September 4, 2007 Feature

Brain-Computer Interface

Transforming Electrical Brain Activity Into Communication

A brain-computer interface (BCI) is a system that allows the user to communicate with the world—without the user utilizing voluntary muscle activity—by interpreting manifestations of brain activity (such as the electroencephalogram or EEG). Progress in electrophysiological neuroimaging, the advent of low-cost yet powerful computer equipment, and the growing recognition of the needs and potential of people with disabilities stimulated the development of BCI programs. The goal of these programs is to develop a novel augmentative and alternative communication and control system for individuals who have severe neuromuscular disorders.

A BCI uses what is known about electrical brain activity to make a "smart guess" as to the message that a user has chosen to communicate. Several types of invasive and noninvasive BCIs are being developed and tested by research groups around the world. A distinction can be made between two types of EEG BCIs. One is based on evidence that through a biofeedback learning process, individuals can acquire the ability to control the spectrum of their own electrical brain activity. By detecting subject-controlled changes in the spectral composition of the EEG, the BCI system can infer the users' choices. This type of BCI provides the user voluntary control over a "joystick," which is a powerful control device. However, a great deal of time and effort are needed to acquire the ability to control electrical brain activity.

Another type of BCI system relies on the findings that the brain reacts differently to different stimuli, based on the level of attention given to the stimulus. The P300-based Speller is one such BCI system (Farewell & Donchin, 1988). This BCI system relies on a brain response known as the P300, whose attributes have been studied in detail since its first discovery by Sutton and his colleagues in 1965. The P300-based BCI emulates a keyboard, rather than a joystick, giving the user the ability to choose from a finite number of options—the keys on a keyboard. The advantage of this system is that it requires almost no prior training.

System Requirements

The P300-based BCI system requires a computer, an amplifier, an electrode application system, and a monitor for stimulus presentation. The user display is a matrix that can be varied in size according to individual preferences and ability. The matrix may present letters, numbers, words, sentences, pictures, and/or symbols. Depending on the user's needs and preferences, the matrix can be as small as a 2"x 2" with four stimuli (for example, "yes," "no," "stop," and "more"), or as large as a 9" x 8" to emulate a computer keyboard.

The system implements what has become known as the "oddball paradigm," in which the row and the column containing the chosen cell of the matrix are the only elements that will elicit a P300. The rows and columns of the matrix are illuminated in a random sequence and the EEG elicited by each of them is examined. By recognizing online and in real time which row and column elicited a P300, the system can identify which character the subject chose to "type." Successful use of the system requires no training, but for optimal use, the system needs to be "calibrated" to the user's pattern of electrical brain activity.

Communication for Individuals Who Are "Locked-In"

Potential beneficiaries of BCI systems are individuals who are "locked-in"—fully conscious, yet completely paralyzed and unable to perform any voluntary muscle movement, including those who have amyotrophic lateral sclerosis (ALS), brainstem strokes, and spinal cord injuries. In his book, The Diving-Bell and the Butterfly, Jean-Dominique Bauby describes his experience as a locked-in patient: "Paralyzed from head to toe, the patient is imprisoned inside his own body, his mind intact but unable to speak or move. In my case, blinking my left eyelid is my only means of communication." (Bauby, 1997, pp. 12).

The immediate goal of the BCI speller is to provide its users, who may be completely locked-in, with basic communication capabilities so that they can express their wishes to caregivers, operate simple word processing programs, or even control a neuroprosthesis. Extensive studies with patients with ALS have demonstrated that the P300 BCI system can allow communication at the rate of eight characters per minute. Since 2002, Sellers and Donchin have tested the system with 25 patients at different stages of ALS in the Cognitive Psychophysiological Laboratory at the University of South Florida.

Currently, most of our studies with the P300-BCI system are with patients who have ALS. Approximately 5,600 people in the United States are diagnosed with ALS each year. The incidence of ALS (two per 100,000 people) is five times higher than Huntington's disease and about equal to multiple sclerosis. ALS, sometimes called Lou Gehrig's disease, is a rapidly progressive, invariably fatal neurological disease that attacks the neurons responsible for controlling voluntary muscles. The vast majority of people with ALS remain mentally sharp despite the progressive degeneration of their bodies.

The P300 BCI system was developed into a portable device, BCI2000, by the Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health. With this system, a user can control a 9" x 8" matrix combined with software that augments the functionality of BCI2000 by allowing the user full control of all Windows and Office 2003 software. The BCI2000 software is available for research purposes and is being used by more than 80 research centers in the United States and abroad. Because the system is still in the developmental stage, operating and maintaining it require intense involvement of an individual with knowledge and experience in the area of psychophysiology. Research is underway to automate many of the functions of the system to provide a self-contained and caretaker-friendly system and to improve the speed-accuracy tradeoff to allow fast and accurate communication.

I became acquainted with the BCI system five years ago when I joined the Cognitive Psychophysiological Laboratory at the University of South Florida to collect electrophysiological data for my research. It felt natural for me, as a speech-language pathologist, to become involved with research to provide a solution for individuals with very limited means of communication. The role of SLPs in the development of these devices in collaboration with engineers and psychophysiologists is crucial. SLPs' familiarity with other AAC devices, ability to identify potential users, and capacity to provide in-depth analysis of an individual's communication abilities and needs are much-needed qualities for the successful development of these AAC devices.

Yael Arbel, is a speech-language pathologist and postdoctoral fellow in the Psychology Department at the University of South Florida (Tampa). She leads the BCI research project in the Cognitive Psychophysiological Laboratory directed by Emanuel Donchin. She wishes to thank Donchin for contributing to this story. Contact her at

cite as: Arbel, Y. (2007, September 04). Brain-Computer Interface : Transforming Electrical Brain Activity Into Communication. The ASHA Leader.

Reading the Brain's Responses With a P300

The P300, first described by Sutton, Braren, Zubin, & John (1965), is one of the components of the brain's response to specific events that can be recorded from the scalp. These "event-related potentials" (ERPs) are manifestations of brain activities invoked in the course of information processing. The P300 reaches its maximal amplitude of at least 300 ms following a rare task-relevant stimuli. It is the largest at the parietal electrodes, somewhat smaller at the central electrodes, and minimal at the frontal electrodes.

Certain conditions are necessary for a given task to elicit a P300. First, a random sequence of stimulus events must be presented. Second, a classification rule that separates these events into two categories must be applied. Third, the task must require using the rule. Fourth, one category of events must be presented infrequently (Donchin, & Coles, 1988). As the P300 is elicited by events belonging to the rare category, its latency varies with the time required for categorizing the events. The amplitude of the P300 varies with the subjective probability and the task relevance of the eliciting events. Thus, the rarer the event, the larger the P300 it elicits.

BCI Web Sites

  • Brain-Computer Interface
  • Berlin Brain Computer Interface
  • National Institute of Biomedical Imaging and Engineering

  • References

    Birbaumer, N. (2006). Breaking the silence: Brain–computer interfaces (BCI) for communication and motor control. Presidential Address, 2005. Psychophysiology, 43(6), 517-532.

    Donchin, E. (1981). Surprise!…surprise?. Psychophysiology, 18, 493–513.

    Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11, 355–372.

    Donchin, E., Spencer, K. M., & Wijesinghe, R. (2000). The mental prosthesis: Assessing the speed of a P300-based brain-computer interface. IEEE Transactions on Rehabilitation Engineering, 8, 174–179.

    Fabiani, M., Gratton, G., Karis, D., & Donchin, E. (1987). Definition, identification, and reliability of measurement of the P300 component of the event-related brain potential. Advances in Psychophysiology, 2, 1–78.

    Farwell, L. A., & Donchin, E. (1988). Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and clinical Neurophysiology, 70, 510–523.

    Sellers, E., Schalk, G., & Donchin, E. (2003). The P300 as a typing tool: Tests of brain computer interface with an ALS patient. Psychophysiology, 40 (suppl. 1), S77.

    Sutton, S., Braren, M., Zubin, J., & John, E. R. (1965). Evoked-potential correlates of stimulus uncertainty. Science, 150, 1187–1188.

    Vaughan, T. M., Heetderks, W. J., Trejo, L. J., Rymer, W. Z., Weinrich, M., Moore, M. M., Kubler, A., Dobkin, B. H., Birbaumer, N., Donchin, E., Wolpaw, E. W., Wolpaw, J. R. (2003). Brain-computer interface technology: a review of the Second International Meeting. IEEE Transactions on Rehabilitation Engineering. 11(2), 94–109.

    Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T.M. (2002). Brain-computer interfaces for communication and control. Clinical Neurophysiology, 113, 767–791. 


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