Mental chronometry and mental rotation abilities in stroke patients with different degrees of sensory deficit

Mu down regulation EEG-neurofeedback training combined to motor imagery facilitates early consolidation in a sequential finger tapping task

Objective.Motor imagery (MI) has demonstrated positive effects on motor performance and triggers activation in the motor cortex (MC). EEG-Neurofeedback (EEG-NF) is a neuromodulation technique that provides real-time feedback on one's brain activity, enabling self-regulation of brain states. While there is increasing evidence of humans controlling the activity of various brain networks, including the MC, through EEG-NF, the tangible benefits of this self-regulation on motor performance remain uncertain. This study investigates the potential benefits of EEG-NF training in explicit learning of a sequential movement, in comparison to MI training and to a combined EEG-NF and MI training.Approach.Ninety-one right-handed healthy adults were randomly assigned to one of four groups (a)NF(n= 24), (b)MI(n= 22), (c)MI + NF(n= 23) and (d)control(n= 22). Participants performed a sequential finger tapping task before and after (immediately, 20 min and 24 h) a single 30 min training session. Motor performance, movement speed and event related desynchronization data were analyzed.Main results.MI training led to a better motor performance compared to control condition immediately after training that was sustained at the 20 min retest time point (p= 0.02 and 0.05). In contrast, EEG-NF training alone did not yield better motor performance compared to control condition at any time-point (p> .05). Remarkably, only the combination of both trainings led to superior motor performance 24 h after training in comparison to control group (p= 0.02). Additionally, all experimental groups successfully decreased mu rhythm amplitude throughout most of the training.Significance.Combined EEG-NF and MI training appears particularly promising for enhancing motor consolidation holding the potential to advance rehabilitation approaches.

Using crutches during walking possibly reduces gait imagery accuracy among healthy young and older adults

[Purpose] Although crutches are widely used in the field of rehabilitation to improve gait performance, patients usually have difficulties using them, and this may increase their risks for falls. This study aimed to define the accuracy of gait imagery during walking with and without crutches, in healthy young and older adults, using the mental chronometry method. [Participants and Methods] Overall, 99 healthy young (mean age, 20.2 ± 1.0 years) and 39 healthy older adults (mean age, 71.3 ± 2.9 years) performed the imagery and execution tasks, which involved walking through a distance of 10 meters both with and without crutches. Using the mental chronometry method, the accuracy of the motor imagery was defined as the difference between the imagery time and the actual execution time. Two-way analysis of variance and one-sample t-tests were performed to evaluate the accuracy of the gait imagery. [Results] Both the young and older adults significantly overestimated their gait speeds when using crutches; the overestimation was larger among the older adults. [Conclusion] The overestimations indicate that participants estimated their gait speeds with crutches to be faster than their actual speeds. Therefore, using crutches decreased the accuracy of gait imagery and might therefore increase an individual’s risk of falling during walking.

Enhancing Detection of SSMVEP Induced by Action Observation Stimuli Based on Task-Related Component Analysis

Action observation (AO)-based brain-computer interface (BCI) is an important technology in stroke rehabilitation training. It has the advantage of simultaneously inducing steady-state motion visual evoked potential (SSMVEP) and activating sensorimotor rhythm. Moreover, SSMVEP could be utilized to perform classification. However, SSMVEP is composed of complex modulation frequencies. Traditional canonical correlation analysis (CCA) suffers from poor recognition performance in identifying those modulation frequencies at short stimulus duration. To address this issue, task-related component analysis (TRCA) was utilized to deal with SSMVEP for the first time. An interesting phenomenon was found: different modulated frequencies in SSMVEP distributed in different task-related components. On this basis, a multi-component TRCA method was proposed. All the significant task-related components were utilized to construct multiple spatial filters to enhance the detection of SSMVEP. Further, a combination of TRCA and CCA was proposed to utilize both advantages. Results showed that the accuracies using the proposed methods were significant higher than that using CCA at all window lengths and significantly higher than that using ensemble-TRCA at short window lengths (≤2 s). Therefore, the proposed methods further validate the induced modulation frequencies and will speed up the application of the AO-based BCI in rehabilitation.

Multi-Session Influence of Two Modalities of Feedback and Their Order of Presentation on MI-BCI User Training

By performing motor-imagery tasks, for example, imagining hand movements, Motor-Imagery based Brain-Computer Interfaces (MI-BCIs) users can control digital technologies, for example, neuroprosthesis, using their brain activity only. MI-BCI users need to train, usually using a unimodal visual feedback, to produce brain activity patterns that are recognizable by the system. The literature indicates that multimodal vibrotactile and visual feedback is more effective than unimodal visual feedback, at least for short term training. However, the multi-session influence of such multimodal feedback on MI-BCI user training remained unknown, so did the influence of the order of presentation of the feedback modalities. In our experiment, 16 participants trained to control a MI-BCI during five sessions with a realistic visual feedback and five others with both a realistic visual feedback and a vibrotactile one. training benefits from a multimodal feedback, in terms of performances and self-reported mindfulness. There is also a significant influence of the order presentation of the modality. Participants who started training with a visual feedback had higher performances than those who started training with a multimodal feedback. We recommend taking into account the order of presentation for future experiments assessing the influence of several modalities of feedback.

Effects of a single mental chronometry training session in subacute stroke patients - a randomized controlled trial

Background

Motor imagery training might be helpful in stroke rehabilitation. This study explored if a single session of motor imagery (MI) training induces performance changes in mental chronometry (MC), motor execution, or changes of motor excitability.

Methods

Subacute stroke patients (n = 33) participated in two training sessions. The order was randomized. One training consisted of a mental chronometry task, the other training was a hand identification task, each lasting 30 min. Before and after the training session, the Box and Block Test (BBT) was fully executed and also performed as a mental version which served as a measure of MC. A subgroup analysis based on the presence of sensory deficits was performed. Patients were allocated to three groups (no sensory deficits, moderate sensory deficits, severe sensory deficits). Motor excitability was measured by transcranial magnetic stimulation (TMS) pre and post training. Amplitudes of motor evoked potentials at rest and during pre-innervation as well as the duration of cortical silent period were measured in the affected and the non-affected hand.

Results

Pre-post differences of MC showed an improved MC after the MI training, whereas MC was worse after the hand identification training. Motor execution of the BBT was significantly improved after mental chronometry training but not after hand identification task training. Patients with severe sensory deficits performed significantly inferior in BBT execution and MC abilities prior to the training session compared to patients without sensory deficits or with moderate sensory deficits. However, pre-post differences of MC were similar in the 3 groups. TMS results were not different between pre and post training but showed significant differences between affected and unaffected side.

Conclusion

Even a single training session can modulate MC abilities and BBT motor execution in a task-specific way. Severe sensory deficits are associated with poorer motor performance and poorer MC ability, but do not have a negative impact on training-associated changes of mental chronometry. Studies with longer treatment periods should explore if the observed changes can further be expanded.

Trial registration

DRKS, DRKS00020355, registered March 9th, 2020, retrospectively registered

Why we should systematically assess, control and report somatosensory impairments in BCI-based motor rehabilitation after stroke studies

The neuronal loss resulting from stroke forces 80% of the patients to undergo motor rehabilitation, for which Brain-Computer Interfaces (BCIs) and NeuroFeedback (NF) can be used. During the rehabilitation, when patients attempt or imagine performing a movement, BCIs/NF provide them with a synchronized sensory (e.g., tactile) feedback based on their sensorimotor-related brain activity that aims at fostering brain plasticity and motor recovery. The co-activation of ascending (i.e., somatosensory) and descending (i.e., motor) networks indeed enables significant functional motor improvement, together with significant sensorimotor-related neurophysiological changes. Somatosensory abilities are essential for patients to perceive the feedback provided by the BCI system. Thus, somatosensory impairments may significantly alter the efficiency of BCI-based motor rehabilitation. In order to precisely understand and assess the impact of somatosensory impairments, we first review the literature on post-stroke BCI-based motor rehabilitation (14 randomized clinical trials). We show that despite the central role that somatosensory abilities play on BCI-based motor rehabilitation post-stroke, the latter are rarely reported and used as inclusion/exclusion criteria in the literature on the matter. We then argue that somatosensory abilities have repeatedly been shown to influence the motor rehabilitation outcome, in general. This stresses the importance of also considering them and reporting them in the literature in BCI-based rehabilitation after stroke, especially since half of post-stroke patients suffer from somatosensory impairments. We argue that somatosensory abilities should systematically be assessed, controlled and reported if we want to precisely assess the influence they have on BCI efficiency. Not doing so could result in the misinterpretation of reported results, while doing so could improve (1) our understanding of the mechanisms underlying motor recovery (2) our ability to adapt the therapy to the patients' impairments and (3) our comprehension of the between-subject and between-study variability of therapeutic outcomes mentioned in the literature.

What are the determinants of explicit and implicit motor imagery ability in stroke patients?: a controlled study

Purpose: The purposes of the study were to (a) investigate both explicit and implicit motor imagery ability (MIA) impairment after stroke, (b) examine predictive effects of clinical characteristics for MIA after stroke.Materials and Methods: Forty one patients with stroke (PwS) (mean age 59.41 ± 10.19 years; %41 female) and 36 healthy participants (mean age 62.47 ± 9.29 years; %47 female) completed Chaotic Motor Imagery Assessment-Hand Rotation for implicit MIA and Movement Imagery Questionnaire-3 (MIQ-3) and Box and Block Test (BBT) for explicit MIA. The severity of motor and sensory impairments were determined by the Fugl-Meyer Assessment-Upper Extremity (FMAUE) scores. The Turkish version of Motor Activity Log-28 was used to assess amount of use (AUS) and quality of movement in daily life.Results: Our results indicated that both implicit and explicit MIA (except kinaesthetic imagery of MIQ-3) in PwS were statistically impaired compared to controls (p < 0.05). The sensorimotor impairment level, amount of use and movement quality of the affected upper limb were found to be correlated with MIA in various degrees. Total motor scores in FMAUE and AUS were significant predictors of explicit MIA (p < 0.01). Additionally, explicit MIA scores of stroke subgroups were statistically different between severely and mildly impaired patients, in favour of mildly impaired group (p < 0.05).Conclusion: In conclusion, both motor impairment level and amount of daily use of upper extremity were found to be predictive factors for explicit MIA. Further investigation with brain imaging techniques is needed to explore the validity of these findings in establishing MIA.

Can a highly accurate multi-class SSMVEP BCI induce sensory-motor rhythm in sensorimotor area?

Different visual stimuli might have different effects on the brain, e.g. the change of brightness, non-biological movement and biological movement. In this study, flicker, checkerboard, and gaiting stimuli were chosen as visual stimuli to investigate whether steady-state motion visual evoked potential (SSMVEP) effected on the sensorimotor area for rehabilitation. The gaiting stimulus was designed as the gaiting sequence of a human. The hypothesis is that only observing the designed gaiting stimulus would simultaneously induce 1) SSMVEP in the occipital area, similarly to an SSVEP stimulus; and 2) sensorimotor rhythm (SMR) in the primary sensorimotor area, because such action observation could activate the mirror neuron system. Canonical correlation analysis was used to detect SSMVEP from occipital EEG, and event-related spectral perturbation was used to identify SMR in the EEG from the sensorimotor area. The results showed that the designed gaiting stimulus-induced SSMVEP, with classification accuracies of 88.9 ± 12.0% in a four-class scenario. More importantly, it induced clear and sustained event-related desynchronization/synchronization (ERD/ERS), while no ERD/ERS could be observed when the other two SSVEP stimuli were used. Further, for participants with a sufficiently clear SSMVEP pattern (classification accuracy > 85%), the ERD index values in the mu-beta band induced by the proposed gaiting stimulus were statistically different from that of the other two types of stimulus. Therefore, a novel BCI based on the designed stimulus has potential in neurorehabilitation applications because it simultaneously has the high accuracy of an SSMVEP (~90% accuracy in a four-class setup) and the ability to activate the sensorimotor area.

Clinical assessment of motor imagery and physical function in mild stroke patients

[Purpose] The aim of this study was to clarify whether the motor imagery of walking and physical function are related in mild hemiplegic stroke patients. [Participants and Methods] Sixteen mild hemiplegic stroke patients were included in this study. We evaluated motor imagery with a 10-m walking, the estimation error and the kinesthetic and visual imagery questionnaire. Physical function was evaluated with the actual 10-m walk test time, Brunnstrom recovery stage, stroke impairment assessment set, and functional independent measure. The correlation coefficient was calculated using Spearman’s correlation coefficient for all evaluation methods. [Results] The 10-m walking motor imagery took an average of 23.36 ± 22.14 s. The actual 10-m walk test averaged 24.87 ± 21.41 s. The 10-m walking motor imagery and the 10-m walking speed were significantly correlated. There was a significant correlation between the 10-m walking motor imagery and the Brunnstrom recovery stage, stroke impairment assessment set, and functional independent measure. There were no significant correlations between the estimation error and all the assessments. [Conclusion] These results show that the motor imagery of walking is related to physical function in mild hemiplegic stroke patients.

A Brain-Computer Interface-Based Action Observation Game That Enhances Mu Suppression

Action observation training based on the theory of activation of the mirror-neuron system has been used for the rehabilitation of patients with stroke. In this paper, we sought to assess whether a brain-computer interface (BCI)-based action observation rehabilitation game, using a flickering action video, could preferentially activate the mirror-neuron system. Feedback of stimulus observation, evoked by the flickering action video, was provided using steady state visually evoked potential and event-related desynchronization. Fifteen healthy subjects have experienced the game with BCI interaction (game and interaction), without BCI interaction (game without interaction), observed non-flickering stimuli, and flickering stimuli without the game background (stimuli only) in a counter-balanced order. The game and interface condition was resulted in significantly stronger activation of the mirror-neuron system than did the other three conditions. In addition, the amount of mirror-neuron system activation is gradually decreased in the game without interface, non-flickering stimuli, and stimuli only conditions in a time-dependent manner; however, in the game and interface condition, the amount of mirror-neuron system activation was maintained until the end of the training. Taken together, these data suggest that the proposed game paradigm, which integrates the action observation paradigm with BCI technology, could provide interactive responses for whether watching video clips can engage patients and enhance rehabilitation.

Motor Imagery Impairment in Postacute Stroke Patients

Not much is known about how well stroke patients are able to perform motor imagery (MI) and which MI abilities are preserved after stroke. We therefore applied three different MI tasks (one mental chronometry task, one mental rotation task, and one EEG-based neurofeedback task) to a sample of postacute stroke patients (n = 20) and age-matched healthy controls (n = 20) for addressing the following questions: First, which of the MI tasks indicate impairment in stroke patients and are impairments restricted to the paretic side? Second, is there a relationship between MI impairment and sensory loss or paresis severity? And third, do the results of the different MI tasks converge? Significant differences between the stroke and control groups were found in all three MI tasks. However, only the mental chronometry task and EEG analysis revealed paresis side-specific effects. Moreover, sensitivity loss contributed to a performance drop in the mental rotation task. The findings indicate that although MI abilities may be impaired after stroke, most patients retain their ability for MI EEG-based neurofeedback. Interestingly, performance in the different MI measures did not strongly correlate, neither in stroke patients nor in healthy controls. We conclude that one MI measure is not sufficient to fully assess an individual's MI abilities.