Modulation of serotonin transporter expression by escitalopram under inflammation.

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

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.

Serotonin is a common thread linking different classes of antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of escitalopram, fluoxetine, reboxetine, and ketamine. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking, and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis, and the monoamine hypothesis).

Dynamical questions in volume transmission.

In volume transmission (or neuromodulation) neurons do not make one-to-one connections to other neurons, but instead simply release neurotransmitter into the extracellular space from numerous varicosities. Many well-known neurotransmitters including serotonin (5HT), dopamine (DA), histamine (HA), Gamma-Aminobutyric Acid (GABA) and acetylcholine (ACh) participate in volume transmission. Typically, the cell bodies are in one volume and the axons project to a distant volume in the brain releasing the neurotransmitter there. We introduce volume transmission and describe mathematically two natural homeostatic mechanisms. In some brain regions several neurotransmitters in the extracellular space affect each other's release. We investigate the dynamics created by this comodulation in two different cases: serotonin and histamine; and the comodulation of 4 neurotransmitters in the striatum and we compare to experimental data. This kind of comodulation poses new dynamical questions as well as the question of how these biochemical networks influence the electrophysiological networks in the brain.

Serotonin is a Common Thread Linking Different Classes of Antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (synaptic plasticity and neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of antidepressants. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis and the monoamine hypothesis).

An In Vivo Definition of Brain Histamine Dynamics Reveals Critical Neuromodulatory Roles for This Elusive Messenger.

Histamine is well known for mediating peripheral inflammation; however, this amine is also found in high concentrations in the brain where its roles are much less known. In vivo chemical dynamics are difficult to measure, thus fundamental aspects of histamine's neurochemistry remain undefined. In this work, we undertake the first in-depth characterization of real time in vivo histamine dynamics using fast electrochemical tools. We find that histamine release is sensitive to pharmacological manipulation at the level of synthesis, packaging, autoreceptors and metabolism. We find two breakthrough aspects of histamine modulation. First, differences in H3 receptor regulation between sexes show that histamine release in female mice is much more tightly regulated than in male mice under H3 or inflammatory drug challenge. We hypothesize that this finding may contribute to hormone-mediated neuroprotection mechanisms in female mice. Second, a high dose of a commonly available antihistamine, the H1 receptor inverse agonist diphenhydramine, rapidly decreases serotonin levels. This finding highlights the sheer significance of pharmaceuticals on neuromodulation. Our study opens the path to better understanding and treating histamine related disorders of the brain (such as neuroinflammation), emphasizing that sex and modulation (of serotonin) are critical factors to consider when studying/designing new histamine targeting therapeutics.

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.

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.

Autoreceptor control of serotonin dynamics.

BACKGROUND: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding involves genomics, neurochemistry, electrophysiology, and behavior. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders. This paper presents a new deterministic model of serotonin metabolism and a new systems population model that takes into account the large variation in enzyme and transporter expression levels, tryptophan input, and autoreceptor function. RESULTS: We discuss the steady state of the model and the steady state distribution of extracellular serotonin under different hypotheses on the autoreceptors and we show the effect of tryptophan input on the steady state and the effect of meals. We use the deterministic model to interpret experimental data on the responses in the hippocampus of male and female mice, and to illustrate the short-time dynamics of the autoreceptors. We show there are likely two reuptake mechanisms for serotonin and that the autoreceptors have long-lasting influence and compare our results to measurements of serotonin dynamics in the substantia nigra pars reticulata. We also show how histamine affects serotonin dynamics. We examine experimental data that show very variable response curves in populations of mice and ask how much variation in parameters in the model is necessary to produce the observed variation in the data. Finally, we show how the systems population model can potentially be used to investigate specific biological and clinical questions. CONCLUSIONS: We have shown that our new models can be used to investigate the effects of tryptophan input and meals and the behavior of experimental response curves in different brain nuclei. The systems population model incorporates individual variation and can be used to investigate clinical questions and the variation in drug efficacy. The codes for both the deterministic model and the systems population model are available from the authors and can be used by other researchers to investigate the serotonergic system.

Modeling the long term effects of thermoregulation on human sleep.

The connection between human sleep and energy exertion has long been regarded as part of the reasoning for the need to sleep. A recent theory proposes that during REM sleep, energy utilized for thermoregulation is diverted to other relevant biological processes. We present a mathematical model of human sleep/wake regulation with thermoregulatory functions to gain quantitative insight into the effects of ambient temperature on sleep quality. Our model extends previous models by incorporating equations for the metabolic processes that control thermoregulation during sleep. We present numerical simulations that provide a quantitative answer for how humans adjust by changing the normal sleep stage progression when it is challenged with ambient temperatures away from thermoneutral. We explore the dynamics for a single night and several nights. Our results indicate that including the effects of temperature is a vital component of modeling sleep.

Fast serotonin voltammetry as a versatile tool for mapping dynamic tissue architecture: I. Responses at carbon fibers describe local tissue physiology.

It is important to monitor serotonin neurochemistry in the context of brain disorders. Specifically, a better understanding of biophysical alterations and associated biochemical functionality within subregions of the brain will enable better of understanding of diseases such as depression. Fast voltammetric tools at carbon fiber microelectrodes provide an opportunity to make direct evoked and ambient serotonin measurements in vivo in mice. In this study, we characterize novel stimulation and measurement circuitries for serotonin analyses in brain regions relevant to psychiatric disease. Evoked and ambient serotonin in these brain areas, the CA2 region of the hippocampus and the medial prefrontal cortex, are compared to ambient and evoked serotonin in the substantia nigra pars reticulata, an area well established previously for serotonin measurements with fast voltammetry. Stimulation of a common axonal location evoked serotonin in all three brain regions. Differences are observed in the serotonin release and reuptake profiles between these three brain areas which we hypothesize to arise from tissue physiology heterogeneity around the carbon fiber microelectrodes. We validate this hypothesis mathematically and via confocal imaging. We thereby show that fast voltammetric methods can provide accurate information about local physiology and highlight implications for chemical mapping. Cover Image for this issue: doi: 10.1111/jnc.14739.

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

[This corrects the article DOI: 10.3389/fnins.2019.00362.].

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.

Voltammetric evidence for discrete serotonin circuits, linked to specific reuptake domains, in the mouse medial prefrontal cortex.

The medial prefrontal cortex (mPFC) is an important brain region, that controls a variety of behavioral and functional outputs. As an important step in characterizing mPFC functionality, in this paper we focus on chemically defining serotonin transmission in this area. We apply cutting-edge analytical methods, fast-scan cyclic voltammetry (FSCV) and fast-scan controlled adsorption cyclic voltammetry (FSCAV), pioneered in our laboratory, for the first real-time in vivo analysis of serotonin in the mPFC. In prior in vivo work in the substantia nigra, pars reticulata, we found that our sub-second measurements of a single evoked serotonin release were subject to two clearance mechanisms. These mechanisms were readily modeled via Uptake 1, mediated by the serotonin transporters (SERTs), and Uptake 2, mediated by monoamine transporters (dopamine transporters (DATs), norepinephrine transporters (NETs), and organic cation transporters (OCTs)). Here in the mPFC, for the first time to our knowledge, we observe two release events in response to a single stimulation of the medial forebrain bundle (MFB). Of particular note is that each response is tied to a discrete reuptake profile comprising both Uptake 1 and 2. We hypothesize that two distinct populations of serotonin axons traverse the MFB and terminate in different domains with specific reuptake profiles. We test and confirm this hypothesis using a multifaceted pharmacological, histological and mathematical approach. We thus present evidence for a highly elaborate biochemical organization that regulates serotonin chemistry in the mPFC. This knowledge provides a solid foundation on which to base future studies of the involvement of the mPFC in brain function and behavior.

Systems biology of robustness and homeostatic mechanisms.

All organisms are subject to large amounts of genetic and environmental variation and have evolved mechanisms that allow them to function well in spite of these challenges. This property is generally referred to as robustness. We start with the premise that phenotypes arise from dynamical systems and are therefore system properties. Phenotypes occur at all levels of the biological organizational hierarchy, from gene products, to biochemical pathways, to cells, tissues, organs, appendages, and whole bodies. Phenotypes at all these levels are subject to environmental and genetic challenges against which their form and function need to be protected. The mechanisms that can produce robustness are diverse and several different kinds often operate simultaneously. We focus, in particular, on homeostatic mechanisms that dynamically maintain form and function against varying environmental and genetic factors. Understanding how homeostatic mechanisms operate, how they reach their set point, and the nature of the set point pose difficult challenges. In developmental systems, homeostatic mechanisms make the progression of morphogenesis relatively insensitive to genetic and environmental variation so that the outcomes vary little, even in the presence of severe mutational and environmental stress. Accordingly, developmental systems give the appearance of being goal-oriented, but how the target phenotype is encoded is not known. We discuss why and how individual variation poses challenges for mathematical modeling of biological systems, and conclude with an explanation of how system population models are a useful method for incorporating individual variation into deterministic ordinary differential equation (ODE) models. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Physiology > Mammalian Physiology in Health and Disease Physiology > Organismal Responses to Environment Biological Mechanisms > Regulatory Biology.

A mathematical model for histamine synthesis, release, and control in varicosities.

BACKGROUND: Histamine (HA), a small molecule that is synthesized from the amino acid histidine, plays an important role in the immune system where it is associated with allergies, inflammation, and T-cell regulation. In the brain, histamine is stored in mast cells and other non-neuronal cells and also acts as a neurotransmitter. The histamine neuron cell bodies are in the tuberomammillary (TM) nucleus of the hypothalamus and these neurons send projections throughout the central nervous system (CNS), in particular to the cerebral cortex, amygdala, basal ganglia, hippocampus, thalamus, retina, and spinal cord. HA neurons make few synapses, but release HA from the cell bodies and from varicosities when the neurons fire. Thus the HA neural system seems to modulate and control the HA concentration in projection regions. It is known that high HA levels in the extracellular space inhibit serotonin release, so HA may play a role in the etiology of depression. RESULTS: We compare model predictions to classical physiological experiments on HA half-life, the concentration of brain HA after histidine loading, and brain HA after histidine is dramatically increased or decreased in the diet. The model predictions are also consistent with in vivo experiments in which extracellular HA is measured, using Fast Scan Cyclic Voltammetry, in the premammillary nucleus (PM) after a 2 s antidromic stimulation of the TM, both without and in the presence of the H 3 autoreceptor antagonist thioperamide. We show that the model predicts well the temporal behavior of HA in the extracellular space over 30 s in both experiments. CONCLUSIONS: Our ability to measure in vivo histamine dynamics in the extracellular space after stimulation presents a real opportunity to understand brain function and control. The observed extracellular dynamics depends on synthesis, storage, neuronal firing, release, reuptake, glial cells, and control by autoreceptors, as well as the behavioral state of the animal (for example, depression) or the presence of neuroinflammation. In this complicated situation, the mathematical model will be useful for interpreting data and conducting in silico experiments to understand causal mechanisms. And, better understanding can suggest new therapeutic drug targets.

State-dependent metabolic partitioning and energy conservation: A theoretical framework for understanding the function of sleep.

Metabolic rate reduction has been considered the mechanism by which sleep conserves energy, similar to torpor or hibernation. This mechanism of energy savings is in conflict with the known upregulation (compared to wake) of diverse functions during sleep and neglects a potential role in energy conservation for partitioning of biological operations by behavioral state. Indeed, energy savings as derived from state-dependent resource allocations have yet to be examined. A mathematical model is presented based on relative rates of energy deployment for biological processes upregulated during either wake or sleep. Using this model, energy savings from sleep-wake cycling over constant wakefulness is computed by comparing stable limit cycles for systems of differential equations. A primary objective is to compare potential energy savings derived from state-dependent metabolic partitioning versus metabolic rate reduction. Additionally, energy conservation from sleep quota and the circadian system are also quantified in relation to a continuous wake condition. As a function of metabolic partitioning, our calculations show that coupling of metabolic operations with behavioral state may provide comparatively greater energy savings than the measured decrease in metabolic rate, suggesting that actual energy savings derived from sleep may be more than 4-fold greater than previous estimates. A combination of state-dependent metabolic partitioning and modest metabolic rate reduction during sleep may enhance energy savings beyond what is achievable through metabolic partitioning alone; however, the relative contribution from metabolic partitioning diminishes as metabolic rate is decreased during the rest phase. Sleep quota and the circadian system further augment energy savings in the model. Finally, we propose that state-dependent resource allocation underpins both sleep homeostasis and the optimization of daily energy conservation across species. This new paradigm identifies an evolutionary selective advantage for the upregulation of central and peripheral biological processes during sleep, presenting a unifying construct to understand sleep function.

Systems Biology of Phenotypic Robustness and Plasticity.

SYNOPSIS: Gene regulatory networks, cellular biochemistry, tissue function, and whole body physiology are imbued with myriad overlapping and interacting homeostatic mechanisms that ensure that many phenotypes are robust to genetic and environmental variation. Animals also often have plastic responses to environmental variables, which means that many different phenotypes can correspond to a single genotype. Since natural selection acts on phenotypes, this raises the question of how selection can act on the genome if genotypes are decoupled from phenotypes by robustness and plasticity mechanisms. The answer can be found in the systems biology of the homeostatic mechanisms themselves. First, all such mechanisms operate over a limited range and outside that range the controlled variable changes rapidly allowing natural selection to act. Second, mutations and environmental stressors can disrupt homeostatic mechanisms, exposing cryptic genetic variation and allowing natural selection to act. We illustrate these ideas by examining the systems biology of four specific examples. We show how it is possible to analyze and visualize the roles of specific genes and specific polymorphisms in robustness in the context of large and realistic nonlinear systems. We also describe a new method, system population models, that allows one to connect causal dynamics to the variable outcomes that one sees in biological populations with large variation.

Analysis of Homeostatic Mechanisms in Biochemical Networks.

Cell metabolism is an extremely complicated dynamical system that maintains important cellular functions despite large changes in inputs. This "homeostasis" does not mean that the dynamical system is rigid and fixed. Typically, large changes in external variables cause large changes in some internal variables so that, through various regulatory mechanisms, certain other internal variables (concentrations or velocities) remain approximately constant over a finite range of inputs. Outside that range, the mechanisms cease to function and concentrations change rapidly with changes in inputs. In this paper we analyze four different common biochemical homeostatic mechanisms: feedforward excitation, feedback inhibition, kinetic homeostasis, and parallel inhibition. We show that all four mechanisms can occur in a single biological network, using folate and methionine metabolism as an example. Golubitsky and Stewart have proposed a method to find homeostatic nodes in networks. We show that their method works for two of these mechanisms but not the other two. We discuss the many interesting mathematical and biological questions that emerge from this analysis, and we explain why understanding homeostatic control is crucial for precision medicine.

A voltammetric and mathematical analysis of histaminergic modulation of serotonin in the mouse hypothalamus.

Histamine and serotonin are neuromodulators which facilitate numerous, diverse neurological functions. Being co-localized in many brain regions, these two neurotransmitters are thought to modulate one another's chemistry and are often implicated in the etiology of disease. Thus, it is desirable to interpret the in vivo chemistry underlying neurotransmission of these two molecules to better define their roles in health and disease. In this work, we describe a voltammetric approach to monitoring serotonin and histamine simultaneously in real time. Via electrical stimulation of the axonal bundles in the medial forebrain bundle, histamine release was evoked in the mouse premammillary nucleus. We found that histamine release was accompanied by a rapid, potent inhibition of serotonin in a concentration-dependent manner. We developed mathematical models to capture the experimental time courses of histamine and serotonin, which necessitated incorporation of an inhibitory receptor on serotonin neurons. We employed pharmacological experiments to verify that this serotonin inhibition was mediated by H3 receptors. Our novel approach provides fundamental mechanistic insights that can be used to examine the full extent of interconnectivity between histamine and serotonin in the brain. Histamine and serotonin are co-implicated in many of the brain's functions. In this paper, we develop a novel voltammetric method for simultaneous real-time monitoring of histamine and serotonin in the mouse premammillary nucleus. Electrical stimulation of the medial forebrain bundle evokes histamine and inhibits serotonin release. We show voltammetrically, mathematically, and pharmacologically that this serotonin inhibition is H3 receptor mediated.