The Pursuit of Chronically Reliable Neural Interfaces: A Materials Perspective

Effects of nanostructuration on the electrochemical performance of metallic bioelectrodes

The use of metallic nanostructures in the fabrication of bioelectrodes (e.g., neural implants) is gaining attention nowadays. Nanostructures provide increased surface area that might benefit the performance of bioelectrodes. However, there is a need for comprehensive studies that assess electrochemical performance of nanostructured surfaces in physiological and relevant working conditions. Here, we introduce a versatile scalable fabrication method based on magnetron sputtering to develop analogous metallic nanocolumnar structures (NCs) and thin films (TFs) from Ti, Au, and Pt. We show that NCs contribute significantly to reduce the impedance of metallic surfaces. Charge storage capacity of Pt NCs is remarkably higher than that of Pt TFs and that of the other metals in both morphologies. Circuit simulations of the electrode/electrolyte interface show that the signal delivered in voltage-controlled systems is less filtered when nanocolumns are used. In a current-controlled system, simulation shows that NCs provide safer stimulation conditions compared to TFs. We have assessed the durability of NCs and TFs for potential use in vivo by reactive accelerated aging test, mimicking one-year in vivo implantation. Although each metal/morphology reveals a unique response to aging, NCs show overall more stable electrochemical properties compared to TFs in spite of their porous structure.

Toward living neuroprosthetics: developing a biological brain pacemaker as a living neuromodulatory implant for improving parkinsonian symptoms

Objective.Therapeutic intervention for Parkinson's disease (PD) via deep brain stimulation (DBS) represents the current paradigm for managing the advanced stages of the disease in patients when treatment with pharmaceuticals becomes inadequate. Although DBS is the prevailing therapy in these cases, the overall effectiveness and reliability of DBS can be diminished over time due to hardware complications and biocompatibility issues with the electronic implants. To achieve a lifetime solution, we envision that the next generation of neural implants will be entirely 'biological' and 'autologous', both physically and functionally. Thus, in this study, we set forth toward developing a biological brain pacemaker for treating PD. Our focus is to investigate engineering strategies for creating a multicellular biological circuit that integrates innate biological design and function while incorporating principles of neuromodulation to create a biological mechanism for delivering high-frequency stimulation with cellular specificity.Approach.We engineer a 3D multicellular circuit design built entirely from biological and biocompatible components using established tissue engineering protocols to demonstrate the feasibility of creating a living neural implant. Furthermore, using 2D co-culture systems, we investigate the physiologically relevant parameters that would be necessary to further develop a therapeutic benefit of high-frequency stimulation with cellular specificity within our construct design.Main results.Our results demonstrate the feasibility of fabricating a 3D multicellular circuit device in an implantable form. Furthermore, we show we can organize cellular materials to create potential functional connections in normal physiological conditions, thus laying down the foundation of designing a high-frequency pacing system for selective and controlled therapeutic neurostimulation.Significance.The findings from this study may lead to the future development of autologous living neural implants that both circumvent the issues inherent in electronic neural implants and form more biocompatible devices with lifelong robustness to repair and restore motor functions, with the ultimate benefit for patients with PD.

Microtopographical patterns promote different responses in fibroblasts and Schwann cells: A possible feature for neural implants

The chronic reliability of bioelectronic neural interfaces has been challenged by foreign body reactions (FBRs) resulting in fibrotic encapsulation and poor integration with neural tissue. Engineered microtopographies could alleviate these challenges by manipulating cellular responses to the implanted device. Parallel microchannels have been shown to modulate neuronal cell alignment and axonal growth, and Sharklet™ microtopographies of targeted feature sizes can modulate bio-adhesion of an array of bacteria, marine organisms, and epithelial cells due to their unique geometry. We hypothesized that a Sharklet™ micropattern could be identified that inhibited fibroblasts partially responsible for FBR while promoting Schwann cell proliferation and alignment. in vitro cell assays were used to screen the effect of Sharklet™ and channel micropatterns of varying dimensions from 2 to 20 μm on fibroblast and Schwann cell metrics (e.g., morphology/alignment, nuclei count, metabolic activity), and a hierarchical analysis of variance was used to compare treatments. In general, Schwann cells were found to be more metabolically active and aligned than fibroblasts when compared between the same pattern. 20 μm wide channels spaced 2 μm apart were found to promote Schwann cell attachment and alignment while simultaneously inhibiting fibroblasts and warrant further in vivo study on neural interface devices. No statistically significant trends between cellular responses and geometrical parameters were identified because mammalian cells can change their morphology dependent on their environment in a manner dissimilar to bacteria. Our results showed although surface patterning is a strong physical tool for modulating cell behavior, responses to micropatterns are highly dependent on the cell type.

Neural signal analysis with memristor arrays towards high-efficiency brain-machine interfaces

Brain-machine interfaces are promising tools to restore lost motor functions and probe brain functional mechanisms. As the number of recording electrodes has been exponentially rising, the signal processing capability of brain–machine interfaces is falling behind. One of the key bottlenecks is that they adopt conventional von Neumann architecture with digital computation that is fundamentally different from the working principle of human brain. In this work, we present a memristor-based neural signal analysis system, where the bio-plausible characteristics of memristors are utilized to analyze signals in the analog domain with high efficiency. As a proof-of-concept demonstration, memristor arrays are used to implement the filtering and identification of epilepsy-related neural signals, achieving a high accuracy of 93.46%. Remarkably, our memristor-based system shows nearly 400× improvements in the power efficiency compared to state-of-the-art complementary metal-oxide-semiconductor systems. This work demonstrates the feasibility of using memristors for high-performance neural signal analysis in next-generation brain–machine interfaces.

Designing energy efficient and high performance brain-machine interfaces with millions of recording electrodes for in-situ analysis remains a challenge. Here, the authors develop a memristor-based neural signal analysis system capable of filtering and identifying epilepsy-related brain activities with an accuracy of 93.46%.

Precision electronic medicine in the brain

Periodically throughout history developments from adjacent fields of science and technology reach a tipping point where together they produce unparalleled advances, such as the Allen Brain Atlas and the Human Genome Project. Today, research focused at the interface between the nervous system and electronics is not only leading to advances in fundamental neuroscience, but also unlocking the potential of implants capable of cellular-level therapeutic targeting. Ultimately, these personalized electronic therapies will provide new treatment modalities for neurodegenerative and neuropsychiatric illness; powerful control of prosthetics for restorative function in degenerative diseases, trauma and amputation; and even augmentation of human cognition. Overall, we believe that emerging advances in tissue-like electronics will enable minimally invasive devices capable of establishing a stable long-term cellular neural interface and providing long-term treatment for chronic neurological conditions.

Neuromodulation of metabolic functions: from pharmaceuticals to bioelectronics to biocircuits

Neuromodulation of central and peripheral neural circuitry brings together neurobiologists and neural engineers to develop advanced neural interfaces to decode and recapitulate the information encoded in the nervous system. Dysfunctional neuronal networks contribute not only to the pathophysiology of neurological diseases, but also to numerous metabolic disorders. Many regions of the central nervous system (CNS), especially within the hypothalamus, regulate metabolism. Recent evidence has linked obesity and diabetes to hyperactive or dysregulated autonomic nervous system (ANS) activity. Neural regulation of metabolic functions provides access to control pathology through neuromodulation. Metabolism is defined as cellular events that involve catabolic and/or anabolic processes, including control of systemic metabolic functions, as well as cellular signaling pathways, such as cytokine release by immune cells. Therefore, neuromodulation to control metabolic functions can be used to target metabolic diseases, such as diabetes and chronic inflammatory diseases. Better understanding of neurometabolic circuitry will allow for targeted stimulation to modulate metabolic functions. Within the broad category of metabolic functions, cellular signaling, including the production and release of cytokines and other immunological processes, is regulated by both the CNS and ANS. Neural innervations of metabolic (e.g. pancreas) and immunologic (e.g. spleen) organs have been understood for over a century, however, it is only now becoming possible to decode the neuronal information to enable exogenous controls of these systems. Future interventions taking advantage of this progress will enable scientists, engineering and medical doctors to more effectively treat metabolic diseases.

Stimulation of peripheral nerves using conductive hydrogel electrodes

Nerve block via electrical stimulation of nerves requires a device capable of transferring large amounts of charge across the neural interface on chronic time scales. Current metal electrode designs are limited in their ability to safely and effectively deliver this charge in a stable manner. Conductive hydrogel (CH) coatings are a promising alternative to metal electrodes for neural interfacing devices. This study assessed the performance of CH electrodes compared to platinum-iridium (PtIr) electrodes in commercial nerve cuff devices in both the in vitro and acute in vivo environments. CH electrodes were found to have higher charge storage capacities and lower impedances compared to bare PtIr electrodes. Application of CH coatings also resulted in a three-fold increase in in vivo charge injection limit. These significant improvements in electrochemical properties will allow for the design of smaller and safer stimulating devices for nerve block applications.

Conductive Hydrogel Electrodes for Delivery of Long-Term High Frequency Pulses

Nerve block waveforms require the passage of large amounts of electrical energy at the neural interface for extended periods of time. It is desirable that such waveforms be applied chronically, consistent with the treatment of protracted immune conditions, however current metal electrode technologies are limited in their capacity to safely deliver ongoing stable blocking waveforms. Conductive hydrogel (CH) electrode coatings have been shown to improve the performance of conventional bionic devices, which use considerably lower amounts of energy than conventional metal electrodes to replace or augment sensory neuron function. In this study the application of CH materials was explored, using both a commercially available platinum iridium (PtIr) cuff electrode array and a novel low-cost stainless steel (SS) electrode array. The CH was able to significantly increase the electrochemical performance of both array types. The SS electrode coated with the CH was shown to be stable under continuous delivery of 2 mA square pulse waveforms at 40,000 Hz for 42 days. CH coatings have been shown as a beneficial electrode material compatible with long-term delivery of high current, high energy waveforms.

Nanomaterials at the neural interface

Interfacing the nervous system with devices able to efficiently record or modulate the electrical activity of neuronal cells represents the underlying foundation of future theranostic applications in neurology and of current openings in neuroscience research. These devices, usually sensing cell activity via microelectrodes, should be characterized by safe working conditions in the biological milieu together with a well-controlled operation-life. The stable device/neuronal electrical coupling at the interface requires tight interactions between the electrode surface and the cell membrane. This neuro-electrode hybrid represents the hyphen between the soft nature of neural tissue, generating electrical signals via ion motions, and the rigid realm of microelectronics and medical devices, dealing with electrons in motion. Efficient integration of these entities is essential for monitoring, analyzing and controlling neuronal signaling but poses significant technological challenges. Improving the cell/electrode interaction and thus the interface performance requires novel engineering of (nano)materials: tuning at the nanoscale electrode's properties may lead to engineer interfacing probes that better camouflaged with their biological target. In this brief review, we highlight the most recent concepts in nanotechnologies and nanomaterials that might help reducing the mismatch between tissue and electrode, focusing on the device's mechanical properties and its biological integration with the tissue.