Determination of head conductivity frequency response in vivo with optimized EIT-EEG

Electroencephalography (EEG) benefits from accurate head models. Dipole source modelling errors can be reduced from over 1 cm to a few millimetres by replacing generic head geometry and conductivity with tailored ones. When adequate head geometry is available, electrical impedance tomography (EIT) can be used to infer the conductivities of head tissues. In this study, the boundary element method (BEM) is applied with three-compartment (scalp, skull and brain) subject-specific head models.The optimal injection of small currents to the head with a modular EIT current injector, and voltage measurement by an EEG amplifier is first sought by simulations. The measurement with a 64-electrode EEG layout is studied with respect to three noise sources affecting EIT: background EEG, deviations from the fitting assumption of equal scalp and brain conductivities, and smooth model geometry deviations from the true head geometry. The noise source effects were investigated depending on the positioning of the injection and extraction electrode and the number of their combinations used sequentially.The deviation from equal scalp and brain conductivities produces rather deterministic errors in the three conductivities irrespective of the current injection locations. With a realistic measurement of around 2 min and around 8 distant distinct current injection pairs, the error from the other noise sources is reduced to around 10% or less in the skull conductivity. The analysis of subsequent real measurements, however, suggests that there could be subject-specific local thinnings in the skull, which could amplify the conductivity fitting errors. With proper analysis of multiplexed sinusoidal EIT current injections, the measurements on average yielded conductivities of 340 mS/m (scalp and brain) and 6.6 mS/m (skull) at 2 Hz. From 11 to 127 Hz, the conductivities increased by 1.6% (scalp and brain) and 6.7% (skull) on the average. The proper analysis was ensured by using recombination of the current injections into virtual ones, avoiding problems in location-specific skull morphology variations.The observed large intersubject variations support the need for in vivo measurement of skull conductivity, resulting in calibrated subject-specific head models

Variability of head tissues’ conductivities and their impact in electrical brain activity research

The presented thesis endeavoured to establish the impact that the variability in electrical conductivity of human head tissues has on electrical brain imaging research, particularly transcranial direct current stimulation (tDCS) and electroencephalography (EEG). A systematic meta-analysis was firstly conducted to determine the consistency of reported measurements, revealing significant deviations in electrical conductivity measurements predominantly for the scalp, skull, GM, and WM. Found to be of particular importance was the variability of skull conductivity, which consists of multiple layers and bone compositions, each with differing conductivity. Moreover, the conductivity of the skull was suggested to decline with participant age and hypothesised to correspondingly impact tDCS induced fields. As expected, the propositioned decline in the equivalent (homogeneous) skull conductivity as a function of age resulted in reduced tDCS fields. A further EEG analysis also revealed, neglecting the presence of adult sutures and deviation in proportion of spongiform and compact bone distribution throughout the skull, ensued significant errors in EEG forward and inverse solutions. Thus, incorporating geometrically accurate and precise volume conductors of the skull was considered as essential for EEG forward analysis and source localisation and tDCS application. This was an overarching conclusion of the presented thesis. Individualised head models, particularly of the skull, accounting for participant age, the presence of sutures and deviation in bone composition distribution are imperative for electrical brain imaging. Additionally, it was shown that in vivo, individualised measurements of skull conductivity are further required to fully understand the relationship between conductivity and participant demographics, suture closure, bone compositions, skull thickness and additional factors