Characterisation and imaging of cortical impedance changes during interictal and ictal activity in the anaesthetised rat

Abstract

Epilepsy affects approximately 50 million people worldwide, and 20-30% of these cases are refractory to antiepileptic drugs. Many patients with intractable epilepsy can benefit from surgical resection of the tissue generating the seizures; however, difficulty in precisely localising seizure foci has limited the number of patients undergoing surgery as well as potentially lowered its effectiveness. Here we demonstrate a novel imaging method for monitoring rapid changes in cerebral tissue impedance occurring during interictal and ictal activity, and show that it can reveal the propagation of pathological activity in the cortex. Cortical impedance was recorded simultaneously to ECoG using a 30-contact electrode mat placed on the exposed cortex of anaesthetised rats, in which interictal spikes (IISs) and seizures were induced by cortical injection of 4-aminopyridine (4-AP), picrotoxin or penicillin. We characterised the tissue impedance responses during IISs and seizures, and imaged these responses in the cortex using Electrical Impedance Tomography (EIT). We found a fast, transient drop in impedance occurring as early as 12ms prior to the IISs, followed by a steep rise in impedance within ~120ms of the IIS. EIT images of these impedance changes showed that they were co-localised and centred at a depth of 1mm in the cortex, and that they closely followed the activity propagation observed in the surface ECoG signals. The fast, pre-IIS impedance drop most likely reflects synchronised depolarisation in a localised network of neurons, and the post-IIS impedance increase reflects the subsequent shrinkage of extracellular space caused by the intense activity. EIT could also be used to picture a steady rise in tissue impedance during seizure activity, which has been previously described. Thus, our results demonstrate that EIT can detect and localise different physiological changes during interictal and ictal activity and, in conjunction with ECoG, may in future improve the localisation of seizure foci in the clinical setting.

Keywords: EIT; Epilepsy; Imaging; Interictal spike; Seizure; Tissue impedance.

Fig. 1

Setup and signal processing for simultaneous ECoG-EIT recordings of epileptic activity. (A) A 30-electrode mat connected to an EEG amplifier and a multiplexed current source was placed on the exposed cortex of an anaesthetised rat. Impedance was measured by injecting a 60 μA, 1700 Hz sinusoidal current between a pair of electrodes on the mat. One of three epileptogenic agents – 4-AP, picrotoxin or penicillin – was injected directly in the cortex through the electrode mat. (B) The recorded broadband voltage signals were low-pass filtered at 300 Hz to recover the ECoG signals (black traces) and band-pass filtered around 1700 Hz (300 Hz bandwidth) followed by demodulation to obtain the dZ signal (red trace). The dZ signal was analysed with respect to IISs observed in the ECoG.

Fig. 2

Reproducible IISs and IIS-related impedance changes across three seizure models. (A) Simultaneous ECoG (top trace) and dZ signals (bottom trace) recorded from the same electrode. Stable IISs were observed in this electrode shortly after injection of 4-AP, and at each IIS the dZ signal exhibited a fast negative deflection followed by a slower rise and decay. (B–C) Same as (A), but for rats injected with picrotoxin (B) or penicillin (C).

Fig. 3

Different impedance measurements were made with the same electrodes by changing the current injection configuration. (A) IIS-triggered dZ signal traces observed across the electrode mat (n = 54). Using the largest IIS over the array as a common trigger, the dZ signal at each electrode was aligned and averaged across IISs and are plotted at their corresponding electrode locations. Filled circles indicate electrodes used for current injection. (B) dZ signals measured using a different pair of injection electrodes (n = 34). (C) Comparison of ECoG (top) and dZ signals (bottom) recorded at the same electrode but using different current injection configurations. Signals measured using the configuration in (A) and (B) are shown in red and blue, respectively, and the corresponding dZ signals are indicated with the same colours in (A) and (B). Thick line: mean signal, band: 99% confidence interval for the mean (n = 54 or 34 IISs for the red or blue trace, respectively). (D) IIS-triggered ECoG signal pattern over the array (n = 54).

Fig. 4

Amplitude and relative timing of IIS-triggered dZ signals; data from the same recording as in Fig. 3. (A) (top) IISs at electrode with largest negative deflections (bottom left neighbour of electrode in Fig. 3), aligned by their negative peaks. Grey traces: individual IISs, thick black line: average IIS. (bottom) IIS-triggered dZ signal traces; each grey trace corresponds to the average measurement at an electrode and for a specific current injection configuration (n = 371 measurement combinations from 16 injection configurations). Blue circles indicate the minimum of each trace, and green circles indicate the first point reaching a significant positive value (p < 0.01, Student's t-test; n between 10 and 57 IISs for each trace). (B) Same data as in (A), but shown over a larger timescale. Red circles indicate the maximum of each trace. (C) Amplitude (top) and time (middle) distributions of the dZ signal minima (blue circles in (A)). (bottom) Distribution of the earliest time that dZ signals attain a positive value (green circles in (A)), expressed as onset time relative to the IIS peak. (D) Amplitude (top) and time (bottom) distributions of the dZ signal maxima (red circles in (B)). (E) Scatter plot between minimum and maximum amplitude of IIS-triggered dZ signal traces showing significant correlation (r =− 0.59, p < 0.01, n = 371).

Fig. 5

Volumetric reconstruction of impedance changes from data shown in Fig. 4. Each tile is a raster image showing the estimated impedance change at a specific depth (rows; range 0.2–2 mm) and time point (columns). The first row shows the simultaneous ECoG map smoothed with a Gaussian filter (standard deviation = half the distance between adjacent electrodes). Tiles are rotated by 90° clockwise relative to the electrode maps shown in Fig. 3. (A) Impedance changes and ECoG map between − 50 ms and 92.5 ms around IIS peak. Fast impedance decreases can be seen around − 12.5 ms, and slow impedance increases start around 32.5–40 ms. (B) Impedance changes and ECoG map between 0 and 950 ms.

Fig. 6

Coincident location of IIS and reconstructed impedance changes. (A–C) Smoothed ECoG map (left column) and reconstructed impedance changes (middle and right columns) for three rats. The orientation of the rasters is the same as that of the electrode maps in Fig. 3. ECoG maps are shown at the time of the IIS peak, and impedance changes are shown at 1 mm depth and at the time of maximum change before the IIS peak (middle column; time shown in inset) or at 500 ms after the IIS peak (right column). Seizure models shown: 4-AP (A; same rat as in Fig. 5), picrotoxin (B) and penicillin (C). (D) Distance in mm between the centres-of-mass of the negative ECoG deflections and the impedance changes for all 8 rats.

Fig. 7

Propagation of IIS in one rat (picrotoxin model). (A) ECoG map shown at 5 time points around the IIS peak (middle tile). Arrow indicates the location of negative voltage deflections preceding the main IIS. (B) Reconstructed impedance changes at 1 mm depth at the same time points as in (A). (C) Reconstructed impedance changes at 1 mm depth at 5 time points after the IIS.

Fig. 8

Simultaneous ECoG (black) and dZ signals (red) during ictal activity in one rat (model: 4-AP). (top) Raster images showing the reconstructed impedance changes at 1 mm depth at the corresponding time points in the main graph. (bottom) Reconstructed impedance changes at 1 mm depth shown over a finer temporal scale (100 ms steps).