Visual gate for brain-computer interfaces

Brain-Computer Interfaces (BCI) based on event related potentials (ERP) have been successfully developed for applications like virtual spellers and navigation systems. This study tests the use of visual stimuli unbalanced in the subject's field of view to simultaneously cue mental imagery tasks (left vs. right hand movement) and detect subject attention. The responses to unbalanced cues were compared with the responses to balanced cues in terms of classification accuracy. Subject specific ERP spatial filters were calculated for optimal group separation. The unbalanced cues appear to enhance early ERPs related to cue visuospatial processing that improved the classification accuracy (as low as 6%) of ERPs in response to left vs. right cues soon (150–200 ms) after the cue presentation. This work suggests that such visual interface may be of interest in BCI applications as a gate mechanism for attention estimation and validation of control decisions.

[1]  Yijun Wang,et al.  An Algorithm for Idle-State Detection in Motor-Imagery-Based Brain-Computer Interface , 2007, Comput. Intell. Neurosci..

[2]  Gary E. Birch,et al.  Towards Development of a 3-State Self-Paced Brain-Computer Interface , 2007, Comput. Intell. Neurosci..

[3]  Steven J. Schiff,et al.  Neuronal spatiotemporal pattern discrimination: The dynamical evolution of seizures , 2005, NeuroImage.

[4]  Dan Wu,et al.  Combining Spatial Filters for the Classification of Single-Trial EEG in a Finger Movement Task , 2007, IEEE Transactions on Biomedical Engineering.

[5]  E Donchin,et al.  A new method for off-line removal of ocular artifact. , 1983, Electroencephalography and clinical neurophysiology.

[6]  D J McFarland,et al.  Brain-computer interface research at the Wadsworth Center. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[7]  B.S. Reddy,et al.  Estimation of driver attention using Visually Evoked Potentials , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[8]  Gert Pfurtscheller,et al.  Motor imagery and direct brain-computer communication , 2001, Proc. IEEE.

[9]  S. Kobayashi,et al.  Electroencephalographic activity associated with shifts of visuospatial attention. , 1994, Brain : a journal of neurology.

[10]  J. Wolpaw,et al.  A P300-based brain–computer interface for people with amyotrophic lateral sclerosis , 2008, Clinical Neurophysiology.

[11]  F. Perrin,et al.  Spherical splines for scalp potential and current density mapping. , 1989, Electroencephalography and clinical neurophysiology.

[12]  Matthias M. Müller,et al.  Concurrent recording of steady-state and transient event-related potentials as indices of visual-spatial selective attention , 2000, Clinical Neurophysiology.

[13]  Xiaorong Gao,et al.  A brain–computer interface using motion-onset visual evoked potential , 2008, Journal of neural engineering.