NeuroImage (Apr 2020)
In vivo imaging of deep neural activity from the cortical surface during hippocampal epileptiform events in the rat brain using electrical impedance tomography
Abstract
Electrical impedance tomography (EIT) is a medical imaging technique which reconstructs images of the internal impedance changes within an object using non-penetrating surface electrodes. To date, EIT has been used to image fast neural impedance changes during somatosensory evoked potentials and epileptiform discharges through the rat cerebral cortex with a resolution of 2 ms and <300 μm. However, imaging of neural activity in subcortical structures has never been achieved with this technique. Here, we evaluated the feasibility of using EIT to image epileptiform activity in the rat hippocampus using non-penetrating electrodes implanted on the cortical surface. Hippocampal epileptiform events, comprising repetitive 30–50 Hz ictal spikes, were induced by electrically stimulating the perforant path of rats anaesthetised with fentanyl-isoflurane. For each of ≥30 seizures, impedance measurements were obtained by applying 100 μA current at 1.4 kHz through an independent pair of electrodes on a 54-electrode planar epicortical array and recording boundary voltages on all remaining electrodes. EIT images of averaged ictal spikes were reconstructed using impedance recordings from all seizures in each animal. These revealed a focus of neural activity localised to the dentate gyrus which was spatially and temporally aligned to local field potential (LFP) recordings and could be reconstructed reproducibly in all animals with a localisation accuracy of ≤400 μm (p < 0.03125, N = 5). These findings represent the first experimental evidence of the ability of EIT to image neural activity in subcortical structures from the surface of the cortex with high spatiotemporal resolution and suggest that this method may be used for improving understanding of functional connectivity between cortico-hippocampal networks in both physiological and pathophysiological states.
