Variation in Reported Human Head Tissue Electrical Conductivity Values

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR

Variation in reported human head tissue electrical conductivity values

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR

Interrogating spatiotemporal patterns of resting state neuronal and hemodynamic activity in the awake mouse model

Since the advent of functional magnetic resonance imaging (fMRI) and the rise in popularity of its use for resting state functional connectivity mapping (rs-FCM) to non-invasively detect correlated networks of brain activity in human and animal models, many resting state FCM studies have reported differences in these networks under pathologies such as Alzheimer’s or schizophrenia, highlighting the potential for the method’s diagnostic relevance. A common underlying assumption of this analysis, however, is that the blood oxygen level dependent (BOLD) signal of fMRI is a direct measurement of local neural activity. The BOLD signal is in fact a measurement of the local changes in concentration of deoxy-hemoglobin (HbR). Thus, it is imperative that neurovascular coupling—the relationship between neuronal activity and subsequent hemodynamic activity—be better characterized to enable accurate interpretation of resting state fMRI in the context of clinical usage. This dissertation first describes the development and utility of WFOM paradigm for the robust and easily adaptable imaging of simultaneous neuronal and hemodynamic activity in awake mouse models of health or disease in strains with genetically encoded fluorescent calcium reporters. Subsequent exploration of resting state WFOM data collected in Thy1-GCaMP3 and Thy1-GCaMP6f mouse strains is then presented, namely the characterization of spatiotemporal patterns of neuronal and hemodynamic activity and different modulatory depths of neuronal activity via a toolbox of unsupervised blind source separation (e.g. k-means clustering) and supervised (e.g. non-negative least squares, Pearson correlation) analysis tools. The presence of these different modulatory depths of neuronal activity were then confirmed in another Thy1-jRGECO1a mouse strain using the same imaging scheme. Finally, the dissertation documents the application of the WFOM paradigm and select analysis tools to a novel mouse model of diffusely infiltrating glioma, through which neuronal and hemodynamic activity changes during diffusely infiltrating glioma development which impact temporal coherence of the tumor region activity relative to non-tumor regions activity were recorded and analyzed. The paradigm also allowed for recording of numerous spontaneous occurrences of interictal neuronal activity during which neurovascular coupling is modified in the tumor, as well as occurrences of non-convulsive generalized seizure activity (during which neurovascular is non-linear and cortex eventually suffers hypoxia). The detection of spatiotemporal patterns and different modulatory depths of activity in the awake mouse cortex, as well as observation of changes in functional activity in the context of diffusely infiltrating glioma, provide us with new insights into the possible mechanisms underlying variations in resting state connectivity networks found in resting state fMRI studies comparing health and disease states

Design and development of magnetic resonance imaging (MRI) compatible tissue mimicking phantoms for evaluating focused ultrasound thermal protocols

Animal models are often used to test the efficacy and safety of clinical applications employing focused ultrasound that range in various stages of research, development and commercialization. The animals are usually subjected to conditions that cause pain, distress and euthanasia. Access to cadaveric models is not easy and affordable for all research institutions, whereas conservation and changes of their physical properties over time can be a delimiting factor for translational research. The above set the motivation for this project, which its primary objective is to design and develop appropriate tissue mimicking phantoms using a simplistic and cost effective methodology. These phantoms are expected to contribute in reducing the need for animal testing and allow researchers to get hands experience with tools that will promote and accelerate testing in focused ultrasound thermal protocols. The main requirements for these phantoms are to be geometrically accurate, compatible with magnetic resonance imaging (MRI) and to be composed of materials that approximate the acoustic and thermal properties of the replicated tissues. Throughout the duration of the project three ultrasonic composite phantoms (head, femur bone-muscle and breast-rib) were developed. The acoustic properties of candidate materials were assessed using pulse-echo immersion and through transmission techniques. The thermal properties were estimated by observing the rate of heat diffusion following a sonication in the soft tissue parts with MR thermometry. Acrylonitrile butadiene styrene (ABS) was used to replicate bone tissue, where its acoustic attenuation coefficient was found to be 16.01 ± 6.18 dB/cm at 1 MHz and the speed of sound at 2048 ± 79 m/s. Soft tissue parts consisted out of agar-based gels doped with varying concentrations of additives that controlled the relative contribution of acoustic absorption (evaporated milk) and scatter (silica dioxide) to total attenuation independently. Brain tissue phantom (2 % w/v agar - 1.2 % w/v SiO2 - 25 % v/v evaporated milk) matched an attenuation coefficient of 0.59 ± 0.05 dB/cm-MHz whereas muscle and breast mimicking phantom (2 % w/v agar - 2 % w/v SiO2 - 40 % v/v evaporated milk) were estimated of inducing an attenuation coefficient of the order of 0.99 ±0.08 dB/cm-MHz. The speed of sound for the brain and muscle/breast recipe were estimated at 1485 ± 12 m/s and 1529 ± 13 m/s respectively. The thermal conductivity of the brain phantom was estimated to be 0.52 ± 0.06 W/mº-C and 0.57 ± 0.10 W/mº-C for the muscle/breast phantom. The acoustic and thermal properties of candidate materials were within range of the replicated tissues extracted from literature, except the speed of sound in ABS compared which was lower compared to bone (~3000 m/s). Three dimensional models of bone parts (skull, femur, rib) were reconstructed in Standard Tessellation Language (STL) format by segmenting bony tissue of interest from adult human computed tomography (CT) images. The STL bone models were 3D printed in ABS using a fused deposition modelling (FDM) machine. The final composite phantoms were fabricated by molding the agar based soft tissue phantoms inside/around the ABS bone phantoms. The functionality of all three composite phantoms was assessed with focused ultrasound sonications applied by a 1 MHz single element transducer while temperature was monitored with 1.5 Tesla MRI scanner. A spoiled gradient recalled (SPGR) pulse sequence was used to produce phase images that were analyzed using a custom coded software developed in Matlab that employed proton-resonance frequency shift (PRFS) thermometry

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