Separation of spikes from background by independent component analysis with dipole modeling and comparison to intracranial recording

K. Kobayashi, I. Merlet, J. Gotman

Research output: Contribution to journalArticle

56 Citations (Scopus)

Abstract

Objective: Epileptiform discharges can be objectively separated from the EEG background by independent component analysis (ICA) into the discharge's waveform and its spatial distribution. The correspondence between ICA components, including epileptiform transients extracted from the scalp EEG and intracranial epileptic fields, was investigated. Methods: In 11 spike patterns from 8 patients, the scalp EEG data were decomposed by ICA. The corresponding averaged intracranial data were compared with the extracted epileptic components regarding the number of source patterns and source locations estimated from ICA maps. Results: Clear epileptic components could be separated in 10/11 spike patterns. The number of epileptic components was identical to the number of intracranial field peaks in 7 spike patterns with simple intracranial fields, and was less in the remaining 3 patterns with complex intracranial peaks. The distance between the contact of the maximal intracranial field and the dipole location estimated by the single dipole model for the clearest epileptic component ranged from 4.7 to 31.9 mm. Conclusions: The number of epileptic ICA components largely matched the number of intracranial field patterns, and the dipole location estimated for the map of the clearest epileptic component was generally correct. This establishes the validity of epileptic components extracted by ICA from the scalp background.

Original languageEnglish
Pages (from-to)405-413
Number of pages9
JournalClinical Neurophysiology
Volume112
Issue number3
DOIs
Publication statusPublished - Mar 3 2001

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Keywords

  • Dipole modeling
  • Independent component analysis
  • Spike
  • Stereoelectroencephalography

ASJC Scopus subject areas

  • Sensory Systems
  • Neurology
  • Clinical Neurology
  • Physiology (medical)

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