

SIGNIFICANCE

Network level recordings provide important specificity in differentiating motor behavior and may provide significant value for future closed loop therapies.

Individual differences in motivation and impulsivity link resting frontal alpha asymmetry and motor beta activation

Previous research has linked neural correlates with motivational traits and measures of impulsivity. However, few previous studies have investigated whether individual differences in motivation and impulsivity moderate the relationship between these disparate neural activity patterns. In a sample of 118 young adults, we used Electroencephalography (EEG) to examine whether behavioral activation and inhibition systems (BIS/BAS) and impulsivity facets (negative urgency, lack of perseverance), moderate the relationship between beta power and resting frontal alpha asymmetry. Regression analyses revealed a novel relationship between lesser beta power and greater left frontal alpha asymmetry (LFA). Moderation analyses suggest this relationship may strengthen as BIS/BAS levels increase, and trait impulsivity levels decrease from the mean. These results are among the first revealing a relationship between two widely investigated neural activity patterns of motivation and provide some indication individual differences moderate this relationship. The limitations of these findings and need for future research are discussed.

Movement-induced hypoalgesia: behavioral characteristics and neural mechanisms

Pain is essential for our survival because it helps to protect us from severe injuries. Nociceptive signals may be exacerbated by continued physical activities but can also be interrupted or overridden by physical movements, a process called movement-induced hypoalgesia. Several neural mechanisms have been proposed to account for this effect, including the reafference principle, non-nociceptive interference, and top-down descending modulation. Given that the hypoalgesic effects of these mechanisms temporally overlap during movement execution, it is unclear whether movement-induced hypoalgesia results from a single neural mechanism or from the joint action of multiple neural mechanisms. To address this question, we conducted five experiments on 129 healthy humans by assessing the hypoalgesic effect after movement execution. Combining psychophysics and electroencephalographic recordings, we quantified the relationship between the strength of voluntary movement and the hypoalgesic effect, as well as the temporal and spatial characteristics of the hypoalgesic effect. Our findings demonstrated that movement-induced hypoalgesia results from the joint action of multiple neural mechanisms. This investigation is the first to disentangle the distinct contributions of different neural mechanisms to the hypoalgesic effect of voluntary movement, which extends our understanding of sensory attenuation arising from voluntary movement and may prove instrumental in developing new strategies for pain management.

Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

BACKGROUND

The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown.

METHODS

32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence.

RESULTS

While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally.

LIMITATIONS

All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas.

CONCLUSIONS

An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression.

EEG Correlates of Central Origin of Cancer-Related Fatigue

The neurophysiological mechanism of cancer-related fatigue (CRF) remains poorly understood. EEG was examined during a sustained submaximal contraction (SC) task to further understand our prior research findings of greater central contribution to early fatigue during SC in CRF. Advanced cancer patients and matched healthy controls performed an elbow flexor SC until task failure while undergoing neuromuscular testing and EEG recording. EEG power changes over left and right sensorimotor cortices were analyzed and correlated with brief fatigue inventory (BFI) score and evoked muscle force, a measure of central fatigue. Brain electrical activity changes during the SC differed in CRF from healthy subjects mainly in the theta (4-8 Hz) and beta (12-30 Hz) bands in the contralateral (to the fatigued limb) hemisphere; changes were correlated with the evoked force. Also, the gamma band (30-50 Hz) power decrease during the SC did not return to baseline after 2 min of rest in CRF, an effect correlated with BFI score. In conclusion, altered brain electrical activity during a fatigue task in patients is associated with central fatigue during SC or fatigue symptoms, suggesting its potential contribution to CRF during motor performance. This information should guide the development and use of rehabilitative interventions that target the central nervous system to maximize function recovery.

Using Data Assimilation for Quantitative Electroencephalography Analysis

We propose a method based on the ensemble Kalman filter (EnKF) together with quantitative electroencephalogram (QEEG) coherence and power spectrum analysis for evaluating changes in brain activity associated with cognitive processes. Such analysis framework has been widely used in the context of data assimilation (DA) in areas such as geosciences, meteorology, and aerospace. However, the use of this approach is less common in neurosciences. In our case, EnKF highlights the spectral contribution of brain signals that are more likely (according to their coherence analysis) to be related to the cognitive process of interest. The power enhancement, due to the cognitive activity, is later validated in the power spectrum analysis by comparing through statistical tests relevant frequency content in two datasets in which assessing the development of cognitive abilities is of interest: the process of getting concentrated and of learning a new skill. Our results show that our DA-based methodology can highlight important frequency characteristics of the electroencephalogram (EEG) data that have been related to different cognitive processes. Hence, our proposal has the potential to understand of neurocognitive phenomena that is tracked through QEEG.

Brain connectivity in patients with dystonia during motor tasks

OBJECTIVE

This study aims to investigate alterations of brain connectivity using multivariate electroencephalographic data to provide new insights of the brain connectivity dynamics of dystonia.

APPROACH

We recorded electroencephalography (EEG) of patients with right upper limb idiopathic focal dystonia and paired controls during resting state, writing-from-memory, and finger-tapping tasks. We applied power spectrum analyses considering the mu, beta and gamma rhythms of the motor cortex and analyzed brain connectivity networks and microstates (MS).

MAIN RESULTS

The power spectra results showed that patients had a loss of desynchronization of the beta rhythm during the writing task. We observed differences in the structure of the connective core in beta rhythm, as well as, in the intensity of the patient's hubs observed with basis in path length measures in mu and beta rhythms. Abnormalities were also identified in MS of default mode networks of patients associated with its performances during motor tasks.

SIGNIFICANCE

The EEG connectivity analyses provided interesting insights about the cortical electrophysiological patterns in dystonia, such as loss of event-related desynchronization, changes in the effective connectivity with similar signature to other neurological diseases, indications of alterations in the default-mode-network. Our findings are consistent with previously described connectivity abnormalities in neuroimaging studies confirming that dystonia is a network disorder.

Spectral Power in Marmoset Frontal Motor Cortex during Natural Locomotor Behavior

During primate arboreal locomotion, substrate orientation modifies body axis orientation and biomechanical contribution of fore- and hindlimbs. To characterize the role of cortical oscillations in integrating these locomotor demands, we recorded electrocorticographic activity from left dorsal premotor, primary motor, and supplementary motor cortices of three common marmosets moving across a branch-like small-diameter pole, fixed horizontally or vertically. Animals displayed behavioral adjustments to the task, namely, the horizontal condition mainly induced quadrupedal walk with pronated/neutral forelimb postures, whereas the vertical condition induced walk and bound gaits with supinated/neutral postures. Examination of cortical activity suggests that β (16–35 Hz) and γ (75–100 Hz) oscillations could reflect different processes in locomotor adjustments. During task, modulation of γ ERS by substrate orientation (horizontal/vertical) and epoch (preparation/execution) suggests close tuning to movement dynamics and biomechanical demands. β ERD was essentially modulated by gait (walk/bound), which could illustrate contribution to movement sequence and coordination. At rest, modulation of β power by substrate orientation underlines its role in sensorimotor processes for postural maintenance.

Compromised Behavior and Gamma Power During Working Memory in Cognitively Healthy Individuals With Abnormal CSF Amyloid/Tau

Research shows that gamma activity changes in Alzheimer’s disease (AD), revealing synaptic pathology and potential therapeutic applications. We aim to explore whether cognitive challenge combined with quantitative EEG (qEEG) can unmask abnormal gamma frequency power in healthy individuals at high risk of developing AD. We analyzed low (30–50 Hz) and high gamma (50–80 Hz) power over six brain regions at EEG sensor level (frontal/central/parietal/left temporal/right temporal/occipital) in a dataset collected from an aging cohort during N-back working memory (WM) testing at two different load conditions (N = 0 or 2). Cognitively healthy (CH) study participants (≥60 years old) of both sexes were divided into two subgroups: normal amyloid/tau ratios (CH-NAT, n = 10) or pathological amyloid/tau (CH-PAT, n = 14) in cerebrospinal fluid (CSF). During low load (0-back) challenge, low gamma is higher in CH-PATs than CH-NATs over frontal and central regions (p = 0.014∼0.032, effect size (Cohen’s d) = 0.95∼1.11). However, during high load (2-back) challenge, low gamma is lower in CH-PATs compared to CH-NATs over the left temporal region (p = 0.045, Cohen’s d = −0.96), and high gamma is lower over the parietal region (p = 0.035, Cohen’s d = −1.02). Overall, our studies show a medium to large negative effect size across the scalp (Cohen’s d = −0.51∼−1.02). In addition, low gamma during 2-back is positively correlated with 0-back accuracy over all regions except the occipital region only in CH-NATs (r = 0.69∼0.77, p = 0.0098∼0.027); high gamma during 2-back correlated positively with 0-back accuracy over all regions in CH-NATs (r = 0.68∼0.78, p = 0.007∼0.030); high gamma during 2-back negatively correlated with 0-back response time over parietal, right temporal, and occipital regions in CH-NATs (r = −0.70∼−0.66, p = 0.025∼0.037). We interpret these preliminary results to show: (1) gamma power is compromised in AD-biomarker positive individuals, who are otherwise cognitively healthy (CH-PATs); (2) gamma is associated with WM performance in normal aging (CH-NATs) (most significantly in the frontoparietal region). Our pilot findings encourage further investigations in combining cognitive challenges and qEEG in developing neurophysiology-based markers for identifying individuals in the prodromal stage, to help improving our understanding of AD pathophysiology and the contributions of low- and high-frequency gamma oscillations in cognitive functions.

EEG Changes in Time and Time-Frequency Domain During Movement Preparation and Execution in Stroke Patients

This study investigated electroencephalogram (EEG) changes during movement preparation and execution in stroke patients. EEG-based event-related potential (ERP) technology was used to measure brain activity changes. Seventeen stroke patients participated in this study and completed ERP tests that were designed to measure EEG changes during unilateral upper limb movements in preparation and execution stages, with Instruction Response Movement (IRM) and Cued Instruction Response Movement (CIRM) paradigms. EEG data were analyzed using motor potential (MP) in the time domain and the mu-rhythm and beta frequency band response mean value (R-means) in the time-frequency domain. In IRM, the MP amplitude at Cz was higher during hemiplegic arm movement than during unaffected arm movement. MP latency was shorter at Cz and the contralesional motor cortex during hemiplegic arm movement in CIRM compared to IRM. No significant differences were found in R-means among locations, between movement sides in both ERP tests. This study presents the brain activity changes in the time and time-frequency domains in stroke patients during movement preparation and execution and supports the contralesional compensation and adjacent-region compensation mechanism of post-stroke brain reconstruction. These findings may contribute to future rehabilitation research about neuroplasticity and technology development such as the brain-computer interface.

Representing Multiple Observed Actions in the Motor System

There is now converging evidence that others' actions are represented in the motor system. However, social cognition requires us to represent not only the actions but also the interactions of others. To do so, it is imperative that the motor system can represent multiple observed actions. The current fMRI study investigated whether this is possible by measuring brain activity from 29 participants while they observed 2 right hands performing sign language gestures. Three key results were obtained. First, brain activity in the premotor and parietal motor cortex was stronger when 2 hands performed 2 different gestures than when 1 hand performed a single gesture. Second, both individual observed gestures could be decoded from brain activity in the same 2 regions. Third, observing 2 different gestures compared with 2 identical gestures activated brain areas related to motor conflict, and this activity was correlated with parietal motor activity. Together, these results show that the motor system is able to represent multiple observed actions, and as such reveal a potential mechanism by which third-party social encounters could be processed in the brain.

Event-related desynchronization of alpha and beta band neural oscillations predicts speech and limb motor timing deficits in normal aging

Normal aging is associated with decline of motor timing mechanisms implicated in planning and execution of movement. Evidence from previous studies has highlighted the relationship between neural oscillatory activities and motor timing processing in neurotypical younger adults; however, it remains unclear how normal aging affects the underlying neural mechanisms of movement in older populations. In the present study, we recorded EEG activities in two groups of younger and older adults while they performed randomized speech and limb motor reaction time tasks cued by temporally predictable and unpredictable sensory stimuli. Our data showed that older adults were significantly slower than their younger counterparts during speech production and limb movement, especially in response to temporally unpredictable sensory stimuli. This behavioral effect was accompanied by significant desynchronization of alpha (7-12 Hz) and beta (13-25 Hz) band neural oscillatory activities in older compared with younger adults, primarily during the preparatory pre-motor phase of responses for speech production and limb movement. In addition, we found that faster motor reaction times in younger adults were significantly correlated with weaker desynchronization of pre-motor alpha and beta band neural activities irrespective of stimulus timing and response modality. However, the pre-motor components of alpha and beta activities were timing-specific in older adults and were more strongly desynchronized in response to temporally predictable sensory stimuli. These findings highlight the role of alpha and beta band neural oscillations in motor timing processing mechanisms and reflect their functional deficits during the planning phase of speech production and limb movement in normal aging.

Modulating dream experience: Noninvasive brain stimulation over the sensorimotor cortex reduces dream movement

Recently, cortical correlates of specific dream contents have been reported, such as the activation of the sensorimotor cortex during dreamed hand clenching. Yet, despite a close resemblance of such activation patterns to those seen during the corresponding wakeful behaviour, the causal mechanisms underlying specific dream contents remain largely elusive. Here, we aimed to investigate the causal role of the sensorimotor cortex in generating movement and bodily sensations during REM sleep dreaming. Following bihemispheric transcranial direct current stimulation (tDCS) or sham stimulation, guided by functional mapping of the primary motor cortex, naive participants were awakened from REM sleep and responded to a questionnaire on bodily sensations in dreams. Electromyographic (EMG) and electroencephalographic (EEG) recordings were used to quantify physiological changes during the preceding REM period. We found that tDCS, compared to sham stimulation, significantly decreased reports of dream movement, especially of repetitive actions. Other types of bodily experiences, such as tactile or vestibular sensations, were not affected by tDCS, confirming the specificity of stimulation effects to movement sensations. In addition, tDCS reduced EEG interhemispheric coherence in parietal areas and affected the phasic EMG correlation between both arms. These findings show that a complex temporal reorganization of the motor network co-occurred with the reduction of dream movement, revealing a link between central and peripheral motor processes and movement sensations of the dream self. tDCS over the sensorimotor cortex interferes with dream movement during REM sleep, which is consistent with a causal contribution to dream experience and has broader implications for understanding the neural basis of self-experience in dreams.

Motor-system dynamics during naturalistic reading of action narratives in first and second language

Do embodied semantic systems play different roles depending on when and how well a given language was learned? Emergent evidence suggests that this is the case for isolated, decontextualized stimuli, but no study has addressed the issue considering naturalistic narratives. Seeking to bridge this gap, we assessed motor-system dynamics in 26 Spanish-English bilinguals as they engaged in free, unconstrained reading of naturalistic action texts (ATs, highlighting the characters’ movements) and neutral texts (NTs, featuring low motility) in their first and second language (L1, L2). To explore functional connectivity spread over each reading session, we recorded ongoing high-density electroencephalographic signals and subjected them to functional connectivity analysis via a spatial clustering approach. Results showed that, in L1, AT (relative to NT) reading involved increased connectivity between left and right central electrodes consistently implicated in action-related processes, as well as distinct source-level modulations in motor regions. In L2, despite null group-level effects, enhanced motor-related connectivity during AT reading correlated positively with L2 proficiency and negatively with age of L2 learning. Taken together, these findings suggest that action simulations during unconstrained narrative reading involve neural couplings between motor-sensitive mechanisms, in proportion to how consolidated a language is. More generally, such evidence addresses recent calls to test the ecological validity of motor-resonance effects while offering new insights on their relation with experiential variables.

Electroencephalography of completely locked-in state patients with amyotrophic lateral sclerosis

Patients in completely locked-in state (CLIS) due to amyotrophic lateral sclerosis (ALS) lose the control of each and every muscle of their body rendering them motionless and without any means of communication. Though some studies have attempted to develop brain-computer interface (BCI)-based communication methods with CLIS patients, little information is available of the neuroelectric brain activity of CLIS patients. However, because of the difficulties with and often loss of communication, the neuroelectric signature may provide some indications of the state of consciousness in these patients. We recorded electroencephalography (EEG) signals from 10 CLIS patients during resting state and compared their power spectral densities with those of healthy participants in fronto-central, central, and centro-parietal channels. The results showed significant power reduction in the high alpha, beta, and gamma bands in CLIS patients, indicating the dominance of slower EEG frequencies in their oscillatory activity. This is the first study showing group-level EEG change of CLIS patients, though the reason for the observed EEG change cannot be concluded without any reliable communication methods with this population.

Influence of Judo Experience on Neuroelectric Activity During a Selective Attention Task

OBJECTIVE

We compared the cognitive performance and neuroelectric responses during a selective attentional task in judo athletes with different levels of expertise.

METHODS

Judo black and white belt athletes performed both general and specific fitness tests while simultaneously completing a Stroop color-word test recorded by 64 electroencephalogram channels.

RESULTS

Cognitive behavioral performance and event-related spectral perturbation (ERSP) present no differences between groups. However, the topographic analysis found different neural source patterns in each group. Judo black belts compared to judo white belts presented a greater peak amplitude of P300 in the middle frontal gyrus and of N200 in the cuneus, but slower latency of P300 in the precuneus.

CONCLUSION

Despite no difference in cognitive behavioral performance, judo expertise causes a difference in the allocation of attentional and conflict detection neural resources.

Too late to be grounded? Motor resonance for action words acquired after middle childhood

Though well established for languages acquired in infancy, the role of embodied mechanisms remains poorly understood for languages learned in middle childhood and adulthood. To bridge this gap, we examined 34 experiments that assessed sensorimotor resonance during processing of action-related words in real and artificial languages acquired since age 7 and into adulthood. Evidence from late bilinguals indicates that foreign-language action words modulate neural activity in motor circuits and predictably facilitate or delay physical movements (even in an effector-specific fashion), with outcomes that prove partly sensitive to language proficiency. Also, data from newly learned vocabularies suggest that embodied effects emerge after brief periods of adult language exposure, remain stable through time, and hinge on the performance of bodily movements (and, seemingly, on action observation, too). In sum, our work shows that infant language exposure is not indispensable for the recruitment of embodied mechanisms during language processing, a finding that carries non-trivial theoretical, pedagogical, and clinical implications for neurolinguistics, in general, and bilingualism research, in particular.