@article {2195, title = {A procedure for measuring latencies in brain-computer interfaces.}, journal = {IEEE Trans Biomed Eng}, volume = {57}, year = {2010}, month = {06/2010}, pages = {1785-97}, abstract = {

Brain-computer interface (BCI) systems must process neural signals with consistent timing in order to support adequate system performance. Thus, it is important to have the capability to determine whether a particular BCI configuration (i.e., hardware and software) provides adequate timing performance for a particular experiment. This report presents a method of measuring and quantifying different aspects of system timing in several typical BCI experiments across a range of settings, and presents comprehensive measures of expected overall system latency for each experimental configuration.

}, keywords = {Brain, Computer Systems, Electroencephalography, Evoked Potentials, Humans, Models, Neurological, Reproducibility of Results, Signal Processing, Computer-Assisted, Time Factors, User-Computer Interface}, issn = {1558-2531}, doi = {10.1109/TBME.2010.2047259}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20403781}, author = {Adam J Wilson and Mellinger, J{\"u}rgen and Gerwin Schalk and Williams, Justin C} } @article {2192, title = {A practical procedure for real-time functional mapping of eloquent cortex using electrocorticographic signals in humans.}, journal = {Epilepsy Behav}, volume = {15}, year = {2009}, month = {07/2009}, pages = {278-86}, abstract = {

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.

}, keywords = {Adult, Brain Mapping, Cerebral Cortex, Electric Stimulation, Electrodes, Implanted, Electroencephalography, Epilepsy, Female, Humans, Male, Middle Aged, Practice Guidelines as Topic, Signal Processing, Computer-Assisted, Young Adult}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2009.04.001}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19366638}, author = {Peter Brunner and A L Ritaccio and Lynch, Timothy M and Emrich, Joseph F and Adam J Wilson and Williams, Justin C and Aarnoutse, Erik J and Ramsey, Nick F and Leuthardt, E C and H Bischof and Gerwin Schalk} } @article {2190, title = {Using an EEG-based brain-computer interface for virtual cursor movement with BCI2000.}, journal = {J Vis Exp}, year = {2009}, month = {07/2009}, abstract = {

A brain-computer interface (BCI) functions by translating a neural signal, such as the electroencephalogram (EEG), into a signal that can be used to control a computer or other device. The amplitude of the EEG signals in selected frequency bins are measured and translated into a device command, in this case the horizontal and vertical velocity of a computer cursor. First, the EEG electrodes are applied to the user s scalp using a cap to record brain activity. Next, a calibration procedure is used to find the EEG electrodes and features that the user will learn to voluntarily modulate to use the BCI. In humans, the power in the mu (8-12 Hz) and beta (18-28 Hz) frequency bands decrease in amplitude during a real or imagined movement. These changes can be detected in the EEG in real-time, and used to control a BCI ([1],[2]). Therefore, during a screening test, the user is asked to make several different imagined movements with their hands and feet to determine the unique EEG features that change with the imagined movements. The results from this calibration will show the best channels to use, which are configured so that amplitude changes in the mu and beta frequency bands move the cursor either horizontally or vertically. In this experiment, the general purpose BCI system BCI2000 is used to control signal acquisition, signal processing, and feedback to the user [3].

}, keywords = {Brain, Calibration, Electrodes, Electroencephalography, Humans, User-Computer Interface}, issn = {1940-087X}, doi = {10.3791/1319}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19641479}, author = {Adam J Wilson and Gerwin Schalk and Walton, L{\'e}o M and Williams, Justin C} } @article {2186, title = {Two-dimensional movement control using electrocorticographic signals in humans.}, journal = {J Neural Eng}, volume = {5}, year = {2008}, month = {03/2008}, pages = {75-84}, abstract = {

We show here that a\ brain-computer\ interface (BCI) using electrocorticographic activity (ECoG) and imagined or overt motor tasks enables humans to control a\ computer\ cursor in two dimensions. Over a brief training period of 12-36 min, each of five human subjects acquired substantial control of particular ECoG features recorded from several locations over the same hemisphere, and achieved average success rates of 53-73\% in a two-dimensional four-target center-out task in which chance accuracy was 25\%. Our results support the expectation that ECoG-based BCIs can combine high performance with technical and\ clinical\ practicality, and also indicate promising directions for further research.

}, keywords = {Adolescent, Adult, Brain Mapping, Data Interpretation, Statistical, Drug Resistance, Electrocardiography, Electrodes, Implanted, Electroencephalography, Epilepsy, Female, Humans, Male, Movement, User-Computer Interface}, issn = {1741-2560}, doi = {10.1088/1741-2560/5/1/008}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18310813}, author = {Gerwin Schalk and Miller, K.J. and Nicholas R Anderson and Adam J Wilson and Smyth, Matt and Ojemann, J G and Moran, D and Jonathan Wolpaw and Leuthardt, E C} }