TY - JOUR T1 - Does the 'P300' speller depend on eye gaze?. JF - J Neural Eng Y1 - 2010 A1 - Peter Brunner A1 - Joshi, S A1 - S Briskin A1 - Jonathan Wolpaw A1 - H Bischof A1 - Gerwin Schalk KW - Adult KW - Event-Related Potentials, P300 KW - Eye Movements KW - Female KW - Humans KW - Male KW - Middle Aged KW - Models, Neurological KW - Photic Stimulation KW - User-Computer Interface KW - Young Adult AB -

Many people affected by debilitating neuromuscular disorders such as amyotrophic lateral sclerosis, brainstem stroke or spinal cord injury are impaired in their ability to, or are even unable to, communicate. A brain-computer interface (BCI) uses brain signals, rather than muscles, to re-establish communication with the outside world. One particular BCI approach is the so-called 'P300 matrix speller' that was first described by Farwell and Donchin (1988 Electroencephalogr. Clin. Neurophysiol. 70 510-23). It has been widely assumed that this method does not depend on the ability to focus on the desired character, because it was thought that it relies primarily on the P300-evoked potential and minimally, if at all, on other EEG features such as the visual-evoked potential (VEP). This issue is highly relevant for the clinical application of this BCI method, because eye movements may be impaired or lost in the relevant user population. This study investigated the extent to which the performance in a 'P300' speller BCI depends on eye gaze. We evaluated the performance of 17 healthy subjects using a 'P300' matrix speller under two conditions. Under one condition ('letter'), the subjects focused their eye gaze on the intended letter, while under the second condition ('center'), the subjects focused their eye gaze on a fixation cross that was located in the center of the matrix. The results show that the performance of the 'P300' matrix speller in normal subjects depends in considerable measure on gaze direction. They thereby disprove a widespread assumption in BCI research, and suggest that this BCI might function more effectively for people who retain some eye-movement control. The applicability of these findings to people with severe neuromuscular disabilities (particularly in eye-movements) remains to be determined.

VL - 7 UR - http://www.ncbi.nlm.nih.gov/pubmed/20858924 IS - 5 ER - TY - JOUR T1 - A practical procedure for real-time functional mapping of eloquent cortex using electrocorticographic signals in humans. JF - Epilepsy Behav Y1 - 2009 A1 - Peter Brunner A1 - A L Ritaccio A1 - Lynch, Timothy M A1 - Emrich, Joseph F A1 - Adam J Wilson A1 - Williams, Justin C A1 - Aarnoutse, Erik J A1 - Ramsey, Nick F A1 - Leuthardt, E C A1 - H Bischof A1 - Gerwin Schalk KW - Adult KW - Brain Mapping KW - Cerebral Cortex KW - Electric Stimulation KW - Electrodes, Implanted KW - Electroencephalography KW - Epilepsy KW - Female KW - Humans KW - Male KW - Middle Aged KW - Practice Guidelines as Topic KW - Signal Processing, Computer-Assisted KW - Young Adult AB -

Functional mapping of eloquent cortex is often necessary prior to invasive brain surgery, but current techniques that derive this mapping have important limitations. In this article, we demonstrate the first comprehensive evaluation of a rapid, robust, and practical mapping system that uses passive recordings of electrocorticographic signals. This mapping procedure is based on the BCI2000 and SIGFRIED technologies that we have been developing over the past several years. In our study, we evaluated 10 patients with epilepsy from four different institutions and compared the results of our procedure with the results derived using electrical cortical stimulation (ECS) mapping. The results show that our procedure derives a functional motor cortical map in only a few minutes. They also show a substantial concurrence with the results derived using ECS mapping. Specifically, compared with ECS maps, a next-neighbor evaluation showed no false negatives, and only 0.46 and 1.10% false positives for hand and tongue maps, respectively. In summary, we demonstrate the first comprehensive evaluation of a practical and robust mapping procedure that could become a new tool for planning of invasive brain surgeries.

VL - 15 UR - http://www.ncbi.nlm.nih.gov/pubmed/19366638 IS - 3 ER - TY - JOUR T1 - Brain-computer interfaces (BCIs): Detection Instead of Classification. JF - J Neurosci Methods Y1 - 2008 A1 - Gerwin Schalk A1 - Peter Brunner A1 - Lester A Gerhardt A1 - H Bischof A1 - Jonathan Wolpaw KW - Adult KW - Algorithms KW - Brain KW - Brain Mapping KW - Electrocardiography KW - Electroencephalography KW - Humans KW - Male KW - Man-Machine Systems KW - Normal Distribution KW - Online Systems KW - Signal Detection, Psychological KW - Signal Processing, Computer-Assisted KW - Software Validation KW - User-Computer Interface AB -

Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer through brain-computer interfaces (BCIs). These devices operate by recording signals from the brain and translating these signals into device commands. They can be used by people who are severely paralyzed to communicate without any use of muscle activity. One of the major impediments in translating this novel technology into clinical applications is the current requirement for preliminary analyses to identify the brain signal features best suited for communication. This paper introduces and validates signal detection, which does not require such analysis procedures, as a new concept in BCI signal processing. This detection concept is realized with Gaussian mixture models (GMMs) that are used to model resting brain activity so that any change in relevant brain signals can be detected. It is implemented in a package called SIGFRIED (SIGnal modeling For Real-time Identification and Event Detection). The results indicate that SIGFRIED produces results that are within the range of those achieved using a common analysis strategy that requires preliminary identification of signal features. They indicate that such laborious analysis procedures could be replaced by merely recording brain signals during rest. In summary, this paper demonstrates how SIGFRIED could be used to overcome one of the present impediments to translation of laboratory BCI demonstrations into clinically practical applications.

VL - 167 UR - http://www.ncbi.nlm.nih.gov/pubmed/17920134 IS - 1 ER -