Model of Impedance Changes in Unmyelinated Nerve Fibers

Non-invasive imaging of neural activity with magnetic detection electrical impedance tomography (MDEIT): a modelling study

Objectives.(1) Develop a computational pipeline for three-dimensional fast neural magnetic detection electrical impedance tomography (MDEIT), (2) determine whether constant current or constant voltage is preferable for MDEIT, (3) perform reconstructions of simulated neural activity in a human head model with realistic noise and compare MDEIT to EIT and (4) perform a two-dimensional study in a saline tank for MDEIT with optically pumped magnetometers (OPMs) and compare reconstruction algorithms.Approach.Forward modelling and image reconstruction were performed with a realistic model of a human head in three dimensions and at three noise levels for four perturbations representing neural activity. Images were compared using the error in the position and size of the reconstructed perturbations. Two-dimensional MDEIT was performed in a saline tank with a resistive perturbation and one OPM. Six reconstruction algorithms were compared using the error in the position and size of the reconstructed perturbations.Main results.A computational pipeline was developed in COMSOL Multiphysics, reducing the Jacobian calculation time from months to days. MDEIT reconstructed images with a lower reconstruction error than EIT with a mean difference of 7.0%, 5.5% and 11% for three noise cases representing current noise, reduced current source noise and reduced current source and magnetometer noise. A rank analysis concluded that the MDEIT Jacobian was less rank-deficient than the EIT Jacobian. Reconstructions of a phantom in a saline tank had a best reconstruction error of 13%, achieved using 0th-order Tikhonov regularisation with simulated noise-based correction.Significance.This study demonstrated that three-dimensional MDEIT for neural imaging is feasible and that MDEIT reconstructed superior images to EIT, which can be explained by the lesser rank deficiency of the MDEIT Jacobian. Reconstructions of a perturbation in a saline tank demonstrated a proof of principle for two-dimensional MDEIT with OPMs and identified the best reconstruction algorithm.

Organotopic organization of the porcine mid-cervical vagus nerve

Introduction

Despite detailed characterization of fascicular organization of somatic nerves, the functional anatomy of fascicles evident in human and large mammal cervical vagus nerve is unknown. The vagus nerve is a prime target for intervention in the field of electroceuticals due to its extensive distribution to the heart, larynx, lungs, and abdominal viscera. However, current practice of the approved vagus nerve stimulation (VNS) technique is to stimulate the entire nerve. This produces indiscriminate stimulation of non-targeted effectors and undesired side effects. Selective neuromodulation is now a possibility with a spatially-selective vagal nerve cuff. However, this requires the knowledge of the fascicular organization at the level of cuff placement to inform selectivity of only the desired target organ or function.

Methods and results

We imaged function over milliseconds with fast neural electrical impedance tomography and selective stimulation, and found consistent spatially separated regions within the nerve correlating with the three fascicular groups of interest, suggesting organotopy. This was independently verified with structural imaging by tracing anatomical connections from the end organ with microCT and the development of an anatomical map of the vagus nerve. This confirmed organotopic organization.

Discussion

Here we show, for the first time, localized fascicles in the porcine cervical vagus nerve which map to cardiac, pulmonary and recurrent laryngeal function (N = 4). These findings pave the way for improved outcomes in VNS as unwanted side effects could be reduced by targeted selective stimulation of identified organ-specific fiber-containing fascicles and the extension of this technique clinically beyond the currently approved disorders to treat heart failure, chronic inflammatory disorders, and more.

Emerging trends and hot spots on electrical impedance tomography extrapulmonary applications

Objective

Electrical impedance tomography (EIT) develops rapidly in technology and applications. Nowadays EIT is used in multiple clinical and experimental scenarios including pulmonary, brain, and tissue monitoring, etc. The present study explores the research trends and hotspots on EIT extrapulmonary application research by bibliometrics analysis.

Approach

Publications on EIT extrapulmonary applications between 1987 and 2021 were retrieved from the Web of Science Core Collection database. For precise screening, search strategy "electrical impedance tomography" plus "hemodynamic" or "brain" or "nerve" or "cancer" or "venous" or "vessel" or "tumor" or "veterinary" or "tissue" or "cell" or "wearable" or "application" and excluding "lung", "ventilation" "respiratory", "pulmonary", "algorithm", "current", "voltage" or "electrode" were used. CiteSpace and VOSviewer were used to analyze the publication features, collaboration, keywords co-occurrence, and co-cited reference.

Main results

A total of 506 articles were finally identified. The global publication numbers on extrapulmonary applications gradually increased yearly in the past 30 years. The US, UK, and China contributed most three publications concerning EIT extrapulmonary applications. "tissues", "conductivity", "model" were research hotspots, and "cutaneous melanoma", "microstructure", "diagnosis" were recent topics (Portions of this research have previously been presented in poster form).

Significance

Overall, EIT extrapulmonary applications bibliometrics analysis provides a unique insight into research focus, current trends, and future directions.

Overcoming temporal dispersion for measurement of activity-related impedance changes in unmyelinated nerves

Objective.Fast neural electrical impedance tomography is an imaging technique that has been successful in visualising electrically evoked activity of myelinated fibres in peripheral nerves by measurement of the impedance changes (dZ) accompanying excitation. However, imaging of unmyelinated fibres is challenging due to temporal dispersion (TP) which occurs due to variability in conduction velocities of the fibres and leads to a decrease of the signal below the noise with distance from the stimulus. To overcome TP and allow electrical impedance tomography imaging in unmyelinated nerves, a new experimental and signal processing paradigm is required allowing dZ measurement further from the site of stimulation than compound neural activity is visible. The development of such a paradigm was the main objective of this study.Approach.A finite element-based statistical model of TP in porcine subdiaphragmatic nerve was developed and experimentally validatedex-vivo. Two paradigms for nerve stimulation and processing of the resulting data-continuous stimulation and trains of stimuli, were implemented; the optimal paradigm for recording dispersed dZ in unmyelinated nerves was determined.Main results.While continuous stimulation and coherent spikes averaging led to higher signal-to-noise ratios (SNRs) at close distances from the stimulus, stimulation by trains was more consistent across distances and allowed dZ measurement at up to 15 cm from the stimulus (SNR = 1.8 ± 0.8) if averaged for 30 min.Significance.The study develops a method that for the first time allows measurement of dZ in unmyelinated nerves in simulation and experiment, at the distances where compound action potentials are fully dispersed.

Can ionic concentration changes due to mechanical deformation be responsible for the neurostimulation caused by focused ultrasound? A simulation study

Objective.Ultrasound stimulation is an emerging neuromodulation technique, for which the exact mechanism of action is still unknown. Despite the number of hypotheses such as mechanosensitive ion channels and intermembrane cavitation, they fail to explain all of the observed experimental effects. Here we are investigating the ionic concentration change as a prime mechanism for the neurostimulation by the ultrasound.Approach.We derive the direct analytical relationship between the mechanical deformations in the tissue and the electric boundary conditions for the cable theory equations and solve them for two types of neuronal axon models: Hodgkin-Huxley and C-fibre. We detect the activation thresholds for a variety of ultrasound stimulation cases including continuous and pulsed ultrasound and estimate the mechanical deformations required for reaching the thresholds and generating action potentials (APs).Main results.We note that the proposed mechanism strongly depends on the mechanical properties of the neural tissues, which at the moment cannot be located in literature with the required certainty. We conclude that given certain common linear assumptions, this mechanism alone cannot cause significant effects and be responsible for neurostimulation. However, we also conclude that if the lower estimation of mechanical properties of neural tissues in literature is true, or if the normal cavitation occurs during the ultrasound stimulation, the proposed mechanism can be a prime cause for the generation of APs.Significance.The approach allows prediction and modelling of most observed experimental effects, including the probabilistic ones, without the need for any extra physical effects or additional parameters.

Gate Mechanism and Parameter Analysis of Anodal-First Waveforms for Improving Selectivity of C-Fiber Nerves

PURPOSE

Few investigations have been conducted on the selective stimulation of small-radius unmyelinated C nerves (C), which are critical to both the recovery of damaged nerves and pain suppression. The purpose of this study is to understand how an anodal pulse in an anodal-first stimulation could improve C-selectivity over myelinated nociceptive Aδ nerves (Aδ) and to further clarify the landscape of the solution space.

MATERIALS AND METHODS

An adapted Hodgkin-Huxley (HH) model and the McIntyre-Richardson-Grill (MRG) model were used for modeling C and Aδ, respectively, to analyze the underlying ion dynamics and the influence of relevant stimulation waveforms, including monopolar, polarity-symmetric, and asymmetric pulses.

RESULTS

The results showed that polarity asymmetric waveforms with preceding anodal stimulations benefit C-selectivity the most, underlain by the decrease in the potassium ion current of C.

CONCLUSION

The optimal parameters for C-selectivity have been identified in the low-frequency band, remarkably benefiting the design of selective stimulation waveforms for the recovery of damaged nerves and pain management.

Imaging fascicular organization of rat sciatic nerves with fast neural electrical impedance tomography

Imaging compound action potentials (CAPs) in peripheral nerves could help avoid side effects in neuromodulation by selective stimulation of identified fascicles. Existing methods have low resolution, limited imaging depth, or are invasive. Fast neural electrical impedance tomography (EIT) allows fascicular CAP imaging with a resolution of <200 µm, <1 ms using a non-penetrating flexible nerve cuff electrode array. Here, we validate EIT imaging in rat sciatic nerve by comparison to micro-computed tomography (microCT) and histology with fluorescent dextran tracers. With EIT, there are reproducible localized changes in tissue impedance in response to stimulation of individual fascicles (tibial, peroneal and sural). The reconstructed EIT images correspond to microCT scans and histology, with significant separation between the fascicles (p < 0.01). The mean fascicle position is identified with an accuracy of 6% of nerve diameter. This suggests fast neural EIT can reliably image the functional fascicular anatomy of the nerves and so aid selective neuromodulation.

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

OBJECTIVE

To increase the impedance signal amplitude produced during neural activity using a novel approach of implementing a parallel resistor inductor capacitor (RLC) circuit across the current source used in electrical impedance tomography (EIT) of peripheral nerve.

APPROACH

The frequency response of the impedance signal was characterized in the range 4-18 kHz, then a frequency range with significant capacitive charge transfer was selected for experiment with the RLC circuit. Design of the RLC circuit was aided by in vitro impedance measurements on nerve and nerve cuff in the range 5 Hz to 50 kHz.

MAIN RESULTS

The frequency response of the impedance signal across 4-18 kHz showed maximum amplitude at 6-8 kHz, and steady decline in amplitude between 8 and 18 kHz with  -6 dB reduction at 14 kHz. The frequency range 17  ±  1 kHz was selected for the RLC experiment. The RLC experiment was performed on four subjects using an RLC circuit designed to produce a resonant frequency of 17 kHz with a bandwidth of 3.6 kHz, and containing a 22 mH inductive element and a 3.45 nF capacitive element with  +0.8/-  3.45 nF manual tuning range. With the RLC circuit connected, relative increases in the impedance signal (±3σ noise) of 44% (±15%), 33% (±30%), 37% (±8.6%), and 16% (±19%) were produced.

SIGNIFICANCE

The increase in impedance signal amplitude at high frequencies, generated by the novel implementation of a parallel RLC circuit across the drive current, improves spatial resolution by increasing the number of parallel drive currents which can be implemented in a frequency division multiplexed (FDM) EIT system, and aids the long term goal of a real-time FDM EIT system by reducing the need for ensemble averaging.