title: Effects of uncertainty in head tissue conductivity and complexity on EEG forward modeling in neonates.
abstract: In this study, we investigated the impact of uncertainty in head tissue conductivities and inherent geometrical complexities including fontanels in neonates. Based on MR and CT coregistered images, we created a realistic neonatal head model consisting of scalp, skull, fontanels, cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM). Using computer simulations, we investigated the effects of exclusion of CSF and fontanels, discrimination between GM and WM, and uncertainty in conductivity of neonatal head tissues on EEG forward modeling. We found that exclusion of CSF from the head model induced the strongest widespread effect on the EEG forward solution. Discrimination between GM and white matter also induced a strong widespread effect, but which was less intense than that of CSF exclusion. The results also showed that exclusion of the fontanels from the neonatal head model locally affected areas beneath the fontanels, but this effect was much less pronounced than those of exclusion of CSF and GM/WM discrimination. Changes in GM/WM conductivities by 25% with respect to reference values induced considerable effects in EEG forward solution, but this effect was more pronounced for GM conductivity. Similarly, changes in skull conductivity induced effects in the EEG forward modeling in areas covered by the cranial bones. The least intense effect on EEG was caused by changes in conductivity of the fontanels. Our findings clearly emphasize the impact of uncertainty in conductivity and deficiencies in head tissue compartments on modeling research and localization of brain electrical activity in neonates. Hum Brain Mapp 37:3604-3622, 2016. © 2016 Wiley Periodicals, Inc.
authors.affiliation: GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France.
authors.forename: Hamed
authors.initials: H
authors.lastname: Azizollahi
authors.affiliation: GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France.
authors.forename: Ardalan
authors.initials: A
authors.lastname: Aarabi
authors.affiliation: GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France.|EFSN Pediatric (Pediatric Nervous System Functional Investigation Unit), Department of Pediatrics, CHU AMIENS-SITE SUD, Amiens, France.
authors.forename: Fabrice
authors.initials: F
authors.lastname: Wallois
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D002555:Cerebrospinal Fluid / Q000502:physiology; D003198:Computer Simulation; D004553:Electric Conductivity; D004569:Electroencephalography; D020342:Finite Element Analysis; D066128:Gray Matter / Q000000981:diagnostic imaging / Q000502:physiology; D006801:Humans; D021621:Imaging, Three-Dimensional; D007231:Infant, Newborn; D008279:Magnetic Resonance Imaging; D008297:Male; D008953:Models, Anatomic; D008959:Models, Neurological; D012535:Scalp / Q000000981:diagnostic imaging / Q000502:physiology; D012886:Skull / Q000000981:diagnostic imaging / Q000502:physiology; D014057:Tomography, X-Ray Computed; D035501:Uncertainty; D066127:White Matter / Q000000981:diagnostic imaging / Q000502:physiology
keywords: electroencephalography; finite element method; fontanels; forward modeling; head model; neonates; tissue conductivity