A method for reconstructing tomographic images of evoked neural activity with electrical impedance tomography using intracranial planar arrays

Abstract

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 fast neural traffic at fascicular level with electrical impedance tomography: proof of principle in rat sciatic nerve

“…EIT images were reconstructed using the following procedure, described in detail in [43], with all of the used tools available online (https://github.com/EIT-team/).…”

“…(2) Inverse problem. Jacobian matrix inversion was accomplished using 0th order Tikhonov regularization and post-processed with noised-based voxel correction [43]. The raw |dZ| data at each time frame was reconstructed in first 5 ms after the stimulus resulting in 500 3D images 0.01 ms apart.…”

Feasibility of imaging evoked activity throughout the rat brain using electrical impedance tomography

“…Zeroth order Tikhonov regularisation with noise based correction was used to reconstruct images (Aristovich et al, 2014), with the regularisation parameter chosen at each time point through generalized cross validation. The reconstructed values in each element of the hexahedral mesh represent a t-score (σ) which was calculated by dividing the reconstructed conductivity change in each element by the reconstructed conductivity change in each element due to baseline noise.…”

Spatial resolution in electrical impedance tomography: A topical review

“…Good resolution was achieved, but the method was unsuitable for test objects lying on the extremes [44]. The same regularization method was optimized for better accuracy by Aristovich et al [45].…”