Electroencephalographic Recording of the Movement-Related Cortical Potential in Ecologically Valid Movements: A Scoping Review

Toward brain-computer interface speller with movement-related cortical potentials as control signals

Brain Computer Interface spellers offer a promising alternative for individuals with Amyotrophic Lateral Sclerosis (ALS) by facilitating communication without relying on muscle activity. This study assessed the feasibility of using movement related cortical potentials (MRCPs) as a control signal for a Brain-Computer Interface speller in an offline setting. Unlike motor imagery-based BCIs, this study focused on executed movements. Fifteen healthy subjects performed three spelling tasks that involved choosing specific letters displayed on a computer screen by performing a ballistic dorsiflexion of the dominant foot. Electroencephalographic signals were recorded from 10 sites centered around Cz. Three conditions were tested to evaluate MRCP performance under varying task demands: a control condition using repeated selections of the letter "O" to isolate movement-related brain activity; a phrase spelling condition with structured text ("HELLO IM FINE") to simulate a meaningful spelling task with moderate cognitive load; and a random condition using a randomized sequence of letters to introduce higher task complexity by removing linguistic or semantic context. The success rate, defined as the presence of an MRCP, was manually determined. It was approximately 69% for both the control and phrase conditions, with a slight decrease in the random condition, likely due to increased task complexity. Significant differences in MRCP features were observed between conditions with Laplacian filtering, whereas no significant differences were found in single-site Cz recordings. These results contribute to the development of MRCP-based BCI spellers by demonstrating their feasibility in a spelling task. However, further research is required to implement and validate real-time applications.

Orthographic character complexity modulates dynamic neural activity in skilled handwriting

Handwriting is an outstanding case of a highly complex and efficient fine motor skill. However, little is known about its neural underpinnings during continuous handwriting production. In the present study, we examined the effects of orthographic character complexity (i.e. the stroke number of a Chinese character) on both neural and behavioural activities during an EEG-based naturalistic fluent sentence-handwriting task from 102 adult Chinese native speakers. For each written character, the interval between finishing the preceding character and its onset (inter-character interval) as well as the amplitudes of the onset-synchronized event-related potential (ERP) in pre- and post-onset time windows was defined as dependent variables. The effects of character complexity and other confounding factors were analysed with linear mixed models. Character complexity increased the inter-character interval and significantly affected ERP amplitudes in both pre- and post-onset time windows. The ERP pattern in the pre-event time window exhibited a dipole-like activation in the left motor cortex, and its amplitude increased with character complexity in line with the documented relationship between the lateralized readiness potential and motor complexity. This study demonstrates the feasibility of studying neurocognitive processes in complex naturalistic motor tasks and extends our knowledge about the dynamic pattern of handwriting-related neural activities.

Associative brain-computer interface training increases wrist extensor corticospinal excitability in patients with subacute stroke

In a recently developed associative rehabilitative brain-computer interface (BCI) system, electroencephalography (EEG) is used to identify the most active phase of the motor cortex during attempted movement and deliver precisely timed peripheral stimulation during training. This approach has been demonstrated to facilitate corticospinal excitability and functional recovery in patients with lower limb weakness following stroke. The current study expands those findings by investigating changes in corticospinal excitability following the associative BCI intervention in patients with post stroke with upper limb weakness. In a randomized controlled trial, 24 patients with subacute stroke, subdivided into an intervention group and a "sham" control group, performed 30 wrist extensions. The intervention comprised 30 pairings of single peripheral nerve stimulation at the motor threshold, timed so that the generated afferent volley arrived at the motor cortex during the peak negativity of the movement-related cortical potential (MRCP), which was identified with EEG. The sham group underwent the same intervention, though the intensity of the nerve stimulation was below the perception threshold. Immediately after training, patients in the associative group exhibited significantly larger amplitudes of muscular-evoked potentials, compared with pretraining measurements in response to transcranial magnetic stimulation. These changes persisted for at least 30 min and were not observed in the sham group. We demonstrate that motor-evoked potential amplitudes increased significantly following paired associative BCI training targeting upper limb muscles in patients with subacute stroke, which is in line with results from lower limb studies.NEW & NOTEWORTHY We have demonstrated that a single training session with an associative brain-computer interface increased corticospinal excitability in patients suffering from upper limb weakness following stroke. This is the first time such an effect is described in the upper limb, which paves the way for effect augmentation of existing upper limb rehabilitation protocols.

Low-Frequency Motor Cortex EEG Predicts Four Rates of Force Development

The movement-related cortical potential (MRCP) is a low-frequency component of the electroencephalography (EEG) signal that originates from the motor cortex and surrounding cortical regions. As the MRCP reflects both the intention and execution of motor control, it has the potential to serve as a communication interface between patients and neurorehabilitation robots. In this study, we investigated the EEG signal recorded centered at the Cz electrode with the aim of decoding four rates of force development (RFD) during isometric contractions of the tibialis anterior muscle. The four levels of RFD were defined with respect to the maximum voluntary contraction (MVC) of the muscle as follows: Slow (20% MVC/s), Medium (30% MVC/s), Fast (60% MVC/s), and Ballistic (120% MVC/s). Three feature sets were assessed for describing the EEG traces in the classification process. These included: (i) MRCP Morphological Characteristics in the -band, such as timing and amplitude; (ii) MRCP Statistical Characteristics in the -band, such as standard deviation, mean, and kurtosis; and (iii) Wideband Time-frequency Features in the 0.1-90 Hz range. The four levels of RFD were accurately classified using a support vector machine. When utilizing the Wideband Time-frequency Features, the accuracy was 83% 9% (mean SD). Meanwhile, when using the MRCP Statistical Characteristics, the accuracy was 78% 12% (mean SD). The analysis of the MRCP waveform revealed that it contains highly informative data on the planning, execution, completion, and duration of the isometric dorsiflexion task. The temporal analysis emphasized the importance of the -band in translating to motor command, and this has promising implications for the field of neural engineering systems.

Brain (EEG) and muscle (EMG) activity related to 3D sit-to-stand kinematics in healthy adults and in central neurological pathology - A systematic review

BACKGROUND

The sit-to-stand transfer is a fundamental functional movement during normal activities of daily living. Central nervous system disorders can negatively impact the execution of sit-to-stand transfers, often impeding successful completion. Despite its importance, the neurophysiological basis at muscle (electromyography (EMG)) and brain (electroencephalography (EEG)) level as related to the kinematic movement is not well understood.

OBJECTIVES

This review synthesises the published literature addressing central and peripheral neural activity during 3D kinematic capture of sit-to-stand transfers.

METHODS

A pre-registered systematic review was conducted. Electronic databases (PubMed, CINAHL Plus, Web of Science, Scopus and EMBASE) were searched from inception using search operators that included sit-to-stand, kinematics and EMG and/or EEG. The search was not limited by study type but was limited to populations comprising of healthy individuals or individuals with a central neurological pathology.

RESULTS

From a total of 28,770 identified papers, 59 were eligible for inclusion. Ten of these 59 studies received a moderate quality rating; with the remainder rated as weak using the Effective Public Health Practice Project tool. Fifty-eight studies captured kinematic data of sit-to-stand with associated EMG activity only and one study captured kinematics with co-registered EMG and EEG data. Fifty-six studies examined sit-to-stand transfer in healthy individuals, reporting four dynamic movement phases and three muscle synergies commonly used by most individuals to stand-up. Pre-movement EEG activity was reported in one study with an absence of data during execution. Eight studies examined participants following stroke and two examined participants with Parkinson's disease, both reporting no statistically significant differences between their kinematics and muscle activity and those of healthy controls.

SIGNIFICANCE

Little is known about the neural basis of the sit-to-stand transfer at brain level with limited focus in central neurological pathology. This poses a barrier to targeted mechanistic-based rehabilitation of the sit-to-stand movement in neurological populations.

Effects of divided attention on movement-related cortical potential in community-dwelling elderly adults: A preliminary study

Dual-tasking is defined as performing two or more tasks concurrently. This study aimed to investigate the effect of divided attention on movement-related cortical potential (MRCP) during dual-task performance in 11 community-dwelling elderly individuals while the load of the secondary task was altered. MRCP was recorded during a single task (ST), simple dual task (S-DT), and complex dual task (C-DT) as no-, low-, and high-load divided attention tasks, respectively. The ST involved self-paced tapping with an extended right index finger. In the S-DT and C-DT, the subjects simultaneously performed the ST and a visual number counting task with different levels of load. The coefficient of variation of movement frequency was significantly more variable in the C-DT than in the ST. The MRCP amplitude from electroencephalography electrode C3, contralateral to the moving hand, was significantly higher in the C-DT than in the ST. Higher attention diversion led to a significant reduction in MRCP amplitude in the participants. These results suggest that attention division in dual-task situations plays an important role in movement preparation and execution. We propose that MRCP can serve as a marker for screening the ability of older individuals to perform dual-tasks.

The Effect of Caffeine on Movement-Related Cortical Potential Morphology and Detection

Movement-related cortical potential (MRCP) is observed in EEG recordings prior to a voluntary movement. It has been used for e.g., quantifying motor learning and for brain-computer interfacing (BCIs). The MRCP amplitude is affected by various factors, but the effect of caffeine is underexplored. The aim of this study was to investigate if a cup of coffee with 85 mg caffeine modulated the MRCP amplitude and the classification of MRCPs versus idle activity, which estimates BCI performance. Twenty-six healthy participants performed 2 × 100 ankle dorsiflexion separated by a 10-min break before a cup of coffee was consumed, followed by another 100 movements. EEG was recorded during the movements and divided into epochs, which were averaged to extract three average MRCPs that were compared. Also, idle activity epochs were extracted. Features were extracted from the epochs and classified using random forest analysis. The MRCP amplitude did not change after consuming caffeine. There was a slight increase of two percentage points in the classification accuracy after consuming caffeine. In conclusion, a cup of coffee with 85 mg caffeine does not affect the MRCP amplitude, and improves MRCP-based BCI performance slightly. The findings suggest that drinking coffee is only a minor confounder in MRCP-related studies.

A causal perspective on brainwave modeling for brain-computer interfaces

Objective. Machine learning (ML) models have opened up enormous opportunities in the field of brain-computer Interfaces (BCIs). Despite their great success, they usually face severe limitations when they are employed in real-life applications outside a controlled laboratory setting.Approach. Mixing causal reasoning, identifying causal relationships between variables of interest, with brainwave modeling can change one's viewpoint on some of these major challenges which can be found in various stages in the ML pipeline, ranging from data collection and data pre-processing to training methods and techniques.Main results. In this work, we employ causal reasoning and present a framework aiming to breakdown and analyze important challenges of brainwave modeling for BCIs.Significance. Furthermore, we present how general ML practices as well as brainwave-specific techniques can be utilized and solve some of these identified challenges. And finally, we discuss appropriate evaluation schemes in order to measure these techniques' performance and efficiently compare them with other methods that will be developed in the future.

Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy

In the realm of motor rehabilitation, Brain-Computer Interface Neurofeedback Training (BCI-NFT) emerges as a promising strategy. This aims to utilize an individual's brain activity to stimulate or assist movement, thereby strengthening sensorimotor pathways and promoting motor recovery. Employing various methodologies, BCI-NFT has been shown to be effective for enhancing motor function primarily of the upper limb in stroke, with very few studies reported in cerebral palsy (CP). Our main objective was to develop an electroencephalography (EEG)-based BCI-NFT system, employing an associative learning paradigm, to improve selective control of ankle dorsiflexion in CP and potentially other neurological populations. First, in a cohort of eight healthy volunteers, we successfully implemented a BCI-NFT system based on detection of slow movement-related cortical potentials (MRCP) from EEG generated by attempted dorsiflexion to simultaneously activate Neuromuscular Electrical Stimulation which assisted movement and served to enhance sensory feedback to the sensorimotor cortex. Participants also viewed a computer display that provided real-time visual feedback of ankle range of motion with an individualized target region displayed to encourage maximal effort. After evaluating several potential strategies, we employed a Long short-term memory (LSTM) neural network, a deep learning algorithm, to detect the motor intent prior to movement onset. We then evaluated the system in a 10-session ankle dorsiflexion training protocol on a child with CP. By employing transfer learning across sessions, we could significantly reduce the number of calibration trials from 50 to 20 without compromising detection accuracy, which was 80.8% on average. The participant was able to complete the required calibration trials and the 100 training trials per session for all 10 sessions and post-training demonstrated increased ankle dorsiflexion velocity, walking speed and step length. Based on exceptional system performance, feasibility and preliminary effectiveness in a child with CP, we are now pursuing a clinical trial in a larger cohort of children with CP.

The Impact of Mental Fatigue on a Strength Endurance Task: Is There a Role for the Movement-Related Cortical Potential?

PURPOSE

Several mechanisms have been proposed to explain how mental fatigue degrades sport performance. In terms of endurance performance, a role for an increased perceived exertion has been demonstrated. Using electroencephalography and, more specifically, the movement-related cortical potential (MRCP), the present study explored the neural mechanisms that could underlie the mental fatigue-associated increase in perceived exertion.

METHODS

Fourteen participants (age, 23 ± 2 yr; 5 women, 9 men) performed one familiarization and two experimental trials in a randomized, blinded, crossover study design. Participants had to complete a submaximal leg extension task after a mentally fatiguing task (EXP; individualized 60-min Stroop task) or control task (CON; documentary). The leg extension task consisted of performing 100 extensions at 35% of 1 repetition maximum, during which multiple physiological (heart rate, electroencephalography) and subjective measures (self-reported feeling of mental fatigue, cognitive load, behand motivation, ratings of perceived exertion) were assessed.

RESULTS

Self-reported feeling of mental fatigue was higher in EXP (72 ± 18) compared with CON (37 ± 17; P < 0.001). A significant decrease in flanker accuracy was detected only in EXP (from 0.96 ± 0.03% to 0.03%; P < 0.05). No significant differences between conditions were found in MRCP characteristics and perceived exertion. Specifically in EXP, alpha wave power increased during the leg extension task ( P < 0.01).

CONCLUSIONS

Mental fatigue did not impact the perceived exertion or MRCP characteristics during the leg extension task. This could be related to low perceived exertion and/or the absence of a performance outcome during the leg extension task. The increase in alpha power during the leg extension task in EXP suggests that participants may engage a focused internal attention mechanism to maintain performance and mitigate feelings of fatigue.

Comparing movement-related cortical potential between real and simulated movement tasks from an ecological validity perspective

Introduction

Concerns regarding the ecological validity of movement-related cortical potential (MRCP) experimental tasks that are related to motor learning have recently been growing. Therefore, we compared MRCP during real movement task (RMT) and simulated movement task (SMT) from an ecological validity perspective.

Methods

The participants performed both RMT and SMT, and MRCP were measured using electroencephalogram (EEG). EEG was based on the 10-20 method, with electrodes placed in the motor cortex (C3 and C4) and supplementary motor cortex (FCz [between Fz and Cz] and Cz) areas. This experiment examined the MRCP using Bereitschaftspotential (BP) and negative slope (NS') onset times, and BP, NS', and motor potential (MP) amplitudes during the task.

Results

The results revealed that the SMT exhibited later BP and NS' onset times and smaller BP, NS', and MP amplitudes than the RMT. Furthermore, in RMT, the onset time of MRCP was delayed, and the amplitude of MRCP was smaller in the second half of the 200 times task than in the first half, whereas in SMT, there was no change in onset time and amplitude. The SMT showed a different MRCP than the RMT, suggesting that the ecological validity of the task should be fully considered when investigating the cortical activity associated with motor skill learning using MRCP.

Conclusion

Ecological validity of the study should be fully considered when investigating the cortical activity associated with motor skill learning using MRCP. Moreover, it is important to understand the differences between the two methods when applied clinically.

A review of combined functional neuroimaging and motion capture for motor rehabilitation

BACKGROUND

Technological advancements in functional neuroimaging and motion capture have led to the development of novel methods that facilitate the diagnosis and rehabilitation of motor deficits. These advancements allow for the synchronous acquisition and analysis of complex signal streams of neurophysiological data (e.g., EEG, fNIRS) and behavioral data (e.g., motion capture). The fusion of those data streams has the potential to provide new insights into cortical mechanisms during movement, guide the development of rehabilitation practices, and become a tool for assessment and therapy in neurorehabilitation.

RESEARCH OBJECTIVE

This paper aims to review the existing literature on the combined use of motion capture and functional neuroimaging in motor rehabilitation. The objective is to understand the diversity and maturity of technological solutions employed and explore the clinical advantages of this multimodal approach.

METHODS

This paper reviews literature related to the combined use of functional neuroimaging and motion capture for motor rehabilitation following the PRISMA guidelines. Besides study and participant characteristics, technological aspects of the used systems, signal processing methods, and the nature of multimodal feature synchronization and fusion were extracted.

RESULTS

Out of 908 publications, 19 were included in the final review. Basic or translation studies were mainly represented and based predominantly on healthy participants or stroke patients. EEG and mechanical motion capture technologies were most used for biomechanical data acquisition, and their subsequent processing is based mainly on traditional methods. The system synchronization techniques at large were underreported. The fusion of multimodal features mainly supported the identification of movement-related cortical activity, and statistical methods were occasionally employed to examine cortico-kinematic relationships.

CONCLUSION

The fusion of motion capture and functional neuroimaging might offer advantages for motor rehabilitation in the future. Besides facilitating the assessment of cognitive processes in real-world settings, it could also improve rehabilitative devices' usability in clinical environments. Further, by better understanding cortico-peripheral coupling, new neuro-rehabilitation methods can be developed, such as personalized proprioceptive training. However, further research is needed to advance our knowledge of cortical-peripheral coupling, evaluate the validity and reliability of multimodal parameters, and enhance user-friendly technologies for clinical adaptation.

DiSCIoser: unlocking recovery potential of arm sensorimotor functions after spinal cord injury by promoting activity-dependent brain plasticity by means of brain-computer interface technology: a randomized controlled trial to test efficacy

BACKGROUND

Traumatic cervical spinal cord injury (SCI) results in reduced sensorimotor abilities that strongly impact on the achievement of daily living activities involving hand/arm function. Among several technology-based rehabilitative approaches, Brain-Computer Interfaces (BCIs) which enable the modulation of electroencephalographic sensorimotor rhythms, are promising tools to promote the recovery of hand function after SCI. The "DiSCIoser" study proposes a BCI-supported motor imagery (MI) training to engage the sensorimotor system and thus facilitate the neuroplasticity to eventually optimize upper limb sensorimotor functional recovery in patients with SCI during the subacute phase, at the peak of brain and spinal plasticity. To this purpose, we have designed a BCI system fully compatible with a clinical setting whose efficacy in improving hand sensorimotor function outcomes in patients with traumatic cervical SCI will be assessed and compared to the hand MI training not supported by BCI.

METHODS

This randomized controlled trial will include 30 participants with traumatic cervical SCI in the subacute phase randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and the hand MI training not supported by BCI. Both interventions are delivered (3 weekly sessions; 12 weeks) as add-on to standard rehabilitation care. A multidimensional assessment will be performed at: randomization/pre-intervention and post-intervention. Primary outcome measure is the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP) somatosensory sub-score. Secondary outcome measures include the motor and functional scores of the GRASSP and other clinical, neuropsychological, neurophysiological and neuroimaging measures.

DISCUSSION

We expect the BCI-based intervention to promote meaningful cortical sensorimotor plasticity and eventually maximize recovery of arm functions in traumatic cervical subacute SCI. This study will generate a body of knowledge that is fundamental to drive optimization of BCI application in SCI as a top-down therapeutic intervention, thus beyond the canonical use of BCI as assistive tool.

TRIAL REGISTRATION

Name of registry: DiSCIoser: improving arm sensorimotor functions after spinal cord injury via brain-computer interface training (DiSCIoser).

TRIAL REGISTRATION NUMBER

NCT05637775; registration date on the ClinicalTrial.gov platform: 05-12-2022.

Can water-based EEG caps record robust movement-related cortical potentials (MRCPs) for single and multiple joint movements?

Movement-related cortical potentials (MRCPs) have been used extensively in the literature to develop rehabilitation interventions for people with neurological conditions. In this pilot study, we recorded and extracted MRCPs using a water-based cap to determine whether water-based caps are effective. Five participants took part in the study, where their EEG was recorded during single-joint (dorsiflexion) and multiple-joint (sit-to-stand) lower limb movements. We were able to see clear MRCPs for both movement types with an average peak negativity (PN) latency of +22ms for dorsiflexion and +218ms for sit-to-stand. Similarly, the PN amplitude of -14.89μV was recorded for dorsiflexion and -43.54μV for sit-to-stand. These values were comparable to the values reported in studies using gel-based caps. Based on these results, water-based caps can be an effective way to produce robust MRCPs, which can have many advantages over gel-based caps.Clinical Relevance- The study provides clinicians with a more viable method of collecting EEGs and extracting MRCPs, thus allowing them to design more robust interventions for people with neurological disorders.

A data-driven machine learning approach for brain-computer interfaces targeting lower limb neuroprosthetics

Prosthetic devices that replace a lost limb have become increasingly performant in recent years. Recent advances in both software and hardware allow for the decoding of electroencephalogram (EEG) signals to improve the control of active prostheses with brain-computer interfaces (BCI). Most BCI research is focused on the upper body. Although BCI research for the lower extremities has increased in recent years, there are still gaps in our knowledge of the neural patterns associated with lower limb movement. Therefore, the main objective of this study is to show the feasibility of decoding lower limb movements from EEG data recordings. The second aim is to investigate whether well-known neuroplastic adaptations in individuals with an amputation have an influence on decoding performance. To address this, we collected data from multiple individuals with lower limb amputation and a matched able-bodied control group. Using these data, we trained and evaluated common BCI methods that have already been proven effective for upper limb BCI. With an average test decoding accuracy of 84% for both groups, our results show that it is possible to discriminate different lower extremity movements using EEG data with good accuracy. There are no significant differences (p = 0.99) in the decoding performance of these movements between healthy subjects and subjects with lower extremity amputation. These results show the feasibility of using BCI for lower limb prosthesis control and indicate that decoding performance is not influenced by neuroplasticity-induced differences between the two groups.

Neural Bases of Age-Related Sensorimotor Slowing in the Upper and Lower Limbs

With advanced age, there is a loss of reaction speed that may contribute to an increased risk of tripping and falling. Avoiding falls and injuries requires awareness of the threat, followed by selection and execution of the appropriate motor response. Using event-related potentials (ERPs) and a simple visual reaction task (RT), the goal of our study was to distinguish sensory and motor processing in the upper- and lower-limbs while attempting to uncover the main cause of age-related behavioral slowing. Strength (amplitudes) as well as timing and speed (latencies) of various stages of stimulus- and motor-related processing were analyzed in 48 healthy individuals (young adults, n = 24, mean age = 34 years; older adults, n = 24, mean age = 67 years). The behavioral results showed a significant age-related slowing, where the younger compared to older adults exhibited shorter RTs for the upper- (222 vs. 255 ms; p = 0.006, respectively) and the lower limb (257 vs. 274 ms; p = 0.048, respectively) as well as lower variability in both modalities (p = 0.001). Using ERP indices, age-related slowing of visual stimulus processing was characterized by overall larger amplitudes with delayed latencies of endogenous potentials in older compared with younger adults. While no differences were found in the P1 component, the later components of recorded potentials for visual stimuli processing were most affected by age. This was characterized by increased N1 and P2 amplitudes and delayed P2 latencies in both upper and lower extremities. The analysis of motor-related cortical potentials (MRCPs) revealed stronger MRCP amplitude for upper- and a non-significant trend for lower limbs in older adults. The MRCP amplitude was smaller and peaked closer to the actual motor response for the upper- than for the lower limb in both age groups. There were longer MRCP onset latencies for lower- compared to upper-limb in younger adults, and a non-significant trend was seen in older adults. Multiple regression analyses showed that the onset of the MRCP peak consistently predicted reaction time across both age groups and limbs tested. However, MRCP rise time and P2 latency were also significant predictors of simple reaction time, but only in older adults and only for the upper limbs. Our study suggests that motor cortical processes contribute most strongly to the slowing of simple reaction time in advanced age. However, late-stage cortical processing related to sensory stimuli also appears to play a role in upper limb responses in the elderly. This process most likely reflects less efficient recruitment of neuronal resources required for the upper and lower extremity response task in older adults.