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

Abstract

Objective. Understanding the coding of neural activity in nerve fascicles is a high priority in computational neuroscience, electroceutical autonomic nerve stimulation and functional electrical stimulation for treatment of paraplegia. Unfortunately, it has been little studied as no technique has yet been available to permit imaging of neuronal depolarization within fascicles in peripheral nerve. Approach. We report a novel method for achieving this, using a flexible cylindrical multi-electrode cuff placed around nerve and the new medical imaging technique of fast neural electrical impedance tomography (EIT). In the rat sciatic nerve, it was possible to distinguish separate fascicles activated in response to direct electrical stimulation of the posterior tibial and common peroneal nerves. Main results. Reconstructed EIT images of fascicular activation corresponded with high spatial accuracy to the appropriate fascicles apparent in histology, as well as the inverse source analysis (ISA) of compound action potentials (CAP). With this method, a temporal resolution of 0.3 ms and spatial resolution of less than 100 µm was achieved. Significance. The method presented here is a potential solution for imaging activity within peripheral nerves with high spatial accuracy. It also provides a basis for imaging and selective neuromodulation to be incorporated in a single implantable nonpenetrating peri-neural device.

Increasing signal amplitude in electrical impedance tomography of neural activity using a parallel resistor inductor capacitor (RLC) circuit

“…Therefore, control of the phase across the drive electrodes and neural tissue, by using the RLC implementation presented here, would be of benefit; though with the caveat that phase contributions from the measurement electrodes must still be contended with. Secondly, the frequency response of the RLC circuit acts as a bandpass filter around the drive current frequency, thereby removing much of the wideband noise which would otherwise be present in the neural activity, typically extracted from peripheral nerve data using a 1 to 2 kHz (-3 dB) low pass filter [10,14], and in the band pass filter range of other drive currents in an FDM EIT system [14].…”

“…Two stainless steel pins, used to administer stimulation pulses, were placed between toes 1-2 and 4-5 of the left hind paw [14], and a third stainless steel pin, which provided a ground path for the data acquisition and filtering hardware via a 460 kΩ resistor, was placed through the contralateral hind paw. An isolated pulse stimulator (A-M Systems Model 2100) administered anode-leading, biphasic stimulation pulses, with 200 μs pulse width per phase and +/-5 mA amplitude, when digitally triggered every 0.5 s [10,14] (National Instruments CompactRIO NI9401). Triggering and recording were synchronised through the LABVIEW FPGA interface, with data recorded for 50 ms windows every 500 ms, and the stimulation pulse triggered at 25 ms through each recording window.…”

“…where the boundary voltage in the inactive nerve state, , was calculated as the average across the time spanning 10 to 5 ms prior to the stimulus pulse. All epochs were processed with the above steps, then several hundred epochs of data were grouped together into data sets, based on the sampling method employed, and ensemble averaged to improve the SNR according to standard practice in impedance signal recordings [10,14]. An example of this collection and ensemble averaging methodology is shown in Fig 3, Figure 4: Grouping of experimental data into sets for characterisation of system noise versus ensemble averaging in experiment 1 (a); characterisation of the temporal changes in the impedance signal in-vitro signal in experiment 2 (b); characterising the frequency response of the impedance signal in experiment 3 (c); and to evaluate the peak amplitude of the impedance signal with and without the RLC circuit in experiment 5 (d).…”

“…Frequency division multiplexing (FDM) of drive currents [12], on the other hand, is theoretically compatible with real-time applications, and has been demonstrated using two multiplexed drive currents in initial studies on epileptiform activity in rat brain [13] and fast neural activity in peripheral nerve [14]. The drawbacks of FDM are the lower signal to noise ratio (SNR) due to each drive current being a noise source and the reduced drive current amplitudes required to avoid stimulating neural tissue, and the limited number of drive currents which can be implemented due to the frequency response roll-off in impedance of neural tissue [10,[15][16][17].…”

Extracting impedance changes from a frequency multiplexed signal during neural activity in sciatic nerve of rat: preliminary study in vitro

“…Furthermore, with the exception of [22] where the bandwidth was +/-50 Hz, the bandwidth of the BPF reflected the frequency components of the underlying transient impedance changes from neural activity, which, as one would expect from the temporal duration of the associated neural activity, are lower in unmyelinated axons of non-mammalian nerves: +/-125 Hz [23], and cerebral cortex: +/-125 to +/-500 Hz [14,15,19,20], than in myelinated axons: +/-2 to +/-3 kHz [2,16]. While most of these neural EIT studies investigated drive currents at more than one frequency [2,[14][15][16][19][20][21][22], only one, a preliminary study on induced epileptic seizures in rat in-vivo at 2.2 and 2.6 kHz, implemented FDM-EIT [20]. Investigations into PDM-EIT of neural activity have, to date, only been performed on resistor phantom [18].…”