Institute Homepage DE Sign In

Back

Empirical Inference Conference Paper 2004

Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface

Thumb ticker sm l1170153
Empirical Inference
Bernhard Schölkopf
  • Director
no image
Empirical Inference
Jeremy Hill
Thumb ticker sm thumb karin bierig
Empirical Inference, Optics and Sensing Laboratory
Karin Bierig
Research Technician

Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm that allows a user to make a binary decision by focusing attention on one of two concurrent auditory stimulus sequences. Using Support Vector Machine classification and Recursive Channel Elimination on the independent components of averaged event-related potentials, we show that an untrained user‘s EEG data can be classified with an encouragingly high level of accuracy. This suggests that it is possible for users to modulate EEG signals in a single trial by the conscious direction of attention, well enough to be useful in BCI.

Author(s): Hill, J. and Lal, TN. and Bierig, K. and Birbaumer, N. and Schölkopf, B.
Book Title: BioCAS04
Journal: Proceedings of the 2004 IEEE International Workshop on Biomedical Circuits and Systems (BioCAS04)
Number (issue): S3/5/INV- S3/17-20
Pages: 4
Year: 2004
Month: December
Day: 0
Publisher: IEEE Computer Society
Bibtex Type: Conference Paper (inproceedings)
Address: Los Alamitos, CA, USA
DOI: 10.1109/BIOCAS.2004.1454156
Event Name: 2004 IEEE International Workshop on Biomedical Circuits and Systems
Event Place: Singapore
Digital: 0
Electronic Archiving: grant_archive
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@inproceedings{2951,
  title = {Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface},
  journal = {Proceedings of the 2004 IEEE International Workshop on Biomedical Circuits and Systems (BioCAS04)},
  booktitle = {BioCAS04},
  abstract = {Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm that allows a user to make a binary decision by focusing attention on one of two concurrent auditory stimulus sequences. Using Support Vector Machine classification and Recursive Channel Elimination on the independent components of averaged event-related potentials, we show that an untrained user‘s EEG data can be classified with an encouragingly high level of accuracy. This suggests that it is possible for users to modulate EEG signals in a single trial by the conscious direction of attention, well enough to be useful in BCI.},
  number = {S3/5/INV- S3/17-20},
  pages = {4},
  publisher = {IEEE Computer Society},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Los Alamitos, CA, USA},
  month = dec,
  year = {2004},
  slug = {2951},
  author = {Hill, J. and Lal, TN. and Bierig, K. and Birbaumer, N. and Sch{\"o}lkopf, B.},
  month_numeric = {12}
}