Objective-The current study evaluates the efficacy of a P300-based Brain-Computer Interface (BCI) communication device for individuals with advanced ALS.Methods-Participants attended to one cell of a N×N matrix while the N rows and N columns flashed randomly. Each cell of the matrix contained one character. Every flash of an attended character served as a rare event in an oddball sequence and elicited a P300 response. Classification coefficients derived using a stepwise linear discriminant function were applied to the data after each set of flashes. The character receiving the highest discriminant score was presented as feedback.Results-In Phase I, six participants used a 6×6 matrix on 12 separate days with a mean rate of 1.2 selections/min and mean online and offline accuracies of 62% and 82% respectively. In Phase II, four participants used either a 6×6 or a 7×7 matrix to produce novel and spontaneous statements with a mean online rate of 2.1 selections/min and online accuracy of 79%. The amplitude and latency of the P300 remained stable over 40 weeks.Conclusions-Participants could communicate with the P300-based BCI and performance was stable over many months.Significance-BCIs could provide an alternative communication and control technology in the in daily lives of people severely disabled by ALS.

People with severe motor disabilities can maintain an acceptable quality of life if they can communicate. Brain-computer interfaces (BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based BCI could help maintain quality of life for people with ALS.

Brain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2-3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session. Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.

This study was designed to develop and test an auditory event-related potential (ERP) based spelling system for a brain-computer interface (BCI) and to compare user's performance between the auditory and visual modality. The spelling system, where letters in a matrix were coded with acoustically presented numbers, was tested on a group of healthy volunteers. The results were compared with a visual spelling system. Nine of the 13 participants presented with the auditory ERP spelling system scored above a predefined criterion level control for communication. Compared to the visual spelling system, users' performance was lower and the peak latencies of the auditorily evoked ERPs were delayed. It was concluded that auditorily evoked ERPs from the majority of the users could be reliably classified. High accuracies were achieved in these users, rendering item selection with a BCI based on auditory stimulation feasible for communication.

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Using brain-computer interfaces (BCI) humans can select letters or other targets on a computer screen without any muscular involvement. An intensively investigated kind of BCI is based on the recording of visual event-related brain potentials (ERP). However, some severely paralyzed patients who need a BCI for communication have impaired vision or lack control of gaze movement, thus making a BCI depending on visual input no longer feasible. In an effort to render the ERP-BCI usable for this group of patients, the ERP-BCI was adapted to auditory stimulation. Letters of the alphabet were assigned to cells in a 5 x 5 matrix. Rows of the matrix were coded with numbers 1 to 5, and columns with numbers 6 to 10, and the numbers were presented auditorily. To select a letter, users had to first select the row and then the column containing the desired letter. Four severely paralyzed patients in the end-stage of a neurodegenerative disease were examined. All patients performed above chance level. Spelling accuracy was significantly lower with the auditory system as compared with a similar visual system. Patients reported difficulties in concentrating on the task when presented with the auditory system. In future studies, the auditory ERP-BCI should be adjusted by taking into consideration specific features of severely paralyzed patients, such as reduced attention span. This adjustment in combination with more intensive training will show whether an auditory ERP-BCI can become an option for visually impaired patients.

The current study investigated the effects of psychological well-being measured as quality of life (QoL), depression, current mood and motivation on brain–computer interface (BCI) performance in amyotrophic lateral sclerosis (ALS). Six participants with most advanced ALS were trained either for a block of 20 sessions with a BCI based on sensorimotor rhythms (SMR) or a block of 10 sessions with a BCI based on event-related potentials, or both. Questionnaires assessed QoL and severity of depressive symptoms before each training block and mood and motivation before each training session. The SMR-BCI required more training than the P300-BCI. The information transfer rate was higher with the P300-BCI (3.25 bits/min) than with the SMR-BCI (1.16 bits/min). Mood and motivation were related to the number of BCI sessions. Motivational factors, specifically challenge and mastery confidence, were positively related to BCI performance (controlled for the number of sessions) in tow participants, while incompetence fear was negatively related with performance in one participant. BCI performance was not related to motivational factors in three other participants nor to mood in any of the six participants. We conclude that motivational factors may be related to BCI performance in individual subjects and suggest that motivational factors and well-being should be assessed in standard BCI protocols. We also recommend using P300-based BCI as first choice in severely paralyzed patients who present with a P300 evoked potential.

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