Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry

Modulation of serotonin transporter expression by escitalopram under inflammation

Selective serotonin reuptake inhibitors (SSRIs) are widely used for depression based on the monoamine deficiency hypothesis. However, the clinical use of these agents is controversial, in part because of their variable clinical efficacy and in part because of their delayed onset of action. Because of the complexities involved in replicating human disease and clinical dosing in animal models, the scientific community has not reached a consensus on the reasons for these phenomena. In this work, we create a theoretical hippocampal model incorporating escitalopram's pharmacokinetics, pharmacodynamics (competitive and non-competitive inhibition, and serotonin transporter (SERT) internalization), inflammation, and receptor dynamics. With this model, we simulate chronic oral escitalopram in mice showing that days to weeks are needed for serotonin levels to reach steady-state. We show escitalopram's chemical efficacy is diminished under inflammation. Our model thus offers mechanisms for how chronic escitalopram affects brain serotonin, emphasizing the importance of optimized dose and time for future antidepressant discoveries.

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.

Maximizing Electrochemical Information: A Perspective on Background-Inclusive Fast Voltammetry

This perspective encompasses a focused review of the literature leading to a tipping point in electroanalytical chemistry. We tie together the threads of a "revolution" quietly in the making for years through the work of many authors. Long-held misconceptions about the use of background subtraction in fast voltammetry are addressed. We lay out future advantages that accompany background-inclusive voltammetry, particularly when paired with modern machine-learning algorithms for data analysis.

Challenges and strategies faced in the electrochemical biosensing analysis of neurochemicals in vivo: A review

Our brain is an intricate neuromodulatory network, and various neurochemicals, including neurotransmitters, neuromodulators, gases, ions, and energy metabolites, play important roles in regulating normal brain function. Abnormal release or imbalance of these substances will lead to various diseases such as Parkinson's and Alzheimer's diseases, therefore, in situ and real-time analysis of neurochemical interactions in pathophysiological conditions is beneficial to facilitate our understanding of brain function. Implantable electrochemical biosensors are capable of monitoring neurochemical signals in real time in extracellular fluid of specific brain regions because they can provide excellent temporal and spatial resolution. However, in vivo electrochemical biosensing analysis mainly faces the following challenges: First, foreign body reactions induced by microelectrode implantation, non-specific adsorption of proteins and redox products, and aggregation of glial cells, which will cause irreversible degradation of performance such as stability and sensitivity of the microsensor and eventually lead to signal loss; Second, various neurochemicals coexist in the complex brain environment, and electroactive substances with similar formal potentials interfere with each other. Therefore, it is a great challenge to design recognition molecules and tailor functional surfaces to develop in vivo electrochemical biosensors with high selectivity. Here, we take the above challenges as a starting point and detail the basic design principles for improving in vivo stability, selectivity and sensitivity of microsensors through some specific functionalized surface strategies as case studies. At the same time, we summarize surface modification strategies for in vivo electrochemical biosensing analysis of some important neurochemicals for researchers' reference. In addition, we also focus on the electrochemical detection of low basal concentrations of neurochemicals in vivo via amperometric waveform techniques, as well as the stability and biocompatibility of reference electrodes during long-term sensing, and provide an outlook on the future direction of in vivo electrochemical neurosensing.

Techniques for Measurement of Serotonin: Implications in Neuropsychiatric Disorders and Advances in Absolute Value Recording Methods

Serotonin (5-HT) is a monoamine neurotransmitter in the peripheral, enteric, and central nervous systems (CNS). Within the CNS, serotonin is principally involved in mood regulation and reward-seeking behaviors. It is a critical regulator in CNS pathologies such as major depressive disorder, addiction, and schizophrenia. Consequently, in vivo serotonin measurements within the CNS have emerged as one of many promising approaches to investigating the pathogenesis, progression, and treatment of these and other neuropsychiatric conditions. These techniques vary in methods, ranging from analyte sampling with microdialysis to voltammetry. Provided this diversity in approach, inherent differences between techniques are inevitable. These include biosensor size, temporal/spatial resolution, and absolute value measurement capabilities, all of which must be considered to fit the prospective researcher's needs. In this review, we summarize currently available methods for the measurement of serotonin, including novel voltammetric absolute value measurement techniques. We also detail serotonin's role in various neuropsychiatric conditions, highlighting the role of phasic and tonic serotonergic neuronal firing within each where relevant. Lastly, we briefly review the present clinical application of these techniques and discuss the potential of a closed-loop monitoring and neuromodulation system utilizing deep brain stimulation (DBS).

Stable in-vivo electrochemical sensing of tonic serotonin levels using PEDOT/CNT-coated glassy carbon flexible microelectrode arrays

Chronic sampling of tonic serotonin (5-hydroxytryptamine, 5-HT) concentrations in the brain is critical for tracking neurological disease development and the time course of pharmacological treatments. Despite their value, in vivo chronic multi-site measurements of tonic 5-HT have not been reported. To fill this technological gap, we batch-fabricated implantable glassy carbon (GC) microelectrode arrays (MEAs) onto a flexible SU-8 substrate to provide an electrochemically stable and biocompatible device/tissue interface. To achieve detection of tonic 5-HT concentrations, we applied a poly(3,4-ethylenedioxythiophene)/carbon nanotube (PEDOT/CNT) electrode coating and optimized a square wave voltammetry (SWV) waveform for selective 5-HT measurement. In vitro, the PEDOT/CNT-coated GC microelectrodes achieved high sensitivity to 5-HT, good fouling resistance, and excellent selectivity against the most common neurochemical interferents. In vivo, our PEDOT/CNT-coated GC MEAs successfully detected basal 5-HT concentrations at different locations within the CA2 region of the hippocampus of both anesthetized and awake mice. Furthermore, the PEDOT/CNT-coated MEAs were able to detect tonic 5-HT in the mouse hippocampus for one week after implantation. Histology reveals that the flexible GC MEA implants caused less tissue damage and reduced inflammatory response in the hippocampus compared to commercially available stiff silicon probes. To the best of our knowledge, this PEDOT/CNT-coated GC MEA is the first implantable, flexible sensor capable of chronic in vivo multi-site sensing of tonic 5-HT.

Galvanic Redox Potentiometry for Fouling-Free and Stable Serotonin Sensing in a Living Animal Brain

Serotonin (5-HT) is a major neurotransmitter broadly involved in many aspects of feeling and behavior. Although its electro-activity makes it a promising candidate for electrochemical sensing, the persistent generation of fouling layers on the electrode by its oxidation products presents a hurdle for reliable sensing. Here, we present a fouling-free 5-HT sensor based on galvanic redox potentiometry. The sensor efficiently minimizes electrode fouling as revealed by in situ Raman spectroscopy, ensuring a less than 3 % signal change in a 2 hour continuous experiment, whereas amperometric sensors losing 90 % within 30 min. Most importantly, the sensor is highly amenable for in vivo studies, permitting real-time 5-HT monitoring, and supporting the mechanism associated with serotonin release in brain. Our system offers an effective way for sensing different neurochemicals having significant fouling issues, thus facilitating the molecular-level understanding of brain function.

Implantable flexible multielectrode arrays for multi-site sensing of serotonin tonic levels

Real-time multi-channel measurements of tonic serotonin (5-hydroxytryptamine, 5-HT) concentrations across different brain regions are of utmost importance to the understanding of 5-HT’s role in anxiety, depression, and impulse control disorders, which will improve the diagnosis and treatment of these neuropsychiatric illnesses. Chronic sampling of 5-HT is critical in tracking disease development as well as the time course of pharmacological treatments. Despite their value, in vivo chronic multi-site measurements of 5-HT have not been reported. To fill this technological gap, we batch fabricated implantable glassy carbon (GC) microelectrode arrays (MEAs) on a flexible SU-8 substrate to provide an electrochemically stable and biocompatible device/tissue interface. Then, to achieve multi-site detection of tonic 5-HT concentrations, we incorporated the poly(3,4-ethylenedioxythiophene)/functionalized carbon nanotube (PEDOT/CNT) coating on the GC microelectrodes in combination with a new square wave voltammetry (SWV) approach, optimized for selective 5-HT measurement. In vitro , the PEDOT/CNT coated GC microelectrodes achieved high sensitivity towards 5-HT, good fouling resistance in the presence of 5-HT, and excellent selectivity towards the most common neurochemical interferents. In vivo , our PEDOT/CNT-coated GC MEAs were able to successfully detect basal 5-HT concentrations at different locations of the CA2 hippocampal region of mice in both anesthetized and awake head-fixed conditions. Furthermore, the implanted PEDOT/CNT-coated MEA achieved stable detection of tonic 5-HT concentrations for one week. Finally, histology data in the hippocampus shows reduced tissue damage and inflammatory responses compared to stiff silicon probes. To the best of our knowledge, this PEDOT/CNT-coated GC MEA is the first implantable flexible multisite sensor capable of chronic in vivo multi-site sensing of tonic 5-HT. This implantable MEA can be custom-designed according to specific brain region of interests and research questions, with the potential to combine electrophysiology recording and multiple analyte sensing to maximize our understanding of neurochemistry.

Highlights

PEDOT/CNT-coated GC microelectrodes enabled sensitive and selective tonic detection of serotonin (5-HT) using a new square wave voltammetry (SWV) approach PEDOT/CNT-coated GC MEAs achieved multi-site in vivo 5-HT tonic detection for one week. Flexible MEAs lead to reduced tissue damage and inflammation compared to stiff silicon probes.

Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo

Tonic extracellular neurotransmitter concentrations are important modulators of central network homeostasis. Disruptions in these tonic levels are thought to play a role in neurologic and psychiatric disease. Therefore, ways to improve their quantification are actively being investigated. Previously published voltammetric software packages have implemented FSCV, which is not capable of measuring tonic concentrations of neurotransmitters in vivo. In this paper, custom software was developed for near-real-time tracking (scans every 10 s) of neurotransmitters’ tonic concentrations with high sensitivity and spatiotemporal resolution both in vitro and in vivo using cyclic voltammetry combined with dynamic background subtraction (M-CSWV and FSCAV). This software was designed with flexibility, speed, and user-friendliness in mind. This software enables near-real-time measurement by reducing data analysis time through an optimized modeling algorithm, and efficient memory handling makes long-term measurement possible. The software permits customization of the cyclic voltammetric waveform shape, enabling experiments to detect a specific analyte of interest. Finally, flexibility considerations allow the user to alter the fitting parameters, filtering characteristics, and size and shape of the analyte kernel, based on data obtained live during the experiment to obtain accurate measurements as experimental conditions change. Herein, the design and advantages of this near-real-time voltammetric software are described, and its use is demonstrated in in vivo experiments.

Deep Brain Stimulation for Addictive Disorders-Where Are We Now?

In the face of a global epidemic of drug addiction, neglecting to develop new effective therapies will perpetuate the staggering human and economic costs of substance use. This review aims to summarize and evaluate the preclinical and clinical studies of deep brain stimulation (DBS) as a novel therapy for refractory addiction, in hopes to engage and inform future research in this promising novel treatment avenue. An electronic database search (MEDLINE, EMBASE, Cochrane library) was performed using keywords and predefined inclusion criteria between 1974 and 6/18/2021 (registered on Open Science Registry). Selected articles were reviewed in full text and key details were summarized and analyzed to understand DBS' therapeutic potential and possible mechanisms of action. The search yielded 25 animal and 22 human studies. Animal studies showed that DBS of targets such as nucleus accumbens (NAc), insula, and subthalamic nucleus reduces drug use and seeking. All human studies were case series/reports (level 4/5 evidence), mostly targeting the NAc with generally positive outcomes. From the limited evidence in the literature, DBS, particularly of the NAc, appears to be a reasonable last resort option for refractory addictive disorders. We propose that future research in objective electrophysiological (e.g., local field potentials) and neurochemical (e.g., extracellular dopamine levels) biomarkers would assist monitoring the progress of treatment and developing a closed-loop DBS system. Preclinical literature also highlighted the prefrontal cortex as a promising DBS target, which should be explored in human research.