Chapter 3Neurochemistry of Addiction

3.1. INTRODUCTION AND SCOPE

Developments in chemical monitoring have provided the neuroscientist with a powerful toolbox for investigating biological mechanisms of drug addiction. Indeed, by sampling time-dependent changes in neurotransmitters in situ, these techniques have contributed prominently to our understanding of the neural substrates of goal-directed behavior and how drugs of abuse alter the functioning of these neural systems and ultimately cause addiction. Historically, chemical monitoring in the central nervous system has been dominated by voltammetry and microdialysis. Fundamentally different in analytical strategy, voltammetry and microdialysis bring distinct strengths and weaknesses to neurotransmitter measurements.

Although this chapter introduces principles of voltammetry and microdialysis and provides a brief historical perspective of these two techniques, the primary focus is newer technologies emerging in the last decade or so. Admittedly, and at the risk of bias, most coverage is devoted to recent advances in voltammetry. The reason is straightforward: While conventional microdialysis has remained the workhorse technique for this sampling approach in the modern era of chemical monitoring, the field of voltammetry has been revolutionized by the emergence of the so-called “real-time” techniques monitoring neurotransmitter with subsecond temporal resolution. Originally developed in a few laboratories, these rapid sampling techniques now have become more widely adopted and have supported diverse applications. To provide a flavor for new developments outside voltammetry, recent advances in microdialysis and in a technique related to voltammetry, enzyme-linked biosensors, are also described. Although clearly exciting and important for the future of chemical monitoring, these developments have yet to reach broad adoption beyond the laboratory of origin, and as a result, applications have been more limited to date. Hence, coverage of microdialysis and enzyme-linked biosensors is less extensive and more general than voltammetry.

To illustrate new developments in the field of chemical monitoring, applications focus on four neurotransmitters/modulators, dopamine, GABA, glutamate, and neuropeptides, established as playing essential roles in addiction (Kalivas and Volkow 2005; Wise 2005; Hyman 2005). As such, this chapter highlights the rapid sampling voltammetric techniques of amperometry, high-speed chronoamperometry and fast-scan cyclic voltammetry for monitoring dopamine. All four analytes are amenable to microdialysis, and emphasis here is placed on capillary liquid chromatography and capillary electrophoresis for separation, and laser-induced fluorescence and mass spectrometry for detection. Finally, recent advances in enzyme-linked biosensors are described for measuring glutamate. Application of these techniques to other neurotransmitters is also noted.

3.2. PRINCIPLES OF VOLTAMMETRY AND MICRODIALYSIS

Several excellent reviews are available for voltammetry (e.g., Justice 1987; Marsden et al. 1988; Stamford 1989; Adams 1990; Kawagoe et al. 1993; Blaha and Phillips 1996) and microdialysis (e.g., Benveniste and Hansen 1991; Ungerstedt 1991; Justice 1993; Westerink 1995; Watson et al. 2006). The entire list is long, and only a few are referenced above. Collectively, this literature details technical aspects, practical considerations, history of development, applications, and of course, limitations and controversies. The reader is encouraged to examine the broader literature in order to augment the necessarily more limited coverage provided here.

3.2.1. General Principles

Four analytical characteristics are important when considering chemical monitoring in the brain: sensitivity, selectivity, speed, and size. Generally speaking, voltammetry exhibits better temporal and spatial resolution, whereas microdialysis is more sensitive and selective. Microdialysis is additionally more versatile, with a greater capability for monitoring multiple analytes and a more diverse set of analytes. Distinct analytical characteristics reflect fundamental differences in the manner in which chemical monitoring is achieved.

The superior sensitivity, selectivity and versatility of microdialysis directly result from independent analysis of a sample distal to collection at the probe. Indeed, powerful analytical methods have been coupled to microdialysis. By contrast, all chemical information regarding analyte identity and quantity is collected by the voltammetric probe itself while implanted. This strategy ultimately places restrictions on sensitivity and selectivity, as well as the chemical species amenable to detection. On the other hand, the sampling strategy of voltammetry permits fast measurements and small size, hence the superior temporal and spatial resolution.

A variety of voltammetric approaches have been developed over the years for chemical monitoring in brain tissue. All share a common principle: An electrical potential is applied to the electrode, and the resulting current is measured. Current consists of charging and faradaic components. Charging current is an unwanted signal generated by capacitance at the electrode-solution interface. The electrochemical signal of interest, faradaic current, results from analyte oxidation (i.e., loss of electrons) or reduction (i.e., gain of electrons) and is proportional to the number of molecules electrolyzed. An instrument known as a potentiostat applies voltage and concomitantly measures current. Several neurochemicals are electroactive and are thus amenable to detection by voltammetry. These include the monoamines, dopamine, norepinephrine, and serotonin and their metabolites, ascorbic acid, oxygen, hydrogen peroxide, and nitric oxide (Justice 1987; Borland and Michael 2007).

The voltammetric measurement of dopamine is conceptually shown in Figure 3.1A. When the electrode is driven to a sufficiently positive potential, the neurotransmitter oxidizes, and two electrons per molecule are transferred to the electrode. The product of dopamine oxidation, dopamine-ortho-oquinone, is also electroactive and is reduced back to dopamine when the potential of the electrode becomes sufficiently negative. In this case, two electrons are transferred from the electrode back to the quinone during reduction. Because the electroformed quinone diffuses away from the electrode, the reductive step must occur very quickly after dopamine oxidation in order for the quinone to be measured. In brain extracellular fluid, the quinone is chemically reduced back to dopamine by ascorbic acid undergoing electrocatalytic oxidation.

FIGURE 3.1

(Please see color insert following page 112.) Comparison of voltammetry (A) and microdialysis (B).

Voltammetric electrodes have been fabricated from carbon paste or fibers (Blaha and Phillips 1996). The sensing surface of a carbon-paste electrode is a disk with a diameter between 150 and 300 μm. Disk electrodes made from a single carbon fiber are considerably smaller. The sensing region is an ellipse, with a minor radius the diameter of the carbon fiber (˜5 to 30 um). The major radius is slightly larger and depends upon the angle of polishing. For cylindrical electrodes, the entire length of the exposed carbon fiber (˜20 to 400 μm) serves as the sensing surface. A variety of waveforms have also been applied to alter electrode potential. Sweep (e.g., linear sweep voltammetry) or pulsed (e.g., chronoamperometry) methods, or a combination of both (e.g., differential pulse voltammetry), were originally used. These so-called slow voltammetric techniques measured analyte with 1-minute temporal resolution.

In microdialysis, contents of extracellular fluid are extracted by an implanted probe and physically removed from brain for chemical analysis. As schematically shown in Figure 3.1B, the microdialysis technique thus has three components: probe, means for separation, and means for detection. Different probes have been used, but a common configuration is concentric tubing covered at the implanted end by a semipermeable membrane (Watson et al. 2006). Molecules in extracellular fluid smaller than the molecule-weight cutoff of the dialysis membrane diffuse into the probe fluid, the so-called dialysate, down a concentration gradient maintained as perfusate is pumped (0.1 to 3 μl/min) between inner and outer tubing. Artificial cerebrospinal fluid is used as perfusate to minimize dialysis of extracellular ions. Probe dimensions are typically 200 to 400 μm in diameter and 1 to 4 mm in length. The temporal resolution of conventional microdialysis is about 10 min.

A workhorse technique for chemical analysis by conventional microdialysis is reverse-phase high-performance liquid chromatography with electrochemical detection. Separation is based on hydrophobicity. An aqueous mobile phase is pumped through a column packed with a hydrophobic stationary phase containing long alkyl chains (-(CH₂)_n-CH₃). The more hydrophobic the analyte is, the more it interacts with the column material and the longer the retention time. Electroactive analytes are detected as they leave the column. Carbon paste and glassy carbon have been used as electrode material, and the principles of operation are the same as voltammetry. Monoamines and their metabolites are oxidized by holding the electrode at a positive potential.

Nonelectroactive neurotransmitters are detected by other means (Westerink 1995). For example, amino acid neurotransmitters, such as glutamate and GABA, are first derivatized (i.e., chemically modified by adding an electroactive or florescent label) so that they are amenable to either electrochemical or florescence detection. Acetylcholine is detected by a two-step enzymatic process, degradation to choline by acetylcholine esterase and conversion to hydrogen peroxide by choline oxidase, followed by electrochemical detection of hydrogen peroxide at a platinum electrode. Neuropeptides are detected by radioimmunoassay, a technique that uses antibodies directed at the analyte of interest for quantification.

3.3. RECENT ADVANCES IN VOLTAMMETRY

The three most commonly used voltammetric techniques in the modern era are amperometry (AMP), high-speed chronoamperometry (HSC), and fast-scan cyclic voltammetry (FSCV). Conceptually and instrumentally, AMP is the simplest technique, because electrode potential is held constant and measured current most directly reflects changes in analyte. In contrast, potential in HSC and FSCV is altered with time, which produces a more complex current response that must be manipulated to reveal the underlying signal of interest. Differences in the manner in which potential is applied, and the resulting current measurements, provide both distinct advantages and disadvantages.

3.3.1. Technical Aspects

In AMP, the electrode is held constant at a potential sufficient for oxidizing or reducing analyte. As such, background current is relatively small. AMP is also an inherently fast technique; as soon as analyte interacts with the sensing surface, it is electrolyzed. Current can therefore be measured as fast as data are acquired by hardware for analog-to-digital conversion. The fast temporal response of AMP has been exploited for monitoring neurotransmitter release from individual vesicles during exocytosis (Wightman et al. 1991; Chow et al. 1992). The measured current spike, representing the vesicle emptying its chemical contents into extracellular space and monitored by a disk carbon-fiber electrode positioned immediately adjacent to the cell, exhibits a short duration of tens of milliseconds.

For the amperometric measurement shown in Figure 3.2, the carbon-fiber electrode was fixed at a potential (0.4 V) sufficient to oxidize dopamine. Each datum represents the current measured every 100 ms in response to 1 μM dopamine. This recording was collected by flow injection analysis (FIA; Kristensen et al. 1986), a common approach for evaluating sensors in vitro. In FIA, the microsensor is placed in a flowing stream of buffer and a bolus (i.e., a step change) of analyte is introduced at a known concentration. The amplitude of the steady-state signal is used for calibration, while the time to reach this steady state is used for determining response time. The dopamine bolus was injected between 5 and 15 s. Small deflections in the signal associated with these times are artifacts of the computer-controlled injection and can be ignored. There is also a ˜2 s delay before injected dopamine reaches the downstream electrode. Nevertheless, the rapid, step increase and the squarelike shape of the signal highlight the attractiveness of AMP for capturing fast neurotransmitter dynamics.

FIGURE 3.2

Amperometry.

Potential is stepped between two limits in HSC by the application of a square wave. For the measurement of dopamine shown in Figure 3.3A, the square wave is applied continuously between a baseline of 0 V and an oxidizing potential of 0.55 V. Each step has a duration of 100 ms, which means that dopamine is sampled every 200 ms. Because potential is stepped instantaneously, the measured current is complex. In particular, each step initially causes a large charging current that subsequently decays with time to a baseline. During the positive step to 0.55 V, current decays to a steady-state level that is comparable to the measurement in AMP.

FIGURE 3.3

High-speed chronoamperometry.

A similar current response is measured in the presence of dopamine, except that current is slightly larger due to faradaic current (Figure 3.3B). Dopamine is oxidized to dopamine-ortho-quinone during the positive step, but unlike AMP, the electro-formed quinone is re-reduced back to dopamine during the negative step. Current is typically integrated over the last portion of the positive step (e.g., 70 to 90 ms), when the large charging current has subsided, and is plotted every 200 ms to characterize the temporal change in dopamine levels. The FIA recording collected by HSC shares with AMP a fast, squarelike response to a dopamine bolus. Additional information is obtained with HSC by taking the ratio of currents integrated during the negative and positive steps. Because reversibility of the redox reaction differs with analyte, this ratio can be used for identification (Gerhardt and Hoffman 2001).

The potential of the microsensor is linearly scanned by applying a triangle wave during FSCV. In Figure 3.4A, top, the triangle wave begins at a baseline potential of –0.4 V, peaks at 1.0 V, and returns to the initial potential. Because potential is ramped quickly (300 V/s), the entire scan occurs in ˜9.3 ms. The electrode rests at the baseline potential during the time between scans. Scans are applied at 100 ms intervals, according to the rule of thumb that ˜10 times the scan duration is required to relax diffusion gradients generated during the scan. Like HSC, the rapid change in potential causes a large charging current. However, because potential is continuously changing during FSCV, a large charging current is measured throughout the scan, switching polarity during the second half of the triangle wave when applied potential returns to baseline. Also like HSC, charging current masks the smaller faradaic current resulting from dopamine.

FIGURE 3.4

(Please see color insert following page 112.) Fast-scan cyclic voltammetry. (With permission from Boyd BW, Witowski SR, Kennedy RT (2000) Trace-level amino acid analysis by capillary liquid chromatography and application to in vivo microdialysis sampling (more...)

Background subtraction is employed to resolve faradaic from charging current. This procedure is successful because the background signal is relatively constant, at least over short time scales, and thus can be mathematically subtracted. As shown in Figure 3.4A, bottom, two distinct peaks emerge for dopamine after background subtraction. The first occurs during the positive sweep at around 0.55 V and is due to the oxidation of dopamine to dopamine-ortho-quinone. The second, in the opposite direction, occurs during the negative sweep at around –0.2 V and results from reduction of the electroformed quinone back to dopamine.

Background-subtracted signals collected for each scan are viewed in time using a three-dimensional, pseudo-color plot to obtain the entire electrochemical record for a dynamic response. The x, y, and z axes are time, applied potential, and measured current, respectively. For the FIA example shown in Figure 3.4B, middle, brown color represents the background current zeroed by the subtraction procedure. Shortly after the dopamine bolus is injected at 5 s, two distinct features appear due to dopamine oxidation at 0.55 V (green-purple) and quinone reduction at 0.2 V (black-yellow). These features, which correspond to the two peaks in the background-subtracted current in Figure 3.4A, bottom, last for the 10-s duration of the bolus injection and then fade into the background brown color.

Quantitative information is derived from the pseudo-colorplot. The temporal response, obtained by plotting current measured at the peak oxidation potential for dopamine (0.55 V) with time (horizontal white line), is shown in Figure 3.4B, bottom. Because scans are applied every 100 ms, dopamine is sampled at this interval. Compared to AMP and HSC, the FIA response collected by FSCV is somewhat slower, with rounder edges. A background-subtracted cyclic voltammogram is generated by plotting the measured current against the applied potential (vertical white line). Shown in Figure 3.4B, top, this current versus potential relationship serves as the chemical signature identifying the analyte as dopamine. Of the known electroactive substances in brain extracellular fluid, only norepinephrine yields a similar voltammogram (Baur et al. 1988).

3.3.2. General Comparisons

While all three voltammetric techniques are capable of monitoring analyte with sub-second temporal resolution, AMP is clearly the fastest. AMP is typically performed with 0.1 to 16.7 ms resolution (Dugast et al. 1994; Forster and Blaha 2003; Venton et al. 2003b), which is more than sufficient for capturing extracellular neurotransmitter dynamics in terminal fields with high fidelity, even for the fastest signals. By comparison, HSC and FSCV are limited by the applied waveform and sample about an order of magnitude slower, 200 and 100 ms, respectively (Kawagoe et al. 1993; Gerhardt and Hoffman 2001).

AMP shares with HSC another advantage that is revealed by FIA, fast response time. By comparison, the dopamine bolus recorded by FSCV is temporally distorted. The source of this distortion is rooted in the measurement itself: dopamine adsorbs to the carbon surface in the time between scans (Bath et al. 2000). Consequently, fast changes in dopamine concentration are “filtered” by the slower adsorption kinetics. By oxidizing dopamine immediately upon contact, the constant potential prevents adsorption in AMP. Any adsorption during the negative step in HSC is also oxidized during the initial positive step, such that dopamine measurements later in time act similarly to AMP. In theory, the temporal distortion in FSCV is removed by deconvolution (Venton et al. 2002). The downside is that this mathematical manipulation, which restores high-frequency components filtered out by adsorption kinetics, adds noise.

Although providing the basis for superior speed, the fixed potential of AMP limits chemical resolution. With a measurement of current at only one potential, there is little electrochemical information to identify the analyte. By contrast, addition of the negative step in HSC enables the determination of a ratio for reductive to oxidative current to aid in identification. Even more powerful is the background-subtracted voltammogram of FSCV, which describes a current profile across the range of potentials for oxidation and reduction. In addition to improving identification, the negative-going potential in HSC and FSCV also reduces dopamine-ortho-quinone back to dopamine. Not only is the buildup of the chemically reactive quinone lessened, but dopamine levels are minimally perturbed during the measurement. By contrast, without regeneration of dopamine, a concentration gradient extending from the electrode is generated by AMP. This gradient makes postcalibration, which is used to convert current measured in brain tissue into concentration, difficult (Kawagoe and Wightman 1994; Venton et al. 2002).

Rapid scanning of the potential during FSCV is not without drawbacks. During the scan, chemical groups on the carbon surface undergo redox reactions, leading to the distinct waves on the background signal (Figure 3.4, middle). The position of these waves is sensitive to background drift and to the ions H⁺ and Ca²⁺, whose brain levels are altered by neuronal activation (Jones et al. 1995; Rice and Nicholson 1995). The response of FSCV to pH is shown in Figure 3.5A. Note that the broad features in the pseudo-color plot and background-subtracted voltammogram overlap dopamine redox potentials. Thus, monitoring current at 0.55 V results in a mixed dopamine-pH temporal response if both analytes change simultaneously. By comparison, AMP is insensitive to the same pH change, because potential is held constant (Figure 3.5B). The pH response of HSC is more complex (Figure 3.5C). HSC is quite sensitive during the early charging current phase, but insensitive when current is integrated over the last 50 ms. A small pH response was reported when current was integrated over the last 80 ms (Gerhardt and Hoffman 2001), perhaps due to the longer integration time.

FIGURE 3.5

(Please see color insert following page 112.) Effects of pH on fast-scan cyclic voltammetry (A; FSCV), amperometry (B; AMP) and high-speed chronoamperometry (C; HCS).

Two strategies have been developed to address problems posed to FSCV by pH. The differential subtraction method (Jones et al. 1995; Venton et al. 2003a) takes advantage of the fact that pH also appears in the electrochemical record at different potentials than dopamine. Recorded at a potential distinct from dopamine, pH is simply subtracted from the mixed dopamine-pH response revealing dopamine. The limitation is that selectivity of the dopamine signal is not always established. Chemometrics has been used to address this issue. With a statistical method called principal component analysis, it is possible to resolve a pure dopamine signal from the mixed response (Heien et al. 2004). However, because of background drift, principal component analysis is restricted to signals of a limited duration. It should also be noted that differential subtraction and principal component analysis allow FSCV to monitor multiple analytes, such as dopamine, pH, and oxygen, simultaneously (Venton et al. 2003a).

Surprisingly, direct comparisons of sensitivity between the three voltammetric techniques are not readily available. Differences in electrode fabrication, instrumentation, and electrochemical parameters, and issues related to calibration, also hinder comparisons between studies. Based on in vivo recordings of electrically evoked dopamine levels measured at the same electrode, AMP was found to exhibit a slightly greater signal-to-noise ratio than FSCV (Venton et al. 2003b). The sensitivity of FSCV is improved by extending scan potential. For the range of –0.6 to 1.4 V,

sensitivity is increased nearly 10-fold (Heien et al. 2003). However, chemical resolution and response time are reduced. For this reason, a less severe extended scan, –0.4 to 1.3 V, is also used. Detection limits for dopamine of ˜15 nM have been reported using extended scan waveforms (Cheer et al. 2004; Stuber et al. 2005b), similar to that described for HSC (Gerhardt and Hoffman 2001). These detection limits are notable in that they approach the lower estimates of basal dopamine levels (˜6 nM) in the striatum as determined by no net flux (Justice 1993).

3.3.3. Applications

To the nonvoltammetrist, differences between AMP, HSC, and FSCV may appear subtle, and the contention that has at times emerged during the development of these techniques, difficult to understand. On one hand, AMP, HSC, and FSCV share the common characteristic of real-time measurement. For some applications, the techniques are therefore interchangeable, and similar results are expected and have been obtained. Nevertheless, unique advantages and disadvantages require careful consideration when selecting a technique.

General guidelines can be proposed. If analyte source is well characterized, all three techniques provide valuable information about neurotransmitter dynamics. Distinct information may, in fact, reflect more the mathematical model used for data analysis than the voltammetric technique. AMP is required for the fastest signals (<100 ms). To obtain signals devoid of distortion by ions or adsorption, AMP or HSC is most appropriate. In this case, selection of the electrode becomes critical. Nafion, used to improve selectivity and sensitivity, slows temporal response (Kawagoe et al. 1992), and larger electrodes may cause complications from tissue damage. On the other hand, if analyte source is unknown, the chemical resolution provided by FSCV is necessary. Techniques can also be combined to exploit different analytical strengths; for example, using FSCV to identify dopamine, and then, at the same electrode and recording location, switching to AMP to obtain better temporal information (Schmitz et al. 2001; Venton et al. 2003b).

Two general approaches have been developed to provide a well-characterized analyte source. The first is application of exogenous neurotransmitter by pressure ejection or iontophoresis (Gerhardt and Palmer 1987; Rice and Nicholson 1995; Kiyatkin et al. 2000). The second is evoking endogenous neurotransmitter release by electrical stimulation (Millar et al. 1985), depolarizing K⁺ solution (Gerhardt et al. 1995), pharmacological agents (Suaud-Chagny et al. 1992), or visual stimuli (Dommett et al. 2005). Exogenous application is the most definitive analyte source. Recording location must be considered when evoking neurotransmitter release. Monitoring evoked dopamine levels in the richly dopamine-innervated striatum is now well established for AMP (Chergui et al. 1994; Gonon 1995; Lee et al. 2006), HSC (Gerhardt et al. 1995; Cass and Manning 1999), and FSCV (Wightman et al. 1988; Young and Michael 1993; Walker et al. 2000). Recording in mixed monoaminergic regions, such as the cortex (Mitchell et al. 1994), thalamus (Ghasemzadeh et al. 1993), amygdala (Jones et al. 1994), and midbrain (Rice et al. 1997), is more challenging.

HSC is typically coupled to pressure ejection for characterizing neurotransmitter uptake in the anesthetized rat. All three monoamines, dopamine (Gulley et al. 2007), serotonin (Daws and Toney 2007), and norepinephrine (Gerhardt 1995), have been examined in this way. Uptake determines the amplitude and clearance rate of the signal recorded at the electrode positioned near the ejection pipette (Zahniser et al. 1998). Signals can also be analyzed by Michaelis-Menten kinetics (Zahniser et al. 1999) and a model incorporating first-order uptake and diffusion (Nicholson 1985; Chen and Budygin 2007). FSCV and AMP have been applied extensively for characterizing dopamine dynamics in anesthetized rats as well, but are more commonly coupled to electrical stimulation (Millar et al. 1985; Chergui et al. 1994). The evoked signal, which increases during the stimulus train and rapidly decays to baseline afterward, contains information about release, uptake, and diffusion (Wightman et al. 1988; Schonfuss et al. 2001; Wu et al. 2001b; Venton et al. 2003b).

Applications of AMP, HSC, and FSCV in anesthetized rats have mainly provided a similar characterization of dopamine uptake in terms of regional differences (Cass et al. 1993; Garris and Wightman 1994; Zahniser et al. 1998), inhibition by psychostimulants (Cass et al. 1992; Suaud-Chagny et al. 1995; Wu et al. 2001a), and autoreceptor regulation (Dickinson et al. 1999; Benoit-Marand et al. 2001; Wu et al. 2002). However, two notable exceptions deserve mention. The first is that basal rates for dopamine uptake are slower when measured by HSC coupled to pressure ejection compared with FSCV coupled to electrical stimulation (Zahniser et al. 1999; Michael et al. 2005; Chen and Budygin 2007). The second is the demonstration by HSC and pressure ejection that uptake inhibitors, under some conditions, increase dopamine uptake rate (Zahniser et al. 1999), which has not been observed with FSCV and electrical stimulation. However, discrepancies appear related to analyte source as opposed to voltammetric technique.

Although both AMP (Falkenburger et al. 2001; Schmitz et al. 2001) and HSC (Hoffman et al. 1998) have been applied to brain slices to some extent, FSCV coupled to electrical stimulation is used extensively in this preparation for characterizing dynamics for dopamine (Palij et al. 1990; Cragg et al. 1997), serotonin (Davidson and Stamford 1995; Bunin and Wightman 1998) and norepinephrine (Palij and Stamford 1992; Callado and Stamford 2000). While information obtained regarding neurotransmitter release and uptake is similar to in vivo FSCV recordings, the in vitro approach has higher throughput and offers greater control of the extracellular milieu and drug application. In vitro voltammetry has factored prominently in characterizing mechanisms of abused drugs. For example, this approach has recently demonstrated that nicotine enhances reward-related dopamine signaling by increasing phasic but inhibiting tonic dopamine release (Rice and Cragg 2004; Zhang and Sulzer 2004). The three main cellular effects of amphetamine on dopamine signaling are also readily observed in the evoked voltammetric trace (Jones et al. 1998, 1999; Schmitz et al. 2001): reduced uptake by competitive inhibition, decreased exocytotic release, and increased nonexocytotic release via reverse transport.

One of the most exciting applications of rapid sampling voltammetry in the last decade is chemical monitoring in ambulatory animals. Such measurements are important for assessing the validity of measurements collected under anesthesia or in brain slices. Moreover, fast chemical monitoring in freely moving animals affords the unique opportunity for correlating neurotransmitter changes with specific aspects of behavior in real time. To date, all three rapid sampling techniques, AMP (Yavich and Tiihonen 2000a), HSC (Kiyatkin et al. 1993; Gerhardt et al. 1999), and FSCV (Garris et al. 1997; Rebec et al. 1997; Kiyatkin et al. 2000), have been applied to freely behaving animals.

Comparable measurements in anesthetized and ambulatory animals indicate that some anesthetics alter rates for dopamine uptake determined voltammetrically (Garris et al. 1997; Gerhardt et al. 1999; Sabeti et al. 2003a). Electrically evoked dopamine release is also suppressed with Equithesin, a mixture including chloral hydrate, pentobarbital, and ethanol (Garris et al. 1997). While drug mechanism is not altered, urethane temporally delays the effects of nomifensine (a psychostimultant) and haloperidol (a mixed D1/D2 antagonist) on electrically evoked dopamine levels (Garris et al. 2003).

The effects of pyschostimulants and haloperidol on dopamine levels evoked by electrical stimulation and measured by FSCV show a particularly close relationship with behavioral activation and catalepsy, respectively (Budygin et al. 2000; Garris et al. 2003; Robinson and Wightman 2004). The effects of cocaine on exogenously applied dopamine measured by HSC and locomotor activity similarly correlate (Sabeti et al. 2002, 2003b). In these studies, baseline and cocaine-induced changes in dopamine uptake measured voltammetrically were additionally linked to the behavioral responsiveness of individual rats to both acute and chronic cocaine administration. Taken together, these studies strongly suggest that indexes of dopamine signaling measured by HSC coupled to pressure ejection and FSCV coupled to electrical stimulation are behaviorally relevant.

The inherent speed of AMP, HSC, and FSCV has provided insight into the study of intracranial self-stimulation. In this classic paradigm, animals work to obtain electrical stimulation at an electrode implanted to activate neural systems involved in reward-related behavior (Olds and Milner 1954). The fast-sampling voltammetric techniques permit dopamine measurements to be linked to individual operant responses, demonstrating a dissociation between dopamine release and the reinforcing electrical stimulation under some conditions (Garris et al. 1999; Kilpatrick et al. 2000; Yavich and Tiihonen 2000b).

More recently, FSCV has been used to characterize naturally occurring dopamine signals associated with behavior. Salient stimuli elicit burst firing in midbrain dopaminergic neurons (Overton and Clark 1997; Schultz 1998) that generates a rapid, dopamine concentration spike in terminal fields (Carelli and Wightman 2004). These so-called dopamine transients typically exhibit an amplitude in the nanomolar range with a duration of a few hundred milliseconds and occur with a baseline frequency of ˜1 to 2 per minute (Robinson and Wightman 2006). Dopamine transients have been linked to specific aspects of behavior during social interaction (Robinson et al. 2001, 2002), cocaine self-administration (Phillips et al. 2003), and food reward (Roitman et al. 2004) and are augmented by noncontingent administration of psychostimulants (Robinson and Wightman 2004; Stuber et al. 2005a). Spontaneously occurring dopamine transients are also observed (Robinson et al. 2002; Cheer et al. 2004).

Figure 3.6 illustrates the FSCV measurement of dopamine changes associated with phasic signaling in a freely behaving rat. This animal was administered WIN55,212-2, a cannabinoid CB1 agonist, to increase the frequency of dopamine transients (Cheer et al. 2004) from about 1 to >7 per minute. The main panel shows a 60-s recording collected in the caudate-putamen. The large increase in signal near the beginning is evoked dopamine release due to electrical stimulation of the substantia nigra. Other, smaller peaks designated by an asterisk are dopamine transients. To the left is an expanded view of the first 10 s with a dopamine transient occurring between 0 and 2 s and the electrically evoked signal beginning at 5 s. Dopamine features for both signals are displayed in the pseudo-color plot in Figure 3.6.

FIGURE 3.6

(Please see color insert following page 112.) Recording dopamine transients in the freely behaving rat by fast-scan cyclic voltammetry. Pseudo-color plots are on identical time scales as the recording immediately below. Electrical stimulation is denoted (more...)

The background-subtracted voltammogram collected during stimulation is used as a reference dopamine signal to identify transients. The inset above the pseudocolor plot shows that voltammograms collected during stimulation and for the transient correlate well. Each voltammogram collected in the recording is statistically compared with the evoked dopamine signal, and only those above a preselected threshold are considered dopamine. Other prominent features occur in the pseudocolor plot after stimulation and are due to changes in extracellular pH (left panel).

This distortion, which causes the signal to fall precipitously after stimulation (solid line), is removed by differential subtraction, revealing the evoked dopamine signal (dashed line).

The capability to resolve dopamine transients from other signals in the electrochemical record attributed to, for example, nondopamine analytes, movement artifact, and noise, clearly highlights the utility of the background-subtracted voltammogram for chemical analysis of phasic neurotransmisson during behavior. The question arises whether FSCV can, as well, selectively monitor dopaminergic tone, the basal level of brain dopamine. Although determination of absolute concentration is still not possible, principal component analysis resolves a slow increase in steady-state dopamine levels following noncontingent administration of several drugs of abuse, including cocaine, ethanol, and nicotine (Heien et al. 2005; Cheer et al. 2007b). FSCV has additionally been used to assess decreases in the baseline voltammetric signal following local infusion of the ionotropic glutamate receptor antagonist, kynurenate (Kulagina et al. 2001; Borland and Michael 2004). Interestingly, the kynurenate-induced drop in signal represents a ˜2 μM decrease in dopamine concentration, if the entire signal is attributed to this neurotransmitter.

Information about how target cells respond to measured neurotransmitter dynamics is also desirable. Separate electrodes have been used to record electrically evoked dopamine levels with AMP and extracellular single unit activity in the striatum of anesthetized rats (Gonon and Sundstrom 1996; Gonon 1997). FSCV lends itself nicely to combined chemical and electrophysiological assessment, because the carbon-fiber electrode is an excellent sensor for unit recording (Millar et al. 1981; Millar and Williams 1988) and the electrochemical measurement is not continuous. Indeed, both voltammetric and electrophysiological measurements have been made at the same carbon-fiber electrode using what is called a time-share or quasi-simultaneous procedure. Originally developed for anesthetized (Williams and Millar 1990a, 1990b) and slice preparations (Stamford et al. 1993), combined measurements have recently been made in ambulatory rats (Cheer et al. 2005, 2007a).

Figure 3.7 shows the technique of quasi-simultaneous voltammetry and electro-physiology. FSCV is performed as described above, but in the time between scans, the carbon-fiber electrode is switched to a circuit for recording units. After data manipulation, the temporal response of dopamine and histogram of unit activity are overlaid, as shown in Figure 3.8A. Data were collected in the striatum of an anesthetized rat by a carbon-fiber electrode prepared from a five-barrel micropipette, as shown in Figure 3.8B. Additional barrels were used for iontophoresis. Excitation of a glutamate-sensitive single unit by an electrically evoked signal mimicking the dynamics and amplitude of a dopamine transient is demonstrated.

FIGURE 3.8

Coupling microiontophoresis to quasi-simultaneous voltammetry and electro-physiology. Effects of electrically evoked dopamine levels on a striatal unit excited by iontophoretically applied glutamate are shown in A. An electron micrograph of a carbon-fiber (more...)

3.4. RECENT ADVANCES IN MICRODIALYSIS

Unlike voltammetry, where AMP, HSC, and FSCV largely displaced the early techniques in the last decade or so, conventional microdialysis continued to be widely used for neurotransmitter monitoring, particularly in freely moving animals. Perhaps as a result, advances and new applications were not on the same large scale as those for voltammetry and described in the previous section. Nevertheless, significant improvements have been made. For example, considerable effort has been directed at increasing temporal resolution, which for conventional microdialysis is about 10 min. Poor temporal resolution is due to the combination of low perfusion rates through the probe and the large sample volume requirement for high-performance liquid chromatography. Consequently, samples must be collected for long periods of time. However, the emergence of capillary liquid chromatography (CLC) and capillary electrophoresis (CE), with their high separation efficiency and low sample volume requirements, coupled to high sensitivity detection methods, such as laser induced fluorescence (LIF) and mass spectrometry (MS), have afforded faster sampling, even down to a few seconds.

FIGURE 3.7

(Please see color insert following page 112.) Quasi-simultaneous voltammetry and electrophysiology. A simplified circuit diagram is described in A. Monitoring of the electrically evoked signal by fast-scan cyclic voltammetry is shown in B. Identification (more...)

3.4.1. Capillary Liquid Chromatography

CLC is similar to conventional high-performance liquid chromatography in that analytes are separated based on mass exchange between the mobile and stationary phase in the separation column. CLC columns, which have an inner diameter of ˜25 to 50 μm, can be viewed as a hybrid between the conventional packed column and the much smaller open tubular capillary columns, which do not contain packing material (Takeuchi 2005). Offering excellent selectivity, CLC must be coupled to high-sensitivity detection techniques because of the required low flow rates. Figure 3.9 shows the separation of amino acid neurotransmitters by CLC coupled to electrochemical detection (Boyd et al. 2000). The nonelectroactive analytes were derivatized by o-phthalaldehyde/tert-butyl thiol and monitored electrochemically with AMP by a carbon-fiber electrode. A detection limit of about 50 attomoles enabled the in vivo monitoring of glutamate, aspartate, GABA, and glycine with 10-s temporal resolution using a conventional microdialysis probe. The neuropeptide met-enkephalin is directly electroactive and has also been detected in dialysate with CLC coupled to a carbon-fiber electrode (Shen et al. 1997).

FIGURE 3.9

Chromatogram from capillary liquid chromatography with electrochemical detection. Dialysate was collected in the striatum of an anesthetized rat. The detector was a carbon-fiber electrode held at constant potential. Abbreviations: GLU, glutamate; ASP, (more...)

3.4.2. Capillary Electrophoresis

As shown in Figure 3.10A, CE separates analytes based on their ability to migrate in an electrical field. Since no mass exchange between mobile phase and capillary wall occurs, migration velocity is determined by the charge density and size of analyte. The mobile phase, or in CE referred to as background electrolyte (BGE), is polar and moves through the separation capillary from the negative to positive pole. This flow of BGE is referred to as electroosmotic flow and is manipulated by changing the voltage of the electric field across the capillary or the pH of the BGE. One advantage of analytes being carried by electroosmotic flow is the near absence of peak broadening, which contributes to CE's high resolution. Indeed, of the liquid separation techniques, CE possesses the highest resolving power (Issaq 1999). Due to its high separation efficiency and resolving power, CE also exhibits the fastest separation times, with analyte migrating in seconds as opposed to eluting in minutes (Issaq 1999; Moini 2002; Powell and Ewing 2005). Compared to CLC, CE supports smaller sample volumes, but this also leads to lower concentration sensitivity (Hernandez-Borges et al. 2004; Chiu et al. 2006). Mass sensitivity is largely independent of separation method.

FIGURE 3.10

A. Capillary electrophoresis. Analyte X⁺ is carried by electrostatic attraction and electroosmotic flow to the negative end of the capillary. B. Laser-induced fluorescence. Analyte is excited by the energy quantum supplied by a laser. Subsequent relaxation (more...)

3.4.3. Laser-Induced Fluorescence

As conceptually shown in Figure 3.10B, in LIF, a laser beam excites analyte to a higher energy state, and fluorescence is emitted when excited analyte decays back

FIGURE 3.11

Electropherogram from capillary electrophoresis with laser-induced fluorescence. Dialysate was obtained from the thalamus of a freely moving rat. Abbreviations: DA, dopamine; NA, norepinephrine; Glu, glutamate; Asp, aspartate; see also Parrot et al. (2004). (more...)

to a lower energy state. One advantage of LIF is that analytes do not need to be electroactive. Because many analytes of interest do not exhibit native fluorescence or have low quantum yields, derivatization with a fluorescent label is necessary. A variety of derivatizing agents and lasers are described in the literature (e.g., Chiu et al. 2006; Garcia-Campana et al. 2007). Chen et al., using 5-furoylquinoline-3-carboxaldehyde, assayed 16 biogenic amine and amino acids including Glu, GABA, and DA (Chen et al. 2001), illustrating the importance of derivatizing agent choice. The three main ways of introducing derivatizing agents online are pre-, on-, or post-separation capillary (Garcia-Campana et al. 2007).

LIF is a highly sensitive method suitable for detecting analytes that are sufficiently separated. CE has been coupled to LIF for in vivo measurements of biogenic amines and amino acids in dialysate with a temporal resolution of between 3 and 100 s (Lada and Kennedy 1996; Tucci et al. 1997; Rebec et al. 2005; Shou et al. 2006). Figure 3.11 shows the CE-LIF monitoring of dopamine, norepinephrine, glutamate, aspartate, and GABA. CE-LIF has also been applied to the freely behaving rat for monitoring GABA and glutamate with 14 s temporal resolution in the nucleus accumbens following presentation of fox odor (Venton et al. 2006a) and in the basolateral amygdala during a conditioned fear paradigm (Venton et al. 2006b).

3.4.4. Mass Spectrometry

The analytical technique of MS is complex, and the reader is encouraged to consult other, more detailed sources (e.g., Niessen 2003) than the very simplified coverage found in this chapter. MS is a unique detection method, because in addition to quantification, structural information about the analyte is also obtained. Thus, when adequate separation is not reached or analytes are unknown, MS is preferred. As conceptually shown in Figure 3.12A, there are three steps to MS: ionization, mass analysis, and detection. Diverse MS configurations, with different levels of analysis capabilities, are available. Ionization strategy depends on analyte polarity and size, and on state (Thurman et al. 2001). An atmospheric pressure ionization method called electrospray ionization (ESI) is used for in vivo monitoring (Hernandez-Borges et al. 2004; Haskins et al. 2004; Powell and Ewing 2005). Suitable for liquid samples, ESI is a soft-ionization procedure that is compatible with almost the entire ionization continuum, including nonvolatile, thermally labile, and polar analytes (Zwiener and Frimmel 2004).

FIGURE 3.12

Mass spectrometry. Principles for a single quadrupole are shown in A. A quadrupole ion trap mass spectrogram of characteristic ion fragments from leu-enkephalin is shown in B. A reconstructed ion chromatogram, which is obtained by monitoring unique ion (more...)

Several methods are available for mass analysis, including quadrupole, quadrupole ion trap, triple quadrupole, time of flight, and fourier transform ion cyclotron resonance (Niessen 2003; Schmitt-Kopplin and Frommberger 2003). Quadrupole ion trap, which applies voltages at different radiofrequencies to trap and analyze ions, has been applied to in vivo monitoring. For example, CLC coupled to MS is used to measure small molecule neurotransmitters, such as acetylcholine, dopamine, norepinephrine, and GABA (Zhang and Beyer 2006; Shackman et al. 2007) and the structurally similar peptides met- and leu-enkephalin (Haskins et al. 2001; Baseski et al. 2005), and to identify novel neuropeptides (Haskins et al. 2004). MS also has excellent sensitivity, and for neuropeptides the concentration detection limit is around 2 pM (Haskins et al. 2001). High sensitivity is especially important when considering that basal concentrations of neuropeptides are between 1 and 100 pM (Kennedy et al. 2002b). An example of a mass spectrogram for leu-enkephalin, along with a chromatogram from an in vivo measurement of met- and leu-enkephalin in the anesthetized rat, is shown in Figure 3.12B and C, respectively.

3.5. RECENT ADVANCES IN BIOSENSORS

Important advances have also been made in biosensors. In addition to the attractive attributes of an electrochemical sensor, such as high temporal and spatial resolution, one important advantage of biosensors is the capability for monitoring nonelectroactive analytes. Biosensors come in many forms, but the common component is the biological recognition element that directly interacts with the analyte (Wilson and Gifford 2005). This section will focus on enzyme-linked biosensors for glutamate, where the biological recognition element is glutamate oxidase. Described below in more detail, the action of glutamate oxidase on glutamate generates an electroactive signal. However, it should be emphasized that other enzymes, such as dehydrogenases, esterases, kinases, and even ionotropic receptors, have formed the basis for biosensor designs and that a number of neurochemicals besides glutamate are amenable to detection with the biosensor approach, including acetylcholine, GABA, aspartate, glucose, lactate, and pyruvate (Hascup et al. 2007). The reader is also directed to reviews comparing glutamate measurements by microdialysis and biosensors (O'Neill et al. 1998; Kahn and Michael 2003; Watson et al. 2006).

The conceptual basis for the glutamate oxidase-based biosensor is shown in Figure 3.13A. Glutamate is enzymatically acted on by glutamate oxidase, ultimately producing electroactive hydrogen peroxide. AMP is used to detect hydrogen peroxide electrochemically at the electrode surface. A series of three reactions is involved:

FIGURE 3.13

Enzyme-linked biosensor for glutamate. The general concept is shown in A. An early design is shown in B. Abbreviations: Glu, glutamate; GluO, glutamate oxidase; AA, ascorbic acid; AAO, ascorbic acid oxidase; αKG, α-ketoglutarate; A^-, electroactive (more...)

glutamate + H₂0 + GluOx(0) → α-ketoglutarate + NH₃ + GluOx(R) (1)

GluOx(R) + 0₂ → GluOx(0) + H₂0₂ (2)

H₂0₂ → 0₂ + 2H⁺ + 2e^- (3)

Although glutamate oxidase is depicted in the oxidized (O) and reduced (R) states, a cofactor, flavin adenine dinucleotide, is actually what is reduced and oxidized in reactions 1 and 2, respectively (i.e., O = FAD and R = FADH₂).

In many respects, development of voltammetric electrodes and enzyme-linked biosensors shares many concerns, with chemical resolution the chief of these. The issue is not the biological recognition element, glutamate oxidase, which is exquisitely selective. Rather, amperometry offers little electrochemical information to resolve hydrogen peroxide from the plethora of easily oxidizable species in brain extracellular fluid. Taking the lead from voltammetry, negatively charged films and other enzymes have been incorporated into glutamate biosensors to address the issue of interferents.

One of the earliest glutamate biosensors was fabricated by first applying Nafion and cellulose acetate to a platinum-iridium wire (Hu et al. 1994). An enzyme layer of glutamate oxidase and ascorbic acid oxidase was then immobilized on this negatively charged film using bovine serum albumin and glutaraldehyde. The mechanism of this biosensor is shown schematically in Figure 3.13B. Negatively charged interferents are repelled by Nafion and cellulose acetate, whereas ascorbic acid is also acted on by ascorbic acid oxidase, producing the nonelectroactive water and dehydroascorbate. Most importantly, hydrogen peroxide generated by the glutamate-glutamate oxidase reaction can diffuse to the electrode for electrolysis. The sensing surface is a cylinder with a diameter of 170 μm and length of 700 μm. A temporal resolution of 1 s for glutamate is exhibited. Monoamines are also detected, but some selectivity is conferred by the slow diffusion of these positively charged neurotransmitters through the negatively charged film. Described next, subsequent glutamate biosensors have improved on this basic design.

One general concern for biosensors based on oxidases is artifacts produced by fluctuating oxygen levels, a cofactor for the enzyme. An important goal for developing glutamate biosensors is thus to reduce oxygen dependency. Interestingly, enzyme loading and miniaturization have recently been found to be beneficial in this regard (McMahon and O'Neill 2005; McMahon et al. 2006). To create a smaller probe, glutamate biosensors were fabricated on the cut end of a platinum wire, yielding a disk-shaped sensing surface with a diameter of 125 μm. Glutamate oxidase was immobilized to the surface using a polymer consisting of o-phenylenediamine and bovine serum albumin. This electrode showed high sensitivity to glutamate, but a relative lack of oxygen interference down to 5 μM, well above the 50 μM average concentration of oxygen in the brain.

To reduce size and increase selectivity, glutamate biosensors have also been constructed with carbon-fiber electrodes using “polymer wires” to transfer electrons to the sensing surface (Kulagina et al. 1999; Cui et al. 2001). The general design and mechanism for this biosensor are shown in Figure 3.14. A polymer containing an osmium-redox complex is used to immobilize three enzymes, glutamate oxidase, horseradish peroxidase and ascorbic acid oxidase, on a cylinder carbon-fiber electrode with a diameter of 10 μm and length of ˜350 μm. The electrode is then coated with Nafion. The key innovation in this design is that hydrogen peroxide, formed by the glutamate-glutamate oxidase reaction, is oxidized by horseradish peroxidase, directly transferring electrons to osmium. Because a negative potential –0.1 V) is applied, the reduced osmium is subsequently oxidized, transferring electrons to the electrode. The negative potential also enhances selectivity by limiting oxidation of extracellular electroactive species. As shown in Figure 3.14B, in vivo glutamate measurements with this biosensor are TTX-sensitive, indicating a neuronal origin for the analyte.

FIGURE 3.14

Enzyme-linked biosensor for glutamate based on an osmium containing redox polymer for directly transferring electrons to the platinum (Pt) electrode. Key features of the conceptual design are shown in A. The TTX-sensitivity of a response recorded in the (more...)

One final glutamate biosensor, the so-called ceramic-based multisite electrode, is described. The original design contained four platinum recording sites, each 50 x 50 µm and spaced 200 μm apart, on a ceramic probe that tapers to a 2–5 μm tip (Burmeister et al. 2000). As shown in Figure 3.15A, newer designs have increased sensing surface area (50 x 150 μm) and reduced spacing between (50 μm edge to edge; Burmeister et al. 2002). The sensing mechanism is schematically shown in Figure 3.15B. Glutamate oxidase is immobilized on the Nafion-coated platinum surface by bovine serum albumin and glutaraldehyde. In addition to multiple recording sites at a single probe, this design also supports self-referencing (Burmeister and Gerhardt 2001). Typically used by a single probe vibrating between two fixed positions, self-referencing is a powerful technique for increasing sensitivity and characterizing analyte flux (Porterfield 2007). For self-referencing by the glutamate biosensor, one of the recording sites becomes the sentinel electrode, which does not contain glutamate oxidase (Figure 3.15B). Subtracting the sentinel signal from that measured at the site containing glutamate oxidase removes common intereferents, such as monoamines (Figure 3.16A) and noise (Figure 3.16B), thereby increasing the quality of glutamate recording.

FIGURE 3.15

Ceramic-based multisite electrode. An electron micrograph of the probe is shown in A. The mechanism of glutamate sensing is shown in B. Abbreviations: Glu, glu-tamate; GluO, glutamate oxidase; AA, ascorbic acid; AAO, ascorbic acid oxidase; αKG, (more...)

3.6. CONCLUDING REMARKS

The emergence of rapid sampling voltammetric techniques have clearly revolutionized the field of chemical monitoring in the last decade or so. Initially developed by a few investigators, these approaches have found their way to many other laboratories and are now used routinely for the study of neurotransmitter dynamics in anesthetized and brain slice preparations. This trend will no doubt continue with further collaboration and instrument commercialization. Because assessing neural substrates of behavior in real time is an exciting direction that is only beginning to flourish, enormous growth in these types of measurements is additionally expected. Microdialysis and biosensors must be considered in any discussion of the future of chemical monitoring. Advances in sensitivity and capabilities for multianalyte measurements, combined with new probes, bode well for the continued success of microdialysis, especially as these new approaches become more accessible to neurobiologists. The opportunity for measuring nonelectroactive neurotransmitters rapidly at a small probe makes biosensors attractive as well. Just as voltammetry and microdialysis dominated the early era of chemical monitoring in the brain, these two techniques combined with biosensors will prominently factor in the study of neural substrates of addiction for many years to come.

FIGURE 3.16

Self-referencing at the ceramic-based multisite electrode. The top panel in A shows the signal recorded at the sentinel and glutamate electrode. Note the response to dopamine at both electrodes, but no glutamate response at the sentinel electrode. The (more...)

ACKNOWLEDGMENTS

We kindly thank Drs. John Baur and Michael Heien for previewing the manuscript. This work was supported by USAMRMC 03281055, NIDA DA 021770, and NSF DBI 0138011.

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