Stretchable Tissue-Like Gold Nanowire Composites with Long-Term Stability for Neural Interfaces.

Soft and stretchable nanocomposites can match the mechanical properties of neural tissue, thereby minimizing foreign body reactions to provide optimal stimulation and recording specificity. Soft materials for neural interfaces should simultaneously fulfill a wide range of requirements, including low Young's modulus (<<1 MPa), stretchability (≥30%), high conductivity (>> 1000 S cm-1), biocompatibility, and chronic stability (>> 1 year). Current nanocomposites do not fulfill the above requirements, in particular not the combination of softness and high conductivity. Here, this challenge is addressed by developing a scalable and robust synthesis route based on polymeric reducing agents for smooth, high-aspect ratio gold nanowires (AuNWs) of controllable dimensions with excellent biocompatibility. AuNW-silicone composites show outstanding performance with nerve-like softness (250 kPa), high conductivity (16 000 S cm-1), and reversible stretchability. Soft multielectrode cuffs based on the composite achieve selective functional stimulation, recordings of sensory stimuli in rat sciatic nerves, and show an accelerated lifetime stability of >3 years. The scalable synthesis method provides a chemically stable alternative to the widely used AgNWs, thereby enabling new applications within electronics, biomedical devices, and electrochemistry.

Ion-tunable antiambipolarity in mixed ion-electron conducting polymers enables biorealistic organic electrochemical neurons.

Biointegrated neuromorphic hardware holds promise for new protocols to record/regulate signalling in biological systems. Making such artificial neural circuits successful requires minimal device/circuit complexity and ion-based operating mechanisms akin to those found in biology. Artificial spiking neurons, based on silicon-based complementary metal-oxide semiconductors or negative differential resistance device circuits, can emulate several neural features but are complicated to fabricate, not biocompatible and lack ion-/chemical-based modulation features. Here we report a biorealistic conductance-based organic electrochemical neuron (c-OECN) using a mixed ion-electron conducting ladder-type polymer with stable ion-tunable antiambipolarity. The latter is used to emulate the activation/inactivation of sodium channels and delayed activation of potassium channels of biological neurons. These c-OECNs can spike at bioplausible frequencies nearing 100 Hz, emulate most critical biological neural features, demonstrate stochastic spiking and enable neurotransmitter-/amino acid-/ion-based spiking modulation, which is then used to stimulate biological nerves in vivo. These combined features are impossible to achieve using previous technologies.

Vertical organic electrochemical transistor platforms for efficient electropolymerization of thiophene based oligomers.

Organic electrochemical transistors (OECTs) have emerged as promising candidates for various fields, including bioelectronics, neuromorphic computing, biosensors, and wearable electronics. OECTs operate in aqueous solutions, exhibit high amplification properties, and offer ion-to-electron signal transduction. The OECT channel consists of a conducting polymer, with PEDOT:PSS receiving the most attention to date. While PEDOT:PSS is highly conductive, and benefits from optimized protocols using secondary dopants and detergents, new p-type and n-type polymers are emerging with desirable material properties. Among these, low-oxidation potential oligomers are highly enabling for bioelectronics applications, however the polymers resulting from their polymerization lag far behind in conductivity compared with the established PEDOT:PSS. In this work we show that by careful design of the OECT geometrical characteristics, we can overcome this limitation and achieve devices that are on-par with transistors employing PEDOT:PSS. We demonstrate that the vertical architecture allows for facile electropolymerization of a family of trimers that are polymerized in very low oxidation potentials, without the need for harsh chemicals or secondary dopants. Vertical and planar OECTs are compared using various characterization methods. We show that vOECTs are superior platforms in general and propose that the vertical architecture can be expanded for the realization of OECTs for various applications.

NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions.

Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain-machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created "NeuroRoots," a biomimetic multi-channel implant with similar dimensions (7 µm wide and 1.5 µm thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode "roots," each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum in vitro and in vivo. NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain-machine interfacing.

Investigating the electrode-electrolyte interface modelling in cochlear implants.

OBJECTIVE: Proposing a good electrode-electrolyte interface (EEI) model and properly identifying relevant parameters may help designing safer and more optimized auditory nerve fiber stimulation and recording in cochlear implants (CI). However, in the literature EEI model parameter values exhibit large variability. We aim to explain some root causes of this variability using the Cole model and its simpler form, the Basic RC model. APPROACH: We use temporal and spectral methods and fit the models to stimulation pulse voltage response (SPVR) and electrochemical impedance spectroscopy (EIS) data. MAIN RESULTS: Temporal fittings show that there are multiple sets of model parameters that provide a good fit to the SPVR data. Therefore, small methodological differences in literature may result in different model fits. While these models share similar characteristics at high frequencies >500 Hz, the SPVR fitting is blind to low frequencies, thus it cannot correctly estimate the Faradaic resistor. Similarly, the polarization capacitor and its fractional order are not estimated robustly (capacitor variations in the nano- to micro-farad range) due to limited observation of mid-range frequencies. EIS provides a good model fit down to ~3Hz, and thus robust estimation for the polarization capacitor. At lower frequencies charge mechanisms may modify the EEI, requiring multi-compartment Cole model fitting to EIS to improve the estimation of Faradaic characteristics. Our EIS data measurements down to 0.05Hz show that a two-compartment Cole model is sufficient to explain the data. SIGNIFICANCE: Our study describes the scope and limitation of SPVR and EIS fitting methods, by which literature variability is explained among CI EEI models. The estimation of mid-to-low-frequency characteristics of the CI EEI is not in the scope of the SPVR method. EIS provides a better fit; however, its results should not be extrapolated to unobserved frequencies where new charge transfer mechanisms may emerge at the EEI.

Downsizing the Channel Length of Vertical Organic Electrochemical Transistors.

Organic electrochemical transistors (OECTs) are promising building blocks for bioelectronic devices such as sensors and neural interfaces. While the majority of OECTs use simple planar geometry, there is interest in exploring how these devices operate with much shorter channels on the submicron scale. Here, we show a practical route toward the minimization of the channel length of the transistor using traditional photolithography, enabling large-scale utilization. We describe the fabrication of such transistors using two types of conducting polymers. First, commercial solution-processed poly(dioxyethylenethiophene):poly(styrene sulfonate), PEDOT:PSS. Next, we also exploit the short channel length to support easy in situ electropolymerization of poly(dioxyethylenethiophene):tetrabutyl ammonium hexafluorophosphate, PEDOT:PF6. Both variants show different promising features, leading the way in terms of transconductance (gm), with the measured peak gm up to 68 mS for relatively thin (280 nm) channel layers on devices with the channel length of 350 nm and with widths of 50, 100, and 200 µm. This result suggests that the use of electropolymerized semiconductors, which can be easily customized, is viable with vertical geometry, as uniform and thin layers can be created. Spin-coated PEDOT:PSS lags behind with the lower values of gm; however, it excels in terms of the speed of the device and also has a comparably lower off current (300 nA), leading to unusually high on/off ratio, with values up to 8.6 × 104. Our approach to vertical gap devices is simple, scalable, and can be extended to other applications where small electrochemical channels are desired.

A Biologically Interfaced Evolvable Organic Pattern Classifier.

Future brain-computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can receive data from a sensor array, process these data into meaningful information, and translate that information into a format that can be interpreted by living systems. Here, the first example of interfacing a hardware-based pattern classifier with a biological nerve is reported. The classifier implements the Widrow-Hoff learning algorithm on an array of evolvable organic electrochemical transistors (EOECTs). The EOECTs' channel conductance is modulated in situ by electropolymerizing the semiconductor material within the channel, allowing for low voltage operation, high reproducibility, and an improvement in state retention by two orders of magnitude over state-of-the-art OECT devices. The organic classifier is interfaced with a biological nerve using an organic electrochemical spiking neuron to translate the classifier's output to a simulated action potential. The latter is then used to stimulate muscle contraction selectively based on the input pattern, thus paving the way for the development of adaptive neural interfaces for closed-loop therapeutic systems.

Obstructive sleep apnea improves with non-invasive hypoglossal nerve stimulation using temporal interference.

BACKGROUND: Peripheral nerve stimulation is used in both clinical and fundamental research for therapy and exploration. At present, non-invasive peripheral nerve stimulation still lacks the penetration depth to reach deep nerve targets and the stimulation focality to offer selectivity. It is therefore rarely employed as the primary selected nerve stimulation method. We have previously demonstrated that a new stimulation technique, temporal interference stimulation, can overcome depth and focality issues. METHODS: Here, we implement a novel form of temporal interference, bilateral temporal interference stimulation, for bilateral hypoglossal nerve stimulation in rodents and humans. Pairs of electrodes are placed alongside both hypoglossal nerves to stimulate them synchronously and thus decrease the stimulation amplitude required to activate hypoglossal-nerve-controlled tongue movement. RESULTS: Comparing bilateral temporal interference stimulation with unilateral temporal interference stimulation, we show that it can elicit the same behavioral and electrophysiological responses at a reduced stimulation amplitude. Traditional transcutaneous stimulation evokes no response with equivalent amplitudes of stimulation. CONCLUSIONS: During first-in-man studies, temporal interference stimulation was found to be well-tolerated, and to clinically reduce apnea-hypopnea events in a subgroup of female patients with obstructive sleep apnea. These results suggest a high clinical potential for the use of temporal interference in the treatment of obstructive sleep apnea and other diseases as a safe, effective, and patient-friendly approach. TRIAL REGISTRATION: The protocol was conducted with the agreement of the International Conference on Harmonisation Good Clinical Practice (ICH GCP), applicable United States Code of Federal Regulations (CFR) and followed the approved BRANY IRB File # 22-02-636-1279.

Metabolite-induced in vivo fabrication of substrate-free organic bioelectronics.

Interfacing electronics with neural tissue is crucial for understanding complex biological functions, but conventional bioelectronics consist of rigid electrodes fundamentally incompatible with living systems. The difference between static solid-state electronics and dynamic biological matter makes seamless integration of the two challenging. To address this incompatibility, we developed a method to dynamically create soft substrate-free conducting materials within the biological environment. We demonstrate in vivo electrode formation in zebrafish and leech models, using endogenous metabolites to trigger enzymatic polymerization of organic precursors within an injectable gel, thereby forming conducting polymer gels with long-range conductivity. This approach can be used to target specific biological substructures and is suitable for nerve stimulation, paving the way for fully integrated, in vivo-fabricated electronics within the nervous system.

Virtual audiometric testing using smartphone mobile applications to detect hearing loss.

Objective: The COVID-19 pandemic drove the need for remote audiometric testing in the form of mobile applications for hearing assessment. This study sought to determine the accuracy of two smartphone-based hearing assessment applications, Mimi and uHear, against the gold standard of in-clinic audiometric testing. Methods: One hundred patients that presented to clinic for hearing assessment were randomly assigned to take either the Mimi or uHear hearing test alongside standard audiometric testing. Hearing thresholds measured using mobile applications were compared to those from audiometric testing to assess validity. Patient satisfaction was measured using a questionnaire that queried if the app met the user's need, if they would recommend the app to others, and how likely they were to use the app again. Results: Using Mimi, there were no differences in average hearing levels measured at any frequency when compared to standard audiometric testing. uHear overestimated hearing loss at 500 and 1000 Hz (p < .001 for both) by 5-10 Hz, and underestimated hearing loss at 6000 Hz (p < .001) by 5-10 Hz compared to standard audiometric testing. When stratified by level of hearing impairment, uHear overestimated impairment in those with normal hearing (p < .001). Mimi had higher sensitivity (0.971) and specificity (0.912) for hearing loss (defined as a pure tone average for 500, 1000, 2000, and 4000 Hz greater than 25 dB) than uHear (0.914 and 0.780, respectively). However, uHear outranked Mimi on all three questions in the satisfaction questionnaire (p = .01, p = .03, and p = .02, respectively). Conclusion: Mimi appears to be a reasonable substitute for standard audiometric testing when individuals cannot present to clinic for gold standard testing; however, the Mimi user experience can be improved. Level of evidence: Level II.