title: Electric Field Encephalography as a tool for functional brain research: a modeling study.
abstract: We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2-3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.
authors.affiliation: Northeastern University, Boston, Massachusetts, United States of America. y.petrov@neu.edu
authors.forename: Yury
authors.initials: Y
authors.lastname: Petrov
authors.forename: Srinivas
authors.initials: S
authors.lastname: Sridhar
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology; D001931:Brain Mapping / Q000379:methods; D004569:Electroencephalography / Q000379:methods; D006801:Humans; D008959:Models, Neurological