title: Detection of spontaneous class-specific visual stimuli with high temporal accuracy in human electrocorticography.
abstract: Most brain-computer interface classification experiments from electrical potential recordings have been focused on the identification of classes of stimuli or behavior where the timing of experimental parameters is known or pre-designated. Real world experience, however, is spontaneous, and to this end we describe an experiment predicting the occurrence, timing, and types of visual stimuli perceived by a human subject from electrocorticographic recordings. All 300 of 300 presented stimuli were correctly detected, with a temporal precision of order 20 ms. The type of stimulus (face/house) was correctly identified in 95% of these cases. There were approximately 20 false alarm events, corresponding to a late 2nd neuronal response to a previously identified event.
authors: Neurobiology & Behavior, Physics, University of Washington, Seattle, WA 98195, USA.
authors: Kai J
authors: KJ
authors: Miller
authors: Dora
authors: D
authors: Hermes
authors: Gerwin
authors: G
authors: Schalk
authors: Nick F
authors: NF
authors: Ramsey
authors: Bharathi
authors: B
authors: Jagadeesh
authors: Marcel
authors: M
authors: den Nijs
authors: Jeffrey G
authors: JG
authors: Ojemann
authors: Rajesh P N
authors: RP
authors: Rao
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000379:methods*; D005074:Evoked Potentials, Visual; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface; D014793:Visual Cortex / Q000503:physiopathology*