Mining terabytes of submillimeter-resolution ECoG datasets for neurophysiologic biomarkers.


Conference Paper

Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. We present innovations in both hardware and software that allow sampling and interpretation of data from brain networks from hundreds or thousands of sensors at submillimeter resolution. These innovations consist of novel flexible, active electrode arrays and unsupervised algorithms for detecting and classifying neurophysiologic biomarkers, specifically high frequency oscillations. We propose these innovations as the foundation for a new generation of closed loop diagnostic and therapeutic medical devices, and brain-machine interfaces.

Full Text

Duke Authors

Cited Authors

  • Viventi, J; Blanco, J; Litt, B

Published Date

  • January 2010

Published In

Volume / Issue

  • 2010 /

Start / End Page

  • 3825 - 3826

PubMed ID

  • 21097061

Pubmed Central ID

  • 21097061

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2010.5627681