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Neural implants have the potential to restore visual capabilities in blind individuals by electrically stimulating the neurons of the visual system. This stimulation can produce visual percepts known as phosphenes. The ideal location of electrical stimulation for achieving vision restoration is widely debated and dependent on the physiological properties of the targeted tissue. Here, the neurophysiology of several potential target structures within the visual system will be explored regarding their benefits and downfalls in producing phosphenes. These regions will include the lateral geniculate nucleus, primary visual cortex, visual area 2, visual area 3, visual area 4 and the middle temporal area. Based on the existing engineering limitations of neural prostheses, we anticipate that electrical stimulation of any singular brain region will be incapable of achieving high-resolution naturalistic perception including color, texture, shape and motion. As improvements in visual acuity facilitate improvements in quality of life, emulating naturalistic vision should be one of the ultimate goals of visual prostheses. To achieve this goal, we propose that multiple brain areas will need to be targeted in unison enabling different aspects of vision to be recreated.

Purpose GammaTile cesium-131 (131Cs) permanent brain implant has received Food and Drug Administration (FDA) clearance as a promising treatment for certain brain tumors. Our center was the first institution in the United States after FDA clearance to offer the clinical use of GammaTile brachytherapy outside of a clinical trial. The purpose of this work is to aid the medical physicist and radiation oncologist in implementing this collagen carrier tile brachytherapy (CTBT) program in their practice. Methods A total of 23 patients have been treated with GammaTile to date at our center. Treatment planning system (TPS) commissioning was performed by configuring the parameters for the 131Cs (IsoRay Model CS-1, Rev2) source, and doses were validated with the consensus data from the American Association of Physicists in Medicine TG-43U1S2. Implant procedures, dosimetry, postimplant planning, and target delineations were established based on our clinical experience. Radiation safety aspects were evaluated based on exposure rate measurements of implanted patients, as well as body and ring badge measurements. Results An estimated timeframe of the GammaTile clinical responsibilities for the medical physicist, radiation oncologist, and neurosurgeon is presented. TPS doses were validated with published dose to water for 131Cs. Clinical aspects, including estimation of the number of tiles, treatment planning, dosimetry, and radiation safety considerations, are presented. Conclusion The implementation of the GammaTile program requires collaboration from multiple specialties, including medical physics, radiation oncology, and neurosurgery. This manuscript provides a roadmap for the implementation of this therapy.

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Novel neural stimulation protocols mimicking biological signals and patterns have demonstrated significant advantages as compared to traditional protocols based on uniform periodic square pulses. At the same time, the treatments for neural disorders which employ such protocols require the stimulator to be integrated into miniaturized wearable devices or implantable neural prostheses. Unfortunately, most miniaturized stimulator designs show none or very limited ability to deliver biomimetic protocols due to the architecture of their control logic, which generates the waveform. Most such designs are integrated into a single System-on-Chip (SoC) for the size reduction and the option to implement them as neural implants. But their on-chip stimulation controllers are fixed and limited in memory and computing power, preventing them from accommodating the amplitude and timing variances, and the waveform data parameters necessary to output biomimetic stimulation. To that end, a new stimulator architecture is proposed, which distributes the control logic over three component tiers – software, microcontroller firmware and digital circuits of the SoC, which is compatible with existing and future biomimetic protocols and with integration into implantable neural prosthetics. A portable prototype with the proposed architecture is designed and demonstrated in a bench-top test with various known biomimetic output waveforms. The prototype is also tested in vivo to deliver a complex, continuous biomimetic stimulation to a rat model of a spinal-cord injury. By delivering this unique biomimetic stimulation, the device is shown to successfully reestablish the connectivity of the spinal cord post-injury and thus restore motor outputs in the rat model.

Several recent studies have reported improved histological and electrophysiological outcomes with soft neural interfaces that have elastic moduli ranging from 10 s of kPa to hundreds of MPa. However, many of these soft interfaces use custom fabrication processes. We test the hypothesis that a readily adoptable fabrication process for only coating the tips of microelectrodes with soft brain-like (elastic modulus of ~5 kPa) material improves the long-term electrical performance of neural interfaces. Conventional tungsten microelectrodes (n = 9 with soft coatings and n = 6 uncoated controls) and Pt/Ir microelectrodes (n = 16 with soft coatings) were implanted in six animals for durations ranging from 5 weeks to over 1 year in a subset of rats. Electrochemical impedance spectroscopy was used to assess the quality of the brain tissue–electrode interface under chronic conditions. Neural recordings were assessed for unit activity and signal quality. Electrodes with soft, silicone coatings showed relatively stable electrical impedance characteristics over 6 weeks to &gt, 1 year compared to the uncoated control electrodes. Single unit activity recorded by coated electrodes showed larger peak-to-peak amplitudes and increased number of detectable neurons compared to uncoated controls over 6–7 weeks. We demonstrate the feasibility of using a readily translatable process to create brain-like soft interfaces that can potentially overcome variable performance associated with chronic rigid neural interfaces.

Effective methods of producing instantaneous and irreversible unconsciousness at the time of slaughter are crucial for ensuring animal welfare in commercial aquaculture. However, the traditional method of visually evaluating unconsciousness has been shown to be insufficient and may lead to misjudgements of stunning efficiency. In this study, we developed a non‐invasive technique that measures brain activity in fish as an alternative to traditional invasive, brain implants and used it to determine when a change in consciousness occurs in trout during anaesthesia induction. Nine rainbow trout (Oncorhynchus mykiss) were equipped with a custom designed silicone cup fitted with electrodes and submerged in 10°C water with dissolved MS‐222. During anaesthesia, the state of consciousness was assessed by recordings of electroencephalogram (EEG). The EEG recordings were analysed both by visually evoked responses from light stimulation (VERs) and from changes in signal amplitude, median frequency and relative signal power. According to the loss of VERs and decrease in signal amplitude, trout transitioned to surgical depth of anaesthesia within 5 min. Our results show that consciousness, or loss of, can be determined using a non‐invasive system to record EEG in fish.

BACKGROUND: Ensemble recording methods are pervasive in basic and clinical neuroscience research. Invasive neural implants are used in patients with drug resistant epilepsy to localize seizure origin, in neuropsychiatric or Parkinson’s patients to alleviate symptoms via deep brain simulation (DBS), and with animal models to conduct basic research. Studies addressing the brain’s physiological response to chronic electrode implants demonstrate that the mechanical trauma of insertion is followed by an acute inflammatory response as well as a chronic foreign body response. Despite use of invasive recording methods with animal models and humans, little is known of their effect on behavior in healthy populations. OBJECTIVE: To quantify the effect of chronic electrode implantation targeting the hippocampus on recognition memory performance. METHODS: Four healthy female rhesus macaques were tested in a delayed nonmatching-to-sample (DNMS) recognition memory task before and after hippocampal implantation with a tetrode array device. RESULTS: Trials to criterion and recognition memory performance were not significantly different before versus after chronic electrode implantation. CONCLUSION: Our results suggest that chronic implants did not produce significant impairments on DNMS performance.

Spatio-temporally controlled drug release based on conducting polymer films offers a powerful technology to improve the tissue integration for implantable neuroprobes. We here explore the release efficiency of such systems in order to improve the understanding of the release mechanism and allow for optimized implementation of this technology into future drug release applications. By exposing drug loaded PEDOT coatings of different thicknesses to a multitude of release signals, along with optimizing the steps during the polymer synthesis, we could identify a highly reproducible electrostatically controlled drug release next to a slow diffusion driven release component. The release efficiency was moreover observed to be higher for a cyclic voltammetry signal in comparison to release driven by a constant potential. Biphasic current pulses, as used during neural stimulation, did not allow for long enough diffusion times to yield efficient active drug expulsion from the polymer films. A quantitative analysis could confirm an overall linear dependency between drug release and film thickness. The amount of drug released in response to the trigger signals was however not linearly correlated with the amount of charge applied. By combining these findings we could develop a model which accurately describes the drug release mechanism from a PEDOT film. The proposed model thereby points the way for how actively controlled, and diffusion related, release can be tuned for obtaining delivery dynamics tailored to specific applications.

Multichannel connectors enable part-replacement of implanted active neural interfaces. For pre-clinical investigation, commercially available miniature connectors enable high channel counts with reduced size and cost. In this paper, Omnetics Nano Circular connectors were encapsulated with medical grade silicone, and assembled using an approach proposed used in surgery. Three 11-pin connectors were tested in PBS for 336 days with cyclic loading for a total of 66 days. A single connector failed with current leakage between channels due to moisture at the connecting interface, and with corrosion at 3 solder joints. The surviving connectors maintained a low contact impedance and high between-channel impedance over 336 days. Inspection of the failed sample emphasizes the need for stress relief near implanted connectors and void-free encapsulation.

Recent developments in the ability to measure neural activity including surface and penetrating microelectrode arrays have allowed for higher-resolution and higher-dimension measurements of neural activity. With the development of this technology also arises the need for analytical methods to enable interpretation of these measurements in the context of underlying neural dynamics and processes. In this paper, we examine the application of methods such as current source density (CSD), histogram correlation, and radial profile analysis for quantifying the spatiotemporal characteristics of neural dynamics in both simulated and recorded local field potential (LFP) data.

Efficient ultrasonic beamforming to millimeter-scale neural implants can reduce implant volume, improve tolerance to misalignment, and allow multiple implants to be operated simultaneously. This work proposes the use of time reversal, a computationally simple approach to beamforming that is robust despite scattering and inhomogeneity of the acoustic medium. A custom ultrasound phased array system is used to demonstrate beam focusing and steering both in a liquid phantom and through tissue. Time reversal is experimentally compared with other beamforming techniques by measuring energy transfer efficiency at varying depths and angles. Simultaneous power delivery to multiple implants is also demonstrated.

Neural implants for closed-loop therapeutic neuromodulation – recording, processing, and delivering state and activity dependent neural stimulation to targeted regions of interest (ROIs) in the brain – are emerging as critical enablers of ground-breaking treatments of a wide range of neurological diseases and disorders. While existing systems [1 –4] deliver electrical stimulation by placing electrodes in close proximity to target neurons, the capability for low-latency configurable stimulation that is spatially localized remains unrealized. Meanwhile, architectures that enable uninterrupted recording, maintain high voltage compliance and achieve excellent charge balance remain critical for implantable stimulators.

In the last years, neurological diseases have resulted in a global health issue, representing the first cause of disability worldwide. Current therapeutic approaches against neurological disorders include oral, topical, or intravenous administration of drugs and more invasive techniques such as surgery and brain implants. Unfortunately, at present, there are no fully effective treatments against neurodegenerative diseases, because they are not associated with a regeneration of the neural tissue but rather act on slowing the neurodegenerative process. The main limitation of central nervous system therapeutics is related to their delivery to the nervous system in therapeutic quantities due to the presence of the blood–brain barrier. In this regard, recently, the intranasal route has emerged as a promising administration site for central nervous system therapeutics since it provides a direct connection to the central nervous system, avoiding the passage through the blood–brain barrier, consequently increasing drug cerebral bioavailability. This review provides an overview of the nose-to-brain route: first, we summarize the anatomy of this route, focusing on the neural mechanisms responsible for the delivery of central nervous system therapeutics to the brain, and then we discuss the recent advances made on the design of intranasal drug delivery systems of central nervous system therapeutics to the brain, focusing in particular on stimuli-responsive hydrogels.

An essential method to investigate neuromodulation effects of an invasive neural interface (INI) is magnetic resonance imaging (MRI). Presently, MRI imaging of patients with neural implants is highly restricted in high field MRI (e.g., 3 T and higher) due to patient safety concerns. This results in lower resolution MRI images and, consequently, degrades the efficacy of MRI imaging for diagnostic purposes in these patients. Cubic silicon carbide (3C-SiC) is a biocompatible wide-band-gap semiconductor with a high thermal conductivity and magnetic susceptibility compatible with brain tissue. It also has modifiable electrical conductivity through doping level control. These properties can improve the MRI compliance of 3C-SiC INIs, specifically in high field MRI scanning. In this work, the MRI compliance of epitaxial SiC films grown on various Si wafers, used to implement a monolithic neural implant (all-SiC), was studied. Via finite element method (FEM) and Fourier-based simulations, the specific absorption rate (SAR), induced heating, and image artifacts caused by the portion of the implant within a brain tissue phantom located in a 7 T small animal MRI machine were estimated and measured. The specific goal was to compare implant materials, thus, the effect of leads outside the tissue was not considered. The results of the simulations were validated via phantom experiments in the same 7 T MRI system. The simulation and experimental results revealed that free-standing 3C-SiC films had little to no image artifacts compared to silicon and platinum reference materials inside the MRI at 7 T. In addition, FEM simulations predicted an ~30% SAR reduction for 3C-SiC compared to Pt. These initial simulations and experiments indicate an all-SiC INI may effectively reduce MRI induced heating and image artifacts in high field MRI. In order to evaluate the MRI safety of a closed-loop, fully functional all-SiC INI as per ISO/TS 10974:2018 standard, additional research and development is being conducted and will be reported at a later date.

The lifetime of neural implants is strongly dependent on packaging due to the aqueous and biochemically aggressive nature of the body. Over the last decade, there has been a drive towards neuromodulatory implants which are wireless and approaching millimeter-scales with increasing electrode count. A so-far unrealized goal for these new types of devices is an in-vivo lifetime comparable to a sizable fraction of a healthy patient’s lifetime (>10–20 years). Existing, approved medical implants commonly encapsulate components in metal enclosures (e.g. titanium) with brazed ceramic inserts for electrode feedthrough. It is unclear how amenable the traditional approach is to the simultaneous goals of miniaturization, increased channel count, and wireless communication. Ceramic materials have also played a significant role in traditional medical implants due to their dielectric properties, corrosion resistance, biocompatibility, and high strength, but are not as commonly used for housing materials due to their brittleness and the difficulty they present in creating complex housing geometries. However, thin-film technology has opened new opportunities for ceramics processing. Thin films derived largely from the semiconductor industry can be deposited and patterned in new ways, have conductivities which can be altered during manufacturing to provide conductors as well as insulators, and can be used to fabricate flexible substrates. In this review, we give an overview of packaging for neural implants, with an emphasis on how ceramic materials have been utilized in medical device packaging, as well as how ceramic thin-film micromachining and processing may be further developed to create truly reliable, miniaturized, neural implants.

Objective. Implanted devices providing real-time neural activity classification and control are increasingly used to treat neurological disorders, such as epilepsy and Parkinson’s disease. Classification performance is critical to identifying brain states appropriate for the therapeutic action (e.g. neural stimulation). However, advanced algorithms that have shown promise in offline studies, in particular deep learning (DL) methods, have not been deployed on resource-restrained neural implants. Here, we designed and optimized three DL models or edge deployment and evaluated their inference performance in a case study of seizure detection. Approach. A deep neural network (DNN), a convolutional neural network (CNN), and a long short-term memory (LSTM) network were designed and trained with TensorFlow to classify ictal, preictal, and interictal phases from the CHB-MIT scalp EEG database. A sliding window based weighted majority voting algorithm was developed to detect seizure events based on each DL model’s classification results. After iterative model compression and coefficient quantization, the algorithms were deployed on a general-purpose, off-the-shelf microcontroller for real-time testing. Inference sensitivity, false positive rate (FPR), execution time, memory size, and power consumption were quantified. Main results. For seizure event detection, the sensitivity and FPR for the DNN, CNN, and LSTM models were 87.36%/0.169 h−1, 96.70%/0.102 h−1, and 97.61%/0.071 h−1, respectively. Predicting seizures for early warnings was also feasible. The LSTM model achieved the best overall performance at the expense of the highest power. The DNN model achieved the shortest execution time. The CNN model showed advantages in balanced performance and power with minimum memory requirement. The implemented model compression and quantization achieved a significant saving of power and memory with an accuracy degradation of less than 0.5%. Significance. Inference with embedded DL models achieved performance comparable to many prior implementations that had no time or computational resource limitations. Generic microcontrollers can provide the required memory and computational resources, while model designs can be migrated to application-specific integrated circuits for further optimization and power saving. The results suggest that edge DL inference is a feasible option for future neural implants to improve classification performance and therapeutic outcomes.

Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological disorders. However, deploying machine learning algorithms on low-power neural devices is challenging, given the tight constraints on computational and memory resources for such devices. In this paper, we review the recent developments in embedding machine learning in neural interfaces, with a focus on design trade-offs and hardware efficiency. We also present our optimized tree-based model for low-power and memory-efficient classification of neural signal in brain implants. Using energy-aware learning and model compression, we show that the proposed oblique trees can outperform conventional machine learning models in applications such as seizure or tremor detection and motor decoding.

Deep brain stimulation (DBS) for Parkinson's disease, essential tremor and epilepsy is an established palliative treatment. DBS uses electrical neuromodulation to suppress symptoms. Most current systems provide a continuous pattern of fixed stimulation, with clinical follow-ups to refine settings constrained to normal office hours. An issue with this management strategy is that the impact of stimulation on circadian, i.e. sleep-wake, rhythms is not fully considered; either in the device design or in the clinical follow-up. Since devices can be implanted in brain targets that couple into the reticular activating network, impact on wakefulness and sleep can be significant. This issue will likely grow as new targets are explored, with the potential to create entraining signals that are uncoupled from environmental influences. To address this issue, we have designed a new brain-machine-interface for DBS that combines a slow-adaptive circadian-based stimulation pattern with a fast-acting pathway for responsive stimulation, demonstrated here for seizure management. In preparation for first-in-human research trials to explore the utility of multi-timescale automated adaptive algorithms, design and prototyping was carried out in line with ISO risk management standards, ensuring patient safety. The ultimate aim is to account for chronobiology within the algorithms embedded in brain-machine-interfaces and in neuromodulation technology more broadly.

Parylene-C has been used as a substrate and encapsulation material for many implantable medical devices. However, to ensure the flexibility required in some applications, minimize tissue reaction, and protect parylene from degradation in vivo an additional outmost layer of polydimethylsiloxane (PDMS) is desired. In such a scenario, the adhesion of PDMS to parylene is of critical importance to prevent early failure caused by delamination in the harsh environment of the human body. Towards this goal, we propose a method based on creating chemical covalent bonds using intermediate ceramic layers as adhesion promoters between PDMS and parylene.To evaluate our concept, we prepared three different sets of samples with PDMS on parylene without and with oxygen plasma treatment (the most commonly employed method to increase adhesion), and samples with our proposed ceramic intermediate layers of silicon carbide (SiC) and silicon dioxide (SiO2). The samples were soaked in phosphate-buffered saline (PBS) solution at room temperature and were inspected under an optical microscope. To investigate the adhesion property, cross-cut tape tests and peel tests were performed. The results showed a significant improvement of the adhesion and in-soak long-term performance of our proposed encapsulation stack compared with PDMS on parylene and PDMS on plasma-treated parylene. We aim to use the proposed solution to package bare silicon chips on active implants.

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.

The methods used to treat various neurological diseases are evolving. The facilities provided by the technology have led to creation of new treatment opportunities. Neuromodulation is one of these important methods. By definition, the neuromodulation is a change in neural activity which occurs by stimulating a specific area of nervous system. The mentioned stimulation can be electrical, magnetic, or chemical. This method is used in various diseases, such as stroke, Parkinson's, Alzheimer's, and amyotrophic lateral sclerosis (ALS). Multiple sclerosis (MS) is no exception in this regard and methods including the neurofeedback and transcranial magnetic stimulation (TMS) are used to treat various complications of the MS. One aspect of neuromodulation is the use of neural implant, which is applied nowadays, especially in the Parkinson's disease, and the use of microchips and prostheses to treat various symptoms in different neurological diseases has received significant attention. Although neural implant has been exploited to improve the symptoms of MS, they appear to have much greater potential to improve the condition of patients with MS. It seems that more attention to the symptoms of MS, on the one hand, and a new approach to the pathogenesis of this disease and considering it as a connectomopathy, on the other hand, can provide new opportunities for application of this method in the treatment of MS.

Diamond possesses many favorable properties for biochemical sensors, including biocompatibility, chemical inertness, resistance to biofouling, an extremely wide potential window, and low double-layer capacitance. The hardness of diamond, however, has hindered its applications in neural implants due to the mechanical property mismatch between diamond and soft nervous tissues. Here, we present a flexible, diamond-based microelectrode probe consisting of multichannel boron-doped polycrystalline diamond (BDD) microelectrodes on a soft Parylene C substrate. We developed and optimized a wafer-scale fabrication approach that allows the use of the growth side of the BDD thin film as the sensing surface. Compared to the nucleation surface, the BDD growth side exhibited a rougher morphology, a higher sp3 content, a wider water potential window, and a lower background current. The dopamine (DA) sensing capability of the BDD growth surface electrodes was validated in a 1.0 mM DA solution, which shows better sensitivity and stability than the BDD nucleation surface electrodes. The results of these comparative studies suggest that using the BDD growth surface for making implantable microelectrodes has significant advantages in terms of the sensitivity, selectivity, and stability of a neural implant. Furthermore, we validated the functionality of the BDD growth side electrodes for neural recordings both in vitro and in vivo. The biocompatibility of the microcrystalline diamond film was also assessed in vitro using rat cortical neuron cultures., Biosensors: Flexible diamond-based microelectrodes for neural sensing A flexible, sensitive, stable neural probe consisting of boron-doped polycrystalline diamond (BDD) microelectrodes has been developed, whereby the BDD growth surface is used as the electrode site for neurophysiological and neurochemical sensing. Among carbon materials, BDD has found widespread use in neurotransmitter detection, but the hardness of diamond has impeded application in neural implants. A team headed by Wen Li at Michigan State University, USA, succeeded in developing a process that allows the growth side of the BDD thin film to be used as the sensing surface: they transferred the BDD patterns from a solid silicon substrate onto a flexible polymer substrate. The authors validated their BDD microelectrode technology for neural recordings both in vitro and in vivo, and they believe it has excellent potential for research into various brain disorders, such as Parkinson’s disease.

Advanced polymer science and design technologies are constantly evolving to meet ever-growing expectations for flexible optical MEMS. In this work, we present design and microfabrication considerations for designed flexible Polymeric Opto-Electro-Mechanical Systems (POEMS). The presented methods integrate waveguide fabrication and laser diode (LD) chip assembly with Lawrence Livermore National Laboratory's (LLNL's) flexible thin-film technology to enable LLNL's first neural optoelectrode that can deliver guided light for neural activation. We support our findings with electrical and optical bench verification tests, present thermal simulation models to analyze heat dissipation of laser light sources on polymer substrates and discuss potential modifications for next generation prototypes. This fully integrated approach will allow spatial precision, scalability and more particularly, longer lifetime, needed to enable chronic studies of brain activities.

Repeated non-diffuse optical imaging of the brain is difficult. This is due to the fact that the cranial bone is highly scattering and thus a strong optical barrier. Repeated craniotomies increase the risk of complications and may disrupt the biological systems being imaged. We previously introduced a potential solution in the form of a transparent ceramic cranial implant called the Window to the Brain (WttB) implant. This implant is made of nanocrystalline Yttria-Stabilized Zirconia (nc-YSZ), which possesses the requisite mechanical strength to serve as a permanent optical access window in human patients. In this present study, we demonstrate repeated brain imaging of n = 5 mice using both OCT and LSI across the WttB implant over 4 weeks. The main objectives are to determine if the WttB implant allows for chronic OCT imaging, and to shed further light on the question of whether optical access provided by the WttB implant remains stable over this duration in the body. The Window to the Brain implant allowed for stable repeated imaging of the mouse brain with Optical Coherence Tomography over 28 days, without loss of signal intensity. Repeated Laser Speckle Imaging was also possible over this timeframe, but signal to noise ratio and the sharpness of vessels in the images decreased with time. This can be partially explained by elevated blood flow during the first imaging session in response to trauma from the surgery, which was also detected by OCT flow imaging. These results are promising for long-term optical access through the WttB implant, making feasible chronic in vivo studies in multiple neurological models of brain disease.

High-channel-count neural interfaces are typically packaged by being permanently bonded to their packaged electronics followed by encapsulation. Such interfaces are often intimately integrated into neural tissue, their removal to replace the battery or upgrade electronics is not undesirable. Gaskets are widely used to provide liquid/electrical isolation and to seal the connection between two or more mating parts. Pressure-driven microgaskets are well established in the field of microfluidics. Although rematable microgaskets for fluidic interconnects exist, the use of microgaskets for electrical isolation have not been demonstrated. Our approach is to electrically isolate 2-D arrays of contact pads using a compressible silicone microgasket. Electrochemical impedance spectroscopy (EIS) was used to quantify the electrical isolation of the microgasket on contact pads, which were formed in a polyimide flex circuit, as a function of frequency after being soaked in saline. Experiments have shown that the compressed sub-millimeter PDMSe microgasket can provide excellent isolation (i.e., >30 MΩ at 1 KHz) that is comparable to the other more conventional packaging methods, such as encapsulation in polydimethylsiloxane elastomer (PDMSe) or parylene-C. Our microgasket-based approach should be scalable to high channel counts and high channel densities enabling much smaller and higher-performance neural implants.

Artificial electrical stimulation of peripheral nerves for sensory feedback restoration can greatly benefit from computational models for simulation-based neural implant design in order to reduce the trial-and-error approach usually taken, thus potentially significantly reducing research and development costs and time. To this end, we built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues was modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation. Ephaptic coupling was found to increase the number of fibers that are activated by artificial stimulation, thus reducing the artificial currents required for axonal recruitment, and it was found to reduce and shift the range of optimal stimulation amplitudes for maximum inter-fascicular selectivity. During propagation, while fibers of similar diameters tended to lock their action potentials and reduce their conduction velocities, as expected from previous knowledge on bundles of identical axons, the presence of many other fibers of different diameters was found to make their interactions weaker and unstable., Author summary The design of neural interfaces for artificial electrical stimulation in prostheses can greatly benefit from simulations using electrode-nerve interface models. Studies on electrical stimulation of nerves generally neglect the effects of ephaptic coupling (i.e., coupling between axon fibers and bundles due to their local electric fields) on axon responses to stimulation as ephaptic coupling is normally assumed to play no significant role in bundles of myelinated axons. However, studies have shown that ephaptic effects are non negligible in mammalian peripheral nerves. As such, we have built a resistor network model of a small peripheral nerve trunk for simulation of ephaptic interactions between axons under artificial electrical stimulation. Results show that ephaptic coupling clearly increases axon recruitment and, hence, influences selectivity. On the other hand, the ephaptic coupling effects during action potential propagation observed in this work are more complex than the known effects for ideal, homogeneous bundles. In this work, heterogeneity and variability of fiber diameters in a bundle were found to greatly diminish the strength of ephaptic interactions to the point where these interactions do not play a relevant role on action potential propagation.

There is growing evidence supporting the use of percutaneous tibial nerve stimulation to manage lower urinary tract symptoms (LUTS) such as urgency, frequency and urge incontinence, in a non-pharmacologic, minimally invasive approach. Given this, there is now an impetus to move this technology forward from an interval (i.e., weekly and/or monthly) toward a continuous dosing, using implantable devices. This review article focuses on the newest implantable devices and the most current data demonstrating safety and efficacy in the management of refractory overactive bladder. There are new studies showing that continuous (or even semi-continuous) stimulation of the tibial nerve can be of similar efficacy as other chronic neural implant devices, such as sacral neuromodulation. This includes the Blue Wind Renova, StimGuard, eCoin, and Bioness Stimrouter. While the data on these devices are still short-term, implantable tibial nerve stimulation holds promise in the field of managing LUTS and pelvic floor disorders. Durability and minimizing migration remain challenging.

Progress has been made in the field of neural interfacing using both mouse and rat models, yet standardization of these models' interchangeability has yet to be established. The mouse model allows for transgenic, optogenetic, and advanced imaging modalities which can be used to examine the biological impact and failure mechanisms associated with the neural implant itself. The ability to directly compare electrophysiological data between mouse and rat models is crucial for the development and assessment of neural interfaces. The most obvious difference in the two rodent models is size, which raises concern for the role of device-induced tissue strain. Strain exerted on brain tissue by implanted microelectrode arrays is hypothesized to affect long-term recording performance. Therefore, understanding any potential differences in tissue strain caused by differences in the implant to tissue size ratio is crucial for validating the interchangeability of rat and mouse models. Hence, this study is aimed at investigating the electrophysiological variances and predictive device-induced tissue strain. Rat and mouse electrophysiological recordings were collected from implanted animals for eight weeks. A finite element model was utilized to assess the tissue strain from implanted intracortical microelectrodes, taking into account the differences in the depth within the cortex, implantation depth, and electrode geometry between the two models. The rat model demonstrated a larger percentage of channels recording single unit activity and number of units recorded per channel at acute but not chronic time points, relative to the mouse model Additionally, the finite element models also revealed no predictive differences in tissue strain between the two rodent models. Collectively our results show that these two models are comparable after taking into consideration some recommendations to maintain uniform conditions for future studies where direct comparisons of electrophysiological and tissue strain data between the two animal models will be required.

Cognitive control is the ability to withhold a default, prepotent response in favor of a more adaptive choice. Control deficits are common across mental disorders, including depression, anxiety, and addiction. Thus, a method for improving cognitive control could be broadly useful in disorders with few effective treatments. Here, we demonstrate closed-loop enhancement of one aspect of cognitive control by direct brain stimulation in humans. We stimulated internal capsule/striatum in participants undergoing intracranial epilepsy monitoring as they performed a cognitive control/conflict task. Stimulation enhanced performance, with the strongest effects from dorsal capsule/striatum stimulation. We then developed a framework to detect control lapses and stimulate in response. This closed-loop approach produced larger behavioral changes than open-loop stimulation, with a slight improvement in performance change per unit of energy delivered. Finally, we decoded task performance directly from activity on a small number of electrodes, using features compatible with existing closed-loop brain implants. Our findings are proof of concept for a new approach to treating severe mental disorders, based on directly remediating underlying cognitive deficits.

Electrophysiology provides a direct readout of neuronal activity at a temporal precision only limited by the sampling rate. However, interrogating deep brain structures, implanting multiple targets or aiming at unusual angles still poses significant challenges even for expert operators, and errors are only discovered by post-hoc histological reconstruction. Here, we propose a method combining the high-resolution information about bone landmarks provided by micro-CT scanning with the soft tissue contrast of the MRI, which allowed us to precisely localize electrodes and optic fibers in mice in vivo. This enables arbitrating the success of implantation directly after surgery with a precision comparable to the gold standard histological reconstruction. Adjustment of the recording depth with electrode microdrives or early termination of unsuccessful experiments saves many working hours, while fast 3-dimensional feedback helps surgeons to avoid systematic errors. Increased aiming precision will allow more precise targeting of small or deep brain nuclei and multiple targeting of specific cortical layers.

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.

Objective. Microfabricated neuroprosthetic devices have made possible important observations on neuron activity; however, long-term high-fidelity recording performance of these devices has yet to be realized. Tissue-device interactions appear to be a primary source of lost recording performance. The current state of the art for visualizing the tissue response surrounding brain implants in animals is immunohistochemistry + confocal microscopy, which is mainly performed after sacrificing the animal. Monitoring the tissue response as it develops could reveal important features of the response which may inform improvements in electrode design. Approach. Optical coherence tomography (OCT), an imaging technique commonly used in ophthalmology, has already been adapted for imaging of brain tissue. Here, we use OCT to achieve real-time, in vivo monitoring of the tissue response surrounding chronically implanted neural devices. The employed tissue-response-provoking implants are coated with a plasma-deposited nanofilm, which has been demonstrated as a biocompatible and anti-inflammatory interface for indwelling devices. We evaluate the method by comparing the OCT results to traditional histology qualitatively and quantitatively. Main results. The differences in OCT signal across the implantation period between the plasma group and the control reveal that the plasma-type coating of otherwise rigid brain probes (glass) only slightly improve the glial encapsulation in the brain parenchyma indicating that geometrical or mechanical influences are dominating the encapsulation process. Significance. Our approach can long-term monitor and compare the tissue-response to chronically-implanted neural probes with and withour plasma coating in living animal models. Our findings provide valuable insigh to the well acknowledged yet not solved challenge.

Background Neural interfaces often elicit inflammatory responses and neuronal loss in the surrounding tissue which adversely affect the function and longevity of the implanted device. Minocycline, an anti-inflammatory pharmaceutics with neuroprotective properties, may be used for reducing the acute brain tissue responses after implantation. However, conventional administration routes require high doses which can cause adverse systemic side effects. Therefore, the aim of this study was to develop and evaluate a new drug-delivery-system for local and sustained administration of minocycline in the brain. Methods Stainless steel needles insulated with Parylene-C were dip-coated with non-crosslinked gelatin and minocycline-loaded PLGA nanoparticles (MC-NPs) were incorporated into the gelatin-coatings by an absorption method and subsequently trapped by drying the gelatin. Parylene-C insulated needles coated only with gelatin were used as controls. The expression of markers for activated microglia (CD68), all microglia (CX3CR1-GFP), reactive astrocytes (GFAP), neurons (NeuN) and all cell nuclei (DAPI) surrounding the implantation sites were quantified at 3 and 7 days after implantation in mice. Results MC-NPs were successfully incorporated into gelatin-coatings of neural implants by an absorption method suitable for thermosensitive drug-loads. Immunohistochemical analysis of the in vivo brain tissue responses, showed that MC-NPs significantly attenuate the activation of microglial cells without effecting the overall population of microglial cells around the implantation sites. A delayed but significant reduction of the astrocytic response was also found in comparison to control implants. No effect on neurons or total cell count was found which may suggest that the MC-NPs are non-toxic to the central nervous system. Conclusions A novel drug-nanoparticle-delivery-system was developed for neural interfaces and thermosensitive drug-loads. The local delivery of MC-NPs was shown to attenuate the acute brain tissue responses nearby an implant and therefore may be useful for improving biocompatibility of implanted neuro-electronic interfaces. The developed drug-delivery-system may potentially also be used for other pharmaceutics to provide highly localized and therefore more specific effects as compared to systemic administration.

Over the past 30 years, stem cell technologies matured from an attractive option to investigate neurodegenerative diseases to a possible paradigm shift in their treatment through the development of cell-based regenerative medicine (CRM). Implantable cell replacement therapies promise to completely restore function of neural structures possibly changing how we currently perceive the onset of these conditions. One of the major clinical hurdles facing the routine implementation of stem cell therapy is the limited and inconsistent benefit observed thus far. While unclear, numerous pre-clinical and a handful of clinical cell fate imaging studies point to poor cell retention and survival. Coupling the need to better understand these mechanisms while providing scalable approaches to monitor these treatments in both pre-clinical and clinical scenarios, we show a proof of concept bioimpedance electronic platform for the Agile development of smart and mobile biomedical applications like neural implants or highly portable monitoring devices.

In all commercial cochlear implant (CI) devices, the electric stimulation is performed with a rectangular pulse that generally has two phases of opposite polarity. To date, developing new stimulation strategies has relied on the efficacy of this shape. Here, we investigate the potential of a novel stimulation paradigm that uses biophysically-inspired electrical ramped pulses. Using electrically-evoked auditory brainstem response (eABR) recordings in mice, we found that less charge, but higher current level amplitude, is needed to evoke responses with ramped shapes that are similar in amplitude to responses obtained with rectangular shapes. The most charge-efficient pulse shape had a rising ramp over both phases, supporting findings from previous in vitro studies. This was also true for longer phase durations. Our study presents the first physiological data on CI-stimulation with ramped pulse shapes. By reducing charge consumption ramped pulses have the potential to produce more battery-efficient CIs and may open new perspectives for designing other efficient neural implants in the future.

When designing electrodes and probes for brain-machine interfaces, one of the challenges faced involves minimizing the brain-tissue response, which would otherwise create an environment that is detrimental for the accurate functioning of such probes. Following the implantation process, the brain reacts with a sterile inflammation response and resulting astrocytic glial scar formation, potentially resulting in neuronal cell loss around the implantation site. Such alterations in the naive brain tissue can hinder both the quality of neuronal recordings, and the efficacy of deep-brain stimulation. In this study, we chronically implanted a glass-supported polyimide microelectrode in the dorsolateral striatum of Sprague-Dawley rats. The effect of high-frequency stimulation (HFS) was investigated using c-fos immunoreactivity techniques. GFAP and ED1 immunohistochemistry were used to analyze the brain-tissue response. No changes in c-fos expression were found for either the acute or chronic stimulus groups; although a c-fos expression was found along the length of the implantation trajectory, following chronic implantation of our stiffened polyimide microelectrode. Furthermore, we also observed the formation of a glial scar around the microelectrode, with an accompanying low number of inflammation cells. Histological and statistical analysis of NeuN-positive cells did not demonstrate a pronounced "kill zone" with accompanying neuronal cell death around the implantation site, neither on the polymer side, nor on the glass side of the PI-glass probe.

Reported clinical cases of patients with neurological disorders who have received brain implants which produced some degrees of cognitive enhancement introduce the possibility of using implantable neurotechnologies in healthy individual brains. However, little is known about the phenomenology of using implants for cognitive gains. Even if brain implants could augment one’s cognitive capacities, it would not guarantee a net benefit for the implanted individual. In this article, we examine the potential psychiatric effects of increased cognitive capacities, namely the burden of abnormality. We draw on a parallel phenomenon, known as the burden of normality, from clinical studies when patients who became suddenly symptom free after treatment with deep brain stimulation experienced psychiatric adverse effects. While we agree that cognitive enhancement could generate important postoperative benefits, we argue that patients augmenting their capacities will likely experience abnormality as much as, or perhaps even more so than normality.

Engineered neural implants have a myriad of potential basic science and clinical neural repair applications. Although there are implants that are currently undergoing their first clinical investigations, optimizing their long-term viability and efficacy remain an open challenge. Functional implants with pre-vascularization of various engineered tissues have proven to enhance post-implantation host integration, and well-known synergistic neural-vascular interplays suggest that this strategy could also be promising for neural tissue engineering . Here, we report the development of a novel bio-engineered neuro-vascular co-culture construct, and demonstrate that it exhibits enhanced neurotrophic factor expression , and more complex neuronal morphology. Crucially, by introducing genetically encoded calcium indicators (GECIs) into the co-culture, we are able to monitor functional activity of the neural network , and demonstrate greater activity levels and complexity as a result of the introduction of endothelial cells in the construct. The presence of this enhanced activity could putatively lead to superior integration outcomes. Indeed, leveraging on the ability to monitor the construct's development post-implantation with GECIs, we observe improved integration phenotypes in the spinal cord of mice relative to non-vascularized controls. Our approach provides a new experimental system with functional neural feedback for studying the interplay between vascular and neural development while advancing the optimization of neural implants towards potential clinical applications.

Neural implants that deliver multi-site electrical stimulation to the nervous systems are no longer the last resort but routine treatment options for various neurological disorders. Multi-site electrical stimulation is also widely used to study nervous system function and neural circuit transformations. These technologies increasingly demand dynamic electrical stimulation and closed-loop feedback control for real-time assessment of neural function, which is technically challenging since stimulus-evoked artifacts overwhelm the small neural signals of interest. We report a novel and versatile artifact removal method that can be applied in a variety of settings, from single- to multi-site stimulation and recording and for current waveforms of arbitrary shape and size. The method capitalizes on linear electrical coupling between stimulating currents and recording artifacts, which allows us to estimate a multi-channel linear Wiener filter to predict and subsequently remove artifacts via subtraction. We confirm and verify the linearity assumption and demonstrate feasibility in a variety of recording modalities, including in vitro sciatic nerve stimulation, bilateral cochlear implant stimulation, and multi-channel stimulation and recording between the auditory midbrain and cortex. We demonstrate a vast enhancement in the recording quality with a typical artifact reduction of 25−40 dB. The method is efficient and can be scaled to arbitrary number of stimulus and recording sites, making it ideal for applications in large-scale arrays, closed-loop implants, and high-resolution multi-channel brain-machine interfaces.

There has not been a major change in how neuroscientists approach stereotaxic methods in decades. Here we present a new stereotaxic method that improves on traditional approaches by reducing costs, training, surgical time, and aiding repeatability. The RatHat brain implantation system is a 3D printable stereotaxic device for rats that is fabricated prior to surgery and fits to the shape of the skull. RatHat builds are directly implanted into the brain without the need for head-leveling or coordinate-mapping during surgery. The RatHat system can be used in conjunction with the traditional u-frame stereotaxic device, but does not require the use of a micromanipulator for successful implantations. Each RatHat system contains several primary components including the implant for mounting intracranial components, the surgical stencil for targeting drill sites, and the protective cap for impacts and debris. Each component serves a unique function and can be used together or separately. We demonstrate the feasibility of the RatHat system in four different proof-of-principle experiments: 1) a 3-pole cannula apparatus, 2) an optrode-electrode assembly, 3) a fixed-electrode array, and 4) a tetrode hyperdrive. Implants were successful, durable, and long-lasting (up to 9 months). RatHat print files are easily created, can be modified in CAD software for a variety of applications, and are easily shared, contributing to open science goals and replications. The RatHat system has been adapted to multiple experimental paradigms in our lab and should be a useful new way to conduct stereotaxic implant surgeries in rodents.Impact StatementWe demonstrate a new approach to rodent stereotaxic surgery. Rodent neurosurgery is a complex skill that requires expensive equipment for head stabilization and micromanipulators for localization. The RatHat is a 3D printable brain implant system that reduces costs and time using pre-mapped and printed surgical files. A surgical stencil allows for quick placement of drill holes, and a RatHat places components in the brain using atlas coordinates. The RatHat system is an easily shared resource facilitating open science goals for simple replications and archiving of specific experimental applications.

A new generation of implantable brain–computer interfaces (BCI) devices have been tested for the first time in a human clinical trial, with significant success. These intelligent implants detect specific neuronal activity patterns, such as an epileptic seizure, and provide information to help patients to respond to the upcoming neuronal events. By forecasting a seizure, the technology keeps patients in the decisional loop; the device gives control to patients on how to respond and decide on a therapeutic course ahead of time. Being kept in the decisional loop can positively increase patients’ quality of life; however, doing so does not come free of ethical concerns. There is currently a lack of evidence concerning the various impacts of closed-loop system BCIs on patients’ decisionmaking processes, especially how being in the decisional loop impacts patients’ sense of autonomy. This article addresses these gaps by providing data that we obtained from a first-in-human clinical trial involving patients implanted with advisory brain devices. This article explores ethical issues related to the risks involved in being kept in the decisional loop.

Objective The Shannon model is often used to define an expected boundary between non-damaging and damaging modes of electrical neurostimulation. Numerous preclinical studies have been performed by manufacturers of neuromodulation devices using different animal models and a broad range of stimulation parameters while developing devices for clinical use. These studies are mostly absent from peer-reviewed literature, which may lead to this information being overlooked by the scientific community. We aimed to locate summaries of these studies accessible via public regulatory databases and to add them to a body of knowledge available to a broad scientific community. Methods We employed web search terms describing device type, intended use, neural target, therapeutic application, company name, and submission number to identify summaries for premarket approval (PMA) devices and 510(k) devices. We filtered these records to a subset of entries that have sufficient technical information relevant to safety of neurostimulation. Results We identified 13 product codes for 8 types of neuromodulation devices. These led us to devices that have 22 PMAs and 154 510(k)s and six transcripts of public panel meetings. We found one PMA for a brain, peripheral nerve, and spinal cord stimulator and five 510(k) spinal cord stimulators with enough information to plot in Shannon coordinates of charge and charge density per phase. Conclusions Analysis of relevant entries from public regulatory databases reveals use of pig, sheep, monkey, dog, and goat animal models with deep brain, peripheral nerve, muscle and spinal cord electrode placement with a variety of stimulation durations (hours to years); frequencies (10–10,000 Hz) and magnitudes (Shannon k from below zero to 4.47). Data from located entries indicate that a feline cortical model that employs acute stimulation might have limitations for assessing tissue damage in diverse anatomical locations, particularly for peripheral nerve and spinal cord simulation.

Electrical stimulation using implantable electrodes is widely used to treat various neuronal disorders such as Parkinson's disease and epilepsy and is a widely used research tool in neuroscience studies. However, to date, devices that help better understand the mechanisms of electrical stimulation in neural tissues have been limited to opaque neural electrodes. Imaging spatiotemporal neural responses to electrical stimulation with minimal artifact could allow for various studies that are impossible with existing opaque electrodes. Here, we demonstrate electrical brain stimulation and simultaneous optical monitoring of the underlying neural tissues using carbon-based, fully transparent graphene electrodes implanted in GCaMP6f mice. Fluorescence imaging of neural activity for varying electrical stimulation parameters was conducted with minimal image artifact through transparent graphene electrodes. In addition, full-field imaging of electrical stimulation verified more efficient neural activation with cathode leading stimulation compared to anode leading stimulation. We have characterized the charge density limitation of capacitive four-layer graphene electrodes as 116.07-174.10 μC/cm

Brain stimulation has emerged as an effective treatment for a wide range of neurological and psychiatric diseases. Parkinson’s disease, epilepsy, and essential tremor have FDA indications for electrical brain stimulation using intracranially implanted electrodes. Interfacing implantable brain devices with local and cloud computing resources have the potential to improve electrical stimulation efficacy, disease tracking, and management. Epilepsy, in particular, is a neurological disease that might benefit from the integration of brain implants with off-the-body computing for tracking disease and therapy. Recent clinical trials have demonstrated seizure forecasting, seizure detection, and therapeutic electrical stimulation in patients with drug-resistant focal epilepsy. In this paper, we describe a next-generation epilepsy management system that integrates local handheld and cloud-computing resources wirelessly coupled to an implanted device with embedded payloads (sensors, intracranial EEG telemetry, electrical stimulation, classifiers, and control policy implementation). The handheld device and cloud computing resources can provide a seamless interface between patients and physicians, and realtime intracranial EEG can be used to classify brain state (wake/sleep, preseizure, and seizure), implement control policies for electrical stimulation, and track patient health. This system creates a flexible platform in which low demand analytics requiring fast response times are embedded in the implanted device and more complex algorithms are implemented in offthebody local and distributed cloud computing environments. The system enables tracking and management of epileptic neural networks operating over time scales ranging from milliseconds to months., Brain Implants integrated with Local and Distributed Computing Devices provide a seamless interface between patients and physicians, and real-time intracranial EEG can be used to classify brain state (wake/sleep, pre-seizure, seizure), implement control policies for electrical stimulation, and track patient health. The system enables tracking and management of epileptic neural networks operating over time scales ranging from milliseconds to months.

Despite the current success of neuromodulation, standard biphasic, rectangular pulse shapes may not be optimal to achieve symptom alleviation. Here, we compared stimulation efficiency (in terms of charge) between complex and standard pulses in two areas of the rat brain. In motor cortex, Gaussian and interphase gap stimulation (IPG) increased stimulation efficiency in terms of charge per phase compared with a standard pulse. Moreover, IPG stimulation of the deep mesencephalic reticular formation in freely moving rats was more efficient compared to a standard pulse. We therefore conclude that complex pulses are superior to standard stimulation, as less charge is required to achieve the same behavioral effects in a motor paradigm. These results have important implications for the understanding of electrical stimulation of the nervous system and open new perspectives for the design of the next generation of safe and efficient neural implants. ispartof: Scientific Reports vol:8 issue:1 pages:1-18 ispartof: location:England status: published

Gelatin coating of brain implants is known to provide considerable benefits in terms of reduced inflammatory sequalae and long-term neuroprotective effects. However, the mechanisms for gelatin's protective role in brain injury are still unknown. To address this question, cellular and molecular markers were studied with quantitative immunohistochemical microscopy at acute (2hours, 1, 3days), intermediate (1-2 weeks) and long-term time points (6 weeks) after transient insertion of stainless steel needles into female rat cortex cerebri with or without gelatin coating. Compared to non-coated controls, injuries caused by gelatin coated needles showed a significantly faster resolution of post-stab bleeding/leakage and differential effects on different groups of microglia cells. While similar levels of matrix metalloproteinase (MMP-2 and MMP-9, two gelatinases) was found for coated and noncoated needle stabs during the first week, markedly increased levels of both MMPs was seen for gelatin-coated but not non-coated needle stabs after 2weeks. Neuronal populations and activated astrocytes were largely unaffected. In conclusion, the beneficial effects of gelatin may be the combined results of faster healing of the blood brain barrier curtailing leakage of blood borne molecules/cells into brain parenchyma and to a modulation of the microglial population response favoring restitution of the injured tissue. These findings present an important therapeutic potential for gelatin coatings in various disease, injury and surgical conditions.The neural interfaces field holds great promise to enable elucidation of neural information processing and to develop new implantable devices for stimulation based therapy. Currently, this field is struggling to find solutions for reducing tissue reactions to implanted micro and nanotechnology. Prior studies have recently shown that gelatin coatings lower activation of digestive microglia and mitigate the ubiquitous loss of neurons adjacent to implanted probes, both of which impede implant function. The underlying mechanisms remain to be elucidated, however. Our findings demonstrate for the first time that gelatin has a significant effect on the BBB by promoting rapid restoration of integrity after injury. Moreover, gelatin alters microglia phenotypes and modulates gelatinase activity for up to 2weeks favoring anti-inflammation and restoration of the tissue. Given the key importance of the BBB for normal brain functions, we believe our findings have substantial significance and will be highly interesting to researchers in the biomaterial field.

The development of implanted neural devices to manage neurological and psychiatric disorders or to restore loss of physiological function is a rapidly advancing area of neuroscience research. We consider whether investigators of brain implant studies have an obligation to facilitate device explantation for participants who request it at study conclusion.

Electrical stimulation technologies capable of modulating neural activity are well established for neuroscientific research and neurotherapeutics. Recent micro-neuromodulation experimental results continue to explain neural processing complexity and suggest the potential for assistive technologies capable of restoring or repairing of basic function. Nonetheless, performance is dependent upon the specificity of the stimulation. Increasingly specific stimulation is hypothesized to be achieved by progressively smaller interfaces. Miniaturization is a current focus of neural implants due to improvements in mitigation of the body's foreign body response. It is likely that these exciting technologies will offer the promise to provide large-scale micro-neuromodulation in the future. Here, we highlight recent successes of assistive technologies through bidirectional neuroprostheses currently being used to repair or restore basic brain functionality. Furthermore, we introduce recent neuromodulation technologies that might improve the effectiveness of these neuroprosthetic interfaces by increasing their chronic stability and microstimulation specificity. We suggest a vision where the natural progression of innovative technologies and scientific knowledge enables the ability to selectively micro-neuromodulate every neuron in the brain.

Neurochemical sensing probes are a valuable diagnostic and therapeutic tool that can be used to study neurodegenerative diseases involving deficiencies in neurotransmitter signaling. However, implantation of these biosensors can elicit a harmful tissue response that alters the neurochemical environment within the brain. Transmission of chemical messengers via neurons is impeded by a barrier-forming glial scar that occurs within weeks after insertion followed by progressive neurodegeneration, attenuating signal sensitivity. Emerging research reveals that non-neuronal cells also influence the neurochemical milieu following injury both directly and indirectly. The reactivity of both microglia and astrocytes to inserted probes have been extensively studied in the past yet there remains other glial subtypes in the brain, such as oligodendrocytes and their precursors, the myelin structures they form, as well as vascular-bound pericytes, that have the potential to contribute significantly to the inflammation due to their responsibility to maintain tissue homeostasis. A brief overview of how tissue injury alters the neurochemical makeup followed by alternative potential targets of investigation and novel strategies to enhance the chemical sensing abilities of implantable probes will be discussed.