Structural, Functional, and Genetic Changes Surrounding Electrodes Implanted in the Brain.

ConspectusImplantable neurotechnology enables monitoring and stimulating of the brain signals responsible for performing cognitive, motor, and sensory tasks. Electrode arrays implanted in the brain are increasingly used in the clinic to treat a variety of sources of neurological diseases and injuries. However, the implantation of a foreign body typically initiates a tissue response characterized by physical disruption of vasculature and the neuropil as well as the initiation of inflammation and the induction of reactive glial states. Likewise, electrical stimulation can induce damage to the surrounding tissue depending on the intensity and waveform parameters of the applied stimulus. These phenomena, in turn, are likely influenced by the surface chemistry and characteristics of the materials employed, but further information is needed to effectively link the biological responses observed to specific aspects of device design. In order to inform improved design of implantable neurotechnology, we are investigating the basic science principles governing device-tissue integration. We are employing multiple techniques to characterize the structural, functional, and genetic changes that occur in the cells surrounding implanted electrodes. First, we have developed a new "device-in-slice" technique to capture chronically implanted electrodes within thick slices of live rat brain tissue for interrogation with single-cell electrophysiology and two-photon imaging techniques. Our data revealed several new observations of tissue remodeling surrounding devices: (a) there was significant disruption of dendritic arbors in neurons near implants, where losses were driven asymmetrically on the implant-facing side. (b) There was a significant loss of dendritic spine densities in neurons near implants, with a shift toward more immature (nonfunctional) morphologies. (c) There was a reduction in excitatory neurotransmission surrounding implants, as evidenced by a reduction in the frequency of excitatory postsynaptic currents (EPSCs). Lastly, (d) there were changes in the electrophysiological underpinnings of neuronal spiking regularity. In parallel, we initiated new studies to explore changes in gene expression surrounding devices through spatial transcriptomics, which we applied to both recording and stimulating arrays. We found that (a) device implantation is associated with the induction of hundreds of genes associated with neuroinflammation, glial reactivity, oligodendrocyte function, and cellular metabolism and (b) electrical stimulation induces gene expression associated with damage or plasticity in a manner dependent upon the intensity of the applied stimulus. We are currently developing computational analysis tools to distill biomarkers of device-tissue interactions from large transcriptomics data sets. These results improve the current understanding of the biological response to electrodes implanted in the brain while producing new biomarkers for benchmarking the effects of novel electrode designs on responses. As the next generation of neurotechnology is developed, it will be increasingly important to understand the influence of novel materials, surface chemistries, and implant architectures on device performance as well as the relationship with the induction of specific cellular signaling pathways.

Structural and functional changes of deep layer pyramidal neurons surrounding microelectrode arrays implanted in rat motor cortex.

Devices capable of recording or stimulating neuronal signals have created new opportunities to understand normal physiology and treat sources of pathology in the brain. However, it is possible that the tissue response to implanted electrodes may influence the nature of the signals detected or stimulated. In this study, we characterized structural and functional changes in deep layer pyramidal neurons surrounding silicon or polyimide-based electrodes implanted in the motor cortex of rats. Devices were captured in 300 µm-thick tissue slices collected at the 1 or 6 week time point post-implantation, and individual neurons were assessed using a combination of whole-cell electrophysiology and 2-photon imaging. We observed disrupted dendritic arbors and a significant reduction in spine densities in neurons surrounding devices. These effects were accompanied by a decrease in the frequency of spontaneous excitatory post-synaptic currents, a reduction in sag amplitude, an increase in spike frequency adaptation, and an increase in filopodia density. We hypothesize that the effects observed in this study may contribute to the signal loss and instability that often accompany chronically implanted electrodes. STATEMENT OF SIGNIFICANCE: Implanted electrodes in the brain can be used to treat sources of pathology and understand normal physiology by recording or stimulating electrical signals generated by local neurons. However, a foreign body response following implantation undermines the performance of these devices. While several studies have investigated the biological mechanisms of device-tissue interactions through histology, transcriptomics, and imaging, our study is the first to directly interrogate effects on the function of neurons surrounding electrodes using single-cell electrophysiology. Additionally, we provide new, detailed assessments of the impacts of electrodes on the dendritic structure and spine morphology of neurons, and we assess effects for both traditional (silicon) and newer polymer electrode materials. These results reveal new potential mechanisms of electrode-tissue interactions.

Spatiotemporal expression of RNA-seq identified proteins at the electrode interface.

Implantation of electrodes in the brain can be used to record from or stimulate neural tissues to treat neurological disease and injury. However, the tissue response to implanted devices can limit their functional longevity. Recent RNA-seq datasets identify hundreds of genes associated with gliosis, neuronal function, myelination, and cellular metabolism that are spatiotemporally expressed in neural tissues following the insertion of microelectrodes. To validate mRNA as a predictor of protein expression, this study evaluates a sub-set of RNA-seq identified proteins (RSIP) at 24-hours, 1-week, and 6-weeks post-implantation using quantitative immunofluorescence methods. This study found that expression of RSIPs associated with glial activation (Glial fibrillary acidic protein (GFAP), Polypyrimidine tract binding protein-1 (Ptbp1)), neuronal structure (Neurofilament heavy chain (Nefh), Proteolipid protein-1 (Plp1), Myelin Basic Protein (MBP)), and iron metabolism (Transferrin (TF), Ferritin heavy chain-1 (Fth1)) reinforce transcriptional data. This study also provides additional context to the cellular distribution of RSIPs using a MATLAB-based approach to quantify immunofluorescence intensity within specific cell types. Ptbp1, TF, and Fth1 were found to be spatiotemporally distributed within neurons, astrocytes, microglia, and oligodendrocytes at the device interface relative to distal and contralateral tissues. The altered distribution of RSIPs relative to distal tissue is largely localized within 100µm of the device injury, which approaches the functional recording range of implanted electrodes. This study provides evidence that RNA-sequencing can be used to predict protein-level changes in cortical tissues and that RSIPs can be further investigated to identify new biomarkers of the tissue response that influence signal quality. STATEMENT OF SIGNIFICANCE: Microelectrode arrays implanted into the brain are useful tools that can be used to study neuroscience and to treat pathological conditions in a clinical setting. The tissue response to these devices, however, can severely limit their functional longevity. Transcriptomics has deepened the understandings of the tissue response by revealing numerous genes which are differentially expressed following device insertion. This manuscript provides validation for the use of transcriptomics to characterize the tissue response by evaluating a subset of known differentially expressed genes at the protein level around implanted electrodes over time. In additional to validating mRNA-to-protein relationships at the device interface, this study has identified emerging trends in the spatiotemporal distribution of proteins involved with glial activation, neuronal remodeling, and essential iron binding proteins around implanted silicon devices. This study additionally provides a new MATLAB based methodology to quantify protein distribution within discrete cell types at the device interface which may be used as biomarkers for further study or therapeutic intervention in the future.

Gene Expression Changes in Cultured Reactive Rat Astrocyte Models and Comparison to Device-Associated Effects in the Brain.

Implanted microelectrode arrays hold immense therapeutic potential for many neurodegenerative diseases. However, a foreign body response limits long-term device performance. Recent literature supports the role of astrocytes in the response to damage to the central nervous system (CNS) and suggests that reactive astrocytes exist on a spectrum of phenotypes, from beneficial to neurotoxic. The goal of our study was to gain insight into the subtypes of reactive astrocytes responding to electrodes implanted in the brain. In this study, we tested the transcriptomic profile of two reactive astrocyte culture models (cytokine cocktail or lipopolysaccharide, LPS) utilizing RNA sequencing, which we then compared to differential gene expression surrounding devices inserted into rat motor cortex via spatial transcriptomics. We interpreted changes in the genetic expression of the culture models to that of 24 hour, 1 week and 6 week rat tissue samples at multiple distances radiating from the injury site. We found overlapping expression of up to ∼250 genes between in vitro models and in vivo effects, depending on duration of implantation. Cytokine-induced cells shared more genes in common with chronically implanted tissue (≥1 week) in comparison to LPS-exposed cells. We revealed localized expression of a subset of these intersecting genes (e.g., Serping1, Chi3l1, and Cyp7b1) in regions of device-encapsulating, glial fibrillary acidic protein (GFAP)-expressing astrocytes identified with immunohistochemistry. We applied a factorization approach to assess the strength of the relationship between reactivity markers and the spatial distribution of GFAP-expressing astrocytes in vivo . We also provide lists of hundreds of differentially expressed genes between reactive culture models and untreated controls, and we observed 311 shared genes between the cytokine induced model and the LPS-reaction induced control model. Our results show that comparisons of reactive astrocyte culture models with spatial transcriptomics data can reveal new biomarkers of the foreign body response to implantable neurotechnology. These comparisons also provide a strategy to assess the development of in vitro models of the tissue response to implanted electrodes.

Differential Co-Expression Analysis of RNA-Seq Data Reveals Novel Potential Biomarkers of Device-Tissue Interaction.

The biological response to electrodes implanted in the brain has been a long-standing barrier to achieving a stable tissue device-interface. Understanding the mechanisms underlying this response could explain phenomena including recording instability and loss, shifting stimulation thresholds, off-target effects of neuromodulation, and stimulation-induced depression of neural excitability. Our prior work detected differential expression in hundreds of genes following device implantation. Here, we extend upon that work by providing new analyses using differential co-expression analysis, which identifies changes in the correlation structure between groups of genes detected at the interface in comparison to control tissues. We used an "eigengene" approach to identify hub genes associated with each module. Our work adds to a growing body of literature which applies new techniques in molecular biology and computational analysis to long-standing issues surrounding electrode integration with the brain.

Spatiotemporal patterns of gene expression around implanted silicon electrode arrays.

Objective.Intracortical brain interfaces are an ever evolving technology with growing potential for clinical and research applications. The chronic tissue response to these devices traditionally has been characterized by glial scarring, inflammation, oxidative stress, neuronal loss, and blood-brain barrier disruptions. The full complexity of the tissue response to implanted devices is still under investigation.Approach.In this study, we have utilized RNA-sequencing to identify the spatiotemporal gene expression patterns in interfacial (within 100µm) and distal (500µm from implant) brain tissue around implanted silicon microelectrode arrays. Naïve, unimplanted tissue served as a control.Main results.The data revealed significant overall differential expression (DE) in contrasts comparing interfacial tissue vs naïve (157 DE genes), interfacial vs distal (94 DE genes), and distal vs naïve tissues (21 DE genes). Our results captured previously characterized mechanisms of the foreign body response, such as astroglial encapsulation, as well as novel mechanisms which have not yet been characterized in the context of indwelling neurotechnologies. In particular, we have observed perturbations in multiple neuron-associated genes which potentially impact the intrinsic function and structure of neurons at the device interface. In addition to neuron-associated genes, the results presented in this study identified significant DE in genes which are associated with oligodendrocyte, microglia, and astrocyte involvement in the chronic tissue response.Significance. The results of this study increase the fundamental understanding of the complexity of tissue response in the brain and provide an expanded toolkit for future investigation into the bio-integration of implanted electronics with tissues in the central nervous system.

Next-Generation Diamond Electrodes for Neurochemical Sensing: Challenges and Opportunities.

Carbon-based electrodes combined with fast-scan cyclic voltammetry (FSCV) enable neurochemical sensing with high spatiotemporal resolution and sensitivity. While their attractive electrochemical and conductive properties have established a long history of use in the detection of neurotransmitters both in vitro and in vivo, carbon fiber microelectrodes (CFMEs) also have limitations in their fabrication, flexibility, and chronic stability. Diamond is a form of carbon with a more rigid bonding structure (sp3-hybridized) which can become conductive when boron-doped. Boron-doped diamond (BDD) is characterized by an extremely wide potential window, low background current, and good biocompatibility. Additionally, methods for processing and patterning diamond allow for high-throughput batch fabrication and customization of electrode arrays with unique architectures. While tradeoffs in sensitivity can undermine the advantages of BDD as a neurochemical sensor, there are numerous untapped opportunities to further improve performance, including anodic pretreatment, or optimization of the FSCV waveform, instrumentation, sp2/sp3 character, doping, surface characteristics, and signal processing. Here, we review the state-of-the-art in diamond electrodes for neurochemical sensing and discuss potential opportunities for future advancements of the technology. We highlight our team's progress with the development of an all-diamond fiber ultramicroelectrode as a novel approach to advance the performance and applications of diamond-based neurochemical sensors.

Flexible, diamond-based microelectrodes fabricated using the diamond growth side for neural sensing.

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 sp 3 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.

Toward guiding principles for the design of biologically-integrated electrodes for the central nervous system.

Innovation in electrode design has produced a myriad of new and creative strategies for interfacing the nervous system with softer, less invasive, more broadly distributed sites with high spatial resolution. However, despite rapid growth in the use of implanted electrode arrays in research and clinical applications, there are no broadly accepted guiding principles for the design of biocompatible chronic recording interfaces in the central nervous system (CNS). Studies suggest that the architecture and flexibility of devices play important roles in determining effective tissue integration: device feature dimensions (varying from 'sub'- to 'supra'-cellular scales, <10 µm to >100 µm), Young's modulus, and bending modulus have all been identified as key features of design. However, critical knowledge gaps remain in the field with respect to the underlying motivation for these designs: (1) a systematic study of the relationship between device design features (materials, architecture, flexibility), biointegration, and signal quality needs to be performed, including controls for interaction effects between design features, (2) benchmarks for success need to be determined (biological integration, recording performance, longevity, stability), and (3) user results, particularly those that champion a specific design or electrode modification, need to be replicated across laboratories. Finally, the ancillary effects of factors such as tethering, site impedance and insertion method need to be considered. Here, we briefly review observations to-date of device design effects on tissue integration and performance, and then highlight the need for comprehensive and systematic testing of these effects moving forward.

Neuronal excitability and network formation on optically transparent electrode materials.

With the advent of genetically-encoded optical tools to trigger or report neuronal activity, new designs for multielectrode arrays (MEAs) used in neural interfacing incorporate both optical and electrical modes of stimulating or recording neural activity. Likewise, the need to improve upon the biocompatibility of implanted MEAs has moved the field towards the use of softer, more compliant materials in device fabrication. However, there is limited available information on the impact of the materials used in MEAs on the function of interfaced individual neurons and neuronal networks. We assessed the responses of rat cortical neurons on optically transparent materials commonly used in the construction of "next-generation" devices: indium tin oxide (ITO), parylene-C, and polydimethylsiloxane (PDMS). We found that neuronal network formation and spiking responses to electrical stimulation were enhanced in neurons cultured on ITO. We observed reduced excitability and synaptic connectivity between neurons cultured on PDMS. We hypothesize that the superior conductivity of ITO and suboptimal neuronal attachment to PDMS contributed to our results.

Regenerative Electrode Interfaces for Neural Prostheses.

Neural prostheses are electrode arrays implanted in the nervous system that record or stimulate electrical activity in neurons. Rapid growth in the use of neural prostheses in research and clinical applications has occurred in recent years, but instability and poor patency in the tissue-electrode interface undermines the longevity and performance of these devices. The application of tissue engineering strategies to the device interface is a promising approach to improve connectivity and communication between implanted electrodes and local neurons, and several research groups have developed new and innovative modifications to neural prostheses with the goal of seamless device-tissue integration. These approaches can be broadly categorized based on the strategy used to maintain and regenerate neurons at the device interface: (1) redesign of the prosthesis architecture to include finer-scale geometries and/or provide topographical cues to guide regenerating neural outgrowth, (2) incorporation of material coatings and bioactive molecules on the prosthesis to improve neuronal growth, viability, and adhesion, and (3) inclusion of cellular grafts to replenish the local neuron population or provide a target site for reinnervation (biohybrid devices). In addition to stabilizing the contact between neurons and electrodes, the potential to selectively interface specific subpopulations of neurons with individual electrode sites is a key advantage of regenerative interfaces. In this study, we review the development of regenerative interfaces for applications in both the peripheral and central nervous system. Current and future development of regenerative interfaces has the potential to improve the stability and selectivity of neural prostheses, improving the patency and resolution of information transfer between neurons and implanted electrodes.