Interface properties of nanostructured carbon-coated biological implants: an overview

The interfaces between medical implants and living tissues are of great complexity because of the simultaneous occurrence of a wide variety of phenomena. The engineering of implant surfaces represents a crucial challenge in material science, but the further improvement of implant properties remains a critical task. It can be achieved through several processes. Among them, the production of specialized coatings based on carbon-based materials stands very promising. The use of carbon coatings allows one to simultaneously fine-tune tribological, mechanical, and chemical properties. Here, we review applications of nanostructured carbon coatings (nanodiamonds, carbon nanotubes, and graphene-related materials) for the improvement of the overall properties of medical implants. We are focusing on biological interactions, improved corrosion resistance, and overall mechanical properties, trying to provide a complete overview within the field.

Interface-Mediated Neurogenic Signaling: The Impact of Surface Geometry and Chemistry on Neural Cell Behavior for Regenerative and Brain-Machine Interfacing Applications

Nanomaterial advancements have driven progress in central and peripheral nervous system applications such as tissue regeneration and brain-machine interfacing. Ideally, neural interfaces with native tissue shall seamlessly integrate, a process that is often mediated by the interfacial material properties. Surface topography and material chemistry are significant extracellular stimuli that can influence neural cell behavior to facilitate tissue integration and augment therapeutic outcomes. This review characterizes topographical modifications, including micropillars, microchannels, surface roughness, and porosity, implemented on regenerative scaffolding and brain-machine interfaces. Their impact on neural cell response is summarized through neurogenic outcome and mechanistic analysis. The effects of surface chemistry on neural cell signaling with common interfacing compounds like carbon-based nanomaterials, conductive polymers, and biologically inspired matrices are also reviewed. Finally, the impact of these extracellular mediated neural cues on intracellular signaling cascades is discussed to provide perspective on the manipulation of neuron and neuroglia cell microenvironments to drive therapeutic outcomes.

Robust adaptive deep brain stimulation control of in-silico non-stationary Parkinsonian neural oscillatory dynamics

Objective. Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson's disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) Parkinsonian beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering accurate and robust control of Parkinsonian neural oscillatory dynamics.Approach. Here, we develop a new robust adaptive closed-loop DBS method for regulating the Parkinsonian beta oscillatory dynamics of the cortex-BG-thalamus network. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated Parkinsonian neural state while reducing the system's sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as an in-silico simulation testbed to generate nonlinear and non-stationary Parkinsonian neural dynamics for evaluating DBS methods.Main results. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG Parkinsonian beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms current on-off and LTI DBS methods.Significance. These results have implications for future designs of closed-loop DBS systems to treat PD.

Polymer Bioelectronics: A Solution for Both Stimulating and Recording Electrodes

The advent of closed-loop bionics has created a demand for electrode materials that are ideal for both stimulating and recording applications. The growing complexity and diminishing size of implantable devices for neural interfaces have moved beyond what can be achieved with conventional metallic electrode materials. Polymeric electrode materials are a recent development based on polymer composites of organic conductors such as conductive polymers. These materials present exciting new opportunities in the design and fabrication of next-generation electrode arrays which can overcome the electrochemical and mechanical limitations of conventional electrode materials. This review will examine the recent developments in polymeric electrode materials, their application as stimulating and recording electrodes in bionic devices, and their impact on the development of soft, conformal, and high-density neural interfaces.

Event detection and classification from multimodal time series with application to neural data

The detection of events in time-series data is a common signal-processing problem. When the data can be modeled as a known template signal with an unknown delay in Gaussian noise, detection of the template signal can be done with a traditional matched filter. However, in many applications, the event of interest is represented in multimodal data consisting of both Gaussian and point-process time series. Neuroscience experiments, for example, can simultaneously record multimodal neural signals such as local field potentials (LFPs), which can be modeled as Gaussian, and neuronal spikes, which can be modeled as point processes. Currently, no method exists for event detection from such multimodal data, and as such our objective in this work is to develop a method to meet this need. Here we address this challenge by developing the multimodal event detector (MED) algorithm which simultaneously estimates event times and classes. To do this, we write a multimodal likelihood function for Gaussian and point-process observations and derive the associated maximum likelihood estimator of simultaneous event times and classes. We additionally introduce a cross-modal scaling parameter to account for model mismatch in real datasets. We validate this method in extensive simulations as well as in a neural spike-LFP dataset recorded during an eye-movement task, where the events of interest are eye movements with unknown times and directions. We show that the MED can successfully detect eye movement onset and classify eye movement direction. Further, the MED successfully combines information across data modalities, with multimodal performance exceeding unimodal performance. This method can facilitate applications such as the discovery of latent events in multimodal neural population activity and the development of brain-computer interfaces for naturalistic settings without constrained tasks or prior knowledge of event times.

Long-term exposure of endangered Danube sturgeon (Acipenser gueldenstaedtii) to bisphenol A (BPA): growth, behavioral, histological, genotoxic, and hematological evaluation

Danube sturgeon (Acipenser gueldenstaedtii) which is identified as endangered species can be exposed to pollutants such as bisphenol A (BPA) that have a disruptive effect on the endocrine system at any time. Starting from this motivation, the current study focused on BPA toxicity in A. gueldenstaedtii juvenile individuals and its adverse effects in sub-lethal concentration. The median lethal concentration (LC50) of BPA was 5.03 mg/L in 96th hour. In the chronic period, 0.625 mg/L and 1.25 mg/L BPA concentrations were evaluated based on the result of acute study. Accordingly, growth performance was significantly decreased in BPA groups (1.25 mg/L BPA group was significantly lowest) compared to control (p < 0.05). In the acute period, behavioral disorders were standing at the bottom/corner of tank, slowing and stopping of gill movement, decreased response to stimuli, and death, respectively. While vacuolization was severe in the liver tissue of the fish in the acute period, intense necrosis and melanomacrophage centers were observed in the chronic period. In terms of genotoxicity, longer DNA migration was observed in all groups exposed to BPA than in the control group. In addition, lower erythrocyte and hemoglobin were observed in the BPA groups compared to control. As a result, the current study revealed toxic effect of BPA on A. gueldenstaedtii juvenile individuals and its negative results on fish physiology.

Acute to long-term characteristics of impedance recordings during neurostimulation in humans

Objective.This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Approach.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24 h impedance cycle throughout the multi-month recording.Main results.Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 d to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24 h impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.Significance.Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.

Wireless Battery-free and Fully Implantable Organ Interfaces

Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.

An Open-Source 3D-Printed Hindlimb Stabilization Apparatus for Reliable Measurement of Stimulation-Evoked Ankle Flexion in Rat

Currently there are numerous methods to evaluate peripheral nerve stimulation interfaces in rats, with stimulation-evoked ankle torque being one of the most prominent. Commercial rat ankle torque measurement systems and custom one-off solutions have been published in the literature. However, commercial systems are proprietary and costly and do not allow for customization. One-off lab-built systems have required specialized machining expertise, and building plans have previously not been made easily accessible. Here, detailed building plans are provided for a low-cost, open-source, and basic ankle torque measurement system from which additional customization can be made. A hindlimb stabilization apparatus was developed to secure and stabilize a rat's hindlimb, while allowing for simultaneous ankle-isometric torque and lower limb muscle electromyography (EMG). The design was composed mainly of adjustable 3D-printed components to accommodate anatomical differences between rat hindlimbs. Additionally, construction and calibration procedures of the rat hindlimb stabilization apparatus were demonstrated in this study. In vivo torque measurements were reliably acquired and corresponded to increasing stimulation amplitudes. Furthermore, implanted leads used for intramuscular EMG recordings complemented torque measurements and were used as an additional functional measurement in evaluating the performance of a peripheral nerve stimulation interface. In conclusion, an open-source and noninvasive platform, made primarily with 3D-printed components, was constructed for reliable data acquisition of evoked motor activity in rat models. The purpose of this apparatus is to provide researchers a versatile system with adjustable components that can be tailored to meet user-defined experimental requirements when evaluating motor function of the rat hindlimbs.

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Objective.Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain-machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales.Approach.Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient learning for modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical SID method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and with spiking and local field potential population activity recorded during a naturalistic reach and grasp behavior.Main results.We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson-Gaussian observations, multiscale SID had a much lower training time while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity and behavior.Significance.Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest, such as for online adaptive BMIs to track non-stationary dynamics or for reducing offline training time in neuroscience investigations.

Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters

BACKGROUND

Peripheral nerve recordings can enhance the efficacy of neurostimulation therapies by providing a feedback signal to adjust stimulation settings for greater efficacy or reduced side effects. Computational models can accelerate the development of interfaces with high signal-to-noise ratio and selective recording. However, validation and tuning of model outputs against in vivo recordings remains computationally prohibitive due to the large number of fibers in a nerve.

METHODS

We designed and implemented highly efficient modeling methods for simulating electrically evoked compound nerve action potential (CNAP) signals. The method simulated a subset of fiber diameters present in the nerve using NEURON, interpolated action potential templates across fiber diameters, and filtered the templates with a weighting function derived from fiber-specific conduction velocity and electromagnetic reciprocity outputs of a volume conductor model. We applied the methods to simulate CNAPs from rat cervical vagus nerve.

RESULTS

Brute force simulation of a rat vagal CNAP with all 1,759 myelinated and 13,283 unmyelinated fibers in NEURON required 286 and 15,860 CPU hours, respectively, while filtering interpolated templates required 30 and 38 seconds on a desktop computer while maintaining accuracy. Modeled CNAP amplitude could vary by over two orders of magnitude depending on tissue conductivities and cuff opening within experimentally relevant ranges. Conduction distance and fiber diameter distribution also strongly influenced the modeled CNAP amplitude, shape, and latency. Modeled and in vivo signals had comparable shape, amplitude, and latency for myelinated fibers but not for unmyelinated fibers.

CONCLUSIONS

Highly efficient methods of modeling neural recordings quantified the large impact that tissue properties, conduction distance, and nerve fiber parameters have on CNAPs. These methods expand the computational accessibility of neural recording models, enable efficient model tuning for validation, and facilitate the design of novel recording interfaces for neurostimulation feedback and understanding physiological systems.

Using Compound Neural Action Potentials for Functional Validation of a High-Density Intraneural Interface: A Preliminary Study

Compound nerve action potentials (CNAPs) were used as a metric to assess the stimulation performance of a novel high-density, transverse, intrafascicular electrode in rat models. We show characteristic CNAPs recorded from distally implanted cuff electrodes. Evaluation of the CNAPs as a function of stimulus current and calculation of recruitment plots were used to obtain a qualitative approximation of the neural interface's placement and orientation inside the nerve. This method avoids elaborate surgeries required for the implantation of EMG electrodes and thus minimizes surgical complications and may accelerate the healing process of the implanted subject.

Accelerating neurotechnology development using an Agile methodology

Novel bioelectronic medical devices that target neural control of visceral organs (e.g., liver, gut, spleen) or inflammatory reflex pathways are innovative class III medical devices like implantable cardiac pacemakers that are lifesaving and life-sustaining medical devices. Bringing innovative neurotechnologies early into the market and the hands of treatment providers would benefit a large population of patients inflicted with autonomic and chronic immune disorders. Medical device manufacturers and software developers widely use the Waterfall methodology to implement design controls through verification and validation. In the Waterfall methodology, after identifying user needs, a functional unit is fabricated following the verification loop (design, build, and verify) and then validated against user needs. Considerable time can lapse in building, verifying, and validating the product because this methodology has limitations for adjusting to unanticipated changes. The time lost in device development can cause significant delays in final production, increase costs, and may even result in the abandonment of the device development. Software developers have successfully implemented an Agile methodology that overcomes these limitations in developing medical software. However, Agile methodology is not routinely used to develop medical devices with implantable hardware because of the increased regulatory burden of the need to conduct animal and human studies. Here, we provide the pros and cons of the Waterfall methodology and make a case for adopting the Agile methodology in developing medical devices with physical components. We utilize a peripheral nerve interface as an example device to illustrate the use of the Agile approach to develop neurotechnologies.

Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review

Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.

Acute to long-term characteristics of impedance recordings during neurostimulation in humans

Objective

This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus (AMG-HPC), and posterior hippocampus (post-HPC) over an extended period.

Approach

Impedance was periodically sampled every 5-15 minutes over several months in five subjects with drug-resistant epilepsy using an experimental neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24-hour impedance cycle throughout the multi-month recording.

Main results

Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 days to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24-hour impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.

Significance

Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.

Stretchable, Self-Rolled, Microfluidic Electronics Enable Conformable Neural Interfaces of Brain and Vagus Neuromodulation

Implantable neuroelectronic interfaces have gained significant importance in long-term brain-computer interfacing and neuroscience therapy. However, due to the mechanical and geometrical mismatches between the electrode-nerve interfaces, personalized and compatible neural interfaces remain serious issues for peripheral neuromodulation. This study introduces the stretchable and flexible electronics class as a self-rolled neural interface for neurological diagnosis and modulation. These stretchable electronics are made from liquid metal-polymer conductors with a high resolution of 30 μm using microfluidic printing technology. They exhibit high conformability and stretchability (over 600% strain) during body movements and have good biocompatibility during long-term implantation (over 8 weeks). These stretchable electronics offer real-time monitoring of epileptiform activities with excellent conformability to soft brain tissue. The study also develops self-rolled microfluidic electrodes that tightly wind the deforming nerves with minimal constraint (160 μm in diameter). The in vivo signal recording of the vagus and sciatic nerve demonstrates the potential of self-rolled cuff electrodes for sciatic and vagus neural modulation by recording action potential and reducing heart rate. The findings of this study suggest that the robust, easy-to-use self-rolled microfluidic electrodes may provide useful tools for compatible neuroelectronics and neural modulation.

Some Mechanical Constraints to the Biomimicry with Peripheral Nerves

Novel high technology devices built to restore impaired peripheral nerves should be biomimetic in both their structure and in the biomolecular environment created around regenerating axons. Nevertheless, the structural biomimicry with peripheral nerves should follow some basic constraints due to their complex mechanical behaviour. However, it is not currently clear how these constraints could be defined. As a consequence, in this work, an explicit, deterministic, and physical-based framework was proposed to describe some mechanical constraints needed to mimic the peripheral nerve behaviour in extension. More specifically, a novel framework was proposed to investigate whether the similarity of the stress/strain curve was enough to replicate the natural nerve behaviour. An original series of computational optimizing procedures was then introduced to further investigate the role of the tangent modulus and of the rate of change of the tangent modulus with strain in better defining the structural biomimicry with peripheral nerves.

Facile fabrication of carboxymethylcellulose/ZnO/g-C3N4 containing nutmeg extract with photocatalytic performance for infected wound healing

New topical antibacterial agents are required to inhibit and development of bacteria and also promoting the wound healing process. This study was evaluating the healing effect of Myristica fragrans extract coated with carboxymethyl cellulose, zinc oxide and graphite carbon nitride (CMC/ZnO/g-C3N4/MyR) by photocatalytic process on the healing process of full-thickness infectious excision wounds in mice. Nanosheets were prepared and physicochemical properties were evaluated. Safety, in vitro release, antibacterial activities under in vitro and in vivo condition, wound contraction, histopathological properties and the protein expressions of tumor necrosis factor-α (TNF-α), collagen 1A (COL1A) and CD31 were also evaluated. Physicochemical properties confirmed their successful synthesis. Nanosheets exhibited antibacterial activity under in vitro and in vivo conditions. The formulations containing CMC/ZnO/g-C3N4/MyR, significantly (P < 0.05) competed with standard ointment of mupirocin for accelerating the wound healing process due to their effects on bacterial count and the expression of TNF-α and also accelerating the proliferative phase. This structure can be used as a safe structure in combination with other agents for accelerating the wound healing process following future clinical studies.

Beyond Tissue replacement: The Emerging role of smart implants in healthcare

Smart implants are increasingly used to treat various diseases, track patient status, and restore tissue and organ function. These devices support internal organs, actively stimulate nerves, and monitor essential functions. With continuous monitoring or stimulation, patient observation quality and subsequent treatment can be improved. Additionally, using biodegradable and entirely excreted implant materials eliminates the need for surgical removal, providing a patient-friendly solution. In this review, we classify smart implants and discuss the latest prototypes, materials, and technologies employed in their creation. Our focus lies in exploring medical devices beyond replacing an organ or tissue and incorporating new functionality through sensors and electronic circuits. We also examine the advantages, opportunities, and challenges of creating implantable devices that preserve all critical functions. By presenting an in-depth overview of the current state-of-the-art smart implants, we shed light on persistent issues and limitations while discussing potential avenues for future advancements in materials used for these devices.

In Vivo Efficacy of a Novel, Sutureless Coaptation Device for Repairing Peripheral Nerve Defects

Although microsuture neurorrhaphy is the accepted clinical standard treatment for severed peripheral nerves, this technique requires microsurgical proficiency and still often fails to provide adequate nerve approximation for effective regeneration. Entubulation utilizing commercially available conduits may enhance the technical quality of the nerve coaptation and potentially provide a proregenerative microenvironment, but still requires precise suture placement. We developed a sutureless nerve coaptation device, Nerve Tape®, that utilizes Nitinol microhooks embedded within a porcine small intestinal submucosa backing. These tiny microhooks engage the outer epineurium of the nerve, while the backing wraps the coaptation to provide a stable, entubulated repair. In this study, we examine the impact of Nerve Tape on nerve tissue and axonal regeneration, compared with repairs performed with commercially available conduit-assisted or microsuture-only repairs. Eighteen male New Zealand white rabbits underwent a tibial nerve transection, immediately repaired with (1) Nerve Tape, (2) conduit plus anchoring sutures, or (3) four 9-0 nylon epineurial microsutures. At 16 weeks postinjury, the nerves were re-exposed to test sensory and motor nerve conduction, measure target muscle weight and girth, and perform nerve tissue histology. Nerve conduction velocities in the Nerve Tape group were significantly better than both the microsuture and conduit groups, while nerve compound action potential amplitudes in the Nerve Tape group were significantly better than the conduit group only. Gross morphology, muscle characteristics, and axon histomorphometry were not statistically different between the three repair groups. In the rabbit tibial nerve repair model, Nerve Tape offers similar regeneration efficacy compared with conduit-assisted and microsuture-only repairs, suggesting minimal impact of microhooks on nerve tissue.

A Pilot In Vivo Study of Flexible Fully Polymeric Nerve Cuff Electrodes. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083283 DOI: 10.1109/embc40787.2023.10341006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Recent trends in the field of bioelectronics have been focused on the development of electrodes that facilitate safe and efficient stimulation of nervous tissues. Novel conducting polymer (CP) based materials, such as flexible and fully polymeric conductive elastomers (CEs), constitute a promising alternative to improve on the limitations of current metallic devices. This pilot study demonstrates the performance of tripolar CE-based peripheral nerve cuffs compared to current commercial tripolar platinum-iridium (PtIr) nerve cuffs in vivo. CE and metallic cuff devices were implanted onto rodent sciatic nerves for a period of 8 weeks. Throughout the entire study, the CE device demonstrated improved charge transfer and electrochemical safety compared to the PtIr cuff, able to safely inject 2 to 3 times more charge. In comparison to the commercial control, the CE cuff was able to record in the in vivo setting with reduced noise and produced smaller voltages at all simulation levels. CE technologies provide a promising alternative to metallic devices for the development of bioelectronics with enhanced chronic device functionality.

Low-threshold, high-resolution, chronically stable intracortical microstimulation by ultraflexible electrodes

Intracortical microstimulation (ICMS) enables applications ranging from neuroprosthetics to causal circuit manipulations. However, the resolution, efficacy, and chronic stability of neuromodulation are often compromised by adverse tissue responses to the indwelling electrodes. Here we engineer ultraflexible stim-nanoelectronic threads (StimNETs) and demonstrate low activation threshold, high resolution, and chronically stable ICMS in awake, behaving mouse models. In vivo two-photon imaging reveals that StimNETs remain seamlessly integrated with the nervous tissue throughout chronic stimulation periods and elicit stable, focal neuronal activation at low currents of 2 μA. Importantly, StimNETs evoke longitudinally stable behavioral responses for over 8 months at a markedly low charge injection of 0.25 nC/phase. Quantified histological analyses show that chronic ICMS by StimNETs induces no neuronal degeneration or glial scarring. These results suggest that tissue-integrated electrodes provide a path for robust, long-lasting, spatially selective neuromodulation at low currents, which lessens risk of tissue damage or exacerbation of off-target side effects.

Optoelectronic and mechanical properties of microstructured polymer optical fiber neural probes

Multifunctional optical fiber-based neural interfaces have attracted significant attention for neural stimulation, recording, and photopharmacology towards understanding the central nervous system. In this work, we demonstrate the fabrication, optoelectrical characterization, and mechanical analysis of four types of microstructured polymer optical fiber neural probes using different soft thermoplastic polymers. The developed devices have integrated metallic elements for electrophysiology and microfluidic channels for localized drug delivery, and can be used for optogenetics in the visible spectrum at wavelengths spanning from 450 nm up to 800 nm. Their impedance, measured by electrochemical impedance spectroscopy, was found to be as low as 21 kΩ and 4.7 kΩ at 1kHz when indium and tungsten wires are used as the integrated electrodes, respectively. Uniform on-demand drug delivery can be achieved by the microfluidic channels with a measured delivery rate from 10 up to 1000 nL/min. In addition, we identified the buckling failure threshold (defined as the conditions for successful implantation) as well as the bending stiffness of the fabricated fibers. Using finite element analysis, we calculated the main critical mechanical properties of the developed probes to avoid buckling during implantation and maintain high flexibility of the probe within the tissue. Our results aim to demonstrate the impact of design, fabrication, and characteristics of the materials on the development of polymer fibers as next-generation implants and neural interfaces.

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain-machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales. Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical subspace identification method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and spike-LFP population activity recorded during a naturalistic reach and grasp behavior. We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson-Gaussian observations, multiscale SID had a much lower computational cost while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity. Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest.

Graphene-Related Nanomaterials for Biomedical Applications

This paper builds on the context and recent progress on the control, reproducibility, and limitations of using graphene and graphene-related materials (GRMs) in biomedical applications. The review describes the human hazard assessment of GRMs in in vitro and in vivo studies, highlights the composition-structure-activity relationships that cause toxicity for these substances, and identifies the key parameters that determine the activation of their biological effects. GRMs are designed to offer the advantage of facilitating unique biomedical applications that impact different techniques in medicine, especially in neuroscience. Due to the increasing utilization of GRMs, there is a need to comprehensively assess the potential impact of these materials on human health. Various outcomes associated with GRMs, including biocompatibility, biodegradability, beneficial effects on cell proliferation, differentiation rates, apoptosis, necrosis, autophagy, oxidative stress, physical destruction, DNA damage, and inflammatory responses, have led to an increasing interest in these regenerative nanostructured materials. Considering the existence of graphene-related nanomaterials with different physicochemical properties, the materials are expected to exhibit unique modes of interactions with biomolecules, cells, and tissues depending on their size, chemical composition, and hydrophil-to-hydrophobe ratio. Understanding such interactions is crucial from two perspectives, namely, from the perspectives of their toxicity and biological uses. The main aim of this study is to assess and tune the diverse properties that must be considered when planning biomedical applications. These properties include flexibility, transparency, surface chemistry (hydrophil-hydrophobe ratio), thermoelectrical conductibility, loading and release capacity, and biocompatibility.

Sensing and Stimulation Applications of Carbon Nanomaterials in Implantable Brain-Computer Interface

Implantable brain–computer interfaces (BCIs) are crucial tools for translating basic neuroscience concepts into clinical disease diagnosis and therapy. Among the various components of the technological chain that increases the sensing and stimulation functions of implanted BCI, the interface materials play a critical role. Carbon nanomaterials, with their superior electrical, structural, chemical, and biological capabilities, have become increasingly popular in this field. They have contributed significantly to advancing BCIs by improving the sensor signal quality of electrical and chemical signals, enhancing the impedance and stability of stimulating electrodes, and precisely modulating neural function or inhibiting inflammatory responses through drug release. This comprehensive review provides an overview of carbon nanomaterials’ contributions to the field of BCI and discusses their potential applications. The topic is broadened to include the use of such materials in the field of bioelectronic interfaces, as well as the potential challenges that may arise in future implantable BCI research and development. By exploring these issues, this review aims to provide insight into the exciting developments and opportunities that lie ahead in this rapidly evolving field.

Colloidal Perspective on Targeted Drug Delivery to the Central Nervous System

This article describes a new approach in targeted drug delivery to the central nervous system (CNS) in a significant departure from the predominant systematic drug administration attempting to penetrate the blood-brain barrier (BBB). Nanoparticles chemically conjugated to neural tract tracer proteins are capable of path-specific axonal retrograde transport, transneuronal transport, and anatomical tract flow to bypass the BBB. To celebrate the work by Dr. Bettye Washington Greene on the physical chemistry of colloidal particles, this article focuses on the physiochemical characteristics of the nanoparticles, various colloidal forces that impact the colloidal stability of nanoparticles in biological media, and surface chemistry strategies to avoid nanoparticle aggregation-induced poor therapeutic outcomes. The biological environment for the anatomical retrograde transport of neural tract tracers is examined to directly link factors impacting the colloidal stability of the new class of CNS-targeting nanoconjugates such as nanoconjugate size, shape, surface charge, surface chemistry, ionic strength, pH, and protein adsorption on the nanoparticle. We conclude with opportunities and challenges for future research.

A new full closed-loop brain-machine interface approach based on neural activity: A study based on modeling and experimental studies

Background

The bidirectional brain-machine interfaces algorithms are machines that decode neural response in order to control the external device and encode position of artificial limb to proper electrical stimulation, so that the interface between brain and machine closes. Most BMI researchers typically consider four basic elements: recording technology to extract brain activity, decoding algorithm to translate brain activity to the predicted movement of the external device, external device (prosthetic limb such as a robotic arm), and encoding interface to convert the motion of the external machine to set of the electrical stimulation of the brain.

New method

In this paper, we develop a novel approach for bidirectional brain-machine interface (BMI). First, we propose a neural network model for sensory cortex (S₁) connected to the neural network model of motor cortex (M₁) considering the topographic mapping between S₁ and M₁. We use 4-box model in S₁ and 4-box in M₁ so that each box contains 500 neurons. Individual boxes include inhibitory and excitatory neurons and synapses. Next, we develop a new BMI algorithm based on neural activity. The main concept of this BMI algorithm is to close the loop between brain and mechaical external device.

Results

The sensory interface as encoding algorithm convert the location of the external device (artificial limb) into the electrical stimulation which excite the S₁ model. The motor interface as decoding algorithm convert neural recordings from the M₁ model into a force which causes the movement of the external device. We present the simulation results for the on line BMI which means that there is a real time information exchange between 9 boxes and 4 boxes of S₁-M₁ network model and the external device. Also, off line information exchange between brain of five anesthetized rats and externnal device was performed. The proposed BMI algorithm has succeeded in controlling the movement of the mechanical arm towards the target area on simulation and experimental data, so that the BMI algorithm shows acceptable WTPE and the average number of iterations of the algorithm in reaching artificial limb to the target region.Comparison with existing methods and Conclusions: In order to confirm the simulation results the 9-box model of S₁-M₁ network was developed and the valid "spike train" algorithm, which has good results on real data, is used to compare the performance accuracy of the proposed BMI algorithm versus "spike train" algorithm on simulation and off line experimental data of anesthetized rats. Quantitative and qualitative results confirm the proper performance of the proposed algorithm compared to algorithm "spike train" on simulations and experimental data.

Upper limb prostheses: bridging the sensory gap

Replacing human hand function with prostheses goes far beyond only recreating muscle movement with feedforward motor control. Natural sensory feedback is pivotal for fine dexterous control and finding both engineering and surgical solutions to replace this complex biological function is imperative to achieve prosthetic hand function that matches the human hand. This review outlines the nature of the problems underlying sensory restitution, the engineering methods that attempt to address this deficit and the surgical techniques that have been developed to integrate advanced neural interfaces with biological systems. Currently, there is no single solution to restore sensory feedback. Rather, encouraging animal models and early human studies have demonstrated that some elements of sensation can be restored to improve prosthetic control. However, these techniques are limited to highly specialized institutions and much further work is required to reproduce the results achieved, with the goal of increasing availability of advanced closed loop prostheses that allow sensory feedback to inform more precise feedforward control movements and increase functionality.

Low-threshold, high-resolution, chronically stable intracortical microstimulation by ultraflexible electrodes

Intracortical microstimulation (ICMS) enables applications ranging from neuroprosthetics to causal circuit manipulations. However, the resolution, efficacy, and chronic stability of neuromodulation is often compromised by the adverse tissue responses to the indwelling electrodes. Here we engineer ultraflexible stim-Nanoelectronic Threads (StimNETs) and demonstrate low activation threshold, high resolution, and chronically stable ICMS in awake, behaving mouse models. In vivo two-photon imaging reveals that StimNETs remain seamlessly integrated with the nervous tissue throughout chronic stimulation periods and elicit stable, focal neuronal activation at low currents of 2 μA. Importantly, StimNETs evoke longitudinally stable behavioral responses for over eight months at markedly low charge injection of 0.25 nC/phase. Quantified histological analysis show that chronic ICMS by StimNETs induce no neuronal degeneration or glial scarring. These results suggest that tissue-integrated electrodes provide a path for robust, long-lasting, spatially-selective neuromodulation at low currents which lessen risks of tissue damage or exacerbation of off-target side-effects.

Self-Closing Stretchable Cuff Electrodes for Peripheral Nerve Stimulation and Electromyographic Signal Recording

The cuff electrode can be wrapped in the columnar or tubular biological tissue for physiological signal detection or stimulation regulation. The reliable and non-excessive interfaces between the electrode and complex tissue are critical. Here, we propose a self-closing stretchable cuff electrode, which is able to self-close onto the bundles of tissues after dropping water. The curliness is realized by the mechanical stress mismatch between different layers of the elastic substrate. The material of the substrate can be selected to match the modulus of the target tissue to achieve minimal constraint on the tissue. Moreover, the self-closing structure keeps the cuff electrode free from any extra mechanical locking structure. For in vivo testing, both sciatic nerve stimulation to drive muscles and electromyographic signal monitoring around a rat's extensor digitorum longus for 1 month prove that our proposed electrode conforms well to the curved surface of biological tissue.

Implantable intracortical microelectrodes: reviewing the present with a focus on the future

Implantable intracortical microelectrodes can record a neuron's rapidly changing action potentials (spikes). In vivo neural activity recording methods often have either high temporal or spatial resolution, but not both. There is an increasing need to record more neurons over a longer duration in vivo. However, there remain many challenges to overcome before achieving long-term, stable, high-quality recordings and realizing comprehensive, accurate brain activity analysis. Based on the vision of an idealized implantable microelectrode device, the performance requirements for microelectrodes are divided into four aspects, including recording quality, recording stability, recording throughput, and multifunctionality, which are presented in order of importance. The challenges and current possible solutions for implantable microelectrodes are given from the perspective of each aspect. The current developments in microelectrode technology are analyzed and summarized.

Peripheral neurostimulation for encoding artificial somatosensations

The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of the nervous sensory pathway can be adopted to restore the artificial sense of touch and proprioception in people suffering from sensory-motor disorders. The modulation of the neural stimulation parameters has a direct effect on the electrically induced sensations, both when targeting the somatosensory cortex and the peripheral somatic nerves. The properties of the artificial sensations perceived, as their location, quality and intensity are strongly dependent on the direct modulation of pulse width, amplitude and frequency of the neural stimulation. Different sensory encoding schemes have been tested in patients showing distinct effects and outcomes according to their impact on the neural activation. Here, I reported the most adopted neural stimulation strategies to artificially encode somatosensation into the peripheral nervous system. The real-time implementation of these strategies in bionic devices is crucial to exploit the artificial sensory feedback in prosthetics. Thus, neural stimulation becomes a tool to directly communicate with the human nervous system. Given the importance of adding artificial sensory information to neuroprosthetic devices to improve their control and functionality, the choice of an optimal neural stimulation paradigm could increase the impact of prosthetic devices on the quality of life of people with sensorimotor disabilities.

Vascular remodeling in sheep implanted with endovascular neural interface

Objective.The aim of this work was to assess vascular remodeling after the placement of an endovascular neural interface (ENI) in the superior sagittal sinus (SSS) of sheep. We also assessed the efficacy of neural recording using an ENI.Approach.The study used histological analysis to assess the composition of the foreign body response. Micro-CT images were analyzed to assess the profiles of the foreign body response and create a model of a blood vessel. Computational fluid dynamic modeling was performed on a reconstructed blood vessel to evaluate the blood flow within the vessel. Recording of brain activity in sheep was used to evaluate efficacy of neural recordings.Main results.Histological analysis showed accumulated extracellular matrix material in and around the implanted ENI. The extracellular matrix contained numerous macrophages, foreign body giant cells, and new vascular channels lined by endothelium. Image analysis of CT slices demonstrated an uneven narrowing of the SSS lumen proportional to the stent material within the blood vessel. However, the foreign body response did not occlude blood flow. The ENI was able to record epileptiform spiking activity with distinct spike morphologies.Significance. This is the first study to show high-resolution tissue profiles, the histological response to an implanted ENI and blood flow dynamic modeling based on blood vessels implanted with an ENI. The results from this study can be used to guide surgical planning and future ENI designs; stent oversizing parameters to blood vessel diameter should be considered to minimize detrimental vascular remodeling.

Seamless Capacitive Body Channel Wireless Power Transmission Toward Freely Moving Multiple Animals in an Animal Cage

Unstable wireless power transmission toward multiple living animals in an animal cage is one of the significant barriers to performing long-term and real-time neural monitoring in preclinical research. Here, seamless capacitive body channel (SCB) wireless power transmission (WPT) along with power management integrated circuit (PMIC) is designed using a standard 65 nm CMOS process. The SCB WPT enables stable wireless power transmission toward multiple 35 mm×20 mm×2 mm sized receivers (RXs) attached to freely moving animals in a 600 mm×600 mm×120 mm sized animal cage. By utilizing fringe-field capacitance and a body channel for wireless power link between the cage and RXs, the maximum difference in all measured power efficiencies in diverse scenarios is only 6.66 % with a 20 mW load. Even with a 90 ^° RX rotation against the cage, power efficiency marks 17.76 %. Furthermore, an in-vivo experiment conducted with three untethered rats demonstrates the capability of continuous long-term power delivery in practical situations.

Micro-magnetic stimulation of primary visual cortex induces focal and sustained activation of secondary visual cortex

Cortical visual prostheses that aim to restore sight to the blind require the ability to create neural activity in the visual cortex. Electric stimulation delivered via microelectrodes implanted in the primary visual cortex (V1) has been the most common approach, although conventional electrodes may not effectively confine activation to focal regions and thus the acuity they create may be limited. Magnetic stimulation from microcoils confines activation to single cortical columns of V1 and thus may prove to be more effective than conventional microelectrodes, but the ability of microcoils to drive synaptic connections has not been explored. Here, we show that magnetic stimulation of V1 using microcoils induces spatially confined activation in the secondary visual cortex (V2) in mouse brain slices. Single-loop microcoils were fabricated using platinum-iridium flat microwires, and their effectiveness was evaluated using calcium imaging and compared with that of monopolar and bipolar electrodes. Our results show that compared to the electrodes, the microcoils better confined activation to a small region in V1. In addition, they produced more precise and sustained activation in V2. The finding that microcoil-based stimulation propagates to higher visual centres raises the possibility that complex visual perception, e.g. that requiring sustained synaptic inputs, may be achievable. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'.

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.

Finding the Location of Axonal Activation by a Miniature Magnetic Coil

Magnetic stimulation for neural activation is widely used in clinical and lab research. In comparison to electric stimulation using an implanted electrode, stimulation with a large magnetic coil is associated with poor spatial specificity and incapability to stimulate deep brain structures. Recent developments in micromagnetic stimulation (μMS) technology mitigates some of these shortcomings. The sub-millimeter coils can be covered with soft, biocompatible material, and chronically implanted. They can provide highly specific neural stimulation in the deep neural structure. Although the μMS technology is expected to provide a precise location of neural stimulation, the exact site of neural activation is difficult to determine. Furthermore, factors that could cause the shifting of the activation site during μMS have not been fully investigated. To estimate the location of axon activation in μMS, we first derived an analytical expression of the activating function, which predicts the location of membrane depolarization in an unmyelinated axon. Then, we developed a multi-compartment, Hodgkin-Huxley (H-H) type of NEURON model of an unmyelinated axon to test the impact of several important coil parameters on the location of axonal activation. The location of axonal activation was dependent on both the parameters of the stimulus and the biophysics properties of the targeted axon during μMS. The activating function analysis predicted that the location of membrane depolarization and activation could shift due to the reversal of the coil current and the change in the coil-axon distance. The NEURON modeling confirmed these predictions. Interestingly, the NEURON simulation further revealed that the intensity of stimulation played a significant role in the activation location. Moderate or strong coil currents activated the axon at different locations, mediated by two distinct ion channel mechanisms. This study reports several experimental factors that could cause a potential shift in the location of neural activation during μMS, which is essential for further development of this novel technology.

Electrochemical modulation enhances the selectivity of peripheral neurostimulation in vivo

SignificanceBioelectronic medicine relies on electrical stimulation for most applications in the peripheral nervous system. It faces persistent challenges in selectively activating bundled nerve fibers. Here, we investigated ion-concentration modulation with ion-selective membranes and whether this modality may enhance the functional selectivity of peripheral nerve stimulation. We designed a multimodal stimulator that could control Ca²⁺ concentrations within a focused volume. Acutely implanting it on the sciatic nerve of a rat, we demonstrated that Ca²⁺ depletion could increase the sensitivity of the nerve to electrical stimulation in vivo. We provided evidence that it selectively influenced individual fascicles of the nerve, allowing selective activation by electrical current. Improved functional selectivity may improve outcomes for important therapeutic modalities.

Feasibility of a Wireless Implantable Multi-electrode System for High-bandwidth Prosthetic Interfacing: Animal and Cadaver Study

BACKGROUND

Currently used prosthetic solutions in upper extremity amputation have limited functionality, owing to low information transfer rates of neuromuscular interfacing. Although surgical innovations have expanded the functional potential of the residual limb, available interfaces are inefficacious in translating this potential into improved prosthetic control. There is currently no implantable solution for functional interfacing in extremity amputation which offers long-term stability, high information transfer rates, and is applicable for all levels of limb loss. In this study, we presented a novel neuromuscular implant, the the Myoelectric Implantable Recording Array (MIRA). To our knowledge, it is the first fully implantable system for prosthetic interfacing with a large channel count, comprising 32 intramuscular electrodes.

QUESTIONS/PURPOSES

The purpose of this study was to evaluate the MIRA in terms of biocompatibility, functionality, and feasibility of implantation to lay the foundations for clinical application. This was achieved through small- and large-animal studies as well as test surgeries in a human cadaver.

METHODS

We evaluated the biocompatibility of the system's intramuscular electromyography (EMG) leads in a rabbit model. Ten leads as well as 10 pieces of a biologically inert control material were implanted into the paravertebral muscles of four animals. After a 3-month implantation, tissue samples were taken and histopathological assessment performed. The probes were scored according to a protocol for the assessment of the foreign body response, with primary endpoints being inflammation score, tissue response score, and capsule thickness in µm. In a second study, chronic functionality of the full system was evaluated in large animals. The MIRA was implanted into the shoulder region of six dogs and three sheep, with intramuscular leads distributed across agonist and antagonist muscles of shoulder flexion. During the observation period, regular EMG measurements were performed. The implants were removed after 5 to 6 months except for one animal, which retained the implant for prolonged observation. Primary endpoints of the large-animal study were mechanical stability, telemetric capability, and EMG signal quality. A final study involved the development of test surgeries in a fresh human cadaver, with the goal to determine feasibility to implant relevant target muscles for prosthetic control at all levels of major upper limb amputation.

RESULTS

Evaluation of the foreign body reaction revealed favorable biocompatibility and a low-grade tissue response in the rabbit study. No differences regarding inflammation score (EMG 4.60 ± 0.97 [95% CI 4.00 to 5.20] versus control 4.20 ± 1.48 [95% CI 3.29 to 5.11]; p = 0.51), tissue response score (EMG 4.00 ± 0.82 [95% CI 3.49 to 4.51] versus control 4.00 ± 0.94 [95% CI 3.42 to 4.58]; p > 0.99), or thickness of capsule (EMG 19.00 ± 8.76 µm [95% CI 13.57 to 24.43] versus control 29.00 ± 23.31 µm [95% CI 14.55 to 43.45]; p = 0.29) were found compared with the inert control article (high-density polyethylene) after 3 months of intramuscular implantation. Throughout long-term implantation of the MIRA in large animals, telemetric communication remained unrestricted in all specimens. Further, the implants retained the ability to record and transmit intramuscular EMG data in all animals except for two sheep where the implants became dislocated shortly after implantation. Electrode impedances remained stable and below 5 kΩ. Regarding EMG signal quality, there was little crosstalk between muscles and overall average signal-to-noise ratio was 22.2 ± 6.2 dB. During the test surgeries, we found that it was possible to implant the MIRA at all major amputation levels of the upper limb in a human cadaver (the transradial, transhumeral, and glenohumeral levels). For each level, it was possible to place the central unit in a biomechanically stable environment to provide unhindered telemetry, while reaching the relevant target muscles for prosthetic control. At only the glenohumeral level, it was not possible to reach the teres major and latissimus dorsi muscles, which would require longer lead lengths.

CONCLUSION

As assessed in a combination of animal model and cadaver research, the MIRA shows promise for clinical research in patients with limb amputation, where it may be employed for all levels of major upper limb amputation to provide long-term stable intramuscular EMG transmission.

CLINICAL RELEVANCE

In our study, the MIRA provided high-bandwidth prosthetic interfacing through intramuscular electrode sites. Its high number of individual EMG channels may be combined with signal decoding algorithms for accessing spinal motor neuron activity after targeted muscle reinnervation, thus providing numerous degrees of freedom. Together with recent innovations in amputation surgery, the MIRA might enable improved control approaches for upper limb amputees, particularly for patients with above-elbow amputation where the mismatch between available control signals and necessary degrees of freedom for prosthetic control is highest.

Designing and Validating a Robust Adaptive Neuromodulation Algorithm for Closed-Loop Control of Brain States

OBJECTIVE

Neuromodulation systems that use closed-loop brain stimulation to control brain states can provide new therapies for brain disorders. To date, closed-loop brain stimulation has largely used linear time-invariant controllers. However, nonlinear time-varying brain network dynamics and external disturbances can appear during real-time stimulation, collectively leading to real-time model uncertainty. Real-time model uncertainty can degrade the performance or even cause instability of time-invariant controllers. Three problems need to be resolved to enable accurate and stable control under model uncertainty. First, an adaptive controller is needed to track the model uncertainty. Second, the adaptive controller additionally needs to be robust to noise and disturbances. Third, theoretical analyses of stability and robustness are needed as prerequisites for stable operation of the controller in practical applications.

APPROACH

We develop a robust adaptive neuromodulation algorithm that solves the above three problems. First, we develop a state-space brain network model that explicitly includes nonlinear terms of real-time model uncertainty and design an adaptive controller to track and cancel the model uncertainty. Second, to improve the robustness of the adaptive controller, we design two linear filters to increase steady-state control accuracy and reduce sensitivity to high-frequency noise and disturbances. Third, we conduct theoretical analyses to prove the stability of the neuromodulation algorithm and establish a trade-off between stability and robustness, which we further use to optimize the algorithm design. Finally, we validate the algorithm using comprehensive Monte Carlo simulations that span a broad range of model nonlinearity, uncertainty, and complexity.

MAIN RESULTS

The robust adaptive neuromodulation algorithm accurately tracks various types of target brain state trajectories, enables stable and robust control, and significantly outperforms state-of-the-art neuromodulation algorithms.

SIGNIFICANCE

Our algorithm has implications for future designs of precise, stable, and robust closed-loop brain stimulation systems to treat brain disorders and facilitate brain functions.

Advanced Implantable Biomedical Devices Enabled by Triboelectric Nanogenerators

Implantable biomedical devices (IMDs) play essential roles in healthcare. Subject to the limited battery life, IMDs cannot achieve long-term in situ monitoring, diagnosis, and treatment. The proposal and rapid development of triboelectric nanogenerators free IMDs from the shackles of batteries and spawn a self-powered healthcare system. This review aims to overview the development of IMDs based on triboelectric nanogenerators, divided into self-powered biosensors, in vivo energy harvesting devices, and direct electrical stimulation therapy devices. Meanwhile, future challenges and opportunities are discussed according to the development requirements of current-level self-powered IMDs to enhance output performance, develop advanced triboelectric nanogenerators with multifunctional materials, and self-driven close-looped diagnosis and treatment systems.

Strategies for interface issues and challenges of neural electrodes

Neural electrodes, as a bridge for bidirectional communication between the body and external devices, are crucial means for detecting and controlling nerve activity. The electrodes play a vital role in monitoring the state of neural systems or influencing it to treat disease or restore functions. To achieve high-resolution, safe and long-term stable nerve recording and stimulation, a neural electrode with excellent electrochemical performance (e.g., impedance, charge storage capacity, charge injection limit), and good biocompatibility and stability is required. Here, the charge transfer process in the tissues, the electrode-tissue interfaces and the electrode materials are discussed respectively. Subsequently, the latest research methods and strategies for improving the electrochemical performance and biocompatibility of neural electrodes are reviewed. Finally, the challenges in the development of neural electrodes are proposed. It is expected that the development of neural electrodes will offer new opportunities for the evolution of neural prosthesis, bioelectronic medicine, brain science, and so on.

A Microclip Peripheral Nerve Interface (μcPNI) for Bioelectronic Interfacing with Small Nerves

Peripheral nerves carry sensory (afferent) and motor (efferent) signals between the central nervous system and other parts of the body. The peripheral nervous system (PNS) is therefore rich in targets for therapeutic neuromodulation, bioelectronic medicine, and neuroprosthetics. Peripheral nerve interfaces (PNIs) generally suffer from a tradeoff between selectivity and invasiveness. This work describes the fabrication, evaluation, and chronic implantation in zebra finches of a novel PNI that breaks this tradeoff by interfacing with small nerves. This PNI integrates a soft, stretchable microelectrode array with a 2-photon 3D printed microclip (μcPNI). The advantages of this μcPNI compared to other designs are: a) increased spatial resolution due to bi-layer wiring of the electrode leads, b) reduced mismatch in biomechanical properties with the nerve, c) reduced disturbance to the host tissue due to the small size, d) elimination of sutures or adhesives, e) high circumferential contact with small nerves, f) functionality under considerable strain, and g) graded neuromodulation in a low-threshold stimulation regime. Results demonstrate that the μcPNIs are electromechanically robust, and are capable of reliably recording and stimulating neural activity in vivo in small nerves. The μcPNI may also inform the development of new optical, thermal, ultrasonic, or chemical PNIs as well.

Ultrasound Mediated Cellular Deflection Results in Cellular Depolarization

Ultrasound has been used to manipulate cells in both humans and animal models. While intramembrane cavitation and lipid clustering have been suggested as likely mechanisms, they lack experimental evidence. Here, high-speed digital holographic microscopy (kiloHertz order) is used to visualize the cellular membrane dynamics. It is shown that neuronal and fibroblast membranes deflect about 150 nm upon ultrasound stimulation. Next, a biomechanical model that predicts changes in membrane voltage after ultrasound exposure is developed. Finally, the model predictions are validated using whole-cell patch clamp electrophysiology on primary neurons. Collectively, it is shown that ultrasound stimulation directly defects the neuronal membrane leading to a change in membrane voltage and subsequent depolarization. The model is consistent with existing data and provides a mechanism for both ultrasound-evoked neurostimulation and sonogenetic control.

Possibilities in bioelectronics: Super humans or science fiction?

Recent years have led to a rapid increase in the development of neurotechnologies for diagnosis, monitoring, and treatment of conditions with neurological targets. The central driving force has been the need for next-generation devices to treat neural injury and disease, where current pharmaceutical or conventional bioelectronics have been unable to impart sufficient therapeutic effects. The advent of new therapies and advanced technologies has resulted in a reemergence of the concept of superhuman performance. This is a hypothetical possibility that is enabled when bionics are used to augment the neural system and has included the notions of improved cognitive ability and enhancement of hearing and seeing beyond the limitations of a healthy human. It is quite conceivable that a bionic eye could be used for night vision; however, the damage to both the neural system and surrounding tissues in placing such a device is only considered acceptable in the case of a patient that can obtain improvement in quality of life. There are also critical limitations that have hindered clinical translation of high-resolution neural interfaces, despite significant advances in biomaterial and bioelectronics technologies, including the advent of biohybrid devices. Surgical damage and foreign body reactions to such devices can be reduced but not eliminated, and these engineering solutions to reduce inflammation present additional challenges to the long-term performance and medical regulation. As a result, while bioelectronics has seen concepts from science fiction realized, there remains a significant gap to their use as enhancements beyond medical therapies.

Nanofibrous PEDOT-Carbon Composite on Flexible Probes for Soft Neural Interfacing

In this study, we report a flexible implantable 4-channel microelectrode probe coated with highly porous and robust nanocomposite of poly (3,4-ethylenedioxythiophene) (PEDOT) and carbon nanofiber (CNF) as a solid doping template for high-performance in vivo neuronal recording and stimulation. A simple yet well-controlled deposition strategy was developed via in situ electrochemical polymerization technique to create a porous network of PEDOT and CNFs on a flexible 4-channel gold microelectrode probe. Different morphological and electrochemical characterizations showed that they exhibit remarkable and superior electrochemical properties, yielding microelectrodes combining high surface area, low impedance (16.8 ± 2 MΩ µm² at 1 kHz) and elevated charge injection capabilities (7.6 ± 1.3 mC/cm²) that exceed those of pure and composite PEDOT layers. In addition, the PEDOT-CNF composite electrode exhibited extended biphasic charge cycle endurance and excellent performance under accelerated lifetime testing, resulting in a negligible physical delamination and/or degradation for long periods of electrical stimulation. In vitro testing on mouse brain slices showed that they can record spontaneous oscillatory field potentials as well as single-unit action potentials and allow to safely deliver electrical stimulation for evoking field potentials. The combined superior electrical properties, durability and 3D microstructure topology of the PEDOT-CNF composite electrodes demonstrate outstanding potential for developing future neural surface interfacing applications.