Fast-scan cyclic voltammetry analysis of dynamic serotonin reponses to acute escitalopram

Microdosing ketamine in Drosophila does not block serotonin reuptake, but causes complex behavioral changes mediated by glutamate and serotonin receptors

Microdosing ketamine is a novel antidepressant for treatment-resistant depression. Traditional antidepressants, like selective serotonin reuptake inhibitors (SSRIs), inhibit serotonin reuptake, but it is not clear if ketamine shows a similar mechanism. Here, we tested the effects of feeding ketamine and SSRIs to Drosophila melanogaster larvae, which has a similar serotonin system to mammals and is a good model to track depressive behaviors, such as locomotion and feeding. Fast-scan cyclic voltammetry (FSCV) was used to measure optogenetically stimulated serotonin changes, and locomotion tracking software and blue dye feeding to monitor behavior. We fed larvae various doses (1-100 mM) of antidepressants for 24 h and found that 1 mM ketamine did not affect serotonin, but increased locomotion and feeding. Low doses (≤10 mM) of escitalopram and fluoxetine inhibited dSERT and also increased feeding and locomotion behaviors. At 100 mM, ketamine inhibited dSERT and increased serotonin concentrations, but decreased locomotion and feeding because of its anesthetic properties. Since microdosing ketamine causes behavioral effects, we further investigated behavioral changes with a SERT16 mutant and low doses of other NMDA receptor antagonists and 5-HT1A and 2 agonists. Feeding and locomotion changes were similar to ketamine in the mutant, and we found NMDA receptor antagonism increased feeding, while serotonin receptor agonism increased locomotion, which could explain these effects with ketamine. Ultimately, this work shows that Drosophila is a good model to discern antidepressant mechanisms, and that ketamine does not work on dSERT like SSRIs, but effects behavior with other mechanisms that should be investigated further.

Electrochemical and biosensor techniques to monitor neurotransmitter changes with depression

Depression is a common mental illness. However, its current treatments, like selective serotonin reuptake inhibitors (SSRIs) and micro-dosing ketamine, are extremely variable between patients and not well understood. Three neurotransmitters: serotonin, histamine, and glutamate, have been proposed to be key mediators of depression. This review focuses on analytical methods to quantify these neurotransmitters to better understand neurological mechanisms of depression and how they are altered during treatment. To quantitatively measure serotonin and histamine, electrochemical techniques such as chronoamperometry and fast-scan cyclic voltammetry (FSCV) have been improved to study how specific molecular targets, like transporters and receptors, change with antidepressants and inflammation. Specifically, these studies show that different SSRIs have unique effects on serotonin reuptake and release. Histamine is normally elevated during stress, and a new inflammation hypothesis of depression links histamine and cytokine release. Electrochemical measurements revealed that stress increases histamine, decreases serotonin, and leads to changes in cytokines, like interleukin-6. Biosensors can also measure non-electroactive neurotransmitters, including glutamate and cytokines. In particular, new genetic sensors have shown how glutamate changes with chronic stress, as well as with ketamine treatment. These techniques have been used to characterize how ketamine changes glutamate and serotonin, and to understand how it is different from SSRIs. This review briefly outlines how these electrochemical techniques work, but primarily highlights how they have been used to understand the mechanisms of depression. Future studies should explore multiplexing techniques and personalized medicine using biomarkers in order to investigate multi-analyte changes to antidepressants.

Genetically encoded sensors for in vivo detection of neurochemicals relevant to depression

Depressive disorders are a common and debilitating form of mental illness with significant impacts on individuals and society. Despite the high prevalence, the underlying causes and mechanisms of depressive disorders are still poorly understood. Neurochemical systems, including serotonin, norepinephrine, and dopamine, have been implicated in the development and perpetuation of depressive symptoms. Current treatments for depression target these neuromodulator systems, but there is a need for a better understanding of their role in order to develop more effective treatments. Monitoring neurochemical dynamics during depressive symptoms is crucial for gaining a better a understanding of their involvement in depressive disorders. Genetically encoded sensors have emerged recently that offer high spatial-temporal resolution and the ability to monitor neurochemical dynamics in real time. This review explores the neurochemical systems involved in depression and discusses the applications and limitations of current monitoring tools for neurochemical dynamics. It also highlights the potential of genetically encoded sensors for better characterizing neurochemical dynamics in depression-related behaviors. Furthermore, potential improvements to current sensors are discussed in order to meet the requirements of depression research.

Serotonin as a biomarker of toxin-induced Parkinsonism

BACKGROUND

Loss of dopaminergic neurons underlies the motor symptoms of Parkinson's disease (PD). However stereotypical PD symptoms only manifest after approximately 80% of dopamine neurons have died making dopamine-related motor phenotypes unreliable markers of the earlier stages of the disease. There are other non-motor symptoms, such as depression, that may present decades before motor symptoms.

METHODS

Because serotonin is implicated in depression, here we use niche, fast electrochemistry paired with mathematical modelling and machine learning to, for the first time, robustly evaluate serotonin neurochemistry in vivo in real time in a toxicological model of Parkinsonism, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP).

RESULTS

Mice treated with acute MPTP had lower concentrations of in vivo, evoked and ambient serotonin in the hippocampus, consistent with the clinical comorbidity of depression with PD. These mice did not chemically respond to SSRI, as strongly as control animals did, following the clinical literature showing that antidepressant success during PD is highly variable. Following L-DOPA administration, using a novel machine learning analysis tool, we observed a dynamic shift from evoked serotonin release in the hippocampus to dopamine release. We hypothesize that this finding shows, in real time, that serotonergic neurons uptake L-DOPA and produce dopamine at the expense of serotonin, supporting the significant clinical correlation between L-DOPA and depression. Finally, we found that this post L-DOPA dopamine release was less regulated, staying in the synapse for longer. This finding is perhaps due to lack of autoreceptor control and may provide a ground from which to study L-DOPA induced dyskinesia.

CONCLUSIONS

These results validate key prior hypotheses about the roles of serotonin during PD and open an avenue to study to potentially improve therapeutics for levodopa-induced dyskinesia and depression.

Microdosing ketamine in Drosophila does not inhibit SERT like SSRIs, but causes behavioral changes mediated by glutamate and serotonin receptors

Recently, the FDA approved microdosing ketamine for treatment resistant depression. Traditional antidepressants, like serotonin selective reuptake inhibitors (SSRIs), block serotonin reuptake, but it is not clear if ketamine blocks serotonin reuptake. Here, we tested the effects of feeding ketamine and SSRIs to Drosophila melanogaster larvae, which has a similar serotonin system to mammals, and is a good model to track depression behaviors, such as locomotion and feeding. Fast-scan cyclic voltammetry (FSCV) was used to measure optogenetically-stimulated serotonin changes, and locomotion tracking software and blue dye feeding to monitor behavior. We fed larvae various doses (1-100 mM) of antidepressants for 24 hours and found that 1 mM ketamine did not affect serotonin, but increased locomotion and feeding. Low doses (≤ 10 mM) of escitalopram and fluoxetine inhibited dSERT and also increased feeding and locomotion behaviors. At 100 mM, ketamine inhibited dSERT and increased serotonin concentrations, but decreased locomotion and feeding due to its anesthetic properties. Since microdosing ketamine causes behavioral effects, we also investigated behavior changes with low doses of other NMDA receptor antagonists and 5-HT1A and 2 agonists, which are other possible sites for ketamine action. NMDA receptor antagonism increased feeding, while serotonin receptor agonism increased locomotion, which could explain these effects with ketamine. Ultimately, this work shows that Drosophila is a good model to discern antidepressant mechanisms, and that ketamine does not work on dSERT like SSRIs at microdoses, but affects behavior with other mechanisms.

Enhancement of faradaic current in an electrochemical cell integrated into silicon microfluidic channels

Implantable electrochemical sensors enable fast and sensitive detection of analytes in biological tissue, but are hampered by bio-foulant attack and are unable to be recalibrated in-situ. Herein, an electrochemical sensor integrated into ultra-low flow (nL/min) silicon microfluidic channels for protection from foulants and in-situ calibration is demonstrated. The small footprint (5 μm radius channel cross-section) of the device allows its integration into implantable sampling probes for monitoring chemical concentrations in biological tissues. The device is designed for fast scan cyclic voltammetry (FSCV) in the thin-layer regime when analyte depletion at the electrode is efficiently compensated by microfluidic flow. A 3X enhancement of faradaic peak currents is observed due to the increased flux of analytes towards the electrodes. Numerical analysis of in-channel analyte concentration confirmed near complete electrolysis in the thin-layer regime below 10 nL/min. The manufacturing approach is highly scalable and reproducible as it utilizes standard silicon microfabrication technologies.

Kappa Opioid Receptors Reduce Serotonin Uptake and Escitalopram Efficacy in the Mouse Substantia Nigra Pars Reticulata

The serotonin and kappa opioid receptor (KOR) systems are strongly implicated in disorders of negative affect, such as anxiety and depression. KORs expressed on axon terminals inhibit the release of neurotransmitters, including serotonin. The substantia nigra pars reticulata (SNr) is involved in regulating affective behaviors. It receives the densest serotonergic innervation in the brain and has high KOR expression; however, the influence of KORs on serotonin transmission in this region is yet to be explored. Here, we used ex vivo fast-scan cyclic voltammetry (FSCV) to investigate the effects of a KOR agonist, U50, 488 (U50), and a selective serotonin reuptake inhibitor, escitalopram, on serotonin release and reuptake in the SNr. U50 alone reduced serotonin release and uptake, and escitalopram alone augmented serotonin release and slowed reuptake, while pretreatment with U50 blunted both the release and uptake effects of escitalopram. Here, we show that the KOR influences serotonin signaling in the SNr in multiple ways and short-term activation of the KOR alters serotonin responses to escitalopram. These interactions between KORs and serotonin may contribute to the complexity in the responses to treatments for disorders of negative affect. Ultimately, the KOR system may prove to be a promising pharmacological target, alongside traditional antidepressant treatments.

SSRI antidepressants differentially modulate serotonin reuptake and release in Drosophila

Selective serotonin reuptake inhibitor (SSRI) antidepressants are commonly prescribed treatments for depression, but their effects on serotonin reuptake and release are not well understood. Drosophila melanogaster, the fruit fly, expresses the serotonin transporter (dSERT), the major target of SSRIs, but real-time serotonin changes after SSRIs have not been characterized in this model. The goal of this study was to characterize effects of SSRIs on serotonin concentration and reuptake in Drosophila larvae. We applied various doses (0.1-100 μM) of fluoxetine (Prozac), escitalopram (Lexapro), citalopram (Celexa), and paroxetine (Paxil), to ventral nerve cord (VNC) tissue and measured optogenetically-stimulated serotonin release with fast-scan cyclic voltammetry (FSCV). Fluoxetine increased reuptake from 1 to 100 μM, but serotonin concentration only increased at 100 μM. Thus, fluoxetine occupies dSERT and slows clearance but does not affect concentration. Escitalopram and paroxetine increased serotonin concentrations at all doses, but escitalopram increased reuptake more. Citalopram showed lower concentration changes and faster reuptake profiles compared with escitalopram, so the racemic mixture of citalopram does not change reuptake as much as the S-isomer. Dose response curves were constructed to compare dSERT affinities and paroxetine showed the highest affinity and fluoxetine the lowest. These data demonstrate SSRI mechanisms are complex, with separate effects on reuptake or release. Furthermore, dynamic serotonin changes in Drosophila are similar to previous studies in mammals. This work establishes how antidepressants affect serotonin in real-time, which is useful for future studies that will investigate pharmacological effects of SSRIs with different genetic mutations in Drosophila.

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.

Voltammetric Approach for Characterizing the Biophysical and Chemical Functionality of Human Induced Pluripotent Stem Cell-Derived Serotonin Neurons

Depression is quickly becoming one of the world's most pressing public health crises, and there is an urgent need for better diagnostics and therapeutics. Behavioral models in animals and humans have not adequately addressed the diagnosis and treatment of depression, and biomarkers of mental illnesses remain ill-defined. It has been very difficult to identify biomarkers of depression because of in vivo measurement challenges. While our group has made important strides in developing in vivo tools to measure such biomarkers (e.g., serotonin) in mice using voltammetry, these tools cannot be easily applied for depression diagnosis and drug screening in humans due to the inaccessibility of the human brain. In this work, we take a chemical approach, ex vivo, to introduce a human-derived system to investigate brain serotonin. We utilize human induced pluripotent stem cells differentiated into serotonin neurons and establish a new ex vivo model of real-time serotonin neurotransmission measurements. We show that evoked serotonin release responds to stimulation intensity and tryptophan preloading, and that serotonin release and reuptake kinetics resemble those found in vivo in rodents. Finally, after selective serotonin reuptake inhibitor (SSRI) exposure, we find dose-dependent internalization of the serotonin reuptake transporters (a signature of the in vivo response to SSRI). Our new human-derived chemical model has great potential to provide an ex vivo chemical platform as a translational tool for in vivo neuropsychopharmacology.

Low-Frequency Oscillations of In Vivo Ambient Extracellular Brain Serotonin

Serotonin is an important neurotransmitter that plays a major role in many aspects of neuroscience. Fast-scan cyclic voltammetry measures fast in vivo serotonin dynamics using carbon fiber microelectrodes. More recently, fast-scan controlled-adsorption voltammetry (FSCAV) has been developed to measure slower, minute-to-minute changes in ambient extracellular serotonin. We have previously demonstrated that FSCAV measurements of basal serotonin levels give critical information regarding brain physiology and disease. In this work, we revealed the presence of low-periodicity fluctuations in serotonin levels in mouse hippocampi, measured in vivo with FSCAV. Using correlation analyses, we found robust evidence of oscillations in the basal serotonin levels, which had a period of 10 min and were not present in vitro. Under control conditions, the oscillations did not differ between male and female mice, nor do they differ between mice that underwent a chronic stress paradigm and those in the control group. After the acute administration of a selective serotonin reuptake inhibitor, we observed a shift in the frequency of the oscillations, leading us to hypothesize that the newly observed fluctuations were transporter regulated. Finally, we optimized the experimental parameters of the FSCAV to measure at a higher temporal resolution and found more pronounced shifts in the oscillation frequency, along with a decreased oscillation amplitude. We postulate that this work may serve as a potential bridge for studying serotonin/endocrine interactions that occur on the same time scale.

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.

Improved Serotonin Measurement with Fast-Scan Cyclic Voltammetry: Mitigating Fouling by SSRIs

Selective serotonin reuptake inhibitors (SSRIs) have been used for decades to treat disorders linked to serotonin dysregulation in the brain. Moreover, SSRIs are often used in studies aimed at measuring serotonin with fast-scan cyclic voltammetry (FSCV) in living tissues. Here, we show that three different SSRIs - fluoxetine, escitalopram, and sertraline - significantly diminish the faradaic oxidation current of serotonin when employing the commonly used Jackson waveform. Coating carbon-fiber microelectrodes (CFMs) with Nafion resulted in further degradation of peak current, increased response times, and decreased background charging currents compared to bare CFMs. To decrease fouling, we employed a recently published extended serotonin waveform, which scans to a maximum positive potential of +1.3 V, rather than +1.0 V used in the Jackson waveform. Use of this waveform with bare CFMs alleviated the decrease in faradaic current, indicating decreased electrode fouling. Collectively, our results suggest that fouling considerations are important when designing FSCV experiments that employ SSRIs and that they can be overcome by using the appropriate waveform.

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.

Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression

Many voltammetry methods have been developed to monitor brain extracellular dopamine levels. Fewer approaches have been successful in detecting serotonin in vivo. No voltammetric techniques are currently available to monitor both neurotransmitters simultaneously across timescales, even though they play integrated roles in modulating behavior. We provide proof-of-concept for rapid pulse voltammetry coupled with partial least squares regression (RPV-PLSR), an approach adapted from multi-electrode systems (i.e., electronic tongues) used to identify multiple components in complex environments. We exploited small differences in analyte redox profiles to select pulse steps for RPV waveforms. Using an intentionally designed pulse strategy combined with custom instrumentation and analysis software, we monitored basal and stimulated levels of dopamine and serotonin. In addition to faradaic currents, capacitive currents were important factors in analyte identification arguing against background subtraction. Compared to fast-scan cyclic voltammetry-principal components regression (FSCV-PCR), RPV-PLSR better differentiated and quantified basal and stimulated dopamine and serotonin associated with striatal recording electrode position, optical stimulation frequency, and serotonin reuptake inhibition. The RPV-PLSR approach can be generalized to other electrochemically active neurotransmitters and provides a feedback pipeline for future optimization of multi-analyte, fit-for-purpose waveforms and machine learning approaches to data analysis.

Carbon-based neural electrodes: promises and challenges

Neural electrodes are primary functional elements of neuroelectronic devices designed to record neural activity based on electrochemical signals. These electrodes may also be utilized for electrically stimulating the neural cells, such that their response can be simultaneously recorded. In addition to being medically safe, the electrode material should be electrically conductive and electrochemically stable under harsh biological environments. Mechanical flexibility and conformability, resistance to crack formation and compatibility with common microfabrication techniques are equally desirable properties. Traditionally, (noble) metals have been the preferred for neural electrode applications due to their proven biosafety and a relatively high electrical conductivity. Carbon is a recent addition to this list, which is far superior in terms of its electrochemical stability and corrosion resistance. Carbon has also enabled 3D electrode fabrication as opposed to the thin-film based 2D structures. One of carbon's peculiar aspects is its availability in a wide range of allotropes with specialized properties that render it highly versatile. These variations, however, also make it difficult to understand carbon itself as a unique material, and thus, each allotrope is often regarded independently. Some carbon types have already shown promising results in bioelectronic medicine, while many others remain potential candidates. In this topical review, we first provide a broad overview of the neuroelectronic devices and the basic requirements of an electrode material. We subsequently discuss the carbon family of materials and their properties that are useful in neural applications. Examples of devices fabricated using bulk and nano carbon materials are reviewed and critically compared. We then summarize the challenges, future prospects and next-generation carbon technology that can be helpful in the field of neural sciences. The article aims at providing a common platform to neuroscientists, electrochemists, biologists, microsystems engineers and carbon scientists to enable active and comprehensive efforts directed towards carbon-based neuroelectronic device fabrication.

High-fat diet induces neuroinflammation and reduces the serotonergic response to escitalopram in the hippocampus of obese rats

Clinical studies indicate that obese individuals have an increased risk of developing co-morbid depressive illness and that these patients have reduced responses to antidepressant therapy, including selective serotonin reuptake inhibitors (SSRIs). Obesity, a condition of chronic mild inflammation including obesity-induced neuroinflammation, is proposed to contribute to decreases in synaptic concentrations of neurotransmitters like serotonin (5HT) by decreasing 5HT synthesis in the dorsal raphe nucleus (DRN) and/or affecting 5HT reuptake in DRN target regions like the hippocampus. In view of these observations, the goal of the current study was to examine inflammatory markers and serotonergic dynamics in co-morbid obesity and depression. Biochemical and behavioral assays revealed that high-fat diet produced an obesity and depressive-like phenotype in one cohort of rats and that these changes were marked by increases in key pro-inflammatory cytokines in the hippocampus. In real time using fast scan cyclic voltammetry (FSCV), we observed no changes in basal levels of hippocampal 5HT; however responses to escitalopram were significantly impaired in the hippocampus of obese rats compared to diet resistant rats and control rats. Further studies revealed that these neurochemical observations could be explained by increases in serotonin transporter (SERT) expression in the hippocampus driven by elevated neuroinflammation. Collectively, these results demonstrate that obesity-induced increases in neuroinflammation adversely affect SERT expression in the hippocampus of obese rats, thereby providing a potential synaptic mechanism for reduced SSRI responsiveness in obese subjects with co-morbid depressive illness.

Glutamate Electropolymerization on Carbon Increases Analytical Sensitivity to Dopamine and Serotonin: An Auspicious In Vivo Phenomenon in Mice?

Carbon is the material of choice for electroanalysis of biological systems, being particularly applicable to neurotransmitter analysis as carbon fiber microelectrodes (CFMs). CFMs are most often applied to dopamine detection; however, the scope of CFM analysis has rapidly expanded over the last decade with our laboratory's focus being on improving serotonin detection at CFMs, which we achieved in the past via Nafion modification. We began this present work by seeking to optimize this modification to gain increased analytical sensitivity toward serotonin under the assumption that exposure of bare carbon to the in vivo environment rapidly deteriorates analytical performance. However, we were unable to experimentally verify this assumption and found that electrodes that had been exposed to the in vivo environment were more sensitive to evoked and ambient dopamine. We hypothesized that high in vivo concentrations of ambient extracellular glutamate could polymerize with a negative charge onto CFMs and facilitate response to dopamine. We verified this polymerization electrochemically and characterized the mechanisms of deposition with micro- and nano-imaging. Importantly, we identified that the application of 1.3 V as a positive upper waveform limit is a crucial factor for facilitating glutamate polymerization, thus improving analytical performance. Critically, information gained from these dopamine studies were extended to an in vivo environment where a 2-fold increase in sensitivity to evoked serotonin was achieved. Thus, we present here the novel finding that innate aspects of the in vivo environment are auspicious for detection of dopamine and serotonin at carbon fibers, offering a solution to our goal of an improved fast-scan cyclic voltammetry serotonin detection paradigm.

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.

Inflammation-Induced Histamine Impairs the Capacity of Escitalopram to Increase Hippocampal Extracellular Serotonin

Commonly prescribed selective serotonin reuptake inhibitors (SSRIs) inhibit the serotonin transporter to correct a presumed deficit in extracellular serotonin signaling during depression. These agents bring clinical relief to many who take them; however, a significant and growing number of individuals are resistant to SSRIs. There is emerging evidence that inflammation plays a significant role in the clinical variability of SSRIs, though how SSRIs and inflammation intersect with synaptic serotonin modulation remains unknown. In this work, we use fast in vivo serotonin measurement tools to investigate the nexus between serotonin, inflammation, and SSRIs. Upon acute systemic lipopolysaccharide (LPS) administration in male and female mice, we find robust decreases in extracellular serotonin in the mouse hippocampus. We show that these decreased serotonin levels are supported by increased histamine activity (because of inflammation), acting on inhibitory histamine H3 heteroreceptors on serotonin terminals. Importantly, under LPS-induced histamine increase, the ability of escitalopram to augment extracellular serotonin is impaired because of an off-target action of escitalopram to inhibit histamine reuptake. Finally, we show that a functional decrease in histamine synthesis boosts the ability of escitalopram to increase extracellular serotonin levels following LPS. This work reveals a profound effect of inflammation on brain chemistry, specifically the rapidity of inflammation-induced decreased extracellular serotonin, and points the spotlight at a potentially critical player in the pathology of depression, histamine. The serotonin/histamine homeostasis thus, may be a crucial new avenue in improving serotonin-based treatments for depression.SIGNIFICANCE STATEMENT Acute LPS-induced inflammation (1) increases CNS histamine, (2) decreases CNS serotonin (via inhibitory histamine receptors), and (3) prevents a selective serotonin reuptake inhibitor (SSRI) from effectively increasing extracellular serotonin. A targeted depletion of histamine recovers SSRI-induced increases in extracellular hippocampal serotonin.

Improving serotonin fast-scan cyclic voltammetry detection: new waveforms to reduce electrode fouling

Serotonin is a neuromodulator implicated in depression that is often measured in real-time by fast-scan cyclic voltammetry (FSCV). A specialized "Jackson" waveform (JW, 0.2, 1.0 V, -0.1 V, 0.2 V, 1000 V s-1) was developed to reduce serotonin fouling, but the 1.0 V switching potential limits sensitivity and electrodes still foul. The goal of this study was to test the effects of extending the FSCV switching potential to increase serotonin sensitivity and decrease fouling. We compared the Jackson waveform, the dopamine waveform (DA, -0.4 V, 1.3 V, 400 V s-1), and two new waveforms: the extended serotonin waveform (ESW, 0.2, 1.3, -0.1, 0.2, 1000 V s-1) and extended hold serotonin waveform (EHSW, 0.2, 1.3 (hold 1 ms), -0.1, 0.2, 400 V s-1). The EHSW was the most sensitive (LOD = 0.6 nM), and the JW the least sensitive (LOD = 2.4 nM). With the Jackson waveform, electrode fouling was significant with repeated injections of serotonin or exposure to its metabolite, 5-hydroxyindoleacetic acid (5-HIAA). Using the extended waveforms, electrodes fouled 50% less than with the Jackson waveform for both analytes. No electrode fouling was observed with the dopamine waveform because of the negative holding potential. The Jackson waveform was the most selective for serotonin over dopamine (800×), and the ESW was also highly selective. All waveforms were useful for measuring serotonin with optogenetic stimulation in Drosophila larvae. These results provide new FSCV waveforms to measure dynamic serotonin changes with different experimental requirements, like high sensitivity (EHSW), high selectivity (ESW, JW), or eliminating electrode fouling (DA).

Glassy carbon microelectrode arrays enable voltage-peak separated simultaneous detection of dopamine and serotonin using fast scan cyclic voltammetry

Glassy carbon (GC) microelectrode arrays can simultaneously discriminate the reduction and oxidation peaks of dopamine and serotonin at low concentrations (10–200 nM). They demonstrated fast electron transfer kinetics and good fouling properties.

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.

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.

Carbon Nanotube Yarn Microelectrodes Promote High Temporal Measurements of Serotonin Using Fast Scan Cyclic Voltammetry

Carbon fiber-microelectrodes (CFMEs) have been the standard for neurotransmitter detection for over forty years. However, in recent years, there have been many advances of utilizing alternative nanomaterials for neurotransmitter detection with fast scan cyclic voltammetry (FSCV). Recently, carbon nanotube (CNT) yarns have been developed as the working electrode materials for neurotransmitter sensing capabilities with fast scan cyclic voltammetry. Carbon nanotubes are ideal for neurotransmitter detection because they have higher aspect ratios enabling monoamine adsorption and lower limits of detection, faster electron transfer kinetics, and a resistance to surface fouling. Several methods to modify CFMEs with CNTs have resulted in increases in sensitivity, but have also increased noise and led to irreproducible results. In this study, we utilize commercially available CNT-yarns to make microelectrodes as enhanced neurotransmitter sensors for neurotransmitters such as serotonin. CNT-yarn microelectrodes have significantly higher sensitivities (peak oxidative currents of the cyclic voltammograms) than CFMEs and faster electron transfer kinetics as measured by peak separation (ΔEP) values. Moreover, both serotonin and dopamine are adsorption controlled to the surface of the electrode as measured by scan rate and concentration experiments. CNT yarn microelectrodes also resisted surface fouling of serotonin onto the surface of the electrode over thirty minutes and had a wave application frequency independent response to sensitivity at the surface of the electrode.

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.

TinyFSCV: FSCV for the Masses

The ability to monitor neurochemical dynamics in target brain regions with a high degree of temporal resolution has assisted researchers in investigating the pathogenesis, and pathophysiology of a variety of neurological and psychiatric disorders. Current systems for neurochemical monitoring are bulky or expensive, limiting widespread exploration of this research field and preventing large-scale parallel experimentation. In this paper, we present a new miniaturized research platform, the TinyFSCV system, which can be used to monitor dynamic changes in neurochemicals through Fast-Scan Cyclic Voltammetry (FSCV). This system contains a precision voltage output circuit that can accurately output potentials between -0.55 to 2 V and scan a connected electrochemical cell at up to 400 V/s, the required speed to sense most neurochemicals with FSCV. In addition, the device includes precision current measurement circuity with a measurement range of -115 to [Formula: see text] capable of taking measurements at up to 56 KS/s. Four experiments are conducted to demonstrate the capability of the system. These consisted of: static bench tests, static ferrocene tests, and static and dynamic dopamine tests. These experiments demonstrate the ability of the miniaturized platform to accurately sense and measure neurochemicals. Ultimately, the TinyFSCV system is a platform that can enable large-scale, low-cost parallel experimentation to take place in the field of neurochemical monitoring. In addition, this device will increase the accessibility of neurochemical sensing, providing advanced tools and techniques to more researchers, and facilitating widespread exploration of the field of neurodynamics.

Phasic dopamine release identification using convolutional neural network

Dopamine has a major behavioral impact related to drug dependence, learning and memory functions, as well as pathologies such as schizophrenia and Parkinson's disease. Phasic release of dopamine can be measured in vivo with fast-scan cyclic voltammetry. However, even for a specialist, manual analysis of experiment results is a repetitive and time consuming task. This work aims to improve the automatic dopamine identification from fast-scan cyclic voltammetry data using convolutional neural networks (CNN). The best performance obtained in the experiments achieved an accuracy of 98.31% using a combined CNN approach. The end-to-end object detection system using YOLOv3 achieved an accuracy of 97.66%. Also, a new public dopamine release dataset was presented, and it is available at https://web.inf.ufpr.br/vri/databases/phasicdopaminerelease/.

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.

In vivo Hippocampal Serotonin Dynamics in Male and Female Mice: Determining Effects of Acute Escitalopram Using Fast Scan Cyclic Voltammetry

Depression is a highly prevalent psychiatric disorder, impacting females at a rate roughly twice that of males. This disparity has become the focus of many studies which are working to determine if there are environmental or biological underpinnings to depression pathology. The biology of depression is not well understood, but experts agree that a key neurotransmitter of interest is serotonin. Most research on basic serotonin neurochemistry, by us and others, has predominantly focused on male models. Thus, it is now critical to include female models to decipher possible fundamental differences between the sexes that may underlie this disorder. In this paper, we seek to determine any such differences using fast-scan cyclic voltammetry (FSCV) and fast-scan controlled adsorption voltammetry. These techniques allow us to probe the serotonergic system via measurement of evoked and ambient serotonin at carbon fiber microelectrodes (CFMs). Our data reveal no statistical differences, in the hippocampus, in female serotonin chemistry during the different stages of the estrous cycle compared to the mean female response. Furthermore, no difference was observed in evoked serotonin release and reuptake, nor ambient extracellular serotonin levels between male and female mice. We applied a previously developed mathematical model that fits our serotonin signals as a function of several synaptic processes that control the extracellular levels of this transmitter. We used the model to study potential system differences between males and females. One hypothesis brought fourth, that female mice exhibit tighter autoreceptor control of serotonin, is validated via literature and methiothepin challenge. We postulate that this tight regulation may act as a control mechanism against changes in the serotonin signal mediated by estrogen spikes. Importantly, this safety mechanism has no consequence for acutely administered escitalopram’s (ESCIT’s) ability to increase extracellular serotonin between the sexes. This work demonstrates little fundamental differences in in vivo hippocampal serotonin between the sexes, bar control mechanisms in female mice that can be observed under extraneous circumstances. We thus highlight the importance of considering sex as a biological factor in determining pharmacodynamics for personalized medical treatments that involve targeting serotonin receptors.

An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction

Dynamic feedback based closed-loop medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. Closed-loop devices integrate a level of neurobiological feedback, which allows for real-time adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential feedback component in closed-loop therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson's disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of feedback for closed-loop neuromodulation treatments. A generic model of the closed-loop treatment is developed to describe the high-level functions of any system designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of closed-loop medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.

In Vivo Ambient Serotonin Measurements at Carbon-Fiber Microelectrodes

The mechanisms that control extracellular serotonin levels in vivo are not well-defined. This shortcoming makes it very challenging to diagnose and treat the many psychiatric disorders in which serotonin is implicated. Fast-scan cyclic voltammetry (FSCV) can measure rapid serotonin release and reuptake events but cannot report critically important ambient serotonin levels. In this Article, we use fast-scan controlled adsorption voltammetry (FSCAV), to measure serotonin's steady-state, extracellular chemistry. We characterize the "Jackson" voltammetric waveform for FSCAV and show highly stable, selective, and sensitive ambient serotonin measurements in vitro. In vivo, we report basal serotonin levels in the CA2 region of the hippocampus as 64.9 ± 2.3 nM (n = 15 mice, weighted average ± standard error). We electrochemically and pharmacologically verify the selectivity of the serotonin signal. Finally, we develop a statistical model that incorporates the uncertainty in in vivo measurements, in addition to electrode variability, to more critically analyze the time course of pharmacological data. Our novel method is a uniquely powerful analysis tool that can provide deeper insights into the mechanisms that control serotonin's extracellular levels.

Serotonin axons in the neocortex of the adult female mouse regrow after traumatic brain injury

It is widely held that injured neurons in the central nervous system do not undergo axonal regrowth. However, there is mounting evidence that serotonin axons are a notable exception. Serotonin axons undergo long-distance regrowth in the neocortex after amphetamine lesion, and, following a penetrating stab injury, they can regrow from cut ends to traverse the stab rift. Traumatic brain injury (TBI) is clinically prevalent and can lead to pathologies, such as depression, that are related to serotonergic dysfunction. Thus, whether serotonin axons can regrow after TBI is an important question. We used two models for TBI-a persistent open skull condition and controlled cortical impact-to evoke injury in adult female mouse neocortex, and assessed serotonin axon density 1 week, 1 month, and 3 months after injury by serotonin transporter immunohistochemistry. We found that after both forms of TBI, serotonin axon density is decreased posterior but not anterior to the injury site when measured in layer 1 at 1 week post surgery, and that serotonin axons are capable of regrowing into the distal zone to increase density by 1 month post surgery. This pattern is consistent with the anterior-to-posterior course of serotonin axons in the neocortex. TBI in these models is associated with significant reactive astrogliosis both anterior and posterior to the impact, but the degree of reactive astrogliosis is not correlated with serotonin axon density when measured 1 week after TBI. Microglial density remains constant following both types of injuries, but microglial condensation was detected 1 week after controlled cortical impact.

Galanin contributes to monoaminergic dysfunction and to dependent neurobehavioral comorbidities of epilepsy

Status epilepticus (SE) in rats, along with chronic epilepsy, leads to the development of behavioral impairments resembling depressive disorder and/or attention deficit/hyperactivity disorder (ADHD), thus reflecting respective comorbidities in epilepsy patients. Suppressed neurotransmitter tone in the raphe nucleus (RN)-prefrontal cortex (PFC) serotonergic pathway and in the locus coeruleus (LC)-PFC noradrenergic pathway underlies depressive- and impulsive-like behavioral deficits respectively. We examined possible mechanisms leading to the monoamine dysfunction in brainstem efferents, namely modulatory effects of the neuropeptide galanin on serotonin (5-HT) and norepinephrine (NE) signaling. SE was induced in young adult male Wistar rats by LiCl and pilocarpine. Epileptic rats were categorized vis-à-vis behavioral deficits as not impaired, "depressed" and "impulsive". Depressive- and impulsive-like behaviors were examined in the forced swimming test (FST). The strength of serotonergic transmission in RN-PFC and of noradrenergic transmission in LC-PFC was analyzed using in vivo fast scan cyclic voltammetry. Galanin receptor type 1 (GalR1)/type 2 (GalR2) antagonist M40, and a preferential GalR2 antagonist M871 were administered over 3days locally into either RN or LC by means of ALZET osmotic minipumps connected to locally implanted infusion cannulas. Intra-RN injection of M40 improved serotonergic tone and depressive-like behavior in epileptic "depressed" rats. Intra-LC injection of M40 improved noradrenergic tone and impulsive-like behavior in epileptic "impulsive" rats. The effects of M40 were only observed in impaired subjects. The treatment did not modify neurotransmission and behavior in naïve and epileptic not impaired rats; in "depressed" rats the effects were limited to serotonergic transmission and immobility, while in "impulsive" rats - to noradrenergic transmission and struggling behavior. Intra-RN administration of M871 exacerbated depressive-like behavior, but had no effects on any other of the examined parameters in any category of animals. These findings suggest that endogenous galanin, acting through GalR1 may be involved in the pathophysiology of epilepsy-associated depression and ADHD via inhibiting RN-PFC serotonergic and LC-PFC noradrenergic transmissions respectively.

Regrowth of Serotonin Axons in the Adult Mouse Brain Following Injury

It is widely believed that damaged axons in the adult mammalian brain have little capacity to regrow, thereby impeding functional recovery after injury. Studies using fixed tissue have suggested that serotonin neurons might be a notable exception, but remain inconclusive. We have employed in vivo two-photon microscopy to produce time-lapse images of serotonin axons in the neocortex of the adult mouse. Serotonin axons undergo massive retrograde degeneration following amphetamine treatment and subsequent slow recovery of axonal density, which is dominated by new growth with little contribution from local sprouting. A stab injury that transects serotonin axons running in the neocortex is followed by local regression of cut serotonin axons and followed by regrowth from cut ends into and across the stab rift zone. Regrowing serotonin axons do not follow the pathways left by degenerated axons. The regrown axons release serotonin and their regrowth is correlated with recovery in behavioral tests.

In vivo histamine voltammetry in the mouse premammillary nucleus

Histamine plays a major role in the mediation of allergic reactions such as peripheral inflammation. This classical monoamine is also a neurotransmitter involved in the central nervous system but its role in this context is poorly understood. Studying histamine neurotransmission is important due to its implications in many neurological disorders. The sensitivity, selectivity and high temporal resolution of fast scan cyclic voltammetry (FSCV) offer many advantages for studying electroactive neurotransmitters. Histamine has previously been studied with FSCV; however, the lack of a robust Faradaic electrochemical signal makes it difficult to selectively identify histamine in complex media, as found in vivo. In this work, we optimize an electrochemical waveform that provides a stimulation-locked and unique electrochemical signal towards histamine. We describe in vitro waveform optimization and a novel in vivo physiological model for stimulating histamine release in the mouse premammillary nucleus via stimulation of the medial forebrain bundle. We demonstrate that a robust signal can be used to effectively identify histamine and characterize its in vivo kinetics.

Sex- and SERT-mediated differences in stimulated serotonin revealed by fast microdialysis

In vivo microdialysis is widely used to investigate how neurotransmitter levels in the brain respond to biologically relevant challenges. Here, we combined recent improvements in the temporal resolution of online sampling and analysis for serotonin with a brief high-K(+) stimulus paradigm to study the dynamics of evoked release. We observed stimulated serotonin overflow with high-K(+) pulses as short as 1 min when determined with 2-min dialysate sampling in ventral striatum. Stimulated serotonin levels in female mice during the high estrogen period of the estrous cycle were similar to serotonin levels in male mice. By contrast, stimulated serotonin overflow during the low estrogen period in female mice was increased to levels similar to those in male mice with local serotonin transporter (SERT) inhibition. Stimulated serotonin levels in mice with constitutive loss of SERT were considerably higher yet, pointing to neuroadaptive potentiation of serotonin release. When combined with brief K(+) stimulation, fast microdialysis reveals dynamic changes in extracellular serotonin levels associated with normal hormonal cycles and pharmacologic vs genetic loss of SERT function.

RECENT DEVELOPMENTS IN ELECTROCHEMICAL SENSORS FOR THE DETECTION OF NEUROTRANSMITTERS FOR APPLICATIONS IN BIOMEDICINE

Neurotransmitters are important biological molecules that are essential to many neurophysiological processes including memory, cognition, and behavioral states. The development of analytical methodologies to accurately detect neurotransmitters is of great importance in neurological and biological research. Specifically designed microelectrodes or microbiosensors have demonstrated potential for rapid, real-time measurements with high spatial resolution. Such devices can facilitate study of the role and mechanism of action of neurotransmitters and can find potential uses in biomedicine. This paper reviews the current status and recent advances in the development and application of electrochemical sensors for the detection of small-molecule neurotransmitters. Measurement challenges and opportunities of electroanalytical methods to advance study and understanding of neurotransmitters in various biological models and disease conditions are discussed.

Voltammetric and mathematical evidence for dual transport mediation of serotonin clearance in vivo

The neurotransmitter serotonin underlies many of the brain's functions. Understanding serotonin neurochemistry is important for improving treatments for neuropsychiatric disorders such as depression. Antidepressants commonly target serotonin clearance via serotonin transporters and have variable clinical effects. Adjunctive therapies, targeting other systems including serotonin autoreceptors, also vary clinically and carry adverse consequences. Fast scan cyclic voltammetry is particularly well suited for studying antidepressant effects on serotonin clearance and autoreceptors by providing real-time chemical information on serotonin kinetics in vivo. However, the complex nature of in vivo serotonin responses makes it difficult to interpret experimental data with established kinetic models. Here, we electrically stimulated the mouse medial forebrain bundle to provoke and detect terminal serotonin in the substantia nigra reticulata. In response to medial forebrain bundle stimulation we found three dynamically distinct serotonin signals. To interpret these signals we developed a computational model that supports two independent serotonin reuptake mechanisms (high affinity, low efficiency reuptake mechanism, and low affinity, high efficiency reuptake system) and bolsters an important inhibitory role for the serotonin autoreceptors. Our data and analysis, afforded by the powerful combination of voltammetric and theoretical methods, gives new understanding of the chemical heterogeneity of serotonin dynamics in the brain. This diverse serotonergic matrix likely contributes to clinical variability of antidepressants.

In vivo monitoring of serotonin in the striatum of freely moving rats with one minute temporal resolution by online microdialysis-capillary high-performance liquid chromatography at elevated temperature and pressure

Online monitoring of serotonin in striatal dialysate from freely moving rats was carried out for more than 16 h at 1 min time resolution using microdialysis coupled online to a capillary HPLC system operating at about 500 bar and 50 °C. Several aspects of the system were optimized toward robust, in vivo online measurements. A two-loop, eight-port rotary injection valve demonstrated better consistency of continuous injections than the more commonly used two-loop, 10-port valve. A six-port loop injector for introducing stimulating solutions (stimulus injector) was placed in-line between the syringe pump and microdialysis probe. We minimized solute dispersion by using capillary tubing (75 μm inside diameter, 70 cm long) for the probe inlet and outlet. In vitro assessment of concentration dispersion during transport with a 30 s time resolution showed that the dispersion standard deviation for serotonin was well within the desired system temporal resolution. Each 30 or 60 s measurement reflects the integral of the true time response over the measurement time. We have accounted for this mathematically in determining the concentration dispersion during transport. The delay time between a concentration change at the probe and its detection is 7 min. The timing of injections from the stimulus injector and the cycle time for the HPLC monitoring of the flow stream were controlled. The electrochemical detector contained a 13 μm spacer to minimize detector dead volume. During in vivo experiments, retention time and separation efficiency were stable and reproducible. There was no statistically significant change over 5.5 h in the electrochemical detector sensitivity factor for serotonin. Dialysate serotonin concentrations change significantly in response to a 120 mM K(+) stimulus. Release of serotonin evoked by a 10 min, 120 mM K(+) stimulation, but not for other K(+) stimuli, exhibited a reproducible, oscillating profile of dialysate serotonin concentration versus time. Infusion of fluoxetine, a serotonin uptake inhibitor, increased dialysate serotonin concentrations and stimulated release magnitude. Transient serotonin increases were observed in response to the stress associated with unexpected handling. This system is simple, efficient, reliable, and suitable for the study of serotonin neurochemistry associated with emotion and behavior.