The Effects of Motor Expertise on Sensorimotor Rhythm Desynchronization during Execution and Imagery of Sequential Movements

Low-frequency sounds combined with motor imagery elicits a transient disruption of force performance: A path to neuromotor reprogramming?

The effectiveness of motor imagery (MI) training on sports performance is now well-documented. Recently, it has been proposed that a single session of MI combined with low frequency sound (LFS) might enhance muscle activation. However, the neural mechanisms underlying this effect remain unknown. We set up a test-retest intervention over the course of 2 consecutive days to evaluate the effect of (i) MI training (MI, n = 20), (ii) MI combined with LFS (MI + LFS, n = 20), and (iii) a control condition (CTRL, n = 20) on force torque produced across repeated maximal voluntary contractions of the quadriceps before (Pretest), after (Posttest) and at +12 h (Retention) post-intervention. We collected the integrated electromyograms of the quadriceps muscles, as well as brain electrical potentials during each experimental intervention. In the CTRL group, total force torque decreased from Pretest to Retention and from Posttest to Retention. By contrast, there was an increase between Posttest and Retention in both MI + LFS and MI groups (both ηP2 = 0.03, p < 0.05). Regression analyses further revealed a negative relationship between force performance and EEG activity in the MI + LFS group only. The data support a transient interference of LFS on cortical activity underlying the priming effects of MI practice on force performance. Findings are discussed in relation to the potential for motor reprogramming through MI combined with LFS.

Motor imagery of finger movements: Effects on cortical and muscle activities

PURPOSE

The purpose of the current study was to explore the immediate effect of motor imagery (MI) involving finger movement of a given limb on cortical response and muscle activity in healthy subjects.

METHODS

Twenty healthy right-handed adults (7 females and 13 males) with a mean + SD age of 22.05 + 6.08 years participated in the study. The beta-band event-related desynchronization (ERD) at the sensorimotor cortex and muscle activity during finger movement tasks using either the index, middle, or thumb digits on the non-dominant left hand were compared before and after an MI training session. Subjects underwent a pre-MI, MI training, and finally a post-MI session where they either performed or imagined performing a button-pushing action 50 times per session with each of the three digits.

RESULTS

The ERD power in the beta frequency band was lower in pre-MI compared to post-MI and was significantly different between the pre- and post-MI sessions for both the index and middle fingers, but not the thumb. A significant decrease was seen in the mean muscle activity during post-MI compared to pre-MI for all the digits except the thumb.

CONCLUSIONS

The results from the current study suggest that complex MI can result in motor learning and improvement in motor performance, thereby requiring less effort during motion.

The neuro-oscillatory profiles of static and dynamic music-induced visual imagery

Visual imagery, i.e., seeing in the absence of the corresponding retinal input, has been linked to visual and motor processing areas of the brain. Music listening provides an ideal vehicle for exploring the neural correlates of visual imagery because it has been shown to reliably induce a broad variety of content, ranging from abstract shapes to dynamic scenes. Forty-two participants listened with closed eyes to twenty-four excerpts of music, while a 15-channel EEG was recorded, and, after each excerpt, rated the extent to which they experienced static and dynamic visual imagery. Our results show both static and dynamic imagery to be associated with posterior alpha suppression (especially in lower alpha) early in the onset of music listening, while static imagery was associated with an additional alpha enhancement later in the listening experience. With regard to the beta band, our results demonstrate beta enhancement to static imagery, but first beta suppression before enhancement in response to dynamic imagery. We also observed a positive association, early in the listening experience, between gamma power and dynamic imagery ratings that was not present for static imagery ratings. Finally, we offer evidence that musical training may selectively drive effects found with respect to static and dynamic imagery and alpha, beta, and gamma band oscillations. Taken together, our results show the promise of using music listening as an effective stimulus for examining the neural correlates of visual imagery and its contents. Our study also highlights the relevance of future work seeking to study the temporal dynamics of music-induced visual imagery.

Features of event-related potentials during retrieval of episodic memory in patients with mild cognitive impairment due to Alzheimer's disease

Objective

To provide a rigorous comparison between patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) and healthy elderly, as well as to assess the value of electroencephalography (EEG) in terms of early diagnosis, we conducted a neutral image recognition memory task involving individuals with positive biomarkers including β amyloid deposition, pathologic tau or neurodegeneration.

Methods

The task involving study and test blocks was designed to evaluate participants' recognition memory. Electroencephalogram was recorded synchronously to elicit event-related potentials in patients with MCI-AD and healthy control subjects. We further analyzed differences between groups or conditions in terms of behavioral performance, time domain, and time-frequency domain.

Results

The MCI-AD cohort showed a slower response time to old/new images and had low accuracy regarding behavioral performance. The amplitude of the late positive complex for the old/new effects was significantly suppressed in the MCI-AD cohort when compared with that in the HC cohort. The amplitude of the late old/new effects was correlated with the Auditory Verbal Learning Test recognition score in all participants. The time-frequency domain analysis revealed that correct recognition of old items elicited a decrease in beta power, mainly limited to the HC cohort. Moreover, the combination of behavioral (processing speed and accuracy) and electrophysiological (average amplitude and relative power of delta band) measures contributes to classifying patients with MCI-AD from healthy elderly people.

Conclusion

Changes of old/new effects, accuracy and response time are sensitive to the impairment of recognition memory in patients with MCI-AD and have moderate value in predicting the incipient stage of AD.

Transcranial Magnetic Stimulation of the Dorsolateral Prefrontal Cortex Increases Posterior Theta Rhythm and Reduces Latency of Motor Imagery

Experiments show activation of the left dorsolateral prefrontal cortex (DLPFC) in motor imagery (MI) tasks, but its functional role requires further investigation. Here, we address this issue by applying repetitive transcranial magnetic stimulation (rTMS) to the left DLPFC and evaluating its effect on brain activity and the latency of MI response. This is a randomized, sham-controlled EEG study. Participants were randomly assigned to receive sham (15 subjects) or real high-frequency rTMS (15 subjects). We performed EEG sensor-level, source-level, and connectivity analyses to evaluate the rTMS effects. We revealed that excitatory stimulation of the left DLPFC increases theta-band power in the right precuneus (PrecuneusR) via the functional connectivity between them. The precuneus theta-band power negatively correlates with the latency of the MI response, so the rTMS speeds up the responses in 50% of participants. We suppose that posterior theta-band power reflects attention modulation of sensory processing; therefore, high power may indicate attentive processing and cause faster responses.

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

Brain-Computer Interfaces (BCI) is an exciting and emerging research area for researchers and scientists. It is a suitable combination of software and hardware to operate any device mentally. This review emphasizes the significant stages in the BCI domain, current problems, and state-of-the-art findings. This article also covers how current results can contribute to new knowledge about BCI, an overview of BCI from its early developments to recent advancements, BCI applications, challenges, and future directions. The authors pointed to unresolved issues and expressed how BCI is valuable for analyzing the human brain. Humans' dependence on machines has led humankind into a new future where BCI can play an essential role in improving this modern world.

Timing-specific patterns of cerebral activations during motor imagery: A case study of the expert brain signature

Brain activations elicited during motor imagery (MI) in experts are typically reduced compared to novices, which is interpreted as a neurophysiological correlate of increased neural efficiency. However, the modulatory effects of MI speed on expertise-related differences in brain activation remains largely unknown. In the present pilot study, we compared the magnetoencephalographic (MEG) correlates of MI in an Olympic medallist and an amateur athlete under conditions of slow, real-time and fast MI. Data revealed event-related changes in the time course of alpha (8-12 Hz) power of MEG oscillations, for all timing conditions. We found that slow MI was associated with a corollary increase in neural synchronization, in both participants. Sensor-level and source-level analyses however disclosed differences between the two expertise levels. The Olympic medallist achieved greater activation of cortical sensorimotor networks than the amateur athlete, particularly during fast MI. Fast MI elicited the strongest event-related desynchronization of alpha oscillations, which was generated from cortical sensorimotor sources in the Olympic medallist, but not in the amateur athlete. Taken together, data suggest that fast MI is a particularly demanding form of motor cognition, putting a specific emphasis on cortical sensorimotor networks to achieve the formation of accurate motor representations under demanding timing constraints.

A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state detection methods are especially on high demand for clinical consciousness monitoring. Traditional anesthesia monitoring methods are not involved with the topological changes between electrodes covering the prefrontal-parietal cortices, by investigating electrocorticography (ECoG). To fill this gap, a framework based on the two-stream graph convolutional network (GCN) was proposed, i.e., one stream for extracting topological structure features, and the other one for extracting node features. The two-stream graph convolutional network includes GCN Model 1 and GCN Model 2. For GCN Model 1, brain connectivity networks were constructed by using phase lag index (PLI), representing different structure features. A common adjacency matrix was founded through the dual-graph method, the structure features were expressed on nodes. Therefore, the traditional spectral graph convolutional network can be directly applied on the graphs with changing topological structures. On the other hand, the average of the absolute signal amplitudes was calculated as node features, then a fully connected matrix was constructed as the adjacency matrix of these node features, as the input of GCN Model 2. This method learns features of both topological structure and nodes of the graph, and uses a dual-graph approach to enhance the focus on topological structure features. Based on the ECoG signals of monkeys, results show that this method which can distinguish awake state, moderate sedation and deep sedation achieved an accuracy of 92.75% in group-level experiments and mean accuracy of 93.50% in subject-level experiments. Our work verifies the excellence of the graph convolutional network in anesthesia monitoring, the high recognition accuracy also shows that the brain network may carry neurological markers associated with anesthesia.

Priming Intermittent Theta Burst Stimulation for Hemiparetic Upper Limb After Stroke: A Randomized Controlled Trial

BACKGROUND

Intermittent theta burst stimulation (iTBS) creates a state with increased excitability that permits treatment modalities to induce neuroplasticity and motor learning. Continuous theta burst stimulation before iTBS may induce metaplasticity and boost the facilitatory effect of iTBS. This study investigated the effects of priming iTBS (ie, applying continuous theta burst stimulation before iTBS) on poststroke hemiparetic upper limb recovery.

METHODS

In this randomized controlled trial, 42 patients with chronic stroke were recruited and randomly allocated to 10 sessions of either priming iTBS, nonpriming iTBS, or sham stimulation to the ipsilesional motor cortex, immediately before robot-assisted training. Outcomes included Fugl-Meyer Assessment-Upper Extremity, Action Research Arm Test and mean movement velocity during each robot-assisted training session. Twenty-one patients were enrolled for measuring the sensorimotor beta event-related desynchronization induced by either mirror visual feedback or movement.

RESULTS

The Fugl-Meyer Assessment-Upper Extremity scores revealed a significant time-by-group interaction (P=0.011). Priming and nonpriming iTBS were both superior to sham stimulation in post hoc comparisons; however, the superiority was diminished at follow-up. Among patients with a higher functioning upper limb, priming iTBS yielded a significantly greater improvement in Fugl-Meyer Assessment-Upper Extremity scores than nonpriming iTBS (P=0.025) and sham stimulation (P=0.029) did. No significant interaction was found when analyzing the Action Research Arm Test and mean movement velocity. Priming iTBS enhanced the patients' mirror visual feedback-induced high beta sensorimotor event-related desynchronization over their ipsilesional hemisphere.

CONCLUSIONS

Priming and nonpriming iTBS are both superior to sham stimulation in enhancing treatment gains from robot-assisted training, and patients with a higher functioning upper limb may experience more benefits from priming iTBS. Priming iTBS may facilitate poststroke motor learning by enhancing the permissiveness of the ipsilesional sensorimotor area to therapeutic sensory modalities, such as the mirror visual feedback.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT04034069.

Brain Connectivity Analysis in Anesthetized and Awake States: an ECoG Study in Monkeys

Increasingly, studies have shown that changes in brain network topology accompany loss of consciousness such that the functional connectivity of the prefrontal-parietal network differs significantly in anesthetized and awake states. In this work, anesthetized and awake segments of electrocorticography were selected from two monkeys. Using phase lag index, functional connectivity matrices were built in multiple frequency bands. Quantifying topological changes in brain network through graph-theoretic properties revealed significant differences between the awake and anesthetized states. Compared to the awake state, there were distinct increases in overall and Delta prefrontal-frontal connectivity, and decreases in Alpha, Beta1 and Beta2 prefrontal-frontal connectivity during the anesthetized state, which indicate a change in the topology of the small-world network. Using functional connectivity features we achieved a satisfactory classification accuracy (93.68%). Our study demonstrates that functional connectivity features are of sufficient power to distinguish awake versus anesthetized state.Clinical Relevance- This explores the brain network topology in awake and anesthetized states, and provides new ideas for clinical depth of anesthesia monitoring.

Handedness effects on motor imagery during kinesthetic and visual-motor conditions

Recent studies show that during a simple movement imagery task, the power of sensorimotor rhythms differs according to handedness. However, the effects of motor imagery perspectives on these differences have not been investigated yet. Our study aimed to check how handedness impacts the activity of alpha (8-13 Hz) and beta (15-30 Hz) oscillations during creating a kinesthetic (KMI) or visual-motor (VMI) representation of movement. Forty subjects (20 right-handed and 20 left-handed) who participated in the experiment were tasked with imagining sequential finger movement from a visual or kinesthetic perspective. Both the electroencephalographic (EEG) activity and behavioral correctness of the imagery task performance were measured. After the registration, we used independent component analysis (ICA) on EEG data to localize visual- and motor-related EEG sources of activity shared by both motor imagery conditions. Significant differences were obtained in the visual cortex (the occipital ICs cluster) and the right motor-related area (right parietal ICs cluster). In comparison to right-handers who, regardless of the task, demonstrated the same pattern in the visual area, left-handers obtained higher power in the alpha waves in the VMI task and better performance in this condition. On the other hand, only the right-handed showed different patterns in the alpha waves in the right motor cortex during the KMI condition. The results indicate that left-handers imagine movement differently than right-handers, focusing on visual experience. This provides new empirical evidence on the influence of movement preferences on imagery processes and has possible future implications for research in the area of neurorehabilitation and motor imagery-based brain-computer interfaces (MI-BCIs).

Brain Patterns During Single- and Dual-Task Leg Movements

The brain is able to engage in dual tasks such as motor imagery (MI) and action observation (AO) or motor execution (ME) with action observation. In this study, we have quantitatively compared event-related desynchronization (ERD) patterns during tasks of pure MI, MI with AO (O-MI), ME, and ME with AO (O-ME) of the leg to investigate the underlying neuronal mechanisms using EEG. Subjects were instructed to imagine or perform rhythmical actions while watching a video of leg movements during O-MI and O-ME tasks; In contrast, subjects imagined and performed the leg movements without observing any video during pure MI and ME tasks. We noticed that the amplitude of ERDs from MI, O-MI, ME and O-ME sequentially increases in central regions of the brain. These quantified ERD patterns in EEG were used to study the differences of brain oscillatory changes among the four tasks. We found that ERDs in motor area were more distinct in O-MI, compared with pure MI. These results suggest that O-MI produced stronger motor activations than MI. Plus, O-ME showed significantly greater activations than ME in the beta band. O-ME has produced stronger neurophysiological effects than MI, and stronger behavioral effects than ME. These empirical results do provide convincing evidence of the dual tasks such combined MI or ME with action observation on brain pattern changes. The video of the goal-directed leg movements is most likely able to improve the ability of performing or imagining movements. O-MI and O-ME may get better and closer therapeutic effects in leg rehabilitation and motor skill training. Furthermore, the extent analysis of ERD may provide the basis for evaluating the ability of O-MI and O-ME in leg rehabilitation and motor skill training.

Disruptions of cortico-kinematic interactions in Parkinson's disease

The cortical role of the motor symptoms reflected by kinematic characteristics in Parkinson's disease (PD) is poorly understood. In this study, we aim to explore how PD affects cortico-kinematic interactions. Electroencephalographic (EEG) and kinematic data were recorded from seven healthy participants and eight participants diagnosed with PD during a set of self-paced finger tapping tasks. Event-related desynchronization (ERD) was compared between groups in the α (8-14 Hz), low-ß (14-20 Hz), and high-ß (20-35 Hz) frequency bands to investigate between-group differences in the cortical activities associated with movement. Average kinematic peak amplitudes and latencies were extracted alongside Sample Entropy (SaEn), a measure of signal complexity, as variables for comparison between groups. These variables were further correlated with average EEG power in each frequency band to establish within-group interactions between cortical motor functions and kinematic motor output. High ß-band power correlated with mean kinematic peak latency and signal complexity in the healthy group, while no correlation was found in the PD group. Also, the healthy group demonstrated stronger ERD in the broad ß-band than the PD participants. Our results suggest that cortical ß-band power in healthy populations is graded to finger tapping latency and complexity of movement, but this relationship is impaired in PD. These insights could help further enhance our understanding of the role of cortical ß-band oscillations in healthy movement and the possible disruption of that relationship in PD. These outcomes can provide further directions for treatment and therapeutic applications and potentially establish cortical biomarkers of Parkinson's disease.

Sustaining Attention for a Prolonged Duration Affects Dynamic Organizations of Frequency-Specific Functional Connectivity

Sustained attention encompasses a cascade of fundamental functions. The human ability to implement a sustained attention task is supported by brain networks that dynamically formed and dissolved through oscillatory synchronization. The decrement of vigilance induced by prolonged task engagement affects sustained attention. However, little is known about which stage or combinations are affected by vigilance decrement. Here, we applied an analysis framework composed of weighted phase lag index (wPLI) and tensor component analysis (TCA) to an EEG dataset collected during 80 min sustained attention task to examine the electrophysiological basis of such effect. We aimed to characterize the phase-coupling networks to untangle different phases involved in sustained attention and study how they are modulated by vigilance decrement. We computed the time–frequency domain wPLI from each block and subject and constructed a fourth-order tensor, containing the time, frequency, functional connectivity (FC), and blocks × subjects. This tensor was subjected to the TCA to identify the interacted and low-dimensional components representing the frequency-specific dynamic FC (fdFC). We extracted four types of neuromakers during a sustained attention task, namely the pre-stimulus alpha right-lateralized parieto-occipital FC, the post-stimulus theta fronto-parieto-occipital FC, delta fronto-parieto-occipital FC, and beta right/left sensorimotor FCs. All these fdFCs were impaired by vigilance decrement. These fdFCs, except for the beta left sensorimotor network, were restored by rewards, although the restoration by reward in the beta right sensorimotor network was transient. These findings provide implications for dissociable effects of vigilance decrement on sustained attention by utilizing the tensor-based framework.

Task-independent Electrophysiological Correlates of Motor Imagery Ability from Kinaesthetic and Visual Perspectives

Motor imagery (MI) ability is highly subjective, as indicated by the individual scores of the MIQ-3 questionnaire, and poor imagers compensate for the difficulty in performing MI with larger cerebral activations, as demonstrated by MI studies involving hands/limbs. In order to identify general, task-independent MI ability correlates, 16 volunteers were stratified with MIQ-3. The scores in the kinaesthetic (K) and 1st-person visual (V) perspectives were associated with EEG patterns obtained during K-MI and V-MI of the same complex MIQ-3 movements during these MI tasks (Spearman's correlation, significance at <0.05, SnPM corrected). EEG measures were relative to rest (relaxation, closed eyes), and based on six electrode clusters both for band spectral content and connectivity (Granger causality). Lower K-MI ability was associated with greater theta decreases during tasks in fronto-central clusters and greater inward information flow to prefrontal clusters for theta, high alpha and beta bands. On the other hand, power band relative decreases were associated with V-MI ability in fronto-central clusters for low alpha and left fronto-central and both centro-parietal clusters for beta bands. The results thus suggest different computational mechanisms for MI-V and MI-K. The association between low alpha/beta desynchronization and V-MIQ scores and between theta changes and K-MIQ scores suggest a cognitive effort with greater cerebral activation in participants with lower V-MI ability. The association between information flow to prefrontal hub and K-MI ability suggest the need for a continuous update of information to support MI-related executive functions in subjects with poor K-MI ability.

On the Better Performance of Pianists with Motor Imagery-Based Brain-Computer Interface Systems

Motor imagery (MI)-based brain-computer interface (BCI) systems detect electrical brain activity patterns through electroencephalogram (EEG) signals to forecast user intention while performing movement imagination tasks. As the microscopic details of individuals' brains are directly shaped by their rich experiences, musicians can develop certain neurological characteristics, such as improved brain plasticity, following extensive musical training. Specifically, the advanced bimanual motor coordination that pianists exhibit means that they may interact more effectively with BCI systems than their non-musically trained counterparts; this could lead to personalized BCI strategies according to the users' previously detected skills. This work assessed the performance of pianists as they interacted with an MI-based BCI system and compared it with that of a control group. The Common Spatial Patterns (CSP) and Linear Discriminant Analysis (LDA) machine learning algorithms were applied to the EEG signals for feature extraction and classification, respectively. The results revealed that the pianists achieved a higher level of BCI control by means of MI during the final trial (74.69%) compared to the control group (63.13%). The outcome indicates that musical training could enhance the performance of individuals using BCI systems.

Investigating Priming Effects of Physical Practice on Motor Imagery-Induced Event-Related Desynchronization

For motor imagery (MI) to be effective, an internal representation of the to-be-imagined movement may be required. A representation can be achieved through prior motor execution (ME), but the neural correlates of MI that are primed by ME practice are currently unknown. In this study, young healthy adults performed MI practice of a unimanual visuo-motor task (Group MI, n = 19) or ME practice combined with subsequent MI practice (Group ME&MI, n = 18) while electroencephalography (EEG) was recorded. Data analysis focused on the MI-induced event-related desynchronization (ERD). Specifically, changes in the ERD and movement times (MT) between a short familiarization block of ME (Block pre-ME), conducted before the MI or the ME combined with MI practice phase, and a short block of ME conducted after the practice phase (Block post-ME) were analyzed. Neither priming effects of ME practice on MI-induced ERD were found nor performance-enhancing effects of MI practice in general. We found enhancements of the ERD and MT in Block post-ME compared to Block pre-ME, but only for Group ME&MI. A comparison of ME performance measures before and after the MI phase indicated however that these changes could not be attributed to the combination of ME and MI practice. The mixed results of this study may be a consequence of the considerable intra- and inter-individual differences in the ERD, introduced by specifics of the experimental setup, in particular the individual and variable task duration, and suggest that task and experimental setup can affect the interplay of ME and MI.

What Perceivers Know About Their Own Affordance Perception: Post Hoc Evaluations of Perceptual Processes Do Not Relate to Accuracy

In 2 studies, we sought to investigate participants’ awareness of their own cognitive process when perceiving affordances (i.e., action capabilities) and whether their evaluations of this process relate to affordance perception accuracy. In Study 1, we combined data from 8 experiments and created a coding scheme designed to capture the unique features of different affordance perception theories within these post hoc evaluations. We then tested whether the perceptual process that participants reported was related to the accuracy of their judgments. We found that evaluations were distributed fairly evenly across the themes. We also found no relationship between the evaluations and accuracy. In Study 2, we conducted an experiment that specifically addressed our hypotheses about awareness and affordance perception accuracy, while controlling for confounds in Study 1. The greater detail participants gave about their cognitive strategy produced reports that largely did not relate to affordance perception theories. Participants used one of a few strategies aimed at estimating their body dimensions. Our results suggest that awareness of the perceptual process has no influence on the accuracy of affordance perception. It is likely that subjective reports of affordance perceptual process, though clear to the perceiver, are not related to the process itself.