Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.

With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques for measuring tonic extracellular concentrations of neurotransmitters, including voltammetry, enzyme-based sensors, amperometry, and in vivo microdialysis, there is currently no means to resolve concentrations of structurally similar neurotransmitters from mixtures in the in vivo environment with high spatiotemporal resolution and limited tissue damage. Since a variety of research and clinical investigations involve brain regions containing electrochemically similar monoamines, such as dopamine and norepinephrine, developing a model to resolve the respective contributions of these neurotransmitters is of vital importance. Here we have developed a deep learning network, DiscrimNet, a convolutional autoencoder capable of accurately predicting individual tonic concentrations of dopamine, norepinephrine, and serotonin from both in vitro mixtures and the in vivo environment in anesthetized rats, measured using voltammetry. The architecture of DiscrimNet is described, and its ability to accurately predict in vitro and unseen in vivo concentrations is shown to vastly outperform a variety of shallow learning algorithms previously used for neurotransmitter discrimination. DiscrimNet is shown to generalize well to data captured from electrodes unseen during model training, eliminating the need to retrain the model for each new electrode. DiscrimNet is also shown to accurately predict the expected changes in dopamine and serotonin after cocaine and oxycodone administration in anesthetized rats in vivo. DiscrimNet therefore offers an exciting new method for real-time resolution of in vivo voltammetric signals into component neurotransmitters.

Elucidating the pathogenesis behind arteriovenous malformations of the central nervous system: a bibliometric analysis.

Arteriovenous malformations (AVMs) are vascular malformations of the central nervous system (CNS) with potential for significant consequences. The exact pathophysiologic mechanism of AVM formation is not fully understood. This study aims to evaluate bibliometric parameters and citations of the literature of AVMs to provide an overview of how the field has evolved. We performed an electronic search on Web of Science to identify the top 100 published and indexed articles with the highest number of citations discussing the pathogenesis of AVMs. This study yielded 1863 articles, of which the top 100 were selected based on the highest total citation count. These articles included 24% basic science, 46% clinical, and 30% review articles. The most-cited article was a clinical article from 2003, and the most recent was published in 2022. The median number of authors was 6, with the highest being 46 for a clinical article. The top 5 journals were identified, with the highest impact factor being 20.1. 13 countries were identified, with the US contributing the most articles (approximately 70%). Regarding genes of investigation, VEGF was one of the early genes investigated, while more interested in RAS/MAPK has been garnered since 2015. There is a growing interest in AVM genomics and pathogenesis research. While progress has been made in understanding clinical aspects and risk factors, the exact pathophysiological mechanisms and genetic basis of AVM formation remain incompletely understood. Further investigation of key genes in AVM pathogenesis can allow identification of potential therapeutic targets.

Acute to long-term characteristics of impedance recordings during neurostimulation in humans.

Objective.This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Approach.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24 h impedance cycle throughout the multi-month recording.Main results.Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 d to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24 h impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.Significance.Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.

Acute to long-term characteristics of impedance recordings during neurostimulation in humans.

Objective: This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus (AMG-HPC), and posterior hippocampus (post-HPC) over an extended period. Approach: Impedance was periodically sampled every 5-15 minutes over several months in five subjects with drug-resistant epilepsy using an experimental neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24-hour impedance cycle throughout the multi-month recording. Main results: Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 days to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24-hour impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures. Significance: Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.

Genetic Modulation at the Neural Microelectrode Interface: Methods and Applications.

The use of implanted microelectrode arrays (MEAs), in the brain, has enabled a greater understanding of neural function, and new treatments for neurodegenerative diseases and psychiatric disorders. Glial encapsulation of the device and the loss of neurons at the device-tissue interface are widely believed to reduce recording quality and limit the functional device-lifetime. The integration of microfluidic channels within MEAs enables the perturbation of the cellular pathways, through defined vector delivery. This provides new approaches to shed light on the underlying mechanisms of the reactive response and its contribution to device performance. In chronic settings, however, tissue ingrowth and biofouling can obstruct or damage the channel, preventing vector delivery. In this study, we describe methods of delivering vectors through chronically implanted, single-shank, "Michigan"-style microfluidic devices, 1⁻3 weeks, post-implantation. We explored and validated three different approaches for modifying gene expression at the device-tissue interface: viral-mediated overexpression, siRNA-enabled knockdown, and cre-dependent conditional expression. We observed a successful delivery of the vectors along the length of the MEA, where the observed expression varied, depending on the depth of the injury. The methods described are intended to enable vector delivery through microfluidic devices for a variety of potential applications; likewise, future design considerations are suggested for further improvements on the approach.

Functional remodeling of subtype-specific markers surrounding implanted neuroprostheses.

Microelectrode arrays implanted in the brain are increasingly used for the research and treatment of intractable neurological disease. However, local neuronal loss and glial encapsulation are known to interfere with effective integration and communication between implanted devices and brain tissue, where these observations are typically based on assessments of broad neuronal and astroglial markers. However, both neurons and astrocytes comprise heterogeneous cellular populations that can be further divided into subclasses based on unique functional and morphological characteristics. In this study, we investigated whether or not device insertion causes alterations in specific subtypes of these cells. We assessed the expression of both excitatory and inhibitory markers of neurotransmission (vesicular glutamate and GABA transporters, VGLUT1 and VGAT, respectively) surrounding single-shank Michigan-style microelectrode arrays implanted in the motor cortex of adult rats by use of quantitative immunohistochemistry. We found a pronounced shift from significantly elevated VGLUT1 within the initial days following implantation to relatively heightened VGAT by the end of the 4-wk observation period. Unexpectedly, we observed VGAT positivity in a subset of reactive astrocytes during the first week of implantation, indicating heterogeneity in early-responding encapsulating glial cells. We coupled our VGLUT1 data with the evaluation of a second marker of excitatory neurons (CamKiiα); the results closely paralleled each other and underscored a progression from initially heightened to subsequently weakened excitatory tone in the neural tissue proximal to the implanted electrode interface (within 40 µm). Our results provide new evidence for subtype-specific remodeling surrounding brain implants that inform observations of suboptimal integration and performance.NEW & NOTEWORTHY We report novel changes in the local expression of excitatory and inhibitory synaptic markers surrounding microelectrode arrays implanted in the motor cortex of rats, where a progressive shift toward increased inhibitory tone was observed over the 4-wk observation period. The result was driven by declining glutamate transporter expression (VGLUT1) in parallel with increasing GABA transporter expression (VGAT) over time, where a reactive VGAT+ astroglial subtype made an unexpected contribution to our findings.