High-Resolution EEG Source Imaging of One-Year Old Children

Zeynep Akalin Acar1, Silvia Ortiz-Mantilla2, April A. Benasich3, Scott Makeig

  • 1University of California San Diego
  • 2Rutgers The State University of New Jersey
  • 3Ctr for the Neurosciences, Rutgers University-Newark

Details

09:00 - 09:15 | Wed 17 Aug | Fantasia F | WeAT6.5

Session: Electrical Source Imaging

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.