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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Neurosci.</journal-id>
<journal-title>Frontiers in Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1662-453X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnins.2018.00238</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Neuroscience</subject>
<subj-group>
<subject>Mini Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The Relationship Between Dopamine Neurotransmitter Dynamics and the Blood-Oxygen-Level-Dependent (BOLD) Signal: A Review of Pharmacological Functional Magnetic Resonance Imaging</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Bruinsma</surname> <given-names>Tyler J.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Sarma</surname> <given-names>Vidur V.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/469523/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Oh</surname> <given-names>Yoonbae</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Jang</surname> <given-names>Dong Pyo</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/79188/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Chang</surname> <given-names>Su-Youne</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/48434/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Worrell</surname> <given-names>Greg A.</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/7031/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Lowe</surname> <given-names>Val J.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/472721/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Jo</surname> <given-names>Hang Joon</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/7815/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Min</surname> <given-names>Hoon-Ki</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c002"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/150052/overview"/>
</contrib>
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<aff id="aff1"><sup>1</sup><institution>Department of Radiology, College of Medicine, Mayo Clinic</institution>, <addr-line>Rochester, MN</addr-line>, <country>United States</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota</institution>, <addr-line>Minneapolis, MN</addr-line>, <country>United States</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Biomedical Engineering, Hanyang University</institution>, <addr-line>Seoul</addr-line>, <country>South Korea</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Neurologic Surgery, College of Medicine, Mayo Clinic</institution>, <addr-line>Rochester, MN</addr-line>, <country>United States</country></aff>
<aff id="aff5"><sup>5</sup><institution>Departments of Physiology and Biomedical Engineering, Mayo Clinic</institution>, <addr-line>Rochester, MN</addr-line>, <country>United States</country></aff>
<aff id="aff6"><sup>6</sup><institution>Department of Neurology, College of Medicine, Mayo Clinic</institution>, <addr-line>Rochester, MN</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Sung Chan Jun, Gwangju Institute of Science and Technology, South Korea</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Lisa D. Nickerson, Harvard Medical School, United States; Frank Angenstein, Deutsche Zentrum f&#x000FC;r Neurodegenerative Erkrankungen (DZNE), Germany</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Hang Joon Jo <email>jo.hang&#x00040;mayo.edu</email></corresp>
<corresp id="c002">Hoon-Ki Min <email>min.paul&#x00040;mayo.edu</email></corresp>
<fn fn-type="other" id="fn003"><p>This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience</p></fn></author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>04</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="collection">
<year>2018</year>
</pub-date>
<volume>12</volume>
<elocation-id>238</elocation-id>
<history>
<date date-type="received">
<day>31</day>
<month>07</month>
<year>2017</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>03</month>
<year>2018</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2018 Bruinsma, Sarma, Oh, Jang, Chang, Worrell, Lowe, Jo and Min.</copyright-statement>
<copyright-year>2018</copyright-year>
<copyright-holder>Bruinsma, Sarma, Oh, Jang, Chang, Worrell, Lowe, Jo and Min</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract><p>Functional magnetic resonance imaging (fMRI) is widely used in investigations of normal cognition and brain disease and in various clinical applications. Pharmacological fMRI (pharma-fMRI) is a relatively new application, which is being used to elucidate the effects and mechanisms of pharmacological modulation of brain activity. Characterizing the effects of neuropharmacological agents on regional brain activity using fMRI is challenging because drugs modulate neuronal function in a wide variety of ways, including through receptor agonist, antagonist, and neurotransmitter reuptake blocker events. Here we review current knowledge on neurotransmitter-mediated blood-oxygen-level dependent (BOLD) fMRI mechanisms as well as recently updated methodologies aimed at more fully describing the effects of neuropharmacologic agents on the BOLD signal. We limit our discussion to dopaminergic signaling as a useful lens through which to analyze and interpret neurochemical-mediated changes in the hemodynamic BOLD response. We also discuss the need for future studies that use multi-modal approaches to expand the understanding and application of pharma-fMRI.</p></abstract>
<kwd-group>
<kwd>dopamine</kwd>
<kwd>BOLD</kwd>
<kwd>fMRI</kwd>
<kwd>pharma-fMRI</kwd>
<kwd>fast-scan cyclic voltammetry</kwd>
</kwd-group>
<contract-num rid="cn001">R01 NS088260</contract-num>
<contract-num rid="cn001">R01 NS092882</contract-num>
<contract-sponsor id="cn001">National Institutes of Health<named-content content-type="fundref-id">10.13039/100000002</named-content></contract-sponsor>
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<fig-count count="2"/>
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<ref-count count="91"/>
<page-count count="8"/>
<word-count count="6957"/>
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</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are used in both basic and clinical research as an indicator of brain health, structurally and dynamically. In fMRI the most common measurement for evaluating changes in functional brain activity is the blood-oxygen-level dependent (BOLD) signal (Ogawa et al., <xref ref-type="bibr" rid="B65">1990</xref>; Bandettini et al., <xref ref-type="bibr" rid="B10">1992</xref>), and in PET it is the cerebral metabolic rate for glucose (CMRglc) (Phelps et al., <xref ref-type="bibr" rid="B71">1979</xref>). Both depend on mapping energy expenditure during pre- and postsynaptic neuronal signaling, events that lead to a rapid need for oxygen and glucose from the vascular system (Attwell and Laughlin, <xref ref-type="bibr" rid="B8">2001</xref>).</p>
<p>In fMRI, BOLD changes have been associated with local field potentials that comprise pre- and post-synaptic signals from synapses and dendrites (Logothetis et al., <xref ref-type="bibr" rid="B51">2001</xref>; see Heeger and Ress, <xref ref-type="bibr" rid="B31">2002</xref> for full review on the association between fMRI and neuronal activity). A quantitative relationship between the cycling of certain neurotransmitters (e.g., glutamate) and the BOLD signal has been well defined. This relationship is considered a major factor in the BOLD signal (Shulman and Rothman, <xref ref-type="bibr" rid="B84">1998</xref>; Magistretti et al., <xref ref-type="bibr" rid="B55">1999</xref>; Rothman et al., <xref ref-type="bibr" rid="B76">1999</xref>) and is reliant on a tightly coupled relationship between synaptic activity and glucose uptake (Pellerin and Magistretti, <xref ref-type="bibr" rid="B69">1994</xref>; Takahashi et al., <xref ref-type="bibr" rid="B86">1995</xref>). The control of blood flow in the brain by neurons and astrocytes in glutamatergic transmitter systems has been reviewed in a greater detail by (Attwell et al., <xref ref-type="bibr" rid="B6">2010</xref>).</p>
<p>In this mini review, we focus on the dopamine (DA) neurotransmitter-signaling pathway and include in our discussion current theories on how DA affects hemodynamic change and the potential of multi-modal methodological approaches to more comprehensively describe dopaminergic-related hemodynamic mechanisms.</p>
</sec>
<sec id="s2">
<title>Pharmacological fMRI (pharma-fMRI)</title>
<p>Neuroimaging has afforded new opportunities to assess the effects of drug interventions in the human brain, including serial, single-subject longitudinal studies. However, because pharmaceutical agents modulate neuronal activities in a variety of ways, imaging studies of the effects of neurochemical induced changes remain challenging. Receptor agonist, antagonist, and neurotransmitter reuptake blocker events translate to diverse and often poorly understood alterations in mental and physical states. PET has been considered the gold standard for molecular imaging because it can assess the binding of radioactive tracers to selected receptor targets and can provide quantitative information on the binding, receptor occupancy, and regional brain distribution of targeted pharmaceuticals (Nguyen et al., <xref ref-type="bibr" rid="B64">2000</xref>; Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>; Lu et al., <xref ref-type="bibr" rid="B53">2014</xref>).</p>
<p>More recently, pharmacological fMRI (pharma-fMRI) has been considered an alternative or complimentary means of assessing the neural mechanisms of drug action (Wise and Tracey, <xref ref-type="bibr" rid="B90">2006</xref>; Iannetti and Wise, <xref ref-type="bibr" rid="B35">2007</xref>; Khalili-Mahani et al., <xref ref-type="bibr" rid="B38">2017</xref>). Over the past decade, sophisticated pharma-fMRI methodologies have evolved for measuring hemodynamic changes by the BOLD signal or, in more advanced applications, by measuring cerebral blood volume (CBV) and arterial spin labeling (ASL) MRI sequences (Mandeville et al., <xref ref-type="bibr" rid="B57">2001</xref>; Wang et al., <xref ref-type="bibr" rid="B88">2011</xref>; Lu et al., <xref ref-type="bibr" rid="B53">2014</xref>; see Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>) for review of the mechanism and applications of pharmacologic MRI, which includes a broader scope of the methodology than pharma-fMRI.</p>
<p>Several representative strengths of pharma-fMRI that complement PET include: (1) a relatively high spatial and temporal resolution; (2) elimination of the need for a radioactive tracer, making it less invasive and expensive than PET; and (3) increased flexibility in study design (Khalili-Mahani et al., <xref ref-type="bibr" rid="B38">2017</xref>), including functional connectivity studies (Khalili-Mahani et al., <xref ref-type="bibr" rid="B39">2012</xref>; Lu and Stein, <xref ref-type="bibr" rid="B54">2014</xref>) (see Figure <xref ref-type="fig" rid="F1">1A</xref>).</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p><bold>(A)</bold> Pharma-fMRI study designs. Pharma-fMRI is usually performed under three experimental designs: <bold>(a)</bold> The red line shows the pharmacodynamics model of a drug (morphine) (Khalili-Mahani et al., <xref ref-type="bibr" rid="B38">2017</xref>). <bold>(b)</bold> Task-based pharma-fMRI analyzes a behavioral event at baseline and while the drug is under effect (Iannetti and Wise, <xref ref-type="bibr" rid="B35">2007</xref>; Borsook et al., <xref ref-type="bibr" rid="B14">2008</xref>); <bold>(c)</bold> continuous collection of fMRI over the course of drug infusion followed by analysis of the change in BOLD signal from pre-drug baseline (Bloom et al., <xref ref-type="bibr" rid="B12">1999</xref>; De Simoni et al., <xref ref-type="bibr" rid="B24">2013</xref>); and <bold>(e)</bold> pharmacological resting-state fMRI (pharma-RSfMRI) which examines several short resting-state intervals over the course of drug administration and compares network property changes across different phases of the pharmacokinetic profile (Khalili-Mahani et al., <xref ref-type="bibr" rid="B39">2012</xref>; Lu and Stein, <xref ref-type="bibr" rid="B54">2014</xref>). Diagram reprinted with permission from Khalili-Mahani et al. (<xref ref-type="bibr" rid="B38">2017</xref>). <bold>(B)</bold> DA neurotransmitter dynamics and hemodynamic response. A schematic of showing the possible factors affecting the link between DA neurotransmitter dynamics and the hemodynamic response (Concept adopted from Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>). Since there are no known voltage-gated vascular receptors, the mechanism by which neurotransmitter release and uptake leads to signaling and release of vasoactive molecules remains unknown, noted here as the &#x0201C;black box&#x0201D; (Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>). Recent updates on DA pathway mechanisms demonstrate a complex release pattern having both phasic and tonic states, dynamically modifying the basal tone of neuronal activity, as seen in disease or drug-induced states (Owesson-White et al., <xref ref-type="bibr" rid="B68">2009</xref>; Grace, <xref ref-type="bibr" rid="B27">2016</xref>). The phasic DA response in the upper left color map is from electrically stimulating (2 s) the nigrostriatal pathway and conducting neurochemical analysis in the caudate, which was confirmed by fMRI in a within subject study of a non-human primate (Min et al., <xref ref-type="bibr" rid="B62">2016</xref>). Each electrochemical signal was converted to molar (M) concentration showing the difference from baseline to an electrically evoked response. The tonic DA response in the lower left color map is from systematic administration of nomifensine, a DA transporter reuptake blocker, and recording the electrochemical response in striatum over a time period of 2 h in rodents (Oh et al., <xref ref-type="bibr" rid="B66">2016</xref>). Other factors are discussed in the current review, including DA receptor family type specific effects, brain area specificity, and DA integration with other neurotransmitters. Finally, neuronal activity would influence vasoactive substances (NO, K<sup>&#x0002B;</sup>) and metabolic by-products (Adenosine, H<sup>&#x0002B;</sup>, CO<sub>2</sub>) affecting the local hemodynamic response.</p></caption>
<graphic xlink:href="fnins-12-00238-g0001.tif"/>
</fig>
<p>There are numerous pharma-fMRI applications that are useful for studying the DA signal pathway, including DA cell lesion studies and receptor-type dependent agonist and antagonist studies (Chen et al., <xref ref-type="bibr" rid="B18">1997</xref>; Takahashi et al., <xref ref-type="bibr" rid="B85">2005</xref>). Recent updates on DA pathway mechanisms demonstrate a complex release pattern having both phasic and tonic states, dynamically modifying the basal tone of neuronal activity (Owesson-White et al., <xref ref-type="bibr" rid="B68">2009</xref>; Grace, <xref ref-type="bibr" rid="B27">2016</xref>; Oh et al., <xref ref-type="bibr" rid="B66">2016</xref>). Disruption of this dynamic state of neuronal activity is a major mechanism of disease states and of neuropharmacological treatment regimens, which highlights the importance of studying neurotransmitter mechanisms when assessing hemodynamic changes (Grace, <xref ref-type="bibr" rid="B27">2016</xref>). Thus, to properly interpret pharma-fMRI results, a more complete understanding of the relationship between the DA signaling pathway and the BOLD signal is needed. Figure <xref ref-type="fig" rid="F1">1B</xref> summarizes presently unexplained aspects of the relationship between fMRI/pharma-fMRI and electrophysiology, metabolism, and vasoactive molecule release (Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>).</p>
</sec>
<sec id="s3">
<title>Dopamine neurotransmitter dynamics and hemodynamic response</title>
<p>Studies investigating DA release kinetics typically operate on the principle of targeting cell surface DA receptors (D1-like or D2-like) with a PET contrast agent tagged to competing ligands of interest. For example, Koepp et al. (<xref ref-type="bibr" rid="B44">1998</xref>) found that PET imaging of D2/D3 receptor occupancy following administration of <sup>11</sup>C-raclopride, a selective D2/D3 antagonist, showed that binding of <sup>11</sup>C-raclopride is significantly decreased in the brains of video game playing human subjects as a consequence of reward-induced DA release. Similarly, challenging endogenous DA with administered DA conjugated to PET contrast agents is a method of assessing task-induced changes in DA release in the human brain (Badgaiyan, <xref ref-type="bibr" rid="B9">2014</xref>). While PET is sensitive to neurochemical activity and neurotransmission, it is limited by its temporal and spatial resolution. It fails to provide insights into functional correlates of neural activity associated with DA neurotransmitter dynamics since it is also influenced in a complex manner by the abundance of target receptors and the amount of neurotransmitter release.</p>
<p>Functional correlates of neural activity linked to DA release from reward areas in the brain have also been assessed in fMRI studies (Knutson et al., <xref ref-type="bibr" rid="B42">2001</xref>). Studies in rats link DA release and either BOLD or CBV signals in temporal brain regions following stimulation with amphetamine (AMPH), which is known to induce the release of DA (Chen et al., <xref ref-type="bibr" rid="B18">1997</xref>, <xref ref-type="bibr" rid="B19">1999</xref>, <xref ref-type="bibr" rid="B17">2005</xref>; Choi et al., <xref ref-type="bibr" rid="B20">2006</xref>).</p>
<p>Several key factors may contribute to the observed coupling of DA release and the brain&#x00027;s hemodynamic response. The DA-mediated pharma-fMRI response can largely be explained in terms of receptor occupancies. For example, there is a positive correlation between DA displacements (PET) and fMRI in the ventral striatum and nucleus accumbens (NAc) in a behavioral task that evoked dopaminergic circuits from the substantia nigra (SN) and ventral tegmental area (VTA) (Pessiglione et al., <xref ref-type="bibr" rid="B70">2006</xref>; Knutson and Gibbs, <xref ref-type="bibr" rid="B43">2007</xref>; Schott et al., <xref ref-type="bibr" rid="B80">2008</xref>). Lesion studies show that pharma-fMRI detects severe DA lesions in animals with sensitivity similar to that of PET (Chen et al., <xref ref-type="bibr" rid="B19">1999</xref>; Schrantee and Reneman, <xref ref-type="bibr" rid="B81">2014</xref>). Simultaneous PET/fMRI in non-human primate (NHP) enabled mapping of an association between DA release and neurovascular coupling (Sander et al., <xref ref-type="bibr" rid="B77">2013</xref>). The potential for a temporal discrepancy between receptor occupancy and hemodynamic changes due to a phenomenon of receptor internalization and desensitization was found using the D2/D3 agonist quinpirole (Sander et al., <xref ref-type="bibr" rid="B78">2016</xref>). Reports also show D3 agonist-induced CBV change to be a good match with D3 receptor mRNA expression (Choi et al., <xref ref-type="bibr" rid="B21">2010</xref>). In another report, the administration of a graded dose of AMPH found that DA measured by microdialysis was linearly correlated with cyclic adenosine monophosphate (cAMP) levels as well as induced-CBV in the striatum of rats (Ren et al., <xref ref-type="bibr" rid="B73">2009</xref>).</p>
<p>An important aspect of DA dynamics is the fact that D1-like family and D2-like family receptors have differing effects on activation and inhibition, respectively. Activation of the D1-like family receptors increases cAMP and induces excitatory signal transduction, and D2-like family receptors subsequently decrease cAMP, leading to an inhibitory effect in neurons (Schinelli et al., <xref ref-type="bibr" rid="B79">1994</xref>). D3 receptor agonist, which is a D2-like category inhibitory receptor, shows negative changes in CBV, whereas the antagonist shows positive changes in CBV (Choi et al., <xref ref-type="bibr" rid="B21">2010</xref>). This fact adds an additional layer of complexity to the DA-mediated hemodynamic response. For example, large increases in DA can inhibit the hemodynamic response. D1 receptors are responsible for an increase of hemodynamic response while D2 receptors are responsible for a decrease of hemodynamic response (Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>).</p>
<p>This relationship between the effects of receptor type (D1-like vs. D2-like) and hemodynamic response has been modeled by independently activating D1 and D2 receptors via cocaine, which is a DA transporter blocker, or via AMPH, which is an endogenous DA releaser (Mandeville et al., <xref ref-type="bibr" rid="B59">2013</xref>). Studies, using AMPH and other pharmaceuticals to induce differential activation of DA receptors may assist in future work examining the intersection of DA and fMRI/pharma-fMRI BOLD responses. DA demonstrates a higher affinity for D2 receptors than D1 receptors (Richfield et al., <xref ref-type="bibr" rid="B74">1989</xref>). D1 receptor activation is dominant in higher doses of AMPH, whereas the high affinity of DA for D2 receptors is expected to drive the response at lower doses. Negative CBV is evident with low doses of DA, but an increasingly higher positive CBV is observed with higher amounts of AMPH (Ren et al., <xref ref-type="bibr" rid="B73">2009</xref>). There is also a species specific difference related to the D1 to D2 receptor ratio in that rats have a higher ratio of D1 to D2 receptors than NHP (Cumming, <xref ref-type="bibr" rid="B22">2011</xref>) and thus exhibit higher positive CBV responses at high doses of DA inducing drugs than do NHP (Mandeville et al., <xref ref-type="bibr" rid="B56">2011</xref>, <xref ref-type="bibr" rid="B59">2013</xref>). Computational modeling studies add weight to these findings (Mandeville et al., <xref ref-type="bibr" rid="B59">2013</xref>, <xref ref-type="bibr" rid="B58">2014</xref>; Bruns et al., <xref ref-type="bibr" rid="B15">2015</xref>). Receptor-based models of neurovascular coupling, incorporating receptor densities and affinities along with biophysical constraints, have demonstrated compelling descriptions of pharma-fMRI signals induced by dopaminergic stimuli (Mandeville et al., <xref ref-type="bibr" rid="B58">2014</xref>). Mandeville et al. (<xref ref-type="bibr" rid="B59">2013</xref>) which confirms this model showing inhibition in fMRI at low dose of AMPH but biphasic response at higher doses in the basal ganglia of NHP (Mandeville et al., <xref ref-type="bibr" rid="B59">2013</xref>).</p>
<p>Optogenetics is a technology that combines genetic and optical methods to control the excitatory or inhibitory pathway of targeted cells. Due to its high specificity and selectivity, optogenetics has been applied extensively to investigate functional circuitries in animal brains (Gradinaru et al., <xref ref-type="bibr" rid="B28">2009</xref>; Lee, <xref ref-type="bibr" rid="B49">2012</xref>). When applying DA cell specific optogenetic stimulation on VTA, DA neurons are activated, and the BOLD response occurs in both the VTA-innervated limbic regions, including the ventral striatum (NAc), and in non-VTA regions, including the dorsal striatum and the globus pallidus (Lohani et al., <xref ref-type="bibr" rid="B52">2017</xref>). Another study conducting both direct electrical stimulation and optogenetic stimulation (targeting only DA cells) of the VTA have found to cause DA release in NAc, but only electrical stimulation has triggered significant BOLD responses in the medial prefrontal/anterior cingulate cortex and NAc (Helbing et al., <xref ref-type="bibr" rid="B32">2016</xref>). Further glutaminergic N-methyl-D-aspartate receptor antagonist reduced the BOLD response by VTA electrical stimulation (Helbing et al., <xref ref-type="bibr" rid="B32">2016</xref>). Given these discrepancies that exist depending on methods of stimulation in studies of DA-engendered BOLD responses, a novel framework to understand neurotransmitter-dependent BOLD functions is necessary. Such a framework could lead to innovative interpretations of the pharma-fMRI data obtained from human studies.</p>
</sec>
<sec id="s4">
<title>Dopamine and neurovascular coupling</title>
<p>The fMRI signal cannot be interpreted exclusively in terms of neuronal activation. Neurovascular coupling, a process partially mediated by non-neuronal processes, must also be taken into account. Ultimately, hemodynamic changes are related to the release of vasoactive substances coupled to neurotransmitter activity, such as nitric oxide (NO), adenosine, and potassium cations (K<sup>&#x0002B;</sup>) (Attwell and Iadecola, <xref ref-type="bibr" rid="B7">2002</xref>). In glutamatergic neurons, calcium influxes in postsynaptic neuron activities and in astrocyte activities during reuptake produce NO, adenosine and arachidonic acid metabolites (Attwell and Iadecola, <xref ref-type="bibr" rid="B7">2002</xref>). In DA neurons, the uptake of DA occurs pre-synaptically and is not calcium dependent, although the DA release is, which implies that DA would not have the same neurovascular coupling as glutamate (Jenkins, <xref ref-type="bibr" rid="B37">2012</xref>). While the fMRI signal through glutamatergic sensory stimulation could be blocked by NO synthase inhibition (Burke and B&#x000FC;hrle, <xref ref-type="bibr" rid="B16">2006</xref>), DA-evoked CBV through DA transporter blocker and D1 agonist was not sensitive to NO synthase inhibition (Choi et al., <xref ref-type="bibr" rid="B20">2006</xref>).</p>
<p>DA neurons have been reported to directly innervate the intraparenchymal vessels in the cortex causing vasoconstriction as confirmed by histology and <italic>in vitro</italic> brain slices (Krimer et al., <xref ref-type="bibr" rid="B46">1998</xref>). However, in the striatum, endogenous DA did not affect local blood flow, as the stimulation-evoked oxygen signal remains the same by DA synthesis blocker measured by fast-scan cyclic voltammetry (FSCV) (Zimmerman and Wightman, <xref ref-type="bibr" rid="B91">1991</xref>).</p>
<p>Due to the ability of FSCV to simultaneously detect tissue diffused oxygen and extra-cellular DA responses in electrochemistry studies (Zimmerman and Wightman, <xref ref-type="bibr" rid="B91">1991</xref>), correlations between extracellular oxygen and pH change have been reported to have a relationship with DA (Venton et al., <xref ref-type="bibr" rid="B87">2003</xref>). Reports show that SN/VTA electrical stimulation evokes DA in the striatum as well as tissue diffused oxygen, which has two peaks (biphasic) within a 30 s timeframe as measured by millisecond temporal resolution of FSCV (Zimmerman and Wightman, <xref ref-type="bibr" rid="B91">1991</xref>; Venton et al., <xref ref-type="bibr" rid="B87">2003</xref>). Venton et al. (<xref ref-type="bibr" rid="B87">2003</xref>) further reports that NO and adenosine partially effect the first and second oxygen peak, respectively, independent of DA change (Venton et al., <xref ref-type="bibr" rid="B87">2003</xref>). In addition both oxygen peaks are reduced by carbonic anhydrase inhibitor, which implies that the hemodynamic response for dopaminergic circuit stimulation relies on CO<sub>2</sub> washout, which produces H<sup>&#x0002B;</sup> as a byproduct (Huang et al., <xref ref-type="bibr" rid="B34">1995</xref>).</p>
</sec>
<sec id="s5">
<title>Multi-modal methodological approaches</title>
<p>Recent improvements in FSCV to correct for nonspecific signal drifting report reliable measurement of both phasic and tonic extracellular DA changes (Atcherley et al., <xref ref-type="bibr" rid="B4">2013</xref>, <xref ref-type="bibr" rid="B5">2015</xref>; Oh et al., <xref ref-type="bibr" rid="B66">2016</xref>). This is important given the complexity of the relationship between DA neural dynamics and fMRI which is highlighted by reports showing an association between cell-firing rate and phasic/tonic DA concentration in extracellular space. In general, cell-firing rates can induce two distinct patterns of DA release. DA neurons in the midbrain fire at 1&#x02013;5 Hz, which controls tonic, levels of DA that are capable of occupying high-affinity D2 receptors in terminal regions of the mesolimbic system. DA neurons firing at relatively high-frequency bursts (&#x0003E;20 Hz) lead to much larger amounts of phasic DA release that are capable of occupying low-affinity D1 receptors in a short time period (Grace, <xref ref-type="bibr" rid="B26">1991</xref>; Phillips et al., <xref ref-type="bibr" rid="B72">2003</xref>; Dreyer et al., <xref ref-type="bibr" rid="B25">2010</xref>). Typically, bursting activity of DA neurons over brief periods (&#x0003C;300 ms) is associated with reward mechanisms in NHP under the modulation of glutamatergic and cholinergic inputs (Gronier and Rasmussen, <xref ref-type="bibr" rid="B30">1998</xref>; Schultz, <xref ref-type="bibr" rid="B82">1998</xref>; Kitai et al., <xref ref-type="bibr" rid="B41">1999</xref>). Tonic levels of DA are modulated by presynaptic limbic and cortical glutamatergic inputs in addition to DA neuronal signals (Grace, <xref ref-type="bibr" rid="B26">1991</xref>; Howland et al., <xref ref-type="bibr" rid="B33">2002</xref>).</p>
<p>Implanting electrical, optogenetic, or drug infusion probes through stereotactic surgery and measuring the local phasic and tonic DA response by FSCV and the global response by fMRI offers a unique combination of modalities to tease apart pre- and post-synaptic-specific effects. At present, few fMRI studies have addressed this issue. However, as in electrophysiology recordings, FSCV recordings require implanting a sensing electrode into brain tissue and probing to get a signal, sometimes referred to as the DA-hotspot in striatum, which connects to a specific DA circuit or behavioral task (McCutcheon et al., <xref ref-type="bibr" rid="B60">2012</xref>; Kruss et al., <xref ref-type="bibr" rid="B48">2017</xref>). Moreover, the basal ganglia and striatum have functional territories related to motor, limbic, and associative functions (Graybiel et al., <xref ref-type="bibr" rid="B29">1994</xref>; Krack et al., <xref ref-type="bibr" rid="B45">2010</xref>; Min et al., <xref ref-type="bibr" rid="B61">2012</xref>), which makes the specificity of stimulation site and recording site all the more important (Kringelbach et al., <xref ref-type="bibr" rid="B47">2007</xref>; Da Cunha et al., <xref ref-type="bibr" rid="B23">2015</xref>). To identify the DA-specific recording site for FSCV in NHP, Min et al. (<xref ref-type="bibr" rid="B62">2016</xref>) used a combination of FSCV and fMRI, electrically stimulating the nigrostriatal pathway and measuring global response using fMRI (Min et al., <xref ref-type="bibr" rid="B62">2016</xref>). Using the fMRI responses in caudate and putamen evoked by electrical stimulation of the subthalamic nucleus, they found that fMRI can be used to identify DA-specific FSCV recording sites. Similarly Settell et al. (<xref ref-type="bibr" rid="B83">2017</xref>) used fMRI BOLD responses in the NAc while stimulating VTA to confirm neurochemical recording of DA in NAc (Settell et al., <xref ref-type="bibr" rid="B83">2017</xref>).</p>
<p>Optogenetic stimulation evoked DA in specific brain circuits has also been measured by FSCV (Bass et al., <xref ref-type="bibr" rid="B11">2010</xref>; Adamantidis et al., <xref ref-type="bibr" rid="B1">2011</xref>), and there are other reports of combining optogenetic stimulation with fMRI (Gradinaru et al., <xref ref-type="bibr" rid="B28">2009</xref>; Lee, <xref ref-type="bibr" rid="B49">2012</xref>), but to our knowledge, there are no reports of combining optogenetic stimulation with both FSCV and fMRI. Of note, several studies suggest that optogenetic and electrical stimulation of an identical structure can cause fundamentally different neuronal activation patterns as measured by BOLD (Ohayon et al., <xref ref-type="bibr" rid="B67">2013</xref>; Albaugh et al., <xref ref-type="bibr" rid="B2">2016</xref>). The combination of fMRI and FSCV to measure circuit specific stimulation via optogenetic and via electrical stimulation would provide new insights, especially given that optogenetic stimulation may generate greater pre-synaptic selectivity than electrical stimulation (see Figure <xref ref-type="fig" rid="F2">2A</xref>).</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Examples of new multi-modal study designs and concepts in large animal (swine) brain diagram: <bold>(A)</bold> Presynaptic-specific effect. Optogenetics enables cell-type specific stimulation, and the fMRI signal induced by stimulation would provide insight into presynaptic-specific effects on BOLD (Albaugh et al., <xref ref-type="bibr" rid="B2">2016</xref>; Helbing et al., <xref ref-type="bibr" rid="B32">2016</xref>; Lohani et al., <xref ref-type="bibr" rid="B52">2017</xref>) along with electrochemical information; <bold>(B)</bold> Postsynaptic-specific effect. Electrical stimulation of a specific pathway forces non-specific activity to the neuronal circuit involving all cell-types near the electrode (Kringelbach et al., <xref ref-type="bibr" rid="B47">2007</xref>), combined with electrode-metal induced susceptibility artifact corrected fMRI (In et al., <xref ref-type="bibr" rid="B36">2017</xref>). Administering receptor antagonists along the stimulated pathway enables the evaluation of receptor-specific effects on BOLD (Ross et al., <xref ref-type="bibr" rid="B75">2016</xref>); <bold>(C)</bold> Circuit-specific drug effect. Popular in animal studies, brain circuit-specific intracranial drug injection (Wise and Hoffman, <xref ref-type="bibr" rid="B89">1992</xref>; Kim et al., <xref ref-type="bibr" rid="B40">2014</xref>) combined with fMRI, could open new possibilities for studying circuit-specific neurotransmitter (agonist) effects on BOLD by limiting the involvement of presynaptic dynamics.</p></caption>
<graphic xlink:href="fnins-12-00238-g0002.tif"/>
</fig>
<p>Intracranial micro-infusions is another often used means of causing brain circuit-specific drug effect (Wise and Hoffman, <xref ref-type="bibr" rid="B89">1992</xref>). Since DA receptors can also be found in the pancreas, kidneys, and blood vessels outside the brain, DA could, for example, cause vasodilation in the heart (Missale et al., <xref ref-type="bibr" rid="B63">1998</xref>). Thus, intracranial micro-infusion could avoid such systemic blood flow changes that could influence fMRI results. Intracranial micro-infusions of a specific receptor antagonist (i.e., D1-like or D2-like) at specific brain sites during a stimulation-induced signaling cascade could be used to discriminate receptor-type specific post-synaptic effects (See Figure <xref ref-type="fig" rid="F2">2B</xref>). Using micro-infusion and BOLD fMRI has been reported in a swine model, showing that Fornix stimulation transmits a dopaminergic and glutaminergic specific response through NAc, affecting prefrontal cortex, amygdala and hippocampus (Ross et al., <xref ref-type="bibr" rid="B75">2016</xref>). Borland and Michael (<xref ref-type="bibr" rid="B13">2004</xref>) also showed a decrease of tonic DA release in the rat striatum by intrastriatal infusion of kynurenic acid, a broad-spectrum antagonist of the ionotropic glutamate receptors (Borland and Michael, <xref ref-type="bibr" rid="B13">2004</xref>). There is also a recent report of chronic adaptation to an intracranial micro-infusion drug system that could be implanted through stereotactic surgery in the large animal brain (swine) (Kim et al., <xref ref-type="bibr" rid="B40">2014</xref>). Micro-infusion-induced DA changes (i.e., through DA agonist) and related changes in the BOLD signal can be used together to identify brain site- and neurotransmitter-specific neuronal activity (see Figure <xref ref-type="fig" rid="F2">2C</xref>).</p>
<p>The use of nanoparticles to more directly detect DA is a new approach on the horizon (Lee et al., <xref ref-type="bibr" rid="B50">2014</xref>). Nanoparticle contrast agents that generate signals based on interactions with endogenously released DA have been introduced for MRI (Kim et al., <xref ref-type="bibr" rid="B40">2014</xref>). The MRI intensity can be modulated based on magnetic field strength or certain properties of the reporter agent such as proton relaxivity and the chemical exchange saturation transfer effect. Bioresponsive contrast agents can be synthesized by engineered metalloproteins or by creating artificial host receptors, which derive from principles of supramolecular host-guest chemistry (Angelovski and T&#x000F3;th, <xref ref-type="bibr" rid="B3">2017</xref>).</p>
</sec>
<sec id="s6">
<title>Summary and future directions</title>
<p>As fMRI and pharma-fMRI continue to expand in application, there is increasing need for a better understanding of the mechanisms by which neurochemical changes induced by pharmacologic agents affect the BOLD signal. The complexity of neurotransmitter dynamics requires sophisticated experimental designs. Several emerging methodologies that enable selective modulation of the presynaptic and postsynaptic pathways relative to neurotransmitter and receptor function detection and manipulation have been reviewed here. By examining these effects through the lens of DA dynamics, studies would be better positioned to address drug-induced neuronal and neurochemical changes relative to the BOLD signal. While each of the methodologies mentioned are readily available, future research is needed to expand the utility of combining these technologies so as to make multi-modality platforms more accessible in investigations of the effects of pharmacological agents on the BOLD signal in pharma-fMRI.</p>
</sec>
<sec id="s7">
<title>Author contributions</title>
<p>Designed framework and idea: HJ and H-KM. Drafted and critically reviewed the manuscript: TB, VS, YO, DJ, S-YC, GW, VL, HJ, H-KM.</p>
<sec>
<title>Conflict of interest statement</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
</sec>
</body>
<back>
<ack><p>This work was supported by the National Institutes of Health (NIH R01 NS088260 to S-YC and NIH R01 NS92882 to GW). We thank Dr. Penelope S. Duffy for her editorial contributions and review.</p>
</ack>
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