Simulation of effects of the electrode structure and material in the density measuring system of the peripheral nerve based on micro-electrical impedance tomography

Modeling the Impact of the Variation in Peripheral Nerve Anatomy on Stimulation

Introduction

The peripheral nervous system has a complex anatomical structure. Stimulation of nerve fibers in the peripheral nervous system depends on the fiber diameter and myelination as well as its location within the nerve, packing fraction and fascicle distribution within the nerve bundle. This paper analyzes the impact of the variation in peripheral nervous system anatomy and the distance of the stimulating electrodes on the probability of generating an action potential.

Methods

A mathematical model for effective fascicle conductivity has been developed to capture the variation in the packing fraction and fiber diameter. A linear activating function is utilized to analyze the impact of this effective conductivity and fascicle distribution as an indicator of generating an action potential.

Results

Finite element simulations are performed for the nerve-electrode configuration to evaluate the electric field. The simulation results are used to analyze the activating function for different packing fractions and type of nerve fibers. The effect of electrode distance on activating function and the total current through a nerve bundle has also been studied.

Discussion

The simulation results indicate that the peripheral nerve anatomy and electrode distance have a significant effect on the action potential generation.

Automatic three-dimensional reconstruction of fascicles in peripheral nerves from histological images

Computational studies can be used to support the development of peripheral nerve interfaces, but currently use simplified models of nerve anatomy, which may impact the applicability of simulation results. To better quantify and model neural anatomy across the population, we have developed an algorithm to automatically reconstruct accurate peripheral nerve models from histological cross-sections. We acquired serial median nerve cross-sections from human cadaveric samples, staining one set with hematoxylin and eosin (H&E) and the other using immunohistochemistry (IHC) with anti-neurofilament antibody. We developed a four-step processing pipeline involving registration, fascicle detection, segmentation, and reconstruction. We compared the output of each step to manual ground truths, and additionally compared the final models to commonly used extrusions, via intersection-over-union (IOU). Fascicle detection and segmentation required the use of a neural network and active contours in H&E-stained images, but only simple image processing methods for IHC-stained images. Reconstruction achieved an IOU of 0.42±0.07 for H&E and 0.37±0.16 for IHC images, with errors partially attributable to global misalignment at the registration step, rather than poor reconstruction. This work provides a quantitative baseline for fully automatic construction of peripheral nerve models. Our models provided fascicular shape and branching information that would be lost via extrusion.

Fabrication and characterization of polyimide-based 'smooth' titanium nitride microelectrode arrays for neural stimulation and recording

OBJECTIVE

As electrodes are required to interact with sub-millimeter neural structures, innovative microfabrication processes are required to enable fabrication of microdevices involved in such stimulation and/or recording. This requires the development of highly integrated and miniaturized systems, comprising die-integration-compatible technology and flexible microelectrodes. To elicit selective stimulation and recordings of sub-neural structures, such microfabrication process flow can beneficiate from the integration of titanium nitride (TiN) microelectrodes onto a polyimide substrate. Finally, assembling onto cuffs is required, as well as electrode characterization.

APPROACH

Flexible TiN microelectrode array integration and miniaturization was achieved through microfabrication technology based on microelectromechanical systems (MEMS) and complementary metal-oxide semiconductor processing techniques and materials. They are highly reproducible processes, granting extreme control over the feature size and shape, as well as enabling the integration of on-chip electronics. This design is intended to enhance the integration of future electronic modules, with high gains on device miniaturization.

MAIN RESULTS

(a) Fabrication of two electrode designs, (1) 2 mm long array with 14 TiN square-shaped microelectrodes (80  ×  80 µm²), and (2) an electrode array with 2 mm  ×  80 µm contacts. The average impedances at 1 kHz were 59 and 5.5 kΩ, respectively, for the smaller and larger contacts. Both designs were patterned on a flexible substrate and directly interconnected with a silicon chip. (b) Integration of flexible microelectrode array onto a cuff electrode designed for acute stimulation of the sub-millimeter nerves. (c) The TiN electrodes exhibited capacitive charge transfer, a water window of  -0.6 V to 0.8 V, and a maximum charge injection capacity of 154  ±  16 µC cm^-2.

SIGNIFICANCE

We present the concept, fabrication and characterization of composite and flexible cuff electrodes, compatible with post-processing and MEMS packaging technologies, which allow for compact integration with control, readout and RF electronics. The fabricated TiN microelectrodes were electrochemically characterized and exhibited a comparable performance to other state-of-the-art electrodes for neural stimulation and recording. Therefore, the presented TiN-on-polyimide microelectrodes, released from silicon wafers, are a promising solution for neural interfaces targeted at sub-millimeter nerves, which may benefit from future upgrades with die-electronic modules.