Imaging of neuronal depolarization in the brain is a major goal in neuroscience, but no technique currently exists that could image neural activity over milliseconds throughout the whole brain. Electrical impedance tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of impedance changes with non-invasive surface electrodes. We report EIT imaging of impedance changes in rat somatosensory cerebral cortex with a resolution of 2 ms and < 200 μm during evoked potentials using epicortical arrays with 30 electrodes. Images were validated with local field potential recordings and current source-sink density analysis. Our results demonstrate that EIT can image neural activity in a volume 7 × 5 × 2 mm in somatosensory cerebral cortex with reduced invasiveness, greater resolution and imaging volume than other methods. Modeling indicates similar resolutions are feasible throughout the entire brain so this technique, uniquely, has the potential to image functional connectivity of cortical and subcortical structures.

A method is presented for reconstructing images of fast neural evoked activity in rat cerebral cortex recorded with electrical impedance tomography (EIT) and a 6 × 5 mm(2) epicortical planar 30 electrode array. A finite element model of the rat brain and inverse solution with Tikhonov regularization were optimized in order to improve spatial resolution and accuracy. The optimized FEM mesh had 7 M tetrahedral elements, with finer resolution (0.05 mm) near the electrodes. A novel noise-based image processing technique based on t-test significance improved depth localization accuracy from 0.5 to 0.1 mm. With the improvements, a simulated perturbation 0.5 mm in diameter could be localized in a region 4 × 5 mm(2) under the centre of the array to a depth of 1.4 mm, thus covering all six layers of the cerebral cortex with an accuracy of <0.1 mm. Simulated deep brain hippocampal or thalamic activity could be localized with an accuracy of 0.5 mm with a 256 electrode array covering the brain. Parallel studies have achieved a temporal resolution of 2 ms for imaging fast neural activity by EIT during evoked activity; this encourages the view that fast neural EIT can now resolve the propagation of depolarization-related fast impedance changes in cerebral cortex and deeper in the brain with a resolution equal or greater to the dimension of a cortical column.

Imaging of acute stroke might be possible using multi-frequency electrical impedance tomography (MFEIT) but requires absolute or frequency difference imaging. Simple linear frequency difference reconstruction has been shown to be ineffective in imaging with a frequency-dependant background conductivity; this has been overcome with a weighted frequency difference approach with correction for the background but this has only been validated for a cylindrical and hemispherical tank. The feasibility of MFEIT for imaging of acute stroke in a realistic head geometry was examined by imaging a potato perturbation against a saline background and a carrot-saline frequency-dependant background conductivity, in a head-shaped tank with the UCLH Mk2.5 MFEIT system. Reconstruction was performed with time difference (TD), frequency difference (FD), FD adjacent (FDA), weighted FD (WFD) and weighted FDA (WFDA) linear algorithms. The perturbation in reconstructed images corresponded to the true position to <9.5% of image diameter with an image SNR of >5.4 for all algorithms in saline but only for TD, WFDA and WFD in the carrot-saline background. No reliable imaging was possible with FD and FDA. This indicates that the WFD approach is also effective for a realistic head geometry and supports its use for human imaging in the future.

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Electrical Impedance Tomography (EIT) is a medical imaging technique which has the potential to reduce time to treatment in acute stroke by rapidly differentiating between ischaemic and haemorrhagic stroke. The potential of these methods has been demonstrated in simulation and phantoms, it has not yet successfully translated to clinical studies, due to high sensitivity to errors in scalp electrode mislocation and poor electrode-skin contact. To overcome these limitations, a novel electrode helmet was designed, bearing 32 independently controlled self-abrading electrodes. The contact impedance was reduced through rotation on an abrasive electrode on the scalp using a combined impedance, rotation and position feedback loop. Potentiometers within each unit measure the electrode tip displacement within 0.1 mm from the rigid helmet body. Characterisation experiments on a large-scale test rig demonstrated that approximately 20 kPa applied pressure and 5 rotations was necessary to achieve the target 5 kΩ contact impedance at 20 Hz. This performance was then replicated in a simplified self-contained unit where spring loaded electrodes are rotated by servo motors. Finally, a 32-channel helmet and controller which sequentially minimised contact impedance and simultaneously located each electrode was built which reduced the electrode application and localisation time to less than five minutes. The results demonstrated the potential of this approach to rapidly apply electrodes in an acute setting, removing a significant barrier for imaging acute stroke with EIT.