Intraneural Electrodes Research Articles

A multi-channel stimulator with an active electrode array implant for vagal-cardiac neuromodulation studies

BackgroundImplantable vagus nerve stimulation is a promising approach for restoring autonomic cardiovascular functions after heart transplantation. For successful treatment a system should have multiple electrodes to deliver precise stimulation and complex neuromodulation patterns.MethodsThis paper presents an implantable multi-channel stimulation system for vagal-cardiac neuromodulation studies in swine species. The system comprises an active electrode array implant percutaneously connected to an external wearable controller. The active electrode array implant has an integrated stimulator ASIC mounted on a ceramic substrate connected to an intraneural electrode array via micro-rivet bonding. The implant is silicone encapsulated for biocompatibility and implanted lifetime. The stimulation parameters are remotely transmitted via a Bluetooth telemetry link.ResultsThe size of the encapsulated active electrode array implant is 8 mm × 10 mm × 3 mm. The stimulator ASIC has 10-bit current amplitude resolution and 16 independent output channels, each capable of delivering up to 550 µA stimulus current and a maximum voltage of 20 V. The active electrode array implant was subjected to in vitro accelerated lifetime testing at 70 °C for 7 days with no degradation in performance. After over 2 h continuous stimulation, the surface temperature change of the implant was less than 0.5 °C. In addition, in vivo testing on the sciatic nerve of a male Göttingen minipig demonstrated that the implant could effectively elicit an EMG response that grew progressively stronger on increasing the amplitude of the stimulation.ConclusionsThe multi-channel stimulator is suitable for long term implantation. It shows potential as a useful tool in vagal-cardiac neuromodulation studies in animal models for restoring autonomic cardiovascular functions after heart transplantation.

Engineered Graphene Material Improves the Performance of Intraneural Peripheral Nerve Electrodes.

Limb neuroprostheses aim to restore motor and sensory functions in amputated or severely nerve-injured patients. These devices use neural interfaces to record and stimulate nerve action potentials, creating a bidirectional connection with the nervous system. Most neural interfaces are based on standard metal microelectrodes. In this work, a new generation of neural interfaces which replaces metals with engineered graphene, called EGNITE, is tested. In vitro and in vivo experiments are conducted to assess EGNITE biocompatibility. In vitro tests show that EGNITE does not impact cell viability. In vivo, no significant functional decrease or harmful effects are observed. Furthermore, the foreign body reaction to the intraneural implant is similar compared to other materials previously used in neural interfaces. Regarding functionality, EGNITE devices are able to stimulate nerve fascicles, during two months of implant, producing selective muscle activation with about three times less current compared to larger microelectrodes of standard materials. CNAP elicited by electrical stimuli and ENG evoked by mechanical stimuli are recorded with high resolution but are more affected by decreased functionality over time. This work constitutes further proof that graphene-derived materials, and specifically EGNITE, is a promising conductive material of neural electrodes for advanced neuroprostheses.

Streamlining neural signal detection for improved bladder control prostheses

Using an intraneural electrode as a sensor could enable more effective closed-loop neuroprosthetic treatments for urinary tract dysfunctions.

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon the implantation procedure and the subject’s anatomy. Currently, few alternatives exist for the determination of the target subject structural and functional anatomy, and statistical characterizations from cadaveric samples are limited because of their high cost. We propose an optimization workflow that can guide both the pre-surgical planning and the determination of maximally selective multisite stimulation protocols for implants consisting of several intraneural electrodes, and we characterize its performance in silico. We show that the availability of structural and functional information leads to very high performances and allows taking informed decisions on neuroprosthetic design. Approach. We employ hybrid models (HMs) of neuromodulation in conjunction with a machine learning-based surrogate model to determine fiber activation under electrical stimulation, and two steps of optimization through particle swarm optimization to optimize in silico implant geometry, implantation and stimulation protocols using morphological data from the human median nerve at a reduced computational cost. Main results. Our method allows establishing the optimal geometry of multi-electrode transverse intra-fascicular multichannel electrode implants, the optimal number of electrodes to implant, their optimal insertion, and a set of multipolar stimulation protocols that lead in silico to selective activation of all the muscles innervated by the human median nerve. Significance. We show how to use effectively HMs for optimizing personalized neuroprostheses for motor function restoration. We provide in-silico evidences about the potential of multipolar stimulation to increase greatly selectivity. We also show that the knowledge of structural and functional anatomies of the target subject leads to very high selectivity and motivate the development of methods for their in vivo characterization.

Study of Electrical Neural Stimulation Effects Using Extraneural and Intraneural Electrodes

Sensory feedback restoration in upper-limb neuroprosthetics can significantly enhance amputees’ quality of life. Neural interfaces allow the elicitation of sensory information through current stimuli. Stimulation studies can be useful to evaluate the electric potential distribution into the nerve in response to a current stimulus and therefore the activation of fibers. In this paper, hybrid FEM-Neuron computational models are used to study nerve fiber activation in different nerve models that resemble the human median nerve. To conduct a comprehensive study, the variability in fascicular topography and different configurations of active sites of two types of electrodes (intraneural and extraneural) has been considered. Furthermore, the simulation results (in terms of the percentage of fiber activation in nerve fascicles, their location in the nerve section models, and the order of their activation when the stimulus increases) are evaluated according to the sensation intensity perceived by a human amputee in an experimental trial. The obtained results let us infer the effect of using intraneural and extraneural electrodes on the number and position of activated fascicles when the minimum values of electric charges considered in the experimental trial are used, and the dependence of the order of fiber activation into the fascicles on the current stimulus.

A POLY(SBMA) ZWITTERIONIC HYDROGEL COATING OF POLYIMIDE SURFACES TO REDUCE THE FOREIGN BODY REACTION TO INVASIVE NEURAL INTERFACES

Intraneural electrodes can be harnessed to control neural prosthetic devices in human amputees. However, in chronic implants we witness a gradual loss of device functionality and electrode isolation due to a nonspecific inflammatory response to the implanted material, called foreign body reaction (FBR). FBR may eventually lead to a fibrous encapsulation of the electrode surface. Poly(ethylene glycol) (PEG) is one of the most common low-fouling materials used to coat and protect electrode surfaces. Yet, PEG can easily undergo encapsulation and oxidative damage in long-term in vivo applications. Poly(sulfobetaine methacrylate) - poly(SBMA) - zwitterionic hydrogels may represent more promising alternatives to minimize the FBR due to their ultra-low fouling features. Here, we tested and compared the poly(SBMA) zwitterionic hydrogel coating with the PEG coating in reducing adhesion and activation of pro-inflammatory and pro-fibrotic cells to polyimide surfaces, which are early hallmarks of FBR. We aimed to coat polyimide surfaces with a hydrogel thin film and analysed the release of a model drug from the hydrogel.We performed hydrogel synthesis, mechanical characterization and biocompatibility analysis. Cell adhesion, viability and morphology of human myofibroblasts cultured on PEG- and hydrogel-coated surfaces were evaluated through confocal microscopy-based high-content analysis (HCA). Reduced activation of pro-inflammatory human macrophages cultured on hydrogels was assessed as well as the hydrogel drug release profile.Because of its high hydration, biocompatibility, low stiffness and ultra-low fouling characteristics the hydrogel enabled lower adhesion and activation of pro-inflammatory and pro-fibrotic cells vs. polystyrene controls, and showed a long-term release of the anti-fibrotic drug Everolimus. Furthermore, a polyimide surface was successfully coated with a hydrogel thin film.Our soft zwitterionic hydrogel could outperform PEG as more suitable coating material of neural electrodes for mitigating the FBR. Such poly(SBMA)-based biomaterial could also be envisioned as long-term delivery system for a sustained release of anti-inflammatory and anti-fibrotic drugs in vivo.

Cardiovascular Response to Intraneural Right Vagus Nerve Stimulation in Adult Minipig

ObjectiveThis study explored intraneural stimulation of the right thoracic vagus nerve (VN) in sexually mature male minipigs to modulate safe heart rate and blood pressure response. Material and MethodsWe employed an intraneural electrode designed for the VN of pigs to perform VN stimulation (VNS). This was delivered using different numbers of contacts on the electrode and different stimulation parameters (amplitude, frequency, and pulse width), identifying the most suitable stimulation configuration. All the parameter ranges had been selected from a computational cardiovascular system model. ResultsClinically relevant responses were observed when stimulating with low current intensities and relatively low frequencies delivered with a single contact. Selecting a biphasic, charge-balanced square wave for VNS with a current amplitude of 500 μA, frequency of 10 Hz, and pulse width of 200 μs, we obtained heart rate reduction of 7.67 ± 5.19 beats per minute, systolic pressure reduction of 5.75 ± 2.59 mmHg, and diastolic pressure reduction of 3.39 ± 1.44 mmHg. ConclusionHeart rate modulation was obtained without inducing any observable adverse effects, underlining the high selectivity of the intraneural approach.

A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity

Bioelectronic medicine is an emerging approach to treat many types of diseases via electrical stimulation of the autonomic nervous system (ANS). Because the vagus nerve (VN) is one of the most important nerves controlling several ANS functions, stimulation protocols based on knowledge of the functional organization of the VN are particularly interesting. Here, we proposed a method to localize different physiological VN functions by exploiting electro-neurographic signals recorded during spontaneous VN fibers activity. We tested our method on a realistic human cervical VN model geometry implanted via epineural or intraneural electrodes. We considered in silico ground truth scenarios of functional topography generated via different functional neural fibers activities covered by background noise. Our method accurately estimated the underlying functional VN topography by outperforming state-of-the-art methods. Our work paves the way for development of spatially selective stimulation protocols targeting multiple VN bodily functions.

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs

Objective. Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation of the ANS, the computational execution time and the memory and power demands of the decoding step are important factors to consider. In the context of cardiovascular and respiratory diseases, these requirements may partially explain why closed-loop clinical neuromodulation protocols that adapt stimulation parameters on patient’s clinical characteristics are currently missing. Approach. Here, we developed a lightweight learning-based decoder for the classification of cardiovascular and respiratory functional challenges from neural signals acquired through intraneural electrodes implanted in the cervical vagus nerve (VN) of five anaesthetized pigs. Our algorithm is based on signal temporal windowing, nine handcrafted features, and random forest (RF) model for classification. Temporal windowing ranging from 50 ms to 1 s, compatible in duration with cardio-respiratory dynamics, was applied to the data in order to mimic a pseudo real-time scenario. Main results. We were able to achieve high balanced accuracy (BA) values over the whole range of temporal windowing duration. We identified 500 ms as the optimal temporal windowing duration for both BA values and computational execution time processing, achieving more than 86% for BA and a computational execution time of only ∼6.8 ms. Our algorithm outperformed in terms of BA and computational execution time a state of the art decoding algorithm tested on the same dataset (Vallone et al 2021 J. Neural Eng. 18 0460a2). We found that RF outperformed other machine learning models such as support vector machines, K-nearest neighbors, and multi-layer perceptrons. Significance. Our approach could represent an important step towards the implementation of a closed-loop neuromodulation protocol relying on a single intraneural interface able to perform real-time decoding tasks and selective modulation of the VN.

A fast and accurate learning-based decoding algorithm for the classification of cardiovascular and respiratory challenges using intraneural electrodes in the pig vagus nerve.

Bioelectronic medicine is a new approach for developing closed-loop neuromodulation protocols on the peripheral nervous system (PNS) to treat a wide range of disorders currently treated with pharmacological approaches. Algorithms need to have low computational cost in order to acquire, process and model data for the modulation of the PNS in real time. Here, we present a fast learning-based decoding algorithm for the classification of cardiovascular and respiratory functional alterations (i.e., challenges) by using neural signals recorded from intraneural electrodes implanted in the vagus nerve of 5 pigs. Our algorithm relies on 9 handcrafted features, extracted following signal temporal windowing, and a multi-layer perceptron (MLP) for feature classification. We achieved fast and accurate classification of the challenges, with a computational time for feature extraction and prediction lower than 1.5 ms. The MLP achieved a balanced accuracy higher than 80 % for all recordings. Our algorithm could represent a step towards the development of a closed-loop system based on a single intraneural interface with both the potential of real time classification and selective modulation of the PNS.

A Soft Zwitterionic Hydrogel as Potential Coating on a Polyimide Surface to Reduce Foreign Body Reaction to Intraneural Electrodes.

Invasive intraneural electrodes can control advanced neural-interfaced prostheses in human amputees. Nevertheless, in chronic implants, the progressive formation of a fibrotic capsule can gradually isolate the electrode surface from the surrounding tissue leading to loss of functionality. This is due to a nonspecific inflammatory response called foreign-body reaction (FBR). The commonly used poly(ethylene glycol) (PEG)-based low-fouling coatings of implantable devices can be easily encapsulated and are susceptible to oxidative damage in long-term in vivo applications. Recently, sulfobetaine-based zwitterionic hydrogels have emerged as an important class of robust ultra-low fouling biomaterials, holding great potential to mitigate FBR. The aim of this proof-of-principle in vitro work was to assess whether the organic zwitterionic—poly(sulfobetaine methacrylate) [poly(SBMA)]—hydrogel could be a suitable coating for Polyimide (PI)-based intraneural electrodes to reduce FBR. We first synthesized and analyzed the hydrogel through a mechanical characterization (i.e., Young’s modulus). Then, we demonstrated reduced adhesion and activation of fibrogenic and pro-inflammatory cells (i.e., human myofibroblasts and macrophages) on the hydrogel compared with PEG-coated and polystyrene surfaces using cell viability assays, confocal fluorescence microscopy and high-content analysis of oxidative stress production. Interestingly, we successfully coated PI surfaces with a thin film of the hydrogel through covalent bond and demonstrated its high hydrophilicity via water contact angle measurement. Importantly, we showed the long-term release of an anti-fibrotic drug (i.e., Everolimus) from the hydrogel. Because of the low stiffness, biocompatibility, high hydration and ultra-low fouling characteristics, our zwitterionic hydrogel could be envisioned as long-term diffusion-based delivery system for slow and controlled anti-inflammatory and anti-fibrotic drug release in vivo.

P25. NEUROSTITCH: NANOFABRICATION OF A HIGH RESOLUTION, BIOMIMETIC PERIPHERAL NERVE INTERFACE

PURPOSE: Over a million people suffer limb loss annually. Existing prostheses are cumbersome with a limited capacity to recapitulate natural hand motion. A stable, high-fidelity neural interface is necessary for 2-way communication between robotic prostheses and the patient’s neural circuitry. Existing neural interfaces are limited by the trade-off between invasiveness, resolution and longevity. METHODS: Ultra-small, flexible electrodes of the same dimensions and compliance as human axons were fabricated. A ‘needle and thread’ approach was used to implant the ultra-flexible devices. Using histology, 2-photon imaging, and the Sciatic Functional Index (SFI), we assessed the neural injury and foreign body reaction (FBR) associated with the device. The Intan system was used to stimulate and record. RESULTS: SFI demonstrates resolution of the initial neuropraxia to baseline by 2 weeks post-implantation. Action potentials were recorded within 30 minutes of device insertion. The size of the electrodes and proximity to individual axons permitted local stimulation — down to a single toe. Immunohistochemistry demonstrated an absence of FBR at 6 months. CONCLUSION: We have fabricated and inserted biomimetic intraneural electrodes with minimal and recoverable nerve injury and absence of FBR. The Neurostitch is capable high selectivity stimulation. This device represents a step forward in the development of a high-resolution, stable man/machine interface for next-generation neuroprostheses.

Biomechanical characterization of isolated epineurial and perineurial membranes of rabbit sciatic nerve

Design of interface devices for effective, long-term integration into neural tissue is dependent on the biomechanical properties of the nerve membranes. Within the peripheral nerve, the two relevant connective tissue layers for interfacing are the epineurium and perineurium. Previous work has reported the forces needed to penetrate the whole nerve, but the mechanical differences between epineurium and perineurium were not reported. Design of intraneural electrodes that place electrodes within the nerve requires knowledge of the mechanics of individual tissues. This study quantified the Young’s moduli and ultimate strains of the perineurium and the epineurium separately. We also measured the forces necessary to penetrate each tissue in isolation. We used a custom-built microtensile testing device to measure the Young’s modulus values. The measured Young’s moduli of the epineurium and the perineurium was 0.4 ± 0.1 MPa and 3.0 ± 0.3 MPa, respectively. We also measured the force required for blunt and sharp stainless steel, 100 µm diameter probes to be inserted into isolated epineurial tissue and perineurial tissue at 2 mm/s. These data provide additional guidelines for selection of materials for long-term implants that best match the tissue properties. The results will guide neural interface design such that electrodes can be placed through either the epineurium alone or both the epineurium and perineurium.

Selective stimulation with intraneural electrodes for bionic limb prostheses can contribute to shed light on human touch sensorimotor integration.

Selective stimulation with intraneural electrodes for bionic limb prostheses can contribute to shed light on human touch sensorimotor integration.

Sensorimotor integration within the primary motor cortex by selective nerve fascicle stimulation.

The integration of sensory inputs in the motor cortex is crucial for dexterous movement. We recently demonstrated that a closed‐loop control based on the feedback provided through intraneural multichannel electrodes implanted in the median and ulnar nerves of a participant with upper limb amputation improved manipulation skills and increased prosthesis embodiment. Here we assessed, in the same participant, whether and how selective intraneural sensory stimulation also elicits a measurable cortical activation and affects sensorimotor cortical circuits. After estimating the activation of the primary somatosensory cortex evoked by intraneural stimulation, sensorimotor integration was investigated by testing the inhibition of primary motor cortex (M1) output to transcranial magnetic stimulation, after both intraneural and perineural stimulation. Selective sensory intraneural stimulation evoked a low‐amplitude, 16 ms‐latency, parietal response in the same area of the earliest component evoked by whole‐nerve stimulation, compatible with fast‐conducting afferent fibre activation. For the first time, we show that the same intraneural stimulation was also capable of decreasing M1 output, at the same time range of the short‐latency afferent inhibition effect of whole‐nerve superficial stimulation. The inhibition generated by the stimulation of channels activating only sensory fibres was stronger than that due to intraneural or perineural stimulation of channels activating mixed fibres. We demonstrate in a human subject that the cortical sensorimotor integration inhibiting M1 output previously described after the experimental whole‐nerve stimulation is present also with a more ecological selective sensory fibre stimulation. Key points Cortical integration of sensory inputs is crucial for dexterous movement.Short‐latency somatosensory afferent inhibition of motor cortical output is typically produced by peripheral whole‐nerve stimulation.We exploited intraneural multichannel electrodes used to provide sensory feedback for prosthesis control to assess whether and how selective intraneural sensory stimulation affects sensorimotor cortical circuits in humans.Activation of the primary somatosensory cortex (S1) was explored by recording scalp somatosensory evoked potentials. Sensorimotor integration was tested by measuring the inhibitory effect of the afferent stimulation on the output of the primary motor cortex (M1) generated by transcranial magnetic stimulation.We demonstrate in humans that selective intraneural sensory stimulation elicits a measurable activation of S1 and that it inhibits the output of M1 at the same time range of whole‐nerve superficial stimulation.

Modulus‐Tailorable, Stretchable, and Biocompatible Carbonene Fiber for Adaptive Neural Electrode

AbstractThe extraneural electrodes that cling to the nerve show great advantages in decreasing the damage of nerves, as compared to the intraneural electrodes. The grand challenge for the extraneural electrode is the instability of its electrode–nerve interface during nerve movement. In the proposed research, an adaptive, stretchable, and biocompatible carbonene extraneural electrode, which integrates rigid 2D defective graphene nanosheets on the soft carbon nanotube (CNT) fiber, is designed. The rigid nanosheets and the soft nanotubes are dominated by sp2 nanocarbon, which is defined as carbonene. Benefiting from the soft and robust nature of the CNT fiber, the hybrid carbonene electrodes can be facile‐tailored into various complex shapes with a wide range of modulus (0.5–600 kPa), which plays a significant role in mechanical match of the modulus with that of the nerve. Moreover, the hybrid carbonene fiber exhibits excellent electrical conductivity (3.3 × 105 S m−1) and novel biocompatibility. As a result, the carbonene electrode shows a preferable performance compared to the traditional metal electrode, whose peak‐to‐peak action potential is 310% higher than the commercial Pt electrode. Overall, this work proposes a novel strategy for assembling the facile‐tailorable and biocompatible carbonene electrode, which can open an avenue for designing the next‐generation neural electrode.

Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop VN stimulation (VNS) would be crucial to increase effectiveness of this approach. Therefore, the extrapolation of useful physiological information from VN electrical activity would represent an invaluable source for single-target applications. Here, we present an advanced decoding algorithm novel to VN studies and properly detecting different functional changes from VN signals. Approach. VN signals were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. We developed a decoding algorithm that combines discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees. Main results. The new decoding algorithm robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. Interestingly our findings suggest that electrodes positioning plays an important role on decoding performances. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles. Significance. This study represents an important step towards the comprehension of VN signaling, paving the way for the development of effective closed-loop VNS systems.

Biomedical and Tissue Engineering Strategies to Control Foreign Body Reaction to Invasive Neural Electrodes.

Neural-interfaced prostheses aim to restore sensorimotor limb functions in amputees. They rely on bidirectional neural interfaces, which represent the communication bridge between nervous system and neuroprosthetic device by controlling its movements and evoking sensory feedback. Compared to extraneural electrodes (i.e., epineural and perineural implants), intraneural electrodes, implanted within peripheral nerves, have higher selectivity and specificity of neural signal recording and nerve stimulation. However, being implanted in the nerve, their main limitation is represented by the significant inflammatory response that the body mounts around the probe, known as Foreign Body Reaction (FBR), which may hinder their rapid clinical translation. Furthermore, the mechanical mismatch between the consistency of the device and the surrounding neural tissue may contribute to exacerbate the inflammatory state. The FBR is a non-specific reaction of the host immune system to a foreign material. It is characterized by an early inflammatory phase eventually leading to the formation of a fibrotic capsule around intraneural interfaces, which increases the electrical impedance over time and reduces the chronic interface biocompatibility and functionality. Thus, the future in the reduction and control of the FBR relies on innovative biomedical strategies for the fabrication of next-generation neural interfaces, such as the development of more suitable designs of the device with smaller size, appropriate stiffness and novel conductive and biomimetic coatings for improving their long-term stability and performance. Here, we present and critically discuss the latest biomedical approaches from material chemistry and tissue engineering for controlling and mitigating the FBR in chronic neural implants.

A machine-learning algorithm correctly classifies cortical evoked potentials from both visual stimulation and electrical stimulation of the optic nerve

Objective. Optic nerve’s intraneural stimulation is an emerging neuroprosthetic approach to provide artificial vision to totally blind patients. An open question is the possibility to evoke individual non-overlapping phosphenes via selective intraneural optic nerve stimulation. To begin answering this question, first, we aim at showing in preclinical experiments with animals that each intraneural electrode could evoke a distinguishable activity pattern in the primary visual cortex. Approach. We performed both patterned visual stimulation and patterned electrical stimulation in healthy rabbits while recording evoked cortical activity with an electrocorticogram array in the primary visual cortex. Electrical stimulation was delivered to the optic nerve with the intraneural array OpticSELINE. We used a support vector machine algorithm paired to a linear regression model to classify cortical responses originating from visual stimuli located in different portions of the visual field and electrical stimuli from the different electrodes of the OpticSELINE. Main results. Cortical activity induced by visual and electrical stimulation could be classified with nearly 100% accuracy relative to the specific location in the visual field or electrode in the array from which it originated. For visual stimulation, the accuracy increased with the separation of the stimuli and reached 100% for separation higher than 7°. For electrical stimulation, at low current amplitudes, the accuracy increased with the distance between electrodes, while at higher current amplitudes, the accuracy was nearly 100% already for the shortest separation. Significance. Optic nerve’s intraneural stimulation with the OpticSELINE induced discernible cortical activity patterns. These results represent a necessary condition for an optic nerve prosthesis to deliver vision with non-overlapping phosphene. However, clinical investigations will be required to assess the translation of these results into perceptual phenomena.

Q-PINE: A quick to implant peripheral intraneural electrode

Objective. The implantation of intraneural electrodes in amputees has been observed to be effective in providing subjects with sensory feedback. However, this implantation is challenging and time consuming. Surgeons must be especially trained to execute the implantation. Therefore, we aimed at developing a novel peripheral intraneural electrode and insertion mechanism, which could drastically reduce the overall implantation time while achieving a high neural selectivity. Approach. A new insertion method based on hollow microneedles was developed to realize the prompt and effective simultaneous implantation of up to 14 active sites in a transversal manner. Each needle guided two Pt/Ir microwires through the nervous tissue. After the insertion, the microneedles were released, leaving behind the microwires. Each microwire had one active site, which was coated with poly-3,4-ethylenedioxythiophene (PEDOT) to enhance the electrochemical properties. The active sites were characterized by evaluating the impedance, charge storage capacity, and maximum injectable charge. Twelve quick to implant peripheral intraneural electrodes (Q-PINEs) were implanted in four pig sciatic nerves to evaluate the implantation time and neural selectivity. We compared the stimulation of the sciatic nerve with that of its branches. Main results. The average surgical access time was 23 min. The insertion time for 12 electrodes was 6.7 min (std. ±1.6 min). The overall implantation time was reduced by 40.3 min compared to the previously reported values. The Q-PINE system demonstrated a satisfactory performance during in vitro and in vivo characterization. The electrochemical results showed that the PEDOT coating successfully increased the electrochemical parameters of the active sites. Significance. With an average impedance of 1.7 kΩ, a maximum charge level of 76.2 nC could be achieved per active site. EMG recruitment curves showed that 46% of the active sites exhibited selective stimulation of four out of six muscles. The histological analysis indicated that the microwires successfully penetrated the nerve and single fascicles.