Next Article in Journal
The Interactions of Insulin and Vitamin A Signaling Systems for the Regulation of Hepatic Glucose and Lipid Metabolism
Next Article in Special Issue
Neurodevelopmental Processes in the Prefrontal Cortex Derailed by Chronic HIV-1 Viral Protein Exposure
Previous Article in Journal
Proteomic Analysis of Niemann-Pick Type C Hepatocytes Reveals Potential Therapeutic Targets for Liver Damage
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

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

by
Kristen A. McLaurin
,
Michael Harris
,
Victor Madormo
,
Steven B. Harrod
,
Charles F. Mactutus
and
Rosemarie M. Booze
*
Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally.
Cells 2021, 10(8), 2158; https://doi.org/10.3390/cells10082158
Submission received: 6 July 2021 / Revised: 10 August 2021 / Accepted: 18 August 2021 / Published: 21 August 2021
(This article belongs to the Special Issue The Past, Present and Future of NeuroHIV: A Perspective to A Cure)

Abstract

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

1. Introduction

Since the beginning of the acquired immunodeficiency syndrome (AIDS) epidemic, neurocognitive impairments (NCI) and affective alterations have been associated with the disease [1,2]. Early in the AIDS epidemic, underlying focal processes and opportunistic infections accounted for approximately 30% of the neurological complications in individuals with AIDS; a progressive dementia, however, was more commonly reported [3]. The identification of human immunodeficiency virus type 1 (HIV-1) as the retroviral etiology of AIDS [4,5] led to the hypothesis that NCI and affective alterations may result from the direct effect of the virus on the brain. Indeed, HIV-1 penetrates the central nervous system (CNS) early in the course of infection [6], evidenced by the presence of HIV-1 in postmortem brain tissue [7,8,9], findings which led to the characterization of this progressive dementia, which became known as AIDS dementia complex (ADC, also recognized as HIV-associated dementia (HAD)).
ADC, which afflicted approximately 66% of autopsy-verified AIDS patients early in the epidemic, was a neurological syndrome primarily occurring during the later phases of systemic AIDS [3]. Early clinical characteristics of ADC included NCI (e.g., forgetfulness, loss of concentration), affective alterations (e.g., apathy) and motor system deficits [3,10,11]. Across time, most patients with ADC exhibited a steady decline in neurocognitive function, leading to severe dementia, ataxia and motor weakness [10].
Pathologically, distinct abnormalities in the white matter and subcortical structures, including the basal ganglia, were observed in the brains of individuals with ADC [12], observations which led researchers to hypothesize dopaminergic system dysfunction as a potential mechanism underlying the disease [13]. Cerebrospinal fluid (CSF) levels of dopamine (DA [14,15]) and homovanillic acid (HVA [15,16,17]), the primary DA metabolite, were significantly reduced in HIV-1/AIDS patients relative to seronegative controls. In HIV-1-infected brains, significant reductions in tyrosine hydroxylase (TH), the rate-limiting enzyme of DA synthesis, were also observed [18]. Most critically, the relationship between CSF HVA levels and neuropsychological function in HIV-1-infected patients provided compelling evidence for the role of dopaminergic system dysfunction in the pathogenesis of ADC [17].
With the discovery and introduction of antiretroviral therapies, however, AIDS/HIV-1 became a chronic, manageable disease, albeit NCI and affective alterations persist. The development of zidovudine (azidothymidine [19]), the first generation of antiretroviral therapy, provided early evidence that effective inhibition of HIV-1 may have some effects on cognitive function in AIDS patients [20,21,22]. Zidovudine monotherapy did not, however, mitigate affective alterations [20]. The subsequent utilization of multiple antiretroviral compounds to treat HIV-1 (i.e., combination antiretroviral therapy (cART)) led to a dramatic decrease in the severity of NCI and affective alterations associated with HIV-1 [23]. Specifically, in the post-cART era, ADC is rare, afflicting only 2–8% of cART-treated HIV-1 seropositive individuals [23]. However, milder forms of NCI and affective alterations persist, afflicting between 30% and 70% of HIV-1 seropositive individuals [24,25,26,27].
Although the pathophysiology of HAND and affective alterations in the post-cART era is likely multidimensional, dopaminergic system dysfunction persists [28,29,30]. Using four interrelated aims, the present review will examine evidence for alterations in dopaminergic levels in HIV-1 in the post-cART era. Given that approximately 73% of HIV-1 seropositive individuals are currently accessing antiretroviral treatment [31], the present review focuses on studies using biological systems (i.e., HIV-1 seropositive individuals, primates, rats, mice) with viral suppression. First, we will report basal/tonic values of DA in the CNS, including a discussion of the experimental approaches (e.g., high-performance liquid chromatography (HPLC), microdialysis, fast-scan cyclic voltammetry (FSCV)) used to measure DA. Second, the present review will examine the prominent evidence, including both anatomical and clinical symptomology, for the persistent decreased dopamine in HIV-1 seropositive individuals. Third, the potential effects of cART on the dopaminergic system will be assessed. Finally, we will address the mechanistic implications for dopamine decreases in HAND.

2. Basal Dopamine Concentrations in the Central Nervous System

The physiological significance of DA [32], and its presence in the brain [33,34,35], was first established in the 1950s. Subsequent methodological advances, including the development of microdialysis, HPLC and FSCV, afforded a critical opportunity to detect changes in basal (or tonic) DA [36]. However, DAs precise influence on cognition and behavior remains unclear, in large part due to inconsistencies in measured DA levels. Thus, one of the primary goals was to illustrate the inconsistencies in values via examination of the standard error of the mean and relative standard error.
DA concentration was estimated using the reported means, which were converted into ng/g of tissue (Table 1). Reported estimates are collapsed across species and biological sex under the assumption that the variability between brain regions and methodological approach are greater than the variability between species and sex [37]. Each manuscript, therefore, provided a single observation for each brain region that was reported. All estimates, as well as information regarding species and biological sex, are reported in Supplementary Table S1.
Critical evaluation of the literature revealed that basal DA values are dependent upon not only brain region, but also methodological technique (between-subjects ANOVA with log estimated DA concentration in ng/g of tissue as the dependent variable: brain region by method interaction, F(5,104) = 7.05, p ≤ 0.001, ηp2 = 0.253; Table 1; Figure 1). For example, utilization of HPLC to measure DA in the nucleus accumbens (NAc) results in an average estimated DA concentration over 40,000 times greater than the average estimated DA concentration measured using microdialysis. This outcome might be anticipated due to tissue homogenization prior to HPLC measurement; HPLC, therefore, measures total tissue DA content, whereas microdialysis measures extracellular DA levels [38]. Additionally, substantial variability in reported basal DA values within a single methodological approach was observed. For example, the relative standard error for the NAc was 33.9%, 17.1% and 27.8% for HPLC, microdialysis and FSCV respectively, values which are even higher in other brain regions (e.g., amygdala: 84.1% (HPLC) and 50% (microdialysis)). Given the substantial variability within and between methodological techniques, a brief discussion of some of the critical experimental considerations underlying these discrepancies is warranted. In addition, the potential utility of the latest technology (i.e., G protein-coupled receptor (GPCR) biosensors) for monitoring DA release is briefly reviewed.

2.1. High-Performance Liquid Chromatography (HPLC)

Broadly, chromatography is a well-established separative and analytical technique introduced by James and Martin [115]; the emergence of HPLC, however, is attributed to Huber and Hulsman [116]. To conduct HPLC, a pressurized liquid solvent (i.e., mobile phase) containing the sample is passed through a column filled with a solid adsorbent material, and each compound elutes at a unique rate, resulting in the separation of components as they flow through the column [117]. The isolated compounds are subsequently identified and quantified using a detector (e.g., UV/Vis spectrometry). HPLC can be further subdivided into multiple types dependent upon the type of column (e.g., liquid–liquid, ion-exchange, size exclusion) and “mobile phase” (e.g., non-polar, polar), factors which influence sensitivity, resolution and the method of brain tissue extraction. Critically, differences in extraction methodology (e.g., time of initial extraction, aqueous pH value, extraction solvents) result in drastic differences in percent recovery, an indirect measure of basal DA concentration [118].
Given HPLC’s wide use, sources of random and systematic error in HPLC have been studied extensively [119]. The brief discussion in the present review will focus on sources of error reported to affect the electrochemical detection of DA. First, the mobile phase column composition (e.g., ion pairing agent type, organic modifier, pH) has a pronounced effect on the capacity factor (k’), retention time, peak height units of DA and peak symmetry [120,121,122,123,124]. Second, the flow gradient rate, similarly, has a prominent effect on the resolution of the eluting compounds, k’ and background current [125]. Finally, chromatographic instrumentation, including the column temperature, alters the retention time of DA, whereby an increase in column temperature is associated with a decrease in retention time [123]. Additionally, column age may influence the resolution between DA and its metabolite (i.e., 3,4-Dihydroxyphenylacetic acid), whereby decreased resolution has been observed after approximately 500 injections of the biological material directly onto the column top [121].

2.2. Microdialysis

The utilization of microdialysis to quantify neurotransmitters in the brain was first reported in the 1970s and 1980s [126,127,128], research which contributed significantly to the widespread implementation of microdialysis methods. Microdialysis relies on the principle of diffusion, whereby molecules move from an area of high concentration to an area of low concentration. Methodologically, a microdialysis probe composed of a semipermeable dialysis membrane is surgically implanted into the brain, and a perfusion medium is infused slowly and continuously [129]. During perfusion, molecules in the extracellular space diffuse through the semipermeable membrane, are transported into outflow tubing and are collected for analyte quantification (e.g., HPLC [129]; Figure 2A). Although microdialysis detects neurotransmitters at low- to sub-nanomolar levels (for DA, see [113]), the technique has relatively low spatiotemporal resolution and is unable to evaluate real-time changes in the neurochemical environment.
Despite being considered the “gold standard” for obtaining basal neurotransmitter levels, methodological limitations may impede precise and/or consistent measurements. The diameter of a typical microdialysis probe is approximately 300 μm, a size which is substantially larger than neurons and glial cells (5–100 μm), as well as blood capillaries (8–10 μm) and vessels (~1 mm) in the brain [130]. Implantation of microdialysis probes, therefore, damages brain tissue, as evidenced by signs of ischemia [131,132] and a compromised blood–brain barrier [131,133]. Additionally, tissue damage resulting from the microdialysis probe disrupts synapses and neurons [134]. Critically, dopaminergic activity is disrupted by the implantation of microdialysis probes, as evidenced by both decreased DA release over post-probe implantation time [135] and alterations in the amplitude of evoked responses [136,137]. Recently developed novel approaches, including pharmacological agents [138,139] and a microfabricated probe [140], have the potential to mitigate some of the concerns regarding tissue disruption.
Consistent measurement of basal DA levels is further dependent upon multiple methodological details. Although HPLC is often used as a method to quantify the output from microdialysis, the methodological details discussed within the present section are conducted prior to the quantification of analytes. First, inappropriate concentrations of specific ions (e.g., Ca2+, NA+, K+) in the perfusate medium disrupt the homeostatic balance of the extracellular environment, altering the basal DA concentration. For example, increases in basal DA concentration are observed when the perfusate medium contains higher (e.g., 3.4 mM) levels of Ca2+ [63,141] or K+ [128]. In sharp contrast, utilization of a perfusion solution with too little Ca2+ [128,142] or too little K+ [142] results in decreased extracellular DA levels. It is vital, therefore, that the composition of perfusion solutions mimic the brain extracellular fluid; additional parameters, including pH and temperature, are also critical considerations [143]. Second, substantial increases in the concentrations of extracellular DA occur immediately following death [144,145,146]. Basal DA levels subsequently decrease as the postmortem interval increases [144,145,146]; albeit, basal DA concentration remains elevated, relative to pre-death levels, for at least an hour postmortem [144,145]. Third, in neutral and basic aqueous solutions, DA degrades rapidly [147], including in many common (e.g., aCSF, brain dialysate) perfusion solutions [148]. Several approaches, including temporal proximity (i.e., minimization of the time between sample collection and analysis [149]), addition of stabilizing agents to either the collection bins [65] or microdialysis media [150] and a microdialysis/LCMS system [148], have been implemented to mitigate the DA instability problem. Despite the validity of these approaches, inter-laboratory differences may preclude determining an estimate of the “true” basal DA concentration.

2.3. Fast-Scan Cyclic Voltammetry (FSCV)

FSCV, an electroanalytical technique developed in the early 1980s [151,152], affords a method to detect rapid neurotransmitter dynamics in the brain [153]. From a theoretical perspective, FSCV relies upon chemical sensing of neurotransmitters at carbon-fiber microelectrodes. Specifically, the voltage potential at the carbon-fiber microelectrode is rapidly increased and decreased, resulting in the oxidation and reduction of electroactive substances [154]. Examination of the cyclic voltammogram, which presents data as time (x-axis) by voltage (y-axis), allows for compound identification [155,156]. The strengths of FSCV include its high spatial (micrometer) acuity, high temporal (sub-second) resolution and high chemical (nanomolar range) sensitivity. However, FSCV is limited by the need for digital background subtraction [157], which restricts measurements to relative neurotransmitter changes, a factor which precludes the measurement of basal concentrations of electroactive species [154]. Therefore, FSCV has typically been utilized to measure phasic, rather than tonic, DA release. Recent novel modifications have afforded an opportunity to investigate tonic DA concentrations using FSCV [103,104,158,159]. While an in-depth discussion of these modifications is beyond the scope of this review, it is an emerging area of research that has the potential to transform our ability to accurately measure basal DA levels.

2.4. G Protein-Coupled Receptor (GPCR) Biosensors

GPCR biosensors for DA (or DA biosensors), the most recent method developed for monitoring DA dynamics, were first reported in 2018 [160,161], and contemporary versions have expanded upon these initial reports [162,163]. Theoretically, fluorescent DA biosensors rely upon the interaction between DA and D1- and D2-like GPCRs. DA biosensors were developed by inserting a genetically encoded, circularly permuted fluorescent protein (e.g., Green: cpGFP, Red: cpmApple) into the third intracellular loop of the naturally occurring human DA receptor. When DA is released, it binds to the endogenous ligand, causing a rapid conformational change in the GPCR, a conformational change that induces a profound increase in fluorescence intensity (i.e., 90–900%, for a review, see [164]; Figure 2C). DA biosensors exhibit high selectivity, molecular specificity, affinity (sub-micromolar) and resolution (sub-second [160,161,162,163,165]), making them ideally suited for tracking DA release. However, DA biosensors may be limited by low basal fluorescence levels, which precludes the detection of basal DA levels. A more comprehensive discussion of GPCR biosensors for DA is provided by Labouesse et al. [164].

2.5. General Experimental Considerations

Ideally, an estimate of basal DA values would be highly replicable when measurements are obtained in the same brain region, using the same methodological technique and in nearly genetically identical animals. However, basal DA concentrations are altered by natural biological variation within and between subjects. Independent of species, there is natural biological variation in basal DA concentrations resulting from within and between subject’s factors. For example, basal extracellular DA levels change across the functional lifespan, with significantly decreased DA observed in aged, relative to young, animals [166]. Furthermore, basal DA levels in the NAc [167,168], striatum [149,169] and medial prefrontal cortex (mPFC [170]) fluctuate in a circadian rhythm. Additionally, hormones have a profound impact on basal DA levels, as evidenced by changes across the estrous cycle [171,172] and resulting from gonadectomy [173].
To date, the substantial variability between studies, even within a single methodological approach, has obfuscated our ability to experimentally determine the “true” basal DA concentration. When appropriate experimental controls are implemented, the impact of a treatment (e.g., HIV-1, substance use) on basal DA concentration can be reliably determined; comparing between studies, however, remains challenging. Stringent and detailed reporting of methodological procedures may aid in determining which studies can be most accurately compared. From a practical perspective, however, the information compiled in Table 1 (expanded in Supplementary Table S1) provides a summary of the techniques currently in use.
In sum, HPLC of tissue homogenates may reveal total DA tissue content, while microdialysis enables sampling of the extracellular basal DA levels, but lacks temporal resolution (minutes) and spatial resolution. FSCV is currently used for relative changes in DA signals, and not for assessing basal DA levels. Although GPCR biosensors for DA may not clarify basal DA levels in the brain, their ability to rapidly detect DA function has the potential to transform our understanding of neural circuits. Critically, each neurochemical method for assessing DA levels has benefits and limitations that must be weighed when designing an experiment.

3. Chronic HIV-1 Results in Decreased Dopamine

Inconsistencies in the estimated basal DA values does not preclude the utilization or importance of these methodological techniques for evaluating group differences. As demonstrated in Table 2, HPLC, microdialysis and FSCV have been fundamental in elucidating how HIV-1 viral protein exposure alters basal DA concentration relative to seronegative individuals or controls. Results (Table 2) overwhelmingly support decreased DA concentrations following chronic HIV-1 viral protein exposure in either HIV-1 seropositive humans or biological systems utilized to model HIV-1.
Despite the overwhelming support for a hypodopaminergic state in HIV-1 (i.e., low levels of DA), there are a few outliers. Three studies [174,175,176] have reported transitory increases in DA concentration in the CSF, caudate putamen and prefrontal cortex (PFC), respectively. The subjects (i.e., humans, mice) evaluated in these studies share a key commonality: early or acute HIV-1. Specifically, the clinical sample included individuals in clinical stage 1 [174], which is characterized by asymptomatic infection and persistent generalized lymphadenopathy [177]. Preclinical measurements were conducted either one [176] or three [175] days after the completion of Tat protein induction by a doxycycline regimen. Critically, these increases in DA either failed to persist for longer intervals after Tat protein induction (i.e., 10 Days: [178], 40 Days: [175]) or were brain region-specific [176]. Moreover, there is no evidence for a hyperdopaminergic state during chronic HIV-1 infection in humans, suggesting little clinical relevance for assessing acute increases in dopamine.
Another notable inference that can be drawn from Table 2 regards the influence of cART on DA function in HIV-1 seropositive individuals. While monotherapy, including zidovudine (azidothymidine), was first implemented in 1985 [19], cART began in 1996. Critically, the strong support for decreased dopaminergic function spans across studies in both the pre- and post-cART era. A more comprehensive discussion for the potential role of cART in dopaminergic system dysfunction is presented in Section 5.
Undoubtedly, long-term HIV-1 viral protein exposure leads to persistent DA deficits, independent of treatment with cART. It is possible that there is an initial transient increase in DA immediately following HIV-1 infection, given the increased life expectancy for HIV-1 seropositive individuals [179,180], however, the acute phase fails to accurately reflect the current clinical syndrome.

4. HIV-1 Clinical Symptoms Reflect a Hypodopaminergic State

In 2007, the nosology for neurological complications in HIV-1 seropositive individuals was updated to reflect the milder phenotype of NCI and affective alterations, collectively termed HIV-1-associated neurocognitive disorders (HAND), observed in the post-cART era [190]. Using the established criteria, HIV-1 seropositive individuals are classified into one of three categories (i.e., asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorders (MND) or HAD) based on neurocognitive performance and alterations in daily functioning [190]. HAND, a progressive disease [191,192,193,194,195], is characterized by prominent neurocognitive deficits in speed of information processing, attention, working memory and executive function [26,196,197]. Affective alterations commonly observed in HAND include apathy [27,198] and depression [199,200]. These clinical symptoms reflect persistent DA deficits in HIV-1 seropositive individuals.
The present review will focus on evaluating the role of DA in the regulation of pre-attentive processes, attention and apathy, as a discussion of all neurocognitive and/or affective alterations, neural circuits and/or cellular mechanisms is beyond the scope. However, it is notable that the effect of decreased DA availability in HIV-1 seropositive individuals extends more broadly, as it is significantly associated with neuropsychological performance [29] and depression [188]. Furthermore, Figure 3 illustrates the profound difference in the clinical symptoms of hyperdopaminergic versus hypodopaminergic systems. There is no clinical evidence supportive of high dopamine levels following chronic HIV-1 infection in humans, suggesting that models/therapeutics must focus on rectifying low dopamine levels.

4.1. Pre-Attentive Processes

Pre-attentive processing (or sensorimotor gating) is defined as the screening of extraneous information to facilitate the uninterrupted processing of relevant information. Pre-pulse inhibition (PPI) of the auditory startle response (ASR), popularized by Hoffman and Ison [201,202], affords a translational experimental paradigm to measure pre-attentive processes. The presentation of a discrete pre-stimulus prior to a startling stimulus attenuates an individual’s startle response during a brief temporal window (i.e., 30–500 msec [203]). Prominent impairments in PPI have been observed in multiple neuropsychological disorders, including schizophrenia [204], obsessive-compulsive disorder [205,206], Huntington’s disease [207] and HIV-1 [208,209]. In HIV-1, deficits in PPI are characterized by a reduction in percent PPI [208,210] and a relative insensitivity to the manipulation of interstimulus interval (ISI, i.e., time between the discrete pre-stimulus and startling stimulus [209,211]). Most critically, impairments in PPI resulting from chronic HIV-1 viral protein exposure are associated with alterations in higher-order cognitive processing [208], progress across the functional lifespan [212,213] and may serve as a diagnostic and/or prognostic biomarker for HAND [214].
PPI is regulated, at least in part, by brain regions integral to the fronto-striatal circuit (i.e., ventral tegmental area (VTA), NAc and PFC) and the dopaminergic system. Specifically, within the neural circuit mediating PPI, the NAc is innervated by dopaminergic projections from the VTA and glutamatergic afferents from the mPFC. Gamma aminobutyric acid (GABA) projections are subsequently relayed from the NAc to the pedunculopontine tegmental nucleus (PPTg). Information is then sent from the PPTg to the caudal pontine reticular nucleus, a component of the acoustic startle circuit [215], resulting in the elicitation of a startle response. The auditory startle pathway and entire neural circuitry underlying PPI is more comprehensively reviewed by Koch [216] and Fendt et al. [217].
Profound reductions in PPI are observed when pharmacological manipulations and lesioning approaches are utilized to induce a hypodopaminergic state. Apomorphine, a direct dopamine agonist, acts in a biphasic dose-dependent manner [218,219], whereby low doses act on presynaptic receptors, resulting in decreased dopaminergic tone; high doses of apomorphine, in sharp contrast, act on both pre- and post-synaptic receptors, resulting in a hyperdopaminergic state. Administration of low doses of apomorphine, independent of sensory modality (i.e., auditory, visual [220]) or ISI [221], leads to prominent reductions in PPI [220,221,222]. Selective D1 receptor antagonists, including SCH23390 [223,224] and SCH39166 [225], also reduce PPI when injected into either the PFC [223,225] or dorsal striatum [224]. Furthermore, inducing a hypodopaminergic tone via 6-hydroxydopamine (6-OHDA) injections, which destroys dopaminergic and noradrenergic neurons [226,227], reduces PPI [228,229]. Collectively, pre-attentive processes, as indexed by PPI, are dramatically reduced under conditions that mimic a hypodopaminergic state, reductions which are similar to those observed in HIV-1 in the post-cART era.

4.2. Attention

Attention is a biologically complex cognitive function dependent upon reciprocal excitatory and inhibitory processes [230]. By definition, attention is selective, requiring the brain to process the most relevant information, while excluding, or inhibiting, irrelevant information [230]. According to a hierarchical model proposed by Sohlberg and Mateer [231,232], attention can be divided into multiple subcomponents (i.e., arousal, focused attention, sustained attention, selective attention, alternating attention and divided attention). With regards to HIV-1, chronic HIV-1 viral protein exposure induces prominent deficits across the subcomponents of attention, including sustained attention or vigilance [233], selective attention [234,235] and divided attention [236].
Although the precise neural circuitry underlying attentional processes has not yet been fully elucidated, there is strong evidence for the fundamental role of the PFC in higher-order cognition. The PFC is divided into six layers, superficial to deep, and is comprised of three major subdivisions, including the lateral PFC (lPFC), mPFC and orbital PFC (oPFC [230]). Midbrain DA neurons project to the PFC via the mesocortical DA pathway, a pathway which can be divided into two parallel systems [237]. Specifically, DA afferents from the VTA innervate the mPFC, whereas the lPFC is innervated by DA projections from the substantia nigra [237]. Most critically, however, DA modulates cognitive processes, including attention, in the PFC.
Induction of a hypodopaminergic state via pharmacological manipulations or lesioning approaches disrupts attentional behavior. First, local administration of the selective D1 antagonist SCH23390 to either the PFC [238,239] or NAc [240] impairs attention. Infusion of the D2 receptor antagonist sulpiride into the NAc [240], but not the PFC [238], also decreased attentional accuracy. Second, neonatal treatment with 6-OHDA produces persistent marked impairments in selective, spatial and/or sustained attention at a juvenile stage [241,242], during adolescence [243] and in adulthood [244]. 6-OHDA lesions of the PFC during adulthood also reduced selective attention, as evidenced by an increased susceptibility to task-irrelevant distractors [245]; attentional set shift, however, is relatively spared [245,246], consistent with observations following chronic HIV-1 viral protein exposure [233]. Furthermore, chronic administration of the selective dopaminergic neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) induced attentional deficits, characterized by impairments in sustained spatial attention and focused attention [247]. Taken together, induction of a hypodopaminergic state produces marked impairments in attentional processes similar to those observed in HIV-1 in the post-cART era.

4.3. Apathy

Traditionally, apathy has been defined as a lack of motivation [248] that is evidenced by the quantitative reduction in voluntary and goal-directed behaviors [249]. Goal-directed behaviors require the use of action to translate an internal state into the attainment of a goal. In clinical studies, apathy is most commonly [250] assessed using either the Apathy Evaluation Scale [251] or the Neuropsychiatric Inventory [252], scales which exhibit both strong reliability and validity [250]. Furthermore, preclinical studies have utilized operant and Pavlovian conditioning as a method to evaluate how willing an animal is to “work” for reinforcement [198,253,254]. Understanding apathy from both a clinical and preclinical perspective is vital, given its prevalence in many neurological disorders (e.g., Alzheimer’s disease [255], Parkinson’s disease [256], HIV-1 [27,257]). Indeed, chronic HIV-1 viral protein exposure induces prominent alterations in goal-directed behaviors [198,254]. The clinical significance of apathy in HIV-1 seropositive individuals cannot be understated, as increased apathy is significantly associated with greater impairments in activities of daily living [27,258], decreased medication adherence [259] and decreased quality of life [260].
Apathy is regulated, at least in part, by the anterior cingulate circuit, one of the behaviorally relevant fronto-striatal circuits [261]. Within this circuit, projections from the anterior cingulate cortex innervate the ventral striatum, including the NAc [262]. Subsequently, neurons in the ventral striatum project to the globus pallidus interna, ventral pallidum and rostrodorsal substantia nigra [263]. Both the ventral striatum and anterior cingulate cortex receive dopaminergic innervation from the VTA, supporting the fundamental role of DA in apathetic behaviors.
Indeed, the reduction of dopaminergic signaling via lesioning and chemogenetic approaches have demonstrated the importance of the neurotransmitter in goal-directed behavior. Induction of hypodopaminergic tone via either 6-OHDA lesions of the substantia nigra pars compacta [264,265,266] or MPTP [267] impaired motivated behaviors. More recently, the chemogenetic inhibition of DA neurons in the VTA dose-dependently reduced effort-based motivation [268]. Collectively, strong evidence supports apathetic behaviors under hypodopaminergic states.

5. Role of cART in Dopaminergic System Dysfunction

Currently, approximately 30 antiviral drugs are approved for the treatment of HIV-1 [269]. The approach to HIV-1 treatment evolved from the use of monotherapy with the nucleoside reverse transcriptase inhibitor (NRTI) zivodudine, to various combinations of two to four compounds composed of a NRTI, integrase strand inhibitor (INSTI), protease inhibitor (PI), or non-nucleoside reverse transcriptase inhibitors (NNRTI). Given that a hypodopaminergic tone is observed following chronic HIV-1 viral protein exposure, it is vital to examine the potential role of cART in dopaminergic dysregulation.
Some cART drugs, particularly those with greater CNS penetrance [270], are associated with adverse psychoactive effects in HIV-1 seropositive individuals [271,272,273,274]. Specifically, NRTIs, including efavirenz, are most commonly associated with adverse neuropsychiatric outcomes [275]. Patients commonly report hallucinations, delusion, paranoia and mania, as well as depression, anxiety, nervousness, dizziness, sleep disturbances and abnormal dreams [271,272,273,274].
Efavirenz exhibits a complex neuropharmacological profile, whereby it interacts with serotonin (5-HT) and GABAA receptors, and multiple monoamine transporters (i.e., serotonin transporter (SERT), dopamine transporter (DAT), vesicular monoamine transporter 2 (VMAT2) [276,277,278]). Further evidence for these interactions is provided by increased basal levels of 5-HT, DA, and norepinephrine, albeit in a region-specific manner, following intraperitoneal injections of 5 mg/kg of efavirenz every other day for two weeks [279]. Under differing experimental conditions, acute, oral administration of efavirenz (0, 25, 50 mg/kg) dose-dependently increased striatal DA levels; however, no significant alterations in basal DA levels were observed after sub-chronic (i.e., two-week) exposure [280]. Highly translational behavioral procedures examining a drug’s pharmacodynamic activity (e.g., drug discrimination, sensitization/habituation) and DA-related behaviors (e.g., drug reinforcement, conditioned reward behaviors) support the observed neuropharmacological profile and will be discussed in turn below.

5.1. Drug Discrimination

Drug discrimination is a free-operant procedure that allows the animal to learn that a subjective drug effect (i.e., discriminative stimulus) sets the occasion for reinforcement of a particular response [281]. Specifically, following injection of a psychoactive drug, responses on one levers are reinforced. Whereas, following a saline, however, responses on the alternative lever are reinforced [282]. After the discrimination is learned, a novel drug can be injected to determine whether the training and test drug share discriminative stimulus properties. If the novel test drug produces a discriminative stimulus similar to the training drug, then animals will respond on the lever associated with the training drug; however, the rat will respond on the saline-associated lever if the novel drug discriminative stimulus is different than that of the training drug.
Using the drug discrimination procedure, Gatch et al. [276] examined whether efavirenz produced a discriminative stimulus similar to different drugs of abuse. First, a group of rats were trained to discriminate the subjective drug effect of lysergic acid diethylamine (LSD), a serotonin receptor agonist, from that produced by saline injection. When tested with various doses of efavirenz, rats responded as if LSD was onboard, an effect that is primarily mediated by the 5-HT2A receptor. Results were confirmed by training a separate group of rats to discriminate an efavirenz-induced drug state from saline. Under testing conditions with LSD, animals responded on the lever associated with the training drug (i.e., efavirenz) rather than the saline-associated lever. Second, a separate group of rats were trained to discriminate the subjective drug effect of cocaine, a DA reuptake inhibitor, from saline. When rats were tested with various doses of efavirenz, they primarily responded on the saline-associated lever. Collectively, the pharmacodynamic activity of efavirenz resembles that of the 5-HT receptor agonist LSD.

5.2. Sensitization

Repeated exposure to psychoactive stimulants produces prominent behavioral changes (e.g., amphetamine [283], cocaine [284]). Specifically, following acute treatment with psychostimulants, laboratory animals exhibit hyperactivity. Repeated drug exposure, however, induces a progressive and persistent increase in hyperactive behavior, commonly termed “behavioral sensitization”. Critically, the later stages of behavioral sensitization are accompanied by significant elevations in DA in response to a drug [285,286]. Measurement of locomotion following a drug challenge is the classic approach to evaluating behavioral sensitization.
With regards to efavirenz, there is no compelling evidence for behavioral sensitization. Rather, locomotor activity was suppressed in a dose-dependent (3, 10, 30 mg/kg, IP) manner following repeated administration. Critically, the time-course of the efavirenz-induced suppression for the highest dose (30 mg/kg) was nearly identical to that produced by LSD (3 mg/kg [276]). Furthermore, efavirenz increased head-twitching, a behavioral measure commonly utilized to profile serotonergic-like compounds; an increase that was abolished in 5-HT2A receptor knockout mice [276]. More recently, oral efavirenz (0, 25, 50 mg/kg) failed to produce sensitization or suppression of line-crossings in an open-field test [280]. Similarly, Möller et al. [279] observed no statistically significant effect of efavirenz (5 mg/kg of efavirenz every other day for two weeks) on locomotor activity. Thus, the profile of efavirenz is again consistent with a serotonergic pharmacodynamic.

5.3. Drug Self-Administration

Preclinical drug self-administration procedures, which evaluate DA-related behaviors, became popularized in the 1960s with the advent of reliable, automated methods for intravenous (IV) drug self-administration [287,288]. The utility of preclinical drug self-administration procedures derives from both their face (i.e., animals self-administer addictive substances commonly abused by humans [198,289,290]) and predictive (i.e., successful identification of substance with high abuse liability; for review, see [291]) validity. Various routes of administration (e.g., oral [290], IV [198]) can be utilized in drug self-administration experimental paradigms to accurately model drug self-administration in humans. For IV drug self-administration, rats are implanted with chronic indwelling jugular catheters and are trained to self-administer drugs by pressing a lever within operant conditioning chambers [287,292]. Similar to other reinforcers, dependence-producing drugs readily maintain behavior on various schedules of reinforcement.
To assess the reinforcing properties of efavirenz, animals were trained to self-administer the DA reuptake inhibitor, cocaine. Following stable self-administration behavior, IV cocaine was replaced with incrementally increasing doses of IV efavirenz (1.0, 0.32, 3.2, or 10.0 mg/kg per infusion). However, independent of dose, lever pressing dramatically decreased during tests in which IV efavirenz was the available reinforcer [276]. Thus, efavirenz fails to maintain operant (goal-directed) behavior [276], indicating that it lacks reinforcing properties associated with drugs that release DA throughout the fronto-striatal system [293].

5.4. Conditioned Place Preference

Conditioned place preference (CPP) is a Pavlovian learning procedure that evaluates the rewarding effect of a drug [294]. The CPP procedure repeatedly conditions an animal to two stimuli: a conditional stimulus (CS) and an unconditional stimulus (US). Specifically, one CS (e.g., dark environmental context) is paired with drug treatment (i.e., US). A second CS (e.g., bright environmental context) is paired with no drug treatment. Following conditioning, animals are tested, whereby the rodent can freely move between the drug-paired and non-drug-paired contexts. During testing, a CPP is learned if the animal spends relatively more time in the drug-paired context. Likewise, a conditioned place aversion (CPA) is learned if an animal spends an increased amount of time in the non-drug-paired context. Drugs that produce DA release and maintain self-administration also produce CPP (e.g., cocaine [295]); however, not all drugs that produce CPP are considered dopaminergic drugs [296]. Overall, the CPP experimental paradigm models a Pavlovian conditioning aspect of drug-taking behavior related to incentive salience conditioned to drug-associated stimuli [297].
Mixed findings fail to provide strong support for efavirenz-mediated conditioned reward learning [276,279]. Specifically, under one experimental condition, no dose of efavirenz tested (5–20 mg/kg, IP) produced CPP in rats [276]. On the other hand, dose-dependent changes in behavior, ranging from CPP (5 mg/kg of efavirenz) to CPA (20 mg/kg of efavirenz), were observed [279]. The CPP procedure is not considered an exclusive screen for dopaminergic drugs, as there are serotonin agonists (e.g., LSD, buspirone) that function as an US to produce CPP [294,296,298]. Thus, it is conceivable that the CPP observed by Moller et al. [279] was mediated by efavirenz’s US effects on the serotonergic system [296,298].

5.5. Conclusions

Collectively, there is no compelling evidence that efavirenz binds to DA receptors (D1, D4 human; D2, D3 rat) or alters DA reuptake. Efavirenz does inhibit DA reuptake in human cloned DAT [276] and acutely increases basal DA levels [279,280]. However, highly translational behavioral procedures fail to support DA behaviors. Specifically, rats experience different interoceptive cue states when treated with systemic cocaine and efavirenz, as evidenced within a drug discrimination experimental paradigm. Furthermore, efavirenz fails to induce sensitization [276,279,280] and is not self-administered by rats [276]. The hypodopaminergic tone observed following chronic HIV-1 viral protein exposure in both the pre- and post-cART eras (Table 2 above) adds additional credence to these observations. Efavirenz, however, resembles an LSD-like drug consistent with putative effects on the serotonergic system, effects which may produce adverse psychiatric alterations in HIV-1 seropositive individuals [276]. Thus, if cART contributes negatively to HAND, it is unlikely that it results from direct protein interactions to alter dopamine transmission via VMAT2, DAT, or DA receptors.
Whether efavirenz, or other cART-approved drugs, functionally alter DA release throughout fronto-striatal systems is a fundamental question. However, to date, few experiments have directly examined if and/or how cART drugs alter DA function. In addition to the reviewed studies examining efavirenz, the PIs ritonavir and saquinavir failed to alter DA release in rodent hypothalamic tissue [299]. Although the currently available data fail to support the impact of cART on DA, there remains a critical need for additional studies of individual and combinations of cART drugs.

6. Mechanistic Implications for Low Dopamine Levels

6.1. Homeostatic Conditions

Microglia, which represent 5–20% of adult brain cells [300], belong to the myeloid phagocytic/monocytic lineage [301,302] and serve as resident innate immune cells in the CNS. Morphologically, microglia are characterized by a small soma and slender, highly branched processes [303,304]. In the healthy brain, “resting” microglia utilize their branched processes to continuously survey the environment [303,304]; environmental surveillance which is uniquely targeted to synaptic structures [305,306]. Critically, strong evidence also supports a fundamental relationship between microglia and the dopaminergic system. Based on the available scientific evidence, which is reviewed in detail below, we propose a (potentially) cyclic model highlighting the interrelationships between microglia, the DA system and synaptic function (Figure 4).
First, microglia and the DA system are highly interrelated, whereby microglia are highly prevalent in the basal ganglia nuclei (i.e., NAc, VTA, SN [307,308]) and express functional D1- and D2-like receptors [309,310,311], as well as DAT [312]. Functionally, prominent alterations in microglial morphology [312], enhanced microglial migration [309] and enhanced assembly of vimentin filaments [312] have been observed in “resting” microglia following DA treatment. Microglia are also involved in the wiring of the embryonic forebrain circuit, including dopaminergic axon outgrowth and positioning of neocortical interneurons, a process which is altered in cases of microglial dysfunction (i.e., via cell-depletion or genetic mutants [313]).
Second, microglia’s environmental surveillance is uniquely targeted to synaptic structures, whereby “resting” microglial processes localize with both pre- and post-synaptic structures, including dendritic spines [305,306]. During early brain development, microglia are involved in either the phagocytic [314,315] or trogocytotic [316] elimination of synapses, playing a critical role in synaptic pruning, a regressive event that is vital for neural circuit refinement and maturation. However, absence of either the fractalkine receptor (Cx3cr1 [314,317]) or complement receptor 3 (CR3 [315]) precludes synaptic pruning and results in immature synaptic connectivity. Microglia’s role in synaptic pruning continues through adolescence, whereby microglia transiently engulf dendritic spines in the PFC [318], and into adulthood [319].
In addition to synaptic pruning, microglia play a critical role in synaptic formation during development [316,317,320,321] and adult neurogenesis [322,323,324]. Specifically, microglia–dendrite interactions promote filopodia-like (i.e., immature postsynaptic protrusions that may develop into mature dendritic spines) formation [316,321]. Alterations in the gene expression of Cx3cr1, which lead to a depletion of microglia, however, precluded spine formation [317]. Furthermore, microglia regulate adult neurogenesis via multiple mechanisms, including phagocytosis [322] and the phagocytosis secretome [324], as well as via a nucleotide-mediated mechanism (i.e., ADP receptors P2Y12 and P2Y13 [323,324]) and the TAM family tyrosine kinases [324].
Notably, the dopaminergic system and synaptic structures may also interact with one another in a bidirectional manner. Dopaminergic afferents predominantly establish synaptic contact on the dendritic spine neck [325], and postsynaptic D1 and D2 receptors are localized in perisynaptic sites, supporting the anatomical interrelationship between the DA system and dendritic spines [326]. DA depletion results in prominent structural alterations in medium spiny neurons (MSNs) of the NAc, including decreased dendritic spine density [327,328] and decreased density of asymmetric synaptic contacts [329,330]. Additionally, a preferential loss of ‘thin’ spines, and a corresponding relative increase in ‘stubby’ spines, has also been reported in MSNs of the NAc following DA denervation [328]. Collectively, evidence supports a strong relationship between microglia, dopaminergic system function and synaptic function. To date, however, it is unknown whether the relationships between microglia and synaptic function or microglia and DA system function are bidirectional.

6.2. Disturbances of Brain Homeostasis: HIV-1

Early in the course of infection, HIV-1-infected monocytes migrate across the blood–brain barrier, infiltrating the brain and infecting microglia [331,332]. During HIV-1 infection, increased expression of microglial markers (e.g., CD68, MHC II) in the brain has often been interpreted as microglial activation [333], and more recent evidence supports morphological changes associated with microglial activation (i.e., amoeboid [334]). Additionally, HIV-1 infection likely leads to microglial dysfunction, as evidenced by cellular senescence [335]. Given the strong interrelationships between microglia, the DA system and synaptic function, microglial dysfunction may underlie the hypodopaminergic state (reviewed in Section 3) and synaptic dysfunction [195,336,337] commonly observed following chronic HIV-1 viral protein exposure (Figure 4B).
First, alterations in the relationship between microglia and DA system function have been observed following induction of the HIV-1 viral protein, Tat [338]. Specifically, Tat simultaneously decreased the number of microglia (i.e., Iba1 immunoreactive cells) and the number of dopamine neurons (i.e., tyrosine hydroxylase positive neurons) in the substantia nigra pars compacta, while an impact of HIV-1 Tat induction was not observed in the VTA [338]. Second, microglial activation and/or dysfunction may underlie HIV-1-associated synaptic dysfunction. HIV-1 viral proteins disrupt microglial proteins and receptors (e.g., Cx3cr1 [339], CR3 [340]) that underlie microglia-mediated neurite and pre- and post-synaptic engulfment [314,315,317]. Finally, chronic HIV-1 viral proteins may alter the bidirectional relationship between the dopaminergic system and synaptic structures. Specifically, in MSNs of the NAc, DA denervation induces a preferential loss of ‘thin’ spines, and a corresponding relative increase in ‘stubby’ spines [328], morphological changes which are consistent with the prominent shift towards ‘stubby’ spines reported following chronic HIV-1 viral protein exposure [337,341]. Thus, we posit that the activation and/or dysfunction of microglia underlies the prominent synaptic and dopaminergic system dysfunction observed in HIV in the post-cART era. Future studies directly investigating how these interrelationships are altered following chronic HIV-1 viral protein exposure have the potential to enhance our understanding of the neural mechanisms underlying HAND and identify novel targets for therapeutic development.

7. Conclusions

  • Dopamine values are dependent upon not only brain region, but also experimental approach (i.e., HPLC, microdialysis, or FSCV). Substantial variability in basal dopamine values may reflect differences in experimental parameters, and innovative genetic fluorescent probes may be a future direction for assessing dopamine signaling.
  • Results overwhelmingly support decreased dopamine concentrations following chronic HIV-1 viral protein exposure in either HIV-1 seropositive humans or biological systems utilized to model HIV-1. Therefore, future therapeutic approaches and models for the neurological complications of HIV-1 need to focus on rectifying decreased dopamine levels.
  • The clinical symptoms, including cognitive impairments and apathetic behaviors, reflect persistent dopamine deficits in HIV-1 seropositive individuals. There is no clinical evidence supporting increased dopamine following chronic HIV-1 infections.
  • To date, there is no compelling evidence that cART has any direct pharmacological action on the dopaminergic system—dopamine deficits persist in the current era of HIV-1 therapeutics.
  • HIV-1 infection likely leads to microglial dysfunction, which may have mechanistic implications for a chronic bidirectional interaction between low dopamine levels and synaptic dysfunction, implicated as neural mechanisms of HAND.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/cells10082158/s1, Table S1: Basal Dopamine (DA) values reported by individual manuscript.

Author Contributions

K.A.M., M.H., and V.M. contributed equally to the review. All authors contributed to the manuscript and have read and agreed to the published version of the manuscript.

Funding

This work was supported in part by National Institutes of Health (NIH) grants HD043680, MH106392, DA013137 and NS100624.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All relevant data are within the manuscript.

Acknowledgments

We are indebted to all lab members and colleagues who, over the years, have contributed with their work in the field of dopamine research to shape the HIV-1 model presented. We are particularly grateful to Adarsh Kumar, who pioneered the field of dopamine and HAND, and was an inspiration to all. Additionally, we would like to acknowledge the contributions of Hailong Li for establishing the GRABDA sensors in our laboratory.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Snider, W.D.; Simpson, D.M. Neurological complications of acquired immune deficiency syndrome: Analysis of 50 patients. Ann. Neurol. 1983, 14, 403–418. [Google Scholar] [CrossRef] [PubMed]
  2. Belman, A.L.; Ultmann, M.H. Neurological complications in infants and children with acquired immune deficiency syndrome. Ann. Neurol. 1985, 18, 560–566. [Google Scholar] [CrossRef]
  3. Navia, B.A.; Jordan, B.D. The AIDS dementia complex: I. Clinical features. Ann. Neurol. 1986, 19, 517–524. [Google Scholar] [CrossRef] [PubMed]
  4. Barré-Sinoussi, F.; Chermann, J.C. Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immune deficiency syndrome (AIDS). Science 1983, 220, 868–871. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Gallo, R.C.; Salahuddin, S.Z. Frequent detection and isolation of cytopathic retroviruses (HTLV-III) from patients with AIDS and at risk for AIDS. Science 1984, 224, 500–503. [Google Scholar] [CrossRef]
  6. Resnick, L.; Berger, J.R. Early penetration of the blood-brain-barrier by HIV. Neurology 1988, 38. [Google Scholar] [CrossRef]
  7. Shaw, G.M.; Harper, M.E. HTLV-III infection in brains of children and adults with AIDS encephalopathy. Science 1985, 227, 177–182. [Google Scholar] [CrossRef]
  8. Ho, D.D.; Rota, T.R. Isolation of HTLV-III from cerebrospinal fluid and neural tissues of patients with neurologic syndromes related to the acquired immunodeficiency syndrome. N. Engl. J. Med. 1985, 313, 1493–1497. [Google Scholar] [CrossRef]
  9. Levy, J.A.; Shimabukuro, J. Isolations of AIDS-associated retroviruses from cerebrospinal fluid and brain of patients with neurological symptoms. Lancet 1985, 2, 586–588. [Google Scholar] [CrossRef]
  10. Navia, B.A.; Price, R.W. The acquired immunodeficiency syndrome dementia complex as the presenting or sole manifestation of human immunodeficiency virus infection. Arch. Neurol. 1987, 44, 65–69. [Google Scholar] [CrossRef] [PubMed]
  11. Tross, S.; Price, R.W. Neuropsychological characterization of the AIDS dementia complex: A preliminary report. AIDS 1988, 2, 81–88. [Google Scholar] [CrossRef]
  12. Navia, B.A.; Cho, E.S. The AIDS dementia complex: II. Neuropathology. Ann. Neurol. 1986, 19, 525–535. [Google Scholar] [CrossRef] [PubMed]
  13. Kieburtz, K.D.; Epstein, L.G. Excitotoxicity and dopaminergic dysfunction in the acquired immunodeficiency syndrome dementia complex. Therapeutic implications. Arch. Neurol. 1991, 48, 1281–1284. [Google Scholar] [CrossRef] [PubMed]
  14. Berger, J.R.; Kumar, M. Cerebrospinal fluid dopamine in HIV-1 infection. AIDS 1994, 8, 67–71. [Google Scholar] [CrossRef]
  15. Sardar, A.M.; Czudek, C. Dopamine deficits in the brain: The neurochemical basis of parkinsonian symptoms in AIDS. Neuroreport 1996, 7, 910–912. [Google Scholar] [CrossRef]
  16. Larsson, M.; Hagberg, L. Cerebrospinal fluid catecholamine metabolites in HIV-infected patients. J. Neursci. Res. 1991, 28, 406–409. [Google Scholar] [CrossRef] [PubMed]
  17. Di Rocco, A.; Bottiglieri, T. Decreased homovanilic acid in cerebrospinal fluid correlates with impaired neuropsychologic function in HIV-1-infected patients. Clin. Neuropharmacol. 2000, 23, 190–194. [Google Scholar] [CrossRef]
  18. Silvers, J.M.; Aksenov, M.Y. Dopaminergic marker proteins in the substantia nigra of human immunodeficiency virus type 1-infected brains. J. Neurovirol. 2006, 12, 140–145. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Mitsuya, H.; Weinhold, K.J. 3′-Azido-3′-deoxythymidine (BW A509U): An antiviral agent that inhibits the infectivity and cytopathic effect of human T-lymphotropic virus type III/lymphadenopathy-associated virus in vitro. Proc. Natl. Acad. Sci. USA 1985, 82, 7096–7100. [Google Scholar] [CrossRef] [Green Version]
  20. Schmitt, F.A.; Bigley, J.W. Neuropsychological outcome of zidovudine (AZT) treatment of patients with AIDS and AIDS-related complex. N. Engl. J. Med. 1988, 319, 1573–1578. [Google Scholar] [CrossRef]
  21. Portegies, P.; de Gans, J. Declining incidence of AIDS dementia complex after introduction of zidovudine treatment. BMJ 1989, 299, 819–821. [Google Scholar] [CrossRef] [Green Version]
  22. Sidtis, J.J.; Gatsonis, C. Zidovudine treatment of the AIDS dementia complex: Results of a placebo-controlled trial. AIDS Clinical Trials Group. Ann. Neurol. 1993, 33, 343–349. [Google Scholar] [CrossRef]
  23. Saylor, D.; Dickiens, A.M. HIV-associated neurocognitive disorder—pathogenesis and prospects for treatment. Nat. Rev. Neurol. 2016, 12, 234–248. [Google Scholar] [CrossRef] [PubMed]
  24. Letendre, S.L.; Ellis, R.J. Neurologic complications of HIV disease and their treatment. Top HIV Med. 2010, 18, 45–55. [Google Scholar]
  25. McArthur, J.C.; Steiner, J. Human immunodeficiency virus-associated neurocognitive disorders: Mind the gap. Ann. Neurol. 2010, 67, 699–714. [Google Scholar] [PubMed]
  26. Heaton, R.K.; Franklin, D.R. HIV-associated neurocognitive disorders before and during the era of combination antiretroviral therapy: Differences in rates, nature, and predictors. J. Neurovirol. 2011, 17, 3–16. [Google Scholar] [CrossRef] [Green Version]
  27. Kamat, R.; Woods, S.P. Implications of apathy for everyday functioning outcomes in persons living with HIV infection. Arch. Clin. Neuropsychol. 2012, 27, 520–531. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Kumar, A.M.; Fernandez, J.B. Human immunodeficiency virus type 1 in the central nervous system leads to decreased dopamine in different regions of postmortem human brains. J. Neurovirol. 2009, 15, 257–274. [Google Scholar] [CrossRef]
  29. Kumar, A.M.; Ownby, R.L. Human immunodeficiency virus infection in the CNS and decreased dopamine availability: Relationship with neuropsychological performance. J. Neurovirol. 2011, 17, 26–40. [Google Scholar] [CrossRef] [PubMed]
  30. Denton, A.R.; Samaranayake, S.A. Selective monoaminergic and histaminergic circuit dysregulation following long-term HIV-1 protein exposure. J. Neurovirol. 2019, 25, 540–550. [Google Scholar] [CrossRef] [PubMed]
  31. Global HIV & AIDS Statistics—Fact Sheet. Available online: https://www.unaids.org/en/resources/fact-sheet (accessed on 4 July 2021).
  32. Blaschko, H. Metabolism and storage of biogenic amines. Experientia 1957, 13, 9–12. [Google Scholar] [CrossRef] [PubMed]
  33. Montagu, K.A. Catechol compounds in rat tissues and in brains of different animals. Nature 1957, 180, 244–245. [Google Scholar] [CrossRef]
  34. Carlsson, A.; Lindqvist, M. On the presence of 3-hydroxytyramine in brain. Science 1958, 127, 471. [Google Scholar] [CrossRef]
  35. Bertler, A.; Rosengren, E. Occurrence and distribution of dopamine in brain and other tisuses. Experientia 1959, 15, 10–11. [Google Scholar] [CrossRef]
  36. Marsden, C. Dopamine: The rewarding years. Br. J. Pharmacol. 2006, 147, S136–S144. [Google Scholar] [CrossRef]
  37. Egenrieder, L.; Mitricheva, E. No basal or drug-induced sex differences in striatal dopaminergic levels: A cluster and meta-analysis of rat microdialysis studies. J. Neurochem. 2020, 152, 482–492. [Google Scholar] [CrossRef]
  38. Liu, C.; Goel, P. Spatial and temporal scales of dopamine transmission. Nat. Rev. Neurosci. 2021, 22, 345–358. [Google Scholar] [CrossRef]
  39. Elchisak, M.A.; Cosgrove, S.E. Distribution of free and conjugated dopamine in monkey brain, peripheral tissues and cerebrospinal fluid determined by high-performance liquid chromatography. Brain Res. 1983, 279, 171–176. [Google Scholar] [CrossRef]
  40. Bradbury, A.J.; Costall, B. Laterality of dopamine function and neuroleptic action in the amygdala in the rat. Neuropharmacology 1985, 24, 1163–1170. [Google Scholar] [CrossRef]
  41. Ebinger, G.; Bruyland, M. Distribution of biogenic amines and their catabolites in brains from patients with Alzheimer’s disease. J. Neurol. Sci. 1987, 77, 267–283. [Google Scholar] [CrossRef]
  42. Carvalho, M.C.; Albrechet-Souza, L. Changes in biogenic amine content of the prefrontal cortex, amygdala, dorsal hippocampus, and nucleus accumbens of rats submitted to single and repeated sessions of the elevated plus-maze test. Braz. J. Med. Biol. Res. 2005, 38, 1857–1866. [Google Scholar] [CrossRef] [Green Version]
  43. Fadok, J.P.; Darvas, M. Long-term memory for pavlovian fear conditioning requires dopamine in the nucleus accumbens and basolateral amygdala. PLoS ONE. 2010, 5, e12751. [Google Scholar] [CrossRef]
  44. Inglis, F.M.; Moghaddam, B. Dopaminergic innervation of the amygdala is highly responsive to stress. J. Neurochem. 1999, 72, 1088–1094. [Google Scholar] [CrossRef]
  45. Weiss, F.; Maldonado-Vlaar, C.S. Control of cocaine-seeking behavior by drug-associated stimuli in rats: Effects on recovery of extinguished operant-responding and extracellular dopamine levels in amygdala and nucleus accumbens. Proc. Natl. Acad. Sci. USA 2000, 97, 4321–4326. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Tor-Agbidye, J.; Yamamoto, B. Seizure activity and hyperthermia potentiate the increases in dopamine and serotonin extracellular levels in the amygdala during exposure to d-amphetamine. Toxicol. Sci. 2001, 60, 103–111. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Adachi, S.; Endo, Y. Increased levels of extracellular dopamine in the nucleus accumbens and amygdala of rats by ingeting a low concentration of a long-chain Fatty Acity. Biosci. Biotechnol. Biochem. 2013, 77, 2175–2180. [Google Scholar] [CrossRef] [Green Version]
  48. Juorio, A.V.; Chedrese, P.J. The concentration of dopamine and related monoamines in arteries and some other tissues of the sheep. Comp. Biochem. Phsyiol. C Comp. Pharmacol. Toxicol. 1990, 95, 35–37. [Google Scholar] [CrossRef]
  49. Davis, D.G.; Sparks, D.L. Dopaminergic and serotonergic neurotransmitters in bone marrow transplant patients. J. Neurol. Sci. 1995, 130, 95–103. [Google Scholar] [CrossRef]
  50. Wilson, J.M.; Levey, A.I. Differential changes in neurochemical markers of striatal dopamine nerve terminals in idiopathic Parkinson’s disease. Neurology 1996, 47, 718–726. [Google Scholar] [CrossRef]
  51. Mushoff, F.; Schmidt, P. Determination of dopamine and dopamine-derived (R)-/(S)-salsolinol and norsalsolinol in various human brain areas using solid-phase extraction and gas chromatography/mass spectrometry. Forensic Sci. Int. 2000, 113, 359–366. [Google Scholar] [CrossRef]
  52. Elsworth, J.D.; Jentsch, J.D. Cozapine normalizes prefrontal cortex dopamine transmission in monkeys subchronically expoed to phencyclidine. Neuropsychopharmacology 2008, 33, 491–496. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Rajput, A.H.; Sitte, H.H. Globus pallidus dopamine and Parkinson motor subtypes: Clinical and brain biochemical correlation. Neurology 2008, 70, 1403–1410. [Google Scholar] [CrossRef]
  54. Goldstein, D.S.; Sullivan, P. Catechols in post-mortem brain of patients with Parkinson disease. Eur. J. Neurol. 2011, 18, 703–710. [Google Scholar] [CrossRef]
  55. Robinson, T.E.; Camp, D.M. Does amphetamine preferentially increase the extracellular concentration of dopamine in the mesolimbic system of freely moving rats? Neuropsychopharmacology 1990, 3, 163–173. [Google Scholar]
  56. Bosse, K.E.; Mathews, T.A. Ethanol-induced increases in extracellular dopamine are blunted in brain-derived neurotrophic factor heterozygous mice. Neurosci. Lett. 2011, 489, 172–176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Lucas, L.A.C.; McMillen, B.A. Differences in brain area concentrations of dopamine and serotonin in Myers’ High Ethanol Preferring (mHEP) and outbred rats. J. Neural Transm. 2002, 109, 279–292. [Google Scholar] [CrossRef] [PubMed]
  58. Wisman, L.A.B.; Sahin, G. Functional convergence of dopaminergic and cholinergic input is critical for hippocampus-dependent working memory. J. Neurosci. 2008, 28, 7797–7807. [Google Scholar] [CrossRef]
  59. Bromek, E.; Haduch, A. Cytochrome P450 mediates dopamine formation in the brain in vivo. J. Neurochem. 2011, 118, 806–815. [Google Scholar] [CrossRef] [PubMed]
  60. Choi, D.L.; Davis, J.F. Orexin signaling in the paraventricular thalamic nucleus modulates mesolimbic dopamine and hedonic feeding in the rat. Neuroscience 2012, 210, 243–248. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Hu, L.; Yang, J. A new stress model, a scream sound, alters learning and monoamine levels in rat brain. Physiol. Behav. 2014, 123, 105–113. [Google Scholar] [CrossRef]
  62. Rysz, M.; Bromek, E. Damage to the brain serotonergic system increases the expression of liver cytochrome P450. Drug Metab. Dispos. 2015, 43, 1345–1352. [Google Scholar] [CrossRef] [Green Version]
  63. Moghaddam, B.; Bunney, B.S. Ionic composition of microdialysis perfusion solution alters the pharmacological responsiveness and basal outflow of striatal dopamine. J. Neurochem. 1989, 53, 652–654. [Google Scholar] [CrossRef]
  64. Maisonneuve, I.M.; Keller, R.W. Interactions between ibogaine, a potential anti-addictive agent, and morphine: An in vivo microdialysis study. Eur. J. Pharmacol. 1991, 199, 35–42. [Google Scholar] [CrossRef]
  65. Shoblock, J.R.; Sullivan, E.B. Neurochemical and behavioral differences between d-methamphetamine and d-amphetamine in rats. Psychopharmacology 2003, 165, 359–369. [Google Scholar] [CrossRef]
  66. Salvatore, M.F.; Pruett, B.S. Comprehensive profiling of dopamine regulation in substantia nigra and ventral tegmental area. J. Vis. Exp. 2012, 66, e4171. [Google Scholar] [CrossRef] [PubMed]
  67. Winner, B.M.; Zhang, H. Metabolism of dopamine in nucleus accumbens astrocytes is preserved in aged mice exposed to MPTP. Front. Aging Neurosci. 2017, 9, 410. [Google Scholar] [CrossRef] [Green Version]
  68. Bergamini, G.; Mechtersheimer, J. Chronic social stress induces peripheral and central immune activation, blunted mesolimbic dopamine function, and reduced reward-directed behaviour in mice. Neurobiol. Stress 2018, 8, 42–56. [Google Scholar] [CrossRef]
  69. Hernandez, L.; Hoebel, B.G. Food reward and cocaine increase extracellular dopamine in the nucleus accumbens as measured by microdialysis. Life Sci. 1988, 42, 1705–1712. [Google Scholar] [CrossRef]
  70. Pettit, H.O.; Pan, H.T. Extracellular concentrations of cocaine and dopamine are enhanced during chronic cocaine administration. J. Neurochem. 1990, 55, 798–804. [Google Scholar] [CrossRef] [PubMed]
  71. Pothos, E.; Rada, P. Dopamine microdialysis in the nucleus accumbens during acute and chronic morphine, naloxone-precipitated withdrawal and clonidine treatment. Brain Res. 1991, 566, 348–350. [Google Scholar] [CrossRef]
  72. Parsons, L.H.; Justice, J.B. Extracellular concentration and in vivo recovery of dopamine in the nucleus accumbens using microdialysis. J. Neurochem. 1992, 58, 212–218. [Google Scholar] [CrossRef]
  73. Maisonneuve, I.M.; Glick, S.D. Interactions between ibogaine and cocaine in rats: In vivo microdialysis and motor behavior. Eur. J. Pharmacol. 1992, 212, 263–266. [Google Scholar] [CrossRef]
  74. Chapman, M.A.; See, R.E. Neurotensin increases extracellular striatal dopamine levels in vivo. Neuropeptides 1992, 22, 175–183. [Google Scholar] [CrossRef]
  75. Chen, J.; Marmur, R. Ventral tegmental microinjection of delta 9-tetrahydrocannabinol enhances ventral tegmental somatodendritic dopamine levels but not forebrain dopamine levels: Evidence for local neural action by marijuana’s psychoactive ingredient. Brain Res. 1993, 621, 65–70. [Google Scholar] [CrossRef]
  76. Blanchard, B.A.; Steindorf, S. Sex differences in ethanol-induced dopamine release in nucleus accumbens and in ethanol consumption in rats. Alcohol. Clin. Exp. Res. 1993, 17, 968–973. [Google Scholar] [CrossRef] [PubMed]
  77. Anagnostakis, Y.; Spyraki, C. Effect of morphine applied by intrapallidal microdialysis on the release of dopamine in the nucleus accumbens. Brain Res. Bull. 1994, 34, 275–282. [Google Scholar] [CrossRef]
  78. Hemby, S.E.; Martin, T.J. The effects of intravenous heroin administration on extracellular nucleus accumbens dopamine concentrations as determined by in vivo microdialysis. J. Pharmacol. Exp. Ther. 1995, 273, 591–598. [Google Scholar] [PubMed]
  79. Blanchard, B.A.; Glick, S.D. Sex differences in mesolimbic dopamine responses to ethanol and relationship to ethanol intake in rats. Recent Dev. Alcohol. 1995, 12, 231–241. [Google Scholar] [PubMed]
  80. Campbell, A.D.; McBride, W.J. Serotonin-3 receptor and ethanol-stimulated dopamine release in the nucleus accumbens. Pharmacol. Biochem. Behav. 1995, 51, 835–842. [Google Scholar] [CrossRef]
  81. Weiss, F.; Parsons, L.H. Ethanol self-administration restores withdrawal-associated deficiencies in accumbal dopamine and 5-hydroxytryptamine release in dependent rats. J. Neurosci. 1996, 16, 3474–3485. [Google Scholar] [CrossRef] [Green Version]
  82. Pearl, S.M.; Maisonneuve, I.M. Prior morphine exposure enhances ibogaine antagonism of morphine-induced dopamine release in rats. Neuropharmacology 1996, 35, 1779–1784. [Google Scholar] [CrossRef]
  83. Kohl, R.R.; Katner, J.S. Ethanol and negative feedback regulation of mesolimbic dopamine release in rats. Psychopharmacology 1998, 139, 79–85. [Google Scholar] [CrossRef]
  84. Yan, Q.S. Extracellular dopamine and serotonin after ethanol monitored with 5-minute microdialysis. Alcohol 1999, 19, 1–7. [Google Scholar] [CrossRef]
  85. Maisonneuve, I.M.; Glick, S.D. Attenuation of the reinforcing efficacy of morphine by 18-methoxycoronaridine. Eur. J. Pharmacol. 1999, 383, 15–21. [Google Scholar] [CrossRef]
  86. Yim, H.J.; Gonzales, R.A. Ethanol-induced increases in dopamine extracellular concentration in rat nucleus accumbens are accounted for by increased release and not uptake inhibition. Alcohol 2000, 22, 107–115. [Google Scholar] [CrossRef]
  87. Szumlinski, K.K.; McCafferty, C.A. Interactions between 18-methoxycoronaridine (18-MC) and cocaine: Dissociation of behavioural and neurochemical sensitization. Brain Res. 2000, 871, 245–248. [Google Scholar] [CrossRef]
  88. Szumlinski, K.K.; Maisonneuve, I.M. The potential anti-addictive agent, 18-methoxycoronaridine, blocks the sensitized locomotor and dopamine responses produced by repeated morphine treatment. Brain Res. 2000, 864, 13–23. [Google Scholar] [CrossRef]
  89. Johnson, D.W.; Eodice, P. Decreased accumbens dopamine release after cocaine challenge in behaviorally sensitized female rats. Pharmacol. Biochem. Behav. 2000, 65, 659–664. [Google Scholar] [CrossRef]
  90. Fadda, P.; Scherma, M. Baclofen antagonizes nicotine-, cocaine-, and morphine-induced dopamine release in the nucleus accumbens of rat. Synapse 2003, 50. [Google Scholar] [CrossRef] [PubMed]
  91. Steinmiller, C.L.; Maisonneuve, I.M. Effects of dextromethorphan on dopamine release in the nucleus accumbnes: Interactions with morphine. Pharmacol. Biochem. Behav. 2003, 74, 803–810. [Google Scholar] [CrossRef]
  92. Kosten, T.A.; Zhang, X.Y. Chronic neonatal isolation stress enhances cocaine-induced increases in ventral striatal dopamine levels in rat pups. Brain Res. Dev. Brain Res. 2003, 141, 109–116. [Google Scholar] [CrossRef]
  93. Smith, J.E.; Co, C. Self-administered heroin and cocaine combinations in the rat: Additive reinforcing effects-supra-additive effects on nucleus accumbens extracellular dopamine. Neuropsychopharmacology 2006, 31, 139–150. [Google Scholar] [CrossRef] [PubMed]
  94. Geiger, B.M.; Haburcak, M. Deficits of mesolimbic dopamine neurotransmission in rat dietary obesity. Neuroscience 2009, 159, 1193–1199. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Borgkvist, A.; Malmlöf, T. Dopamine in the hippocampus is cleared by the norepinephrine transporter. Int. J. Neuropsychopharmacol. 2012, 15, 531–540. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. McCallum, S.E.; Cowe, M.A. α3β4 nicotinic acetylcholine receptors in the medial habenula modulate the mesolimbic dopaminergic response to acute nicotine in vivo. Neuropharmacology 2012, 63, 434–440. [Google Scholar] [CrossRef] [Green Version]
  97. Grotewold, S.K.; Wall, V.L. Effects of cocaine combined with a social cue on conditioned place preference and nucleus accumbens monoamines after isolation rearing in rats. Psychopharmacology 2014, 231, 3041–3053. [Google Scholar] [CrossRef] [Green Version]
  98. Cummings, J.A.; Jagannathan, L. Sex differences in the effects of estradiol in the nucleus accumbens and striatum on the response to cocaine: Neurochemistry and behavior. Drug Alcohol Depend. 2014, 135, 22–28. [Google Scholar] [CrossRef] [Green Version]
  99. Eggan, B.L.; McCallum, S.E. 18-Methoxycoronaridine acts in the medial habenula to attenuate behavioral and neurochemical sensitization to nicotine. Behav. Brain Res. 2016, 307, 186–193. [Google Scholar] [CrossRef] [PubMed]
  100. Roitman, M.F.; Wheeler, R.A. Real-time chemical responses in the nucleus accumbens differentiate rewarding and aversive stimuli. Nat. Neurosci. 2008, 11, 1376–1377. [Google Scholar] [CrossRef]
  101. Owesson-White, C.A.; Roitman, M.F. Sources contributing to the average extracellular concentration of dopamine in the nucleus accumbens. J. Neurochem. 2012, 121, 252–262. [Google Scholar] [CrossRef]
  102. Dreyer, J.K.; Vander Weele, C.M. Functionally distinct dopamine signals in nucleus accumbens core and shell in the freely moving rat. J. Neurosci. 2016, 36, 98–112. [Google Scholar] [CrossRef]
  103. Atcherley, C.W.; Wood, K.M. The coaction of tonic and phasic dopamine dynamics. Chem. Commun. 2015, 51, 2235–2238. [Google Scholar] [CrossRef] [Green Version]
  104. Johnson, J.A.; Rodeberg, N.T. Measurement of basal neurotransmitter levels using convolution-based nonfaradaic current removal. Anal. Chem. 2018, 90, 7181–7189. [Google Scholar] [CrossRef] [PubMed]
  105. Kita, T.; Matsunari, Y. Methamphetamine-induced striatal dopamine release, behavior changes and neurotoxicity in BALB/c mice. Int. J. Dev. Neurosci. 2000, 18, 521–530. [Google Scholar] [CrossRef]
  106. Bałkowiec-Iskra, E.; Kurkowska-Jastrzebska, I. MPTP-induced central dopamine depletion exacerbates experimental autoimmune encephalomyelitis (EAE) in C57BL mice. Inflamm. Res. 2007, 56, 311–317. [Google Scholar] [CrossRef]
  107. Petzinger, G.M.; Walsh, J.P. Effects of treadmill exercise on dopaminergic transmission in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-lesioned mouse model of basal ganglia injury. J. Neurosci. 2007, 27, 5291–5300. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Swiercz, R.; Grzelińska, Z. Catecholamine levels in the brain of rats exposed by inhalation to benzalkonium chloride. Int. J. Occup. Med. Environ. Health 2009, 22, 107–113. [Google Scholar] [CrossRef] [Green Version]
  109. Villar-Cheda, B.; Dominguez-Meijide, A. Aging-related dysregulation of dopamine and angiotensin receptor interaction. Neurobiol. Aging 2014, 35, 1726–1738. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Nikishina, Y.O.; Sapronova, A.Y. The effect of dopamine secreted by the brain into the systemic circulation on prolactin synthesis by the pituitary gland in ontogenesis. Acta Naturae 2016, 8, 111–117. [Google Scholar] [CrossRef]
  111. Garrido-Gil, P.; Rodriguez-Perez, A.I. Bidirectional neural interaction between central dopaminergic and gut lesions in Parkinson’s disease models. Mol. Neurobiol. 2018, 55, 7297–7316. [Google Scholar] [CrossRef]
  112. Bradberry, C.W. Acute and chronic dopamine dynamics in a nonhuman primate model of recreational cocaine use. J. Neurosci. 2000, 20, 7109–7115. [Google Scholar] [CrossRef] [Green Version]
  113. Shou, M.; Ferrario, C.R. Monitoring dopamine in vivo by microdialysis sampling and on-line CE-laser-induced fluorescence. Anal. Chem. 2006, 78, 6717–6725. [Google Scholar] [CrossRef]
  114. Zhang, Y.; Picetti, R. Behavioral and neurochemical changes induced by oxycodone differ between adolescent and adult mice. Neuropsychopharmacology 2009, 34, 912–922. [Google Scholar] [CrossRef] [PubMed]
  115. James, A.T.; Martin, A.J.P. Gas-liquid partition chromatography: The separation and micro-estimation of volatile fatty acids from formic acid to dodecanoic acid. Biochem. J. 1952, 50, 679–690. [Google Scholar] [CrossRef] [PubMed]
  116. Huber, J.F.; Hulsman, J.A. A study of liquid chromatography in columns. The time of separation. Anal. Chim. Acta 1967, 38, 305–313. [Google Scholar] [CrossRef]
  117. JOVE Science Education Database. High-performance liquid chromatography (HPLC). In Analytical Chemistry; JOVE: Cambridge, MA, USA, 2021. [Google Scholar]
  118. Sasa, S.; Blank, C.L. Determination of serotonin and dopamine in mouse brain tissue by high performance liquid chromatography with electrochemical detection. Anal. Chem. 1977, 49, 354–359. [Google Scholar] [CrossRef]
  119. Barwick, V.J. Sources of uncertainty in gas chromatography and high-performance liquid chromatography. J. Chromatogr. A 1999, 849, 13–33. [Google Scholar] [CrossRef]
  120. Knox, J.H.; Jurand, J. Separation of catecholamines and their metabolites by adsorption, ion-pair and soap chromatography. J. Chromatogr. A 1976, 125, 89–101. [Google Scholar] [CrossRef]
  121. Magnusson, O.; Nilsson, L.B. Simultaneous determination of dopamine, DOPAC and homovanillic acid. Direct injection of supernatants from brain tissue homogenates in a liquid chromatography—Electochemical detection system. J. Chromatogr. B Biomed. Sci. Appl. 1980, 221, 237–247. [Google Scholar] [CrossRef]
  122. Kilts, C.D.; Breese, G.R. Simultaneous quantification of dopamine, 5-hydroxytryptamine and four metabolically related compounds by means of reversed-phase high-performance liquid chromatography with electrochemical detection. J. Chromatogr. B Biomed. Sci. Appl. 1981, 225, 347–357. [Google Scholar] [CrossRef]
  123. Kontur, P.; Dawson, R. Manipulation of mobile phase parameters for the HPLC separation of endogenous monoamines in rat brain tissue. J. Neurosci. Methods 1984, 11, 5–18. [Google Scholar] [CrossRef]
  124. Bartlett, W.A. Effects of mobile phase composition on the chromatographic and electrochemical behaviour of catecholamines and selected metabolites; Reversed-phase ion-paired high-performance liquid chromatography using multiple-electrode detection. J. Chromatogr. B Biomed. Sci. Appl. 1989, 493, 1–14. [Google Scholar] [CrossRef]
  125. Rossetti, Z.L.; Mercuro, G. A study of the parameters affecting flow gradient analysis of catecholamines, DOPA and DOPAC by ion pair liquid chromatography with electrochemical detection. Life Sci. 1983, 33, 2387–2397. [Google Scholar] [CrossRef]
  126. Ungerstedt, U.; Pycock, C. Functional correlates of dopamine neurotransmission. Bull. Schweiz. Akad. Med. Wiss. 1974, 30, 44–55. [Google Scholar] [PubMed]
  127. Ungerstedt, U.; Herrera-Marschitz, M. Dopamine synaptic mechanisms reflected in studies combining behavioural recordings and brain dialysis. In Advances in Dopamine Research, 1st ed.; Kohsaka, M., Shohmori, T., Eds.; Pergamon Press: Oxford, UK, 1982; pp. 219–231. [Google Scholar]
  128. Imperato, A.; Di Chiara, G. Trans-striatal dialysis coupled to reverse phase high performance liquid chromatography with electrochemical detection: A new method for the study of the in vivo release of endogenous dopamine and metabolites. J. Neurosci. 1984, 4, 966–977. [Google Scholar] [CrossRef] [PubMed]
  129. Chefer, V.I.; Thompson, A.C. Overview of brain microdialysis. Curr. Protoc. Neurosci. 2009, 7. [Google Scholar] [CrossRef] [Green Version]
  130. Peters, A.; Palay, S.L. The Fine Structure of the Nervous System: The Neurons and Supporting Cells, 3rd ed.; Oxford University Press: New York, NY, USA, 1991. [Google Scholar]
  131. Mitala, C.M.; Wang, Y. Impact of microdialysis probes on vasculature and dopamine in the rat striatum: A combined fluorescence and voltammetric study. J. Neurosci. Methods 2008, 174, 177–185. [Google Scholar] [CrossRef] [Green Version]
  132. Jaquins-Gerstl, A.; Michael, A.C. Comparison of the brain penetration injury associated with microdialysis and voltammetry. J. Neurosci. Methods 2009, 183, 127–135. [Google Scholar] [CrossRef] [Green Version]
  133. Morgan, M.E.; Singhal, D. Quantitative assessment of blood-brain barrier damage during microdialysis. J. Pharmacol. Exp. Ther. 1996, 277, 1167–1176. [Google Scholar]
  134. Clapp-Lilly, K.L.; Roberts, R.C. An ultrastructural analysis of tissue surrounding a microdialysis probe. J. Neurosci. Methods 1999, 90, 129–142. [Google Scholar] [CrossRef]
  135. Holson, R.R.; Gazzara, R.A. Declines in stimulated striatal dopamine release over the first 32 h following microdialysis probe insertion: Generalization across releasing mechanisms. Brain Res. 1998, 808, 182–189. [Google Scholar] [CrossRef]
  136. Borland, L.M.; Shi, G. Voltammetric study of extracellular dopamine near microdialysis probes acutely implanted in the striatum of the anesthetized rat. J. Neurosci. Methods 2005, 146, 149–158. [Google Scholar] [CrossRef]
  137. Yang, H.; Michael, A.C. In vivo fast-scan cyclic voltammetry of dopamine near microdialysis probes. In Electrochemical Methods for Neuroscience; Michael, A.C., Borland, L.M., Eds.; CRC Press/Taylor & Francis: Boca Raton, FL, USA, 2007; Chapter 22. [Google Scholar]
  138. Nesbitt, K.M.; Jaquins-Gerstl, A. Pharmacological mitigation of tissue damage during brain microdialysis. Anal. Chem. 2013, 85, 8173–8179. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  139. Nesbitt, K.M.; Varner, E.L. Microdialysis in the rat striatum: Effects of 24 h dexamethasone retrodialysis on evoked dopamine release and penetration injury. ACS Chem. Neurosci. 2015, 6, 163–173. [Google Scholar] [CrossRef] [Green Version]
  140. Lee, W.H.; Ngernsutivorakul, T. Microfabrication and in vivo performance of a microdialysis probe with embedded membrane. Anal. Chem. 2016, 88, 1230–1237. [Google Scholar] [CrossRef] [Green Version]
  141. Chen, N.H.; Lai, Y.J. Effects of different perfusion medium on the extracellular basal concentration of dopamine in striatum and medial prefrontal cortex: A zero-net flux microdialysis study. Neurosci. Lett. 1997, 225, 197–200. [Google Scholar] [CrossRef]
  142. Osborne, P.G.; O’Connor, W.T. Effect of varying the ionic concentration of a microdialysis perfusate on basal striatal dopamine levels in awake rats. J. Neurochem. 1991, 56, 452–456. [Google Scholar] [CrossRef] [PubMed]
  143. Krebs-Kraft, D.L.; Frantz, K.J. In Vivo Microdialysis: A Method for Sampling Extracellular Fluid in Discrete Brain Regions. In Handbook of Neurochemistry and Molecular Neurobiology; Lajtha, A., Baker, G., Eds.; Springer: Boston, MA, USA, 2007; pp. 219–256. [Google Scholar]
  144. Vulto, A.G.; Sharp, T. Rapid postmortem increase in extracellular dopamine in the rat brain as assessed by brain microdialysis. J. Neurochem. 1988, 51, 746–749. [Google Scholar] [CrossRef] [PubMed]
  145. Gonzalez-Mora, J.L.; Miadment, N.T. Post-mortem dopamine dynamics assessed by voltammetry and microdialysis. Brain Res. Bull. 1989, 23, 323–327. [Google Scholar] [CrossRef]
  146. Takahashi, A.; Ikarashi, Y. Dopamine output upon death reflects intraneuronal aspects while alive: Accumulation of releasable dopamine during tetrodotoxin perfusion. Neurosci. Res. 1993, 18, 45–51. [Google Scholar] [CrossRef]
  147. Shen, Y.; Ye, M.Y. Determination of the stability of dopamine in aqueous solutions by high performance liquid chromatography. J. Liq. Chromatogr. 1994, 17, 1557–1565. [Google Scholar] [CrossRef]
  148. El-Sherbeni, A.A.; Stocco, M.R. Addressing the instability issue of dopamine during microdialysis: The determination of dopamine, serotonin, methamphetamine and its metabolites in rat brain. J. Chromatogr. A 2020, 1627, 461403. [Google Scholar] [CrossRef]
  149. Ferris, M.J.; España, R.A. Dopamine transporters govern diurnal variation in extracellular dopamine tone. Proc. Natl. Acad. Sci. USA 2014, 111, E2751–E2759. [Google Scholar] [CrossRef] [Green Version]
  150. Tang, A.; Bungay, P.M. Characterization of probe and tissue factors that influence interpretation of quantitative microdialysis experiments for dopamine. J. Neurosci. Methods 2003, 126, 1–11. [Google Scholar] [CrossRef]
  151. Millar, J.; Armstrong-James, M. Polarographic assay of iontophoretically applied dopamine and low-noise unit recording using a multibarrel carbon fibre microelectrode. Brain Res. 1981, 205, 419–424. [Google Scholar] [CrossRef]
  152. Millar, J.; Stamford, J.A. Electrochemical, pharmacological and electrophysiological evidence of rapid dopamine release and removal in the rat caudate nucleus following electrical stimulation of the median forebrain bundle. Eur. J. Phamarcol. 1985, 109, 341–348. [Google Scholar] [CrossRef]
  153. Fortin, S.M.; Cone, J.J. Sampling phasic dopamine signaling with fast-scan cyclic voltammetry in awake, behaving rats. Curr. Protoc. Neurosci. 2015, 70, 7.25.1–7.25.20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  154. Robinson, D.L.; Venton, B.J. Detecting subsecond dopamine release with fast-scan cyclic voltammetry in vivo. Clin. Chem. 2003, 49, 1763–1773. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  155. Ewing, A.G.; Bigelow, J.C. Direct in vivo monitoring of dopamine released from two striatal compartments in the rat. Science 1983, 221, 169–171. [Google Scholar] [CrossRef]
  156. Heien, M.L.; Johnson, M.A. Resolving neurotransmitters detected by fast-scan cyclic voltammetry. Anal. Chem. 2004, 76, 5697–5704. [Google Scholar] [CrossRef]
  157. Howell, J.O.; Kuhr, W.G. Background subtraction for rapid scan voltammetry. J. Electroanal. Chem. Interfacial Electrochem. 1986, 209, 77–90. [Google Scholar] [CrossRef]
  158. Oh, Y.; Park, C. Monitoring in vivo changes in tonic extracellular dopamine level by charge-balancing multiple waveform fast-scan cyclic voltammetry. Anal. Chem. 2016, 88, 10962–10970. [Google Scholar] [CrossRef] [PubMed]
  159. Oh, Y.; Heien, M.L. Tracking tonic dopamine levels in vivo using multiple cyclic square wave voltammetry. Biosens. Bioelectron. 2018, 121, 174–182. [Google Scholar] [CrossRef] [PubMed]
  160. Patriarchi, T.; Cho, J.R. Ultrafast neuronal imaging of dopamine dynapics with designed genetically encoded sensors. Science 2018, 360, eaat4422. [Google Scholar] [CrossRef] [Green Version]
  161. Sun, F.; Zeng, J. A genetically encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice. Cell 2018, 174, 481–496. [Google Scholar] [CrossRef] [PubMed]
  162. Patriarchi, T.; Mohebi, A. An expanded palette of dopamine sensors for multiplex imaging in vivo. Nat. Methods 2020, 17, 1147–1155. [Google Scholar] [CrossRef]
  163. Sun, F.; Zhou, J. Next-generation GRBA sensors for monitoring dopaminergic activity in vivo. Nat. Methods 2020, 17, 1156–1166. [Google Scholar] [CrossRef]
  164. Labouesse, M.A.; Cola, R.B. GPCR-based dopamine sensors—A detailed guide to inform sensor choice for in vivo imaging. Int. J. Mol. Sci. 2020, 21, 8048. [Google Scholar] [CrossRef]
  165. Mohebi, A.; Pettibone, J.R. Dissociable dopamine dynamics for learning and motivation. Nature 2019, 570, 65–70. [Google Scholar] [CrossRef]
  166. Gerhardt, G.A.; Maloney, R.E. Microdialysis studies of basal levels and stimulus-evoked overflow of dopamine and metabolites in the striatum of young and aged Fischer 344 rats. Brain Res. 1999, 816, 68–77. [Google Scholar] [CrossRef]
  167. Paulson, P.E.; Robinson, T.E. Regional differences in the effects of amphetamine withdrawal on dopamine dynamics in the striatum. Analysis of circadian patterns using automated on-line microdialysis. Neuropsychopharmacology 1996, 14, 325–337. [Google Scholar] [CrossRef] [Green Version]
  168. Castañeda, T.R.; de Prado, B.M. Circadian rhythms of dopamine, glutamate and GABA in the striatum and nucleus accumbens of the awake rat: Modulation by light. J. Pineal Res. 2004, 36, 177–185. [Google Scholar] [CrossRef] [Green Version]
  169. Smith, A.D.; Olson, R.J. Quantitative microdialysis of dopamine in the striatum: Effect of circadian variation. J. Neurosci. Methods 1992, 44, 33–41. [Google Scholar] [CrossRef]
  170. Feenstra, M.G.; Botterblom, M.H. Dopamine and noradrenaline efflux in the prefrontal cortex in the light and dark period: Effects of novelty and handling and comparison to the nucleus accumbens. Neuroscience 2000, 100, 741–748. [Google Scholar] [CrossRef]
  171. Xiao, L.; Becker, J.B. Quantitative microdialysis determination of extracellular striatal dopamine concentration in male and female rats: Effects of estrous cycle and gonadectomy. Neurosci. Lett. 1994, 180, 155–158. [Google Scholar] [CrossRef] [Green Version]
  172. Dazzi, L.; Seu, E. Estrous cycle-dependent changes in basal and ethanol-induced activity of cortical dopaminergic neurons in the rat. Neuropsychopharmacology 2007, 32, 892–901. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  173. Aubele, T.; Kritzer, M.F. Gonadectomy and hormone replacement affects in vivo basal extracellular dopamine levels in the prefrontal cortex but not motor cortex of adult male rates. Cereb. Cortex 2011, 21, 222–232. [Google Scholar] [CrossRef]
  174. Scheller, C.; Arendt, G. Increased dopaminergic neurotransmission in therapy-naïve asymptomatic HIV patients is not associated with adaptive changes at the dopaminergic synapses. J. Neural Transm. 2010, 117, 699–705. [Google Scholar] [CrossRef] [PubMed]
  175. Kesby, J.P.; Markous, A. The effects of HIV-1 regulatory TAT protein expression on brain reward function, response to psychostimulants and delay-dependent memory in mice. Neuropharmacology 2016, 109, 205–215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  176. Strauss, M.; O’Donovan, B. [3H] dopamine uptake through the dopamine and norepinephrine transporters is decreased in the prefrontal cortex of transgenic mice expressing HIV-1 transactivator of transcription protein. J. Pharmacol. Exp. Ther. 2020, 374, 241–251. [Google Scholar] [CrossRef]
  177. WHO Case Definitions of HIV for Surveillance and Revised Clinical Staging and Immunological Classification of HIV-Related Disease in Adults and Children. Available online: https://www.who.int/hiv/pub/guidelines/HIVstaging150307.pdf (accessed on 4 July 2021).
  178. Kesby, J.P.; Markou, A. Effects of HIV/TAT protein expression and chronic selegiline treatment on spatial memory, reversal learning and neurotransmitter levels in mice. Behav. Brain Res. 2016, 311, 131–140. [Google Scholar] [CrossRef] [Green Version]
  179. Romley, J.A.; Juday, T. Early HIV treatment led to life expectancy gains valued at $80 billion for people infected in 1996–2009. Health Aff. 2014, 33, 370–377. [Google Scholar] [CrossRef] [Green Version]
  180. Teeraananchai, S.; Kerr, S.J. Life expectancy of HIV-positive people after starting combination antiretroviral therapy: A meta-analysis. HIV Med. 2017, 18, 256–266. [Google Scholar] [CrossRef] [PubMed]
  181. Czub, S.; Koutsilieri, E. Enhancement of central nervous system pathology in early simian immunodeficiency virus infection by dopaminergic drugs. Acta Neuropathol. 2001, 101, 85–91. [Google Scholar] [PubMed]
  182. Koutsilieri, E.; Sopper, S. Parkinsonism in HIV dementia. J. Neural Trasm. 2002, 109, 767–775. [Google Scholar] [CrossRef]
  183. Jenuwein, M.; Scheller, C. Dopamine deficits and regulation of the cAMP second messenger system in brains of simian immunodeficiency virus-infected rhesus monkeys. J. Neurovirol. 2004, 10, 163–170. [Google Scholar] [CrossRef] [PubMed]
  184. Scheller, C.; Sopper, S. Early impairment in dopaminergic neurotransmission in brains of SIV-infected rhesus monkeys due to microglia activation. J. Neurochem. 2005, 95, 377–387. [Google Scholar] [CrossRef]
  185. Ferris, M.J.; Frederick-Duus, D. In vivo microdialysis in awake, freely moving rats demonstrates HIV-1 Tat-induced alterations in dopamine transmission. Synapse 2009, 63, 181–185. [Google Scholar] [CrossRef] [Green Version]
  186. Horn, A.; Scheller, C. The dopamine-related polymorphisms BDNF, COMT, DRD2, DRD3, and DRD4 are not linked with changes in CSF dopamine levels and frequency of HIV infection. J. Neural Transm. 2017, 124, 501–509. [Google Scholar] [CrossRef] [PubMed]
  187. Javadi-Paydar, M.; Roscoe, R.F., Jr. HIV-1 and cocaine disrupt dopamine reuptake and medium spiny neurons in female rat striatum. PLoS ONE 2017, 12, e0188404. [Google Scholar] [CrossRef] [Green Version]
  188. Saloner, R.; Cherner, M. Lower CSF homovanillic acid relates to higher burden of neuroinflammation and depression in people with HIV disease. Brain Behav. Immun. 2020, 90, 353–363. [Google Scholar] [CrossRef] [PubMed]
  189. Denton, A.R.; Mactutus, C.F. Chronic SSRI treatment reverses HIV-1 protein-mediated synaptodendritic damage. J. Neurovirol. 2021, 27, 403–421. [Google Scholar] [CrossRef] [PubMed]
  190. Antinori, A.; Arendt, G. Updated research nosology for HIV-associated neurocognitive disorders. Neurology 2007, 69, 1789–1799. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  191. Heaton, R.K.; Franklin, D.R. Neurocognitive change in the era of HIV combination antiretroviral therapy: The longitudinal CHARTER study. Clin. Infect. Dis. 2015, 60, 473–480. [Google Scholar] [CrossRef] [PubMed]
  192. Sacktor, N.; Skolasky, R.L. Prevalence of HIV-associated neurocognitive disorders in the Multicenter AIDS Cohort Study. Neurology 2016, 86, 334–340. [Google Scholar] [CrossRef] [Green Version]
  193. Rubin, L.H.; Maki, P.M. Cognitive trajectories over 4 years among HIV-infected women with optimal viral suppression. Neurology 2017, 89, 1594–1603. [Google Scholar] [CrossRef]
  194. Gott, C.; Gates, T. Cognitive change trajectories in virally suppressed HIV-infected individuals indicate high prevalence of disease activity. PLoS ONE 2017, 12, e0171887. [Google Scholar] [CrossRef] [Green Version]
  195. McLaurin, K.A.; Li, H. Disruption of timing: NeuroHIV progression in the post-cART era. Sci. Rep. 2019, 9, 827. [Google Scholar] [CrossRef] [Green Version]
  196. Cysique, L.A.; Maruff, P. Prevalence and pattern of neuropsychological impairment in human immunodeficiency virus-infected/acquired immunodeficiency syndrome (HIV/AIDS) patients across pre- and post-highly active antiretroviral therapy eras: A combined study of two cohorts. J. Neurovirol. 2004, 10, 350–357. [Google Scholar] [CrossRef]
  197. Garvey, L.J.; Yerrakalva, D. Correlations between computerized battery testing and a memory questionnaire for identification of neurocognitive impairment in HIV type 1-infected subjects on stable antiretroviral therapy. AIDS Res. Hum. Retrovir. 2009, 25, 765–769. [Google Scholar] [CrossRef]
  198. Bertrand, S.J.; Mactutus, C.F. HIV-1 proteins dysregulate motivational processes and dopamine circuitry. Sci. Rep. 2018, 8, 7869. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  199. Bhatia, M.S.; Munjal, S. Prevalence of depression in people living with HIV/AIDS undergoing ART and factors associated with it. J. Clin. Diagn Res. 2014, 8, WC01–WC04. [Google Scholar] [CrossRef] [PubMed]
  200. Do, A.N.; Rosenberg, E.S. Excess burden of depression among HIV-infected persons receiving medical care in the United States: Data from the medical monitoring project and the behavioral risk factor surveillance system. PLoS ONE 2014, 9, e92842. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  201. Hoffman, H.S.; Searle, J.L. Acoustic variables in the modification of startle reaction in the rat. J. Comp. Physiol. Psychol. 1965, 60, 53–58. [Google Scholar] [CrossRef]
  202. Ison, J.R.; Hammond, G.R. Modification of the startle reflex in the rat by changes in the auditory and visual environments. J. Comp. Phsyiol. Psychol. 1971, 75, 435–452. [Google Scholar] [CrossRef]
  203. Hoffman, H.S.; Ison, J.R. Reflex modification in the domain of startle: I. Some empirical findings and their implications for how the nervous system processes sensory input. Psychol. Rev. 1980, 87, 175–189. [Google Scholar] [CrossRef]
  204. Braff, D.; Stone, C. Prestimulus effects on human startle reflex in normal and schizophrenics. Psychophysiology 1978, 15, 339–343. [Google Scholar] [CrossRef]
  205. Hoenig, K.; Hochrein, A. Impaired prepulse inhibition of acoustic startle in obsessive-compulsive disorder. Biol. Psychiatry 2005, 57, 1153–1158. [Google Scholar] [CrossRef]
  206. Ahmari, S.E.; Risbrough, V.B. Impaired sensorimotor gating in unmedicated adults with obsessive-compulsive disorder. Neuropsychopharmacology 2012, 37, 1216–1223. [Google Scholar] [CrossRef]
  207. Swerdlow, N.R.; Paulsen, J. Impaired prepulse inhibition of acoustic and tactile startle response in patients with Huntington’s disease. J. Neurol. Neurosurg. Psychiatry 1995, 58, 192–200. [Google Scholar] [CrossRef] [Green Version]
  208. Minassian, A.; Henry, B.L. Prepulse inhibition in HIV-associated neurocognitive disorders. J. Int. Neuropsychol. Soc. 2013, 19, 709–717. [Google Scholar] [CrossRef] [Green Version]
  209. Moran, L.M.; Booze, R.M. Time and time again: Temporal processing demands implicate perceptual and gating deficits in the HIV-1 transgenic rat. J. Neuroimmune Pharmacol. 2013, 8, 988–997. [Google Scholar] [CrossRef] [Green Version]
  210. Bachis, A.; Forcelli, P. Expression of p120 in mice evokes anxiety behavior: Co-occurrence with increased dendritic spines and brain-derived neurotrophic factor in the amygdala. Brain Behav. Immun. 2016, 54, 170–177. [Google Scholar] [CrossRef] [Green Version]
  211. McLaurin, K.A.; Booze, R.M. Temporal processing demands in the HIV-1 transgenic rat: Amodal gating and implications for diagnostics. Int. J. Dev. Neurosci. 2017, 57, 12–20. [Google Scholar] [CrossRef] [Green Version]
  212. McLaurin, K.A.; Booze, R.M. Progression of temporal processing deficits in the HIV-1 transgenic rat. Sci. Rep. 2016, 6, 32831. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  213. McLaurin, K.A.; Booze, R.M. Evolution of the HIV-1 transgenic rat: Utility in assessing the progression of HIV-1-associated neurocognitive disorders. J. Neurovirol. 2018, 24, 229–245. [Google Scholar] [CrossRef]
  214. McLaurin, K.A.; Booze, R.M. Diagnostic and prognostic biomarkers for HAND. J. Neurovirol. 2019, 25, 686–701. [Google Scholar] [CrossRef]
  215. Davis, M.; Gendelman, D.S. A primary acoustic startle circuit: Lesion and stimulation studies. J. Neurosci. 1982, 2, 791–805. [Google Scholar] [CrossRef] [PubMed]
  216. Koch, M. The neurobiology of startle. Prog. Neurobiol. 1999, 59, 107–128. [Google Scholar] [CrossRef]
  217. Fendt, M.; Li, L. Brain stem circuits mediating prepulse inhibition of the startle reflex. Psychopharmacology 2001, 156, 216–224. [Google Scholar] [CrossRef] [PubMed]
  218. Di Chiara, G.; Porceddu, M.L. Evidence for dopamine receptors mediating sedation in the mouse brain. Nature 1976, 264, 564–567. [Google Scholar] [CrossRef] [PubMed]
  219. Goodale, D.P.; Rusterholz, D.B. Neurochemical and behavioral evidence for a selective presynaptic dopamine receptor agonist. Science 1980, 210, 1141–1143. [Google Scholar] [CrossRef]
  220. Campeau, S.; Davis, M. Prepulse inhibition of the acoustic startle reflect using visual and auditory prepulses: Disruption by apomorphine. Psychopharmacology 1995, 117, 267–274. [Google Scholar] [CrossRef] [PubMed]
  221. Jones, C.K.; Shannon, H.E. Effects of scopolamine in comparison with apomorphine and phencyclidine on prepulse inhibition in rats. Eur. J. Pharmacol. 2000, 391, 105–112. [Google Scholar] [CrossRef]
  222. Mansbach, R.S.; Geyer, M.A. Dopaminergic stimulation disrupts sensorimotor gating in the rat. Psychopharmacology 1988, 94, 507–514. [Google Scholar] [CrossRef]
  223. Zavitsanou, K.; Cranney, J. Dopamine antagonists in the orbital prefrontal cortex reduce prepulse inhibition of the acoustic startle reflex in the rat. Pharmacol. Biochem. Behav. 1999, 63, 55–61. [Google Scholar] [CrossRef]
  224. Rodrigues, S.; Salum, C. Dorsal striatum D1-expressing neurons are involved with sensorimotor gating on prepulse inhibition test. J. Psychopharmacol. 2017, 31, 505–513. [Google Scholar] [CrossRef] [PubMed]
  225. Ellenbroek, B.A.; Budde, S. Prepulse inhibition and latent inhibition: The role of dopamine in the medial prefrontal cortex. Neuroscience 1996, 75, 535–542. [Google Scholar] [CrossRef] [Green Version]
  226. Ungerstedt, U. 6-hydroxy-dopamine induced degeneration of central monoamine neurons. Eur. J. Pharmacol. 1968, 5, 107–110. [Google Scholar] [CrossRef]
  227. Bloom, F.E.; Algeri, S. Lesions of central norepinephrine terminals with 6-OH-dopamine: Biochemistry and fine structure. Science 1969, 166, 1284–1286. [Google Scholar] [CrossRef]
  228. Schwarzkopf, S.B.; Mitra, T. Sensory gating in rats depleted of dopamine as neonates: Potential relevance to findings in schizophrenic patients. Biol. Psychiatry 1992, 31, 759–773. [Google Scholar] [CrossRef]
  229. Bubser, M.; Koch, M. Prepulse inhibition of the acoustic startle response of rats is reduced by 6-hydroxydopamine lesions of the medial prefrontal cortex. Psychopharmacology 1994, 113, 487–492. [Google Scholar] [CrossRef]
  230. Fuster, J.M. The Prefrontal Cortex, 4th ed.; Academic Press: New York, NY, USA, 2008. [Google Scholar]
  231. Sohlberg, M.M.; Mateer, C.A. Effectiveness of an attention-training program. J. Clin. Exp. Neuropscyhol. 1987, 9, 117–130. [Google Scholar] [CrossRef]
  232. Sohlberg, M.M.; Mateer, C.A. Introduction to Cognitive Rehabilityation: Theory and Practice; Guilford Press: New York, NY, USA, 1989. [Google Scholar]
  233. Moran, L.M.; Booze, R.M. Modeling deficits in attention, inhibition, and flexibility in HAND. J. Neuroimmune Pharmacol. 2014, 9, 508–521. [Google Scholar] [CrossRef] [Green Version]
  234. Lew, B.J.; McDermott, T.J. Neural dynamics of selective attention deficits in HIV-associated neurocognitive disorder. Neurology 2018, 91, e1860–e1869. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  235. McLaurin, K.A.; Moran, L.M. Selective estrogen receptor β agonists: A therapeutic approach for HIV-1 associated neurocognitive disorders. J. Neuroimmune Pharmacol. 2020, 15, 264–279. [Google Scholar] [CrossRef] [Green Version]
  236. Hinkin, C.H.; Castellon, S.A. Dual task performance in HIV-1 infection. J. Clin. Exp. Neuropsychol. 2000, 22, 16–24. [Google Scholar] [CrossRef]
  237. Williams, S.M.; Goldman-Rakic, P.S. Widespread origin of the primate mesofrontal dopamine system. Cereb. Cortex 1998, 8, 321–345. [Google Scholar] [CrossRef] [Green Version]
  238. Granon, S.; Passetti, F. Enhanced and impaired attentional performance after infusion of D1 dopaminergic receptor agents into rat prefrontal cortex. J. Neurosci. 2000, 20, 1208–1215. [Google Scholar] [CrossRef]
  239. Rose, J.; Schiffer, A.M. The role of dopamine in maintenance and distractability of attention in the “prefrontal cortex” of pigeons. Neuroscience 2010, 167, 232–237. [Google Scholar] [CrossRef]
  240. Pezze, M.A.; Dalley, J.W. Differential roles of dopamine D1 and D2 receptors in the nucleus accumbens in attentional performance on the five-choice serial reaction time task. Neuropsychopharmacology 2007, 32, 273–283. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  241. Caballero, M.; Núnez, F. Caffeine improves attention deficit in neonatal 6-OHDA lesioned rats, an animal model of attention deficit hyperactivity disorder (ADHD). Neurosci. Lett. 2011, 494, 44–48. [Google Scholar] [CrossRef]
  242. Bouchatta, O.; Manouze, H. Neonatal 6-OHDA lesion model in mouse induces Attention-Deficit/Hyperactivity Disorder (ADHD)-like behaviour. Sci. Rep. 2018, 8, 15349. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  243. Bouchatta, O.; Manouze, H. Neonatal 6-OHDA lesion model in mouse induces cognitive dysfunctions of Attention-Deficit/Hyperactivity Disorder (ADHD) during young age. Front. Behav. Neurosci. 2020, 14, 27. [Google Scholar] [CrossRef]
  244. Oke, A.F.; Adams, R.N. Selective attention dysfunctions in adult rats neonatally treated with 6-hydroxydopamine. Pharmacol. Biochem. Behav. 1978, 9, 429–432. [Google Scholar] [CrossRef]
  245. Crofts, H.S.; Dalley, J.W. Differential effects of 6-OHDA lesions of the frontal cortex and caudate nucleus on the ability to acquire an attentional set. Cereb. Cortex 2001, 11, 1015–1026. [Google Scholar] [CrossRef] [Green Version]
  246. Roberts, A.C.; De Salvia, M.A. 6-Hydroxydopamine lesions of the prefrontal cortex in monkeys enhance performance on an analog of the Wisconsin Card Sort Test: Possible interactions with subcortical dopamine. J. Neurosci. 1994, 14, 2531–2544. [Google Scholar] [CrossRef] [Green Version]
  247. Decamp, E.; Schneider, J.S. Attention and executive function deficits in chronic low-dose MPTP-treated non-human primates. Eur. J. Neurosci. 2004, 20, 1371–1378. [Google Scholar] [CrossRef] [PubMed]
  248. Marin, R.S. Apathy: A neuropsychiatric syndrome. J. Neuropsychiatry Clin. Neurosci. 1991, 3, 243–254. [Google Scholar]
  249. Levy, R.; Dubois, B. Apathy and the functional anatomy of the prefrontal cortex-basal ganglia circuits. Cereb. Cortex 2006, 16, 916–928. [Google Scholar] [CrossRef] [Green Version]
  250. Clarke, D.E.; Ko, J.Y. Are the available apathy measures reliable and valid? A review of the psychometric evidence. J. Psychosom. Res. 2011, 70, 73–97. [Google Scholar] [CrossRef] [Green Version]
  251. Marin, R.S.; Biedrzycki, R.C. Reliability and validity of the Apathy Evaluation Scale. Psychiatry Res. 1991, 38, 143–162. [Google Scholar] [CrossRef]
  252. Cummings, J.L.; Mega, M. The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology 1994, 44, 2308–2314. [Google Scholar] [CrossRef] [Green Version]
  253. Oakeshott, S.; Port, R. A mixed fixed ratio/progressive ratio procedure reveals an apathy phenotype in the BAC HD and the z_Q175 KI mouse models of Huntington’s disease. PLoS Curr. 2012, 4, e4f972cffe82c0. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  254. McLaurin, K.A.; Bertrand, S.J. S-equol mitigates motivational deficits and dysregulation associated with HIV-1. Sci. Rep. 2021, 11, 11870. [Google Scholar] [CrossRef] [PubMed]
  255. Zhao, Q.F.; Tan, L. The prevalence of neuropsychiatric symptoms in Alzheimer’s disease: Systematic review and meta-analysis. J. Affect. Disord. 2016, 190, 264–271. [Google Scholar] [CrossRef]
  256. den Brok, M.G.; van Dalen, J.W. Apathy in Parkinson’s disease: A systematic review and meta-analysis. Mov. Disord. 2015, 30, 759–769. [Google Scholar] [CrossRef] [PubMed]
  257. Tate, D.; Paul, R.H. The impact of apathy and depression on quality of life in patients infected with HIV. AIDS Patient Care STDs 2003, 17, 115–120. [Google Scholar] [CrossRef] [PubMed]
  258. Kamat, R.; Morgan, E. Implications of apathy and depression for everyday functioning in HIV/AIDS in Brazil. J. Affect. Disord. 2013, 150, 1069–1075. [Google Scholar] [CrossRef] [Green Version]
  259. Panos, S.E.; Del Re, A.C. The impact of neurobehavioral features on medication adherence in HIV: Evidence from longitudinal models. AIDS Care 2014, 26, 79–86. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  260. Kamat, R.; Doyle, K.L. Neurobehavioral disturbances during acute and early HIV infection. Cogn Behav Neurol. 2016, 29, 1–10. [Google Scholar] [CrossRef] [Green Version]
  261. Bonelli, R.M.; Cummings, J.L. Frontal-subcortical circuitry and behavior. Dialogues Clin. Neurosci. 2007, 9, 141–151. [Google Scholar] [PubMed]
  262. Selemon, L.D.; Goldman-Rakic, P.S. Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey. J. Neurosci. 1985, 5, 776–794. [Google Scholar] [CrossRef] [Green Version]
  263. Critchley, H.D. Neural mechanisms of autonomic, affective, and cognitive integration. J. Comp. Neurol. 2005, 493, 154–166. [Google Scholar] [CrossRef] [PubMed]
  264. Drui, G.; Carnicella, S. Loss of dopaminergic nigrostriatal neurons accounts for the motivational and affective deficits in Parkinson’s disease. Mol. Psychiatry. 2014, 19, 358–367. [Google Scholar] [CrossRef] [Green Version]
  265. Favier, M.; Duran, T. Pramipexole reverses Parkinson’s disease-related motivational deficits in rats. Mov. Disord. 2014, 29, 912–920. [Google Scholar] [CrossRef] [PubMed]
  266. Carnicella, S.; Drui, G. Implication of dopamine D3 receptor activation in the reversion of Parkinson’s disease-related motivational deficits. Transl. Psychiatry 2014, 4, e401. [Google Scholar] [CrossRef]
  267. Brown, C.A.; Campbell, M.C. Dopamine pathway loss in nucleus accumbens and ventral tegmental area predicts apathetic behavior in MPTP-lesioned monkeys. Exp. Neurol. 2012, 236, 190–197. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  268. Fitzpatrick, C.M.; Runegaard, A.H. Differential effects of chemogenetic inhibition of dopamine and norepinephrine neurons in the mouse 5-choice serial reaction time task. Prog. Neuropsychopharmacol. Biol. Psychiatry 2019, 90, 264–276. [Google Scholar] [CrossRef]
  269. Guidelines for the Use of Antiretroviral Agents in Adults and Adolescents Living with HIV. Available online: https://clinicalinfo.hiv.gov/en/guidelines/adult-and-adolescent-arv/whats-new-guidelines (accessed on 4 December 2020).
  270. Letendre, S.; Marquie-Beck, J. Validation of the CNS Penetration-Effectiveness rank for quantifying antiretroviral penetration into the central nervous system. Arch. Neurol. 2008, 65, 65–70. [Google Scholar] [CrossRef] [Green Version]
  271. Morlese, J.F.; Qazi, N.A. Nevirapine-induced neuropsychiatric complications, a class effect of non-nucleoside reverse transcriptase inhibitors? AIDS 2002, 16, 1840–1841. [Google Scholar] [CrossRef] [PubMed]
  272. Wise, M.E.J.; Mistry, K. Drug points: Neuropsychiatric complications of nevirapine treatment. BMJ 2002, 324, 879. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  273. Rihs, T.A.; Begley, K. Efavirenz and chronic neuropsychiatric symptoms: A cross-sectional case control study. HIV Med. 2006, 7, 544–548. [Google Scholar] [CrossRef] [PubMed]
  274. Cespedes, M.S.; Aberg, J.A. Neuropsychiatric complications of antiretroviral therapy. Drug Saf. 2006, 29, 865–874. [Google Scholar] [CrossRef] [PubMed]
  275. Treisman, G.J.; Soudry, O. Neuropsychiatric Effects of HIV Antiviral Medications. Drug Saf. 2016, 39, 945–957. [Google Scholar] [CrossRef]
  276. Gatch, M.B.; Kozlenkov, A. The HIV antiretroviral drug efavirenz has LSD-like properties. Neuropsychopharmacology 2013, 38, 2373–2384. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  277. Dalwadi, D.A.; Kim, S. Molecular mechanisms of serotonergic action of the HIV-1 antiretroviral efavirenz. Pharmacol. Res. 2016, 110, 10–24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  278. Huang, R.; Chen, Z. The dual modulatory effects of efavirenz on GABAA receptors are mediated via two distinct sites. Neuropharmacology 2017, 121, 167–178. [Google Scholar] [CrossRef] [PubMed]
  279. Möller, M.; Fourie, J. Efavirenz exposure, alone and in combination with known drugs of abuse, engenders addictive-like bio-behavioural changes in rats. Sci. Rep. 2018, 8, 12837. [Google Scholar] [CrossRef]
  280. Cavalcante, G.I.T.; Chaves Filho, A.J.M. HIV antiretroviral drug Efavirenz induces anxiety-like and depression-like behavior in rats: Evaluation of neurotransmitter alterations in the striatum. Eur. J. Pharmacol. 2017, 799, 7–15. [Google Scholar] [CrossRef]
  281. Overton, D.A. Major theories of state-dependent learning. In Drug Discrimination and State Dependent Learning; Ho, B.T., Richards, D.W., Eds.; Academic Press: New York, NY, USA, 1978; pp. 283–309. [Google Scholar]
  282. Appel, J.B.; Kuhn, D.M. Dual receptor mediation of the discriminative stimulus properties of pentazocine. In Drug Discrimination and State Dependent Learning; Ho, B.T., Richards, D.W., Eds.; Academic Press: New York, NY, USA, 1978; pp. 149–160. [Google Scholar]
  283. Anagnostaras, S.G.; Robinson, T.E. Sensitization to the psychomotor stimulant effects of amphetamine: Modulation by associative learning. Behavioral. Neurosci. 1996, 110, 1397–1414. [Google Scholar] [CrossRef]
  284. Harrod, S.B.; Mactutus, C.F. Intra-accumbal Tat1-72 alters acute and sensitized responses to cocaine. Pharmacol. Biochem. Behav. 2008, 90, 723–729. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  285. Robinson, T.E.; Jurson, P.A. Persistent sensitization of dopamine neurotransmission in ventral striatum (nucleus accumbens) produced by prior experience with (+)-amphetamine: A microdialysis study in freely moving rats. Brain Res. 1988, 462, 211–222. [Google Scholar] [CrossRef] [Green Version]
  286. Heidbreder, C.A.; Thompson, A.C. Role of extracellular dopamine in the initiation and long-term expression of behavioral sensitization to cocaine. J. Pharmacol. Exp. Ther. 1996, 278, 490–502. [Google Scholar] [PubMed]
  287. Weeks, J.R. Experimental morphine addiction: Method for automatic intravenous injections in unrestrained rats. Science 1962, 138, 143–144. [Google Scholar] [CrossRef]
  288. Pickens, R. Self-administration of stimulants by rats. Int. J. Addict. 1968, 3, 215–221. [Google Scholar] [CrossRef]
  289. De Guglielmo, G.; Fu, Y. Increases in compulsivity, inflammation, and neural injury in HIV transgenic rats with escalated methamphetamine self-administration under extended-access conditions. Brain Res. 2020, 1726, 146502. [Google Scholar] [CrossRef]
  290. Zanni, G.; DeSalle, M.J. Female and male rats readily consume and prefer oxycodone to water in a chronic, continuous access, two-bottle oral voluntary paradigm. Neuropharmacology 2020, 167, 107978. [Google Scholar] [CrossRef]
  291. O’Connor, E.C.; Chapman, K. The predictive validity of the rat self-administration model for abuse liability. Neurosci. Biobehav. Rev. 2011, 35, 912–938. [Google Scholar] [CrossRef] [Green Version]
  292. Clark, R.; Schuster, C.R. Instrumental conditioning of jugular self-infusion in the rhesus monkey. Science 1961, 133, 1829–1830. [Google Scholar] [CrossRef] [PubMed]
  293. Illenberger, J.M.; Harrod, S.B. HIV Infection and Neurocognitive Disorders in the Context of Chronic Drug Abuse: Evidence for Divergent Findings Dependent upon Prior Drug History. J. Neuroimmune Pharmacol. 2020, 15, 715–728. [Google Scholar] [CrossRef]
  294. Bardo, M.T.; Bevins, R.A. Conditioned place preference: What does it add to our preclinical understanding of drug reward? Psychopharmacology 2000, 153, 31–43. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  295. Nomikos, G.G.; Spyraki, C. Cocaine-induced place conditioning: Importance of route of administration and other procedural variables. Psychopharmacology 1988, 94, 119–125. [Google Scholar] [CrossRef]
  296. Meehan, S.M.; Schechter, M.D. LSD produces conditioned place preference in male but not female fawn hooded rats. Pharmacol. Biochem. Behav. 1998, 59, 105–108. [Google Scholar] [CrossRef]
  297. Prus, A.J.; James, J.R. Conditioned Place Preference. In Methods of Behavior Analysis in Neuroscience, 2nd ed.; Buccafusco, J.J., Ed.; CRC Press/Taylor & Francis: Boca Raton, FL, USA, 2009. [Google Scholar]
  298. Neisewander, J.L.; McDougall, S.A. Conditioned taste aversion and place preference with buspirone and gepirone. Psychopharmacology 1990, 100, 485–490. [Google Scholar] [CrossRef] [PubMed]
  299. Orlando, G.; Brunetti, L. Ritonavir and Saquinavir directly stimulate anterior pituitary prolactin secretion, in vitro. Int. J. Immunopathol. Pharmacol. 2002, 15, 65–68. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  300. Polazzi, E.; Monti, B. Microglia and neuroprotection: From in vitro studies to therapeutic applications. Prog. Neurobiol. 2010, 92, 293–315. [Google Scholar] [CrossRef]
  301. Murabe, Y.; Sano, Y. Morphological studies on neuroglia. VI. Postnatal development of microglial cells. Cell Tissue Res. 1982, 225, 469–485. [Google Scholar] [CrossRef] [PubMed]
  302. Perry, V.H.; Hume, D.A. Immunohistochemical localization of macrophages and microglia in the adult and developing mouse brain. Neuroscience 1985, 15, 313–326. [Google Scholar] [CrossRef]
  303. Davalos, D.; Grutzendler, J. ATP mediates rapid microglial response to local brain injury in vivo. Nat. Neurosci. 2005, 8, 752–758. [Google Scholar] [CrossRef]
  304. Nimmerjahn, A.; Kirchhoff, F. Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science 2005, 308, 1314–1318. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  305. Wake, H.; Moorhouse, A.J. Resting microglia directly monitor the functional state of synapses in vivo and determine the fate of ischemic terminals. J. Neurosci. 2009, 29, 3974–3980. [Google Scholar] [CrossRef] [Green Version]
  306. Tremblay, M.E.; Lowery, R.L. Microglial interactions with synapses are modulated by visual experience. PLoS Biol. 2010, 8, e1000527. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  307. Lawson, L.J.; Perry, V.H. Heterogeneity in the distribution and morphology of microglia in the normal adult mouse brain. Neuroscience 1990, 39, 151–170. [Google Scholar] [CrossRef]
  308. De Biase, L.M.; Schuebel, K.E. Local cues establish and maintain region-specific phenotypes of basal ganglia microglia. Neuron 2017, 95, 341–356. [Google Scholar] [CrossRef] [Green Version]
  309. Färber, K.; Pannasch, U. Dopamine and noradrenaline control distinct functions in rodent microglial cells. Mol. Cell. Neurosci. 2005, 29, 128–138. [Google Scholar] [CrossRef]
  310. Mastroeni, D.; Grover, A. Microglial responses to dopamine in a cell culture model of Parkinson’s disease. Neurobiol. Aging 2009, 30, 1805–1817. [Google Scholar] [CrossRef] [Green Version]
  311. Huck, J.H.J.; Freyer, D. De novo expression of dopamine D2 receptors on microglia after stroke. J. Cereb. Blood Flow Metab. 2015, 35, 1804–1811. [Google Scholar] [CrossRef] [Green Version]
  312. Fan, Y.; Chen, Z. Differential regulation of adhesion and phagocytosis of resting and activated microglia by dopamine. Front. Cell. Neurosci. 2018, 12, 309. [Google Scholar] [CrossRef]
  313. Squarzoni, P.; Oller, G. Microglia modulate wiring of the embryonic forebrain. Cell Rep. 2014, 8, 1271–1279. [Google Scholar] [CrossRef] [Green Version]
  314. Paolicelli, R.C.; Bolasco, G. Synaptic pruning by microglia is necessary for normal brain development. Science 2011, 333, 1456–1458. [Google Scholar] [CrossRef] [Green Version]
  315. Schafer, D.P.; Lehrman, E.K. Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner. Neuron 2012, 74, 691–705. [Google Scholar] [CrossRef] [Green Version]
  316. Weinhard, L.; di Barolomei, G. Microglia remodel synapses by presynaptic trogocytosis and spine head filopodia induction. Nat. Commun. 2018, 9, 1228. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  317. Parkhurst, C.N.; Yang, G. Microglia promote learning-dependent synapse formation through brain-derived neurotrophic factor. Cell 2013, 155, 1596–1609. [Google Scholar] [CrossRef] [Green Version]
  318. Mallya, A.P.; Wang, H.D. Microglial pruning of synapses in the prefrontal cortex during adolescence. Cereb. Cortex 2019, 29, 1634–1643. [Google Scholar] [CrossRef]
  319. Choudhury, M.E.; Miyanishi, K. Phagocytic elimination of synapses by microglia during sleep. Glia 2020, 68, 44–59. [Google Scholar] [CrossRef] [Green Version]
  320. Lim, S.H.; Park, E. Neuronal synapse formation induced by microglia and interleukin 10. PLoS ONE 2013, 8, e81218. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  321. Miyamoto, A.; Wake, H. Microglia contact induces synapse formation in developing somatosensory cortex. Nat. Commun. 2016, 7, 12540. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  322. Sierra, A.; Encinas, J.M. Microglia shape adult hippocampal neurogenesis through apoptosis-coupled phagocytosis. Cell Stem Cell 2010, 7, 483–495. [Google Scholar] [CrossRef] [Green Version]
  323. Stefani, J.; Tschesnokowa, O. Disruption of the microglial ADP receptor P2Y13 enhances adult hippocampal neurogenesis. Front. Cell. Neurosci. 2018, 12, 134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  324. Diaz-Aparicio, I.; Paris, I. Microglia actively remodel adult hippocampal neurogenesis through the phagocytosis secretome. J. Neurosci. 2020, 40, 1453–1482. [Google Scholar] [CrossRef] [PubMed]
  325. Freund, T.F.; Powell, J.F. Tyrosine hydroxylase-immunoreactive boutons in synaptic contact with identified striatonigral neurons, with particular reference to dendritic spines. Neuroscience 1984, 13, 1189–1215. [Google Scholar] [CrossRef]
  326. Yao, W.D.; Spealman, R.D. Dopaminergic signaling in dendritic spines. Biochem. Pharmacol. 2008, 75, 2055–2069. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  327. Meredith, G.E.; Ypma, P. Effects of dopamine depletion on the morphology of medium spiny neurons in the shell and core of the rat nucleus accumbens. J. Neurosci. 1995, 15, 3808–3820. [Google Scholar] [CrossRef]
  328. Neely, M.D.; Schmidt, D.E. Cortical regulation of dopamine depletion-induced dendritic spine loss in striatal medium spiny neurons. Neuroscience 2007, 149, 457–464. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  329. Ingham, C.A.; Hood, S.H. Morphological changes in the rat neostriatum after unilateral 6-hydroxydopamine injections into the nigrostriatal pathway. Exp. Brain Res. 1993, 93, 17–27. [Google Scholar] [CrossRef]
  330. Ingham, C.A.; Hood, S.H. Plasticity of synapses in the rat neostriatum after unilateral lesion of the nigrostriatal dopaminergic pathway. J. Neurosci. 1998, 18, 4732–4743. [Google Scholar] [CrossRef]
  331. Thompson, K.A.; Cherry, C.L. Brain cell reservoirs of latent virus in presymptomatic HIV-infected individuals. Am. J. Pathol. 2011, 179, 1623–1629. [Google Scholar] [CrossRef] [Green Version]
  332. Ko, A.; Kang, G. Macrophages but not astrocytes harbor HIV DNA in the brains of HIV-1-infected aviremic individuals on suppressive antiretroviral therapy. J. Neuroimmune Pharmacol. 2019, 14, 110–119. [Google Scholar] [CrossRef] [Green Version]
  333. Anthony, I.C.; Ramage, S.N. Influence of HAART on HIV-related CNS disease and neuroinflammation. J. Neuropathol. Exp. Neurol. 2005, 64, 529–536. [Google Scholar] [CrossRef] [Green Version]
  334. Li, H.; Mactutus, C.F. HIV-1 expression in human medial prefrontal cortex: Association with HAND. In Proceedings of the International Symposium for NeuroVirology, Virtual, 2–4 June 2021. Abstract Number 52. [Google Scholar]
  335. Thangaraj, A.; Chivero, E.T. HIV Tat-mediated microglial senescence: Role of SIRT3-dependent mitochondrial oxidative stress. Redox Biol. 2021, 40, 101843. [Google Scholar] [CrossRef] [PubMed]
  336. Gelman, B.B.; Lisinicchia, J.G. Prefrontal dopaminergic and enkephalinergic synaptic accommodation in HIV-associated neurocognitive disorders and encephalitis. J. Neuroimmune Pharmacol. 2012, 7, 686–700. [Google Scholar] [CrossRef] [Green Version]
  337. Roscoe, R.F.; Mactutus, C.F. HIV-1 transgenic female rat: Synaptodendritic alterations of medium spiny neurons in the nucleus accumbens. J. Neuroimmune Pharmacol. 2014, 9, 642–653. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  338. Miller, D.R.; Shaerzadeh, F. HIV-1 Tat regulation of dopamine transmission and microglial reactivity is brain region specific. Glia 2018, 66, 1915–1928. [Google Scholar] [CrossRef] [PubMed]
  339. Duan, M.; Yao, H. HIV-1 Tat disrupts CX3CL1-CX3CR1 axis in microglia via the NF-ΚBYY1 pathway. Curr. HIV Res. 2014, 12, 189–200. [Google Scholar] [CrossRef] [PubMed]
  340. Mishra, N.; Mohata, M. Expression of complement receptor 3 (CR3) and regulatory protein CD46 on dendritic cells of antiretroviral naïve and treated HIV-1 infected individuals: Correlation with immune activation status. Mol. Immunol. 2018, 96, 83–87. [Google Scholar] [CrossRef] [PubMed]
  341. Festa, L.; Gutoskey, C.J. Induction of interleukin-1βby human immunodeficiency virus-1 viral proteins leads to increased levels of neuronal ferritin heavy chain, synaptic injury, and deficits in flexible attention. J. Neurosci. 2015, 35, 10550–10561. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Graphical illustration of the profound differences in estimated dopamine (DA) concentration (ng/g of tissue; X ± SEM) dependent upon methodology (i.e., (A) high-performance liquid chromatography, (B) microdialysis, (C) fast-scan cyclic voltammetry) and brain region. Each dot represents the estimated DA concentration from a study.
Figure 1. Graphical illustration of the profound differences in estimated dopamine (DA) concentration (ng/g of tissue; X ± SEM) dependent upon methodology (i.e., (A) high-performance liquid chromatography, (B) microdialysis, (C) fast-scan cyclic voltammetry) and brain region. Each dot represents the estimated DA concentration from a study.
Cells 10 02158 g001
Figure 2. Technical illustration of three of the prominent methods utilized to detect dopamine (DA) levels in the CNS. Given that high-performance liquid chromatography (HPLC) is more classically used for analyte quantification on brain tissue homogenates or following microdialysis, the method is not illustrated. (A) During microdialysis, a probe composed of a semipermeable dialysis membrane is surgically implanted into the brain, and a perfusion medium (white arrows) is infused slowly and continuously. During perfusion, molecules in the extracellular space diffuse through the semipermeable membrane, and are transported into outflow tubing and collected for analyte quantification (e.g., HPLC). (B) In fast-scan cyclic voltammetry, a small carbon-fiber microelectrode is surgically implanted into the brain. The voltage potential at the carbon-fiber microelectrode is rapidly increased and decreased, resulting in the oxidation and reduction of DA. During the oxidation and reduction processes, the transfer of electrons is measured in current at the surface of the carbon-fiber microelectrode, and the amount of current can be subsequently converted into the concentration of DA. Additionally, the voltammogram is used for analyte identification, whereby DA exhibits one oxidation and one reduction peak. (C) More recently, G-protein coupled receptor (GPCR) biosensors for DA have been developed, affording an opportunity to track the release dynamics of DA. DA biosensors have a circularly permuted fluorescent protein (e.g., Green: cpGFP, Red: cpmApple) inserted into the third intracellular loop of the DA receptor. When DA binds to the endogenous ligand, the GPCR exhibits a conformational change, resulting in an increased fluorescent intensity. Our laboratory has recently transfected cells with GRAB-DA2m, a DA receptor 2 subtype biosensor, in vitro. Upon stimulation with 100 nm DA, an increase in the fluorescence intensity of cpGFP is observed.
Figure 2. Technical illustration of three of the prominent methods utilized to detect dopamine (DA) levels in the CNS. Given that high-performance liquid chromatography (HPLC) is more classically used for analyte quantification on brain tissue homogenates or following microdialysis, the method is not illustrated. (A) During microdialysis, a probe composed of a semipermeable dialysis membrane is surgically implanted into the brain, and a perfusion medium (white arrows) is infused slowly and continuously. During perfusion, molecules in the extracellular space diffuse through the semipermeable membrane, and are transported into outflow tubing and collected for analyte quantification (e.g., HPLC). (B) In fast-scan cyclic voltammetry, a small carbon-fiber microelectrode is surgically implanted into the brain. The voltage potential at the carbon-fiber microelectrode is rapidly increased and decreased, resulting in the oxidation and reduction of DA. During the oxidation and reduction processes, the transfer of electrons is measured in current at the surface of the carbon-fiber microelectrode, and the amount of current can be subsequently converted into the concentration of DA. Additionally, the voltammogram is used for analyte identification, whereby DA exhibits one oxidation and one reduction peak. (C) More recently, G-protein coupled receptor (GPCR) biosensors for DA have been developed, affording an opportunity to track the release dynamics of DA. DA biosensors have a circularly permuted fluorescent protein (e.g., Green: cpGFP, Red: cpmApple) inserted into the third intracellular loop of the DA receptor. When DA binds to the endogenous ligand, the GPCR exhibits a conformational change, resulting in an increased fluorescent intensity. Our laboratory has recently transfected cells with GRAB-DA2m, a DA receptor 2 subtype biosensor, in vitro. Upon stimulation with 100 nm DA, an increase in the fluorescence intensity of cpGFP is observed.
Cells 10 02158 g002
Figure 3. Overview of behaviors characteristic of a hyperdopaminergic versus hypodopaminergic state.
Figure 3. Overview of behaviors characteristic of a hyperdopaminergic versus hypodopaminergic state.
Cells 10 02158 g003
Figure 4. Proposed (potentially) cyclical model of the interrelationship between microglia, and synaptic and dopaminergic system function. (A) Under homeostatic conditions, microglia influence both the dopamine (DA) system and synaptic maintenance. Furthermore, synaptic and dopaminergic system functions exhibit a bidirectional relationship. To date, it is unknown whether the relationships between microglia and synaptic function or microglia and DA system function are bidirectional, as indicated via the dashed lines. (B) Chronic exposure to HIV-1 viral proteins induces activation, dysfunction and/or senescence of microglia, and microglial alterations which may underlie the prominent low DA levels and/or synaptic dysfunction observed in the post-cART era. DA: dopamine; DAT: dopamine transporter; DA1 Receptor: dopamine 1 receptor; VMAT2: vesicular monoamine transporter 2.
Figure 4. Proposed (potentially) cyclical model of the interrelationship between microglia, and synaptic and dopaminergic system function. (A) Under homeostatic conditions, microglia influence both the dopamine (DA) system and synaptic maintenance. Furthermore, synaptic and dopaminergic system functions exhibit a bidirectional relationship. To date, it is unknown whether the relationships between microglia and synaptic function or microglia and DA system function are bidirectional, as indicated via the dashed lines. (B) Chronic exposure to HIV-1 viral proteins induces activation, dysfunction and/or senescence of microglia, and microglial alterations which may underlie the prominent low DA levels and/or synaptic dysfunction observed in the post-cART era. DA: dopamine; DAT: dopamine transporter; DA1 Receptor: dopamine 1 receptor; VMAT2: vesicular monoamine transporter 2.
Cells 10 02158 g004
Table 1. Estimated basal dopamine (DA) values. Abbreviations: High Performance Liquid Chromatogrphy (HPLC); Fast Scan Cyclic Voltammetry (FSCV).
Table 1. Estimated basal dopamine (DA) values. Abbreviations: High Performance Liquid Chromatogrphy (HPLC); Fast Scan Cyclic Voltammetry (FSCV).
Brain RegionMethodologyEstimated DA Concentration in ng/g of Tissue
(X ± SEM)
Relative Standard ErrorReferences
AmygdalaHPLC3683.85 ± 309784.1%[39,40,41,42,43]
Microdialysis0.06 ± 0.0350%[44,45,46,47]
CaudateHPLC16,365.9 ± 12,341.0475.4%[28,39,41,48,49,50,51,52,53,54]
Microdialysis0.88 ± 0.6675%[44,55,56]
Frontal CortexHPLC200.73 ± 84.4142.1%[28,39,42,52,54,57,58,59,60,61,62]
Microdialysis0.23 ± 0.1043.5%[44,63,64,65]
Nucleus AccumbensHPLC35,772.90 ± 12,020.2833.6%[41,42,43,51,52,57,59,60,62,66,67,68]
Microdialysis0.76 ± 0.1317.1%[44,45,47,55,63,64,65,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99]
FSCV6.95 ± 1.9327.8%[100,101,102,103,104]
StriatumHPLC67,460.52 ± 29,013.2843%[59,61,62,66,67,105,106,107,108,109,110,111]
Microdialysis1.42 ± 0.4028.2%[64,73,74,76,79,82,85,112,113,114]
Ventral Tegmental AreaHPLC9200 [66]
Microdialysis0.25 ± 0.0728%[75,83]
Table 2. Influence of HIV-1 viral protein exposure on dopamine (DA) concentration relative to controls. Asterisks (*) indicate manuscripts that measured DA metabolites (e.g., homovanillic acid). Symbols: DA concentration is decreased ( Cells 10 02158 i001) or increased ( Cells 10 02158 i002) relative to controls. The equal sign ( Cells 10 02158 i003) indicates no statistically significant differences in DA concentration between HIV and controls.
Table 2. Influence of HIV-1 viral protein exposure on dopamine (DA) concentration relative to controls. Asterisks (*) indicate manuscripts that measured DA metabolites (e.g., homovanillic acid). Symbols: DA concentration is decreased ( Cells 10 02158 i001) or increased ( Cells 10 02158 i002) relative to controls. The equal sign ( Cells 10 02158 i003) indicates no statistically significant differences in DA concentration between HIV and controls.
ReferencesDA Concentration Relative to ControlsVirusBrain RegionSpeciesMethod
Larsson et al., 1991 [16] Cells 10 02158 i001HIVCSFHumanHPLC *
Berger et al., 1994 [14] Cells 10 02158 i001HIVCSFHumanHPLC
Sardar et al., 1996 [15] Cells 10 02158 i001HIVCaudate NucleusHumanHPLC
Di Rocco, 2000 [17] Cells 10 02158 i001HIVCSFHumanHPLC *
Czub et al., 2001 [181] Cells 10 02158 i001SIVHippocampusPrimateHPLC
Cells 10 02158 i001PFC
Cells 10 02158 i001Putamen
Koutsilieri, 2002 [182] Cells 10 02158 i001HIVStriatumPrimateHPLC
Jenuwein et al., 2004 [183] Cells 10 02158 i001SIVNAcPrimateHPLC
Scheller et al., 2005 [184] Cells 10 02158 i001SIVPutamenPrimateHPLC
Kumar et al., 2009 [28] Cells 10 02158 i001HIVCaudate NucleusHumanHPLC
Cells 10 02158 i001Globus Pallidus
Cells 10 02158 i001Putamen
Cells 10 02158 i001Substantia Nigra
Ferris et al., 2009 [185] Cells 10 02158 i001Tat ProteinStriatumRatMicrodialysis
Scheller et al., 2010 [174] Cells 10 02158 i002Early HIVCSFHumanHPLC
Kumar et al., 2011 [29] Cells 10 02158 i001HIVCaudate NucleusHumanHPLC
Cells 10 02158 i001Globus Pallidus
Cells 10 02158 i001Putamen
Cells 10 02158 i001Substantia Nigra
Kesby et al., 2016 [175] Cells 10 02158 i002Acute Tat ProteinCaudate PutamenMouseHPLC
Cells 10 02158 i003NAc
Cells 10 02158 i003Tat ProteinCaudate PutamenMouseHPLC
Cells 10 02158 i003NAc
Kesby et al., 2016 [178] Cells 10 02158 i003Acute Tat ProteinCaudate PutamenMouseHPLC
Cells 10 02158 i003Hippocampus
Cells 10 02158 i003PFC
Cells 10 02158 i003OFC
Horn et al., 2017 [186] Cells 10 02158 i003HIVCSFHumanHPLC
Javadi-Paydar et al., 2017 [187] Cells 10 02158 i001HIV-1 ProteinsNAcRatEx vivo slice voltammetry
Denton et al., 2019 [30] Cells 10 02158 i001HIV-1 ProteinsNAcRatFSCV
Saloner et al., 2020 [188] Cells 10 02158 i001HIVCSFHumanHPLC
Strauss et al., 2020 [176] Cells 10 02158 i002Acute Tat ProteinPFCMouseHPLC
Cells 10 02158 i003Striatum
Denton et al., 2021 [189] Cells 10 02158 i001HIV-1 ProteinsNAcRatFSCV
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

McLaurin, K.A.; Harris, M.; Madormo, V.; Harrod, S.B.; Mactutus, C.F.; Booze, R.M. HIV-Associated Apathy/Depression and Neurocognitive Impairments Reflect Persistent Dopamine Deficits. Cells 2021, 10, 2158. https://doi.org/10.3390/cells10082158

AMA Style

McLaurin KA, Harris M, Madormo V, Harrod SB, Mactutus CF, Booze RM. HIV-Associated Apathy/Depression and Neurocognitive Impairments Reflect Persistent Dopamine Deficits. Cells. 2021; 10(8):2158. https://doi.org/10.3390/cells10082158

Chicago/Turabian Style

McLaurin, Kristen A., Michael Harris, Victor Madormo, Steven B. Harrod, Charles F. Mactutus, and Rosemarie M. Booze. 2021. "HIV-Associated Apathy/Depression and Neurocognitive Impairments Reflect Persistent Dopamine Deficits" Cells 10, no. 8: 2158. https://doi.org/10.3390/cells10082158

APA Style

McLaurin, K. A., Harris, M., Madormo, V., Harrod, S. B., Mactutus, C. F., & Booze, R. M. (2021). HIV-Associated Apathy/Depression and Neurocognitive Impairments Reflect Persistent Dopamine Deficits. Cells, 10(8), 2158. https://doi.org/10.3390/cells10082158

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop