Sonja C. Kleih

Motivation modulates the P300 amplitude during brain-computer interface use

OBJECTIVE This study examined the effect of motivation as a possible psychological influencing variable on P300 amplitude and performance in a brain-computer interface (BCI) controlled by event-related potentials (ERP). METHODS Participants were instructed to copy spell a sentence by attending to cells of a randomly flashing 7*7 matrix. Motivation was manipulated by monetary reward. In two experimental groups participants received 25 (N=11) or 50 (N=11) Euro cent for each correctly selected character; the control group (N=11) was not rewarded. BCI performance was defined as the overall percentage of correctly selected characters (correct response rate=CRR). RESULTS Participants performed at an average of 99%. At electrode location Cz the P300 amplitude was positively correlated to self-rated motivation. The P300 amplitude of the most motivated participants was significantly higher than that of the least motivated participants. Highly motivated participants were able to communicate correctly faster with the ERP-BCI than less motivated participants. CONCLUSIONS Motivation modulates the P300 amplitude in an ERP-BCI. SIGNIFICANCE Motivation may contribute to variance in BCI performance and should be monitored in BCI settings.

P300 brain computer interface: current challenges and emerging trends

A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.

An auditory oddball brain–computer interface for binary choices

OBJECTIVE Brain-computer interfaces (BCIs) provide non-muscular communication for individuals diagnosed with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)). In the final stages of the disease, a BCI cannot rely on the visual modality. This study examined a method to achieve high accuracies using auditory stimuli only. METHODS We propose an auditory BCI based on a three-stimulus paradigm. This paradigm is similar to the standard oddball but includes an additional target (i.e. two target stimuli, one frequent stimulus). Three versions of the task were evaluated in which the target stimuli differed in loudness, pitch or direction. RESULTS Twenty healthy participants achieved an average information transfer rate (ITR) of up to 2.46 bits/min and accuracies of 78.5%. Most subjects (14 of 20) achieved their best performance with targets differing in pitch. CONCLUSIONS With this study, the viability of the paradigm was shown for healthy participants and will next be evaluated with individuals diagnosed with ALS or locked-in syndrome (LIS) after stroke. SIGNIFICANCE The here presented BCI offers communication with binary choices (yes/no) independent of vision. As it requires only little time per selection, it may constitute a reliable means of communication for patients who lost all motor function and have a short attention span.

Brain Painting: First Evaluation of a New Brain–Computer Interface Application with ALS-Patients and Healthy Volunteers

Brain–computer interfaces (BCIs) enable paralyzed patients to communicate; however, up to date, no creative expression was possible. The current study investigated the accuracy and user-friendliness of P300-Brain Painting, a new BCI application developed to paint pictures using brain activity only. Two different versions of the P300-Brain Painting application were tested: A colored matrix tested by a group of ALS-patients (n = 3) and healthy participants (n = 10), and a black and white matrix tested by healthy participants (n = 10). The three ALS-patients achieved high accuracies; two of them reaching above 89% accuracy. In healthy subjects, a comparison between the P300-Brain Painting application (colored matrix) and the P300-Spelling application revealed significantly lower accuracy and P300 amplitudes for the P300-Brain Painting application. This drop in accuracy and P300 amplitudes was not found when comparing the P300-Spelling application to an adapted, black and white matrix of the P300-Brain Painting application. By employing a black and white matrix, the accuracy of the P300-Brain Painting application was significantly enhanced and reached the accuracy of the P300-Spelling application. ALS-patients greatly enjoyed P300-Brain Painting and were able to use the application with the same accuracy as healthy subjects. P300-Brain Painting enables paralyzed patients to express themselves creatively and to participate in the prolific society through exhibitions.

Sensorimotor rhythm-based brain?computer interface training: the impact on motor cortical responsiveness

The main purpose of electroencephalography (EEG)-based brain-computer interface (BCI) technology is to provide an alternative channel to support communication and control when motor pathways are interrupted. Despite the considerable amount of research focused on the improvement of EEG signal detection and translation into output commands, little is known about how learning to operate a BCI device may affect brain plasticity. This study investigated if and how sensorimotor rhythm-based BCI training would induce persistent functional changes in motor cortex, as assessed with transcranial magnetic stimulation (TMS) and high-density EEG. Motor imagery (MI)-based BCI training in naïve participants led to a significant increase in motor cortical excitability, as revealed by post-training TMS mapping of the hand muscles cortical representation; peak amplitude and volume of the motor evoked potentials recorded from the opponens pollicis muscle were significantly higher only in those subjects who develop a MI strategy based on imagination of hand grasping to successfully control a computer cursor. Furthermore, analysis of the functional brain networks constructed using a connectivity matrix between scalp electrodes revealed a significant decrease in the global efficiency index for the higher-beta frequency range (22-29 Hz), indicating that the brain network changes its topology with practice of hand grasping MI. Our findings build the neurophysiological basis for the use of non-invasive BCI technology for monitoring and guidance of motor imagery-dependent brain plasticity and thus may render BCI a viable tool for post-stroke rehabilitation.

Brain Painting

BACKGROUND For many years the reestablishment of communication for people with severe motor paralysis has been in the focus of brain-computer interface (BCI) research. Recently applications for entertainment have also been developed. Brain Painting allows the user creative expression through painting pictures. OBJECTIVE The second, revised prototype of the BCI Brain Painting application was evaluated in its target function - free painting - and compared to the P300 spelling application by four end users with severe disabilities. METHODS According to the International Organization for Standardization (ISO), usability was evaluated in terms of effectiveness (accuracy), efficiency (information transfer rate (ITR)), utility metric, subjective workload (National Aeronautics and Space Administration Task Load Index (NASA TLX)) and user satisfaction (Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) 2.0 and Assistive Technology Device Predisposition Assessment (ATD PA), Device Form). RESULTS The results revealed high performance levels (M≥80% accuracy) in the free painting and the copy painting conditions, ITRs (4.47-6.65bits/min) comparable to other P300 applications and only low to moderate workload levels (5-49 of 100), thereby proving that the complex task of free painting did neither impair performance nor impose insurmountable workload. Users were satisfied with the BCI Brain Painting application. Main obstacles for use in daily life were the system operability and the EEG cap, particularly the need of extensive support for adjustment. CONCLUSION The P300 Brain Painting application can be operated with high effectiveness and efficiency. End users with severe motor paralysis would like to use the application in daily life. User-friendliness, specifically ease of use, is a mandatory necessity when bringing BCI to end users. Early and active involvement of users and iterative user-centered evaluation enable developers to work toward this goal.

Out of the frying pan into the fire--the P300-based BCI faces real-world challenges.

Brain-computer interfaces (BCIs) have been investigated for more than 20 years. Many BCIs use noninvasive electroencephalography as a measurement technique and the P300 event-related potential as an input signal (P300 BCI). Since the first experiment with a P300 BCI system in 1988 by Farwell and Donchin, not only data processing has improved but also stimuli presentation has been varied and a plethora of applications was developed and refined. Nowadays, these applications are facing the challenge of being transferred from the research laboratory into real-life situations to serve motor-impaired people in their homes as assistive technology.

The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications.

Albeit research on brain-computer interfaces (BCI) for controlling applications has expanded tremendously, we still face a translational gap when bringing BCI to end-users. To bridge this gap, we adapted the user-centered design (UCD) to BCI research and development which implies a shift from focusing on single aspects, such as accuracy and information transfer rate (ITR), to a more holistic user experience. The UCD implements an iterative process between end-users and developers based on a valid evaluation procedure. Within the UCD framework usability of a device can be defined with regard to its effectiveness, efficiency, and satisfaction. We operationalized these aspects to evaluate BCI-controlled applications. Effectiveness was regarded equivalent to accuracy of selections and efficiency to the amount of information transferred per time unit and the effort invested (workload). Satisfaction was assessed with questionnaires and visual-analogue scales. These metrics have been successfully applied to several BCI-controlled applications for communication and entertainment, which were evaluated by end-users with severe motor impairment. Results of four studies, involving a total of N = 19 end-users revealed: effectiveness was moderate to high; efficiency in terms of ITR was low to high and workload low to medium; depending on the match between user and technology, and type of application satisfaction was moderate to high. The here suggested evaluation metrics within the framework of the UCD proved to be an applicable and informative approach to evaluate BCI controlled applications, and end-users with severe impairment and in the locked-in state were able to participate in this process.

Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude

Objective Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball. Methods Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude. Results Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy. Conclusions Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection. Significance Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.

Effects of training and motivation on auditory P300 brain–computer interface performance

OBJECTIVES Brain-computer interface (BCI) technology aims at helping end-users with severe motor paralysis to communicate with their environment without using the natural output pathways of the brain. For end-users in complete paralysis, loss of gaze control may necessitate non-visual BCI systems. The present study investigated the effect of training on performance with an auditory P300 multi-class speller paradigm. For half of the participants, spatial cues were added to the auditory stimuli to see whether performance can be further optimized. The influence of motivation, mood and workload on performance and P300 component was also examined. METHODS In five sessions, 16 healthy participants were instructed to spell several words by attending to animal sounds representing the rows and columns of a 5 × 5 letter matrix. RESULTS 81% of the participants achieved an average online accuracy of ⩾ 70%. From the first to the fifth session information transfer rates increased from 3.72 bits/min to 5.63 bits/min. Motivation significantly influenced P300 amplitude and online ITR. No significant facilitative effect of spatial cues on performance was observed. CONCLUSIONS Training improves performance in an auditory BCI paradigm. Motivation influences performance and P300 amplitude. SIGNIFICANCE The described auditory BCI system may help end-users to communicate independently of gaze control with their environment.