The theory of velocity selective neural recording: a study based on simulation

Ex-vivo systems for neuromodulation: A comparison of ex-vivo and in-vivo large animal nerve electrophysiology

BACKGROUND

Little research exists on extending ex-vivo systems to large animal nerves, and to the best of our knowledge, there has yet to be a study comparing these against in-vivo data. This paper details the first ex-vivo system for large animal peripheral nerves to be compared with in-vivo results.

NEW METHOD

Detailed ex-vivo and in-vivo closed-loop neuromodulation experiments were conducted on pig ulnar nerves. Temperatures from 20 °C to 37 °C were evaluated for the ex-vivo system. The data were analysed in the time and velocity domains, and a regression analysis established how evoked compound action potential amplitude and modal conduction velocity (CV) varied with temperature and time after explantation.

MAIN RESULTS

Pig ulnar nerves were sustained ex-vivo up to 5 h post-explantation. CV distributions of ex-vivo and in-vivo data were compared, showing closer correspondence at 37 °C. Regression analysis results also demonstrated that modal CV and time since explantation were negatively correlated, whereas modal CV and temperature were positively correlated.

COMPARISON WITH EXISTING METHODS

Previous ex-vivo systems were primarily aimed at small animal nerves, and we are not aware of an ex-vivo system to be directly compared with in-vivo data. This new approach provides a route to understand how ex-vivo systems for large animal nerves can be developed and compared with in-vivo data.

CONCLUSION

The proposed ex-vivo system results were compared with those seen in-vivo, providing new insights into large animal nerve activity post-explantation. Such a system is crucial for complementing in-vivo experiments, maximising collected experimental data, and accelerating neural interface development.

Enhancing the selective electrical activation of human vagal nerve fibers: a comparative computational modeling study with validation in a rat sciatic model

Objective.Vagus nerve stimulation (VNS) is an emerging treatment option for a myriad of medical disorders, where the method of delivering electrical pulses can vary depending on the clinical indication. In this study, we investigated the relative effectiveness of electrically activating the cervical vagus nerve among three different approaches: nerve cuff electrode stimulation (NCES), transcutaneous electrical nerve stimulation (TENS), and enhanced TENS (eTENS). The objectives were to characterize factors that influenced nerve activation and to compare the nerve recruitment properties as a function of nerve fiber diameter.Methods.The Finite Element Model, based on data from the Visible Human Project, was implemented in COMSOL. The three simulation types were compared under a range of vertical and horizontal displacements relative to the location of the vagus nerve. Monopolar anodic stimulation was examined, along with latency and activation of different fiber sizes. Nerve activation was determined via the activating function and McIntyre-Richardson-Grill models, and activation thresholds were validated in anin-vivorodent model.Results.While NCES produced the lowest activation thresholds, eTENS generally performed superior to TENS under the range of conditions and fiber diameters, producing activation thresholds up to three times lower than TENS. eTENS also preserved its enhancement when surface electrodes were displaced away from the nerve. Anodic stimulation revealed an inhibitory region that removed eTENS benefits. eTENS also outperformed TENS by up to four times when targeting smaller diameter nerve fibers, scaling similar to a cuff electrode. In latency and activation of smaller diameter nerve fibers, eTENS results resembled those of NCES more than a TENS electrode. Activation threshold ratios were consistent inin-vivovalidation.Significance.Our findings expand upon previously identified mechanisms for eTENS and further demonstrate how eTENS emulates a nerve cuff electrode to achieve lower activation thresholds. This work further characterizes considerations required for VNS under the three stimulation methods.

Adaptation of the Two-CAP Method for Conduction Velocity Distribution Estimation in Multi-Channel Recordings

Closed-loop neural interfaces capable of both stimulating and recording from peripheral nerves have the potential to enhance the long-term efficacy of neural implants. One challenge associated with closed loop interfaces is the accurate estimation of the distribution of active fibre conduction velocities (DCV) when recording the immediate effect of stimulation. DCV estimation has been performed in monopolar surface recordings using the Two-CAP method. This work extends the Two-CAP method and demonstrates its application to bipolar in-vivo recordings made with multiple-electrode arrays. A sensitivity analysis was conducted using simulated data with ground truth to ascertain the stability and limits of the algorithm before experimental data was examined. The sensitivity analysis highlighted that recording distance shows a considerable impact on the performance of this extended Two-CAP method, as well as the velocity interval chosen when creating the model. The in-vivo data was also compared against an equivalent simulated model, and a relatively low mean squared error was obtained when comparing the two distributions.

An in-vitro system for closed loop neuromodulation of peripheral nerves

Current neuromodulation research relies heavily on in-vivo animal experiments for developing novel devices and paradigms, which can be costly, time-consuming, and ethically contentious. As an alternative to this, in-vitro systems are being developed for examining explanted tissue in a controlled environment. However, these systems are typically tailored for cellular studies. Thus, this paper describes the development of an in-vitro system for electrically recording and stimulating large animal nerves. This is demonstrated experimentally using explanted pig ulnar nerves, which show evoked compound action potentials (eCAPs) when stimulated. These eCAPs were examined both in the time and velocity domain at a baseline temperature of 20° C, and at temperatures increasing up to those seen in-vivo (37°C). The results highlight that as the temperature is increased within the in-vitro system, faster conduction velocities (CVs) similar to those present in-vivo can be observed. To our knowledge, this is the first time an in-vitro peripheral nerve system has been validated against in-vivo data, which is crucial for promoting more widespread adoption of such systems for the optimisation of neural interfaces.

A Comparison of Delay-and-Add and Maximum Likelihood Estimation for Velocity-Selective Recording Using Multi-Electrode Cuffs

Extracting information from the peripheral nervous system with implantable devices remains a significant challenge that limits the advancement of closed-loop neural prostheses. Linear electrode arrays can record neural signals with both temporal and spatial selectivity, and velocity selective recording using the delay-and-add algorithm can enable classification based on fibre type. The maximum likelihood estimation method also measures velocity and is frequently used in electromyography but has never been applied to electroneurography. Therefore, this study compares the two algorithms using in-vivo recordings of electrically evoked compound action potentials from the ulnar nerve of a pig. The performance of these algorithms was assessed using the velocity quality factor (Q-factor), computational time and the influence of the number of channels. The results show that the performance of both algorithms is significantly influenced by the number of channels in the recording array, with accuracies ranging from 77% with only two channels to 98% for 11 channels. Both algorithms were comparable in accuracy and Q-factor for all channels, with the delay-and-add having a slight advantage in the Q-factor.

Pig Ulnar Nerve Recording with Sinusoidal and Temporal Interference Stimulation

Temporal interference stimulation has been suggested as a method to reach deep targets during transcutaneous electrical stimulation. Despite its growing use in transcutaneous stimulation therapies, the mechanism of its operation is not fully understood. Recent efforts to fill that gap have focused on computational modelling, in vitro and in vivo experiments relying on physical observations - e.g., sensation or movement. This paper expands the current range of experimental methods by demonstrating in vivo extraneural recordings from the ulnar nerve of a pig while applying temporal interference stimulation at a location targeting a distal part of the nerve. The main aim of the experiment was to compare neural activation using sinusoidal stimulation (100 Hz, 2 kHz, 4 kHz) and temporal interference stimulation (2 kHz and 4 kHz). The recordings showed a significant increase in the magnitude of stimulation artefacts at higher frequencies. While those artefacts could be removed and provided an indication of the depth of modulation, they resulted in the saturation of the amplifiers, limiting the stimulation currents and amplifier gains used. The results of the 100 Hz sine wave stimulation showed clear neural activity correlated to the stimulation waveform. However, this was not observed with temporal interference stimulation. The results suggest that, despite its greater penetration, higher currents might be required to observe a neural response with temporal interference stimulation, and more complex artefact rejection techniques may be required to validate the method.

Tutorial: A guide to techniques for analysing recordings from the peripheral nervous system

The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of peripheral nerve interfaces, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.

The Use of the Velocity Selective Recording Technique to Reveal the Excitation Properties of the Ulnar Nerve in Pigs

Decoding information from the peripheral nervous system via implantable neural interfaces remains a significant challenge, considerably limiting the advancement of neuromodulation and neuroprosthetic devices. The velocity selective recording (VSR) technique has been proposed to improve the classification of neural traffic by combining temporal and spatial information through a multi-electrode cuff (MEC). Therefore, this study investigates the feasibility of using the VSR technique to characterise fibre type based on the electrically evoked compound action potentials (eCAP) propagating along the ulnar nerve of pigs in vivo. A range of electrical stimulation parameters (amplitudes of 50 μA-10 mA and pulse durations of 100 μs, 500 μs, 1000 μs, and 5000 μs) was applied on a cutaneous and a motor branch of the ulnar nerve in nine Danish landrace pigs. Recordings were made with a 14 ring MEC and a delay-and-add algorithm was used to convert the eCAPs into the velocity domain. The results revealed two fibre populations propagating along the cutaneous branch of the ulnar nerve, with mean velocities of 55 m/s and 21 m/s, while only one dominant fibre population was found for the motor branch, with a mean velocity of 63 m/s. Because of its simplicity to provide information on the fibre selectivity and direction of propagation of nerve fibres, VSR can be implemented to advance the performance of the bidirectional control of neural prostheses and bioelectronic medicine applications.

Array processing of neural signals recorded from the peripheral nervous system for the classification of action potentials

BACKGROUND

Recording from the peripheral nervous system is key in the development of implantable neural interfaces. Despite a long history of using implantable electrodes for neuro-stimulation, it is difficult to make recordings from the nerves as signal amplitudes are often too small to be detected. Methods exist that are suitable for recording evoked potentials, but these require artificial stimulation of the nerve and thus have limited use in implanted neural interfaces.

NEW METHOD

In order to address these issues new methods are developed to analyse spontaneously occurring action potentials by extending an approach called velocity selective recording, which uses longitudinally spaced electrodes to record action potentials as they propagate. The new methods using image processing techniques to automatically identify and classify action potentials without any prior knowledge of their morphology.

RESULTS

Simulations are developed to test the methods, and a detailed experimental validation is performed using in-vivo recordings from the L5 dorsal rootlet of rat. Results show that this new approach can discriminate action potentials from both simulated and real recordings and the experimental validation demonstrates an ability to detect dermal stimulation by changes in the firing patterns of different axons.

COMPARISON TO EXISTING METHODS

This framework, unlike existing methods, is intrinsically suitable for recordings of spontaneous neural activity. Further it improves upon both the computational complexity and the overall performance of existing methods.

CONCLUSION

It is possible to perform on-line discrimination and identification of action potentials without any prior knowledge of their morphology using new image processing inspired methods.

The Effects of the Presence of Multiple Conduction Velocities in the Analysis of Electrically-Evoked Compound Action Potentials (eCAPs)

New methods for the analysis of electrically-evoked compound action potentials (eCAPs) are described. Mammalian nerves tend to have broad multi-modal distributions of fibre diameters, which translates into a spread of conduction velocities. The method of velocity selective recording (VSR) is unable to distinguish between this spectral spread and the transfer function of the system. The concept of the velocity impulse function (VIF) is introduced as a tool to differentiate between these signal and system attributes. The new methods enable separate estimates of velocity spectral broadening and signal-to-noise ratio (SNR) to be obtained.

A microfabricated nerve-on-a-chip platform for rapid assessment of neural conduction in explanted peripheral nerve fibers

Peripheral nerves are anisotropic and heterogeneous neural tissues. Their complex physiology restricts realistic in vitro models, and high resolution and selective probing of axonal activity. Here, we present a nerve-on-a-chip platform that enables rapid extracellular recording and axonal tracking of action potentials collected from tens of myelinated fibers. The platform consists of microfabricated stimulation and recording microchannel electrode arrays. First, we identify conduction velocities of action potentials traveling through the microchannel and propose a robust data-sorting algorithm using velocity selective recording. We optimize channel geometry and electrode spacing to enhance the algorithm reliability. Second, we demonstrate selective heat-induced neuro-inhibition of peripheral nerve activity upon local illumination of a conjugated polymer (P3HT) blended with a fullerene derivative (PCBM) coated on the floor of the microchannel. We demonstrate the nerve-on-a-chip platform is a versatile tool to optimize the design of implantable peripheral nerve interfaces and test selective neuromodulation techniques ex vivo.

Peripheral nerves have a complex physiology and it is therefore difficult to measure axonal activity in vitro. Here the authors make a nerve-on-a-chip platform to align peripheral nerves and permit measurement of conduction amplitude and velocity along several axons in a single experiment.

An implantable ENG detector with in-system velocity selective recording (VSR) capability

Detection and classification of electroneurogram (ENG) signals in the peripheral nervous system can be achieved by velocity selective recording (VSR) using multi-electrode arrays. This paper describes an implantable VSR-based ENG recording system representing a significant development in the field since it is the first system of its type that can record naturally evoked ENG and be interfaced wirelessly using a low data rate transcutaneous link. The system consists of two CMOS ASICs one of which is placed close to the multi-electrode cuff array (MEC), whilst the other is mounted close to the wireless link. The digital ASIC provides the signal processing required to detect selectively ENG signals based on velocity. The design makes use of an original architecture that is suitable for implantation and reduces the required data rate for transmission to units placed outside the body. Complete measured electrical data from samples of the ASICs are presented that show that the system has the capability to record signals of amplitude as low as 0.5 μV, which is adequate for the recording of naturally evoked ENG. In addition, measurements of electrically evoked ENG from the explanted sciatic nerves of Xenopus Laevis frogs are presented.

A phantom axon setup for validating models of action potential recordings

Electrode designs and strategies for electroneurogram recordings are often tested first by computer simulations and then by animal models, but they are rarely implanted for long-term evaluation in humans. The models show that the amplitude of the potential at the surface of an axon is higher in front of the nodes of Ranvier than at the internodes; however, this has not been investigated through in vivo measurements. An original experimental method is presented to emulate a single fiber action potential in an infinite conductive volume, allowing the potential of an axon to be recorded at both the nodes of Ranvier and the internodes, for a wide range of electrode-to-fiber radial distances. The paper particularly investigates the differences in the action potential amplitude along the longitudinal axis of an axon. At a short radial distance, the action potential amplitude measured in front of a node of Ranvier is two times larger than in the middle of two nodes. Moreover, farther from the phantom axon, the measured action potential amplitude is almost constant along the longitudinal axis. The results of this new method confirm the computer simulations, with a correlation of 97.6 %.

An enhancement to velocity selective discrimination of neural recordings: extraction of neuronal firing rates

This paper describes improvements to the theory of velocity selective recording (VSR) of neural signals. Action potentials are classified and differentiated based on their conduction velocities which can be calculated from concurrent neural recordings taking at different locations on a nerve. Existing work has focussed primarily on electrically evoked compound action potentials (CAPs) where only a single evoked response per velocity is recorded. This paper extends the theory of VSR to naturally occurring neural signals recorded from rat and attempts to identify the level of activity (firing rates) within particular velocity ranges.

Improved Signal Processing Methods for Velocity Selective Neural Recording Using Multi-Electrode Cuffs

This paper describes an improved system for obtaining velocity spectral information from electroneurogram recordings using multi-electrode cuffs (MECs). The starting point for this study is some recently published work that considers the limitations of conventional linear signal processing methods (`delay-and-add') with and without additive noise. By contrast to earlier linear methods, the present paper adopts a fundamentally non-linear velocity classification approach based on a type of artificial neural network (ANN). The new method provides a unified approach to the solution of the two main problems of the earlier delay-and-add technique, i.e., a damaging decline in both velocity selectivity and velocity resolution at high velocities. The new method can operate in real-time, is shown to be robust in the presence of noise and also to be relatively insensitive to the form of the action potential waveforms being classified.

Fibre-selective discrimination of physiological ENG using velocity selective recording: report on pilot rat experiments

This paper presents results from a pilot experiment in which the technique of velocity selective recording (VSR) was used to identify naturally occurring electroneurogram (ENG) signals within the intact nerve of a rat. Signals were acquired using a set of electrodes placed along the length of the nerve, formed from simple wire hooks. This basic form of recording has already been applied in-vivo to the analysis of electrically excited compound action potentials (CAPs) in both pig and frog, however, this method has never before been used to identify naturally occurring neural signals. Results in this paper highlight challenges which must be overcome in order for the transition to be made from electrically evoked potentials to naturally occurring signals.