Lingual electrotactile stimulation as an alternative sensory feedback pathway for brain–computer interface applications

Cortical activation and BCI performance during brief tactile imagery: A comparative study with motor imagery

Brain-computer interfaces (BCIs) rely heavily on motor imagery (MI) for operation, yet tactile imagery (TI) presents a novel approach that may be advantageous in situations where visual feedback is impractical. The current study aimed to compare the cortical activity and digit classification performance induced by TI and MI to assess the viability of TI for use in BCIs. Twelve right-handed participants engaged in trials of TI and MI, focusing on their left and right index digits. Event-related desynchronization (ERD) in the mu and beta bands was analyzed, and classification accuracy was determined through an artificial neural network (ANN). Comparable ERD patterns were observed in both TI and MI, with significant decreases in ERD during imagery tasks. The ANN demonstrated high classification accuracy, with TI achieving a mean±SD of 79.30 ± 3.91 % and MI achieving 81.10 ± 2.96 %, with no significant difference between the two (p = 0.11). The study found that TI induces substantial ERD comparable to MI and maintains high classification accuracy, supporting its potential as an effective mental strategy for BCIs. This suggests that TI could be a valuable alternative in BCI applications, particularly for individuals unable to rely on visual cues.

Biomechanical and Cortical Control of Tongue Movements During Chewing and Swallowing

Tongue function is vital for chewing and swallowing and lingual dysfunction is often associated with dysphagia. Better treatment of dysphagia depends on a better understanding of hyolingual morphology, biomechanics, and neural control in humans and animal models. Recent research has revealed significant variation among animal models in morphology of the hyoid chain and suprahyoid muscles which may be associated with variation in swallowing mechanisms. The recent deployment of XROMM (X-ray Reconstruction of Moving Morphology) to quantify 3D hyolingual kinematics has revealed new details on flexion and roll of the tongue during chewing in animal models, movements similar to those used by humans. XROMM-based studies of swallowing in macaques have falsified traditional hypotheses of mechanisms of tongue base retraction during swallowing, and literature review suggests that other animal models may employ a diversity of mechanisms of tongue base retraction. There is variation among animal models in distribution of hyolingual proprioceptors but how that might be related to lingual mechanics is unknown. In macaque monkeys, tongue kinematics-shape and movement-are strongly encoded in neural activity in orofacial primary motor cortex, giving optimism for development of brain-machine interfaces for assisting recovery of lingual function after stroke. However, more research on hyolingual biomechanics and control is needed for technologies interfacing the nervous system with the hyolingual apparatus to become a reality.

Preparing participants for the use of the tongue visual sensory substitution device

PURPOSE

Visual sensory substitution devices (SSDs) convey visual information to a blind person through another sensory modality. Using a visual SSD in various daily activities requires training prior to use the device independently. Yet, there is limited literature about procedures and outcomes of the training conducted for preparing users for practical use of SSDs in daily activities.

METHODS

We trained 29 blind adults (9 with congenital and 20 with acquired blindness) in the use of a commercially available electro-tactile SSD, BrainPort. We describe a structured training protocol adapted from the previous studies, responses of participants, and we present retrospective qualitative data on the progress of participants during the training.

RESULTS

The length of the training was not a critical factor in reaching an advanced stage. Though performance in the first two sessions seems to be a good indicator of participants' ability to progress in the training protocol, there are large individual differences in how far and how fast each participant can progress in the training protocol. There are differences between congenital blind users and those blinded later in life.

CONCLUSIONS

The information on the training progression would be of interest to researchers preparing studies, and to eye care professionals, who may advise patients to use SSDs.IMPLICATIONS FOR REHABILITATIONThere are large individual differences in how far and how fast each participant can learn to use a visual-to-tactile sensory substitution device for a variety of tasks.Recognition is mainly achieved through top-down processing with prior knowledge about the possible responses. Therefore, the generalizability is still questionable.Users develop different strategies in order to succeed in training tasks.

BCI-FES With Multimodal Feedback for Motor Recovery Poststroke

An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals-user-generated intent-to-move neural activity recorded from cerebral cortical motor areas-to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.

Electrotactile Perception Properties and Its Applications: A Review

With the increased demands of human-machine interaction, haptic feedback is becoming increasingly critical. However, the high cost, large size and low efficiency of current haptic systems severely hinder further development. As a portable and efficient technology, cutaneous electrotactile stimulation has shown promising potential for these issues. This paper presents a review on and insight into cutaneous electrotactile perception and its applications. Research results on perceptual properties and evaluation methods have been summarized and discussed to understand the effects of electrotactile stimulation on humans. Electrotactile applications are presented in categories to understand the methods and progress in various fields such as prostheses control, sensory substitution, sensory restoration and sensorimotor restoration. State of the art has demonstrated the superiority of electrotactile feedback, its efficiency and its flexibility. However, the complex factors and the limitations of evaluation methods made it challenging for precise electrotactile control. Groundbreaking innovation in electrotactile theory is expected to overcome challenges such as precise perception control, information capacity increasing, comprehension burden reducing and implementation costs.

Palatal Electrotactile Display Outperforms Visual Display in Tongue Motor learning

Incomplete tongue motor control is a common yet challenging issue among individuals with neurotraumas and neurological disorders. In development of the training protocols, multiple sensory modalities including visual, auditory, and tactile feedback have been employed. However, the effectiveness of each sensory modality in tongue motor learning is still in question. The object of this study was to test the effectiveness of visual and electrotactile assistance on tongue motor learning, respectively. Eight healthy subjects performed the tongue pointing task, in which they were visually instructed to touch the target on the palate by their tongue tip as accurately as possible. Each subject wore a custom-made dental retainer with 12 electrodes distributed over the palatal area. For visual training, 3×4 LED array on the computer screen, corresponding to the electrode layout, was turned on with different colors according to the tongue contact. For electrotactile training, electrical stimulation was applied to the tongue with frequencies depending on the distance between the tongue contact and the target, along with a small protrusion on the retainer as an indicator of the target. One baseline session, one training session, and three post-training sessions were conducted over four-day duration. Experimental result showed that the error was decreased after both visual and electrotactile trainings, from 3.56±0.11 (Mean±STE) to 1.27±0.16, and from 3.97±0.11 to 0.53±0.19, respectively. The result also showed that electrotactile training leads to stronger retention than visual training, as the improvement was retained as 62.68±1.81% after electrotactile training and 36.59±2.24% after visual training, at 3-day post training.

Ipsilesional Mu Rhythm Desynchronization Correlates With Improvements in Affected Hand Grip Strength and Functional Connectivity in Sensorimotor Cortices Following BCI-FES Intervention for Upper Extremity in Stroke Survivors

Stroke is a leading cause of acquired long-term upper extremity motor disability. Current standard of care trajectories fail to deliver sufficient motor rehabilitation to stroke survivors. Recent research suggests that use of brain-computer interface (BCI) devices improves motor function in stroke survivors, regardless of stroke severity and chronicity, and may induce and/or facilitate neuroplastic changes associated with motor rehabilitation. The present sub analyses of ongoing crossover-controlled trial NCT02098265 examine first whether, during movements of the affected hand compared to rest, ipsilesional Mu rhythm desynchronization of cerebral cortical sensorimotor areas [Brodmann’s areas (BA) 1-7] is localized and tracks with changes in grip force strength. Secondly, we test the hypothesis that BCI intervention results in changes in frequency-specific directional flow of information transmission (direct path functional connectivity) in BA 1-7 by measuring changes in isolated effective coherence (iCoh) between cerebral cortical sensorimotor areas thought to relate to electrophysiological signatures of motor actions and motor learning. A sample of 16 stroke survivors with right hemisphere lesions (left hand motor impairment), received a maximum of 18–30 h of BCI intervention. Electroencephalograms were recorded during intervention sessions while outcome measures of motor function and capacity were assessed at baseline and completion of intervention. Greater desynchronization of Mu rhythm, during movements of the impaired hand compared to rest, were primarily localized to ipsilesional sensorimotor cortices (BA 1-7). In addition, increased Mu desynchronization in the ipsilesional primary motor cortex, Post vs. Pre BCI intervention, correlated significantly with improvements in hand function as assessed by grip force measurements. Moreover, the results show a significant change in the direction of causal information flow, as measured by iCoh, toward the ipsilesional motor (BA 4) and ipsilesional premotor cortices (BA 6) during BCI intervention. Significant iCoh increases from ipsilesional BA 4 to ipsilesional BA 6 were observed in both Mu [8–12 Hz] and Beta [18–26 Hz] frequency ranges. In summary, the present results are indicative of improvements in motor capacity and behavior, and they are consistent with the view that BCI-FES intervention improves functional motor capacity of the ipsilesional hemisphere and the impaired hand.

A BCI-Based Vibrotactile Neurofeedback Training Improves Motor Cortical Excitability During Motor Imagery

In this study, we address the issue of whether vibrotactile feedback can enhance the motor cortex excitability translated into the plastic changes in local cortical areas during motor imagery (MI) BCI-based training. For this purpose, we focused on two of the most notable neurophysiological effects of MI - the event-related desynchronization (ERD) level and the increase in cortical excitability assessed with navigated transcranial magnetic stimulation (nTMS). For TMS navigation, we used individual high-resolution 3D brain MRIs. Ten BCI-naive and healthy adults participated in this study. The MI (rest or left/right hand imagery using Graz-BCI paradigm) tasks were performed separately in the presence and absence of feedback. To investigate how much the presence/absence of vibrotactile feedback in MI BCI-based training could contribute to the sensorimotor cortical activations, we compared the MEPs amplitude during MI after training with and without feedback. In addition, the ERD levels during MI BCI-based training were investigated. Our findings provide evidence that applying vibrotactile feedback during MI training leads to (i) an enhancement of the desynchronization level of mu-rhythm EEG patterns over the contralateral motor cortex area corresponding to the MI of the non-dominant hand; (ii) an increase in motor cortical excitability in hand muscle representation corresponding to a muscle engaged by the MI.

Visual-Electrotactile Stimulation Feedback to Improve Immersive Brain-Computer Interface Based on Hand Motor Imagery

In the aging society, the number of people suffering from vascular disorders is rapidly increasing and has become a social problem. The death rate due to stroke, which is the second leading cause of global mortality, has increased by 40% in the last two decades. Stroke can also cause paralysis. Of late, brain-computer interfaces (BCIs) have been garnering attention in the rehabilitation field as assistive technology. A BCI for the motor rehabilitation of patients with paralysis promotes neural plasticity, when subjects perform motor imagery (MI). Feedback, such as visual and proprioceptive, influences brain rhythm modulation to contribute to MI learning and motor function restoration. Also, virtual reality (VR) can provide powerful graphical options to enhance feedback visualization. This work aimed to improve immersive VR-BCI based on hand MI, using visual-electrotactile stimulation feedback instead of visual feedback. The MI tasks include grasping, flexion/extension, and their random combination. Moreover, the subjects answered a system perception questionnaire after the experiments. The proposed system was evaluated with twenty able-bodied subjects. Visual-electrotactile feedback improved the mean classification accuracy for the grasping (93.00%  $\pm$  3.50%) and flexion/extension (95.00%  $\pm$  5.27%) MI tasks. Additionally, the subjects achieved an acceptable mean classification accuracy (maximum of 86.5%  $\pm$  5.80%) for the random MI task, which required more concentration. The proprioceptive feedback maintained lower mean power spectral density in all channels and higher attention levels than those of visual feedback during the test trials for the grasping and flexion/extension MI tasks. Also, this feedback generated greater relative power in the $\mu$ -band for the premotor cortex, which indicated better MI preparation. Thus, electrotactile stimulation along with visual feedback enhanced the immersive VR-BCI classification accuracy by 5.5% and 4.5% for the grasping and flexion/extension MI tasks, respectively, retained the subject’s attention, and eased MI better than visual feedback alone.

Lingual electrotactile discrimination ability is associated with the presence of specific connective tissue structures (papillae) on the tongue surface

Electrical stimulation of nerve endings in the tongue can be used to communicate information to users and has been shown to be highly effective in sensory substitution applications. The anterior tip of the tongue has very small somatosensory receptive fields, comparable to those of the finger tips, allowing for precise two-point discrimination and high tactile sensitivity. However, perception of electrotactile stimuli varies significantly between users, and across the tongue surface. Despite this, previous studies all used uniform electrode grids to stimulate a region of the dorsal-medial tongue surface. In an effort to customize electrode layouts for individual users, and thus improve efficacy for sensory substitution applications, we investigated whether specific neuroanatomical and physiological features of the tongue are associated with enhanced ability to perceive active electrodes. Specifically, the study described here was designed to test whether fungiform papillae density and/or propylthiouracil sensitivity are positively or negatively associated with perceived intensity and/or discrimination ability for lingual electrotactile stimuli. Fungiform papillae number and distribution were determined for 15 participants and they were exposed to patterns of electrotactile stimulation (ETS) and asked to report perceived intensity and perceived number of stimuli. Fungiform papillae number and distribution were then compared to ETS characteristics using comprehensive and rigorous statistical analyses. Our results indicate that fungiform papillae density is correlated with enhanced discrimination ability for electrical stimuli. In contrast, papillae density, on average, is not correlated with perceived intensity of active electrodes. However, results for at least one participant suggest that further research is warranted. Our data indicate that propylthiouracil taster status is not related to ETS perceived intensity or discrimination ability. These data indicate that individuals with higher fungiform papillae number and density in the anterior medial tongue region may be better able to use lingual ETS for sensory substitution.

A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback

Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration and real-time feedback of individual patterns of brain activity with the aim of achieving self-regulation of specific neural substrates or control of external devices. These approaches have historically employed visual stimuli. However, in some cases vision is unsuitable or inadequately engaging. Other sensory modalities, such as auditory or haptic feedback have been explored, and multisensory stimulation is expected to improve the quality of the interaction loop. Moreover, for motor imagery tasks, closing the sensorimotor loop through haptic feedback may be relevant for motor rehabilitation applications, as it can promote plasticity mechanisms. This survey reviews the various haptic technologies and describes their application to BCIs and NF. We identify major trends in the use of haptic interfaces for BCI and NF systems and discuss crucial aspects that could motivate further studies.

Poor resolution at the back of the tongue is the bottleneck for spatial pattern recognition

Spatial patterns presented on the tongue using electro-tactile sensory substitution devices (SSDs) have been suggested to be recognized better by tracing the pattern with the tip of the tongue. We examined if the functional benefit of tracing is overcoming the poor sensitivity or low spatial resolution at the back of the tongue or alternatively compensating for limited information processing capacity by fixating on a segment of the spatial pattern at a time. Using a commercially available SSD, the BrainPort, we compared letter recognition performance in three presentation modes; tracing, static, and drawing. Stimulation intensity was either constant or increased from the tip to the back of the tongue to partially compensate for the decreasing sensitivity. Recognition was significantly better for tracing, compared to static and drawing conditions. Confusion analyses showed that letters were confused based on their characteristics presented near the tip in static and drawing conditions. The results suggest that recognition performance is limited by the poor spatial resolution at the back of the tongue, and tracing seems to be an effective strategy to overcome this. Compensating for limited information processing capacity or poor sensitivity by drawing or increasing intensity at the back, respectively, does not improve the performance.

Decoding Movement From Electrocorticographic Activity: A Review

Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.

Non-linearity of Skin Properties in Electrotactile Applications: Identification and Mitigation

Electrotactile displays can open a new sensory substitution channel to be utilized in a vast array of applications. Our Finger-Eye research used this approach to build a system for the blind to easily read any text not written in Braille. But there are still challenges in different aspects of such systems. One of the most crucial concerns, is the effects of receptor fatigue. Our tests show that during prolonged exposure of receptors to the electrical signals, their sensitivity to the signal level changes gradually and adjustments in the signal's power are required to keep the receptors is the stimulated state. This was confirmed by monitoring the electrical current passing through the skin and calculating the corresponding impedance. More interestingly, the rates of the impedance changes are different for each part of the skin, indicating inconsistent rates of receptor fatigue for each region of the skin. These electrical properties of the skin were addressed in this research for the purpose of rendering consistent sensations for the users regardless of the person or skin conditions. To solve these challenges, two methods are employed: a voltage control system based on pulse-width modulation is used to adjust the signal power; and Kalman filtering is used to predict impedance changes in advance and supply the skin with the proper signal. The result is a self-contained automated system capable of managing the signal power for any user at any given time or skin condition.

Ipsilesional Mu Rhythm Desynchronization and Changes in Motor Behavior Following Post Stroke BCI Intervention for Motor Rehabilitation

Loss of motor function is a common deficit following stroke insult and often manifests as persistent upper extremity (UE) disability which can affect a survivor's ability to participate in activities of daily living. Recent research suggests the use of brain-computer interface (BCI) devices might improve UE function in stroke survivors at various times since stroke. This randomized crossover-controlled trial examines whether intervention with this BCI device design attenuates the effects of hemiparesis, encourages reorganization of motor related brain signals (EEG measured sensorimotor rhythm desynchronization), and improves movement, as measured by the Action Research Arm Test (ARAT). A sample of 21 stroke survivors, presenting with varied times since stroke and levels of UE impairment, received a maximum of 18-30 h of intervention with a novel electroencephalogram-based BCI-driven functional electrical stimulator (EEG-BCI-FES) device. Driven by spectral power recordings from contralateral EEG electrodes during cued attempted grasping of the hand, the user's input to the EEG-BCI-FES device modulates horizontal movement of a virtual cursor and also facilitates concurrent stimulation of the impaired UE. Outcome measures of function and capacity were assessed at baseline, mid-therapy, and at completion of therapy while EEG was recorded only during intervention sessions. A significant increase in r-squared values [reflecting Mu rhythm (8-12 Hz) desynchronization as the result of attempted movements of the impaired hand] presented post-therapy compared to baseline. These findings suggest that intervention corresponds with greater desynchronization of Mu rhythm in the ipsilesional hemisphere during attempted movements of the impaired hand and this change is related to changes in behavior as a result of the intervention. BCI intervention may be an effective way of addressing the recovery of a stroke impaired UE and studying neuromechanical coupling with motor outputs. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT02098265.

Behavioral Outcomes Following Brain-Computer Interface Intervention for Upper Extremity Rehabilitation in Stroke: A Randomized Controlled Trial

Stroke is a leading cause of persistent upper extremity (UE) motor disability in adults. Brain-computer interface (BCI) intervention has demonstrated potential as a motor rehabilitation strategy for stroke survivors. This sub-analysis of ongoing clinical trial (NCT02098265) examines rehabilitative efficacy of this BCI design and seeks to identify stroke participant characteristics associated with behavioral improvement. Stroke participants (n = 21) with UE impairment were assessed using Action Research Arm Test (ARAT) and measures of function. Nine participants completed three assessments during the experimental BCI intervention period and at 1-month follow-up. Twelve other participants first completed three assessments over a parallel time-matched control period and then crossed over into the BCI intervention condition 1-month later. Participants who realized positive change (≥1 point) in total ARAT performance of the stroke affected UE between the first and third assessments of the intervention period were dichotomized as "responders" (<1 = "non-responders") and similarly analyzed. Of the 14 participants with room for ARAT improvement, 64% (9/14) showed some positive change at completion and approximately 43% (6/14) of the participants had changes of minimal detectable change (MDC = 3 pts) or minimally clinical important difference (MCID = 5.7 points). Participants with room for improvement in the primary outcome measure made significant mean gains in ARATtotal score at completion (ΔARATtotal = 2, p = 0.028) and 1-month follow-up (ΔARATtotal = 3.4, p = 0.0010), controlling for severity, gender, chronicity, and concordance. Secondary outcome measures, SISmobility, SISadl, SISstrength, and 9HPTaffected, also showed significant improvement over time during intervention. Participants in intervention through follow-up showed a significantly increased improvement rate in SISstrength compared to controls (p = 0.0117), controlling for severity, chronicity, gender, as well as the individual effects of time and intervention type. Participants who best responded to BCI intervention, as evaluated by ARAT score improvement, showed significantly increased outcome values through completion and follow-up for SISmobility (p = 0.0002, p = 0.002) and SISstrength (p = 0.04995, p = 0.0483). These findings may suggest possible secondary outcome measure patterns indicative of increased improvement resulting from this BCI intervention regimen as well as demonstrating primary efficacy of this BCI design for treatment of UE impairment in stroke survivors. Clinical Trial Registration: ClinicalTrials.gov, NCT02098265.

The critical stability task: quantifying sensory-motor control during ongoing movement in nonhuman primates

Everyday behaviors require that we interact with the environment, using sensory information in an ongoing manner to guide our actions. Yet, by design, many of the tasks used in primate neurophysiology laboratories can be performed with limited sensory guidance. As a consequence, our knowledge about the neural mechanisms of motor control is largely limited to the feedforward aspects of the motor command. To study the feedback aspects of volitional motor control, we adapted the critical stability task (CST) from the human performance literature (Jex H, McDonnell J, Phatak A. IEEE Trans Hum Factors Electron 7: 138-145, 1966). In the CST, our monkey subjects interact with an inherently unstable (i.e., divergent) virtual system and must generate sensory-guided actions to stabilize it about an equilibrium point. The difficulty of the CST is determined by a single parameter, which allows us to quantitatively establish the limits of performance in the task for different sensory feedback conditions. Two monkeys learned to perform the CST with visual or vibrotactile feedback. Performance was better under visual feedback, as expected, but both monkeys were able to utilize vibrotactile feedback alone to successfully perform the CST. We also observed changes in behavioral strategy as the task became more challenging. The CST will have value for basic science investigations of the neural basis of sensory-motor integration during ongoing actions, and it may also provide value for the design and testing of bidirectional brain computer interface systems. NEW & NOTEWORTHY Currently, most behavioral tasks used in motor neurophysiology studies require primates to make short-duration, stereotyped movements that do not necessitate sensory feedback. To improve our understanding of sensorimotor integration, and to engineer meaningful artificial sensory feedback systems for brain-computer interfaces, it is crucial to have a task that requires sensory feedback for good control. The critical stability task demands that sensory information be used to guide long-duration movements.

Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity

Interventional therapy using brain-computer interface (BCI) technology has shown promise in facilitating motor recovery in stroke survivors; however, the impact of this form of intervention on functional networks outside of the motor network specifically is not well-understood. Here, we investigated resting-state functional connectivity (rs-FC) in stroke participants undergoing BCI therapy across stages, namely pre- and post-intervention, to identify discriminative functional changes using a machine learning classifier with the goal of categorizing participants into one of the two therapy stages. Twenty chronic stroke participants with persistent upper-extremity motor impairment received neuromodulatory training using a closed-loop neurofeedback BCI device, and rs-functional MRI (rs-fMRI) scans were collected at four time points: pre-, mid-, post-, and 1 month post-therapy. To evaluate the peak effects of this intervention, rs-FC was analyzed from two specific stages, namely pre- and post-therapy. In total, 236 seeds spanning both motor and non-motor regions of the brain were computed at each stage. A univariate feature selection was applied to reduce the number of features followed by a principal component-based data transformation used by a linear binary support vector machine (SVM) classifier to classify each participant into a therapy stage. The SVM classifier achieved a cross-validation accuracy of 92.5% using a leave-one-out method. Outside of the motor network, seeds from the fronto-parietal task control, default mode, subcortical, and visual networks emerged as important contributors to the classification. Furthermore, a higher number of functional changes were observed to be strengthening from the pre- to post-therapy stage than the ones weakening, both of which involved motor and non-motor regions of the brain. These findings may provide new evidence to support the potential clinical utility of BCI therapy as a form of stroke rehabilitation that not only benefits motor recovery but also facilitates recovery in other brain networks. Moreover, delineation of stronger and weaker changes may inform more optimal designs of BCI interventional therapy so as to facilitate strengthened and suppress weakened changes in the recovery process.

A historical evaluation of Chinese tongue diagnosis in the treatment of septicemic plague in the pre-antibiotic era, and as a new direction for revolutionary clinical research applications

Chinese tongue diagnosis was initially developed to quickly and efficiently diagnose and prescribe medicine, while at the same time allowing the doctor to have minimal contact with the patient. At the time of its compiling, the spread of Yersinia pestis, often causing septicaemia and gangrene of the extremities, may have discouraged doctors to come in direct contact with their patients and take the pulse. However, in recent decades, modern developments in the field of traditional Chinese medicine, as well as the spread of antibiotics in conjunction with the advancements of microbiology, have overshadowed the original purpose of this methodology. Nevertheless, the fast approaching post-antibiotic era and the development of artificial intelligence may hold new applications for tongue diagnosis. This article focuses on the historical development of what is the world's earliest tongue diagnosis monograph, and discusses the directions that such knowledge may be used in future clinical research.

Designing Guiding Systems for Brain-Computer Interfaces

Brain–Computer Interface (BCI) community has focused the majority of its research efforts on signal processing and machine learning, mostly neglecting the human in the loop. Guiding users on how to use a BCI is crucial in order to teach them to produce stable brain patterns. In this work, we explore the instructions and feedback for BCIs in order to provide a systematic taxonomy to describe the BCI guiding systems. The purpose of our work is to give necessary clues to the researchers and designers in Human–Computer Interaction (HCI) in making the fusion between BCIs and HCI more fruitful but also to better understand the possibilities BCIs can provide to them.

Perceived Intensity and Discrimination Ability for Lingual Electrotactile Stimulation Depends on Location and Orientation of Electrodes

Malfunctioning sensory systems can severely impact quality of life and repair is not always possible. One solution, called sensory substitution, is to use another sensory system to bring lost information to the brain. This approach often involves the use of bioengineered devices that electrically stimulate somatosensory fibers. Interestingly, the tongue is an ideal location for electrotactile stimulation due to its dense innervation, moisture, and protected environment. Success with transmitting visual and vestibular information through the tongue indicates promise for future applications. However, sensitivity and discrimination ability varies between individuals and across the tongue surface complicating efforts to produce reliable and consistent sensations. The goals of the present study were to investigate these differences more precisely to better understand the mechanosensory innervation of the tongue so that future electrotactile devices can be designed more effectively. Specifically, we tested whether stimulation of certain regions of the tongue consistently result in better perception, whether the spacing of stimulating electrodes affects perceived intensity, and whether the orientation of electrodes affects perceived intensity and discrimination. To test these hypotheses, we built a custom tongue stimulation device, recruited 25 participants, and collected perceived intensity and discrimination data. We then subjected the data to thorough statistical analyses. Consistent with previous studies, we found that stimulation of the anterior medial tongue region was perceived as more intense than stimulation of lateral and posterior regions. This region also had the best discrimination ability for electrodes. Dividing the stimulated tongue area into 16 distinct regions allowed us to compare perception ability between anterior and posterior regions, medial and lateral regions, and the left and right sides of the tongue. Stimulation of the most anterior and medial tongue resulted in the highest perceived intensity and the best discrimination ability. Most individuals were able to perceive and discriminate electrotactile stimulation better on one side of the tongue, and orientation of stimulating electrodes affected perception. In conclusion, the present studies reveal new information about the somatosensory innervation of the tongue and will assist the design of future electrotactile tongue stimulation devices that will help provide sensory information to people with damaged sensory systems.

A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke

Stroke is a leading cause of acquired disability resulting in distal upper extremity functional motor impairment. Stroke mortality rates continue to decline with advances in healthcare and medical technology. This has led to an increased demand for advanced, personalized rehabilitation. Survivors often experience some level of spontaneous recovery shortly after their stroke event, yet reach a functional plateau after which there is exiguous motor recovery. Nevertheless, studies have demonstrated the potential for recovery beyond this plateau. Non-traditional neurorehabilitation techniques, such as those incorporating the brain-computer interface (BCI), are being investigated for rehabilitation. BCIs may offer a gateway to the brain's plasticity and revolutionize how humans interact with the world. Non-invasive BCIs work by closing the proprioceptive feedback loop with real-time, multi-sensory feedback allowing for volitional modulation of brain signals to assist hand function. BCI technology potentially promotes neuroplasticity and Hebbian-based motor recovery by rewarding cortical activity associated with sensory-motor rhythms through use with a variety of self-guided and assistive modalities.

Brain-Computer Interface Training after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers

Background: Brain–computer interface (BCI) devices are being investigated for their application in stroke rehabilitation, but little is known about how structural changes in the motor system relate to behavioral measures with the use of these systems.

Objective: This study examined relationships among diffusion tensor imaging (DTI)-derived metrics and with behavioral changes in stroke patients with and without BCI training.

Methods: Stroke patients (n = 19) with upper extremity motor impairment were assessed using Stroke Impact Scale (SIS), Action Research Arm Test (ARAT), Nine-Hole Peg Test (9-HPT), and DTI scans. Ten subjects completed four assessments over a control period during which no training was administered. Seventeen subjects, including eight who completed the control period, completed four assessments over an experimental period during which subjects received interventional BCI training. Fractional anisotropy (FA) values were extracted from each corticospinal tract (CST) and transcallosal motor fibers for each scan.

Results: No significant group by time interactions were identified at the group level in DTI or behavioral measures. During the control period, increases in contralesional CST FA and in asymmetric FA (aFA) correlated with poorer scores on SIS and 9-HPT. During the experimental period (with BCI training), increases in contralesional CST FA were correlated with improvements in 9-HPT while increases in aFA correlated with improvements in ARAT but with worsening 9-HPT performance; changes in transcallosal motor fibers positively correlated with those in the contralesional CST. All correlations p < 0.05 corrected.

Conclusion: These findings suggest that the integrity of the contralesional CST may be used to track individual behavioral changes observed with BCI training after stroke.

BCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?

It has been known that stroke constitutes a major source of acquired disability, with nearly 800,000 new strokes each year in the USA alone. While advances in public and preventative health have helped reduce stroke incidence in high-income countries in recent decades, growth of the aging population, increasing stroke rates in low- to middle-income countries and medical advances that have reduced stroke mortality are all contributing to an increase in stroke survivors worldwide. Large numbers of stroke survivors have residual motor deficits. This editorial will provide an introduction to a class of new therapies being investigated with the aim of improving motor outcomes in stroke patients that uses what is known as brain-computer interface technology.

Case report: post-stroke interventional BCI rehabilitation in an individual with preexisting sensorineural disability

Therapies involving new technologies such as brain-computer interfaces (BCI) are being studied to determine their potential for interventional rehabilitation after acute events such as stroke produce lasting impairments. While studies have examined the use of BCI devices by individuals with disabilities, many such devices are intended to address a specific limitation and have been studied when this limitation or disability is present in isolation. Little is known about the therapeutic potential of these devices for individuals with multiple disabilities with an acquired impairment overlaid on a secondary long-standing disability. We describe a case in which a male patient with congenital deafness suffered a right pontine ischemic stroke, resulting in persistent weakness of his left hand and arm. This patient volunteer completed four baseline assessments beginning at 4 months after stroke onset and subsequently underwent 6 weeks of interventional rehabilitation therapy using a closed-loop neurofeedback BCI device with visual, functional electrical stimulation, and tongue stimulation feedback modalities. Additional assessments were conducted at the midpoint of therapy, upon completion of therapy, and 1 month after completing all BCI therapy. Anatomical and functional MRI scans were obtained at each assessment, along with behavioral measures including the Stroke Impact Scale (SIS) and the Action Research Arm Test (ARAT). Clinically significant improvements in behavioral measures were noted over the course of BCI therapy, with more than 10 point gains in both the ARAT scores and scores for the SIS hand function domain. Neuroimaging during finger tapping of the impaired hand also showed changes in brain activation patterns associated with BCI therapy. This case study demonstrates the potential for individuals who have preexisting disability or possible atypical brain organization to learn to use a BCI system that may confer some rehabilitative benefit.