Neural Interface Technologies Research Articles

Glassy Carbon Fiber‐Like Multielectrode Arrays for Neurochemical Sensing and Electrophysiology Recording

AbstractReal‐time measurement of neurochemical and electrophysiological activities in the living brain is vital for advancing neuroscience and understanding brain disorders. Carbon fiber microelectrodes (CFEs) have been widely utilized for in vivo electrochemical detection due to their subcellular size, biocompatibility, and desirable electrochemical properties, and CFE arrays have demonstrated excellent multi‐site chronic sensing of dopamine (DA) and neural activity recording capabilities. However, manual fabrication of CFE arrays lacks reproducibility and batch production capacity. Alternatively, photolithography enables batch fabrication of glassy carbon (GC) multielectrode arrays (GC‐MEAs) with high resolution and reproducibility, but the insertion of planar flexible MEAs poses challenges. In this study, GC fiber‐like (GCF) MEAs are presented and fabricated using photolithography. The GCF MEAs feature fiber‐like GC electrodes with small cross‐sections, facilitating self‐insertion into brain tissue without additional aids. Batch fabrication of GCF MEAs allows for customizable designs with minimal manual intervention. Comparative analysis with CFEs demonstrates improved electrochemical properties of GCF. In vivo experiments in mouse brains confirm the GCF MEAs' ability to measure neurotransmitter concentrations and record neural activities. This novel fabrication approach is promising for multimodal electrical and chemical measurements with minimal footprint, offering significant advancements in neural interface technology for neuroscience research and clinical applications.

Liquid metal neuro-electrical interface

Liquid metal (LM), an emerging functional material, plays increasing roles in biomedical and healthcare areas. It has particular values in neural interfaces as it combines high conductivity, flowability, and biocompatibility properties. Neuro-electrical interfaces (NEIs) are effective tools to provide a bridge between the nervous system and the outside world. The main target of developing neural interfaces is to help disabled people repair damaged nerves and enhance human capacity above normal ability. This article systematically summarizes LM-based neural interface technologies, including neural electrodes for electrical signal acquisition and administration of electrical stimulation and nerve guidance conduits for neural connectivity and functional reconstruction. The discussion begins with an overview of the fundamental properties associated with LM materials involved in the field of neural interface applications. The fabrication methods of LM-based neuro-electrodes and conduits are then introduced, and the current development status of LM-based neuro-electrodes and conduits is elaborated. Finally, the prospects and possible challenges of LM-based neural interfaces are outlined.

Multichannel microneedle dry electrode patches for minimally invasive transdermal recording of electrophysiological signals

The collection of multiple-channel electrophysiological signals enables a comprehensive understanding of the spatial distribution and temporal features of electrophysiological activities. This approach can help to distinguish the traits and patterns of different ailments to enhance diagnostic accuracy. Microneedle array electrodes, which can penetrate skin without pain, can lessen the impedance between the electrodes and skin; however, current microneedle methods are limited to single channels and cannot achieve multichannel collection in small areas. Here, a multichannel (32 channels) microneedle dry electrode patch device was developed via a dimensionality reduction fabrication and integration approach and supported by a self-developed circuit system to record weak electrophysiological signals, including electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG) signals. The microneedles reduced the electrode–skin contact impedance by penetrating the nonconducting stratum corneum in a painless way. The multichannel microneedle array (MMA) enabled painless transdermal recording of multichannel electrophysiological signals from the subcutaneous space, with high temporal and spatial resolution, reaching the level of a single microneedle in terms of signal precision. The MMA demonstrated the detection of the spatial distribution of ECG, EMG and EEG signals in live rabbit models, and the microneedle electrode (MNE) achieved better signal quality in the transcutaneous detection of EEG signals than did the conventional flat dry electrode array. This work offers a promising opportunity to develop advanced tools for neural interface technology and electrophysiological recording.

The potential to restore vision with Neuralink’s “Blindsight” neural interface technology

The potential to restore vision with Neuralink’s “Blindsight” neural interface technology

Fork-shaped neural interface with multichannel high spatial selectivity in the peripheral nerve of a rat

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.

Neural rehabilitation based on brain computer interface

BCI is a newly developed technology that can be used for neurological rehabilitation of brain injuries and paralysis. This article first reviews the history of BCI, and then introduces two major neurorehabilitation BCI technologies for neurorecording and neuromodulation, invasive and non-invasive. For each technology, we describe the challenges of each technology, analyzing the current state and future development trends. In terms of non-invasive technology, the most mature and extensive EEG brain signal analysis methods and two brain regulation technologies, transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), as well as the application of brain signal analysis techniques such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy fNIRS) were also discussed. In terms of invasive technology, the implantable neural interface technology focuses on implantable neural interface technology, which collects cortical electrical brain signals (ECoG), which can obtain more original neural information and has high temporal and spatial resolution characteristics. In recent years, with the development of microelectronics technology and material technology, invasive BCI technology has made a lot of cutting-edge progress, which is an important future development direction of neurorehabilitation technology.

On-Site Formation of Functional Dopaminergic Presynaptic Terminals on Neuroligin-2-Modified Gold-Coated Microspheres.

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.

A Review on Biomaterials for Neural Interfaces: Enhancing Brain-Machine Interfaces

Biomaterials are essential to the development of neural interfaces, including brainmachine interfaces. Biomaterial methods improve neural interface functionality, compatibility, and longevity, enabling brain-device communication. An extensive investigation of biomaterials utilized in brain electrode arrays, neural probes, & implantable devices rely on how materials affect neural signals recording, stimulation, & tissue contact. It also investigates how biomaterials, bioelectronics and 3D printing could improve neural interfaces. Biomaterials modulate neuroinflammatory responses, enhance brain tissue regeneration, and promote neural interface longevity. This study shows the potential for change of biomaterial-based neural interfaces in neuroprosthetics, neurological rehabilitation, and fundamental neuroscience research, addressing the need for brain-machine relationship and neurotechnology innovation. These findings suggest expanding biomaterials research and development to advance and sustain neural interface technologies for future use.

Neural interface technology for human-computer interaction

The Brain-Computer Interface (BCI) is a highly promising way to establish a direct link between the human brain and external computerised apparatus, enabling individuals with severe disabilities to interact with their external environment. By harnessing BCI technology, these individuals can exert control over specific computerized devices, ranging from computers and wheelchairs to neural prosthetics, thus facilitating meaningful interaction with the world around them. However, while BCI technology holds immense potential, several aspects remain in conceptual stages or are constrained by specific circumstances. This review offers a comprehensive exploration of the fundamental principles governing BCI classification. It also provides an overview of applications that BCI has to offer and its multifaceted utility, particularly in the application of neuroprostheses, in conjunction with FES, and in the rehabilitation of stroke and epilepsy. The review navigates through the landscape of BCI application technologies, elucidating their challenges, and constraints. After analyses, potential developments in BCI technology were identified, and possible future challenges were highlighted.

Neural interface technology for human-computer interaction

Brain-Computer Interfaces (BCI) offer a direct communication channel between the brain and external devices, marking a pivotal convergence of neuroscience and technology. Neural activities, essentially electrical impulses, can be captured either invasively, with methods such as Electrocorticography (ECoG) which require surgical implantation, or non-invasively using techniques like Electroencephalography (EEG) that operate externally. Once acquired, raw neural data undergoes processing; external and physiological noises are filtered out, and meaningful patterns or neural fingerprints are extracted. Modern BCIs then employ machine learning, specifically deep learning, to translate these cleaned neural patterns into discernible commands, with continuous feedback loops enhancing system adaptability. These decoded signals can control varied devices, from medical-grade robotic limbs to cursors on screens. BCIs have transformative applications across sectors: theyre pivotal in neurorehabilitation after brain injuries, providing feedback where traditional methods might fail; theyre integrated with virtual reality for immersive feedback; they revolutionize cognitive training and meditation practices; and theyre finding a foothold in high-risk sectors like deep-sea exploration and military operations. Additionally, research on tactile Event-Related Potential (ERP)-based BCIs emphasizes the importance of congruent Control-Display Mapping for efficient user experience. However, with these advancements come ethical concerns, such as the potential invasion of the privacy of ones thoughts, challenges to human identity and autonomy, societal disparities in access, and health implications.

A Self-powered Neural Stimulator Based on Programmable Triboelectric Nanogenerators.

Modulation of peripheral nerve is an emerging field for neuroprosthesis and bioelectronic medicine. With the developing neural interfacing technology that directly communicates with peripheral nerves, several powering schemes have been investigated for long-term use of implantable devices such as wireless and conversion of human body energy. But due to the limitations such as energy conversion efficiency and complexity, none of these methods can fully replace the current battery-based neuroprosthetic systems. This study proposes a new scheme based on programmable triboelectric nanogenerators for self-powered neural stimulations. The device can generate current pulses of more than 100 V by slightly shaking the device. The capability of neural stimulation is validated by sciatic nerve stimulation. Furthermore, the shaking frequency can control the measured kicking force of the rat leg. This prototype can be further minimized and optimized for a fully implantable self-powered/wireless neuroprosthetic system.

A Real-Time Non-Implantation Bi-Directional Brain-Computer Interface Solution without Stimulation Artifacts.

The non-implantation bi-directional brain-computer interface (BCI) is a neural interface technology that enables direct two-way communication between the brain and the external world by both "reading" neural signals and "writing" stimulation patterns to the brain. This technology has vast potential applications, such as improving the quality of life for individuals with neurological and mental illnesses and even expanding the boundaries of human capabilities. Nonetheless, non-implantation bi-directional BCIs face challenges in generating real-time feedback and achieving compatibility between stimulation and recording. These issues arise due to the considerable overlap between electrical stimulation frequencies and electrophysiological recording frequencies, as well as the impediment caused by the skull to the interaction of external and internal currents. To address those challenges, this work proposes a novel solution that combines the temporal interference stimulation paradigm and minimally invasive skull modification. A longitudinal animal experiment has preliminarily validated the feasibility of the proposed method. In signal recording experiments, the average impedance of our scheme decreased by 4.59 kΩ, about 67%, compared to the conventional technique at 18 points. The peak-to-peak value of the Somatosensory Evoked Potential increased by 8%. Meanwhile, the signal-to-noise ratio of Steady-State Visual Evoked Potential increased by 5.13 dB, and its classification accuracy increased by 44%. The maximum bandwidth of the resting state rose by 63%. In electrical stimulation experiments, the signal-to-noise ratio of the low-frequency response evoked by our scheme rose by 8.04 dB, and no stimulation artifacts were generated. The experimental results show that signal quality in acquisition has significantly improved, and frequency-band isolation eliminates stimulation artifacts at the source. The acquisition and stimulation pathways are real-time compatible in this non-implantation bi-directional BCI solution, which can provide technical support and theoretical guidance for creating closed-loop adaptive systems coupled with particular application scenarios in the future.

A-IGZO thin-film transistors with transparent ultrathin Al/Ag bilayer source and drain for active neural interfaces

Electro-optical neural interface technologies based on transparent electronics have been developed to take advantage of both high spatial resolution of optical cellular imaging by microscopes and high temporal resolution of electrical neural recordings. Recently, active-matrix systems based on amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFTs) have been suggested for high-density electrical neural recordings owing to the high mobility and optical transparency of the IGZO. However, conventional metallic source and drain electrodes forming ohmic contacts with the a-IGZO are the limiting factors of the overall system transparency because the electrodes have substantial portions in the TFT structures. In this work, we propose an ultrathin metal bilayer as the transparent source and drain electrodes of the a-IGZO TFTs for fully transparent TFT-based electro-optical neural interfaces. The ultrathin metal bilayer electrodes consist of 2.5–4.5 nm-thick aluminum as a seed layer and 8 nm-thick silver. The ultrathin Al/Ag bilayer suppressed localized surface plasmonic resonance, showing 40–70% of transmittance in the range of 350–700 nm and thus allowing us to observe cultured neurons through the transparent electrodes. We also confirmed that the ultrathin Al/Ag electrodes form decent ohmic contacts to the IGZO, showing width-normalized contact resistance of 2.9 kΩ-cm which is similar to the previously reported other transparent S/D electrodes. The a-IGZO TFTs with the ultrathin Al/Ag showed the highest linear mobility of 3.9 cm2/Vs of in long channels and 0.2–0.64 cm2/Vs in short channels. The gate-bias normalized cut-off frequency was 8–26 kHz/V at Lch = 20 μm, which would be sufficient for recording a wide range of neural signals.

A 0.00426 mm2 77.6-dB Dynamic Range VCO-Based CTDSM for Multi-Channel Neural Recording

Driven by needs in neuroscientific research, future neural interface technologies demand integrated circuits that can record a large number of channels of neural signals in parallel while maintaining a miniaturized physical form factor. Using conventional methods, it is challenging to reduce circuit area while maintaining the high dynamic range, low noise, and low power consumption required in the neural application. This paper proposes to address this challenge using a VCO-based continuous-time delta-sigma modulator (CTDSM) circuit, which can record and digitize neural signals directly without the need for front-end instrumentation amplifiers and anti-aliasing filters, which are limited by the abovementioned circuit-area performance tradeoff. Thanks to the multi-level quantization and intrinsic mismatch-shaping capabilities of the VCO-based approach, the proposed first-order CTDSM can achieve comparable electrical performance to a higher-order CTDSM while offering further area and power reductions. We prototyped the circuit in a 22-channel test chip and demonstrate, based on the chip measurement results, that the proposed modulator occupies an area of 0.00426 mm2 while achieving input-referred noise levels of 6.26 and 3.54 µVrms in the action potential (AP) and local field potential (LFP) bands, respectively. With a 77.6 dB wide-dynamic range, the noise and total harmonic distortion meet the requirements of a neural interface with up to 149 mVpp input AC amplitude or up to ±68 mV DC offsets. We also validated the feasibility of the circuit for multi-channel recording applications by examining the impact of cross-channel VCO oscillation interferences on the circuit noise performance. The experimental results demonstrate the proposed architecture is an excellent candidate to implement future multi-channel neural-recording interfaces.

Development of a Three-Dimensional Nerve Stretch Growth Device towards an Implantable Neural Interface.

Because of rising traumatic accidents and diseases, the number of patients suffering from nerve injury is increasing. Without effective rehabilitation therapy, the patients will get motor or sensory function losses or even a lifelong disability. As for amputees, neural interface technology can be used to splice nerves and electrical wires together in a way that allows them to control an artificial limb as if it was a natural extension of the body. However, the means the need for an autologous nerve to stimulate axonal regeneration and extension into target tissues, which are limited by the supply of donor nerves. Based on the principle of mechanical force regulating axon growth, in this paper, we developed a three-dimensional nerve stretch growth device for an implantable neural interface. The device consists of three motors controlled by single chip microcomputer and some mechanical parts. The stability and reliability of the device were tested. Then, we used neurons derived from human pluripotent stem cells by small chemical molecules to explore the optimal three-dimensional stretch culture parameters. Furthermore, we found that the axons were intact through 10 rotations per day and 1 mm of horizontal pulling per day. The results of this research will provide convenience for patients treated through an implantable neural interface.

In vivo spatiotemporal dynamics of astrocyte reactivity following neural electrode implantation

Brain computer interfaces (BCIs), including penetrating microelectrode arrays, enable both recording and stimulation of neural cells. However, device implantation inevitably causes injury to brain tissue and induces a foreign body response, leading to reduced recording performance and stimulation efficacy. Astrocytes in the healthy brain play multiple roles including regulating energy metabolism, homeostatic balance, transmission of neural signals, and neurovascular coupling. Following an insult to the brain, they are activated and gather around the site of injury. These reactive astrocytes have been regarded as one of the main contributors to the formation of a glial scar which affects the performance of microelectrode arrays. This study investigates the dynamics of astrocytes within the first 2 weeks after implantation of an intracortical microelectrode into the mouse brain using two-photon microscopy. From our observation astrocytes are highly dynamic during this period, exhibiting patterns of process extension, soma migration, morphological activation, and device encapsulation that are spatiotemporally distinct from other glial cells, such as microglia or oligodendrocyte precursor cells. This detailed characterization of astrocyte reactivity will help to better understand the tissue response to intracortical devices and lead to the development of more effective intervention strategies to improve the functional performance of neural interfacing technology.

Нейроинтерфейсы: обзор технологий и современные решения

The purpose of this study is to provide an overview of the current state of neural interface technology and to compare their various modern implementations with each other, highlighting their advantages and features. The article considers the essence of the concept of "neural interface", its purpose, disassembled the structure of this technology and the principles underlying it, as well as classification according to various criteria. Examples of areas of activity in which this technology is currently used or can potentially be applied in the future are given. In addition, the most commonly used modern solutions are collected and analyzed in order to identify the most promising option in terms of functionality and convenience of everyday use. It has been established that the Emotiv Epoc neural interface has the widest functionality with comfortable everyday wear. It was also concluded that the areas of application in which solutions based on neural interfaces currently show the best results are medical diagnostics and remote control of electronic devices, as evidenced by the large number of projects involving neural interfaces in this area and a large number of articles, dedicated to them.

In situ stability monitoring of platinum thin-film electrodes for neural interfaces in the presence of proteins.

The long-term stability of platinum electrodes is a key factor that determines the life-time of biomedical devices, such as implanted neural interfaces like brain stimulation or recording electrodes, cochlear implants, and biosensors. The downsizing of such devices relies on the usage of microfabricated thin-film electrodes. In order to determine and investigate the causal degradation processes for platinum electrodes, it is essential to use potential-controlled experiments, which allow selectable polarization of the electrode without exceeding the water stability window boundaries. Therefore, the surface processes and redox reactions occurring at the electrode are known at all times. In this study, we present the continuous in situ monitoring of platinum-based thin-film electrodes along their complete life cycle in neutral pH with and without the presence of proteins. The usage of chronoamperometry for electrode aging, monitoring of surface processes and the tracking of analyte redox processes, together with cyclic voltammetry to determine the complete amount of surface charge, allows a reliable quantification of fundamental degradation processes. We found that platinum dissolution is primarily driven by the formation and removal of Pt oxide. Despite the significantly lowered charge transfer, the presence of proteins did not prevent material loss or increase electrode lifetime. These results should be considered when interpreting results from current-controlled methods as typically used for neural interfaces. Clinical Relevance- All clinically relevant applications of microelectrodes, ranging from cell culture over diagnostics to in vivo use, involve the presence of proteins. Detailed and fundamental insight into electrode stability in the presence of proteins is therefore essential for successful clinical translation of neural interface technologies.

Closed-Loop Vagus Nerve Stimulation for the Treatment of Cardiovascular Diseases: State of the Art and Future Directions.

The autonomic nervous system exerts a fine beat-to-beat regulation of cardiovascular functions and is consequently involved in the onset and progression of many cardiovascular diseases (CVDs). Selective neuromodulation of the brain-heart axis with advanced neurotechnologies is an emerging approach to corroborate CVDs treatment when classical pharmacological agents show limited effectiveness. The vagus nerve is a major component of the cardiac neuroaxis, and vagus nerve stimulation (VNS) is a promising application to restore autonomic function under various pathological conditions. VNS has led to encouraging results in animal models of CVDs, but its translation to clinical practice has not been equally successful, calling for more investigation to optimize this technique. Herein we reviewed the state of the art of VNS for CVDs and discuss avenues for therapeutic optimization. Firstly, we provided a succinct description of cardiac vagal innervation anatomy and physiology and principles of VNS. Then, we examined the main clinical applications of VNS in CVDs and the related open challenges. Finally, we presented preclinical studies that aim at overcoming VNS limitations through optimization of anatomical targets, development of novel neural interface technologies, and design of efficient VNS closed-loop protocols.

High resolution ultrasonic neural modulation observed via in vivo two-photon calcium imaging

Neural modulation plays a major role in delineating the circuit mechanisms and serves as the cornerstone of neural interface technologies. Among the various modulation mechanisms, ultrasound enables noninvasive label-free deep access to mammalian brain tissue. To date, most if not all ultrasonic neural modulation implementations are based on ∼1 MHz carrier frequency. The long acoustic wavelength results in a spatially coarse modulation zone, often spanning over multiple function regions. The modulation of one function region is inevitably linked with the modulation of its neighboring regions. Moreover, the lack of in vivo cellular resolution cell-type-specific recording capabilities in most studies prevents the revealing of the genuine cellular response to ultrasound. To significantly increase the spatial resolution, we explored the application of high-frequency ultrasound. To investigate the neuronal response at cellular resolutions, we developed a dual-modality system combining in vivo two-photon calcium imaging and focused ultrasound modulation. The studies show that the ∼30 MHz ultrasound can suppress the neuronal activity in awake mice at 100-μm scale spatial resolutions, paving the way for high-resolution ultrasonic neural modulation. The dual-modality in vivo system validated through this study will serve as a general platform for studying the dynamics of various cell types in response to ultrasound.