title: Analysis of large-scale brain data for brain-computer interfaces.
abstract: We present a systematic technique for extraction of useful information from large-scale neural data in the context of brain-computer interfaces. The technique is based on a direct linear discriminant analysis, recently developed for face recognition problems. We show that this technique is capable of extracting useful information from brain data in a systematic fashion and can serve as a general analytical tool for other types of biomedical data, such as images and collections of images (movies). The performance of the method is tested on intracranial electroencephalographic data recorded from the human brain.
authors.affiliation: Department of Electrical Engineering & Computer Science, University of California, Irvine, CA 92697, USA. jmeyer@uci.edu
authors.forename: Koel
authors.initials: K
authors.lastname: Das
authors.forename: Joerg
authors.initials: J
authors.lastname: Meyer
authors.forename: Zoran
authors.initials: Z
authors.lastname: Nenadic
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D003201:Computers; D003627:Data Interpretation, Statistical; D016002:Discriminant Analysis; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D013997:Time Factors; D014584:User-Computer Interface