EEG changes during sequences of visual and kinesthetic motor imagery

Characterization and classification of kinesthetic motor imagery levels

Objective.Kinesthetic Motor Imagery (KMI) represents a robust brain paradigm intended for electroencephalography (EEG)-based commands in brain-computer interfaces (BCIs). However, ensuring high accuracy in multi-command execution remains challenging, with data from C3 and C4 electrodes reaching up to 92% accuracy. This paper aims to characterize and classify EEG-based KMI of multilevel muscle contraction without relying on primary motor cortex signals.Approach.A new method based on Hurst exponents is introduced to characterize EEG signals of multilevel KMI of muscle contraction from electrodes placed on the premotor, dorsolateral prefrontal, and inferior parietal cortices. EEG signals were recorded during a hand-grip task at four levels of muscle contraction (0%, 10%, 40%, and 70% of the maximal isometric voluntary contraction). The task was executed under two conditions: first, physically, to train subjects in achieving muscle contraction at each level, followed by mental imagery under the KMI paradigm for each contraction level. EMG signals were recorded in both conditions to correlate muscle contraction execution, whether correct or null accurately. Independent component analysis (ICA) maps EEG signals from the sensor to the source space for preprocessing. For characterization, three algorithms based on Hurst exponents were used: the original (HO), using partitions (HRS), and applying semivariogram (HV). Finally, seven classifiers were used: Bayes network (BN), naive Bayes (NB), support vector machine (SVM), random forest (RF), random tree (RT), multilayer perceptron (MP), and k-nearest neighbors (kNN).Main results.A combination of the three Hurst characterization algorithms produced the highest average accuracy of 96.42% from kNN, followed by MP (92.85%), SVM (92.85%), NB (91.07%), RF (91.07%), BN (91.07%), and RT (80.35%). of 96.42% for kNN.Significance.Results show the feasibility of KMI multilevel muscle contraction detection and, thus, the viability of non-binary EEG-based BCI applications without using signals from the motor cortex.

The effect of combining action observation in virtual reality with kinesthetic motor imagery on cortical activity

Introduction

In the past, various techniques have been used to improve motor imagery (MI), such as immersive virtual-reality (VR) and kinesthetic rehearsal. While electroencephalography (EEG) has been used to study the differences in brain activity between VR-based action observation and kinesthetic motor imagery (KMI), there has been no investigation into their combined effect. Prior research has demonstrated that VR-based action observation can enhance MI by providing both visual information and embodiment, which is the perception of oneself as part of the observed entity. Additionally, KMI has been found to produce similar brain activity to physically performing a task. Therefore, we hypothesized that utilizing VR to offer an immersive visual scenario for action observation while participants performed kinesthetic motor imagery would significantly improve cortical activity related to MI.

Methods

In this study, 15 participants (9 male, 6 female) performed kinesthetic motor imagery of three hand tasks (drinking, wrist flexion-extension, and grabbing) both with and without VR-based action observation.

Results

Our results indicate that combining VR-based action observation with KMI enhances brain rhythmic patterns and provides better task differentiation compared to KMI without action observation.

Discussion

These findings suggest that using VR-based action observation alongside kinesthetic motor imagery can improve motor imagery performance.

Repetitive Peripheral Magnetic Stimulation Combined with Motor Imagery Changes Resting-State EEG Activity: A Randomized Controlled Trial

Repetitive peripheral magnetic stimulation is a novel non-invasive technique for applying repetitive magnetic stimulation to the peripheral nerves and muscles. Contrarily, a person imagines that he/she is exercising during motor imagery. Resting-state electroencephalography can evaluate the ability of motor imagery; however, the effects of motor imagery and repetitive peripheral magnetic stimulation on resting-state electroencephalography are unknown. We examined the effects of motor imagery and repetitive peripheral magnetic stimulation on the vividness of motor imagery and resting-state electroencephalography. The participants were divided into a motor imagery group and motor imagery and repetitive peripheral magnetic stimulation group. They performed 60 motor imagery tasks involving wrist dorsiflexion movement. In the motor imagery and repetitive peripheral magnetic stimulation group, we applied repetitive peripheral magnetic stimulation to the extensor carpi radialis longus muscle during motor imagery. We measured the vividness of motor imagery and resting-state electroencephalography before and after the task. Both groups displayed a significant increase in the vividness of motor imagery. The motor imagery and repetitive peripheral magnetic stimulation group exhibited increased β activity in the anterior cingulate cortex by source localization for electroencephalography. Hence, combined motor imagery and repetitive peripheral magnetic stimulation changes the resting-state electroencephalography activity and may promote motor imagery.

Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm

Motor imagery (MI) refers to the mental rehearsal of movement in the absence of overt motor action, which can activate or inhibit cortical excitability. EEG mu/beta oscillations recorded over the human motor cortex have been shown to be consistently suppressed during both the imagination and performance of movements, although the specific effect on brain function remains to be confirmed. In this study, Granger causality (GC) was used to construct the brain functional network of subjects during motor imagery and resting state based on EEG in order to explore the effects of motor imagery on brain function. Parameters of the brain functional network were compared and analyzed, including degree, clustering coefficient, characteristic path length and global efficiency of EEG mu/beta rhythm in different states. The results showed that the clustering coefficient and efficiency of EEG mu/beta rhythm decreased significantly during motor imagery (p < 0.05), while degree distribution and characteristic path length increased significantly (p < 0.05), mainly concentrated in the frontal lobe and sensorimotor area. For the resting state after motor imagery, the changes of brain functional characteristics were roughly similar to those of the task state. Therefore, it is concluded that motor imagery plays an important role in activation of cortical excitability.

Methylphenidate decreases the EEG mu power in the right primary motor cortex in healthy adults during motor imagery and execution

This study investigated the effects of dopaminergic drugs on the EEG mu power during motor imagery, action observation, and execution. This is a double-blind, crossover study with a sample of 15 healthy adults under placebo vs. methylphenidate vs. risperidone conditions during motor imagery, action observation, and execution tasks. The participants had drug dosage adjustment based on body weight/dose (mg/kg). We also analyzed the mu band power by electroencephalography during the study steps. The main result is the interaction between the condition and task factors for the C3 and C4 electrodes, with decreasing EEG mu power in the methylphenidate when compared to risperidone (p ≤ 0.0083). Our results can indicate that the methylphenidate decreases the neurophysiological activity in the central cortical regions during the perceptual experience of tasks with or without body movement.

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.

Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity

Motor imagery is often used inducing changes in electroencephalographic (EEG) signals for imagery-based brain-computer interfacing (BCI). A BCI is a device translating brain signals into control signals providing severely motor-impaired persons with an additional, non-muscular channel for communication and control. In the last years, there is increasing interest using BCIs also for healthy people in terms of enhancement or gaming. Most studies focusing on improving signal processing feature extraction and classification methods, but the performance of a BCI can also be improved by optimizing the user's control strategies, e.g., using more vivid and engaging mental tasks for control. We used multichannel EEG to investigate neural correlates of a sports imagery task (playing tennis) compared to a simple motor imagery task (squeezing a ball). To enhance the vividness of both tasks participants performed a short physical exercise between two imagery sessions. EEG was recorded from 60 closely spaced electrodes placed over frontal, central, and parietal areas of 30 healthy volunteers divided in two groups. Whereas Group 1 (EG) performed a physical exercise between the two imagery sessions, Group 2 (CG) watched a landscape movie without physical activity. Spatiotemporal event-related desynchronization (ERD) and event-related synchronization (ERS) patterns during motor imagery (MI) tasks were evaluated. The results of the EG showed significant stronger ERD patterns in the alpha frequency band (8-13 Hz) during MI of tennis after training. Our results are in evidence with previous findings that MI in combination with motor execution has beneficial effects. We conclude that sports MI combined with an interactive game environment could be a future promising task in motor learning and rehabilitation improving motor functions in late therapy processes or support neuroplasticity.

EEG Brain Activity in Dynamic Health Qigong Training: Same Effects for Mental Practice and Physical Training?

In recent years, there has been significant uptake of meditation and related relaxation techniques, as a means of alleviating stress and fostering an attentive mind. Several electroencephalogram (EEG) studies have reported changes in spectral band frequencies during Qigong meditation indicating a relaxed state. Much less is reported on effects of brain activation patterns induced by Qigong techniques involving bodily movement. In this study, we tested whether (1) physical Qigong training alters EEG theta and alpha activation, and (2) mental practice induces the same effect as a physical Qigong training. Subjects performed the dynamic Health Qigong technique Wu Qin Xi (five animals) physically and by mental practice in a within-subjects design. Experimental conditions were randomized. Two 2-min (eyes-open, eyes-closed) EEG sequences under resting conditions were recorded before and immediately after each 15-min exercise. Analyses of variance were performed for spectral power density data. Increased alpha power was found in posterior regions in mental practice and physical training for eyes-open and eyes-closed conditions. Theta power was increased after mental practice in central areas in eyes-open conditions, decreased in fronto-central areas in eyes-closed conditions. Results suggest that mental, as well as physical Qigong training, increases alpha activity and therefore induces a relaxed state of mind. The observed differences in theta activity indicate different attentional processes in physical and mental Qigong training. No difference in theta activity was obtained in physical and mental Qigong training for eyes-open and eyes-closed resting state. In contrast, mental practice of Qigong entails a high degree of internalized attention that correlates with theta activity, and that is dependent on eyes-open and eyes-closed resting state.

Neural plasticity during motor learning with motor imagery practice: Review and perspectives

In the last decade, many studies confirmed the benefits of mental practice with motor imagery. In this review we first aimed to compile data issued from fundamental and clinical investigations and to provide the key-components for the optimization of motor imagery strategy. We focused on transcranial magnetic stimulation studies, supported by brain imaging research, that sustain the current hypothesis of a functional link between cortical reorganization and behavioral improvement. As perspectives, we suggest a model of neural adaptation following mental practice, in which synapse conductivity and inhibitory mechanisms at the spinal level may also play an important role.

The influence of motor imagery on the learning of a fine hand motor skill

Motor imagery has been argued to affect the acquisition of motor skills. The present study examined the specificity of motor imagery on the learning of a fine hand motor skill by employing a modified discrete sequence production task: the Go/NoGo DSP task. After an informative cue, a response sequence had either to be executed, imagined, or withheld. To establish learning effects, the experiment was divided into a practice phase and a test phase. In the latter phase, we compared mean response times and accuracy during the execution of unfamiliar sequences, familiar imagined sequences, and familiar executed sequences. The electroencephalogram was measured in the practice phase to compare activity between motor imagery, motor execution, and a control condition in which responses should be withheld. Event-related potentials (ERPs) and event-related lateralizations (ERLs) showed strong similarities above cortical motor areas on trials requiring motor imagery and motor execution, while a major difference was found with trials on which the response sequence should be withheld. Behavioral results from the test phase showed that response times and accuracy improved after physical and mental practice relative to unfamiliar sequences (so-called sequence-specific learning effects), although the effect of motor learning by motor imagery was smaller than the effect of physical practice. These findings confirm that motor imagery also resembles motor execution in the case of a fine hand motor skill.

Effect of Gait Imagery Tasks on Lower Limb Muscle Activity With Respect to Body Posture

The objective of this study was to evaluate the effect of gait imagery tasks on lower limb muscle activity with respect to body posture. The sitting and standing position and lower limb muscle activity were evaluated in 27 healthy female students (24.4 ± 1.3 years, 167.2 ± 5.2 cm, 60.10 ± 6.4 kg). Surface electromyography was assessed during rest and in three different experimental conditions using mental imagery. These included a rhythmic gait, rhythmic gait simultaneously with observation of a model, and rhythmic gait after performing rhythmic gait. The normalized root mean square EMG values with respect to corresponding rest position were compared using non-parametric statistics. Standing gait imagery tasks had facilitatory effect on proximal lower limb muscle activity. However, electromyography activity of distal leg muscles decreased for all gait imagery tasks in the sitting position, when the proprioceptive feedback was less appropriate. For subsequent gait motor imagery tasks, the muscle activity decreased, probably as result of habituation. In conclusion, the effect of motor imagery on muscle activity appears to depend on relative strength of facilitatory and inhibitory inputs.

The effect of neurofeedback on a brain wave and visual perception in stroke: a randomized control trial

[Purpose] This study investigated a brain wave and visual perception changes in stroke subjects using neurofeedback (NFB) training. [Subjects] Twenty-seven stroke subjects were randomly allocated to the NFB (n = 13) group and the control group (n=14). [Methods] Two expert therapists provided the NFB and CON groups with traditional rehabilitation therapy in 30 thirst-minute sessions over the course of 6 weeks. NFB training was provided only to the NFB group. The CON group received traditional rehabilitation therapy only. Before and after the 6-week intervention, a brain wave test and motor free visual perception test (MVPT) were performed. [Results] Both groups showed significant differences in their relative beta wave values and attention concentration quotients. Moreover, the NFB group showed a significant difference in MVPT visual discrimination, form constancy, visual memory, visual closure, spatial relation, raw score, and processing time. [Conclusion] This study demonstrated that NFB training is more effective for increasing concentration and visual perception changes than traditional rehabilitation. In further studies, detailed and diverse investigations should be performed considering the number and characteristics of subjects, and the NFB training period.

Comparative analysis electroencephalographic of alpha, Beta and gamma bands of a healthy individual and one with hemiparesis

[Purpose] The study analyzed the electroencephalographic (EEG) data of the central cortical areas, during execution of the motor gestures of feeding, activation of the system of mirror neurons, and imagery between a right hemiparetic volunteer (RHV) and a healthy volunteer (HV). [Subjects and Methods] The volunteers’ EEG data were recorded with their eyes open for 4 minutes while they performed five experimental tasks. [Results] The alpha band, absolute power value of HV was lower than that of RHV. In the beta band, during the practice condition, there was an increase in the magnitude of the absolute power value of HV at T3, possibly because T3 is representative of secondary motor areas that work with cortical neurons related to planning and organizing sequence of movements performed by the hands. The gamma band is related to the state of preparation for movement and memory. The results of this study indicate that there was increased activation of the gamma frequency band of HV. [Conclusion] The findings of this study have revealed the changes in pattern characteristics of each band which may be associated with the brain injury of the hemiparetic patient.

Design of the multi-channel electroencephalography-based brain-computer interface with novel dry sensors

The traditional brain-computer interface (BCI) system measures the electroencephalography (EEG) signals by the wet sensors with the conductive gel and skin preparation processes. To overcome the limitations of traditional BCI system with conventional wet sensors, a wireless and wearable multi-channel EEG-based BCI system is proposed in this study, including the wireless EEG data acquisition device, dry spring-loaded sensors, a size-adjustable soft cap. The dry spring-loaded sensors are made of metal conductors, which can measure the EEG signals without skin preparation and conductive gel. In addition, the proposed system provides a size-adjustable soft cap that can be used to fit user's head properly. Indeed, the results are shown that the proposed system can properly and effectively measure the EEG signals with the developed cap and sensors, even under movement. In words, the developed wireless and wearable BCI system is able to be used in cognitive neuroscience applications.

Befunde aus EEG-Untersuchungen zum Mentalen Training

Mentales Training (MT) im Sinne der planmäßig wiederholten Vorstellung eines Bewegungsablaufes ist ein zentraler Gegenstand sportpsychologischer Forschung. Im Hochleistungssport und in der Rehabilitation wird es zur Optimierung von Bewegungen eingesetzt. Einen Erklärungsansatz der Trainingswirkung bietet die Simulationstheorie mit dem zentralen Postulat, dass Bewegungsausführung und -vorstellung gleiche neuronale Strukturen aktivieren (funktionale Äquivalenz). Diese Annahme wurde mittels verschiedener neurophysiologischer Methoden geprüft, die teils zu widersprüchlichen Befunden führten. Die Elektroenzephalographie (EEG) kann unserer Ansicht nach dabei helfen, Lücken im theoretischen Erkenntnisprozess zu schließen. In diesem Artikel geben wir einen Überblick über die aktuelle Befundlage zum Mentalen Training mittels EEG. Es sollen drei wesentliche Vorteile der Methode aufgezeigt werden: (a) das EEG liefert Maße der neurophysiologischen Aktivität mit hoher zeitlicher Auflösung, (b) technische Weiterentwicklungen (drahtlose Hardware, tragbare Ausrüstung) erlauben die notwendige Bewegungsfreiheit für eine Anwendung im Sportkontext und (c) in der Rehabilitation kann die Vorstellung von Bewegungen als mentale Strategie dienen, um eine Neuroprothese auf Basis von Hirnsignalen zu steuern.