Influence of dual-tasking with different levels of attention diversion on characteristics of the movement-related cortical potential

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.

Shades of gravity - effects of planetary gravity levels on electrocortical activity and neurocognitive performance

The plans of international space agencies to return to the Moon and explore deep space, including Mars, highlight the challenges of human adaptation and stress the need for a thorough analysis of the factors that facilitate, limit and modify human performance under extreme environments. This study investigates the influence of partial gravity on behavioural (error rate and reaction time) and neuronal parameters (event-related potentials) through parabolic flights. Brain cortical activity was assessed using EEG from 18 participants who solved a neurocognitive task, consisting of a mental arithmetic task and an auditory oddball paradigm, during Earth (1G), Lunar (0.16G + 0.25G) and Martian gravity (0.38G + 0.5G) for 15 consecutive parabolas. Data shows higher electrocortical activity in Earth gravity compared to Lunar and Martian gravity in the parietal lobe. No differences in participants' performance were found among the gravity levels. Event-related potentials displayed gravity-dependent variations, though limited stimuli recording suggests caution in interpretation. Data suggests a threshold between Earth and Martian gravity within the different gravities responsible for physiological changes, but it seems to vary greatly between individuals. The altered neuronal communication could be explained with a model developed by Kohn and Ritzmann in 2018. The increasing intracranial pressure in weightlessness changes the properties of the cell membrane of neurons and leads to a depolarisation of the resting membrane potential. The findings underscore the individuality of physiological changes in response to gravity alterations, signalling the need for further investigations in future studies.

Cued motor processing in autism and typical development: A high-density electrical mapping study of response-locked neural activity in children and adolescents

Motor atypicalities are common in autism spectrum disorder (ASD) and are often evident prior to classical ASD symptoms. Despite evidence of differences in neural processing during imitation in autistic individuals, research on the integrity and spatiotemporal dynamics of basic motor processing is surprisingly sparse. To address this need, we analysed electroencephalography (EEG) data recorded from a large sample of autistic (n = 84) and neurotypical (n = 84) children and adolescents while they performed an audiovisual speeded reaction time (RT) task. Analyses focused on RTs and response-locked motor-related electrical brain responses over frontoparietal scalp regions: the late Bereitschaftspotential, the motor potential and the reafferent potential. Evaluation of behavioural task performance indicated greater RT variability and lower hit rates in autistic participants compared to typically developing age-matched neurotypical participants. Overall, the data revealed clear motor-related neural responses in ASD, but with subtle differences relative to typically developing participants evident over fronto-central and bilateral parietal scalp sites prior to response onset. Group differences were further parsed as a function of age (6-9, 9-12 and 12-15 years), sensory cue preceding the response (auditory, visual and bi-sensory audiovisual) and RT quartile. Group differences in motor-related processing were most prominent in the youngest group of children (age 6-9), with attenuated cortical responses observed for young autistic participants. Future investigations assessing the integrity of such motor processes in younger children, where larger differences may be present, are warranted.

Different brain activation patterns in the prefrontal area between self-paced and high-speed driving tasks

The purpose of this study was to investigate the effects on prefrontal cortex brain activity when participants attempted to stop a car accurately at a stop line when driving at different speeds using functional near-infrared spectroscopy (fNIRS). Twenty healthy subjects with driving experience drove their own cars for a distance of 60 m five times each at their own pace or as fast as possible. The variation in the distance between the stop line and the car was not significantly different between the self-paced and high-speed tasks. However, oxygenated hemoglobin concentration in the prefrontal cortex was significantly higher in the high-speed task than in the self-paced task. These findings suggest that driving at high speed requires more divided attention than driving at self-paced speed, even though the participants were able to stop the car at the same distance from the target. This study shows the advantages and usefulness of fNIRS .

Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram (EEG). In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations.

The Effect of Pedaling at Different Cadence on Attentional Resources

We investigated the relationship between attentional resources and pedaling cadence using electroencephalography (EEG) to measure P300 amplitudes and latencies. Twenty-five healthy volunteers performed the oddball task while pedaling on a stationary bike or relaxing (i.e., no pedaling). We set them four conditions, namely, (1) performing only the oddball task (i.e., control), (2) performing the oddball task while pedaling at optimal cadence (i.e., optimal), (3) performing the oddball task while pedaling faster than optimal cadence (i.e., fast), and (4) performing the oddball task while pedaling slower than optimal cadence (i.e., slow). P300 amplitudes at Cz and Pz electrodes under optimal, fast, and slow conditions were significantly lower than those under control conditions. P300 amplitudes at Pz under fast and slow conditions were significantly lower than those under the optimal condition. No significant changes in P300 latency at any electrode were observed under any condition. Our findings revealed that pedaling at non-optimal cadence results in less attention being paid to external stimuli compared with pedaling at optimal cadence.

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

The movement-related cortical potential (MRCP) is a brain signal that can be recorded using surface electroencephalography (EEG) and represents the cortical processes involved in movement preparation. The MRCP has been widely researched in simple, single-joint movements, however, these movements often lack ecological validity. Ecological validity refers to the generalizability of the findings to real-world situations, such as neurological rehabilitation. This scoping review aimed to synthesize the research evidence investigating the MRCP in ecologically valid movement tasks. A search of six electronic databases identified 102 studies that investigated the MRCP during multi-joint movements; 59 of these studies investigated ecologically valid movement tasks and were included in the review. The included studies investigated 15 different movement tasks that were applicable to everyday situations, but these were largely carried out in healthy populations. The synthesized findings suggest that the recording and analysis of MRCP signals is possible in ecologically valid movements, however the characteristics of the signal appear to vary across different movement tasks (i.e., those with greater complexity, increased cognitive load, or a secondary motor task) and different populations (i.e., expert performers, people with Parkinson’s Disease, and older adults). The scarcity of research in clinical populations highlights the need for further research in people with neurological and age-related conditions to progress our understanding of the MRCPs characteristics and to determine its potential as a measure of neurological recovery and intervention efficacy. MRCP-based neuromodulatory interventions applied during ecologically valid movements were only represented in one study in this review as these have been largely delivered during simple joint movements. No studies were identified that used ecologically valid movements to control BCI-driven external devices; this may reflect the technical challenges associated with accurately classifying functional movements from MRCPs. Future research investigating MRCP-based interventions should use movement tasks that are functionally relevant to everyday situations. This will facilitate the application of this knowledge into the rehabilitation setting.

Online detection of movement during natural and self-initiated reach-and-grasp actions from EEG signals

Movement intention detection using electroencephalography (EEG) is a challenging but essential component of brain-computer interfaces (BCIs) for people with motor disabilities.Objective.The goal of this study is to develop a new experimental paradigm to perform asynchronous online detection of movement based on low-frequency time-domain EEG features, concretely on movement-related cortical potentials. The paradigm must be easily transferable to people without any residual upper-limb movement function and the BCI must be independent of upper-limb movement onset measurements and external cues.Approach. In a study with non-disabled participants, we evaluated a novel BCI paradigm to detect self-initiated reach-and-grasp movements. Two experimental conditions were involved. In one condition, participants performed reach-and-grasp movements to a target and simultaneously shifted their gaze towards it. In a control condition, participants solely shifted their gaze towards the target (oculomotor task). The participants freely decided when to initiate the tasks. After eye artefact correction, the EEG signals were time-locked to the saccade onset and the resulting amplitude features were exploited on a hierarchical classification approach to detect movement asynchronously.Main results. With regards to BCI performance, 54.1% (14.4% SD) of the movements were correctly identified, and all participants achieved a performance above chance-level (around 12%). An average of 21.5% (14.1% SD) of the oculomotor tasks were falsely detected as upper-limb movement. In an additional rest condition, 1.7 (1.6 SD) false positives per minute were measured. Through source imaging, movement information was mapped to sensorimotor, posterior parietal and occipital areas.Significance. We present a novel approach for movement detection using EEG signals which does not rely on upper-limb movement onset measurements or on the presentation of external cues. The participants' behaviour closely matches the natural behaviour during goal-directed reach-and-grasp movements, which also constitutes an advantage with respect to current BCI protocols.

Online control of an assistive active glove by slow cortical signals in patients with amyotrophic lateral sclerosis

Objective.A brain-computer interface (BCI) allows users to control external devices using brain signals that can be recorded non-invasively via electroencephalography (EEG). Movement related cortical potentials (MRCPs) are an attractive option for BCI control since they arise naturally during movement execution and imagination, and therefore, do not require an extensive training. This study tested the feasibility of online detection of reaching and grasping using MRCPs for the application in patients suffering from amyotrophic lateral sclerosis (ALS).Approach.A BCI system was developed to trigger closing of a soft assistive glove by detecting a reaching movement. The custom-made software application included data collection, a novel method for collecting the input data for classifier training from the offline recordings based on a sliding window approach, and online control of the glove. Eight healthy subjects and two ALS patients were recruited to test the developed BCI system. They performed assessment blocks without the glove active (NG), in which the movement detection was indicated by a sound feedback, and blocks (G) in which the glove was controlled by the BCI system. The true positive rate (TPR) and the positive predictive value (PPV) were adopted as the outcome measures. Correlation analysis between forehead EEG detecting ocular artifacts and sensorimotor area EEG was conducted to confirm the validity of the results.Main results.The overall median TPR and PPV were >0.75 for online BCI control, in both healthy individuals and patients, with no significant difference across the blocks (NG versus G).Significance.The results demonstrate that cortical activity during reaching can be detected and used to control an external system with a limited amount of training data (30 trials). The developed BCI system can be used to provide grasping assistance to ALS patients.

Detection of movement related cortical potentials in freehand drawing on digital tablet

BACKGROUND

Cortical activity connected to movements has been investigated long since, and is related, among other factors, to saliency of the gesture. However, experiments performed on movements in actual situations are rare, as most of them have been performed in laboratory simulations. Besides, no research seems to have been carried out on subjects during freehand drawing.

NEW METHOD

We propose a method based upon a commercial drawing tablet and wireless pen, that has been synchronized with EEG recording by means of a piezoelectric sensor attached to the pen tip. Complete freedom of movement is allowed, and any kind of drawing style can be performed using currently available graphics software.

RESULTS

EEG recordings during meaningful drawing were compared with recordings where the pen was tapped and shifted on tablet without specific purpose. With reference to T0 event (pen touching tablet), several components could be observed in pre- and post-T0 epochs. The most important appeared to be a triphasic wave (N-150, P-40 and N + 30), where P-40 showed a striking difference between drawing and tap session, being much larger in the former.

COMPARISON WITH EXISTING METHODS

Onset of muscle EMG is usually employed for synchronization. In complex and free gestures too many muscles are active to allow reliable identification of such reference. Our method provides a precise trigger event easily detected without movement constraints.

CONCLUSIONS

With this method it will be possible to record EEG activity related to creative aspects of drawing and explore other skilled movements.

Effects of a dual task and different levels of divided attention on motor-related cortical potential

[Purpose] The aim of this study was to investigate the effect of divided attention on motor-related cortical potential (MRCP) during dual task performance while the difficulty of the secondary task was altered. [Participants and Methods] Twenty-two right-handed healthy volunteers participated in the study. MRCPs were recorded during two tasks, a single task (ST) and a simple (S-DT) or complex dual task (C-DT). The ST involved a self-paced tapping task in which the participants extended their right index finger. In the dual task, the participants performed the ST and a visual number counting task simultaneously. [Results] The amplitude and integral value of MRCP from electroencephalography electrode C3 was significantly higher in the S-DT than in the ST, whereas they were similar between the C-DT and the ST. Medium-load divided attention (i.e., S-DT) led to significantly more changes in the MRCP magnitude than did low-load divided attention (i.e., ST). However, the MRCP of high-load divided attention (i.e., C-DT) was similar to that of low-load divided attention. [Conclusion] These results suggest that MRCP reflects the function of or network between the supplementary motor area and the dorsolateral prefrontal cortex, and may serve as a marker for screening the capacity of individuals to perform dual tasks.

Adaptive Brain-Computer Interface with Attention Alterations in Patients with Amyotrophic Lateral Sclerosis

The users' mental state such as attention variations can have an effect on the brain-computer interface (BCI) performance. In this project, we implemented an adaptive online BCI system with alterations in the users' attention. Twelve electroencephalography (EEG) signals were obtained from six patients with Amyotrophic Lateral Sclerosis (ALS). Participants were asked to execute 40 trials of ankle dorsiflexion concurrently with an auditory oddball task. EEG channels, classifiers and features with superior offline performance in the training phase of the classification of attention level were selected to use in the online mode for prediction the attention status. A feedback was provided to the users to reduce the amount of attention diversion created by the oddball task. The findings revealed that the users' attention can control an online BCI system and real-time neurofeedback can be applied to focus the attention of the user back onto the main task.

Real-time neurofeedback is effective in reducing diversion of attention from a motor task in healthy individuals and patients with amyotrophic lateral sclerosis

OBJECTIVE

The performance of brain-computer interface (BCI) systems is influenced by the user's mental state, such as attention diversion. In this study, we propose a novel online BCI system able to adapt with variations in the users' attention during real-time movement execution.

APPROACH

Electroencephalography signals were recorded from healthy participants and patients with Amyotrophic Lateral Sclerosis while attention to the target task (a dorsiflexion movement) was drifted using an auditory oddball task. For each participant, the selected channels, classifiers and features from a training data set were used in the online phase to predict the attention status.

MAIN RESULTS

For both healthy controls and patients, feedback to the user on attentional status reduced the amount of attention diversion.

SIGNIFICANCE

The findings presented here demonstrate successful monitoring of the users' attention in a fully online BCI system, and further, that real-time neurofeedback on the users' attention state can be implemented to focus the attention of the user back onto the main task.

Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury

We show that persons with spinal cord injury (SCI) retain decodable neural correlates of attempted arm and hand movements. We investigated hand open, palmar grasp, lateral grasp, pronation, and supination in 10 persons with cervical SCI. Discriminative movement information was provided by the time-domain of low-frequency electroencephalography (EEG) signals. Based on these signals, we obtained a maximum average classification accuracy of 45% (chance level was 20%) with respect to the five investigated classes. Pattern analysis indicates central motor areas as the origin of the discriminative signals. Furthermore, we introduce a proof-of-concept to classify movement attempts online in a closed loop, and tested it on a person with cervical SCI. We achieved here a modest classification performance of 68.4% with respect to palmar grasp vs hand open (chance level 50%).

EEG patterns of self-paced movement imaginations towards externally-cued and internally-selected targets

In this study, we investigate the neurophysiological signature of the interacting processes which lead to a single reach-and-grasp movement imagination (MI). While performing this task, the human healthy participants could either define their movement targets according to an external cue, or through an internal selection process. After defining their target, they could start the MI whenever they wanted. We recorded high density electroencephalographic (EEG) activity and investigated two neural correlates: the event-related potentials (ERPs) associated with the target selection, which reflect the perceptual and cognitive processes prior to the MI, and the movement-related cortical potentials (MRCPs), associated with the planning of the self-paced MI. We found differences in frontal and parietal areas between the late ERP components related to the internally-driven selection and the externally-cued process. Furthermore, we could reliably estimate the MI onset of the self-paced task. Next, we extracted MRCP features around the MI onset to train classifiers of movement vs. rest directly on self-paced MI data. We attained performance significantly higher than chance level for both time-locked and asynchronous classification. These findings contribute to the development of more intuitive brain-computer interfaces in which movement targets are defined internally and the movements are self-paced.