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Neural interfaces are crucial conduits between neural tissues and external devices, enabling the recording and modulation of neural activity. However, with increasing demand, simple neural interfaces are no longer adequate to meet the requirements for precision, functionality, and safety. There are three main challenges in fabricating advanced neural interfaces: sensitivity, heat management, and biocompatibility. The electrical, chemical, and optical properties of 2D nanomaterials enhance the sensitivity of various types of neural interfaces, while the newly developed interfaces do not exhibit adverse reactions in terms of heat management and biocompatibility. Additionally, 2D nanomaterials can further improve the functionality of these interfaces, including magnetic resonance imaging (MRI) compatibility, stretchability, and drug delivery. In this review, we examine the recent applications of 2D nanomaterials in neural interfaces, focusing on their contributions to enhancing performance and functionality. Finally, we summarize the advantages and disadvantages of these nanomaterials, analyze the importance of biocompatibility testing for 2D nanomaterials, and propose that improving and developing composite material structures to enhance interface performance will continue to lead the forefront of this field.

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Peripheral neural interfaces facilitate bidirectional communication between the nervous system and external devices, enabling precise control for prosthetic limbs, sensory feedback systems, and therapeutic interventions in the field of Bioelectronic Medicine. Intraneural interfaces hold great promise since they ensure high selectivity in communicating only with the desired nerve fascicles. Despite significant advancements, challenges such as chronic immune response, signal degradation over time, and lack of long-term biocompatibility remain critical considerations in the development of such devices. Here we report on the development and benchtop characterization of a novel design of an intraneural interface based on carbon fiber bundles. Carbon fibers possess low impedance, enabling enhanced signal detection and stimulation efficacy compared to traditional metal electrodes. We provided a 3D-stabilizing structure for the carbon fiber bundles made of PEDOT:PSS hydrogel, to enhance the biocompatibility between the carbon fibers and the nervous tissue. We further coated the overall bundles with a thin layer of elastomeric material to provide electrical insulation. Taken together, our results demonstrated that our electrode possesses adequate structural and electrochemical properties to ensure proper stimulation and recording of peripheral nerve fibers and a biocompatible interface with the nervous tissue.

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Recent advancements in nano- and microfabrication techniques have led to the development of highly biomimetic patterned substrates able to guide neuronal sprouting, routing, elongation, and branching. Such substrates, recapitulating shapes and geometries found in the native brain, may pave the way toward the development of cell instructive paradigms able to guide morphogenesis at the neuron-material interface. In this scenario, high-resolution electron microscopy approaches, owing to their ability of discerning the details of neural morphogenesis at a nanoscale resolution, may play a crucial role in unravelling the fine ultrastructure of neurons interfacing with biomimetic structured substrates.

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Organic electrochemical transistors (OECTs) have emerged as powerful tools for biosignal amplification, including electrocorticography (ECoG). However, their widespread application has been limited by the complexities associated with existing fabrication techniques, restricting accessibility and scalability. Here, we introduce a novel all-planar, all-printed high-performance OECT device that significantly enhances the accuracy and sensitivity of ECoG recordings. Achieved through an innovative three-step drop-on-demand inkjet printing process on flexible substrates, our device offers a rapid response time of 0.5 ms, a compact channel area of 1950 µm2, and is characterized by a transconductance of 11 mS. This process not only simplifies integration but also reduces costs. Our optimized in-plane gate voltage control facilitates operation at peak transconductance, which elevates the signal-to-noise ratio (SNR) by up to 133%. In vivo evaluations in a rat model of seizure demonstrate the device's performance in recording distinct electrographic phases, surpassing the capabilities of PEDOT:PSS-coated gold-based ultralow impedance passive electrodes, achieving a high SNR of 48 db. Our results underscore the potential of Inkjet-printed OECTs in advancing the accessibility and accuracy of diagnostic tools that could enhance patient care by facilitating timely detection of neurological conditions.

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Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a loss of generalizability across broad neural interfaces. To address this, this paper proposes a highly scalable, programmable neurostimulator with a System-on-Chip (SOC) capable of 32 channels of independent stimulation. The compliance voltage reaches up to ±22.5 V. A pair of 8-bit current-mode DACs support independent waveforms for source and sink operations and feature a user-selectable dual range for low-current intraparenchymal microstimulation with a resolution of 4.31 µA/bit, as well as high current stimulation for spinal cord and DBS applications with a resolution of 48.00 µA/bit, achieving a wide stimulation range of 12.24 mA while maintaining high-resolution biological stimulation. A dedicated communication protocol enables full programmable control of stimulation waveforms, effectively improving the range of stimulation parameters. In vivo electrophysiological experiments successfully validate the functionality of the proposed stimulator. This flexible stimulator architecture aims to enhance its generality across a wide range of neural interfaces and will provide more diverse and refined stimulation strategies.

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Durable and conductive interfaces that enable chronic and high-resolution recording of neural activity are essential for understanding and treating neurodegenerative disorders. These chronic implants require long-term stability and small contact areas. Consequently, they are often coated with a blend of conductive polymers and are crosslinked to enhance durability despite the potentially deleterious effect of crosslinking on the mechanical and electrical properties. Here the grafting of the poly(3,4 ethylenedioxythiophene) scaffold, poly(styrenesulfonate)-b-poly(poly(ethylene glycol) methyl ether methacrylate block copolymer brush to gold, in a controlled and tunable manner, by surface-initiated atom-transfer radical polymerization (SI-ATRP) is described. This "block-brush" provides high volumetric capacitance (120 F cm─3), strong adhesion to the metal (4 h ultrasonication), improved surface hydrophilicity, and stability against 10 000 charge-discharge voltage sweeps on a multiarray neural electrode. In addition, the block-brush film showed 33% improved stability against current pulsing. This approach can open numerous avenues for exploring specialized polymer brushes for bioelectronics research and application.

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Cochlear implants can directly activate the auditory system's primary sensory neurons, the spiral ganglion neurons (SGNs), via circumvention of defective cochlear hair cells. This bypass restores auditory input to the brainstem. SGN loss etiologies are complex, with limited mammalian regeneration. Protecting and revitalizing SGN is critical. Tissue engineering offers a novel therapeutic strategy, utilizing seed cells, biomolecules, and scaffold materials to create a cellular environment and regulate molecular cues. This review encapsulates the spectrum of both human and animal research, collating the factors contributing to SGN loss, the latest advancements in the utilization of exogenous stem cells for auditory nerve repair and preservation, the taxonomy and mechanism of action of standard biomolecules, and the architectural components of scaffold materials tailored for the inner ear. Furthermore, we delineate the potential and benefits of the biohybrid neural interface, an incipient technology in the realm of implantable devices. Nonetheless, tissue engineering requires refined cell selection and differentiation protocols for consistent SGN quality. In addition, strategies to improve stem cell survival, scaffold biocompatibility, and molecular cue timing are essential for biohybrid neural interface integration.

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In recent years, in vitro three-dimensional (3D) neuronal network models utilizing extracellular matrices have been advancing. To understand the network activity from these models, attempts have been made to measure activity in multiple regions simultaneously using a microelectrode array (MEA). Although there hve been many attempts to measure the activity of 3D networks using 2-dimensional (2D) MEAs, the physical coupling between the 3D network and the microelectrodes was not stable and needed to be improved. In this study, we proposed a neuronal cluster interface that improves the active channel ratio of commercial 2D MEAs, enabling reliable measurement of 3D network activity. To achieve this, neuronal clusters, which consist of a small number of neurons, were patterned on microelectrodes and used as mediators to transmit the signal between the 3D network and the microelectrodes. We confirmed that the patterned neuronal clusters enhanced the active channel ratio and SNR(signal-to-noise-ratio) about 3D network recording and stimulation for a month. Our interface was able to functionally connect with 3D networks and measure the 3D network activity without significant alternation of activity characteristics. Finally, we demonstrated that our interface can be used to analyze the differences in the dynamics of 3D and 2D networks and to construct the 3D clustered network. This method is expected to be useful for studying the functional activity of various 3D neuronal network models, offering broad applications for the use of these models.

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Understanding brain function is essential for advancing our comprehension of human cognition, behavior, and neurological disorders. Magnetic resonance imaging (MRI) stands out as a powerful tool for exploring brain function, providing detailed insights into its structure and physiology. Combining MRI technology with electrophysiological recording system can enhance the comprehension of brain functionality through synergistic effects. However, the integration of neural implants with MRI technology presents challenges because of its strong electromagnetic (EM) energy during MRI scans. Therefore, MRI-compatible neural implants should facilitate detailed investigation of neural activities and brain functions in real-time in high resolution, without compromising patient safety and imaging quality. Here, we introduce the fully MRI-compatible monolayer open-mesh pristine PEDOT:PSS neural interface. This approach addresses the challenges encountered while using traditional metal-based electrodes in the MRI environment such as induced heat or imaging artifacts. PEDOT:PSS has a diamagnetic property with low electrical conductivity and negative magnetic susceptibility similar to human tissues. Furthermore, by adopting the optimized open-mesh structure, the induced currents generated by EM energy are significantly diminished, leading to optimized MRI compatibility. Through simulations and experiments, our PEDOT:PSS-based open-mesh electrodes showed improved performance in reducing heat generation and eliminating imaging artifacts in an MRI environment. The electrophysiological recording capability was also validated by measuring the local field potential (LFP) from the somatosensory cortex with an in vivo experiment. The development of neural implants with maximized MRI compatibility indicates the possibility of potential tools for future neural diagnostics.

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Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the nervous system and ensures a stable interface with nervous tissue, facilitating autonomous neural adaptation. Herein, we present a novel neural interface platform that modulates the peripheral nervous system using flexible nerve electrodes and advanced neuromodulation techniques. Specifically, we have developed a surface-based inverse recruitment model for effective joint position control via direct electrical nerve stimulation. Utilizing barycentric coordinates, this model constructs a three-dimensional framework that accurately interpolates inverse isometric recruitment values across various joint positions, thereby enhancing control stability during stimulation. Experimental results from rabbit ankle joint control trials demonstrate our model's effectiveness. In combination with a proportional-integral-derivative (PID) controller, it shows superior performance by achieving reduced settling time (less than 1.63 s), faster rising time (less than 0.39 s), and smaller steady-state error (less than 3 degrees) compared to the legacy model. Moreover, the model's compatibility with recent advances in flexible interfacing technologies and its integration into a closed-loop controlled functional neuromuscular stimulation (FNS) system highlight its potential for precise neuroprosthetic applications in joint position control. This approach marks a significant advancement in the management of neurological disorders with advanced neuroprosthetic solutions.

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Neuralink is a neurotechnology company founded by Elon Musk in 2016, which has been quietly developing revolutionary technology allowing for ultra-high precision bidirectional communication between external devices and the brain. In this paper, we explore the multifaceted ethical considerations surrounding neural interfaces, analyzing potential societal impacts, risks, and call for a need for responsible innovation. Despite the technological, medical, medicolegal, and ethical challenges ahead, neural interface technology remains extremely promising and has the potential to create a new era of medicine.

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Emerging therapies in bioelectronic medicine highlight the need for deeper understanding of electrode material performance in the context of tissue stimulation. Electrochemical properties are characterized on the benchtop, facilitating standardization across experiments. On-nerve electrochemistry differs from benchtop characterization and the relationship between electrochemical performance and nerve activation thresholds are not commonly established. This relationship is important in understanding differences between electrical stimulation requirements and electrode performance. We report functional electrochemistry as a follow-up to benchtop testing, describing a novel experimental approach for evaluating on-nerve electrochemical performance in the context of nerve activation. An ex-vivo rat sciatic nerve preparation was developed to quantify activation thresholds of fiber subtypes and electrode material charge injection limits for platinum iridium, iridium oxide, titanium nitride and PEDOT. Finally, we address experimental complexities arising in these studies, and demonstrate statistical solutions that support rigorous material performance comparisons for decision making in neural interface development.

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The paralysis of the muscles controlling the hand dramatically limits the quality of life of individuals living with spinal cord injury (SCI). Here, with a non-invasive neural interface, we demonstrate that eight motor complete SCI individuals (C5-C6) are still able to task-modulate in real-time the activity of populations of spinal motor neurons with residual neural pathways. In all SCI participants tested, we identified groups of motor units under voluntary control that encoded various hand movements. The motor unit discharges were mapped into more than 10 degrees of freedom, ranging from grasping to individual hand-digit flexion and extension. We then mapped the neural dynamics into a real-time controlled virtual hand. The SCI participants were able to match the cue hand posture by proportionally controlling four degrees of freedom (opening and closing the hand and index flexion/extension). These results demonstrate that wearable muscle sensors provide access to spared motor neurons that are fully under voluntary control in complete cervical SCI individuals. This non-invasive neural interface allows the investigation of motor neuron changes after the injury and has the potential to promote movement restoration when integrated with assistive devices.

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Objective.This study aims to develop and validate a sophisticated fork-shaped neural interface (FNI) designed for peripheral nerves, focusing on achieving high spatial resolution, functional selectivity, and improved charge storage capacities. The objective is to create a neurointerface capable of precise neuroanatomical analysis, neural signal recording, and stimulation.Approach.Our approach involves the design and implementation of the FNI, which integrates 32 multichannel working electrodes featuring enhanced charge storage capacities and low impedance. An insertion guide holder is incorporated to refine neuronal selectivity. The study employs meticulous electrode placement, bipolar electrical stimulation, and comprehensive analysis of induced neural responses to verify the FNI's capabilities. Stability over an eight-week period is a crucial aspect, ensuring the reliability and durability of the neural interface.Main results.The FNI demonstrated remarkable efficacy in neuroanatomical analysis, exhibiting accurate positioning of motor nerves and successfully inducing various movements. Stable impedance values were maintained over the eight-week period, affirming the durability of the FNI. Additionally, the neural interface proved effective in recording sensory signals from different hind limb areas. The advanced charge storage capacities and low impedance contribute to the FNI's robust performance, establishing its potential for prolonged use.Significance.This research represents a significant advancement in neural interface technology, offering a versatile tool with broad applications in neuroscience and neuroengineering. The FNI's ability to capture both motor and sensory neural activity positions it as a comprehensive solution for neuroanatomical studies. Moreover, the precise neuromodulation potential of the FNI holds promise for applications in advanced bionic prosthetic control and therapeutic interventions. The study's findings contribute to the evolving field of neuroengineering, paving the way for enhanced understanding and manipulation of peripheral neural functions.

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Objective. Chronopotentiometric voltage transients (VTs) are used to assess the performance of bionic electrodes. The data obtained from VTs are used to define the safe operating conditions of clinical devices. Various approaches to analysing VTs have been reported, and a number of limitations in the accuracy of the measurements in relation to electrode size have been noted previously.Approach. The impact of electronic hardware and electrode configuration on VTs is discussed.Main results. The slew rate, rise time, sample time, minimum pulse length and waveform averaging characteristics of the electronic hardware, and electrode configuration will impact on VT measurement accuracy. Subsequently, activation and polarisation voltage measurements, and the definition of safe stimulation levels can be affected by the electronic hardware and electrode configuration.Significance. This article has identified some limitations in the previous literature related to the measurement and reporting of VTs and subsequent analysis of access and polarisation voltages. Furthermore, the commonly used Shannon plot used to define safe stimulation protocols does not correct for uncompensated resistance, account for electrode roughness or changes in electrode configuration. The creation of a safe stimulation plot which has been corrected for uncompensated resistance would generate more widely applicable stimulation guidelines for clinical devices used in different anatomical locations such as endovascular neural interfaces.

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Objective. Bi-directional electronic neural interfaces, capable of both electrical recording and stimulation, communicate with the nervous system to permit precise calibration of electrical inputs by capturing the evoked neural responses. However, one significant challenge is that stimulation artifacts often mask the actual neural signals. To address this issue, we introduce a novel approach that employs dynamical control systems to detect and decipher electrically evoked neural activity despite the presence of electrical artifacts.Approach. Our proposed method leverages the unique spatiotemporal patterns of neural activity and electrical artifacts to distinguish and identify individual neural spikes. We designed distinctive dynamical models for both the stimulation artifact and each neuron observed during spontaneous neural activity. We can estimate which neurons were active by analyzing the recorded voltage responses across multiple electrodes post-stimulation. This technique also allows us to exclude signals from electrodes heavily affected by stimulation artifacts, such as the stimulating electrode itself, yet still accurately differentiate between evoked spikes and electrical artifacts.Main results. We applied our method to high-density multi-electrode recordings from the primate retina in anex vivosetup, using a grid of 512 electrodes. Through repeated electrical stimulations at varying amplitudes, we were able to construct activation curves for each neuron. The curves obtained with our method closely resembled those derived from manual spike sorting. Additionally, the stimulation thresholds we estimated strongly agreed with those determined through manual analysis, demonstrating high reliability (R2=0.951for human 1 andR2=0.944for human 2).Significance. Our method can effectively separate evoked neural spikes from stimulation artifacts by exploiting the distinct spatiotemporal propagation patterns captured by a dense, large-scale multi-electrode array. This technique holds promise for future applications in real-time closed-loop stimulation systems and for managing multi-channel stimulation strategies.

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Advancements in neural interface technologies have enabled the direct connection of neurons and electronics, facilitating chemical communication between neural systems and external devices. One promising approach is a synaptogenesis-involving method, which offers an opportunity for synaptic signaling between these systems. Janus synapses, one type of synaptic interface utilizing synaptic cell adhesion molecules for interface construction, possess unique features that enable the determination of location, direction of signal flow, and types of neurotransmitters involved, promoting directional and multifaceted communication. This study presents the first successful establishment of a Janus synapse between dopaminergic (DA) neurons and abiotic substrates by using a neuroligin-2 (NLG2)-mediated synapse-inducing method. NLG2 immobilized on gold-coated microspheres can induce synaptogenesis upon contact with spatially isolated DA axons. The induced DA Janus synapses exhibit stable synaptic activities comparable to that of native synapses over time, suggesting their suitability for application in neural interfaces. By calling for DA presynaptic organizations, the NLG2-immobilized abiotic substrate is a promising tool for the on-site detection of synaptic dopamine release.

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With the lack of minimally invasive tools for probing neuronal systems across spatiotemporal scales, understanding the working mechanism of the nervous system and limited assessments available are imperative to prevent or treat neurological disorders. In particular, nanoengineered neural interfaces can provide a solution to this technological barrier. This review covers recent surface engineering approaches, including nanoscale surface coatings, and a range of topographies from the microscale to the nanoscale, primarily focusing on neural-interfaced biosystems. Specifically, the immobilization of bioactive molecules to fertilize the neural cell lineage, topographical engineering to induce mechanotransduction in neural cells, and enhanced cell-chip coupling using three-dimensional structured surfaces are highlighted. Advances in neural interface design will help us understand the nervous system, thereby achieving the effective treatments for neurological disorders. STATEMENT OF SIGNIFICANCE: • This review focuses on designing bioactive neural interface with a nanoscale chemical modification and topographical engineering at multiscale perspective. • Versatile nanoscale surface coatings and topographies for neural interface are summarized. • Recent advances in bioactive materials applicable for neural cell culture, electrophysiological sensing, and neural implants are reviewed.

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Modern implantable bioelectronics demand soft, biocompatible components that make robust, low-impedance connections with the body and circuit elements. Concurrently, such technologies must demonstrate high efficiency, with the ability to interface between the body's ionic and external electronic charge carriers. Here, a mixed-conducting suture, the e-suture, is presented. Composed of silk, the conducting polymer poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), and insulating jacketing polymers,the resulting e-suture has mixed-conducting properties at the interface with biological tissue as well as effective insulation along its length. The e-suture can be mechanically integrated into electronics, enabling the acquisition of biopotentials such as electrocardiograms, electromyograms, and local field potentials (LFP). Chronic, in vivo acquisition of LFP with e-sutures remains stable for months with robust brain activity patterns. Furthermore, e-sutures can establish electrophoretic-based local drug delivery, potentially offering enhanced anatomical targeting and decreased side effects associated with systemic administration, while maintaining an electrically conducting interface for biopotential monitoring. E-sutures expand on the conventional role of sutures and wires by providing a soft, biocompatible, and mechanically sound structure that additionally has multifunctional capacity for sensing, stimulation, and drug delivery.