Brain-computer interface (BCI) research deals with establishing communication pathways between the brain
and external devices. BCI systems can be broadly classified depending on the placement of the electrodes
used to detect and measure neurons firing in the brain: in invasive systems, electrodes are inserted directly
into the cortex; in noninvasive systems, they are placed on the scalp and use electroencephalography or
electrocorticography to detect neuron activity. This WTEC study was designed to gather information on
worldwide status and trends in BCI research and to disseminate it to government decisionmakers and the
research community. The study reviewed and assessed the state of the art in sensor technology, the bioticabiotic
interface and biocompatibility, data analysis and modeling, hardware implementation, systems
engineering, functional electrical stimulation, noninvasive communication systems, and cognitive and
emotional neuroprostheses in academic research and industry.
The WTEC panel identified several major trends in current and evolving BCI research in North America,
Europe, and Asia. First, BCI research throughout the world is extensive, with the magnitude of that research
clearly on the rise. Second, BCI research is rapidly approaching a level of first-generation medical practice;
moreover, BCI research is expected to rapidly accelerate in nonmedical arenas of commerce as well,
particularly in the gaming, automotive, and robotics industries. Third, the focus of BCI research throughout
the world is decidedly uneven, with invasive BCIs almost exclusively centered in North America,
noninvasive BCI systems evolving primarily from European and Asian efforts, and the integration of BCIs
and robotics systems championed by Asian research programs.
In terms of funding, BCI and brain-controlled robotics programs have been a hallmark of recent European
research and technological development. The range and investment levels of multidisciplinary, multinational,
multilaboratory programs in Europe appear to far exceed that of most university and government-funded BCI
programs in the United States and Canada. Although several U.S. government programs are advancing neural
prostheses and BCIs, private sources have yet to make a major impact on BCI research in North America
generally. However, the U.S. Small Business Innovative Research grants (SBIRs) and Small Technology
Transfer Research grants (STTRs) have been effective in promoting transition from basic research to
precommercialized prototypes. In Asia, China is investing heavily in biological sciences and engineering in
general, and the extent of investment in BCI and BCI-related research has grown particularly rapidly; still,
the panel observed little coordination between various programs. Japanese universities, research institutes,
and laboratories also are increasing their investment in BCI research. Japan is especially vigorous in pursuing
nonmedical applications and exploiting its expertise in BCI-controlled robotics.
The WTEC panel concludes that there are abundant and fertile opportunities for worldwide collaborations in
BCI research and allied fields.

Citation, or Unpublished: Berger, T., Chapin, J., Gerhardt, G., McFarland, D., Principe, J., Soussou, W., Taylor, D., Tresco, P. WTEC Panel Report on International Assessment of Research and Development in Brain-Computer Interfaces. October 2007.

Adam Wilson, a graduate student at the University of Winsconsin-Madison, with support from the Wadsworth Center in Albany, NY, has successfully demonstrated that people can post twitter messages simply by thinking about them.  At least, that’s what the popular news media has been reporting.  Over.  And over.  In fact, this may be the most publicized account of a BCI application ever.  All thanks to the twitter buzz that has been flying around recently.  View the application in action here.

But in fact, the underlying technology behind this accomplishment has been around since at least 1988, when Farwell and Donchin demonstrated that the P300 event related potential can be used to select characters from a grid and eventually spell words.  Here’s how it works:

A subject views a grid of characters and makes a decision about what character he would like to select.  Entire rows or columns of the grid flash in a random order.  Each time the desired character is highlighted a P300 event related potential is elicited, which is a noticeable increase in EEG amplitude occurring about 300 milliseconds after the presentation of interesting or notable stimuli, often called the “oddball” response.  Through trial averaging, an algorithm can determine which character in the grid the subject is focusing on.  String together a bunch of these character selections and voila, you have a sentence.  Integrate this technology with twitter, and you have a tweet.

While this latest account may be nothing more than a repackaged old idea, at least it is presenting that idea in a way that is meaningful to the general population.  Greater public interest in brain-computer interface technology could lead to increased funding, which could lead to new discoveries.  I predict that the Facebook BCI is soon to follow.