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.

Model-based geometrical optimisation and in vivo validation of a spatially selective multielectrode cuff array for vagus nerve neuromodulation.

BACKGROUND: Neuromodulation by electrical stimulation of the human cervical vagus nerve may be limited by adverse side effects due to stimulation of off-target organs. It may be possible to overcome this by spatially selective stimulation of peripheral nerves. Preliminary studies have shown this is possible using a cylindrical multielectrode human-sized nerve cuff in vagus nerve selective neuromodulation. NEW METHOD: The model-based optimisation method for multi-electrode geometric design is presented. The method was applied for vagus nerve cuff array and suggested two rings of 14 electrodes, 3 mm apart, with 0.4 mm electrode width and separation and length 0.5-3 mm, with stimulation through a pair in the same radial position on the two rings. The electrodes were fabricated using PDMS-embedded stainless steel foil and PEDOT: pTS coating. RESULTS: In the cervical vagus nerve in anaesthetised sheep, it was possible to selectively reduce the respiratory breath rate (RBR) by 85 ± 5% without affecting heart rate, or selectively reduce heart rate (HR) by 20 ± 7% without affecting respiratory rate. The cardiac- and pulmonary-specific sites on the nerve cross-sectional perimeter were localised with a radial separation of 105 ± 5 degrees (P < 0.01, N = 24 in 12 sheep). CONCLUSIONS: Results suggest organotopic or function-specific organisation of neural fibres in the cervical vagus nerve. The optimised electrode array demonstrated selective electrical neuromodulation without adverse side effects. It may be possible to translate this to improved treatment by electrical autonomic neuromodulation for currently intractable conditions.

Quantification of clinically applicable stimulation parameters for precision near-organ neuromodulation of human splenic nerves.

Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial.

Simulation of impedance changes with a FEM model of a myelinated nerve fibre.

OBJECTIVE: Fast neural electrical impedance tomography (EIT) is a method which permits imaging of neuronal activity in nerves by measuring the associated impedance changes (dZ). Due to the small magnitudes of dZ signals, EIT parameters require optimization, which can be done using in silico modelling: apart from predicting the best parameters for imaging, it can also help to validate experimental data and explain the nature of the observed dZ. This has previously been completed for unmyelinated fibres, but an extension to myelinated fibres is required for the development of a full nerve model which could aid imaging neuronal traffic at the fascicular level and optimise neuromodulation of the supplied internal organs to treat various diseases. APPROACH: An active finite element method (FEM) model of a myelinated fibre coupled with external space was developed. A spatial dimension was added to the experimentally validated space-clamped model of a human sensory fibre using the double cable paradigm. Electrical parameters of the model were changed so that nodal and internodal membrane potential as well as propagation velocity agreed with experimental values. Impedance changes were simulated during activity under various conditions and the optimal parameters for imaging were determined. MAIN RESULTS: When using AC, dZ could be recorded only at frequencies above 4 kHz, which is supported by experimental data. Optimal bandwidths for dZ measurement were found to increase with AC frequency. SIGNIFICANCE: The novel fully bi-directionally coupled FEM model of a myelinated fibre was able to optimize EIT for myelinated fibres and explain the biophysical basis of the measured signals.

Effect of dispersion in nerve on compound action potential and impedance change: a modelling study.

OBJECTIVE: Electrical impedance tomography (EIT) is capable of imaging fast compound electrical activity (compound action potentials, or CAPs) inside peripheral nerves. The ability of EIT to detect impedance changes (dZ) which arise from the opening of ion channels during the CAP is limited by the dispersion with distance from the site of onset, as fibres have differing conduction velocities. The effect is largest for autonomic nerves mainly formed of slower conducting unmyelinated fibres where signals cannot be recorded more than a few cm away from the stimulation. However, as CAPs are biphasic, monophasic dZ are expected to be detectable further than them; testing this hypothesis was the main objective of this study. APPROACH: An anatomically accurate FEM model and simplified statistical models of 50-fibre Hodgkin-Huxley and C-nociceptor nerves were developed with normally distributed conduction velocities; the statistical models were extended to realistic nerves. MAIN RESULTS: Fifty-fibre models showed that dZ could persist further than biphasic CAPs, as these then cancelled. For realistic nerves consisting of Aα or Aß fibres, significant dZ could be detected at 50 cm from the onset site with signal-to-noise ratios (SNR, mean ± s.d.) of 2.7 ± 0.2 and 1.8 ± 0.1 respectively; Aδ and rat sciatic nerve-at 20 cm (1.6 ± 0.03 and 1.6 ± 0.06), rat vagus-at 10 cm (1.6 ± 0.05); C fibres-at 1-2 cm (2.4 ± 0.02). SIGNIFICANCE: This study provides a basis for determining the distance over which EIT may be used to image fascicular activity in electroceuticals and suggests dZ will persist further than CAPs if biphasic.

Model of Impedance Changes in Unmyelinated Nerve Fibers.

OBJECTIVE: Currently, there is no imaging method that is able to distinguish the functional activity inside nerves. Such a method would be essential for understanding peripheral nerve physiology and would allow precise neuromodulation of organs these nerves supply. Electrical impedance tomography (EIT) is a method that produces images of electrical impedance change (dZ) of an object by injecting alternating current and recording surface voltages. It has been shown to be able to image fast activity in the brain and large peripheral nerves. To image inside small autonomic nerves, mostly containing unmyelinated fibers, it is necessary to maximize SNR and optimize the EIT parameters. An accurate model of the nerve is required to identify these optimal parameters as well as to validate data obtained in the experiments. METHODS: In this study, we developed two three-dimensional models of unmyelinated fibers: Hodgkin-Huxley (HH) squid giant axon (single and multiple) and mammalian C-nociceptor. A coupling feedback system was incorporated into the models to simulate direct and alternating current application and simultaneously record external field during action potential propagation. RESULTS: Parameters of the developed models were varied to study their influence on the recorded impedance changes; the optimal parameters were identified. The negative dZ was found to monotonically decrease with frequency for both HH and C fiber models, in accordance with the experimental data. CONCLUSION AND SIGNIFICANCE: The accurate realistic model of unmyelinated nerve allows the optimization of EIT parameters and matches literature and experimental results.