Massively parallel microwire arrays integrated with CMOS chips for neural recording

Neural interface systems with on-device computing: machine learning and neuromorphic architectures

Development of neural interface and brain-machine interface (BMI) systems enables the treatment of neurological disorders including cognitive, sensory, and motor dysfunctions. While neural interfaces have steadily decreased in form factor, recent developments target pervasive implantables. Along with advances in electrodes, neural recording, and neurostimulation circuits, integration of disease biomarkers and machine learning algorithms enables real-time and on-site processing of neural activity with no need for power-demanding telemetry. This recent trend on combining artificial intelligence and machine learning with modern neural interfaces will lead to a new generation of low-power, smart, and miniaturized therapeutic devices for a wide range of neurological and psychiatric disorders. This paper reviews the recent development of the 'on-chip' machine learning and neuromorphic architectures, which is one of the key puzzles in devising next-generation clinically viable neural interface systems.

Novel transducers for high-channel-count neuroelectronic recording interfaces

Neuroelectronic interfaces with the nervous system are an essential technology in state-of-the-art neuroscience research aiming to uncover the fundamental working mechanisms of the brain. Progress towards increased spatio-temporal resolution has been tightly linked to the advance of microelectronics technology and novel materials. Translation of these technologies to neuroscience has resulted in multichannel neural probes and acquisition systems enabling the recording of brain signals using thousands of channels. This review provides an overview of state-of-the-art neuroelectronic technologies, with emphasis on recording site architectures which enable the implementation of addressable arrays for high-channel-count neural interfaces. In this field, active transduction mechanisms are gaining importance fueled by novel materials, as they facilitate the implementation of high density addressable arrays.

Nanoenabled Bioelectrical Modulation

Studying the formation and interactions between biological systems and artificial materials is significant for probing complex biophysical behaviors and addressing challenging biomedical problems. Bioelectrical interfaces, especially nanostructure-based, have improved compatibility with cells and tissues and enabled new approaches to biological modulation. In particular, free-standing and remotely activated bioelectrical devices demonstrate potential for precise biophysical investigation and efficient clinical therapies. Interacting with single cells or organelles requires devices of sufficiently small size for high resolution probing. Nanoscale semiconductors, given their diverse functionalities, are promising device platforms for subcellular modulation. Tissue-level modulation requires additional consideration regarding the device's mechanical compliance for either conformal contact with the tissue surface or seamless three-dimensional (3D) biointegration. Flexible or even open-framework designs are essential in such methods. For chronic organ integration, the highest level of biocompatibility is required for both the materials and device configurations. Additionally, a scalable and high-throughput design is necessary to simultaneously interact with many individual cells in the organ. The physical, chemical, and mechanical stabilities of devices for organ implantation may be improved by ensuring matching of mechanical behavior at biointerfaces, including passivation or resistance designs to mitigate physiological impacts, or incorporating self-healing or adaptative properties. Recent research demonstrates principles of nanostructured material designs that can be used to improve biointerfaces. Nanoenabled extracellular interfaces were frequently used for either electrical or remote optical modulation of cells and tissues. In particular, methods are now available for designing and screening nanostructured silicon, especially chemical vapor deposition (CVD)-derived nanowires and two-dimensional (2D) nanostructured membranes, for biological modulation in vitro and in vivo. For intra- and intercellular biological modulation, semiconductor/cell composites have been created through the internalization of nanowires, and such cellular composites can even integrate with living tissues. This approach was demonstrated for both neuronal and cardiac modulation. At a different front, laser-derived nanocrystalline semiconductors showed electrochemical and photoelectrochemical activities, and they were used to modulate cells and organs. Recently, self-assembly of nanoscale building blocks enabled fabrication of efficient monolithic carbon-based electrodes for in vitro stimulation of cardiomyocytes, ex vivo stimulation of retinas and hearts, and in vivo stimulation of sciatic nerves. Future studies on nanoenabled bioelectrical modulation should focus on improving efficiency and stability of current and emerging technologies. New materials and devices can access new interrogation targets, such as subcellular structures, and possess more adaptable and responsive properties enabling seamless integration. Drawing inspiration from energy science and catalysis can help in such progress and open new avenues for biological modulation. The fundamental study of living bioelectronics could yield new cellular composites for diverse biological signaling control. In situ self-assembled biointerfaces are of special interest in this area as cell type targeting can be achieved.

Customizing MRI-Compatible Multifunctional Neural Interfaces through Fiber Drawing

Fiber drawing enables scalable fabrication of multifunctional flexible fibers that integrate electrical, optical and microfluidic modalities to record and modulate neural activity. Constraints on thermomechanical properties of materials, however, have prevented integrated drawing of metal electrodes with low-loss polymer waveguides for concurrent electrical recording and optical neuromodulation. Here we introduce two fabrication approaches: (1) an iterative thermal drawing with a soft, low melting temperature (Tm) metal indium, and (2) a metal convergence drawing with traditionally non-drawable high Tm metal tungsten. Both approaches deliver multifunctional flexible neural interfaces with low-impedance metallic electrodes and low-loss waveguides, capable of recording optically-evoked and spontaneous neural activity in mice over several weeks. We couple these fibers with a light-weight mechanical microdrive (1g) that enables depth-specific interrogation of neural circuits in mice following chronic implantation. Finally, we demonstrate the compatibility of these fibers with magnetic resonance imaging (MRI) and apply them to visualize the delivery of chemical payloads through the integrated channels in real time. Together, these advances expand the domains of application of the fiber-based neural probes in neuroscience and neuroengineering.

Chronic, Multi-Site Recordings Supported by Two Low-Cost, Stationary Probe Designs Optimized to Capture Either Single Unit or Local Field Potential Activity in Behaving Rats

Rodent models of cognitive behavior have greatly contributed to our understanding of human neuropsychiatric disorders. However, to elucidate the neurobiological underpinnings of such disorders or impairments, animal models are more useful when paired with methods for measuring brain function in awake, behaving animals. Standard tools used for systems-neuroscience level investigations are not optimized for large-scale and high-throughput behavioral battery testing due to various factors including cost, time, poor longevity, and selective targeting limited to measuring only a few brain regions at a time. Here we describe two different "user-friendly" methods for building extracellular electrophysiological probes that can be used to measure either single units or local field potentials in rats performing cognitive tasks. Both probe designs leverage several readily available, yet affordable, commercial products to facilitate ease of production and offer maximum flexibility in terms of brain-target locations that can be scalable (32-64 channels) based on experimental needs. Our approach allows neural activity to be recorded simultaneously with behavior and compared between micro (single unit) and more macro (local field potentials) levels of brain activity in order to gain a better understanding of how local brain regions and their connected networks support cognitive functions in rats. We believe our novel probe designs make collecting electrophysiology data easier and will begin to fill the gap in knowledge between basic and clinical research.

Restoring upper extremity function with brain-machine interfaces

One of the most exciting advances to emerge in neural interface technologies has been the development of real-time brain-machine interface (BMI) neuroprosthetic devices to restore upper extremity function. BMI neuroprostheses, made possible by synergistic advances in neural recording technologies, high-speed computation and signal processing, and neuroscience, have permitted the restoration of volitional movement to patients suffering the loss of upper-extremity function. In this chapter, we review the scientific and technological advances underlying these remarkable devices. After presenting an introduction to the current state of the field, we provide an accessible technical discussion of the two fundamental requirements of a successful neuroprosthesis: signal extraction from the brain and signal decoding that results in robust prosthetic control. We close with a presentation of emerging technologies that are likely to substantially advance the field.

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.

Anti-fouling peptide functionalization of ultraflexible neural probes for long-term neural activity recordings in the brain

Implantable neural probes constitute an essential tool for neuronal activity recordings in basic neuroscience and also hold great promise for the development of neuroprosthesis to restore lost motor or sensory functions of the body. However, conventional neural probes are susceptible to biofouling because of their physicochemical mismatch with neural tissues, resulting in signal degradation in chronic studies. Here, we describe an ultraflexible neural probe (uFNP) with anti-fouling zwitterionic peptide modification for long-term stable neural activity recordings. The anti-fouling zwitterionic peptide consists of two parts: negatively charged glutamic acid (E) and positively charged lysine (K) formed EKEKEK (EK) head to create a hydration layer that resists protein adsorption on the microelectrodes, and a fragment of laminin formed IKVAV tail to increase the adhesion of the microelectrodes to neuronal cells. We demonstrate that EK-IKVAV modified uFNPs can allow for stable neuronal activity recordings over 16 weeks. Immunohistological studies confirm that EK-IKVAV functionalized uFNPs could induce greatly reduced neuronal cell loss. Collectively, these results suggest that the anti-fouling zwitterionic peptide functionalization of uFNPs provide a promising route to construct biocompatible and stable neural interfaces.

Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia

OBJECTIVE

Individuals with neurological disease or injury such as amyotrophic lateral sclerosis, spinal cord injury or stroke may become tetraplegic, unable to speak or even locked-in. For people with these conditions, current assistive technologies are often ineffective. Brain-computer interfaces are being developed to enhance independence and restore communication in the absence of physical movement. Over the past decade, individuals with tetraplegia have achieved rapid on-screen typing and point-and-click control of tablet apps using intracortical brain-computer interfaces (iBCIs) that decode intended arm and hand movements from neural signals recorded by implanted microelectrode arrays. However, cables used to convey neural signals from the brain tether participants to amplifiers and decoding computers and require expert oversight, severely limiting when and where iBCIs could be available for use. Here, we demonstrate the first human use of a wireless broadband iBCI.

METHODS

Based on a prototype system previously used in pre-clinical research, we replaced the external cables of a 192-electrode iBCI with wireless transmitters and achieved high-resolution recording and decoding of broadband field potentials and spiking activity from people with paralysis. Two participants in an ongoing pilot clinical trial completed on-screen item selection tasks to assess iBCI-enabled cursor control.

RESULTS

Communication bitrates were equivalent between cabled and wireless configurations. Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications. Within-day comparison of cabled and wireless interfaces evaluated bit error rate, packet loss, and the recovery of spike rates and spike waveforms from the recorded neural signals. In a representative use case, the wireless system recorded intracortical signals from two arrays in one participant continuously through a 24-hour period at home.

SIGNIFICANCE

Wireless multi-electrode recording of broadband neural signals over extended periods introduces a valuable tool for human neuroscience research and is an important step toward practical deployment of iBCI technology for independent use by individuals with paralysis. On-demand access to high-performance iBCI technology in the home promises to enhance independence and restore communication and mobility for individuals with severe motor impairment.

Directions of Deep Brain Stimulation for Epilepsy and Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) is an effective treatment for movement disorders and neurological/psychiatric disorders. DBS has been approved for the control of Parkinson disease (PD) and epilepsy.

OBJECTIVES

A systematic review and possible future direction of DBS system studies is performed in the open loop and closed-loop configuration on PD and epilepsy.

METHODS

We searched Google Scholar database for DBS system and development. DBS search results were categorized into clinical device and research system from the open-loop and closed-loop perspectives.

RESULTS

We performed literature review for DBS on PD and epilepsy in terms of system development by the open loop and closed-loop configuration. This study described development and trends for DBS in terms of electrode, recording, stimulation, and signal processing. The closed-loop DBS system raised a more attention in recent researches.

CONCLUSION

We overviewed development and progress of DBS. Our results suggest that the closed-loop DBS is important for PD and epilepsy.

Sharpened and Mechanically Durable Carbon Fiber Electrode Arrays for Neural Recording

Bioelectric medicine treatments target disorders of the nervous system unresponsive to pharmacological methods. While current stimulation paradigms effectively treat many disorders, the underlying mechanisms are relatively unknown, and current neuroscience recording electrodes are often limited in their specificity to gross averages across many neurons or axons. Here, we develop a novel, durable carbon fiber electrode array adaptable to many neural structures for precise neural recording. Carbon fibers ( [Formula: see text] diameter) were sharpened using a reproducible blowtorchmethod that uses the reflection of fibers against the surface of a water bath. The arrays were developed by partially embedding carbon fibers in medical-grade silicone to improve durability. We recorded acute spontaneous electrophysiology from the rat cervical vagus nerve (CVN), feline dorsal root ganglia (DRG), and rat brain. Blowtorching resulted in fibers of 72.3 ± 33.5-degree tip angle with [Formula: see text] exposed carbon. Observable neural clusters were recorded using sharpened carbon fiber electrodes fromrat CVN ( [Formula: see text]), feline DRG ( [Formula: see text]), and rat brain ( [Formula: see text]). Recordings from the feline DRG included physiologically relevant signals from increased bladder pressure and cutaneous brushing. These results suggest that this carbon fiber array is a uniquely durable and adaptable neural recordingdevice. In the future, this device may be useful as a bioelectric medicine tool for diagnosis and closed-loop neural control of therapeutic treatments and monitoring systems.

Responsive manipulation of neural circuit pathology by fully implantable, front-end multiplexed embedded neuroelectronics

Responsive neurostimulation is increasingly required to probe neural circuit function and treat neuropsychiatric disorders. We introduce a multiplex-then-amplify (MTA) scheme that, in contrast to current approaches (which necessitate an equal number of amplifiers as number of channels), only requires one amplifier per multiplexer, significantly reducing the number of components and the size of electronics in multichannel acquisition systems. It also enables simultaneous stimulation of arbitrary waveforms on multiple independent channels. We validated the function of MTA by developing a fully implantable, responsive embedded system that merges the ability to acquire individual neural action potentials using conformable conducting polymer-based electrodes with real-time onboard processing, low-latency arbitrary waveform stimulation, and local data storage within a miniaturized physical footprint. We verified established responsive neurostimulation protocols and developed a network intervention to suppress pathological coupling between the hippocampus and cortex during interictal epileptiform discharges. The MTA design enables effective, self-contained, chronic neural network manipulation with translational relevance to the treatment of neuropsychiatric disease.

Energy harvesting optical modulators with sub-attojoule per bit electrical energy consumption

The light input to a semiconductor optical modulator can constitute an electrical energy supply through the photovoltaic effect, which is unexploited in conventional modulators. In this work, we leverage this effect to demonstrate a silicon modulator with sub-aJ/bit electrical energy consumption at sub-GHz speeds, relevant for massively parallel input/output systems such as neural interfaces. We use the parasitic photovoltaic current to self-charge the modulator and a single transistor to modulate the stored charge. This way, the electrical driver only needs to charge the nano-scale gate of the transistor, with attojoule-scale energy dissipation. We implement this ‘photovoltaic modulator’ in a monolithic CMOS platform. This work demonstrates how close integration and co-design of electronics and photonics offers a path to optical switching with as few as 500 injected electrons and electrical energy consumption as low as 20 zJ/bit, achieved only by recovering the absorbed optical energy that is wasted in conventional modulation.

Optical modulators are a critical component for many future applications. Here the authors present a photovoltaic modulator that uses photogenerated charges and a nanoscale switch to enable low power (attojoule level), GHz-speed modulation in a CMOS-compatible platform.

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

Advances in Carbon-Based Microfiber Electrodes for Neural Interfacing

Neural interfacing devices using penetrating microelectrode arrays have emerged as an important tool in both neuroscience research and medical applications. These implantable microelectrode arrays enable communication between man-made devices and the nervous system by detecting and/or evoking neuronal activities. Recent years have seen rapid development of electrodes fabricated using flexible, ultrathin carbon-based microfibers. Compared to electrodes fabricated using rigid materials and larger cross-sections, these microfiber electrodes have been shown to reduce foreign body responses after implantation, with improved signal-to-noise ratio for neural recording and enhanced resolution for neural stimulation. Here, we review recent progress of carbon-based microfiber electrodes in terms of material composition and fabrication technology. The remaining challenges and future directions for development of these arrays will also be discussed. Overall, these microfiber electrodes are expected to improve the longevity and reliability of neural interfacing devices.

The Argo: a high channel count recording system for neural recording in vivo

OBJECTIVE

Decoding neural activity has been limited by the lack of tools available to record from large numbers of neurons across multiple cortical regions simultaneously with high temporal fidelity. To this end, we developed the Argo system to record cortical neural activity at high data rates.

APPROACH

Here we demonstrate a massively parallel neural recording system based on platinum-iridium microwire electrode arrays bonded to a CMOS voltage amplifier array. The Argo system is the highest channel count in vivo neural recording system, supporting simultaneous recording from 65 536 channels, sampled at 32 kHz and 12-bit resolution. This system was designed for cortical recordings, compatible with both penetrating and surface microelectrodes.

MAIN RESULTS

We validated this system through initial bench testing to determine specific gain and noise characteristics of bonded microwires, followed by in-vivo experiments in both rat and sheep cortex. We recorded spiking activity from 791 neurons in rats and surface local field potential activity from over 30 000 channels in sheep.

SIGNIFICANCE

These are the largest channel count microwire-based recordings in both rat and sheep. While currently adapted for head-fixed recording, the microwire-CMOS architecture is well suited for clinical translation. Thus, this demonstration helps pave the way for a future high data rate intracortical implant.

Soft, Wireless and subdermally implantable recording and neuromodulation tools

Progress in understanding neuronal interaction and circuit behavior of the central and peripheral nervous system strongly relies on the advancement of tools that record and stimulate with high fidelity and specificity. Currently, devices used in exploratory research predominantly utilize cables or tethers to provide pathways for power supply, data communication, stimulus delivery and recording, which constrains the scope and use of such devices. In particular, the tethered connection, mechanical mismatch to surrounding soft tissues and bones frustrate the interface leading to irritation and limitation of motion of the subject, which in the case of fundamental and preclinical studies, impacts naturalistic behaviors of animals and precludes the use in experiments involving social interaction and ethologically relevant three-dimensional environments, limiting the use of current tools to mostly rodents and exclude species such as birds and fish. This review explores the current state-of-the-art in wireless, subdermally implantable tools that quantitively expand capabilities in analysis and perturbation of the central and peripheral nervous system by removing tethers and externalized features of implantable neuromodulation and recording tools. Specifically, the review explores power harvesting strategies, wireless communication schemes, and soft materials and mechanics that enable the creation of such devices and discuss their capabilities in the context of freely-behaving subjects. Highlights of this class of devices includes wireless battery-free and fully implantable operation with capabilities in cell specific recording, multimodal neural stimulation and electrical, optogenetic and pharmacological neuromodulation capabilities. We conclude with discussion on translation of such technologies which promises routes towards broad dissemination.

3D Interfacing between Soft Electronic Tools and Complex Biological Tissues

Recent developments in soft functional materials have created opportunities for building bioelectronic devices with tissue-like mechanical properties. Their integration with the human body could enable advanced sensing and stimulation for medical diagnosis and therapies. However, most of the available soft electronics are constructed as planar sheets, which are difficult to interface with the target organs and tissues that have complex 3D structures. Here, the recent approaches are highlighted to building 3D interfaces between soft electronic tools and complex biological organs and tissues. Examples involve mesh devices for conformal contact, imaging-guided fabrication of organ-specific electronics, miniaturized probes for neurointerfaces, instrumented scaffold for tissue engineering, and many other soft 3D systems. They represent diverse routes for reconciling the interfacial mismatches between electronic tools and biological tissues. The remaining challenges include device scaling to approach the complexity of target organs, biological data acquisition and processing, 3D manufacturing techniques, etc., providing a range of opportunities for scientific research and technological innovation.

From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior

Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity in vivo as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.

How is flexible electronics advancing neuroscience research?

Innovative neurotechnology must be leveraged to experimentally answer the multitude of pressing questions in modern neuroscience. Driven by the desire to address the existing neuroscience problems with newly engineered tools, we discuss in this review the benefits of flexible electronics for neuroscience studies. We first introduce the concept and define the properties of flexible and stretchable electronics. We then categorize the four dimensions where flexible electronics meets the demands of modern neuroscience: chronic stability, interfacing multiple structures, multi-modal compatibility, and neuron-type-specific recording. Specifically, with the bending stiffness now approaching that of neural tissue, implanted flexible electronic devices produce little shear motion, minimizing chronic immune responses and enabling recording and stimulation for months, and even years. The unique mechanical properties of flexible electronics also allow for intimate conformation to the brain, the spinal cord, peripheral nerves, and the retina. Moreover, flexible electronics enables optogenetic stimulation, microfluidic drug delivery, and neural activity imaging during electrical stimulation and recording. Finally, flexible electronics can enable neuron-type identification through analysis of high-fidelity recorded action potentials facilitated by its seamless integration with the neural circuitry. We argue that flexible electronics will play an increasingly important role in neuroscience studies and neurological therapies via the fabrication of neuromorphic devices on flexible substrates and the development of enhanced methods of neuronal interpenetration.

Recent advances in bioelectronics chemistry

Research in bioelectronics is highly interdisciplinary, with many new developments being based on techniques from across the physical and life sciences. Advances in our understanding of the fundamental chemistry underlying the materials used in bioelectronic applications have been a crucial component of many recent discoveries. In this review, we highlight ways in which a chemistry-oriented perspective may facilitate novel and deep insights into both the fundamental scientific understanding and the design of materials, which can in turn tune the functionality and biocompatibility of bioelectronic devices. We provide an in-depth examination of several developments in the field, organized by the chemical properties of the materials. We conclude by surveying how some of the latest major topics of chemical research may be further integrated with bioelectronics.

Recent advances in bioelectronics chemistry

Research in bioelectronics is highly interdisciplinary, with many new developments being based on techniques from across the physical and life sciences. Advances in our understanding of the fundamental chemistry underlying the materials used in bioelectronic applications have been a crucial component of many recent discoveries. In this review, we highlight ways in which a chemistry-oriented perspective may facilitate novel and deep insights into both the fundamental scientific understanding and the design of materials, which can in turn tune the functionality and biocompatibility of bioelectronic devices. We provide an in-depth examination of several developments in the field, organized by the chemical properties of the materials. We conclude by surveying how some of the latest major topics of chemical research may be further integrated with bioelectronics.

Recent Advances in Electrical Neural Interface Engineering: Minimal Invasiveness, Longevity, and Scalability

Electrical neural interfaces serve as direct communication pathways that connect the nervous system with the external world. Technological advances in this domain are providing increasingly more powerful tools to study, restore, and augment neural functions. Yet, the complexities of the nervous system give rise to substantial challenges in the design, fabrication, and system-level integration of these functional devices. In this review, we present snapshots of the latest progresses in electrical neural interfaces, with an emphasis on advances that expand the spatiotemporal resolution and extent of mapping and manipulating brain circuits. We include discussions of large-scale, long-lasting neural recording; wireless, miniaturized implants; signal transmission, amplification, and processing; as well as the integration of interfaces with optical modalities. We outline the background and rationale of these developments and share insights into the future directions and new opportunities they enable.

Computational challenges and opportunities for a bi-directional artificial retina

A future artificial retina that can restore high acuity vision in blind people will rely on the capability to both read (observe) and write (control) the spiking activity of neurons using an adaptive, bi-directional and high-resolution device. Although current research is focused on overcoming the technical challenges of building and implanting such a device, exploiting its capabilities to achieve more acute visual perception will also require substantial computational advances. Using high-density large-scale recording and stimulation in the primate retina with an ex vivo multi-electrode array lab prototype, we frame several of the major computational problems, and describe current progress and future opportunities in solving them. First, we identify cell types and locations from spontaneous activity in the blind retina, and then efficiently estimate their visual response properties by using a low-dimensional manifold of inter-retina variability learned from a large experimental dataset. Second, we estimate retinal responses to a large collection of relevant electrical stimuli by passing current patterns through an electrode array, spike sorting the resulting recordings and using the results to develop a model of evoked responses. Third, we reproduce the desired responses for a given visual target by temporally dithering a diverse collection of electrical stimuli within the integration time of the visual system. Together, these novel approaches may substantially enhance artificial vision in a next-generation device.

Classifying Intracortical Brain-Machine Interface Signal Disruptions Based on System Performance and Applicable Compensatory Strategies: A Review

Brain-machine interfaces (BMIs) record and translate neural activity into a control signal for assistive or other devices. Intracortical microelectrode arrays (MEAs) enable high degree-of-freedom BMI control for complex tasks by providing fine-resolution neural recording. However, chronically implanted MEAs are subject to a dynamic in vivo environment where transient or systematic disruptions can interfere with neural recording and degrade BMI performance. Typically, neural implant failure modes have been categorized as biological, material, or mechanical. While this categorization provides insight into a disruption's causal etiology, it is less helpful for understanding degree of impact on BMI function or possible strategies for compensation. Therefore, we propose a complementary classification framework for intracortical recording disruptions that is based on duration of impact on BMI performance and requirement for and responsiveness to interventions: (1) Transient disruptions interfere with recordings on the time scale of minutes to hours and can resolve spontaneously; (2) Reversible disruptions cause persistent interference in recordings but the root cause can be remedied by an appropriate intervention; (3) Irreversible compensable disruptions cause persistent or progressive decline in signal quality, but their effects on BMI performance can be mitigated algorithmically; and (4) Irreversible non-compensable disruptions cause permanent signal loss that is not amenable to remediation or compensation. This conceptualization of intracortical BMI disruption types is useful for highlighting specific areas for potential hardware improvements and also identifying opportunities for algorithmic interventions. We review recording disruptions that have been reported for MEAs and demonstrate how biological, material, and mechanical mechanisms of disruption can be further categorized according to their impact on signal characteristics. Then we discuss potential compensatory protocols for each of the proposed disruption classes. Specifically, transient disruptions may be minimized by using robust neural decoder features, data augmentation methods, adaptive machine learning models, and specialized signal referencing techniques. Statistical Process Control methods can identify reparable disruptions for rapid intervention. In-vivo diagnostics such as impedance spectroscopy can inform neural feature selection and decoding models to compensate for irreversible disruptions. Additional compensatory strategies for irreversible disruptions include information salvage techniques, data augmentation during decoder training, and adaptive decoding methods to down-weight damaged channels.

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.

Cellular-scale silicon probes for high-density, precisely localized neurophysiology

Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared with the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at a cellular scale (5 × 10 µm cross section), with ultra-high-density packing (as little as 66 µm between shanks) and 64 or 256 closely spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and record large spikes in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal µ-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits and potentially for human brain-machine interfaces.NEW & NOTEWORTHY Devices with many electrodes penetrating into the brain are an important tool for investigating neural information processing, but they are typically large compared with neurons. This results in substantial damage and makes it harder to reconstruct recording locations within brain circuits. This paper presents high-channel-count silicon probes with much smaller features and a method for slicing through probe, brain, and skull all together. This allows probe tips to be directly observed relative to immunohistochemical markers.

A biohybrid synapse with neurotransmitter-mediated plasticity

Brain-inspired computing paradigms have led to substantial advances in the automation of visual and linguistic tasks by emulating the distributed information processing of biological systems¹. The similarity between artificial neural networks (ANNs) and biological systems has inspired ANN implementation in biomedical interfaces including prosthetics² and brain-machine interfaces³. While promising, these implementations rely on software to run ANN algorithms. Ultimately, it is desirable to build hardware ANNs^4,5 that can both directly interface with living tissue and adapt based on biofeedback^6,7. The first essential step towards biologically integrated neuromorphic systems is to achieve synaptic conditioning based on biochemical signalling activity. Here, we directly couple an organic neuromorphic device with dopaminergic cells to constitute a biohybrid synapse with neurotransmitter-mediated synaptic plasticity. By mimicking the dopamine recycling machinery of the synaptic cleft, we demonstrate both long-term conditioning and recovery of the synaptic weight, paving the way towards combining artificial neuromorphic systems with biological neural networks.

A biohybrid synapse with neurotransmitter-mediated plasticity

Brain-inspired computing paradigms have led to substantial advances in the automation of visual and linguistic tasks by emulating the distributed information processing of biological systems¹. The similarity between artificial neural networks (ANNs) and biological systems has inspired ANN implementation in biomedical interfaces including prosthetics² and brain-machine interfaces³. While promising, these implementations rely on software to run ANN algorithms. Ultimately, it is desirable to build hardware ANNs^4,5 that can both directly interface with living tissue and adapt based on biofeedback^6,7. The first essential step towards biologically integrated neuromorphic systems is to achieve synaptic conditioning based on biochemical signalling activity. Here, we directly couple an organic neuromorphic device with dopaminergic cells to constitute a biohybrid synapse with neurotransmitter-mediated synaptic plasticity. By mimicking the dopamine recycling machinery of the synaptic cleft, we demonstrate both long-term conditioning and recovery of the synaptic weight, paving the way towards combining artificial neuromorphic systems with biological neural networks.

CHIME: CMOS-Hosted in vivo Microelectrodes for Massively Scalable Neuronal Recordings

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at high spatiotemporal resolution have been difficult to scale. The most intensively studied mammalian neuronal networks, such as the neocortex, show a layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the three-dimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics. Here, we discuss a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from high-density CMOS in vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<25 μV RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 μm) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area, which is largely independent of the core diameter. We show that the microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and we demonstrate that microwire arrays can stably record single-unit activity. Combining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress in electrical neuronal recordings to the rapid progress in silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to extend a two-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays, such as electrical stimulation devices.

Recent advances in neural interfaces-Materials chemistry to clinical translation

Implantable neural interfaces are important tools to accelerate neuroscience research and translate clinical neurotechnologies. The promise of a bidirectional communication link between the nervous system of humans and computers is compelling, yet important materials challenges must be first addressed to improve the reliability of implantable neural interfaces. This perspective highlights recent progress and challenges related to arguably two of the most common failure modes for implantable neural interfaces: (1) compromised barrier layers and packaging leading to failure of electronic components; (2) encapsulation and rejection of the implant due to injurious tissue-biomaterials interactions, which erode the quality and bandwidth of signals across the biology-technology interface. Innovative materials and device design concepts could address these failure modes to improve device performance and broaden the translational prospects of neural interfaces. A brief overview of contemporary neural interfaces is presented and followed by recent progress in chemistry, materials, and fabrication techniques to improve in vivo reliability, including novel barrier materials and harmonizing the various incongruences of the tissue-device interface. Challenges and opportunities related to the clinical translation of neural interfaces are also discussed.

Spikes to Pixels: Camera Chips for Large-scale Electrophysiology

Implanted neural probes are among the most important techniques in both fundamental and clinical neuroscience. Despite great successes and promise, neural electrodes are technically limited by their scalability. A recent study by Obaid et al. demonstrated an innovative way to greatly scale up the channel count and density of neural electrode arrays.

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.