Injectable 2D Material-Based Sensor Array for Minimally Invasive Neural Implants

Intracranial implants for diagnosis and treatment of brain diseases have been developed over the past few decades. However, the platform of conventional implantable devices still relies on invasive probes and bulky sensors in conjunction with large-area craniotomy and provides only limited biometric information. Here, an implantable multi-modal sensor array that can be injected through a small hole in the skull and inherently spread out for conformal contact with the cortical surface is reported. The injectable sensor array, composed of graphene multi-channel electrodes for neural recording and electrical stimulation and MoS2-based sensors for monitoring intracranial temperature and pressure, is designed based on a mesh structure whose elastic restoring force enables the contracted device to spread out. It is demonstrated that the sensor array injected into a rabbit's head can detect epileptic discharges on the surface of the cortex and mitigate it by electrical stimulation while monitoring both intracranial temperature and pressure. This method provides good potential for implanting a variety of functional devices via minimally invasive surgery.

A Nanozyme-Based Electrode for High-Performance Neural Recording

Implanted neural electrodes have been widely used to treat brain diseases that require high sensitivity and biocompatibility at the tissue-electrode interface. However, currently used clinical electrodes cannot meet both these requirements simultaneously, which hinders the effective recording of electronic signals. Herein, nanozyme-based neural electrodes incorporating bioinspired atomically precise clusters are developed as a general strategy with a heterogeneous design for multiscale and ultrasensitive neural recording via quantum transport and biocatalytic processes. Owing to the dual high-speed electronic and ionic currents at the electrode-tissue interface, the impedance of nanozyme electrodes is 26 times lower than that of state-of-the-art metal electrodes, and the acquisition sensitivity for the local field potential is ≈10 times higher than that of clinical PtIr electrodes, enabling a signal-to-noise ratio (SNR) of up to 14.7 dB for single-neuron recordings in rats. The electrodes provide more than 100-fold higher antioxidant and multi-enzyme-like activities, which effectively decrease 67% of the neuronal injury area by inhibiting glial proliferation and allowing sensitive and stable neural recording. Moreover, nanozyme electrodes can considerably improve the SNR of seizures in acute epileptic rats and are expected to achieve precise localization of seizure foci in clinical settings.

On-demand electrically controlled melatonin release from PEDOT/SNP composite improves quality of chronic neural recording

Long-time and high-quality signal acquisition performance from implantable electrodes is the key to establish stable and efficient brain-computer interface (BCI) connections. The chronic performance of implantable electrodes is hindered by the inflammatory response of brain tissue. In order to solve the material limitation of biological interface electrodes, we designed sulfonated silica nanoparticles (SNPs) as the dopant of Poly (3,4-ethylenedioxythiophene) (PEDOT) to modify the implantable electrodes. In this work, melatonin (MT) loaded SNPs were incorporated in PEDOT via electrochemical deposition on nickel-chromium (Ni-Cr) alloy electrode and carbon nanotube (CNT) fiber electrodes, without affecting the acute neural signal recording capacity. After coating with PEDOT/SNP-MT, the charge storage capacity of both electrodes was significantly increased, and the electrochemical impedance at 1 kHz of the Ni-Cr alloy electrodes was significantly reduced, while that of the CNT electrodes was significantly increased. In addition, this study inspected the effect of electrically triggered MT release every other day on the quality and longevity of neural recording from implanted neural electrodes in rat hippocampus for 1 month. Both MT modified Ni-Cr alloy electrodes and CNT electrodes showed significantly higher spike amplitude after 26-day recording. Significantly, the histological studies showed that the number of astrocytes around the implanted Ni-Cr alloy electrodes was significantly reduced after MT release. These results demonstrate the potent outcome of PEDOT/SNP-MT treatment in improving the chronic neural recording quality possibly through its anti-inflammatory property.

Conducting Polymer-Hydrogel Interpenetrating Networks for Improving the Electrode-Neural Interface

Implantable neural microelectrodes are recognized as a bridge for information exchange between inner organisms and outer devices. Combined with novel modulation technologies such as optogenetics, it offers a highly precise methodology for the dissection of brain functions. However, achieving chronically effective and stable microelectrodes to explore the electrophysiological characteristics of specific neurons in free-behaving animals continually poses great challenges. To resolve this, poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)/poly(vinyl alcohol) (PEDOT/PSS/PVA) interpenetrating conducting polymer networks (ICPN) are fabricated via a hydrogel scaffold precoating and electrochemical polymerization process to improve the performance of neural microelectrodes. The ICPN films exhibit robust interfacial adhesion, a significantly lower electrochemical impedance, superior mechanical properties, and improved electrochemical stability compared to the pure poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)(PEDOT/PSS) films, which may be attributed to the three-dimensional (3D) porous microstructure of the ICPN. Hippocampal neurons and rat pheochromocytoma cells (PC12 cells) adhesion on ICPN and neurite outgrowth are observed, indicating enhanced biocompatibility. Furthermore, alleviated tissue response at the electrode-neural tissue interface and improved recording signal quality are confirmed by histological and electrophysiological studies, respectively. Owing to these merits, optogenetic modulations and electrophysiological recordings are performed in vivo, and an anxiolytic effect of hippocampal glutamatergic neurons on behavior is shown. This study demonstrates the effectiveness and advantages of ICPN-modified neural implants for in vivo applications.

Conducting polymer-based nanostructured materials for brain-machine interfaces

As scientists discovered that raw neurological signals could translate into bioelectric information, brain-machine interfaces (BMI) for experimental and clinical studies have experienced massive growth. Developing suitable materials for bioelectronic devices to be used for real-time recording and data digitalizing has three important necessitates which should be covered. Biocompatibility, electrical conductivity, and having mechanical properties similar to soft brain tissue to decrease mechanical mismatch should be adopted for all materials. In this review, inorganic nanoparticles and intrinsically conducting polymers are discussed to impart electrical conductivity to systems, where soft materials such as hydrogels can offer reliable mechanical properties and a biocompatible substrate. Interpenetrating hydrogel networks offer more mechanical stability and provide a path for incorporating polymers with desired properties into one strong network. Promising fabrication methods, like electrospinning and additive manufacturing, allow scientists to customize designs for each application and reach the maximum potential for the system. In the near future, it is desired to fabricate biohybrid conducting polymer-based interfaces loaded with cells, giving the opportunity for simultaneous stimulation and regeneration. Developing multi-modal BMIs, Using artificial intelligence and machine learning to design advanced materials are among the future goals for this field. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulse-modulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals. The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms.

Multimodal Electrocorticogram Active Electrode Array Based on Zinc Oxide-Thin Film Transistors

Active electrocorticogram (ECoG) electrodes can amplify weak electrophysiological signals and improve anti-interference ability; however, traditional active electrodes are opaque and cannot realize photoelectric collaborative observation. In this study, an active and fully transparent ECoG array based on zinc oxide thin-film transistors (ZnO TFTs) is developed as a local neural signal amplifier for electrophysiological monitoring. The transparency of the proposed ECoG array is up to 85%, which is superior to that of the previously reported active electrode arrays. Various electrical characterizations have demonstrated its ability to record electrophysiological signals with a higher signal-to-noise ratio of 19.9 dB compared to the Au grid (13.2 dB). The high transparency of the ZnO-TFT electrode array allows the concurrent collection of high-quality electrophysiological signals (32.2 dB) under direct optical stimulation of the optogenetic mice brain. The ECoG array can also work under 7-Tesla magnetic resonance imaging to record local brain signals without affecting brain tissue imaging. As the most transparent active ECoG array to date, it provides a powerful multimodal tool for brain observation, including recording brain activity under synchronized optical modulation and 7-Tesla magnetic resonance imaging.

Engineering Electrodes with Robust Conducting Hydrogel Coating for Neural Recording and Modulation

Coating conventional metallic electrodes with conducting polymers has enabled the essential characteristics required for bioelectronics, such as biocompatibility, electrical conductivity, mechanical compliance, and the capacity for structural and chemical functionalization of the bioelectrodes. However, the fragile interface between the conducting polymer and the electrode in wet physiological environment greatly limits their utility and reliability. Here, a general yet reliable strategy to seamlessly interface conventional electrodes with conducting hydrogel coatings is established, featuring tissue-like modulus, highly-desirable electrochemical properties, robust interface, and long-term reliability. Numerical modeling reveals the role of toughening mechanism, synergy of covalent anchorage of long-chain polymers, and chemical cross-linking, in improving the long-term robustness of the interface. Through in vivo implantation in freely-moving mouse models, it is shown that stable electrophysiological recording can be achieved, while the conducting hydrogel-electrode interface remains robust during the long-term low-voltage electrical stimulation. This simple yet versatile design strategy addresses the long-standing technical challenges in functional bioelectrode engineering, and opens up new avenues for the next-generation diagnostic brain-machine interfaces.

Using deep learning to study emotional behavior in rodent models

Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus (e.g., open vs. closed arms of an elevated plus maze). Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained.

Electrochemical Testing of a New Polyimide Thin Film Electrode for Stimulation, Recording, and Monitoring of Brain Activity

Subdural electrode arrays are used for monitoring cortical activity and functional brain mapping in patients with seizures. Until recently, the only commercially available arrays were silicone-based, whose thickness and lack of conformability could impact their performance. We designed, characterized, manufactured, and obtained FDA clearance for 29-day clinical use (510(k) K192764) of a new thin-film polyimide-based electrode array. This study describes the electrochemical characterization undertaken to evaluate the quality and reliability of electrical signal recordings and stimulation of these new arrays. Two testing paradigms were performed: a short-term active soak with electrical stimulation and a 29-day passive soak. Before and after each testing paradigm, the arrays were evaluated for their electrical performance using Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV) and Voltage Transients (VT). In all tests, the impedance remained within an acceptable range across all frequencies. The different CV curves showed no significant changes in shape or area, which is indicative of stable electrode material. The electrode polarization remained within appropriate limits to avoid hydrolysis.

All-Polymeric Electrode Based on PEDOT:PSS for In Vivo Neural Recording

One of the significant challenges today in the brain-machine interfaces that use invasive methods is the stability of the chronic record. In recent years, polymer-based electrodes have gained notoriety for achieving mechanical strength values close to that of brain tissue, promoting a lower immune response to the implant. In this work, we fabricated fully polymeric electrodes based on PEDOT:PSS for neural recording in Wistar rats. We characterized the electrical properties and both in vitro and in vivo functionality of the electrodes. Additionally, we employed histological processing and microscopical visualization to evaluate the tecidual immune response at 7, 14, and 21 days post-implant. Electrodes with 400-micrometer channels showed a 12 dB signal-to-noise ratio. Local field potentials were characterized under two conditions: anesthetized and free-moving. There was a proliferation of microglia at the tissue-electrode interface in the early days, though there was a decrease after 14 days. Astrocytes also migrated to the interface, but there was not continuous recruitment of these cells in the tissue; there was inflammatory stability by day 21. The signal was not affected by this inflammatory action, demonstrating that fully polymeric electrodes can be an alternative means to prolong the valuable time of neural recordings.

Patternable Gelatin Methacrylate/PEDOT/Polystyrene Sulfonate Microelectrode Coatings for Neuronal Recording

This manuscript addresses the need for new soft biomaterials that can be fabricated on the surface of microelectrodes to reduce the mechanical mismatch between biological tissues and electrodes and improve the performance at the neural interface. By electrochemical polymerization of poly(3,4-dioxythiophene) (PEDOT)/polystyrene sulfonate (PSS) through a gelatin methacrylate (GelMA) hydrogel, we demonstrate the synthesis of a conducting polymer hydrogel (CPH) to meet the performance criteria of bioelectrodes. The hybrid material can be photolithographically patterned and covalently attached to gold microelectrodes, forming an interpenetrating network, as confirmed by infrared spectroscopy. The GelMA/PEDOT/PSS coatings were found to be reversibly electroactive by cyclic voltammetry and had low impedance compared to bare gold and GelMA-coated microelectrodes. The CPH coatings showed impedance at levels similar to conventional PEDOT/PSS coatings at a frequency of 1000 Hz. CPH exhibited electrochemical stability over 1000 CV cycles, and its performance was maintained over 14 days. Biocompatibility of the CPH coatings was confirmed by primary hippocampal neuronal cultures via a neuronal viability assay. The CPH-coated microelectrode arrays (MEAs) successfully recorded neuronal activity from primary hippocampal neuronal cells. The CPH GelMA/PEDOT/PSS is a highly promising coating material to enhance microelectrode performance at the neural interface.

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.

Conductive Polymer Enabled Biostable Liquid Metal Electrodes for Bioelectronic Applications

Gallium (Ga)-based liquid metal materials have emerged as a promising material platform for soft bioelectronics. Unfortunately, Ga has limited biostability and electrochemical performance under physiological conditions, which can hinder the implementation of its use in bioelectronic devices. Here, an effective conductive polymer deposition strategy on the liquid metal surface to improve the biostability and electrochemical performance of Ga-based liquid metals for use under physiological conditions is demonstrated. The conductive polymer [poly(3,4-ethylene dioxythiophene):tetrafluoroborate]-modified liquid metal surface significantly outperforms the liquid metal.based electrode in mechanical, biological, and electrochemical studies. In vivo action potential recordings in behaving nonhuman primate and invertebrate models demonstrate the feasibility of using liquid metal electrodes for high-performance neural recording applications. This is the first demonstration of single-unit neural recording using Ga-based liquid metal bioelectronic devices to date. The results determine that the electrochemical deposition of conductive polymer over liquid metal can improve the material properties of liquid metal electrodes for use under physiological conditions and open numerous design opportunities for next-generation liquid metal-based bioelectronics.

Integrated Micro-Devices for a Lab-in-Organoid Technology Platform: Current Status and Future Perspectives

Advancements in stem cell technology together with an improved understanding of in vitro organogenesis have enabled new routes that exploit cell-autonomous self-organization responses of adult stem cells (ASCs) and homogenous pluripotent stem cells (PSCs) to grow complex, three-dimensional (3D), mini-organ like structures on demand, the so-called organoids. Conventional optical and electrical neurophysiological techniques to acquire functional data from brain organoids, however, are not adequate for chronic recordings of neural activity from these model systems, and are not ideal approaches for throughput screenings applied to drug discovery. To overcome these issues, new emerging approaches aim at fusing sensing mechanisms and/or actuating artificial devices within organoids. Here we introduce and develop the concept of the Lab-in-Organoid (LIO) technology for in-tissue sensing and actuation within 3D cell aggregates. This challenging technology grounds on the self-aggregation of brain cells and on integrated bioelectronic micro-scale devices to provide an advanced tool for generating 3D biological brain models with in-tissue artificial functionalities adapted for routine, label-free functional measurements and for assay's development. We complete previously reported results on the implementation of the integrated self-standing wireless silicon micro-devices with experiments aiming at investigating the impact on neuronal spheroids of sinusoidal electro-magnetic fields as those required for wireless power and data transmission. Finally, we discuss the technology headway and future perspectives.

The Design of a Low Noise, Multi-Channel Recording System for Use in Implanted Peripheral Nerve Interfaces

In the development of implantable neural interfaces, the recording of signals from the peripheral nerves is a major challenge. Since the interference from outside the body, other biopotentials, and even random noise can be orders of magnitude larger than the neural signals, a filter network to attenuate the noise and interference is necessary. However, these networks may drastically affect the system performance, especially in recording systems with multiple electrode cuffs (MECs), where a higher number of electrodes leads to complicated circuits. This paper introduces formal analyses of the performance of two commonly used filter networks. To achieve a manageable set of design equations, the state equations of the complete system are simplified. The derived equations help the designer in the task of creating an interface network for specific applications. The noise, crosstalk and common-mode rejection ratio (CMRR) of the recording system are computed as a function of electrode impedance, filter component values and amplifier specifications. The effect of electrode mismatches as an inherent part of any multi-electrode system is also discussed, using measured data taken from a MEC implanted in a sheep. The accuracy of these analyses is then verified by simulations of the complete system. The results indicate good agreement between analytic equations and simulations. This work highlights the critical importance of understanding the effect of interface circuits on the performance of neural recording systems.

Poly(3,4-ethylenedioxythiophene)-Based Neural Interfaces for Recording and Stimulation: Fundamental Aspects and In Vivo Applications

Next-generation neural interfaces for bidirectional communication with the central nervous system aim to achieve the intimate integration with the neural tissue with minimal neuroinflammatory response, high spatio-temporal resolution, very high sensitivity, and readout stability. The design and manufacturing of devices for low power/low noise neural recording and safe and energy-efficient stimulation that are, at the same time, conformable to the brain, with matched mechanical properties and biocompatibility, is a convergence area of research where neuroscientists, materials scientists, and nanotechnologists operate synergically. The biotic-abiotic neural interface, however, remains a formidable challenge that prompts for new materials platforms and innovation in device layouts. Conductive polymers (CP) are attractive materials to be interfaced with the neural tissue and to be used as sensing/stimulating electrodes because of their mixed ionic-electronic conductivity, their low contact impedance, high charge storage capacitance, chemical versatility, and biocompatibility. This manuscript reviews the state-of-the-art of poly(3,4-ethylenedioxythiophene)-based neural interfaces for extracellular recording and stimulation, focusing on those technological approaches that are successfully demonstrated in vivo. The aim is to highlight the most reliable and ready-for-clinical-use solutions, in terms of materials technology and recording performance, other than spot major limitations and identify future trends in this field.

Free-Standing Nanofilm Electrode Arrays for Long-Term Stable Neural Interfacings

Flexible neural electrodes integrated on micrometer-thick polymer substrates offer important opportunities for improving the stability of neuronal activity recordings during cognitive processes. However, the bending stiffness of micrometer-thick polymer substrates is typically two orders of magnitude higher than that of nanofilm electrodes, making it a limiting factor in electrode-tissue interfacings. Here, this limitation is overcome by developing self-assembled nanofilm electrode arrays (NEAs) that consist of high-density, free-standing gold nanofilm electrodes. Chronically implanted NEAs can form intimate and innervated interfaces with neural tissue, enabling stable neuronal activity recordings across multiple brain regions over several months. As an application example, the activities of the same neuronal populations are tracked across odor discrimination reversal learning and it is illustrated how dorsal striatal neurons represent and update stimulus-outcome associations across multiple timescales. The results underscore the potential of free-standing nanoscale materials for interfacing biological systems over long terms.

The Use of the Velocity Selective Recording Technique to Reveal the Excitation Properties of the Ulnar Nerve in Pigs

Decoding information from the peripheral nervous system via implantable neural interfaces remains a significant challenge, considerably limiting the advancement of neuromodulation and neuroprosthetic devices. The velocity selective recording (VSR) technique has been proposed to improve the classification of neural traffic by combining temporal and spatial information through a multi-electrode cuff (MEC). Therefore, this study investigates the feasibility of using the VSR technique to characterise fibre type based on the electrically evoked compound action potentials (eCAP) propagating along the ulnar nerve of pigs in vivo. A range of electrical stimulation parameters (amplitudes of 50 μA-10 mA and pulse durations of 100 μs, 500 μs, 1000 μs, and 5000 μs) was applied on a cutaneous and a motor branch of the ulnar nerve in nine Danish landrace pigs. Recordings were made with a 14 ring MEC and a delay-and-add algorithm was used to convert the eCAPs into the velocity domain. The results revealed two fibre populations propagating along the cutaneous branch of the ulnar nerve, with mean velocities of 55 m/s and 21 m/s, while only one dominant fibre population was found for the motor branch, with a mean velocity of 63 m/s. Because of its simplicity to provide information on the fibre selectivity and direction of propagation of nerve fibres, VSR can be implemented to advance the performance of the bidirectional control of neural prostheses and bioelectronic medicine applications.

Investigation of the Feasibility of Ventricular Delivery of Resveratrol to the Microelectrode Tissue Interface

(1) Background: Intracortical microelectrodes (IMEs) are essential to basic brain research and clinical brain-machine interfacing applications. However, the foreign body response to IMEs results in chronic inflammation and an increase in levels of reactive oxygen and nitrogen species (ROS/RNS). The current study builds on our previous work, by testing a new delivery method of a promising antioxidant as a means of extending intracortical microelectrodes performance. While resveratrol has shown efficacy in improving tissue response, chronic delivery has proven difficult because of its low solubility in water and low bioavailability due to extensive first pass metabolism. (2) Methods: Investigation of an intraventricular delivery of resveratrol in rats was performed herein to circumvent bioavailability hurdles of resveratrol delivery to the brain. (3) Results: Intraventricular delivery of resveratrol in rats delivered resveratrol to the electrode interface. However, intraventricular delivery did not have a significant impact on electrophysiological recordings over the six-week study. Histological findings indicated that rats receiving intraventricular delivery of resveratrol had a decrease of oxidative stress, yet other biomarkers of inflammation were found to be not significantly different from control groups. However, investigation of the bioavailability of resveratrol indicated a decrease in resveratrol accumulation in the brain with time coupled with inconsistent drug elution from the cannulas. Further inspection showed that there may be tissue or cellular debris clogging the cannulas, resulting in variable elution, which may have impacted the results of the study. (4) Conclusions: These results indicate that the intraventricular delivery approach described herein needs further optimization, or may not be well suited for this application.

Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments

Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.

Flexible Neural Probes with Electrochemical Modified Microelectrodes for Artifact-Free Optogenetic Applications

With the rapid increase in the use of optogenetics to investigate nervous systems, there is high demand for neural interfaces that can simultaneously perform optical stimulation and electrophysiological recording. However, high-magnitude stimulation artifacts have prevented experiments from being conducted at a desirably high temporal resolution. Here, a flexible polyimide-based neural probe with polyethylene glycol (PEG) packaged optical fiber and Pt-Black/PEDOT-GO (graphene oxide doped poly(3,4-ethylene-dioxythiophene)) modified microelectrodes was developed to reduce the stimulation artifacts that are induced by photoelectrochemical (PEC) and photovoltaic (PV) effects. The advantages of this design include quick and accurate implantation and high-resolution recording capacities. Firstly, electrochemical performance of the modified microelectrodes is significantly improved due to the large specific surface area of the GO layer. Secondly, good mechanical and electrochemical stability of the modified microelectrodes is obtained by using Pt-Black as bonding layer. Lastly, bench noise recordings revealed that PEC noise amplitude of the modified neural probes could be reduced to less than 50 µV and no PV noise was detected when compared to silicon-based neural probes. The results indicate that this device is a promising optogenetic tool for studying local neural circuits.

Neurochip3: An Autonomous Multichannel Bidirectional Brain-Computer Interface for Closed-Loop Activity-Dependent Stimulation

Toward addressing many neuroprosthetic applications, the Neurochip3 (NC3) is a multichannel bidirectional brain-computer interface that operates autonomously and can support closed-loop activity-dependent stimulation. It consists of four circuit boards populated with off-the-shelf components and is sufficiently compact to be carried on the head of a non-human primate (NHP). NC3 has six main components: (1) an analog front-end with an Intan biophysical signal amplifier (16 differential or 32 single-ended channels) and a 3-axis accelerometer, (2) a digital control system comprised of a Cyclone V FPGA and Atmel SAM4 MCU, (3) a micro SD Card for 128 GB or more storage, (4) a 6-channel differential stimulator with ±60 V compliance, (5) a rechargeable battery pack supporting autonomous operation for up to 24 h and, (6) infrared transceiver and serial ports for communication. The NC3 and earlier versions have been successfully deployed in many closed-loop operations to induce synaptic plasticity and bridge lost biological connections, as well as deliver activity-dependent intracranial reinforcement. These paradigms to strengthen or replace impaired connections have many applications in neuroprosthetics and neurorehabilitation.

Superior galvanostatic electrochemical deposition of platinum nanograss provides high performance planar microelectrodes forin vitroneural recording

Objective.Platinum nanograss (Ptng) has been demonstrated as an excellent coating to increase the electrode roughness and reduce the impedance of microelectrodes for neural recording. However, the optimisation of the original potentiostatic electrochemical deposition (PSED) method has been performed by the original group only and noin vitrovalidation of functionality was reported.Approach.This study firstly reinvestigates the use of the PSED method for Ptng coating at different charge densities which highlights non-uniformities in the edges of the microelectrodes for increasing deposition charge densities, leading to a decreased impedance which is in fact an artefact. We then introduce a novel Ptng fabrication method of galvanostatic electrochemical deposition (GSED).Main results.We demonstrate that the GSED deposition method also significantly reduces the electrode impedance, raises the charge storage capacity and provides a significantly more planar electrode surface in comparison to the PSED method with negligible edge effects. In addition, we demonstrate how high-quality neural recordings were performed, for the first time, using the Ptng GSED deposition microelectrodes from human hNT neurons and how spiking and bursting were observed.Significance.Thus, the GSED Ptng deposition method presented here provides an alternative method of microelectrode fabrication for neural applications with excellent impedance and planarity of surface.

Advances in Neural Recording and Stimulation Integrated Circuits

In the past few decades, driven by the increasing demands in the biomedical field aiming to cure neurological diseases and improve the quality of daily lives of the patients, researchers began to take advantage of the semiconductor technology to develop miniaturized and power-efficient chips for implantable applications. The emergence of the integrated circuits for neural prosthesis improves the treatment process of epilepsy, hearing loss, retinal damage, and other neurological diseases, which brings benefits to many patients. However, considering the safety and accuracy in the neural prosthesis process, there are many research directions. In the process of chip design, designers need to carefully analyze various parameters, and investigate different design techniques. This article presents the advances in neural recording and stimulation integrated circuits, including (1) a brief introduction of the basics of neural prosthesis circuits and the repair process in the bionic neural link, (2) a systematic introduction of the basic architecture and the latest technology of neural recording and stimulation integrated circuits, (3) a summary of the key issues of neural recording and stimulation integrated circuits, and (4) a discussion about the considerations of neural recording and stimulation circuit architecture selection and a discussion of future trends. The overview would help the designers to understand the latest performances in many aspects and to meet the design requirements better.

Recording Strategies for High Channel Count, Densely Spaced Microelectrode Arrays

Neuroscience research into how complex brain functions are implemented at an extra-cellular level requires in vivo neural recording interfaces, including microelectrodes and read-out circuitry, with increased observability and spatial resolution. The trend in neural recording interfaces toward employing high-channel-count probes or 2D microelectrodes arrays with densely spaced recording sites for recording large neuronal populations makes it harder to save on resources. The low-noise, low-power requirement specifications of the analog front-end usually requires large silicon occupation, making the problem even more challenging. One common approach to alleviating this consumption area burden relies on time-division multiplexing techniques in which read-out electronics are shared, either partially or totally, between channels while preserving the spatial and temporal resolution of the recordings. In this approach, shared elements have to operate over a shorter time slot per channel and active area is thus traded off against larger operating frequencies and signal bandwidths. As a result, power consumption is only mildly affected, although other performance metrics such as in-band noise or crosstalk may be degraded, particularly if the whole read-out circuit is multiplexed at the analog front-end input. In this article, we review the different implementation alternatives reported for time-division multiplexing neural recording systems, analyze their advantages and drawbacks, and suggest strategies for improving performance.

A Bidirectional Neural Interface SoC With Adaptive IIR Stimulation Artifact Cancelers

We present a 180-nm CMOS bidirectional neural interface system-on-chip that enables simultaneous recording and stimulation with on-chip stimulus artifact cancelers. The front-end cancellation scheme incorporates a least-mean-square engine that adapts the coefficients of a 2-tap infinite-impulse-response filter to replicate the stimulation artifact waveform and subtract it at the front-end. Measurements demonstrate the efficacy of the canceler in mitigating artifacts up to 700 mVpp and reducing the front-end amplifier saturation recovery time in response to a 2.5 Vpp artifact. Each recording channel houses a pair of adaptive infinite-impulse-response filters, which enable cancellation of the artifacts generated by the simultaneous operation of the 2 on-chip stimulators. The analog front-end consumes 2.5 μW of power per channel, has a maximum gain of 50 dB and a bandwidth of 9.0 kHz with 6.2 μVrms integrated input-referred noise.

Three-micrometer-diameter needle electrode with an amplifier for extracellular in vivo recordings

Microscale needle-electrode devices offer neuronal signal recording capability in brain tissue; however, using needles of smaller geometry to minimize tissue damage causes degradation of electrical properties, including high electrical impedance and low signal-to-noise ratio (SNR) recording. We overcome these limitations using a device assembly technique that uses a single needle-topped amplifier package, called STACK, within a device of ∼1 × 1 mm2 Based on silicon (Si) growth technology, a <3-µm-tip-diameter, 400-µm-length needle electrode was fabricated on a Si block as the module. The high electrical impedance characteristics of the needle electrode were improved by stacking it on the other module of the amplifier. The STACK device exhibited a voltage gain of >0.98 (-0.175 dB), enabling recording of the local field potential and action potentials from the mouse brain in vivo with an improved SNR of 6.2. Additionally, the device allowed us to use a Bluetooth module to demonstrate wireless recording of these neuronal signals; the chronic experiment was also conducted using STACK-implanted mice.

Rhode Island COBRE Center for Central Nervous System Function: Progress and Perspectives

The Center of Biomedical Research Excellence (COBRE) Center for Central Nervous System Function (CCNSF) was funded in 2013 by the National Institute for General Medical Sciences to establish a collaborative environment for basic and applied research in higher nervous system function with humans and experimental animal model systems. Since its inception, the COBRE CCNSF has funded junior faculty investigators as Project and Pilot Project Leaders and one established investigator on projects investigating fundamental properties of nervous system function using a range of tools spanning molecular genetics, neurophysiology, invasive and non-invasive brain stimulation, behavior and neuroimaging. The Administrative Core facilitates all Center activities with a focus on career development, grant proposal submission, and deployment of technology developed by our research cores. The Design and Analysis Core aims to provide principled study design expertise, statistical modeling, machine learning, inference, and computation. The Behavior and Neuroimaging Core provides project-specific collaboration and support to COBRE scientists to promote the acquisition of high quality behavioral, physiological, neuroimaging and neurostimulation data, to ensure the integrity of the data collection infrastructure and to help implement robust data processing and visualization pipelines. While the cores principally serve Center scientists, our Center and the core resources have availability to all Rhode Island researchers.

Carbon Nanotube Modified Microelectrode Array for Neural Interface

Carbon nanotubes (CNTs) coatings have been shown over the past few years as a promising material for neural interface applications. In particular, in the field of nerve implants, CNTs have fundamental advantages due to their unique mechanical and electrical properties. In this study, carbon nanotubes multi-electrode arrays (CNT-modified-Au MEAs) were fabricated based on gold multi-electrode arrays (Au-MEAs). The electrochemical impedance spectra of CNT-modified-Au MEA and Au-MEA were compared employing equivalent circuit models. In comparison with Au-MEA (17 Ω), CNT-modified-Au MEA (8 Ω) lowered the overall impedance of the electrode at 1 kHz by 50%. The results showed that CNT-modified-Au MEAs have good properties such as low impedance, high stability and durability, as well as scratch resistance, which makes them appropriate for long-term application in neural interfaces.

Compensation Strategies for Bioelectric Signal Changes in Chronic Selective Nerve Cuff Recordings: A Simulation Study

Peripheral nerve interfaces (PNIs) allow us to extract motor, sensory, and autonomic information from the nervous system and use it as control signals in neuroprosthetic and neuromodulation applications. Recent efforts have aimed to improve the recording selectivity of PNIs, including by using spatiotemporal patterns from multi-contact nerve cuff electrodes as input to a convolutional neural network (CNN). Before such a methodology can be translated to humans, its performance in chronic implantation scenarios must be evaluated. In this simulation study, approaches were evaluated for maintaining selective recording performance in the presence of two chronic implantation challenges: the growth of encapsulation tissue and rotation of the nerve cuff electrode. Performance over time was examined in three conditions: training the CNN at baseline only, supervised re-training with explicitly labeled data at periodic intervals, and a semi-supervised self-learning approach. This study demonstrated that a selective recording algorithm trained at baseline will likely fail over time due to changes in signal characteristics resulting from the chronic challenges. Results further showed that periodically recalibrating the selective recording algorithm could maintain its performance over time, and that a self-learning approach has the potential to reduce the frequency of recalibration.

Bioinspired Materials for In Vivo Bioelectronic Neural Interfaces

The success of in vivo neural interfaces relies on their long-term stability and large scale in interrogating and manipulating neural activity after implantation. Conventional neural probes, owing to their limited spatiotemporal resolution and scale, face challenges for studying the massive, interconnected neural network in its native state. In this review, we argue that taking inspiration from biology will unlock the next generation of in vivo bioelectronic neural interfaces. Reducing the feature sizes of bioelectronic neural interfaces to mimic those of neurons enables high spatial resolution and multiplexity. Additionally, chronic stability at the device-tissue interface is realized by matching the mechanical properties of bioelectronic neural interfaces to those of the endogenous tissue. Further, modeling the design of neural interfaces after the endogenous topology of the neural circuitry enables new insights into the connectivity and dynamics of the brain. Lastly, functionalization of neural probe surfaces with coatings inspired by biology leads to enhanced tissue acceptance over extended timescales. Bioinspired neural interfaces will facilitate future developments in neuroscience studies and neurological treatments by leveraging bidirectional information transfer and integrating neuromorphic computing elements.

Flexible Fiber Probe for Efficient Neural Stimulation and Detection

Functional probes are a leading contender for the recognition and manipulation of nervous behavior and are characterized by substantial scientific and technological potential. Despite the recent development of functional neural probes, a flexible biocompatible probe unit that allows for long-term simultaneous stimulation and signaling is still an important task. Here, a category of flexible tiny multimaterial fiber probes (<0.3 g) is described in which the metal electrodes are regularly embedded inside a biocompatible polymer fiber with a double-clad optical waveguide by thermal drawing. Significantly, this arrangement enables great improvement in mechanical properties, achieves high optical transmission (>90%), and effectively minimizes the impedance (by up to one order of magnitude) of the probe. This ability allows to realize long-term (at least 10 weeks) simultaneous optical stimulation and neural recording at the single-cell level in behaving mice with signal-to-noise ratio (SNR = 30 dB) that is more than 6 times that of the benchmark probe such as an all-polymer fiber.

Hemispherical Microelectrode Array for Ex Vivo Retinal Neural Recording

To investigate the neuronal visual encoding process in the retina, researchers have performed in vitro and ex vivo electrophysiological experiments using animal retinal tissues. The microelectrode array (MEA) has become a key component in retinal experiments because it enables simultaneous neural recording from a population of retinal neurons. However, in most retinal experiments, it is inevitable that the retinal tissue is flattened on the planar MEA, becoming deformed from the original hemispherical shape. During the tissue deforming process, the retina is subjected to mechanical stress, which can induce abnormal physiological conditions. To overcome this problem, in this study, we propose a hemispherical MEA with a curvature that allows retinal tissues to adhere closely to electrodes without tissue deformation. The electrode array is fabricated by stretching a thin, flexible polydimethylsiloxane (PDMS) electrode layer onto a hemispherical substrate. To form micro patterns of electrodes, laser processing is employed instead of conventional thin-film microfabrication processes. The feasibility for neural recording from retinal tissues using this array is shown by conducting ex vivo retinal experiments. We anticipate that the proposed techniques for hemispherical MEAs can be utilized not only for ex vivo retinal studies but also for various flexible electronics.

Ultra-small carbon fiber electrode recording site optimization and improved in vivo chronic recording yield

OBJECTIVE

Carbon fiber electrodes may enable better long-term brain implants, minimizing the tissue response commonly seen with silicon-based electrodes. The small diameter fiber may enable high-channel count brain-machine interfaces capable of reproducing dexterous movements. Past carbon fiber electrodes exhibited both high fidelity single unit recordings and a healthy neuronal population immediately adjacent to the recording site. However, the recording yield of our carbon fiber arrays chronically implanted in the brain typically hovered around 30%, for previously unknown reasons. In this paper we investigated fabrication process modifications aimed at increasing recording yield and longevity.

APPROACH

We tested a new cutting method using a 532nm laser against traditional scissor methods for the creation of the electrode recording site. We verified the efficacy of improved recording sites with impedance measurements and in vivo array recording yield. Additionally, we tested potentially longer-lasting coating alternatives to PEDOT:pTS, including PtIr and oxygen plasma etching. New coatings were evaluated with accelerated soak testing and acute recording.

MAIN RESULTS

We found that the laser created a consistent, sustainable 257 ± 13.8 µm2 electrode with low 1 kHz impedance (19 ± 4 kΩ with PEDOT:pTS) and low fiber-to-fiber variability. The PEDOT:pTS coated laser cut fibers were found to have high recording yield in acute (97% > 100 µV pp , N = 34 fibers) and chronic (84% > 100 µV pp , day 7; 71% > 100 µV pp , day 63, N = 45 fibers) settings. The laser cut recording sites were good platforms for the PtIr coating and oxygen plasma etching, slowing the increase in 1 kHz impedance compared to PEDOT:pTS in an accelerated soak test.

SIGNIFICANCE

We have found that laser cut carbon fibers have a high recording yield that can be maintained for over two months in vivo and that alternative coatings perform better than PEDOT:pTS in accelerated aging tests. This work provides evidence to support carbon fiber arrays as a viable approach to high-density, clinically-feasible brain-machine interfaces.

Verification of a Rapidly Multiplexed Circuit for Scalable Action Potential Recording

This report presents characterizations of in vivo neural recordings performed with a CMOS multichannel neural recording chip that uses rapid multiplexing directly at the electrodes, without any pre-amplification or buffering. Neural recordings were taken from a 16-channel microwire array implanted in rodent cortex, with comparison to a gold-standard commercial bench-top recording system. We were able to record well-isolated threshold crossings from 10 multiplexed electrodes and typical local field potential waveforms from 16, with strong agreement with the standard system (average SNR = 2.59 and 3.07 respectively). For 10 electrodes, the circuit achieves an effective area per channel of 0.0077 mm², which is >5x smaller than typical multichannel chips. Extensive characterizations of noise and signal quality are presented and compared to fundamental theory, as well as results from in vivo and in vitro experiments. By demonstrating the validation of rapid multiplexing directly at the electrodes, this report confirms it as a promising approach for reducing circuit area in massively-multichannel neural recording systems, which is crucial for scaling recording site density and achieving large-scale sensing of brain activity with high spatiotemporal resolution.

Magnetic Actuation of Flexible Microelectrode Arrays for Neural Activity Recordings

Implantable microelectrodes that can be remotely actuated via external fields are promising tools to interface with biological systems at a high degree of precision. Here, we report the development of flexible magnetic microelectrodes (FMμEs) that can be remotely actuated by magnetic fields. The FMμEs consist of flexible microelectrodes integrated with dielectrically encapsulated FeNi (iron-nickel) alloy microactuators. Both magnetic torque- and force-driven actuation of the FMμEs have been demonstrated. Nanoplatinum-coated FMμEs have been applied for in vivo recordings of neural activities from peripheral nerves and cerebral cortex of mice. Moreover, owing to their ultrasmall sizes and mechanical compliance with neural tissues, chronically implanted FMμEs elicited greatly reduced neuronal cell loss in mouse brain compared to conventional stiff probes. The FMμEs open up a variety of new opportunities for electrically interfacing with biological systems in a controlled and minimally invasive manner.

The Connection Between the Nervous System and Machines: Commentary

Decades of technological developments have populated the field of brain-machine interfaces and neuroprosthetics with several replacement strategies, neural modulation treatments, and rehabilitation techniques to improve the quality of life for patients affected by sensory and motor disabilities. This field is now quickly expanding thanks to advances in neural interfaces, machine learning techniques, and robotics. Despite many clinical successes, and multiple innovations in animal models, brain-machine interfaces remain mainly confined to sophisticated laboratory environments indicating a necessary step forward in the used technology. Interestingly, Elon Musk and Neuralink have recently presented a new brain-machine interface platform with thousands of channels, fast implantation, and advanced signal processing. Here, how their work takes part in the context of the restoration of sensory-motor functions through neuroprostheses is commented.

Electrodeposited PEDOT:Nafion Composite for Neural Recording and Stimulation

Microelectrode arrays are used for recording and stimulation in neurosciences both in vitro and in vivo. The electrodeposition of conductive polymers, such as poly(3,4-ethylene dioxythiophene) (PEDOT), is widely adopted to improve both the in vivo recording and the charge injection limit of metallic microelectrodes. The workhorse of conductive polymers in the neurosciences is PEDOT:PSS, where PSS represents polystyrene-sulfonate. In this paper, the counterion is the fluorinated polymer Nafion, so the composite PEDOT:Nafion is deposited onto a flexible neural microelectrode array. PEDOT:Nafion coated electrodes exhibit comparable in vivo recording capability to the reference PEDOT:PSS, providing a large signal-to-noise ratio in a murine animal model. Importantly, PEDOT:Nafion exhibits a minimized polarization during electrical stimulation, thereby resulting in an improved charge injection limit equal to 4.4 mC cm^-2 , almost 80% larger than the 2.5 mC cm^-2 that is observed for PEDOT:PSS.

Flexible Micropillar Electrode Arrays for In Vivo Neural Activity Recordings

Flexible electronics that can form tight interfaces with neural tissues hold great promise for improving the diagnosis and treatment of neurological disorders and advancing brain/machine interfaces. Here, the facile fabrication of a novel flexible micropillar electrode array (µPEA) is described based on a biotemplate method. The flexible and compliant µPEA can readily integrate with the soft surface of a rat cerebral cortex. Moreover, the recording sites of the µPEA consist of protruding micropillars with nanoscale surface roughness that ensure tight interfacing and efficient electrical coupling with the nervous system. As a result, the flexible µPEA allows for in vivo multichannel recordings of epileptiform activity with a high signal-to-noise ratio of 252 ± 35. The ease of preparation, high flexibility, and biocompatibility make the µPEA an attractive tool for in vivo spatiotemporal mapping of neural activity.

A supervised machine learning approach to characterize spinal network function

Spontaneous activity is a common feature of immature neuronal networks throughout the central nervous system and plays an important role in network development and consolidation. In postnatal rodents, spontaneous activity in the spinal cord exhibits complex, stochastic patterns that have historically proven challenging to characterize. We developed a software tool for quickly and automatically characterizing and classifying episodes of spontaneous activity generated from developing spinal networks. We recorded spontaneous activity from in vitro lumbar ventral roots of 16 neonatal [postnatal day (P)0-P3] mice. Recordings were DC coupled and detrended, and episodes were separated for analysis. Amplitude-, duration-, and frequency-related features were extracted from each episode and organized into five classes. Paired classes and features were used to train and test supervised machine learning algorithms. Multilayer perceptrons were used to classify episodes as rhythmic or multiburst. We increased network excitability with potassium chloride and tested the utility of the tool to detect changes in features and episode class. We also demonstrate usability by having a novel experimenter use the program to classify episodes collected at a later time point (P5). Supervised machine learning-based classification of episodes accounted for changes that traditional approaches cannot detect. Our tool, named SpontaneousClassification, advances the detail in which we can study not only developing spinal networks, but also spontaneous networks in other areas of the nervous system. NEW & NOTEWORTHY Spontaneous activity is important for nervous system network development and consolidation. Our software uses machine learning to automatically and quickly characterize and classify episodes of spontaneous activity in the spinal cord of newborn mice. It detected changes in network activity following KCl-enhanced excitation. Using our software to classify spontaneous activity throughout development, in pathological models, or with neuromodulation, may offer insight into the development and organization of spinal circuits.

A Magnetically Assembled High-Aspect-Ratio Needle Electrode for Recording Neuronal Activity

Microelectrode devices, which enable the detection of neuronal signals in brain tissues, have made significant contributions in the field of neuroscience and the brain-machine interfaces. To further develop such microelectrode devices, the following requirements must be met: i) a fine needle's diameter (<30 µm) to reduce damage to tissues; ii) a long needle (e.g., ≈1 mm for rodents and ≈2 mm for macaques); and iii) multiple electrodes to achieve high spatial recording (<100 µm in pitch). In order to meet these requirements, this study herein reports an assembly technique for high-aspect-ratio microneedles, which employs a magnet. The assembly is demonstrated, in which nickel wires of length 750 µm and diameter 25 µm are produced on a silicon substrate. The impedance magnitude of the assembled needle-like electrode measured at 1 kHz is 5.6 kΩ, exhibiting output and input signal amplitudes of 96.7% at 1 kHz. To confirm the recording capability of the fabricated device, neuronal signal recordings are performed using mouse cerebra in vivo. The packaged single microneedle electrode penetrates the barrel field in the primary somatosensory cortex of the mouse and enables the detection of evoked neuronal activity of both local field potentials and action potentials.

Quantification of Signal-to-Noise Ratio in Cerebral Cortex Recordings Using Flexible MEAs With Co-localized Platinum Black, Carbon Nanotubes, and Gold Electrodes

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5–1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (<1500 Hz).

Acquisition of Neural Action Potentials Using Rapid Multiplexing Directly at the Electrodes

Neural recording systems that interface with implanted microelectrodes are used extensively in experimental neuroscience and neural engineering research. Interface electronics that are needed to amplify, filter, and digitize signals from multichannel electrode arrays are a critical bottleneck to scaling such systems. This paper presents the design and testing of an electronic architecture for intracortical neural recording that drastically reduces the size per channel by rapidly multiplexing many electrodes to a single circuit. The architecture utilizes mixed-signal feedback to cancel electrode offsets, windowed integration sampling to reduce aliased high-frequency noise, and a successive approximation analog-to-digital converter with small capacitance and asynchronous control. Results are presented from a 180 nm CMOS integrated circuit prototype verified using in vivo experiments with a tungsten microwire array implanted in rodent cortex. The integrated circuit prototype achieves <0.004 mm² area per channel, 7 µW power dissipation per channel, 5.6 µVrms input referred noise, 50 dB common mode rejection ratio, and generates 9-bit samples at 30 kHz per channel by multiplexing at 600 kHz. General considerations are discussed for rapid time domain multiplexing of high-impedance microelectrodes. Overall, this work describes a promising path forward for scaling neural recording systems to numbers of electrodes that are orders of magnitude larger.

Scalable, Modular Three-Dimensional Silicon Microelectrode Assembly via Electroless Plating

We devised a scalable, modular strategy for microfabricated 3-D neural probe synthesis. We constructed a 3-D probe out of individual 2-D components (arrays of shanks bearing close-packed electrodes) using mechanical self-locking and self-aligning techniques, followed by electroless nickel plating to establish electrical contact between the individual parts. We detail the fabrication and assembly process and demonstrate different 3-D probe designs bearing thousands of electrode sites. We find typical self-alignment accuracy between shanks of <0.2° and demonstrate orthogonal electrical connections of 40 µm pitch, with thousands of connections formed electrochemically in parallel. The fabrication methods introduced allow the design of scalable, modular electrodes for high-density 3-D neural recording. The combination of scalable 3-D design and close-packed recording sites may support a variety of large-scale neural recording strategies for the mammalian brain.

Olfactory Landmark-Based Communication in Interacting Drosophila

To communicate with conspecifics, animals deploy various strategies to release pheromones, chemical signals modulating social and sexual behaviors [1-5]. Importantly, a single pheromone induces different behaviors depending on the context and exposure dynamics [6-8]. Therefore, to comprehend the ethological role of pheromones, it is essential to characterize how neurons in the recipients respond to temporally and spatially fluctuating chemical signals emitted by donors during natural interactions. In Drosophila melanogaster, the male pheromone 11-cis-vaccenyl acetate (cVA) [9] activates specific olfactory receptor neurons (ORNs) [10, 11] to regulate diverse social and sexual behaviors in recipients [12-15]. Physicochemical analyses have identified this chemical on an animal's body [16, 17] and in its local environment [18, 19]. However, because these methods are imprecise in capturing spatiotemporal dynamics, it is poorly understood how individual pheromone cues are released, detected, and interpreted by recipients. Here, we developed a system based on bioluminescence to monitor neural activity in freely interacting Drosophila, and investigated the active detection and perception of the naturally emitted cVA. Unexpectedly, neurons specifically tuned to cVA did not exhibit significant activity during physical interactions between males, and instead responded strongly to olfactory landmarks deposited by males. These landmarks mediated attraction through Or67d receptors and allured both sexes to the marked region. Importantly, the landmarks remained attractive even when a pair of flies was engaged in courtship behavior. In contrast, female deposits did not affect the exploration pattern of either sex. Thus, Drosophila use pheromone marking to remotely signal their sexual identity and to enhance social interactions.

Recent Advances in Materials, Devices, and Systems for Neural Interfaces

Technologies capable of establishing intimate, long-lived optical/electrical interfaces to neural systems will play critical roles in neuroscience research and in the development of nonpharmacological treatments for neurological disorders. The development of high-density interfaces to 3D populations of neurons across entire tissue systems in living animals, including human subjects, represents a grand challenge for the field, where advanced biocompatible materials and engineered structures for electrodes and light emitters will be essential. This review summarizes recent progress in these directions, with an emphasis on the most promising demonstrated concepts, materials, devices, and systems. The article begins with an overview of electrode materials with enhanced electrical and/or mechanical performance, in forms ranging from planar films, to micro/nanostructured surfaces, to 3D porous frameworks and soft composites. Subsequent sections highlight integration with active materials and components for multiplexed addressing, local amplification, wireless data transmission, and power harvesting, with multimodal operation in soft, shape-conformal systems. These advances establish the foundations for scalable architectures in optical/electrical neural interfaces of the future, where a blurring of the lines between biotic and abiotic systems will catalyze profound progress in neuroscience research and in human health/well-being.

Multimed: An Integrated, Multi-Application Platform for the Real-Time Recording and Sub-Millisecond Processing of Biosignals

Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of generic processing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels. The FPGA core processing unit makes Multimed suitable as either a reconfigurable electrophysiology system or a prototyping platform for VLSI implantable medical devices. It is specifically designed for open- and closed-loop experiments and provides consistent feedback rules, well within biological microseconds timeframes. This paper presents the specifications and architecture of the Multimed system, then details the biosignal processing algorithms and their digital implementation. Finally, three applications utilizing Multimed in neuroscience and diabetes research are described. They demonstrate the system’s configurability, its multi-channel, real-time processing, and its feedback control capabilities.

Online Artifact Cancelation in Same-Electrode Neural Stimulation and Recording Using a Combined Hardware and Software Architecture

Advancing studies of neural network dynamics and developments of closed-loop neural interfaces requires the ability to simultaneously stimulate and record the neural cells. Recording adjacent to or at the stimulation site produces artifact signals that are orders of magnitude larger than the neural responses of interest. These signals often saturate the recording amplifier causing distortion or loss of short-latency evoked responses. This paper proposes a method to cancel the artifact in simultaneous neural recording and stimulation on the same electrode. By combining a novel hardware architecture with concurrent software processing, the design achieves neural signal recovery in a wide range of conditions. The proposed system uniquely demonstrates same-electrode stimulation and recording, with neural signal recovery in presence of stimulation artifact 100 dB larger in magnitude than the underlying signals. The system is tested both in vitro and in vivo, during concurrent stimulation and recording on the same electrode. In vivo results in a rodent model are compared to recordings made by a commercial neural amplifier system connected in parallel.

A Brain-Spinal Interface (BSI) System-on-Chip (SoC) for Closed-Loop Cortically-Controlled Intraspinal Microstimulation

This paper reports on a fully miniaturized brain-spinal interface (BSI) system for closed-loop cortically-controlled intraspinal microstimulation (ISMS). Fabricated in AMS 0.35μm two-poly four-metal complementary metal-oxide-semiconductor (CMOS) technology, this system-on-chip (SoC) measures ~ 3.46mm × 3.46mm and incorporates two identical 4-channel modules, each comprising a spike-recording front-end, embedded digital signal processing (DSP) unit, and programmable stimulating back-end. The DSP unit is capable of generating multichannel trigger signals for a wide array of ISMS triggering patterns based on real-time discrimination of a programmable number of intracortical neural spikes within a pre-specified time-bin duration via thresholding and user-adjustable time-amplitude windowing. The system is validated experimentally using an anesthetized rat model of a spinal cord contusion injury at the T8 level. Multichannel neural spikes are recorded from the cerebral cortex and converted in real time into electrical stimuli delivered to the lumbar spinal cord below the level of the injury, resulting in distinct patterns of hindlimb muscle activation.