Electrical conductivities of compact, spongiosum, and bulk layers of the live human skull were determined at varying frequencies and electric fields at room temperature using the four-electrode method. Current, at higher densities that occur in human cranium, was applied and withdrawn over the top and bottom surfaces of each sample and potential drop across different layers was measured. We used a model that considers variations in skull thicknesses to determine the conductivity of the tri-layer skull and its individual anatomical structures. The results indicate that the conductivities of the spongiform (16.2-41.1 milliS/m), the top compact (5.4-7.2 milliS/m) and lower compact (2.8-10.2 milliS/m) layers of the skull have significantly different and inhomogeneous conductivities. The conductivities of the skull layers are frequency dependent in the 10-90 Hz region and are non-ohmic in the 0.45-2.07 A/m2 region. These current densities are much higher than those occurring in human brain.

We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting-state networks (RSNs) compared to echo-planar imaging (Posse et al., 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arterio-venous malformations, and detection of abnormal resting-state connectivity in epilepsy. In patients with motor impairment, resting-state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arterio-venous malformations and a trend toward reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting-state connectivity and cerebro-vascular pulsatility for clinical and neuroscience research applications.

Magnetic source imaging can provide unique localization information that is not available when other noninvasive methods are used. Magnetic source imaging appears most useful for cases of neocortical epilepsy. In particular, when an MS imaging study revealed six or more interictal spikes that were densely clustered in a single anatomical location, the MS image was highly correlated with the zone of seizure origin identified by ECoG. In these cases the MS imaging data may be useful to guide placement of intracranial electrodes.

The electrical conductivities (sigma) of freshly excised neocortex and subcortical white matter were studied in the frequency range of physiological relevance for EEG (5-1005 Hz) in 21 patients (ages 0.67 to 55 years) undergoing epilepsy neurosurgery. Surgical patients were classified as having cortical dysplasia (CD) or non-CD pathologies. Diffusion tensor imaging (DTI) for apparent diffusion coefficient (ADC) and fractional anisotropy (FA) was obtained in 9 patients. Results found that electrical conductivities in freshly excised neocortex vary significantly from patient to patient (sigma = 0.0660-0.156 S/m). Cerebral cortex from CD patients had increased conductivities compared with non-CD cases. In addition, longer seizure durations positively correlated with conductivities for CD tissue, while they negatively correlated for non-CD tissue. DTI ADC eigenvalues inversely correlated with electrical conductivity in CD and non-CD tissue. These results in a small initial cohort indicate that electrical conductivity of freshly excised neocortex from epilepsy surgery patients varies as a consequence of clinical variables, such as underlying pathology and seizure duration, and inversely correlates with DTI ADC values. Understanding how disease affects cortical electrical conductivity and ways to non-invasively measure it, perhaps through DTI, could enhance the ability to localize EEG dipoles and other relevant information in the treatment of epilepsy surgery patients.