Search for: All records

Current standards for safe delivery of electrical stimulation to the central nervous system are based on foundational studies which examined post-mortem tissue for histological signs of damage. This set of observations and the subsequently proposed limits to safe stimulation, termed the “Shannon limits,” allow for a simple calculation (using charge per phase and charge density) to determine the intensity of electrical stimulation that can be delivered safely to brain tissue. In the three decades since the Shannon limits were reported, advances in molecular biology have allowed for more nuanced and detailed approaches to be used to expand current understanding of the physiological effects of stimulation. Here, we demonstrate the use of spatial transcriptomics (ST) in an exploratory investigation to assess the biological response to electrical stimulation in the brain. Electrical stimulation was delivered to the rat visual cortex with either acute or chronic electrode implantation procedures. To explore the influence of device type and stimulation parameters, we used carbon fiber ultramicroelectrode arrays (7 μm diameter) and microwire electrode arrays (50 μm diameter) delivering charge and charge density levels selected above and below reported tissue damage thresholds (range: 2–20 nC, 0.1–1 mC/cm 2 ). Spatial transcriptomics was performed using Visium Spatial Gene Expression Slides (10x Genomics, Pleasanton, CA, United States), which enabled simultaneous immunohistochemistry and ST to directly compare traditional histological metrics to transcriptional profiles within each tissue sample. Our data give a first look at unique spatial patterns of gene expression that are related to cellular processes including inflammation, cell cycle progression, and neuronal plasticity. At the acute timepoint, an increase in inflammatory and plasticity related genes was observed surrounding a stimulating electrode compared to a craniotomy control. At the chronic timepoint, an increase in inflammatory and cell cycle progression related genes was observed both in the stimulating vs. non-stimulating microwire electrode comparison and in the stimulating microwire vs. carbon fiber comparison. Using the spatial aspect of this method as well as the within-sample link to traditional metrics of tissue damage, we demonstrate how these data may be analyzed and used to generate new hypotheses and inform safety standards for stimulation in cortex. 

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.