Development and validation of a realistic head model for EEG

The utility of extracranial electrical or magnetic field recordings (EEG or MEG) is greatly enhanced if the generators of the bioelectromagnetic fields can be determined accurately from the measured fields. This procedure, known as the 'inverse method,' depends critically on calculations of the projection from generators in the brain to the EEG and MEG sensors. Improving and validating this calculation, known as the 'forward solution,' is the focus of this dissertation. The improvements involve more accurate modeling of the structures of the brain and thus understanding how current flows within the brain as a result of addition of structures in the forward model. Validation compares calculations using different forward models to the experimental results obtained by stimulating with implanted dipole electrodes.;The human brain tissue displays inhomogeneity in electrical conductivity and also displays anisotropy, notably in the skull and brain white matter. In this dissertation, a realistic head model has been implemented using the finite element method to calculate the effects of inhomogeneity and anisotropy in the human brain. Accurate segmentation of the brain tissue type is implemented using a semi-automatic method to segment multimodal imaging data from multi-spectral MRI scans (different flip angles) in conjunction with the regular T1-weighted scans and computed x-ray tomography images. The electrical conductivity in the anisotropic white matter tissue is quantified from diffusion tensor MRI. The finite element model is constructed using AMIRA, a commercial segmentation and visualization tool and solved using ABAQUS, a commercial finite element solver.;The model is validated using experimental data collected from intracranial stimulation in medically intractable epileptic patients. Depth electrodes are implanted in medically intractable epileptic patients in order to direct surgical therapy when the foci cannot be localized with the scalp EEG. These patients present the unique opportunity to generate sources at known positions in the human brain using the depth electrodes. Known dipolar sources were created inside the human brain at known locations by injecting a weak biphasic current (sub-threshold) between alternate contacts on the depth electrode. The corresponding bioelectric fields (intracranial and scalp EEG) were recorded in patients during the injection of biphasic pulses.;The in vivo depth stimulation data provides a direct test of the performance of the forward model. The factors affecting the accuracy of the intracranial measurements are quantified in a precise manner by studying the effects of including different tissue types and anisotropy. The results show that white matter anisotropy is crucial for predicting the electric fields in a precise manner for intracranial locations, thereby affecting the source reconstructions. Accurate modeling of the skull is necessary for predicting accurately the scalp measurements. In sum, with the aid of high-resolution finite element realistic head models it is possible to accurately predict electric fields generated by current sources in the brain and thus in a precise way, understand the relationship between electromagnetic measure and neuronal activity at the voxel-scale.