In infants, the fontanels and sutures as well as conductivity of the skull influence the volume currents accompanying primary currents generated by active neurons and thus the associated electroencephalography (EEG) and magnetoencephalography (MEG) signals. We used a finite element method (FEM) to construct a realistic model of the head of an infant based on MRI images. Using this model, we investigated the effects of the fontanels, sutures and skull conductivity on forward and inverse EEG and MEG source analysis. Simulation results show that MEG is better suited than EEG to study early brain development because it is much less sensitive than EEG to distortions of the volume current caused by the fontanels and sutures and to inaccurate estimates of skull conductivity. Best results will be achieved when MEG and EEG are used in combination.

Elucidation of infant brain development is a critically important goal given the enduring impact of these early processes on various domains including later cognition and language. Although infants' whole-brain growth rates have long been available, regional growth rates have not been reported systematically. Accordingly, relatively less is known about the dynamics and organization of typically developing infant brains. Here we report global and regional volumetric growth of cerebrum, cerebellum, and brainstem with gender dimorphism, in 33 cross-sectional scans, over 3 to 13 months, using T1-weighted 3-dimensional spoiled gradient echo images and detailed semi-automated brain segmentation. Except for the midbrain and lateral ventricles, all absolute volumes of brain regions showed significant growth, with 6 different patterns of volumetric change. When normalized to the whole brain, the regional increase was characterized by 5 differential patterns. The putamen, cerebellar hemispheres, and total cerebellum were the only regions that showed positive growth in the normalized brain. Our results show region-specific patterns of volumetric change and contribute to the systematic understanding of infant brain development. This study greatly expands our knowledge of normal development and in future may provide a basis for identifying early deviation above and beyond normative variation that might signal higher risk for neurological disorders.