Monitoring In Vivo Changes in Tonic Extracellular Dopamine Level by Charge-Balancing Multiple Waveform Fast-Scan Cyclic Voltammetry

Micromagnetic stimulation (μMS) controls dopamine release: anin vivostudy using WINCSHarmoni

Research into the role of neurotransmitters in regulating normal and pathologic brain functions has made significant progress. Yet, clinical trials that aim to improve therapeutic interventions do not take advantage of thein vivochanges in the neurochemistry that occur in real time during disease progression, drug interactions or response to pharmacological, cognitive, behavioral, and neuromodulation therapies. In this work, we used the WINCSHarmonitool to study the real timein vivochanges in dopamine release in rodent brains for the micromagnetic neuromodulation therapy. Although still in its infancy, micromagnetic stimulation (μMS) using micro-meter sized coils or microcoils (μcoils) has shown incredible promise in spatially selective, galvanic contact free and highly focal neuromodulation. These μcoils are powered by a time-varying current which generates a magnetic field. As per Faraday's Laws of Electromagnetic Induction, this magnetic field induces an electric field in a conducting medium (here, the brain tissues). We used a solenoidal-shaped μcoil to stimulate the medial forebrain bundle (MFB) of the rodent brainin vivo. The evokedin vivodopamine releases in the striatum were tracked in real time by carbon fiber microelectrodes (CFM) using fast scan cyclic voltammetry (FSCV). Our experiments report that μcoils can successfully activate the MFB in rodent brains, triggering dopamine releasein vivo. We further show that the successful release of dopamine upon micromagnetic stimulation is dependent on the orientation of the μcoil. Furthermore, varied intensities of μMS can control the concentration of dopamine releases in the striatum. This work helps us better understand the brain and its conditions arising from a new therapeutic intervention, like μMS, at the level of neurotransmitter release. Despite its early stage, this study potentially paves the path for μMS to enter the clinical world as a precisely controlled and optimized neuromodulation therapy.

SeroWare: An Open-Source Software Suite for Voltammetry Data Acquisition and Analysis

Voltammetry is widely used for fast, data-dense measurements of redox-active analytes in versatile environments, including the brain. Voltammetry requires minimal hardware beyond a potentiostat, a front-end amplifier, and a computer. Nonetheless, researchers must often develop or modify software packages for application-specific uses. Of the voltammetry software available, significant issues exist with source code inaccessible for updating or customization, nonconfigurable data processing procedures, and hardware incompatibilities. These limitations, coupled with the recent proliferation of waveform types and increased demands for high bandwidth data acquisition and efficient data processing, create the need for sophisticated, powerful, and flexible voltammetry software. We report developing "SeroWare", an open-source, end-to-end voltammetry acquisition and analysis software package designed to handle a wide variety of use cases encountered by voltammetry users. Although inspired by neurochemical analyses, this software is flexible, customizable, and compatible with open-source toolkits. The modular software architecture enables users to generate, acquire, and analyze voltammetry data of different types, ranging from pulse and sweep waveforms to fast and slow scans via easily accessible and exportable file formats. Template code is provided for communicating with a variety of standard external devices. We report several novel features for waveform applications and data flow. In-depth documentation in a User Guide and video tutorials are provided to enable new research directions, particularly regarding shareability and lowering the barriers to entry for new investigators.

Batch-fabricated full glassy carbon fibers for real-time tonic and phasic dopamine detection

Dopamine (DA) is a critical neurotransmitter that is key in regulating motor functions, motivation, and reward-related behavior. Measuring both tonic (baseline, steady-state) and phasic (rapid, burst-like) DA release is essential for elucidating the mechanisms underlying neurological disorders, such as schizophrenia and Parkinson's disease, which are associated with dysregulated tonic and phasic DA signaling. Carbon fiber microelectrodes (CFEs) are considered the gold standard for measuring rapid neurotransmitter changes due to their small size (5-10 µm), biocompatibility, flexibility, and excellent electrochemical properties. However, achieving consistent results and large-scale production of CFE arrays through manual fabrication poses significant challenges. We previously developed flexible glassy carbon (GC) microelectrode arrays (MEAs) and GC fiber-like MEAs (GCF MEAs) for neurotransmitter detection and electrophysiology recording. We also demonstrated the feasibility of fabricating GC MEA with both GC electrodes and interconnects made from a single homogeneous material, eliminating the need for metal interconnections and addressing related concerns about electrical and mechanical stability under prolonged electrochemical cycling. Building on our prior experience, we now present a double-etching microfabrication technique for the batch production of 10 μm × 10 µm full GC fibers (fGCFs) and fGCF arrays, composed entirely of homogeneous GC material. This process uses a 2 µm-thick low-stress silicon nitride as the bottom insulator layer for the fGCFs. The effectiveness of the fabrication process was validated through scanning electron microscophy (SEM) and energy dispersive X-ray spectroscopy (EDS) elemental analyses, which confirmed the uniformity of the Si₃N₄ insulation layer and ensured the overall integrity of the fGCFs. Using finite element analysis, we optimized the fGCF form factor to achieve self-penetration up to 3 mm into the mouse striatum without additional support. The electrochemical characterization of fGCFs demonstrated high electrical conductivity and a wide electrochemical window. The ability of fGCFs to detect phasic and tonic DA release was confirmed using fast scan cyclic voltammetry (FSCV) and square wave voltammetry (SWV), respectively, both in vitro and in vivo. With their high sensitivity for phasic and tonic DA detection, combined with a scalable fabrication process and self-supporting insertion capability, fGCFs are promising sensors that offer enhanced practicality for comprehensive DA monitoring.

Recent Progress in Flexible Microelectrode Arrays for Combined Electrophysiological and Electrochemical Sensing

Understanding brain function requires advanced neural probes to monitor electrical and chemical signaling across multiple timescales and brain regions. Microelectrode arrays (MEAs) are widely used to record neurophysiological activity across various depths and brain regions, providing single-unit resolution for extended periods. Recent advancements in flexible MEAs, built on micrometer-thick polymer substrates, have improved integration with brain tissue by mimicking the brain's soft nature, reducing mechanical trauma and inflammation. These flexible, subcellular-scale MEAs can record stable neural signals for months, making them ideal for long-term studies. In addition to electrical recording, MEAs have been functionalized for electrochemical neurotransmitter detection. Electroactive neurotransmitters, such as dopamine, serotonin, and adenosine, can be directly measured via electrochemical methods, particularly on carbon-based surfaces. For non-electroactive neurotransmitters like acetylcholine, glutamate, and γ-aminobutyric acid, alternative strategies, such as enzyme immobilization and aptamer-based recognition, are employed to generate electrochemical signals. This review highlights recent developments in flexible MEA fabrication and functionalization to achieve both electrochemical and electrophysiological recordings, minimizing sensor fowling and brain damage when implanted long-term. It covers multi-time scale neurotransmitter detection, development of conducting polymer and nanomaterial composite coatings to enhance sensitivity, incorporation of enzyme and aptamer-based recognition methods, and the integration of carbon electrodes on flexible MEAs. Finally, it summarizes strategies to acquire electrochemical and electrophysiological measurements from the same device.

Ventral tegmental area deep brain stimulation reverses ethanol-induced dopamine increase in the rat nucleus accumbens

The neurophysiology of alcohol use disorder (AUD) is complex, but a major contributor to addictive phenotypes is the tendency for drugs of abuse to increase tonic extracellular dopamine (DA) levels in the nucleus accumbens (NAc). Repeated exposure to substances of abuse such as ethanol results in the overstimulation of the mesolimbic pathway, causing an excessive release of DA from the ventral tegmental area (VTA) to target regions such as the NAc. This heightened DA signaling is associated with the reinforcing effects of substances, leading to a strong desire for continued use. Recent work has postulated that high frequency deep brain stimulation (DBS) of the ventral tegmental area may reduce dopamine transmission to the nucleus accumbens following acute drug of abuse exposure, thereby mitigating the drug's addictive potential. We first demonstrate ethanol's ability to decrease phasic DA release over time and to increase tonic extracellular DA concentrations in the nucleus accumbens. Next, we demonstrate the capability for high frequency VTA DBS to reverse this ethanol-associated surge in tonic DA concentrations in the nucleus accumbens to levels not significantly different from baseline. This study suggests a promising new avenue for investigating the mechanisms of alcohol use disorder.

Wideband ratiometric measurement of tonic and phasic dopamine release in the striatum

Reward learning, cognition, and motivation are supported by changes in neurotransmitter levels across multiple timescales. Current measurement technologies for various neuromodulators (such as dopamine and serotonin) do not bridge timescales of fluctuations, limiting the ability to define the behavioral significance, regulation, and relationship between fast (phasic) and slow (tonic) dynamics. To help resolve longstanding debates about the behavioral significance of dopamine across timescales, we developed a novel quantification strategy, augmenting extensively used carbon-fiber Fast Scan Cyclic Voltammetry (FSCV). We iteratively engineered the FSCV scan sequence to rapidly modify electrode sensitivity within a sampling window and applied ratiometric analysis for wideband dopamine measurement. This allowed us to selectively eliminate artifacts unrelated to electrochemical detection (i.e., baseline drift), overcoming previous limitations that precluded wideband dopamine detection from milliseconds to hours. We extensively characterize this approach in vitro, validate performance in vivo with simultaneous microdialysis, and deploy this technique to measure wideband dopamine changes across striatal regions under pharmacological, optogenetic, and behavioral manipulations. We demonstrate that our approach can extend to additional analytes, including serotonin and pH, providing a robust platform to assess the contributions of multi-timescale neuromodulator fluctuations to cognition, learning, and motivation.

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.

Understanding the different effects of fouling mechanisms on working and reference electrodes in fast-scan cyclic voltammetry for neurotransmitter detection

Fast-scan cyclic voltammetry (FSCV) is a widely used technique for detecting neurotransmitters. However, electrode fouling can negatively impact its accuracy and sensitivity. Fouling refers to the accumulation of unwanted materials on the electrode surface, which can alter its electrochemical properties and reduce its sensitivity and selectivity. Fouling mechanisms can be broad and may include biofouling, the accumulation of biomolecules on the electrode surface, and chemical fouling, the deposition of unwanted chemical species. Despite individual studies discussing fouling effects on either the working electrode or the reference electrode, no comprehensive study has been conducted to compare the overall fouling effects on both electrodes in the context of FSCV. Here, we examined the effects of biofouling and chemical fouling on the carbon fiber micro-electrode (CFME) as the working electrode and the Ag/AgCl reference electrode with FSCV. Both fouling mechanisms significantly decreased the sensitivity and caused peak voltage shifts in the FSCV signal with the CFME, but not with the Ag/AgCl reference electrode. Interestingly, previous studies have reported peak voltage shifts in FSCV signals due to the fouling of Ag/AgCl electrodes after implantation in the brain. We noticed in a previous study that energy-dispersive spectroscopy (EDS) spectra showed increased sulfide ion concentration after implantation. We hypothesized that sulfide ions may be responsible for the peak voltage shift. To test this hypothesis, we added sulfide ions to the buffer solution, which decreased the open circuit potential of the Ag/AgCl electrode and caused a peak voltage shift in the FSCV voltammograms. Also, EDS analysis showed that sulfide ion concentration increased on the surface of the Ag/AgCl electrodes after 3 weeks of chronic implantation, necessitating consideration of sulfide ions as the fouling agent for the reference electrodes. Overall, our study provides important insights into the mechanisms of electrode fouling and its impact on FSCV measurements. These findings could inform the design of FSCV experiments, with the development of new strategies for improving the accuracy and reliability of FSCV measurements in vivo.

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.

Continuous long-range measurement of tonic dopamine with advanced FSCV for pharmacodynamic analysis of levodopa-induced dyskinesia in Parkinson's disease

Levodopa, a dopamine prodrug, alleviates the motor symptoms of Parkinson's disease (PD), but its chronic use gives rise to levodopa-induced dyskinesia (LID). However, it remains unclear whether levodopa pharmacodynamics is altered during the progressive onset of LID. Using in vivo fast-scan cyclic voltammetry and second-derivative-based background drift removal, we continuously measured tonic dopamine levels using high temporal resolution recording over 1-h. Increases to tonic dopamine levels following acute levodopa administration were slow and marginal within the naïve PD model. However, these levels increased faster and higher in the LID model. Furthermore, we identified a strong positive correlation of dyskinetic behavior with the rate of dopamine increase, but much less with its cumulative level, at each time point. Here, we identified the altered signature of striatal DA dynamics underlying LID in PD using an advanced FSCV technique that demonstrates the long-range dynamics of tonic dopamine following drug administration.

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).

Improved circuitry and post-processing for interleaved fast-scan cyclic voltammetry and electrophysiology measurements

The combination of electrophysiology and electrochemistry acquisition methods using a single carbon fiber microelectrode (CFM) in the brain has enabled more extensive analysis of neurochemical release, neural activity, and animal behavior. Predominantly, analog CMOS (Complementary Metal Oxide Semiconductor) switches are used for these interleaved applications to alternate the CFM output between electrophysiology and electrochemistry acquisition circuitry. However, one underlying issue with analog CMOS switches is the introduction of transient voltage artifacts in recorded electrophysiology signals resulting from CMOS charge injection. These injected artifacts attenuate electrophysiology data and delay reliable signal observation after every switch actuation from electrochemistry acquisition. Previously published attempts at interleaved electrophysiology and electrochemistry were able to recover reliable electrophysiology data within approximately 10-50 ms after switch actuation by employing various high-pass filtering methods to mitigate the observed voltage artifacts. However, high-pass filtering of this nature also attenuates valuable portions of the local-field potential (LFP) frequency range, thus limiting the extent of network-level insights that can be derived from in vivo measurements. This paper proposes a solution to overcome the limitation of charge injection artifacts that affect electrophysiological data while preserving important lower-frequency LFP bands. A voltage follower operational amplifier was integrated before the CMOS switch to increase current flow to the switch and dissipate any injected charge. This hardware addition resulted in a 16.98% decrease in electrophysiology acquisition delay compared to circuitry without a voltage follower. Additionally, single-term exponential modeling was implemented in post-processing to characterize and subtract remaining transient voltage artifacts in recorded electrophysiology data. As a result, electrophysiology data was reliably recovered 3.26 ± 0.22 ms after the beginning of the acquisition period (a 60% decrease from previous studies), while also minimizing LFP attenuation. Through these advancements, coupled electrophysiology and electrochemistry measurements can be conducted at higher scan rates while retaining data integrity for a more comprehensive analysis of neural activity and neurochemical release.

Simultaneous Estimation of Tonic Dopamine and Serotonin with High Temporal Resolution In Vitro Using Deep Learning

Quantitative measurement of the phasic (changes in several seconds) and tonic (changes in minutes to hours) level changes of neurotransmitters is an essential technique for understanding brain functions and brain diseases regulated by the neurotransmitters. However, monitoring phasic and tonic levels of multiple neurotransmitters is still a challenging technology. Microdialysis can measure the tonic levels of multiple neurotransmitters simultaneously but has a low temporal resolution (minute) to analyze precisely. Fast-scan cyclic voltammetry (FSCV) has high temporal resolution and high sensitivity, but it was not able to simultaneously measure the tonic level of multiple neurotransmitters. The recently proposed deep learning-based FSCV method was still only capable of phasic concentration estimation of neurotransmitters. In this study, we estimate the tonic levels of dopamine and serotonin simultaneously by training a deep-learning network with the extracted tonic information from the FSCV. The proposed deep learning model was validated in vitro to simultaneously estimate tonic concentrations of two neurotransmitters with statistically significantly higher accuracy than previously proposed background subtraction-based models (p<0.001). In particular, in the case of serotonin concentration estimation error, the proposed model showed higher prediction performance than the background subtraction-based model (48 nM and 73 nM, respectively). We expect that the proposed technique will help simultaneous measurement of the phasic and tonic levels of numerous neurotransmitters in vivo soon.Clinical Relevance- This study proposes a method to simultaneously measure tonic dopamine and tonic serotonin with high temporal resolution with a single electrode in the brain.

Oxycodone-induced dopaminergic and respiratory effects are modulated by deep brain stimulation

Introduction: Opioids are the leading cause of overdose death in the United States, accounting for almost 70,000 deaths in 2020. Deep brain stimulation (DBS) is a promising new treatment for substance use disorders. Here, we hypothesized that VTA DBS would modulate both the dopaminergic and respiratory effect of oxycodone. Methods: Multiple-cyclic square wave voltammetry (M-CSWV) was used to investigate how deep brain stimulation (130 Hz, 0.2 ms, and 0.2 mA) of the rodent ventral segmental area (VTA), which contains abundant dopaminergic neurons, modulates the acute effects of oxycodone administration (2.5 mg/kg, i.v.) on nucleus accumbens core (NAcc) tonic extracellular dopamine levels and respiratory rate in urethane-anesthetized rats (1.5 g/kg, i.p.). Results: I.V. administration of oxycodone resulted in an increase in NAcc tonic dopamine levels (296.9 ± 37.0 nM) compared to baseline (150.7 ± 15.5 nM) and saline administration (152.0 ± 16.1 nM) (296.9 ± 37.0 vs. 150.7 ± 15.5 vs. 152.0 ± 16.1, respectively, p = 0.022, n = 5). This robust oxycodone-induced increase in NAcc dopamine concentration was associated with a sharp reduction in respiratory rate (111.7 ± 2.6 min-1 vs. 67.9 ± 8.3 min-1; pre- vs. post-oxycodone; p < 0.001). Continuous DBS targeted at the VTA (n = 5) reduced baseline dopamine levels, attenuated the oxycodone-induced increase in dopamine levels to (+39.0% vs. +95%), and respiratory depression (121.5 ± 6.7 min-1 vs. 105.2 ± 4.1 min-1; pre- vs. post-oxycodone; p = 0.072). Discussion: Here we demonstrated VTA DBS alleviates oxycodone-induced increases in NAcc dopamine levels and reverses respiratory suppression. These results support the possibility of using neuromodulation technology for treatment of drug addiction.

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.

Micromagnetic Stimulation (μMS) Controls Dopamine Release: An in vivo Study Using WINCS Harmoni

Objective

Research into the role of neurotransmitters in regulating normal and pathologic brain functions has made significant progress. Yet, clinical trials that aim to improve therapeutic interventions do not take advantage of the in vivo changes in the neurochemistry that occur in real time during disease progression, drug interactions or response to pharmacological, cognitive, behavioral, and neuromodulation therapies. In this work, we used the WINCS Harmoni tool to study the real time in vivo changes in dopamine release in rodent brains for the micromagnetic neuromodulation therapy.

Approach

Although still in its infancy, micromagnetic stimulation (µMS) using micro-meter sized coils or microcoils (μcoils) has shown incredible promise in spatially selective, galvanic contact free and highly focal neuromodulation. These μcoils are powered by a time-varying current which generates a magnetic field. As per Faraday's Laws of Electromagnetic Induction, this magnetic field induces an electric field in a conducting medium (here, the brain tissues). We used a solenoidal-shaped μcoil to stimulate the medial forebrain bundle (MFB) of the rodent brain in vivo. The evoked in vivo dopamine releases in the striatum were tracked in real time by carbon fiber microelectrodes (CFM) using fast scan cyclic voltammetry (FSCV).

Results

Our experiments report that μcoils can successfully activate the MFB in rodent brains, triggering dopamine release in vivo. We further show that the successful release of dopamine upon micromagnetic stimulation is dependent on the orientation of the μcoil. Furthermore, varied intensities of µMS can control the concentration of dopamine releases in the striatum.

Significance

This work helps us better understand the brain and its conditions arising from a new therapeutic intervention, like µMS, at the level of neurotransmitter release. Despite its early stage, this study potentially paves the path for µMS to enter the clinical world as a precisely controlled and optimized neuromodulation therapy.

High frequency deep brain stimulation can mitigate the acute effects of cocaine administration on tonic dopamine levels in the rat nucleus accumbens

Cocaine's addictive properties stem from its capacity to increase tonic extracellular dopamine levels in the nucleus accumbens (NAc). The ventral tegmental area (VTA) is a principal source of NAc dopamine. To investigate how high frequency stimulation (HFS) of the rodent VTA or nucleus accumbens core (NAcc) modulates the acute effects of cocaine administration on NAcc tonic dopamine levels multiple-cyclic square wave voltammetry (M-CSWV) was used. VTA HFS alone decreased NAcc tonic dopamine levels by 42%. NAcc HFS alone resulted in an initial decrease in tonic dopamine levels followed by a return to baseline. VTA or NAcc HFS following cocaine administration prevented the cocaine-induced increase in NAcc tonic dopamine. The present results suggest a possible underlying mechanism of NAc deep brain stimulation (DBS) in the treatment of substance use disorders (SUDs) and the possibility of treating SUD by abolishing dopamine release elicited by cocaine and other drugs of abuse by DBS in VTA, although further studies with chronic addiction models are required to confirm that. Furthermore, we demonstrated the use of M-CSWV can reliably measure tonic dopamine levels in vivo with both drug administration and DBS with minimal artifacts.

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.

Second-Derivative-Based Background Drift Removal for a Tonic Dopamine Measurement in Fast-Scan Cyclic Voltammetry

The dysregulation of dopamine, a neuromodulator, is associated with a broad spectrum of brain disorders, including Parkinson's disease, addiction, and schizophrenia. Quantitative measurements of dopamine are essential for understanding dopamine functional dynamics. Fast-scan cyclic voltammetry (FSCV) is the most popular electrochemical technique for measuring real-time in vivo dopamine level changes. Standard FSCV has only analyzed "phasic dopamine" (changes in seconds) because the gradual generation of background charging current is inevitable and is the primary noise source in the low-frequency band. Although "tonic dopamine" (changes in minutes to hours) is critical for understanding the dopamine system, an electrochemical technique capable of simultaneously measuring phasic and tonic dopamine in an in vivo environment has not been established. Several modified voltammetric techniques have been developed for measuring tonic dopamine; however, the sampling rates (0.1-0.05 Hz) are too low to be useful. Further investigation of the in vivo applicability of previously developed background drift removal methods for measuring tonic dopamine levels is required. We developed a second-derivative-based background removal (SDBR) method for simultaneously measuring phasic and tonic neurotransmitter levels in real-time. The performance of this technique was tested via in silico and in vitro tonic dopamine experiments. Furthermore, its applicability was tested in vivo. SDBR is a simple, robust, postprocessing technique that can extract tonic neurotransmitter levels from all FSCV data. As SDBR is calculated in individual-scan voltammogram units, it can be applied to any real-time closed-loop system that uses a neurotransmitter as a biomarker.

Flexible Glassy Carbon Multielectrode Array for In Vivo Multisite Detection of Tonic and Phasic Dopamine Concentrations

Dopamine (DA) plays a central role in the modulation of various physiological brain functions, including learning, motivation, reward, and movement control. The DA dynamic occurs over multiple timescales, including fast phasic release, as a result of neuronal firing and slow tonic release, which regulates the phasic firing. Real-time measurements of tonic and phasic DA concentrations in the living brain can shed light on the mechanism of DA dynamics underlying behavioral and psychiatric disorders and on the action of pharmacological treatments targeting DA. Current state-of-the-art in vivo DA detection technologies are limited in either spatial or temporal resolution, channel count, longitudinal stability, and ability to measure both phasic and tonic dynamics. We present here an implantable glassy carbon (GC) multielectrode array on a SU-8 flexible substrate for integrated multichannel phasic and tonic measurements of DA concentrations. The GC MEA demonstrated in vivo multichannel fast-scan cyclic voltammetry (FSCV) detection of electrically stimulated phasic DA release simultaneously at different locations of the mouse dorsal striatum. Tonic DA measurement was enabled by coating GC electrodes with poly(3,4-ethylenedioxythiophene)/carbon nanotube (PEDOT/CNT) and using optimized square-wave voltammetry (SWV). Implanted PEDOT/CNT-coated MEAs achieved stable detection of tonic DA concentrations for up to 3 weeks in the mouse dorsal striatum. This is the first demonstration of implantable flexible MEA capable of multisite electrochemical sensing of both tonic and phasic DA dynamics in vivo with chronic stability.

Applying a Fast-Scan Cyclic Voltammetry to Explore Dopamine Dynamics in Animal Models of Neuropsychiatric Disorders

Progress in the development of technologies for the real-time monitoring of neurotransmitter dynamics has provided researchers with effective tools for the exploration of etiology and molecular mechanisms of neuropsychiatric disorders. One of these powerful tools is fast-scan cyclic voltammetry (FSCV), a technique which has progressively been used in animal models of diverse pathological conditions associated with alterations in dopamine transmission. Indeed, for several decades FSCV studies have provided substantial insights into our understanding of the role of abnormal dopaminergic transmission in pathogenetic mechanisms of drug and alcohol addiction, Parkinson’s disease, schizophrenia, etc. Here we review the applications of FSCV to research neuropsychiatric disorders with particular attention to recent technological advances.

Cocaine increases stimulation-evoked serotonin efflux in the nucleus accumbens

Although dopamine is the most implicated neurotransmitter in the mediation of the pathophysiology of addiction, animal studies show serotonin also plays a vital role. Cocaine is one of the most common illicit drugs globally, but the role of serotonin in its mechanism of action is insufficiently characterized. Consequently, we investigated the acute effects of the psychomotor stimulant cocaine on electrical stimulation-evoked serotonin (phasic) release in the nucleus accumbens core (NAcc) of urethane-anesthetized (1.5 g/kg ip) male Sprague-Dawley rats using N-shaped fast-scan cyclic voltammetry (N-FSCV). A single carbon fiber microelectrode was first implanted in the NAcc. Stimulation was applied to the medial forebrain bundle using 60 Hz, 2 ms, 0.2 mA, 2-s biphasic pulses before and after cocaine (2 mg/kg iv) was administered. Stimulation-evoked serotonin release significantly increased 5 min after cocaine injection compared with baseline (153 ± 21 nM vs. 257 ± 12 nM; P = 0.0042; n = 5) but was unaffected by saline injection (1 mL/kg iv; n = 5). N-FSCV's selective measurement of serotonin release in vivo was confirmed pharmacologically via administration of the selective serotonin reuptake inhibitor escitalopram (10 mg/kg ip) that effectively increased the signal in a separate group of rats (n = 5). Selectivity to serotonin was further confirmed in vitro in which dopamine was minimally detected by N-FSCV with a serotonin to dopamine response ratio of 1:0.04 (200 nM of serotonin:1 µM dopamine ratio; P = 0.0048; n = 5 electrodes). This study demonstrates a noteworthy influence of cocaine on serotonin dynamics, and confirms that N-FSCV can effectively and selectively measure phasic serotonin release in the NAcc.NEW & NOTEWORTHY Serotonin plays a vital role in drug addiction. Here, using N-shaped fast-scan cyclic voltammetry, we demonstrated the effect of cocaine on the phasic release of serotonin at the nucleus accumbens core. To the best of our knowledge, this has not previously been elucidated. Our results not only reinforce the role of serotonin in the mechanism of action of cocaine but also help to fill a gap in our knowledge and provide a baseline for future studies in cocaine addiction.

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

Here, we present the development of a novel voltammetric technique, N-shaped multiple cyclic square wave voltammetry (N-MCSWV) and its application in vivo. It allows quantitative measurements of tonic extracellular levels of serotonin in vivo with mitigated fouling effects. N-MCSWV enriches the electrochemical information by generating high dimensional voltammograms, which enables high sensitivity and selectivity against 5-hydroindoleacetic acid (5-HIAA), dopamine, 3,4-dihydroxyphenylacetic acid (DOPAC), histamine, ascorbic acid, norepinephrine, adenosine, and pH. Using N-MCSWV, in combination with PEDOT:Nafion-coated carbon fiber microelectrodes, a tonic serotonin concentration of 52 ± 5.8 nM (n = 20 rats, ±SEM) was determined in the substantia nigra pars reticulata of urethane-anesthetized rats. Pharmacological challenges with dopaminergic, noradrenergic, and serotonergic synaptic reuptake inhibitors supported the ability of N-MCSWV to selectively detect tonic serotonin levels in vivo. Overall, N-MCSWV is a novel voltammetric technique for analytical quantification of serotonin. It offers continuous monitoring of changes in tonic serotonin concentrations in the brain to further our understanding of the role of serotonin in normal behaviors and psychiatric disorders.

HIV-Associated Apathy/Depression and Neurocognitive Impairments Reflect Persistent Dopamine Deficits

Individuals living with human immunodeficiency virus type 1 (HIV-1) are often plagued by debilitating neurocognitive impairments and affective alterations;the pathophysiology underlying these deficits likely includes dopaminergic system dysfunction. The present review utilized four interrelated aims to critically examine the evidence for dopaminergic alterations following HIV-1 viral protein exposure. First, basal dopamine (DA) values are dependent upon both brain region andexperimental approach (i.e., high-performance liquid chromatography, microdialysis or fast-scan cyclic voltammetry). Second, neurochemical measurements overwhelmingly support decreased DA concentrations following chronic HIV-1 viral protein exposure. Neurocognitive impairments, including alterations in pre-attentive processes and attention, as well as apathetic behaviors, provide an additional line of evidence for dopaminergic deficits in HIV-1. Third, to date, there is no compelling evidence that combination antiretroviral therapy (cART), the primary treatment regimen for HIV-1 seropositive individuals, has any direct pharmacological action on the dopaminergic system. Fourth, the infection of microglia by HIV-1 viral proteins may mechanistically underlie the dopamine deficit observed following chronic HIV-1 viral protein exposure. An inclusive and critical evaluation of the literature, therefore, supports the fundamental conclusion that long-term HIV-1 viral protein exposure leads to a decreased dopaminergic state, which continues to persist despite the advent of cART. Thus, effective treatment of HIV-1-associated apathy/depression and neurocognitive impairments must focus on strategies for rectifying decreases in dopamine function.

Integral methods for automatic quantification of fast-scan-cyclic-voltammetry detected neurotransmitters

Modern techniques for estimating basal levels of electroactive neurotransmitters rely on the measurement of oxidative charges. This requires time integration of oxidation currents at certain intervals. Unfortunately, the selection of integration intervals relies on ad-hoc visual identification of peaks on the oxidation currents, which introduces sources of error and precludes the development of automated procedures necessary for analysis and quantification of neurotransmitter levels in large data sets. In an effort to improve charge quantification techniques, here we present novel methods for automatic selection of integration boundaries. Our results show that these methods allow quantification of oxidation reactions both in vitro and in vivo and of multiple analytes in vitro.

Cocaine-Induced Changes in Tonic Dopamine Concentrations Measured Using Multiple-Cyclic Square Wave Voltammetry in vivo

For over 40 years, in vivo microdialysis techniques have been at the forefront in measuring the effects of illicit substances on brain tonic extracellular levels of dopamine that underlie many aspects of drug addiction. However, the size of microdialysis probes and sampling rate may limit this technique’s ability to provide an accurate assessment of drug effects in microneural environments. A novel electrochemical method known as multiple-cyclic square wave voltammetry (M-CSWV), was recently developed to measure second-to-second changes in tonic dopamine levels at microelectrodes, providing spatiotemporal resolution superior to microdialysis. Here, we utilized M-CSWV and fast-scan cyclic voltammetry (FSCV) to measure changes in tonic or phasic dopamine release in the nucleus accumbens core (NAcc) after acute cocaine administration. Carbon-fiber microelectrodes (CFM) and stimulating electrodes were implanted into the NAcc and medial forebrain bundle (MFB) of urethane anesthetized (1.5 g/kg i.p.) Sprague-Dawley rats, respectively. Using FSCV, depths of each electrode were optimized by determining maximal MFB electrical stimulation-evoked phasic dopamine release. Changes in phasic responses were measured after a single dose of intravenous saline or cocaine hydrochloride (3 mg/kg; n = 4). In a separate group, changes in tonic dopamine levels were measured using M-CSWV after intravenous saline and after cocaine hydrochloride (3 mg/kg; n = 5). Both the phasic and tonic dopamine responses in the NAcc were augmented by the injection of cocaine compared to saline control. The phasic and tonic levels changed by approximately x2.4 and x1.9, respectively. These increases were largely consistent with previous studies using FSCV and microdialysis. However, the minimal disruption/disturbance of neuronal tissue by the CFM may explain why the baseline tonic dopamine values (134 ± 32 nM) measured by M-CSWV were found to be 10-fold higher when compared to conventional microdialysis. In this study, we demonstrated phasic dopamine dynamics in the NAcc with acute cocaine administration. M-CSWV was able to record rapid changes in tonic levels of dopamine, which cannot be achieved with other current voltammetric techniques. Taken together, M-CSWV has the potential to provide an unprecedented level of physiologic insight into dopamine signaling, both in vitro and in vivo, which will significantly enhance our understanding of neurochemical mechanisms underlying psychiatric conditions.

3D fuzzy graphene microelectrode array for dopamine sensing at sub-cellular spatial resolution

The development of a high sensitivity real-time sensor for multi-site detection of dopamine (DA) with high spatial and temporal resolution is of fundamental importance to study the complex spatial and temporal pattern of DA dynamics in the brain, thus improving the understanding and treatments of neurological and neuropsychiatric disorders. In response to this need, here we present high surface area out-of-plane grown three-dimensional (3D) fuzzy graphene (3DFG) microelectrode arrays (MEAs) for highly selective, sensitive, and stable DA electrochemical sensing. 3DFG microelectrodes present a remarkable sensitivity to DA (2.12 ± 0.05 nA/nM, with LOD of 364.44 ± 8.65 pM), the highest reported for nanocarbon MEAs using Fast Scan Cyclic Voltammetry (FSCV). The high surface area of 3DFG allows for miniaturization of electrode down to 2 × 2 μm², without compromising the electrochemical performance. Moreover, 3DFG MEAs are electrochemically stable under 7.2 million scans of continuous FSCV cycling, present exceptional selectivity over the most common interferents in vitro with minimum fouling by electrochemical byproducts and can discriminate DA and serotonin (5-HT) in response to the injection of their 50:50 mixture. These results highlight the potential of 3DFG MEAs as a promising platform for FSCV based multi-site detection of DA with high sensitivity, selectivity, and spatial resolution.

An FSCV Deep Neural Network: Development, Pruning, and Acceleration on an FPGA

Fast-scan cyclic voltammetry (FSCV) is an electrochemical technique for measuring rapid changes in the extracellular concentration of neurotransmitters within the brain. Due to its fast scan rate and large output-data size, the current analysis of the FSCV data is often conducted on a computer external to the FSCV device. Moreover, the analysis is semi-automated and requires a good understanding of the characteristics of the underlying chemistry to interpret, making it unsuitable for real-time implementation on low-resource FSCV devices. This paper presents a hardware-software co-design approach for the analysis of FSCV data. Firstly, a deep neural network (DNN) is developed to predict the concentration of a dopamine solution and identify the data recording electrode. Secondly, the DNN is pruned to decrease its computation complexity, and a custom overlay is developed to implement the pruned DNN on a low-resource FPGA-based platform. The pruned DNN attains a recognition accuracy of 97.2% with a compression ratio of 3.18. When the DNN overlay is implemented on a PYNQ-Z2 platform, it achieves the execution time of 13 ms and power consumption of 1.479 W on the entire PYNQ-Z2 board. This study demonstrates the possibility of operating the DNN for FSCV data analysis on portable FPGA-based platforms.

Brain neurochemical monitoring

Brain neurochemical monitoring aims to provide continuous and accurate measurements of brain biomarkers. It has enabled significant advances in neuroscience for application in clinical diagnostics, treatment, and prevention of brain diseases. Microfabricated electrochemical and optical spectroscopy sensing technologies have been developed for precise monitoring of brain neurochemicals. Here, a comprehensive review on the progress of sensing technologies developed for brain neurochemical monitoring is presented. The review provides a summary of the widely measured clinically relevant neurochemicals and commonly adopted recognition technologies. Recent advances in sampling, electrochemistry, and optical spectroscopy for brain neurochemical monitoring are highlighted and their application are discussed. Existing gaps in current technologies and future directions to design industry standard brain neurochemical sensing devices for clinical applications are addressed.

Resource-constrained FPGA/DNN co-design

Deep neural networks (DNNs) have demonstrated super performance in most learning tasks. However, a DNN typically contains a large number of parameters and operations, requiring a high-end processing platform for high-speed execution. To address this challenge, hardware-and-software co-design strategies, which involve joint DNN optimization and hardware implementation, can be applied. These strategies reduce the parameters and operations of the DNN, and fit it into a low-resource processing platform. In this paper, a DNN model is used for the analysis of the data captured using an electrochemical method to determine the concentration of a neurotransmitter and the recoding electrode. Next, a DNN miniaturization algorithm is introduced, involving combined pruning and compression, to reduce the DNN resource utilization. Here, the DNN is transformed to have sparse parameters by pruning a percentage of its weights. The Lempel-Ziv-Welch algorithm is then applied to compress the sparse DNN. Next, a DNN overlay is developed, combining the decompression of the DNN parameters and DNN inference, to allow the execution of the DNN on a FPGA on the PYNQ-Z2 board. This approach helps avoid the need for inclusion of a complex quantization algorithm. It compresses the DNN by a factor of 6.18, leading to about 50% reduction in the resource utilization on the FPGA.

Automatic and Reliable Quantification of Tonic Dopamine Concentrations In Vivo Using a Novel Probabilistic Inference Method

Dysregulation of the neurotransmitter dopamine (DA) is implicated in several neuropsychiatric conditions. Multiple-cyclic square-wave voltammetry (MCSWV) is a state-of-the-art technique for measuring tonic DA levels with high sensitivity (<5 nM), selectivity, and spatiotemporal resolution. Currently, however, analysis of MCSWV data requires manual, qualitative adjustments of analysis parameters, which can inadvertently introduce bias. Here, we demonstrate the development of a computational technique using a statistical model for standardized, unbiased analysis of experimental MCSWV data for unbiased quantification of tonic DA. The oxidation current in the MCSWV signal was predicted to follow a lognormal distribution. The DA-related oxidation signal was inferred to be present in the top 5% of this analytical distribution and was used to predict a tonic DA level. The performance of this technique was compared against the previously used peak-based method on paired in vivo and post-calibration in vitro datasets. Analytical inference of DA signals derived from the predicted statistical model enabled high-fidelity conversion of the in vivo current signal to a concentration value via in vitro post-calibration. As a result, this technique demonstrated reliable and improved estimation of tonic DA levels in vivo compared to the conventional manual post-processing technique using the peak current signals. These results show that probabilistic inference-based voltammetry signal processing techniques can standardize the determination of tonic DA concentrations, enabling progress toward the development of MCSWV as a robust research and clinical tool.

The development of an implantable deep brain stimulation device with simultaneous chronic electrophysiological recording and stimulation in humans

Deep brain stimulation (DBS) is used to treat a wide array of neurologic conditions. However, traditional programming of stimulation parameters relies upon short term subjective observation of patient symptoms and undesired stimulation effects while in the clinic. To gain a more objective measure of the neuronal activity that contributes to patient symptoms and response to treatment, there is a clear need for a fully-implantable DBS system capable of chronically recording patient-specific electrophysiological biomarker signals over time. By providing an objective correlate of a patient's disease and response to treatment, this capability has the potential to improve therapeutic benefit while preventing undesirable side effects. Herein, the engineering and capabilities of the Percept PC, the first FDA-approved, fully-implantable DBS device capable of nearly-simultaneous electrophysiological recordings and stimulation, are discussed. The device's ability to chronically record local field potentials (LFPs) at implanted DBS leads was validated in patients with neurological disorders. Lastly, the electrophysiological activity correlates of clinically relevant patient-reported events are presented. While FDA approved for conditions such as Parkinson's disease, essential tremor, dystonia, obsessive-compulsive disorder, and epilepsy, chronic electrophysiological recordings in humans has broad applications within basic science and clinical practice beyond DBS, offering a wealth of information related to normal and abnormal neurophysiology within distinct brain areas.

Imaging Neurotransmitter and Neuromodulator Dynamics In Vivo with Genetically Encoded Indicators

The actions of neuromodulation are thought to mediate the ability of the mammalian brain to dynamically adjust its functional state in response to changes in the environment. Altered neurotransmitter (NT) and neuromodulator (NM) signaling is central to the pathogenesis or treatment of many human neurological and psychiatric disorders, including Parkinson's disease, schizophrenia, depression, and addiction. To reveal the precise mechanisms by which these neurochemicals regulate healthy and diseased neural circuitry, one needs to measure their spatiotemporal dynamics in the living brain with great precision. Here, we discuss recent development, optimization, and applications of optical approaches to measure the spatial and temporal profiles of NT and NM release in the brain using genetically encoded sensors for in vivo studies.

Real-Time Fast Scan Cyclic Voltammetry Detection and Quantification of Exogenously Administered Melatonin in Mice Brain

Melatonin (MT) has been recently considered an excellent candidate for the treatment of sleep disorders, neural injuries, and neurological diseases. To better investigate the actions of MT in various brain functions, real-time detection of MT concentrations in specific brain regions is much desired. Previously, we have demonstrated detection of exogenously administered MT in anesthetized mouse brain using square wave voltammetry (SWV). Here, for the first time, we show successful detection of exogenous MT in the brain using fast scan cyclic voltammetry (FSCV) on electrochemically pre-activated carbon fiber microelectrodes (CFEs). In vitro evaluation showed the highest sensitivity (28.1 nA/μM) and lowest detection limit (20.2 ± 4.8 nM) ever reported for MT detection at carbon surface. Additionally, an extensive CFE stability and fouling assessment demonstrated that a prolonged CFE pre-conditioning stabilizes the background, in vitro and in vivo, and provides consistent CFE sensitivity over time even in the presence of a high MT concentration. Finally, the stable in vivo background, with minimized CFE fouling, allows us to achieve a drift-free FSCV detection of exogenous administered MT in mouse brain over a period of 3 min, which is significantly longer than the duration limit (usually < 90 s) for traditional in vivo FSCV acquisition. The MT concentration and dynamics measured by FSCV are in good agreement with SWV, while microdialysis further validated the concentration range. These results demonstrated reliable MT detection using FSCV that has the potential to monitor MT in the brain over long periods of time.

Live-Cell Imaging of Neurotransmitter Release with a Cell-Surface-Anchored DNA-Nanoprism Fluorescent Sensor

Neurotransmitters are essential chemical mediators for neuronal communication in variable neuromodulations. However, the progress of neuroscience is hampered by the shortage of suitable sensors to track neurotransmitters with high spatial and temporal resolution. Here, we introduce a self-assembled DNA-nanoprism fluorescent probe capable of nongenetically engineering the cell surface for ultrasensitive imaging of the neurotransmitter release at a single live-cell level. The DNA-nanoprism structure conjugated with three cholesterol tails enables the probe to rapidly and stably anchor on the cell surface within 10 min. The in situ detection of neurotransmitters is achieved by equipping the DNA-nanoprism with an aptamer-based "turn-on" fluorescent sensory module for the transmitter of interest. In a proof-of-concept study, we directly visualized the transient dopamine (DA) release on the cell surface with selective responsivity and high spatiotemporal precision and further explored the dynamic correlation between DA release and calcium influx triggered by high K⁺. This study provides a robust and sensitive tool for cell-surface-targeted imaging of neuromodulations, which might open up a new avenue to improve the understanding of neurochemistry and advance neuroscience research.

Evaluation of electrochemical methods for tonic dopamine detection in vivo

Dysfunction in dopaminergic neuronal systems underlie a number of neurologic and psychiatric disorders such as Parkinson's disease, drug addiction, and schizophrenia. Dopamine systems communicate via two mechanisms, a fast "phasic" release (sub-second to second) that is related to salient stimuli and a slower "tonic" release (minutes to hours) that regulates receptor tone. Alterations in tonic levels are thought to be more critically important in enabling normal motor, cognitive, and motivational functions, and dysregulation in tonic dopamine levels are associated with neuropsychiatric disorders. Therefore, development of neurochemical recording techniques that enable rapid, selective, and quantitative measurements of changes in tonic extracellular levels are essential in determining the role of dopamine in both normal and disease states. Here, we review state-of-the-art advanced analytical techniques for in vivo detection of tonic levels, with special focus on electrochemical techniques for detection in humans.

Hypoxia-Associated Changes in Striatal Tonic Dopamine Release: Real-Time in vivo Measurements With a Novel Voltammetry Technique

Introduction

Striatal tonic dopamine increases rapidly during global cerebral hypoxia. This phenomenon has previously been studied using microdialysis techniques which have relatively poor spatio-temporal resolution. In this study, we measured changes in tonic dopamine during hypoxia (death) in real time with high spatio-temporal resolution using novel multiple cyclic square wave voltammetry (MCSWV) and conventional fast scan cyclic voltammetry (FSCV) techniques.

Methods

MCSWV and FSCV were used to measure dopamine release at baseline and during hypoxia induced by euthanasia, with and without prior alpha-methyl-p-tyrosine (AMPT) treatment, in urethane anesthetized male Sprague-Dawley rats.

Results

Baseline tonic dopamine levels were found to be 274.1 ± 49.4 nM (n = 5; mean ± SEM). Following intracardiac urethane injection, the tonic levels increased to a peak concentration of 1753.8 ± 95.7 nM within 3.6 ± 0.6 min (n = 5), followed by a decline to 50.7 ± 21.5 nM (n = 4) at 20 min. AMPT pre-treatment significantly reduced this dopamine peak to 677.9 ± 185.7 nM (n = 3). FSCV showed a significantly higher (p = 0.0079) peak dopamine release of 6430.4 ± 1805.7 nM (n = 5) during euthanasia-induced cerebral hypoxia.

Conclusion

MCSWV is a novel tool to study rapid changes in tonic dopamine release in vivo during hypoxia. We found a 6-fold increase in peak dopamine levels during hypoxia which was attenuated with AMPT pre-treatment. These changes are much lower compared to those found with microdialysis. This could be due to improved estimation of baseline tonic dopamine with MCSWV. Higher dopamine response measured with FSCV could be due to an increased oxidation current from electroactive interferents.

Moving Fast-Scan Cyclic Voltammetry toward FDA Compliance with Capacitive Decoupling Patient Protection

Carbon-fiber microelectrodes allow for high spatial and temporal measurements of electroactive neurotransmitter measurements in vivo using fast-scan cyclic voltammetry (FSCV). However, common instrumentation for such measurements systems lack patient safety precautions. To add safety precautions as well as to overcome chemical and electrical noise, a two-electrode FSCV headstage was modified to introduce an active bandpass filter on the electrode side of the measurement amplifier. This modification reduced the measured noise and ac-coupled the voltammetric measurement and moved it from a classical direct current response measurement. ac-coupling not only reduces the measured noise, but also moves FSCV toward compliance with IEC-60601-1, enabling future human trials. Here, we develop a novel ac-coupled voltammetric measurement method of electroactive neurotransmitters. Our method allows for the modeling of a system to then calculate a waveform to compensate for added impedance and capacitance for the system. We describe how first by measuring the frequency response of the system and modeling the analogue response as a digital filter we can then calculate a predicted waveform. The predicted waveform, when applied to the bandpass filter, is modulated to create a desired voltage sweep at the electrode interface. Further, we describe how this modified FSCV waveform is stable, allowing for the measurement of electroactive neurotransmitters. We later describe a 32.7% sensitivity enhancement for dopamine with this new measurement as well as maintaining a calibration curve for dopamine, 3,4-dihydroxyphenylacetic acid, ascorbic acid, and serotonin in vitro. We then validate dopamine in vivo with stimulated release. Our developed measurement method overcame the added capacitance that would traditionally make a voltammetric measurement impossible, and it has wider applications in electrode sensor development, allowing for measurement with capacitive systems, which previously would not have been possible.

Electrochemical detection of exogenously administered melatonin in the brain

Melatonin (MT) is an important electroactive hormone that regulates different physiological actions in the brain, ranging from circadian clock to neurodegeneration. An impressive number of publications have highlighted the effectiveness of MT treatments in different types of sleep and neurological disorders, including Alzheimer's and Parkinson's disease. The ability to detect MT in different regions of the brain would provide further insights into the physiological roles and therapeutic effects of MT. While multiple electrochemical methods have been used to detect MT in biological samples, monitoring MT in the brain of live animals has not been demonstrated. Here, we optimized a square wave voltammetry (SWV) electroanalytical method to evaluate the MT detection performance at CFEs in vitro and in vivo. SWV was able to sensitively detect the MT oxidation peak at 0.7 V, and discriminate MT from most common interferents in vitro. More importantly, using the optimized SWV, CFEs successfully detected and reliably quantified MT concentrations in the visual cortex of anesthetized mice after intraperitoneal injections of different MT doses, offering stable MT signals for up to 40 minutes. To the best of our knowledge, this is the first electrochemical measurement of exogenously administered MT in vivo. This electrochemical MT sensing technique will provide a powerful tool for further understanding MT's action in the brain.

Aberrant Tonic Inhibition of Dopaminergic Neuronal Activity Causes Motor Symptoms in Animal Models of Parkinson's Disease

Current pharmacological treatments for Parkinson's disease (PD) are focused on symptomatic relief, but not on disease modification, based on the strong belief that PD is caused by irreversible dopaminergic neuronal death. Thus, the concept of the presence of dormant dopaminergic neurons and its possibility as the disease-modifying therapeutic target against PD have not been explored. Here we show that optogenetic activation of substantia nigra pars compacta (SNpc) neurons alleviates parkinsonism in acute PD animal models by recovering tyrosine hydroxylase (TH) from the TH-negative dormant dopaminergic neurons, some of which still express DOPA decarboxylase (DDC). The TH loss depends on reduced dopaminergic neuronal firing under aberrant tonic inhibition, which is attributed to excessive astrocytic GABA. Blocking the astrocytic GABA synthesis recapitulates the therapeutic effect of optogenetic activation. Consistently, SNpc of postmortem PD patients shows a significant population of TH-negative/DDC-positive dormant neurons surrounded by numerous GABA-positive astrocytes. We propose that disinhibiting dormant dopaminergic neurons by blocking excessive astrocytic GABA could be an effective therapeutic strategy against PD.

Sensitive and Selective Measurement of Serotonin in Vivo Using Fast Cyclic Square-Wave Voltammetry

Although N-shaped fast scan cyclic voltammetry (N-FSCV) is well-established as an electroanalytical method to measure extracellular serotonin concentrations in vivo, it is in need of improvement in both sensitivity and selectivity. Based on our previous studies using fast cyclic square-wave voltammetry (FCSWV) for in vivo dopamine measurements, we have modified this technique to optimize the detection of serotonin in vivo. A series of large amplitude square-shaped potentials was superimposed onto an N-shaped waveform to provide cycling through multiple redox reactions within the N-shaped waveform to enhance the sensitivity and selectivity to serotonin measurement when combined with a two-dimensional voltammogram. N-Shaped fast cyclic square-wave voltammetry (N-FCSWV) showed significantly higher sensitivity to serotonin compared to conventional N-FSCV. In addition, N-FCSWV showed better performance than conventional N-shaped FSCV in differentiating serotonin from its major interferents, dopamine and 5-hydroxyindoleascetic acid (5-HIAA). It was also confirmed that the large amplitude of the square waveform did not influence local neuronal activity, and it could monitor electrical stimulation evoked phasic release of serotonin in the rat substantia nigra pars reticulata (SNr) before and after systemic injection of escitalopram (ESCIT, 10 mg/kg i.p.), a serotonin selective reuptake inhibitor.

Analysis of Carbon-Based Microelectrodes for Neurochemical Sensing

The comprehensive microscopic, spectroscopic, and in vitro voltammetric analysis presented in this work, which builds on the well-studied properties of carbon-based materials, facilitates potential ways for improvement of carbon fiber microelectrodes (CFMs) for neuroscience applications. Investigations by both, scanning electron microscopy (SEM) and confocal Raman spectroscopy, confirm a higher degree of structural ordering for the fibers exposed to carbonization temperatures. An evident correlation is also identified between the extent of structural defects observed from SEM and Raman results with the CFM electrochemical performance for dopamine detection. To improve CFM physico-chemical surface stability and increase its mechanical resistance to the induced compressive stress during anticipated in vivo tissue penetration, successful coating of the carbon fiber with boron-doped diamond (BDD) is also performed and microspectroscopically analyzed here. The absence of spectral shifts of the diamond Raman vibrational signature verifies that the growth of an unstrained BDD thin film was achieved. Although more work needs to be done to identify optimal parameter values for improved BDD deposition, this study serves as a demonstration of foundational technology for the development of more sensitive electrochemical sensors, that may have been impractical previously for clinical applications, due to limitations in either safety or performance.

Direct in Vivo Electrochemical Detection of Resting Dopamine Using Poly(3,4-ethylenedioxythiophene)/Carbon Nanotube Functionalized Microelectrodes

Dopamine (DA) is a monoamine neurotransmitter responsible for the maintenance of a variety of vital life functions. In vivo DA signaling occurs over multiple time scales, from subsecond phasic release due to dopamine neuron firing to tonic release responsible for long-term DA concentration changes over minutes to hours. Due to the complex, multifaceted nature of DA signaling, analytical sensing technology must be capable of recording DA from multiple locations and over multiple time scales. Decades of research has focused on improving in vivo detection capabilities for subsecond phasic DA, but the accurate detection of absolute resting DA levels in real time has proven challenging. We have developed a poly(3,4-ethylenedioxythiophene) (PEDOT)-based nanocomposite coating that exhibits excellent DA sensing capabilities for resting DA. PEDOT/functionalized carbon nanotube (PEDOT/CNT)-coated carbon fiber microelectrodes (CFEs) are capable of directly measuring resting DA using square wave voltammetry (SWV) with high sensitivity and selectivity. Incorporation of a PEDOT/CNT coating significantly increases the sensitivity for the detection of resting DA by a factor of 422. SWV measurements performed at PEDOT/CNT-functionalized CFEs implanted in the rat dorsal striatum reveal the absolute basal DA concentration to be 82 ± 6 nM. Systemic administration of the dopamine transporter inhibitor nomifensine increases resting DA to a maximum 207 ± 16 nM at 28 ± 2 min following injection. PEDOT/CNT was also functionalized onto individual gold electrode sites along silicon microelectrode arrays (MEAs) to produce a multisite DA sensing electrode. MEA implantation allows for the quantification of basal DA from different brain regions with excellent spatial resolution. SWV detection paired with PEDOT/CNT functionalization is highly adaptable and shows great promise for tonic DA detection with high spatial and temporal resolution.

Frontiers in Electrochemical Sensors for Neurotransmitter Detection: Towards Measuring Neurotransmitters as Chemical Diagnostics for Brain Disorders

It is extremely challenging to chemically diagnose disorders of the brain. There is hence great interest in designing and optimizing tools for direct detection of chemical biomarkers implicated in neurological disorders to improve diagnosis and treatment. Tools that are capable of monitoring brain chemicals, neurotransmitters in particular, need to be biocompatible, perform with high spatiotemporal resolution, and ensure high selectivity and sensitivity. Recent advances in electrochemical methods are addressing these criteria; the resulting devices demonstrate great promise for in vivo neurotransmitter detection. None of these devices are currently used for diagnostic purposes, however these cutting-edge technologies are promising more sensitive, selective, faster, and less invasive measurements. Via this review we highlight significant technical advances and in vivo studies, performed in the last 5 years, that we believe will facilitate the development of diagnostic tools for brain disorders.

Drift Subtraction for Fast-Scan Cyclic Voltammetry Using Double-Waveform Partial-Least-Squares Regression

Background-subtracted fast-scan cyclic voltammetry (FSCV) provides a method for detecting molecular fluctuations with high spatiotemporal resolution in the brain of awake and behaving animals. The rapid scan rates generate large background currents that are subtracted to reveal changes in analyte concentration. Although these background currents are relatively stable, small changes do occur over time. These changes, referred to as electrochemical drift, result in background-subtraction artifacts that constrain the utility of FSCV, particularly when quantifying chemical changes that gradually occur over long measurement times (minutes). The voltammetric features of electrochemical drift are varied and can span the entire potential window, potentially obscuring the signal from any targeted analyte. We present a straightforward method for extending the duration of a single FSCV recording window. First, we have implemented voltammetric waveforms in pairs that consist of a smaller triangular sweep followed by a conventional voltammetric scan. The initial, abbreviated waveform is used to capture drift information that can serve as a predictor for the contribution of electrochemical drift to the subsequent full voltammetric scan using partial-least-squares regression (PLSR). This double-waveform partial-least-squares regression (DW-PLSR) paradigm permits reliable subtraction of the drift component to the voltammetric data. Here, DW-PLSR is used to improve quantification of adenosine, dopamine, and hydrogen peroxide fluctuations occurring >10 min from the initial background position, both in vitro and in vivo. The results demonstrate that DW-PLSR is a powerful tool for evaluating and interpreting both rapid (seconds) and gradual (minutes) chemical changes captured in FSCV recordings over extended durations.

Spontaneous Regional Brain Activity in Healthy Individuals is Nonlinearly Modulated by the Interaction of ZNF804A rs1344706 and COMT rs4680 Polymorphisms

ZNF804A rs1344706 has been identified as one of the risk genes for schizophrenia. However, the neural mechanisms underlying this association are unknown. Given that ZNF804A upregulates the expression of COMT, we hypothesized that ZNF804A may influence brain activity by interacting with COMT. Here, we genotyped ZNF804A rs1344706 and COMT rs4680 in 218 healthy Chinese participants. Amplitudes of low-frequency fluctuations (ALFFs) were applied to analyze the main and interaction effects of ZNF804A rs1344706 and COMT rs4680. The ALFFs of the bilateral dorsolateral prefrontal cortex showed a significant ZNF804A rs1344706 × COMT rs4680 interaction, manifesting as a U-shaped modulation, presumably by dopamine signaling. Significant main effects were also found. These findings suggest that ZNF804A affects the resting-state functional activation by interacting with COMT, and may improve our understanding of the neurobiological effects of ZNF804A and its association with schizophrenia.

A baseline drift detrending technique for fast scan cyclic voltammetry

Fast scan cyclic voltammetry (FSCV) has been commonly used to measure extracellular neurotransmitter concentrations in the brain. Due to the unstable nature of the background currents inherent in FSCV measurements, analysis of FSCV data is limited to very short amounts of time using traditional background subtraction. In this paper, we propose the use of a zero-phase high pass filter (HPF) as the means to remove the background drift. Instead of the traditional method of low pass filtering across voltammograms to increase the signal to noise ratio, a HPF with a low cutoff frequency was applied to the temporal dataset at each voltage point to remove the background drift. As a result, the HPF utilizing cutoff frequencies between 0.001 Hz and 0.01 Hz could be effectively used to a set of FSCV data for removing the drifting patterns while preserving the temporal kinetics of the phasic dopamine response recorded in vivo. In addition, compared to a drift removal method using principal component analysis, this was found to be significantly more effective in reducing the drift (unpaired t-test p < 0.0001, t = 10.88) when applied to data collected from Tris buffer over 24 hours although a drift removal method using principal component analysis also showed the effective background drift reduction. The HPF was also applied to 5 hours of FSCV in vivo data. Electrically evoked dopamine peaks, observed in the nucleus accumbens, were clearly visible even without background subtraction. This technique provides a new, simple, and yet robust, approach to analyse FSCV data with an unstable background.

Tracking tonic dopamine levels in vivo using multiple cyclic square wave voltammetry

For over two decades, fast-scan cyclic voltammetry (FSCV) has served as a reliable analytical method for monitoring dopamine release in near real-time in vivo. However, contemporary FSCV techniques have been limited to measure only rapid (on the order of seconds, i.e. phasic) changes in dopamine release evoked by either electrical stimulation or elicited by presentation of behaviorally salient stimuli, and not slower changes in the tonic extracellular levels of dopamine (i.e. basal concentrations). This is because FSCV is inherently a differential method that requires subtraction of prestimulation tonic levels of dopamine to measure phasic changes relative to a zeroed baseline. Here, we describe the development and application of a novel voltammetric technique, multiple cyclic square wave voltammetry (M-CSWV), for analytical quantification of tonic dopamine concentrations in vivo with relatively high temporal resolution (10 s). M-CSWV enriches the electrochemical information by generating two dimensional voltammograms which enable high sensitivity (limit of detection, 0.17 nM) and selectivity against ascorbic acid, and 3,4-dihydroxyphenylacetic acid (DOPAC), including changes in pH. Using M-CSWV, a tonic dopamine concentration of 120 ± 18 nM (n = 7 rats, ± SEM) was determined in the striatum of urethane anethetized rats. Pharmacological treatments to elevate dopamine by selectively inhibiting dopamine reuptake and to reduce DOPAC by inhibition of monoamine oxidase supported the selective detection of dopamine in vivo. Overall, M-CSWV offers a novel voltammetric technique to quantify levels and monitor changes in tonic dopamine concentrations in the brain to further our understanding of the role of dopamine in normal behavior and neuropsychiatric disorders.

Fast Cyclic Square-Wave Voltammetry To Enhance Neurotransmitter Selectivity and Sensitivity

Although fast-scan cyclic voltammetry (FSCV) has been widely used for in vivo neurochemical detection, the sensitivity and selectivity of the technique can be further improved. In this study, we develop fast cyclic square-wave voltammetry (FCSWV) as a novel voltammetric technique that combines large-amplitude cyclic square-wave voltammetry (CSWV) with background subtraction. A large-amplitude, square-shaped potential was applied to induce cycling through multiple redox reactions within a square pulse to increase sensitivity and selectivity when combined with a two-dimensional voltammogram. As a result, FCSWV was significantly more sensitive than FSCV ( n = 5 electrodes, two-way ANOVA, p = 0.0002). In addition, FCSWV could differentiate dopamine from other catecholamines (e.g., epinephrine and norepinephrine) and serotonin better than conventional FSCV. With the confirmation that FCSWV did not influence local neuronal activity, despite the large amplitude of the square waveform, it could monitor electrically induced phasic changes in dopamine release in rat striatum before and after injecting nomifensine, a dopamine reuptake inhibitor.