The role of cortical sensorimotor oscillations in action anticipation

Coping strategies and brain activity in table tennis players faced with discrepancies between predicted and actual outcomes

Prior studies have shown that experts possess an excellent ability for action anticipation. However, it is not clear how experts process the discrepancies between predicted outcomes and actual outcomes. Based on Bayesian theory, Experiment 1 in the current study explored this question by categorizing unexpected outcomes into gradually increasing discrepancies and comparing the performance of experts and novices on a congruence discrimination task. Our behavioral analysis revealed that experts outperformed novices significantly in detecting these discrepancies. The following electroencephalogram study in Experiment 2 was conducted focused exclusively on experts to examine the role of theta wave oscillations within the mid-frontal cortex in processing varying levels of discrepancy. The results showed that reaction time and theta oscillations gradually increased as the magnitude of discrepancy increased. These findings indicate that compared to the novices, experts have a better ability to perceptual the discrepancy. Also, the magnitude of discrepancies induced an increase in mid-frontal theta in experts, providing greater flexibility in their response strategies.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Skill and experience impact neural activity during global and local biological motion processing

During biological motion perception, individuals with perceptual experience learn to use more global processing, simultaneously extracting information from multiple body segments. Less experienced observers may use more local processing of individual body segments. The parietal lobe (e.g., alpha and beta power) has been shown to be critical to global and local static stimulus perception. Therefore, in this paper, we examined how skill impacts motion processing by assessing behavioral and neural responses to degrading global or local motion information for soccer penalty kicks. Skilled (N = 21) and less skilled (N = 19) soccer players anticipated temporally occluded videos of penalty kicks under normal, blurred (degraded local information), or spatially occluded (hips-only; degraded global information) viewing conditions. EEG was used to measure parietal alpha and beta power. Skilled players outperformed less skilled players, albeit both skill groups were less accurate in the blurred and hips-only conditions. Skilled performers showed significant decreases in bilateral parietal beta power in the hips-only condition, suggesting a greater reliance on global motion information under normal viewing conditions. Additionally, the hips-only condition elicited significantly greater beta relative to alpha power (beta - alpha), lower beta power, and lower alpha power than the control condition for both skill groups, suggesting spatial occlusion elicited a shift towards more local processing. Our novel findings demonstrate that skill and experience impact how motion is processed.

Skilled Performers Show Right Parietal Lateralization during Anticipation of Volleyball Attacks

Global and local biological motion processing are likely influenced by an observer's perceptual experience. Skilled athletes anticipating an opponent's movements use globally distributed motion information, while less skilled athletes focus on single kinematic cues. Published reports have demonstrated that attention can be primed globally or locally before perceptual tasks; such an intervention could highlight motion processing mechanisms used by skilled and less skilled observers. In this study, we examined skill differences in biological motion processing using attentional priming. Skilled (N = 16) and less skilled (N = 16) players anticipated temporally occluded videos of volleyball attacks after being primed using a Navon matching task while parietal EEG was measured. Skilled players were more accurate than less skilled players across priming conditions. Global priming improved performance in both skill groups. Skilled players showed significantly reduced alpha and beta power in the right compared to left parietal region, but brain activity was not affected by the priming interventions. Our findings highlight the importance of right parietal dominance for skilled performers, which may be functional for inhibiting left hemispheric local processing or enhancing visual spatial attention for dynamic visual scenes. Further work is needed to systematically determine the function of this pattern of brain activity during skilled anticipation.

Parieto-Occipital Electrocortical Dynamics during Real-World Table Tennis

Traditional human electroencephalography (EEG) experiments that study visuomotor processing use controlled laboratory conditions with limited ecological validity. In the real world, the brain integrates complex, dynamic, multimodal visuomotor cues to guide the execution of movement. The parietal and occipital cortices are especially important in the online control of goal-directed actions. Table tennis is a whole-body, responsive activity requiring rapid visuomotor integration that presents a myriad of unanswered neurocognitive questions about brain function during real-world movement. The aim of this study was to quantify the electrocortical dynamics of the parieto-occipital cortices while playing a sport with high-density electroencephalography. We included analysis of power spectral densities (PSDs), event-related spectral perturbations, intertrial phase coherences (ITPCs), event-related potentials (ERPs), and event-related phase coherences of parieto-occipital source-localized clusters while participants played table tennis with a ball machine and a human. We found significant spectral power fluctuations in the parieto-occipital cortices tied to hit events. Ball machine trials exhibited more fluctuations in θ power around hit events, an increase in intertrial phase coherence and deflection in the event-related potential, and higher event-related phase coherence between parieto-occipital clusters as compared with trials with a human. Our results suggest that sport training with a machine elicits fundamentally different brain dynamics than training with a human.

Brain dynamics of visual anticipation during spatial occlusion tasks in expert tennis players

Stimulus identification and action outcome understanding for a rapid and accurate response selection, play a fundamental role in racquet sports. Here, we investigated the neurodynamics of visual anticipation in tennis manipulating the postural and kinematic information associated with the body of opponents by means of a spatial occlusion protocol. Event Related Potentials (ERPs) were evaluated in two groups of professional tennis players (N = 37) with different levels of expertise, while they observed pictures of opponents and predicted the landing position as fast and accurately as possible. The observed action was manipulated by deleting different body districts of the opponent (legs, ball, racket and arm, trunk). Full body image (no occlusion) was used as control condition. The worst accuracy and the slowest response time were observed in the occlusion of trunk and ball. The former was associated with a reduced amplitude of the ERP components likely linked to body processing (the N1 in the right hemisphere) and visual-motor integration awareness (the pP1), as well as with an increase of the late frontal negativity (the pN2), possibly reflecting an effort by the insula to recover and/or complete the most correct sensory-motor representation. In both occlusions, a decrease in the pP2 may reflect an impairment of decisional processes upon action execution following sensory evidence accumulation. Enhanced amplitude of the P3 and the pN2 components were found in more experienced players, suggesting a greater allocation of resources in the process connecting sensory encoding and response execution, and sensory-motor representation.

Temporal profiles of cortical oscillations in novice performers for goal-directed aiming in a shooting task

Goal-directed aiming relies on the ability to control attention and visuomotor movements while preparing for motor execution. Research in precision sports has investigated cortical oscillations for supporting expert performance. However, the results may be influenced by adaptive and strategic behaviors after intensive training. Whether and at what time points distinctive oscillations support goal-directed aiming without such training remains elusive. In this electroencephalographic (EEG) study, we investigated how the theta, alpha and beta oscillations change to support accurate aiming before novices took an action. We first conducted a model-based analysis to examine the correlation of cortical oscillations with accurate shooting on a trial-by-trial basis in a within-individual manner. The results showed that alpha and beta oscillations at different time points during the aiming period were better predictors of aiming accuracy. We then compared the oscillatory power for good versus poor performance. The results showed decreases in the alpha and beta power across distributed cortical areas and an increase in the frontal theta power successively before shot release. Moreover, greater intertrial phase coherence was observed for good performance than for poor performance in posterior alpha activity and anterior beta activity during the aiming period. In conclusion, these results advance our understanding of the temporal dynamics of theta, alpha and beta oscillations in orchestrating goal setting, motor preparation and focused attention to monitoring both external and internal states for accurate aiming. Among the three, alpha and beta oscillations are critical for predicting aiming performance and theta oscillations reflect effortful cognitive control.

Body into Narrative: Behavioral and Neurophysiological Signatures of Action Text Processing After Ecological Motor Training

Embodied cognition research indicates that sensorimotor training can influence action concept processing. Yet, most studies employ isolated (pseudo)randomized stimuli and require repetitive single-effector responses, thus lacking ecological validity. Moreover, the neural signatures of these effects remain poorly understood. Here, we examined whether immersive bodily training can modulate behavioral and functional connectivity correlates of action-verb processing in naturalistic narratives. The study involved three phases. First, in the Pre-training phase, 32 healthy persons listened to an action text (rich in movement descriptions) and a non-action text (focused on its characters' perceptual and mental processes), completed comprehension questionnaires, and underwent resting-state electroencephalogram (EEG) recordings. Second, in the four-day Training phase, half the participants completed an exergaming intervention (eliciting full-body movements for 60 min a day) while the remaining half played static videogames (requiring no bodily engagement other than button presses). Finally, in the Post-training phase, all participants repeated the Pre-training protocol with different action and non-action texts and a new EEG session. We found that exergaming selectively reduced action-verb outcomes and fronto-posterior functional connectivity in the motor-sensitive ∼ 10-20 Hz range, both patterns being positively correlated. Conversely, static videogame playing yielded no specific effect on any linguistic category and did not modulate functional connectivity. Together, these findings suggest that action-verb processing and key neural correlates can be focally influenced by full-body motor training in a highly ecological setting. Our study illuminates the role of situated experience and sensorimotor circuits in action-concept processing, addressing calls for naturalistic insights on language embodiment.

Characterizing and Removing Artifacts Using Dual-Layer EEG during Table Tennis

Researchers can improve the ecological validity of brain research by studying humans moving in real-world settings. Recent work shows that dual-layer EEG can improve the fidelity of electrocortical recordings during gait, but it is unclear whether these positive results extrapolate to non-locomotor paradigms. For our study, we recorded brain activity with dual-layer EEG while participants played table tennis, a whole-body, responsive sport that could help investigate visuomotor feedback, object interception, and performance monitoring. We characterized artifacts with time-frequency analyses and correlated scalp and reference noise data to determine how well different sensors captured artifacts. As expected, individual scalp channels correlated more with noise-matched channel time series than with head and body acceleration. We then compared artifact removal methods with and without the use of the dual-layer noise electrodes. Independent Component Analysis separated channels into components, and we counted the number of high-quality brain components based on the fit of a dipole model and using an automated labeling algorithm. We found that using noise electrodes for data processing provided cleaner brain components. These results advance technological approaches for recording high fidelity brain dynamics in human behaviors requiring whole body movement, which will be useful for brain science research.

Neurofeedback training: Decreases in Mu rhythm lead to improved motor performance in complex visuomotor skills

The physiological function of the Mu rhythm (8-13 Hz in the central region) is still unclear, particularly its role in visuomotor performance in sports (shooting vs. golf putting), as both the complexity of the motor skills (i.e., simple vs. complex visuomotor skills) and the skill level (e.g., novices vs. experts or low-skilled vs. highly skilled) may modulate Mu rhythm. To gain a broader understanding of the association between Mu rhythm and visuomotor skill performance, a study design that considers both a control moderator (the difference in skill level) and the ability to manipulate Mu rhythm (i.e., either increase or decrease Mu rhythm) is required. To achieve this, we recruited 30 novice golfers who were randomly assigned to either the increased Mu rhythm group (IMG), decreased Mu rhythm group (DMG), or sham group (SG) and used electroencephalographic-neurofeedback training (EEG-NFT) to manipulate Mu rhythm during a golf putting task (complex visuomotor skill). The aim was to determine whether the complexity of the motor skill was a potential moderator of Mu rhythm. We mainly found that Mu power was significantly decreased in the DMG following EEG-NFT, which lead to increased motor control and improved performance. We suggest that (1) the complexity of the motor skill, rather than the difference in skill level, may be a potential moderator of Mu rhythm and visuomotor performance, as our results were not consistent with a previous study that reported that increased Mu rhythm improved shooting performance (a simple visuomotor task) in novices.

Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats

The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10–15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.

Constructing Time-varying Directed EEG network by Multivariate Nonparametric Dynamical Granger Causality

Time-varying directed electroencephalography (EEG) network is the potential tool for studying the dynamical causality among brain areas at a millisecond level; which conduces to understanding how our brain effectively adapts to information processing, giving inspiration to causality- and brain-inspired machine learning. Currently, its construction still mainly relies on the parametric approach such as multivariate adaptive autoregressive (MVAAR), represented by the most widely used adaptive directed transfer function (ADTF). Restricted by the model assumption, the corresponding performance largely depends on the MVAAR modeling which usually encounters difficulty in fitting complex spectral features. In this study, we proposed to construct EEG directed network with multivariate nonparametric dynamical Granger causality (mndGC) method that infers the causality of a network, instead, in a data-driven way directly and therefore avoids the trap in the model-dependent parametric approach. Comparisons between mndGC and ADTF were conducted both with simulation and real data application. Simulation study demonstrated the superiority of mndGC both in noise resistance and capturing the instantaneous directed network changes. When applying to the real motor imagery (MI) data set, distinguishable network characters between left- and right-hand MI during different MI stages were better revealed by mndGC. Our study extends the nonparametric causality exploration and provides practical suggestions for the time-varying directed EEG network analysis.

The field of expertise modulates the time course of neural processes associated with inhibitory control in a sport decision-making task

Inhibitory control (IC), the ability to suppress inappropriate actions, can be improved by regularly facing complex and dynamic situations requiring flexible behaviors, such as in the context of intensive sport practice. However, researchers have not clearly determined whether and how this improvement in IC transfers to ecological and nonecological computer-based tasks. We explored the spatiotemporal dynamics of changes in the brain activity of three groups of athletes performing sport-nonspecific and sport-specific Go/NoGo tasks with video footages of table tennis situations to address this question. We compared table tennis players (n = 20), basketball players (n = 20) and endurance athletes (n = 17) to identify how years of practicing a sport in an unpredictable versus predictable environment shape the IC brain networks and increase the transfer effects to untrained tasks. Overall, the table tennis group responded faster than the two other groups in both Go/NoGo tasks. The electrical neuroimaging analyses performed in the sport-specific Go/NoGo task revealed that this faster response time was supported by an early engagement of brain structures related to decision-making processes in a time window where inhibition processes typically occur. Our collective findings have relevant applied perspectives, as they highlight the importance of designing more ecological domain-related tasks to effectively capture the complex decision-making processes acquired in real-life situations. Finally, the limited effects from sport practice to laboratory-based tasks found in this study question the utility of cognitive training intervention, whose effects would remain specific to the practice environment.

Audio and visual speech emotion activate the left pre-supplementary motor area

Sensorimotor brain areas have been implicated in the recognition of emotion expressed on the face and through nonverbal vocalizations. However, no previous study has assessed whether sensorimotor cortices are recruited during the perception of emotion in speech-a signal that includes both audio (speech sounds) and visual (facial speech movements) components. To address this gap in the literature, we recruited 24 participants to listen to speech clips produced in a way that was either happy, sad, or neutral in expression. These stimuli also were presented in one of three modalities: audio-only (hearing the voice but not seeing the face), video-only (seeing the face but not hearing the voice), or audiovisual. Brain activity was recorded using electroencephalography, subjected to independent component analysis, and source-localized. We found that the left presupplementary motor area was more active in response to happy and sad stimuli than neutral stimuli, as indexed by greater mu event-related desynchronization. This effect did not differ by the sensory modality of the stimuli. Activity levels in other sensorimotor brain areas did not differ by emotion, although they were greatest in response to visual-only and audiovisual stimuli. One possible explanation for the pre-SMA result is that this brain area may actively support speech emotion recognition by using our extensive experience expressing emotion to generate sensory predictions that in turn guide our perception.

Decoding motor expertise from fine-tuned oscillatory network organization

Can motor expertise be robustly predicted by the organization of frequency-specific oscillatory brain networks? To answer this question, we recorded high-density electroencephalography (EEG) in expert Tango dancers and naïves while viewing and judging the correctness of Tango-specific movements and during resting. We calculated task-related and resting-state connectivity at different frequency-bands capturing task performance (delta [δ], 1.5-4 Hz), error monitoring (theta [θ], 4-8 Hz), and sensorimotor experience (mu [μ], 8-13 Hz), and derived topographical features using graph analysis. These features, together with canonical expertise measures (i.e., performance in action discrimination, time spent dancing Tango), were fed into a data-driven computational learning analysis to test whether behavioral and brain signatures robustly classified individuals depending on their expertise level. Unsurprisingly, behavioral measures showed optimal classification (100%) between dancers and naïves. When considering brain models, the task-based classification performed well (~73%), with maximal discrimination afforded by theta-band connectivity, a hallmark signature of error processing. Interestingly, mu connectivity during rest outperformed (100%) the task-based approach, matching the optimal classification of behavioral measures and thus emerging as a potential trait-like marker of sensorimotor network tuning by intense training. Overall, our findings underscore the power of fine-tuned oscillatory network signatures for capturing expertise-related differences and their potential value in the neuroprognosis of learning outcomes.

Robust anticipation of continuous steering actions from electroencephalographic data during simulated driving

Driving a car requires high cognitive demands, from sustained attention to perception and action planning. Recent research investigated the neural processes reflecting the planning of driving actions, aiming to better understand the factors leading to driving errors and to devise methodologies to anticipate and prevent such errors by monitoring the driver’s cognitive state and intention. While such anticipation was shown for discrete driving actions, such as emergency braking, there is no evidence for robust neural signatures of continuous action planning. This study aims to fill this gap by investigating continuous steering actions during a driving task in a car simulator with multimodal recordings of behavioural and electroencephalography (EEG) signals. System identification is used to assess whether robust neurophysiological signatures emerge before steering actions. Linear decoding models are then used to determine whether such cortical signals can predict continuous steering actions with progressively longer anticipation. Results point to significant EEG signatures of continuous action planning. Such neural signals show consistent dynamics across participants for anticipations up to 1 s, while individual-subject neural activity could reliably decode steering actions and predict future actions for anticipations up to 1.8 s. Finally, we use canonical correlation analysis to attempt disentangling brain and non-brain contributors to the EEG-based decoding. Our results suggest that low-frequency cortical dynamics are involved in the planning of steering actions and that EEG is sensitive to that neural activity. As a result, we propose a framework to investigate anticipatory neural activity in realistic continuous motor tasks.

Enhanced biological motion perception in deaf native signers

We conducted two studies to test how deaf signed language users perceive biological motions. We created 18 Biological Motion point-light displays (PLDs) depicting everyday human actions, and 18 Scrambled control PLDs. First, we conducted an online behavioral rating survey, in which deaf and hearing raters identified the biological motion PLDs and rated how easy it was for them to identify the actions. Then, we conducted an EEG study in which Deaf Signers and Hearing Non-Signers watched both the Biological Motion PLDs and the Scrambled PLDs, and we computed the time-frequency responses within the theta, alpha, and beta EEG rhythms. From the behavioral rating task, we show that the deaf raters reported significantly less effort required for identifying the Biological motion PLDs, across all stimuli. The EEG results showed that the Deaf Signers showed theta, mu, and beta differentiation between Scrambled and Biological PLDs earlier and more consistently than Hearing Non-Signers. We conclude that native ASL users exhibit experience-dependent neuroplasticity in the domain of biological human motion perception.

Neural Encoding of the Reliability of Directional Information During the Preparation of Targeted Movements

Visual information about the location of an upcoming target can be used to prepare an appropriate motor response and reduce its reaction time. Here, we investigated the brain mechanisms associated with the reliability of directional information used for motor preparation. We recorded brain activity using magnetoencephalography (MEG) during a delayed reaching task in which a visual cue provided valid information about the location of the upcoming target with 50, 75, or 100% reliability. We found that reaction time increased as cue reliability decreased and that trials with invalid cues had longer reaction times than trials with valid cues. MEG channel analysis showed that during the late cue period the power of the beta-band from left mid-anterior channels, contralateral to the responding hand, correlated with the reliability of the cue. This effect was source localized over a large motor-related cortical and subcortical network. In addition, during invalid-cue trials there was a phasic increase of theta-band power following target onset from left posterior channels, localized to the left occipito-parietal cortex. Furthermore, the theta-beta cross-frequency coupling between left mid-occipital and motor cortex transiently increased before responses to invalid-cue trials. In conclusion, beta-band power in motor-related areas reflected the reliability of directional information used during motor preparation, whereas phasic theta-band activity may have signaled whether the target was at the expected location or not. These results elucidate mechanisms of interaction between attentional and motor processes.

Distinct modulation of mu and beta rhythm desynchronization during observation of embodied fake hand rotation

The rubber hand illusion (RHI) is a phenomenon whereby participants recognize a fake hand as their own. Studies have examined the effects of observing fake hand movements after the RHI on brain sensorimotor activity, although results remain controversial. To address these discrepancies, we investigated the effects of observation of fake hand rotation after the RHI on sensorimotor mu (μ: 8-13 Hz) and beta (β: 15-25 Hz) rhythm event-related desynchronization (ERD) using electroencephalography (EEG). Questionnaire results and proprioceptive drift revealed that the RHI occurred in participants when their invisible hand and fake visible hand were stroked synchronously but not during asynchronous stroking. Independent component (IC) clustering from EEG data during movement observation identified three IC clusters, including the right sensorimotor, left sensorimotor, and left occipital cluster. In the right sensorimotor cluster, we observed distinct modulation of μ and β ERD during fake hand rotation. Illusory ownership over the fake hand enhanced μ ERD but inversely attenuated β ERD. Further, the extent of μ ERD correlated with proprioceptive drift, but not with questionnaire ratings, whereas the converse results were obtained for β ERD. No ownership-dependent ERD modulation was detected in the left sensorimotor cluster. Alpha (α: 8-13 Hz) rhythm ERD of the left occipital cluster was smaller in the synchronous condition than in the asynchronous condition, but α ERD was not correlated with questionnaire rating or drift. These findings suggest that observing embodied fake hand rotation induces distinct cortical processing in sensorimotor brain areas.

The sound of silence: an EEG study of how musicians time pauses in individual and joint music performance

Pauses are an integral feature of social interaction. Conversation partners often pause between conversational turns, and musical co-performers often pause between musical phrases. How do humans coordinate the duration of pauses to ensure seamless interaction? A total of 40 trained pianists performed a simple melody containing fermatas (notated expressive pauses of unspecified duration) first alone (Solo) and then with a partner (Duet) while electroencephalography (EEG) was recorded. As predicted, Duet partners' tone onset synchrony was reduced for tones following pauses. Pauses were shorter in Duet relative to Solo performance, and synchrony of partners' Duet tone onsets was enhanced for tones following shorter pauses. EEG analysis revealed classic signatures of action preparation during pauses, namely decreases in the power of cortical beta oscillations (13-30 Hz, event-related desynchronization ERD). Beta ERD did not differ between pauses in Solo and Duet performance, but was enhanced for shorter relative to longer pauses, suggesting that reduced pause durations in Duet performance facilitated a neural state of enhanced action readiness. Together these findings provide novel insight into behavioural strategies by which musical partners resolve coordination challenges posed by expressive silence, and capture a clear neural signature of action planning during time-varying silences in natural music performance.

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.

Backward Walking Induces Significantly Larger Upper-Mu-Rhythm Suppression Effects Than Forward Walking Does

Studies have compared the differences and similarities between backward walking and forward walking, and demonstrated the potential of backward walking for gait rehabilitation. However, current evidence supporting the benefits of backward walking over forward walking remains inconclusive. Considering the proven association between gait and the cerebral cortex, we used electroencephalograms (EEG) to differentiate the effects of backward walking and forward walking on cortical activities, by comparing the sensorimotor rhythm (8–12 Hz, also called mu rhythm) of EEG signals. A systematic signal procedure was used to eliminate the motion artifacts induced by walking to safeguard EEG signal fidelity. Statistical test results of our experimental data demonstrated that walking motions significantly suppressed mu rhythm. Moreover, backward walking exhibited significantly larger upper mu rhythm (10–12 Hz) suppression effects than forward walking did. This finding implies that backward walking induces more sensorimotor cortex activity than forward walking does, and provides a basis to support the potential benefits of backward walking over forward walking. By monitoring the upper mu rhythm throughout the rehabilitation process, medical experts can adaptively adjust the intensity and duration of each walking training session to improve the efficacy of a walking ability recovery program.

Effects of virtual reality training intervention on predictive motor control of children with DCD - A randomized controlled trial

It has been hypothesised that deficits in the functions of predictive motor control and internal modeling may contribute to motor control issues of children with Developmental Coordination Disorder (DCD). Virtual reality (VR) technologies have great potential to provide opportunity for Motor observation and motor imagery (MI) which could enhance learning and development of motor skills in children with DCD. Thus, the present study aimed to investigate the benefits of a VR training intervention to improve predictive motor control functions of children with DCD. Forty female children with DCD (aged 7-10) were randomly assigned to VR and control groups. In this study, an experimental pre-post and follow-up design was used, and Predictive motor control functions were measured before and after the VR intervention and two-months later. Predictive motor control was evaluated using MI (by hand rotation task), action planning (by sword placement task), and rapid and online control (by rotational tracking task) tests. VR intervention consisted of a selection of Xbox 360 Kinect games that were performed for sixteen 30-min sessions over 8 weeks. Compared to the control group, the VR group improved significantly on measures of MI, motor planning, and rapid and online control scores from pre- to post-test and retained their performance to follow-up. Overall, it seems that virtual reality training program may be used as an appropriate intervention approach for developing the ability of MI and predictive motor control functions in DCD children.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback

This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

Muscular effort coding in action representation in ballet dancers and controls: Electrophysiological evidence

The present electrophysiological (EEG) study investigated the neural correlates of perceiving effortful vs. effortless movements belonging to a specific repertoire (ballet). Previous evidence has shown an increased heart and respiratory rate during the observation and imagination of human actions that require a great muscular effort. In addition, TMS (transcranial magnetic stimulation) and EEG studies have evidenced a greater muscle-specific cortical excitability and an increase in late event-related potentials during the observation of effortful actions. In this investigation, fifteen professional female ballet dancers and 15 controls with no experience whatsoever with dance, gymnastics, or martial arts were recruited. They were shown 326 short videos displaying a male dancer performing standard ballet steps that could be either effortful or relatively effortless. Participants were instructed to observe each clip and imagine themselves physically executing the same movement. Importantly, they were blinded to the stimuli properties. The observation of effortful compared with effortless movements resulted in a larger P300 over frontal sites in dancers only, likely because of their visuomotor expertise with the specific steps. Moreover, an enhanced Late Positivity was identified over posterior sites in response to effortful stimuli in both groups, possibly reflecting the processing of larger quantities of visual kinematic information. The source reconstruction swLORETA performed on the Late Positivity component showed greater engagement of frontoparietal regions in dancers, while task-related frontal and occipitotemporal visual regions were more active in controls. It, therefore, appears that, in dancers, effort information was encoded in a more refined manner during action observation and in the absence of explicit instruction. Acquired motor knowledge seems to result in visuomotor resonance processes, which, in turn, underlies enhanced action representation of the observed movements.

Spatially and Temporally Distinct Encoding of Muscle and Kinematic Information in Rostral and Caudal Primary Motor Cortex

The organizing principle of human motor cortex does not follow an anatomical body map, but rather a distributed representational structure in which motor primitives are combined to produce motor outputs. Electrophysiological recordings in primates and human imaging data suggest that M1 encodes kinematic features of movements, such as joint position and velocity. However, M1 exhibits well-documented sensory responses to cutaneous and proprioceptive stimuli, raising questions regarding the origins of kinematic motor representations: are they relevant in top-down motor control, or are they an epiphenomenon of bottom-up sensory feedback during movement? Here we provide evidence for spatially and temporally distinct encoding of kinematic and muscle information in human M1 during the production of a wide variety of naturalistic hand movements. Using a powerful combination of high-field functional magnetic resonance imaging and magnetoencephalography, a spatial and temporal multivariate representational similarity analysis revealed encoding of kinematic information in more caudal regions of M1, over 200 ms before movement onset. In contrast, patterns of muscle activity were encoded in more rostral motor regions much later after movements began. We provide compelling evidence that top-down control of dexterous movement engages kinematic representations in caudal regions of M1 prior to movement production.

The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering

Deficits in basal ganglia-based inhibitory and timing circuits along with sensorimotor internal modeling mechanisms are thought to underlie stuttering. However, much remains to be learned regarding the precise manner how these deficits contribute to disrupting both speech and cognitive functions in those who stutter. Herein, we examine the suitability of electroencephalographic (EEG) mu rhythms for addressing these deficits. We review some previous findings of mu rhythm activity differentiating stuttering from non-stuttering individuals and present some new preliminary findings capturing stuttering-related deficits in working memory. Mu rhythms are characterized by spectral peaks in alpha (8-13 Hz) and beta (14-25 Hz) frequency bands (mu-alpha and mu-beta). They emanate from premotor/motor regions and are influenced by basal ganglia and sensorimotor function. More specifically, alpha peaks (mu-alpha) are sensitive to basal ganglia-based inhibitory signals and sensory-to-motor feedback. Beta peaks (mu-beta) are sensitive to changes in timing and capture motor-to-sensory (i.e., forward model) projections. Observing simultaneous changes in mu-alpha and mu-beta across the time-course of specific events provides a rich window for observing neurophysiological deficits associated with stuttering in both speech and cognitive tasks and can provide a better understanding of the functional relationship between these stuttering symptoms. We review how independent component analysis (ICA) can extract mu rhythms from raw EEG signals in speech production tasks, such that changes in alpha and beta power are mapped to myogenic activity from articulators. We review findings from speech production and auditory discrimination tasks demonstrating that mu-alpha and mu-beta are highly sensitive to capturing sensorimotor and basal ganglia deficits associated with stuttering with high temporal precision. Novel findings from a non-word repetition (working memory) task are also included. They show reduced mu-alpha suppression in a stuttering group compared to a typically fluent group. Finally, we review current limitations and directions for future research.

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.

The modulation of event-related alpha rhythm during the time course of anticipation

Anticipation is the ability to accurately predict future actions or events ahead of the act itself. When attempting to anticipate, researchers have identified that at least two broad sources of information are used: contextual information relating to the situation in question; and biological motion from postural cues. However, the neural correlates associated with the processing of these different sources of information across groups varying in expertise has yet to be examined empirically. We compared anticipation performance and electrophysiological activity in groups of expert (n = 12) and novice (n = 15) performers using a video-based task. Participants made anticipation judgements after being presented information under three conditions: contextual information only; kinematic information only; and both sources of information combined. The experts responded more accurately across all three conditions. Stronger alpha event-related desynchronization over occipital and frontocentral sites occurred in experts compared to the novices when anticipating. The experts relied on stronger preparatory attentional mechanisms when they processed contextual information. When kinematic information was available, the domain specific motor representations built up over many years of practice likely underpinned expertise. Our findings have implications for those interested in identifying and subsequently, enhancing the neural mechanisms involved in anticipation.

Agency and responsibility over virtual movements controlled through different paradigms of brain-computer interface

KEY POINTS

Embodiment of a virtual body was induced and its movements were controlled by two different brain-computer interface (BCI) paradigms - one based on signals from sensorimotor versus one from visual cortical areas. BCI-control of movements engenders agency, but not equally for all paradigms. Cortical sensorimotor activation correlates with agency and responsibility. This has significant implications for neurological rehabilitation and neuroethics.

ABSTRACT

Agency is the attribution of an action to the self and is a prerequisite for experiencing responsibility over its consequences. Here we investigated agency and responsibility by studying the control of movements of an embodied avatar, via brain-computer interface (BCI) technology, in immersive virtual reality. After induction of virtual body ownership by visuomotor correlations, healthy participants performed a motor task with their virtual body. We compared the passive observation of the subject's 'own' virtual arm performing the task with (1) the control of the movement through activation of sensorimotor areas (motor imagery) and (2) the control of the movement through activation of visual areas (steady-state visually evoked potentials). The latter two conditions were carried out using a BCI and both shared the intention and the resulting action. We found that BCI-control of movements engenders the sense of agency, which is strongest for sensorimotor area activation. Furthermore, increased activity of sensorimotor areas, as measured using EEG, correlates with levels of agency and responsibility. We discuss the implications of these results for the neural basis of agency.

Sensorimotor and Posterior Brain Activations During the Observation of Illusory Embodied Fake Hand Movement

In the rubber hand illusion (RHI), the subject recognizes a fake hand as his or her own. We recently found that the observation of embodied fake hand movement elicited mu-rhythm (8–13 Hz) desynchronization on electroencephalography (EEG), suggesting brain activation in the sensorimotor regions. However, it is known that mu-rhythm desynchronization during action observation is confounded with occipital alpha-rhythm desynchronization, which is modulated by attention. This study examined the independence of brain activities in the sensorimotor and occipital regions relating to the movement observation under the RHI. The invisible participant’s left and fake right hands were stroked simultaneously, which was interrupted by unexpected fake hand movements. A mirror-reversed image of the fake hand was shown on a monitor in front of the participant with a delay of 80, 280, or 480 ms. Illusion strength decreased as a function of the delay. EEG independent component analysis (ICA) and ICA clustering revealed six clusters with observation-induced desynchronization of 8–13 Hz frequency band. In the right sensorimotor cluster, mu-rhythm desynchronization was the greatest under the 80-ms delay, while alpha-rhythm desynchronization of the occipital clusters did not show delay-dependence. These results suggest that brain activation in the sensorimotor areas (i.e., mu-rhythm desynchronization) induced by embodied fake hand movement is independent of that in the occipital areas (alpha-rhythm desynchronization).

Building blocks of joint attention: Early sensitivity to having one's own gaze followed

Detecting when one's own gaze has been followed is a critical component of joint attention, but little is known about its development. To address this issue, we used electroencephalography (EEG) to record infant neural responses at 6.5 and 9.5 months during observation of an adult either turning to look at the same object as the infant (congruent actor), or turning to look at a different object (incongruent actor). We also used a preferential looking paradigm to investigate whether infants would demonstrate a preference for the congruent versus incongruent actor. Greater suppression of alpha band activity in the congruent compared to incongruent condition was revealed at both ages in central and parietal regions. However, the effect of congruency on alpha suppression was stronger at 9.5 months, and only at this age did infants demonstrate a preference towards looking at the congruent actor. Together, these results suggest that although infants are sensitive to others' gaze following from early on, important neural and behavioural developments occur between 6.5 and 9.5 months.

Motor system recruitment during action observation: No correlation between mu-rhythm desynchronization and corticospinal excitability

Observing others’ actions desynchronizes electroencephalographic (EEG) rhythms and modulates corticospinal excitability as assessed by transcranial magnetic stimulation (TMS). However, it remains unclear if these measures reflect similar neurofunctional mechanisms at the individual level. In the present study, a within-subject experiment was designed to assess these two neurophysiological indexes and to quantify their mutual correlation. Participants observed reach-to-grasp actions directed towards a small (precision grip) or a large object (power grip). We focused on two specific time points for both EEG and TMS. The first time point (t1) coincided with the maximum hand aperture, i.e. the moment at which a significant modulation of corticospinal excitability is expected. The second (t2), coincided with the EEG resynchronization occurring at the end of the action, i.e. the moment at which a hypothetic minimum for action observation effect is expected. Results showed a Mu rhythm bilateral desynchronization at t1 with differential resynchronization at t2 in the two hemispheres. Beta rhythm was more desynchronized in the left hemisphere at both time points. These EEG differences, however, were not influenced by grip type. Conversely, motor potentials evoked by TMS in an intrinsic hand muscle revealed an interaction effect of grip and time. No significant correlations between Mu/Beta rhythms and motor evoked potentials were found. These findings are discussed considering the spatial and temporal resolution of the two investigated techniques and argue over two alternative explanations: i. each technique provides different measures of the same process or ii. they describe complementary features of the action observation network in humans.

Concurrent Imitative Movement During Action Observation Facilitates Accuracy of Outcome Prediction in Less-Skilled Performers

Skilled athletes can predict the outcome of actions performed by others, based on the kinematic information inherent in others' actions, earlier and more accurately than less-skilled athletes. Activation of the motor cortex during action observation indicates motor simulation of other's actions in one's own motor system; this contributes to skilled outcome prediction. Thus, the present study investigated whether concurrent movements during action observation that affect motor simulation influence the accuracy of outcome prediction, namely, whether concurrent imitative movement and self-movement enhance and inhibit accuracy, respectively, based on skill level. Twelve male varsity basketball players (skilled group) and twelve male college students with no special training in basketball (less-skilled group) were required to predict the outcome of a basketball free throw by another player based on the action kinematics in the following four conditions: prediction without any action (observation), prediction with right-wrist volar flexion with maximum speed (incongruent-action), prediction with concurrent imitative movement during observation by right-wrist flexion as if imitating the model's action (imitative-motion), or prediction with concurrent self-movement by right-wrist flexion as if shooting by oneself (self-motion). The results showed that the skilled group had degraded accuracy of outcome prediction in the self-motion condition compared to the observation condition. In contrast, accuracy in the less-skilled group was facilitated in the imitative-motion condition compared to the observation condition. The findings suggest that, at least in less-skilled participants, the appropriate motor simulation that relates to skilled prediction can be virtually induced by concurrent imitative movement during the prediction task, even if they have less experience of free throws. This effect in imitative movement is likely to occur by producing identical motor commands with observed action, thereby enabling the prediction of sensory consequences and outcome accurately via a forward model. We propose that traditional perceptual training with concurrent imitative movement is likely to be an effective way to develop visual- and motor-based hybrid outcome predictions that produce superior inferences in skilled athletes.

Early maternal mirroring predicts infant motor system activation during facial expression observation

Processing facial expressions is an essential component of social interaction, especially for preverbal infants. In human adults and monkeys, this process involves the motor system, with a neural matching mechanism believed to couple self- and other-generated facial gestures. Here, we used electroencephalography to demonstrate recruitment of the human motor system during observation and execution of facial expressions in nine-month-old infants, implicating this system in facial expression processing from a very young age. Notably, examination of early video-recorded mother-infant interactions supported the common, but as yet untested, hypothesis that maternal mirroring of infant facial gestures is central to the development of a neural matching mechanism for these gestures. Specifically, the extent to which mothers mirrored infant facial expressions at two months postpartum predicted infant motor system activity during observation of the same expressions at nine months. This suggests that maternal mirroring strengthens mappings between visual and motor representations of facial gestures, which increases infant neural sensitivity to particularly relevant cues in the early social environment.

Short-term EEG dynamics and neural generators evoked by navigational images

The ecological environment offered by virtual reality is primarily supported by visual information. The different image contents and their rhythmic presentation imply specific bottom-up and top-down processing. Because these processes already occur during passive observation we studied the brain responses evoked by the presentation of specific 3D virtual tunnels with respect to 2D checkerboard. For this, we characterized electroencephalograhy dynamics (EEG), the evoked potentials and related neural generators involved in various visual paradigms. Time-frequency analysis showed modulation of alpha-beta oscillations indicating the presence of stronger prediction and after-effects of the 3D-tunnel with respect to the checkerboard. Whatever the presented image, the generators of the P100 were situated bilaterally in the occipital cortex (BA18, BA19) and in the right inferior temporal cortex (BA20). In checkerboard but not 3D-tunnel presentation, the left fusiform gyrus (BA37) was additionally recruited. P200 generators were situated in the temporal cortex (BA21) and the cerebellum (lobule VI/Crus I) specifically for the checkerboard while the right parahippocampal gyrus (BA36) and the cerebellum (lobule IV/V and IX/X) were involved only during the 3D-tunnel presentation. For both type of image, P300 generators were localized in BA37 but also in BA19, the right BA21 and the cerebellar lobule VI for only the checkerboard and the left BA20-BA21 for only the 3D-tunnel. Stronger P300 delta-theta oscillations recorded in this later situation point to a prevalence of the effect of changing direction over the proper visual content of the 3D-tunnel. The parahippocampal gyrus (BA36) implicated in navigation was also identified when the 3D-tunnel was compared to their scrambled versions, highlighting an action-oriented effect linked to navigational content.