High-resolution EEG source imaging of one-year-old children

Zeynep Akalin Acar, Silvia Ortiz-Mantilla, April Benasich, Scott Makeig

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Recently we described an iterative skull conductivity and source location estimation (SCALE) algorithm for simultaneously estimating head tissue conductivities and brain source locations. SCALE uses a realistic FEM forward problem head model and scalp maps of 10 or more near-dipolar sources identified by independent component analysis (ICA) decomposition of sufficient high-density EEG data. In this study, we applied SCALE to 20 minutes of 64-channel EEG data and magnetic resonance (MR) head images from four twelve-months-of-age infants. For each child, we selected 15-16 near-dipolar independent components from multiple-model adaptive mixture ICA (AMICA) decomposition of their EEG data. SCALE converged to brain-to-skull conductivity ratio (BSCR) estimates in the 10-12 range and mostly compact gyral or sulcal cortical distributions for the IC sources.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages117-120
Number of pages4
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2016-October

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country/TerritoryUnited States
CityOrlando
Period8/16/168/20/16

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Health Informatics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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