Cuff and sieve electrode (CASE): The combination of neural electrodes for bi-directional peripheral nerve interfacing

High-Porosity Sieve-Type Neural Electrodes for Motor Function Recovery and Nerve Signal Acquisition

In this study, the effects of electrode porosity on nerve regeneration and functional recovery after sciatic nerve transection in rats was investigated. A sieve-type neural electrode with 70% porosity was designed and compared with an electrode with 30% porosity. Electrodes were fabricated from photosensitive polyimide and implanted into the transected sciatic nerves. Motor function recovery was evaluated using the Sciatic Function Index. The number of active channels and their signal quality were recorded and analyzed to assess the sensory neural signal acquisition. Electrical impedance spectroscopy was used to evaluate the electrode performance. The group implanted with the 70% porosity electrode demonstrated significantly enhanced nerve regeneration and motor function recovery, approaching control group levels by the fifth week. In contrast, the group with the 30% porosity electrode exhibited limited improvement. Immunohistochemical analysis confirmed extensive nerve fiber growth within the 70% porous structure. Moreover, the 70% porosity electrode consistently acquired neural signals from more channels compared to the 30% porosity electrode, demonstrating its superior performance in sensory signal detection. These findings emphasize the importance of optimizing electrode porosity in the development of advanced neural interfaces, with the potential to enhance clinical outcomes in peripheral nerve repair and neuroprosthetic applications.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

System of Implantable Electrodes for Neural Signal Acquisition and Stimulation for Wirelessly Connected Forearm Prosthesis

There is great interest in the development of prosthetic limbs capable of complex activities that are wirelessly connected to the patient's neural system. Although some progress has been achieved in this area, one of the main problems encountered is the selective acquisition of nerve impulses and the closing of the automation loop through the selective stimulation of the sensitive branches of the patient. Large-scale research and development have achieved so-called "cuff electrodes"; however, they present a big disadvantage: they are not selective. In this article, we present the progress made in the development of an implantable system of plug neural microelectrodes that relate to the biological nerve tissue and can be used for the selective acquisition of neuronal signals and for the stimulation of specific nerve fascicles. The developed plug electrodes are also advantageous due to their small thickness, as they do not trigger nerve inflammation. In addition, the results of the conducted tests on a sous scrofa subject are presented.

Sensory Restoration for Improved Motor Control of Prostheses

Somatosensory neuroprostheses are devices with the potential to restore the senses of touch and movement from prosthetic limbs for people with limb amputation or paralysis. By electrically stimulating the peripheral or central nervous system, these devices evoke sensations that appear to emanate from the missing or insensate limb, and when paired with sensors on the prosthesis, they can improve the functionality and embodiment of the prosthesis. There have been major advances in the design of these systems over the past decade, although several important steps remain before they can achieve widespread clinical adoption outside the lab setting. Here, we provide a brief overview of somatosensory neuroprostheses and explores these hurdles and potential next steps towards clinical translation.

A finite element model of the mechanical interactions between peripheral nerves and intrafascicular implants

Objective.Intrafascicular peripheral nerve implants are key components in the development of bidirectional neuroprostheses such as touch-enabled bionic limbs for amputees. However, the durability of such interfaces is hindered by the immune response following the implantation. Among the causes linked to such reaction, the mechanical mismatch between host nerve and implant is thought to play a decisive role, especially in chronic settings.Approach.Here we focus on modeling mechanical stresses induced on the peripheral nerve by the implant's micromotion using finite element analysis. Through multiple parametric sweeps, we analyze the role of the implant's material, geometry (aspect-ratio and shape), and surface coating, deriving a set of parameters for the design of better-integrated implants.Main results.Our results indicate that peripheral nerve implants should be designed and manufactured with smooth edges, using materials at most three orders of magnitude stiffer than the nerve, and with innovative geometries to redistribute micromotion-associated loads to less delicate parts of the nerve such as the epineurium.Significance.Overall, our model is a useful tool for the peripheral nerve implant designer that is mindful of the importance of implant mechanics for long term applications.

Translating node of Ranvier currents to extraneural electrical fields: a flexible FEM modeling approach

Simulations of electroneurogram recording could help find the optimal set of electrodes and algorithms for selective neural recording. However, no flexible methods are established for selective neural recording as for neural stimulation. This paper proposes a method to couple a compartmental and a FEM nerve model, implemented in NEURON and COMSOL, respectively, to translate Node of Ranvier currents into extraneural electric fields. The study simulate ex-vivo experimental conditions, and the method allows flexibility in electrode geometries and nerve topologies. This model has been made available in a public repository⁴. So far, the model behavior complies with available experimental results and expectations from literature. There is good agreement in terms of signal amplitude and waveform, and computational times are acceptable, leaving room for flexible simulation studies complementary to animal tests.

Improving the Selectivity of an Osseointegrated Neural Interface: Proof of Concept For Housing Sieve Electrode Arrays in the Medullary Canal of Long Bones

Sieve electrodes stand poised to deliver the selectivity required for driving advanced prosthetics but are considered inherently invasive and lack the stability required for a chronic solution. This proof of concept experiment investigates the potential for the housing and engagement of a sieve electrode within the medullary canal as part of an osseointegrated neural interface (ONI) for greater selectivity toward improving prosthetic control. The working hypotheses are that (A) the addition of a sieve interface to a cuff electrode housed within the medullary canal of the femur as part of an ONI would be capable of measuring efferent and afferent compound nerve action potentials (CNAPs) through a greater number of channels; (B) that signaling improves over time; and (C) that stimulation at this interface generates measurable cortical somatosensory evoked potentials through a greater number of channels. The modified ONI was tested in a rabbit (n = 1) amputation model over 12 weeks, comparing the sieve component to the cuff, and subsequently compared to historical data. Efferent CNAPs were successfully recorded from the sieve demonstrating physiological improvements in CNAPs between weeks 3 and 5, and somatosensory cortical responses recorded at 12 weeks postoperatively. This demonstrates that sieve electrodes can be housed and function within the medullary canal, demonstrated by improved nerve engagement and distinct cortical sensory feedback. This data presents the conceptual framework for housing more sophisticated sieve electrodes in bone as part of an ONI for improving selectivity with percutaneous connectivity toward improved prosthetic control.

Compliant peripheral nerve interfaces

Peripheral nerve interfaces (PNIs) record and/or modulate neural activity of nerves, which are responsible for conducting sensory-motor information to and from the central nervous system, and for regulating the activity of inner organs. PNIs are used both in neuroscience research and in therapeutical applications such as precise closed-loop control of neuroprosthetic limbs, treatment of neuropathic pain and restoration of vital functions (e.g. breathing and bladder management). Implantable interfaces represent an attractive solution to directly access peripheral nerves and provide enhanced selectivity both in recording and in stimulation, compared to their non-invasive counterparts. Nevertheless, the long-term functionality of implantable PNIs is limited by tissue damage, which occurs at the implant-tissue interface, and is thus highly dependent on material properties, biocompatibility and implant design. Current research focuses on the development of mechanically compliant PNIs, which adapt to the anatomy and dynamic movements of nerves in the body thereby limiting foreign body response. In this paper, we review recent progress in the development of flexible and implantable PNIs, highlighting promising solutions related to materials selection and their associated fabrication methods, and integrated functions. We report on the variety of available interface designs (intraneural, extraneural and regenerative) and different modulation techniques (electrical, optical, chemical) emphasizing the main challenges associated with integrating such systems on compliant substrates.