Spatiotemporal linear decoding of brain state: application to performance augmentation in high-throughput tasks

Parra, L., Christoforou, C., Gerson, A., Dyrholm, M., Luo, A., Wagner, M., Philiastides, M.G. and Sajda, P. (2008) Spatiotemporal linear decoding of brain state: application to performance augmentation in high-throughput tasks. IEEE Signal Processing Magazine, 25(1), pp. 107-115. (doi: 10.1109/MSP.2008.4408447)

Abstract

This review summarizes linear spatiotemporal signal analysis methods that derive their power from careful consideration of spatial and temporal features of skull surface potentials. BCIs offer tremendous potential for improving the quality of life for those with severe neurological disabilities. At the same time, it is now possible to use noninvasive systems to improve performance for time-demanding tasks. Signal processing and machine learning are playing a fundamental role in enabling applications of BCI and in many respects, advances in signal processing and computation have helped to lead the way to real utility of noninvasive BCI.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Philiastides, Professor Marios
• Authors: Parra, L., Christoforou, C., Gerson, A., Dyrholm, M., Luo, A., Wagner, M., Philiastides, M.G., and Sajda, P.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: IEEE Signal Processing Magazine
• Publisher: IEEE
• ISSN: 1053-5888