Correlation between intra- and extracranial background EEG

Jonas Duun-Henriksen, Troels W. Kjaer, Rasmus E. Madsen, Line S. Remvig, Carsten E. Thomsen, Helge B.D. Sorensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Scalp EEG is the most widely used modality to record the electrical signals of the brain. It is well known that the volume conduction of these brain waves through the brain, cerebrospinal fluid, skull and scalp reduces the spatial resolution and the signal amplitude. So far the volume conduction has primarily been investigated by realistic head models or interictal spike analysis. We have set up a novel and more realistic experiment that made it possible to compare the information in the intra- and extracranial EEG. We found that intracranial EEG channels contained correlated patterns when placed less than 30 mm apart, that intra- and extracranial channels were partly correlated when placed less than 40 mm apart, and that extracranial channels probably were correlated over larger distances. The underlying cortical area that influences the extracranial EEG is found to be up to 45 cm2. This area is larger than previously reported.
Original languageEnglish
Title of host publicationIEEE Engineering in medicine and biology society conference proceedings
PublisherIEEE
Publication date2012
Pages5198 - 5201
ISBN (Print)978-1-4244-4119-8
DOIs
Publication statusPublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Hilton Bayfront Hotel, San Diego, CA, United States
Duration: 28 Aug 20121 Sep 2012
http://embc2012.embs.org/

Conference

Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
LocationHilton Bayfront Hotel
CountryUnited States
CitySan Diego, CA
Period28/08/201201/09/2012
Internet address

Keywords

  • Bioengineering
  • Communication, Networking & Broadcasting
  • Components, Circuits, Devices & Systems
  • Computing & Processing (Hardware/Software)
  • Signal Processing & Analysis

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