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Hindawi Publishing CorporationAdvances in Pharmacological SciencesVolume 2012, Article ID 281768, 17 pagesdoi:10.1155/2012/281768

Review Article

Preclinical Determinants of Drug Choice under ConcurrentSchedules of Drug Self-Administration

Matthew L. Banks and S. Stevens Negus

Department of Pharmacology and Toxicology, Virginia Commonwealth University, P.O. Box 980613, Richmond, VA 23298, USA

Correspondence should be addressed to Matthew L. Banks, [email protected]

Received 15 June 2012; Accepted 14 October 2012

Academic Editor: Edward W. Boyer

Copyright © 2012 M. L. Banks and S. S. Negus. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Drug self-administration procedures have played a critical role in the experimental analysis of psychoactive compounds, such ascocaine, for over 50 years. While there are numerous permutations of this procedure, this paper will specifically focus on choiceprocedures using concurrent schedules of intravenous drug self-administration. The aims of this paper are to first highlight theevolution of drug choice procedures and then review the subsequent preclinical body of literature utilizing these choice proceduresto understand the environmental, pharmacological, and biological determinants of the reinforcing stimulus effects of drugs. Amain rationale for this paper is our proposition that choice schedules are underutilized in investigating the reinforcing effects ofdrugs in assays of drug self-administration. Moreover, we will conclude with potential future directions and unexplored scientificspace for the use of drug choice procedures.

1. The Evolution of Drug Choice Procedures

Drug self-administration procedures have played a criticalrole in the experimental analysis of psychoactive compounds,such as cocaine, for more than 50 years. In general, preclinicaldrug self-administration procedures are utilized for twomain scientific purposes. One purpose is in abuse liabilitytesting of psychoactive compounds for potential schedulingas controlled substances by the Drug Enforcement Agency,and there are already excellent reviews on the use of drug self-administration procedures for this purpose, see [1, 2]. Theother main purpose of drug self-administration proceduresis in understanding the pharmacological, environmental andbiological determinants of drug-taking behavior as a modelof drug addiction. This paper will focus on the use ofconcurrent-choice schedules of drug self-administration toaddress this latter purpose.

Although there are numerous permutations of drug self-administration procedures, all use the classic 3-term con-tingency of operant conditioning to investigate the stimulus

properties of drugs [3]. This 3-term contingency can bediagrammed as follows:

SD −→ R −→ SC , (1)

where SD designates a discriminative stimulus, R designatesa response on the part of the organism, and SC designatesa consequent stimulus. The arrows specify the contingencythat, in the presence of the discriminative stimulus SD, per-formance of the response R will result in delivery of theconsequent stimulus SC . As a simple and common examplefrom a preclinical laboratory, a rat implanted with a chronicindwelling catheter might be connected to an infusion pumpcontaining a dose of a psychoactive drug and placed into anexperimental chamber that contains a stimulus light and aresponse lever. Contingencies can be programmed such that,if the stimulus light is illuminated (the discriminative stim-ulus), then depression of the response lever (the response)will result in delivery of a drug injection (the consequentstimulus). Conversely, if the stimulus light is not illuminated,

2 Advances in Pharmacological Sciences

then responding does not result in the delivery of the druginjection. Under these conditions, subjects typically learnto respond when the discriminative stimulus is present.Consequent stimuli that increase responding leading to theirdelivery are operationally defined as reinforcers, whereasstimuli that decrease responding leading to their deliveryare defined as punishers. The contingencies that relatediscriminative stimuli, responses, and consequent stimuli aredefined by the schedule of reinforcement [4].

The first published reports of intravenous drug self-administration used exactly this type of single-responseprocedure described above to examine morphine self-administration in morphine-dependent rats [5, 6]. Further-more, these seminal studies demonstrated three principlesthat have been commonly observed in single-response drugself-administration procedures ever since. First, these studiesdemonstrated that intravenous morphine could maintainschedule-appropriate rates and patterns of responding lead-ing to its delivery, indicating that morphine functioned as areinforcer. Second, this single-response procedure produceda bitonic, “inverted U shaped” dose-effect function relatingthe unit dose of morphine in each injection to measuresof rate (either rates of responding or injection delivery).Thus, maximal rates of self-administration were maintainedby intermediate morphine doses, and lower rates were main-tained not only by lower morphine doses, but also by higherdoses. Importantly, this pattern of responding indicates adissociation between rates of self-administration maintainedby a given consequent stimulus and the reinforcing efficacyof that stimulus [7, 8], because if the research subject isgiven a choice between a lower and higher dose of the samedrug, the subject will almost always choose the higher drugdose indicating that the higher drug dose is the preferredor more efficacious reinforcer [9, 10]. Why would rates ofdrug self-administration decrease as dose increases abovesome apparent optimal level? As is often the case in otherpharmacology domains, the presence of a bitonic dose-effectfunction indicates that multiple and/or opposing drug effectsare being integrated into a common dependent variable.For example, measures of self-administration rate can beinfluenced not only by the reinforcing effects of a drug(which would have the effect of increasing rates), but alsoby other effects of the self-administered drug that can eitherincrease or decrease rates (e.g., effects that improve or impairmotor competence or information processing). These otherdrug effects will be collectively referred to as “reinforcement-independent rate-altering effects” in this paper to distinguishthem from reinforcing effects, and one goal of more recentlydeveloped procedures is to dissociate reinforcing drug effectsfrom reinforcement-independent rate-altering effects.

The third and final principle revealed by these earlystudies was that rates of morphine self-administration couldbe altered by treatment with other drugs. These effectswere interpreted to suggest treatment effects on drug rein-forcement (and by extension, to provide evidence regardingmechanisms of drug reinforcement). However, just as self-administration rates can be influenced by multiple effectsof the self-administered drug, so these rates can also beinfluenced by multiple effects of a treatment drug (or of any

other experimental manipulation, such as a lesion or geneticmodification) [11, 12]. More specifically, these experimentalmanipulations can alter rates of self-administration not onlyby changing the reinforcing effects of the self-administereddrug, but also by changing the reinforcer-independentrate-altering effects of the self-administered drug, or byproducing its own reinforcement-independent rate-alteringeffects. Overall, these early studies illustrated the promiseof drug self-administration as a model of drug addiction,but they also provided a glimpse of the challenges tointerpretation of rate-based measures generated by single-response procedures.

Since the early 1960s, preclinical drug self-administrationresearch has flourished, and techniques for intravenous drugself-administration were rapidly extended to studies withother drug classes and in other species of experimentalsubjects [13, 14]. However, over the decades, drug rein-forcement research has evolved along three divergent paths.One path of self-administration research has retained theuse of single-response procedures initially used by Weeksand colleagues [5, 6] and utilized more demanding andcomplex schedules of reinforcement, such as progressive-ratio and second-order schedules, than the simple fixed-ratioschedules used by Weeks and colleagues. In general, studiesusing these approaches have demonstrated that numerousdrug classes can maintain rates and patterns of respondingconsistent with the hypothesis that drugs can function asreinforcers [15]. However, these approaches have been lesssuccessful in generating dependent measures that clearlydissociate reinforcing drug effects from reinforcement-independent rate-altering drug effects. To highlight theprevalence of single-response procedures in the current drugself-administration literature, we used the keyword “self-administration” in PubMed on April 11, 2012, to retrievethe 50 most recent preclinical studies using intravenous drugself-administration procedures as the primary independentvariable. This “snapshot” of the literature revealed that 15 ofthe 50 most recent studies used a single-response drug self-administration procedure.

A second path of self-administration research hasretained the simple fixed-ratio schedules utilized by Weeksand colleagues on one response lever, but incorporatedrudimentary aspects of choice by introducing an “inactive”response option in addition to the “active” drug option. Forexample, an early study by Pickens and Thompson [16] useda two-lever self-administration procedure in which respond-ing on one “active” lever produced intravenous cocainedelivery under an FR1 schedule of reinforcement, whereasresponding on a second “inactive” lever had no scheduledconsequences. Schedule-appropriate responding was main-tained exclusively on the “active” lever, and when the con-tingencies on the two levers were reversed, rats rapidly real-located their responding to the newly “active” lever. In oursnapshot analysis of the current self-administration litera-ture, the majority of drug self-administration studies (32 outof 50) used an “inactive” manipulandum. Differential ratesof responding on “active” and “inactive” manipulanda areuseful for investigating the reinforcing effects of consequentstimuli associated with the “active” manipulandum; however,

Advances in Pharmacological Sciences 3

the utility of this simple type of choice procedure is limitedfor at least two main reasons. First, although “active/inactive-response” procedures technically employ a concurrent sched-ule capable of generating measures of response allocationand choice, such measures are rarely computed or reported.Rather, investigators more commonly report measures ofresponse or reinforcement rate on the “active” manipulan-dum as if it were the only response option available, and suchrate-based measures of drug reinforcement are vulnerable toall the reinforcement-independent rate-altering drug effectsdescribed above. Second, baseline rates of behavior on the“active” and “inactive” manipulanda are normally vastlydifferent, with rates on the “inactive” manipulandum beingvery low. As a result, data on “inactive” responding are pri-marily useful for only detecting reinforcement-independentrate-increasing effects. However, because “inactive” rates arealready low, they are insensitive to reinforcer-independentrate-decreasing effects of experimental manipulations. Thisis a critical issue, because most drug self-administrationstudies are designed to evaluate the ability of experimentalmanipulations, such as pharmacological, environmental, orgenetic variables, to decrease drug reinforcement as indicatedby decreases in drug self-administration rates. Thus, proce-dures that use “active” and “inactive” manipulanda are notmuch different than the single-response self-administrationprocedures described above.

The third and least common path of drug self-admin-istration research has used concurrent schedules in whichresponding is maintained on two or more manipulanda bytwo or more motivationally relevant consequent stimuli. Forexample, responding on one manipulandum might resultin delivery of a particular drug dose, and responding on adifferent, concurrently available manipulandum might resultin delivery of a different dose of the same drug, a differentdrug, or a qualitatively different consequent stimulus suchas food (Figure 1). These procedures are often referred to as“choice” procedures, because subjects allocate their behavior,or “choose,” between the available consequent stimuli, andthe relative reinforcing effects of drug in comparison toan alternative are derived from measures of behavioralallocation (or “drug choice”) rather than behavioral rate. Aswith any other type of self-administration procedure, theself-administered drug or other experimental manipulationsmight also influence overall self-administration rate byproducing reinforcement-independent rate-altering effects;however, the impact of these other effects on choice measuresof drug reinforcement can be minimized by appropriate useof manipulanda, discriminative, and alternative reinforcingstimuli, and schedules of reinforcement. A specific exampleof this dissociation is shown in Figure 1. Cocaine versusfood choice increases as the unit cocaine dose increases;however, rates of responding display the prototypic inverted-U shaped dose-effect function. Moreover, choice proceduresgenerate distinct measures of behavioral allocation andbehavioral rate that permit dissociation of reinforcing effectsfrom reinforcement-independent rate-altering effects. Forexample, an experimental manipulation that decreases rein-forcing efficacy of a drug might be expected to reduce drugchoice but increase choice of the alternative and produce

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Figure 1: Baseline choice between different doses of cocaine (0–0.1 mg/kg/injection) and food pellets in rhesus monkeys (n = 4)under a concurrent FR10 : FR100 schedule of cocaine injectionsand food availability. Abscissae: unit dose of cocaine in milligramsper kilogram per injection. Top ordinate: percent cocaine choice.Middle ordinate: rates of responding in responses per second.Bottom ordinate: number of choices completed. All points representmean data SEM obtained during the last 3 days of saline treatment.These unpublished data demonstrate two key observations fromchoice procedures. First, cocaine choice increases in a monotonicfunction as the unit cocaine dose increases. Second, while rates ofresponding display the prototypic, inverted-U-shaped dose-effectfunction, rates of responding are not predictive of cocaine choice,nor are rates of responding predictive of the number of choicescompleted per component.


no net change in overall reinforcement rates. A specificexample of this selective effect from the literature is shownin Figure 2 examining cocaine versus food choice duringchronic treatment with the dopamine (DA)-selective releaserm-fluoroamphetamine [17]. Conversely, a manipulation thatproduces reinforcement-independent rate-altering effects(e.g., motor impairment) might be expected to reduceoverall reinforcement rates without altering drug choice. Anexample of this specific effect from the literature is shownin Figure 3 examining cocaine versus food choice duringchronic treatment with the mu-opioid agonist methadone[18]. These distinct dependent measures of reinforcingeffects (represented in measures of drug choice) andreinforcement-independent rate-altering effects (representedin measures of overall self-administration rates) are analo-gous to the use of concurrent schedules in the closely relatedfield of drug discrimination research to generate dependentmeasures that permit dissociation of discriminative stim-ulus effects (represented in measures of drug-appropriateresponding) from discrimination-independent rate-alteringeffects (represented in measures of overall rates of respond-ing or reinforcement). Despite this apparent advantage, ourPubMed search indicated that only 3 of the 50 most recent IVdrug self-administration studies used a concurrent scheduleof reinforcement. This paucity of research with concurrentschedules in research on the reinforcing stimulus effects ofdrugs stands in striking contrast to the almost exclusiveuse of concurrent schedules in drug discrimination researchand suggests that concurrent schedules are underutilized instudies of drug self-administration [19].

Although choice procedures have been underutilized,their value has long been appreciated. As noted above,the earliest studies of intravenous drug self-administrationused single-response procedures, but these studies werepredated by choice studies in which drug was delivered byother routes of administration. For example, more than twodecades before the studies by Weeks and colleagues, Spraggevaluated choice between intramuscular morphine and fruitin morphine-dependent chimpanzees and demonstrated thatchoice was largely influenced by the state of morphinewithdrawal (such that morphine withdrawal was associ-ated with increased probability of morphine choice) [20].Similarly, Nichols and colleagues established responding fororal morphine in rats and found that morphine withdrawalincreased choice of morphine over water [21]. Intravenousdrug delivery subsequently gained prominence in drug self-administration research because it promotes a rapid onsetof drug action that facilitates learned contingencies betweenresponding and drug delivery. However, the rise of intra-venous drug self-administration was also accompanied bya growing reliance on single-response and “active/inactive”-response procedures, perhaps because the limited lifespanof intravenous catheters selected for procedures that requirethe least initial training. Nonetheless, the use of choiceprocedures persisted, especially in studies of oral drug self-administration [13, 22] and in a small but steady series ofintravenous drug self-administration studies. The goal hereis to review the history and major findings of research onintravenous drug choice.

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Figure 2: Effects of chronic intravenous m-fluoroamphetamine(0.1 mg/kg/hr) administration on choice between cocaine and foodin rhesus monkeys (n = 4). Abscissae: unit dose of cocaine inmilligrams per kilogram per injection. Top ordinate: percentcocaine choice. Middle ordinate: rates of responding in responsesper second. Bottom ordinate: number of choices completed. Allpoints represent mean data SEM obtained during the last 3days of m-fluoroamphetamine treatment. These published data[17] demonstrate that experimental manipulations can selectivelydecrease cocaine choice without also decreasing rates of respondingand the number of choices completed. This profile would beconsidered ideal for a candidate medication to treat cocainedependence.


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Figure 3: Effects of chronic intravenous methadone (0.32 mg/kg/hr) administration on choice between cocaine and food in rhesus monkeys(n = 3). Abscissae: unit dose of cocaine in milligrams per kilogram per injection. Top ordinate: percent cocaine choice. Middle ordinate:rates of responding in responses per second. Bottom ordinate: number of choices completed. All points represent mean data SEM obtainedduring the last 3 days of methadone treatment. These published data [18] demonstrate that experimental manipulations can selectivelydecrease rates of responding and the number of choices completed without decreasing cocaine choice.

Before proceeding, two other points are worthy ofmention. First, although choice procedures are sparinglyused in preclinical studies of drug reinforcement, they haveemerged as the standard approach in clinical studies of drugreinforcement [23, 24]. Consequently, increased preclini-cal use of choice procedures might facilitate translationalresearch on drug reinforcement. Second, scientific interest indrug reinforcement derives in large part from its presumedrole in drug addiction, and drug addiction can be defined asa disorder of choice and behavioral allocation [25, 26]. More-over, 5 of the 7 diagnostic criteria for substance dependencein the revised fourth edition of the Diagnostic and StatisticalManual (DSM) of Mental Disorders are defined by allocationof behavior towards procurement and use of the substancecompared to other behavior maintained by nondrug andpresumably more adaptive alternative reinforcers [27]. In thefifth edition of the DSM that is still under development,6 of the 11 diagnostic criteria are defined by behavioralallocations toward the procurement and use of the substance

[28]. Thus, addiction implies excessive drug choice at theexpense of more adaptive behaviors. The pharmacological,environmental, and genetic determinants that influence drugchoice and contribute to drug addiction can be directlystudied using choice procedures.

2. Determinants of Drug Choice

2.1. Overview. While the first drug choice procedure waspublished in 1940 [20] by Spragg it was not until 1972that the first intravenous drug choice procedure was pub-lished, approximately 10 years after intravenous drug self-administration procedures were introduced [5]. In theirseminal study, Findley et al. [29] examined the effectsof dependence and withdrawal on secobarbital and chlor-diazepoxide preference. Since 1972, there have been 66publications examining the determinants of drug choice,and these publications are summarized in Table 1. Thepredominant drugs examined have been cocaine (80%)


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and heroin (15%). Furthermore, nonhuman primates havebeen the predominant research subjects (81%) utilized inthese studies, with rhesus monkeys (70%) being the mostcommonly used species. The results and implications of thisliterature will be reviewed in more detail below.

2.2. Choice between Drug and Itself

2.2.1. Effect of Dose. One of the first fundamental researchquestions to be answered was whether drug choice wasdose-dependent. This question was important in deter-mining whether drug choice varied independently of ratesof responding as drug dose increased, such that, choicewould increase and response rates decrease as a function ofincreasing drug doses. Although this specific experimentalquestion has only been explicitly examined using intravenouscocaine as the reinforcer and rhesus monkeys as the researchsubjects, animals almost always choose the larger drug dose[9, 30–33]. Furthermore, in the manuscripts that did reportrates of responding, there was no systematic relationshipbetween cocaine choice and rates of cocaine-maintainedresponding [30, 34]. Overall, this body of literature supportsthe conclusion that drug choice is dose-dependent and thatdrug choice may be less sensitive than single-response proce-dures to reinforcer-independent rate-altering drug effects.

2.2.2. Effect of Temporal Parameters of Reinforcer Delivery.Another fundamental question to be answered was whetherdrug choice was sensitive to manipulations in the delivery ofthe drug. In general, when equal drug doses are available asthe consequence for two response options, research subjectswill allocate their behavior equally between the two responseoptions. However, if the infusion rate was to be variedbetween the two response options, subjects will almost exclu-sively choose the dose associated with the shorter (faster)infusion rate [32, 35, 36]. The delay between response anddrug delivery is a related variable that has been manipulatedin choice studies [31, 37]. For example, Woolverton andAnderson [37] systematically varied the delay betweencompleting the response requirement and delivery of theintravenous drug injection. When the delay was 0 sec and thechoice was between a low (0.025 mg/kg/injection) and high(0.05 mg/kg/injection) unit cocaine dose, the subjects almostexclusively chose the high cocaine dose. However, increasingdelays in the delivery of the high cocaine dose produceda monotonic decrease in high cocaine dose choice and areciprocal increase in choice of the alternative low cocainedose. Overall, these data support the notion that drug choiceis highly sensitive to manipulations that affect the timingor probability of reinforcer delivery and that subjects preferreinforcers to be delivered quickly and with no delay.

2.2.3. Effect of Schedule of Reinforcement. Finally, a thirdfundamental question to be addressed was whether theprogrammed schedules of reinforcement influenced drugchoice. For example, when rhesus monkeys were given achoice between identical cocaine doses, but the probabilityof reinforcement was decreased such that every other FR5(probability 50%) or every fourth FR5 (probability 25%)

completion resulted in delivery of the cocaine injection onone of the response options, monkeys consistently chosethe response option associated with the higher probabilityof reinforcement [38]. Several laboratories have examinedthe effects of schedule manipulations under concurrentvariable-interval (VI): VI schedules. Under a VI scheduleof reinforcement, the first response after a variable amountof time has passed results in presentation of the reinforcer.The variability in time is anchored at some programmedtime interval by the investigator such that, on average, theinterval of reinforcement is the anchored time, for example600 sec. Most of the studies have examined cocaine versuscocaine choice [30, 33, 39, 40], but a few have also examinedother drugs such as the mu-opioid agonists alfentanil [41] orremifentanil [42] and the barbiturate methohexital [41, 42].In general, these studies have been used to demonstratethat drug self-administration procedures adhere well tothe predictions of the matching law, which posits that theallocation of behavior between two response options willmatch the frequency of reinforcement associated with thoseoptions [30, 33, 39–41]. Moreover, as predicted, subjectswill chose reinforcers delivered under shorter versus longerVI schedules. In contrast to concurrent VI: VI schedules,only one published study has examined the effects ofmanipulating the response requirement under a concurrentfixed-ratio (FR): FR schedule of choice between a drug anditself [31]. In this study, only one of the three monkeyswas sensitive to FR manipulations such that increases in theFR requirement decreased choice of the higher unit cocainedose and produced a reciprocal increase in choice of thelower unit cocaine dose. Thus, choice behavior maintainedunder concurrent FR: FR schedules appears to be morequantal than choice behavior maintained under current VI:VI schedules. Overall, this body of the literature suggests thatsubjects prefer schedules of reinforcement that produce thehigher probability of reinforcement.

2.3. Choice between Drug and Alternatives

2.3.1. Behavioral Economic Considerations. One method tounderstand how concurrently available reinforcers interact isto apply conceptual frameworks employed by behavioral eco-nomics [43, 44]. Based on economic theories, concurrentlyavailable reinforcers can interact in one of three ways [44,45]. First, concurrently available reinforcers can function assubstitutes; such that as the price of one reinforcer increases,choice of that reinforcer decreases and is replaced by choiceof the substitute. The perfect substitute for a commodityis itself, so that studies summarized above that consideredchoice between a drug and itself could be conceptualized aschoice between substitutes. However, different commoditiescan also function as economic substitutes for each other.For example, potato chips and pretzels can function assubstitutes, such that as the price of potato chips increases,consumption of potato chips decreases and consumptionof pretzels increases. Secondly, concurrently available rein-forcers can function as complements; under this condition,as price of one reinforcer increases, choice of that reinforcer,and choice of a complement also decreases. For example,


peanut butter and jelly can function as complements, and asthe price of peanut butter increases, choice of both peanutbutter and jelly decreases. Finally, concurrently availablereinforcers can function as independents, such that changes inthe price and consumption of one reinforcer would have noeffect on choice of an independent reinforcer. For example,peanut butter and shoes typically function as independents,such that as the price of peanut butter increases andchoice of peanut butter decreases, and consumption ofshoes is unlikely to change. The interaction between twoconcurrently available reinforcers will be an important con-sideration in the following sections. In general, alternativereinforcers used in studies of drug choice are expected tofunction as substitutes, but this is an empirical question.

2.3.2. Drug versus Other Drugs. To ascertain the relativereinforcing efficacy of two different drugs in maintainingbehavior, a choice procedure could be programmed. Asstated earlier, a significant advantage of choice proceduresis that the primary dependent measure (behavioral allo-cation or choice) is less confounded by reinforcement-independent rate-altering drug effects. Critical factors toconsider when assessing the relative reinforcing efficacybetween two different drugs are dose, pharmacokinetics, andpharmacodynamics. The entire literature on choice betweentwo drugs has employed cocaine versus “drug X” choiceprocedures, with “X” being the dopamine (DA) uptakeinhibitor methylphenidate [10, 31], the sodium channelblocker procaine [46], the monoamine releaser cathinone[47], DA agonists [48], nicotine [49], the DA uptakeinhibitor 2β-propanoyl-3β-(4tolyl)-tropane (PTT) [50], orthe mu-opioid agonists remifentanil [51] and heroin [52].In general, these studies have reported that as dose ofthe alternative drug reinforcer increased, cocaine choicedecreased. Such results are consistent with the conclusionthat the alternative drug functioned as a substitute forcocaine. However, there were two notable exceptions. Whenchoice was between cocaine versus procaine [46] or cocaineversus nicotine [49], cocaine choice predominated despiteincreasing doses of procaine or nicotine or decreasing dosesof cocaine. Moreover, only one study has explicitly examinedwhether two drugs function as substitutes, complements, orindependents. In monkeys choosing between cocaine andthe mu-opioid agonist remifentanil, remifentanil was foundto function as a behavioral economic substitute for cocaine[51]. Overall, drug versus drug choice procedures can beuseful for assessing the relative reinforcing efficacy of twodifferent compounds and this procedure may hold utility inabuse liability testing.

2.3.3. Drug versus Nondrug Reinforcers. Analysis of the choicestudies in Table 1 revealed that 61% (41/67) used a nondrugalternative reinforcer with 93% (38/41) of these studiesusing food and 7% (3/41) using saccharin or sucrose asthe alternative. In the first drug versus nondrug choice pro-cedure, rhesus monkeys were allowed to choose betweencocaine injections and food in a closed economy, such thatno other food source was available outside of the choiceprocedure [53]. Over the 8 experimental days, monkeys

almost exclusively choose cocaine over food despite bodyweight decreases of 6 to 10% over the course of the 8days. More recent studies have utilized other experimentaldesigns to evaluate the effects of multiple cocaine dosesversus food using a within-session choice procedure [17, 54–56]. For example, Figure 1 demonstrates that a completecocaine versus food dose-effect function can be determinedwithin a single daily experimental session. Cocaine choiceincreased in a monotonic function demonstrating that therelative reinforcing efficacy of cocaine versus food is dose-dependent. Furthermore, this monotonic increase in cocainechoice was in contrast to rates of responding, which displayedthe prototypic inverted U-shaped dose-effect function. Thus,the example shown in Figure 1 clearly demonstrates the dis-sociation between using dependent measures of behavioralallocation (choice) and behavioral rate discussed above as amain rationale for the use of drug choice procedures.

As was evident in drug versus drug choice proce-dures described above, the magnitude of the alternativenondrug reinforcer, programmed schedule consequences,and reinforcement delay were also important independentvariables that could impact drug choice [37, 55, 57–60].For example, increasing the magnitude of the alternativefood reinforcer was shown to decrease cocaine choice [55,57]. In another example, heroin versus food choice wasdecreased by increasing the intertrial interval [60]. Theseresults suggest that under economic conditions where accessto reinforcers was restricted, baboons choose food over a lowdose of heroin. Moreover, if the reinforcing value of food wasdecreased by providing supplemental access to food beforethe cocaine versus food choice procedure, cocaine choiceincreased [55, 59].

While most of the drug versus nondrug alternative choiceprocedures discussed so far used nonhuman primates asresearch subjects, there is a small, but growing body ofliterature of drug versus food choice procedures in rodents.For example, a recent study by Thomsen et al. [61]established a within-session cocaine dose-effect versus ensurechoice procedure similar to the within-session cocaine dose-effect versus food choice procedure shown in Figure 1. Otherrodent studies have demonstrated that introduction of analternative nondrug reinforcer such as a glucose/saccharinsolution [62] or food [63, 64] will attenuate cocaine ormethamphetamine choice. In contrast to these other rodentstudies, rats choosing between cocaine injections and 0.2%saccharin never chose cocaine over the saccharin solution[65]. This later result suggests that 0.2% saccharin is a verystrong and highly preferred reinforcer in rats. Overall, thisbody of literature demonstrates that nondrug reinforcers candecrease drug choice, but that reinforcer selection, reinforcermagnitude, delay of reinforcement, and reinforcer accessconditions are all key independent variables to be consideredin drug versus nondrug choice procedures.

2.3.4. Drug versus Compound Consequent Stimuli. In general,two categories of studies have investigated drug choice inthe context of another compound consequent stimulus.One category has involved assessment of choice involvingdrug plus another putative reinforcer (e.g., drug + drug or


drug + food). For example, when contingencies were pro-grammed such that one response option produced a highheroin dose and a second response option produced a lowerheroin dose delivered in combination with food, monkeysreallocated their behavior away from the high dose herointowards lower heroin doses plus food [66]. Other studieshave examined choice between (a) food and either cocainealone or cocaine + mu-opioid agonist, or (b) choice betweenfood and either mu agonist alone or delta-opioid + muagonist [67–70] and, in general, reported that the relativereinforcing efficacies of these drug mixtures were additive.

The other category has involved pairing one of thechoices with a putative punisher, such as electric shock[71] or intravenous histamine [72, 73]. For example, Johan-son [71] examined choice between cocaine alone versuscocaine + electric shock. In all of these studies, the punisherwas effective in decreasing choice of the reinforce + punisherand increasing choice of the alternative reinforcer [71–73]. However, effects of punishment on drug choice couldbe mitigated by increasing the drug dose [71] associatedwith the punisher, decreasing the intensity of the punisher[72, 73], or increasing the delay between delivery of thereinforcer and delivery of the punisher [73]. Furthermore,pairing the punisher with the alternative reinforcer can alsoincrease drug choice. For example, in a study of cocaineversus food choice, histamine injections paired with cocainedecreased cocaine choice, but if the histamine injections werepaired with food, cocaine choice increased [72]. Moreover,these studies highlight the potential for cocaine use tobe influenced by environmental contingencies that maygovern choice of nondrug alternative reinforcers. Overall,these results highlight the utility of concurrent schedules ofreinforcement to understand relatively sophisticated behav-iors maintained by complex, compound consequent stimuli.Moreover, the use of choice procedures to understandabuse of multiple drugs, drug mixtures, and drug + otherconsequent stimuli is a scientific space that remains relativelyunexplored.

2.4. Other Factors Affecting Drug Choice

2.4.1. Effect of Drug Dependence and Withdrawal. Most pub-lished studies examining effects of dependence and with-drawal on drug choice have focused on opioids [66, 74–78].In contemporary experimental designs examining choice ofmu agonists such heroin or the short-acting opioid remifen-tanil, the total amount of opioid available during dailychoice sessions is sufficiently limited to prevent developmentof significant opioid dependence. Under these nondepen-dent conditions, opioid choice can be effectively reducedby treatment with opioid antagonists like naloxone [76].However, if opioid dependence is established by chronic non-contingent opioid treatment or by permitting supplementaldaily access to contingent opioid self-administration, thendrug effects on opioid choice change dramatically. So longas dependence is maintained by opioid agonist exposure,opioid choice during choice sessions is generally maintained(when the alternative is food, [76, 79]) or reduced in somesubjects (when cocaine is the alternative, [78]). However,

either spontaneous withdrawal or antagonist-precipitatedwithdrawal produce robust increases in opioid choice, andthis withdrawal-associated increase in opioid choice can beblocked by opioid agonists such as methadone, which areeffective maintenance medications for treatment of opioidaddiction [75, 76, 78, 79]. Overall, then, opioid withdrawalin opioid-dependent subjects increases opioid choice, andopioid agonists that are effective maintenance medicationsfor treatment of opioid addiction can block this withdrawal-associated increase in opioid choice.

In contrast to the opioid dependence literature citedabove, minimal research has been conducted examiningthe effects of dependence and withdrawal on drug choicemaintained by other drug classes. Consistent with theopioid studies described above, Findley and colleagues [29]reported that withdrawal from the barbiturate secobarbitalin secobarbital-dependent subjects increased choice of lowersecobarbital doses versus food. However, similar results havenot been demonstrated with cocaine. For example, Banksand Negus [80] evaluated cocaine versus food choice whensubjects were exposed to and withdrawn from supplementaldaily access to cocaine self-administration under conditionsidentical to those used to establish opioid dependence [76].During supplemental cocaine access, daily cocaine intakeincreased more than 10-fold and was sufficient to dis-rupt performance during choice sessions; however, neitherexposure to nor withdrawal from supplemental cocainesignificantly altered cocaine versus food choice. The extentto which drug dependence and withdrawal alters drug choiceof other drug classes, such as benzodiazepines, monoaminereleasers, or N-methyl D-aspartate antagonists, remains to beelucidated.

2.4.2. Effect of Pharmacological Variables. Another importantbody of literature has examined effects of pharmacologicalmanipulations on drug choice, either to evaluate effects ofcandidate antiaddiction medications or to evaluate mech-anisms of drug reinforcement. Effects of opioid agonistsand antagonists on opioid choice in nondependent andopioid-dependent rhesus monkeys was described above, andadditional studies have investigated potential mechanismsthat may underlie withdrawal-associated increases in opioidchoice. For example, opioid withdrawal functions as a stres-sor to activate endogenous release of the stress-related neuro-transmitters dynorphin and corticotrophin releasing factor(CRF). This suggested that the hypothesis that either dynor-phin acting at kappa-opioid receptors or CRF acting atCRF1 receptors might contribute to withdrawal-associatedincreases in opioid reinforcement; however, neither thekappa antagonist 5′-guanidinonaltrindole nor the CRF anta-gonist antalarmin was as effective as morphine in blockingwithdrawal-associated increases in opioid choice [79].

A total of 10 studies have investigated pharmacologicalmodulation of cocaine versus food choice. In studies exam-ining candidate “agonist” medications for cocaine addiction,DA-selective monoamine releasers, such as d-amphetamineand phenmetrazine, significantly decreased cocaine choice,whereas mixed DA-serotonin (5HT) releasers or 5HT-selecitve releasers did not [17, 55, 81]. Importantly, these


studies demonstrated a selective decrease in cocaine choicewithout also decreasing rates of behavior, and a rep-resentative example of this selective effect is shown inFigure 2 during treatment with the DA-selective releaser m-fluoroamphetamine. The atypical antipsychotic and DA D2receptor partial agonist aripiprazole also decreased cocainechoice in rats after acute treatment, although this effectwas not sustained during repeated treatment, and neitheracute nor repeated aripiprazole altered cocaine choice inrhesus monkeys [61, 82]. Treatment with the benzodiazepineagonist diazepam also decreased cocaine choice in rats [83].In contrast to these studies showing decreases in cocainechoice, cocaine choice was increased by treatment with a5HT1A agonist, a kappa-opioid, agonist and high doses ofdopamine receptor antagonists [55, 84–86]. Finally, othertreatments that have failed to alter cocaine choice up to dosesthat suppress responding include methadone and lithium[18, 87]. Overall, this body of the literature suggests that drugchoice is sensitive to both acute and chronic pharmacologicalmanipulations, that pharmacological effects on drug choicecan be dissociated from other drug effects, and that thereis a clear need for more research in understanding thepharmacological mechanisms of drug choice.

One final point regarding the effects of pharmacologicalvariables on drug choice is worth mentioning. An over-arching rationale for preclinical studies investigating thepharmacological determinants of drug self-administrationis the development of candidate medications to treat drugaddiction. Moreover, a main goal of pharmacotherapyshould be not only to decrease drug-taking behavior, butalso to reallocate behavior to activities maintained by moreadaptive reinforcers [88]. Thus, in preclinical studies thataspire to evaluate candidate medications for drug addiction,choice procedures can play a critical role in the preclinicaldrug development process to determine whether a givenexperimental manipulation produces this critical reallocationof behavior [19, 24]. Furthermore, human laboratory studiesprovide an additional critical step in drug developmentbetween animal studies and clinical trials, and human lab-oratory research to evaluate effects of candidate medicationson drug self-administration relies exclusively on drug versusnondrug choice procedures [24]. Consequently, the use ofchoice procedures in preclinical studies may facilitate trans-lation of results to choice procedures in human laboratorystudies at this critical juncture in the drug developmentprocess, and existing data suggest excellent concordancebetween medication effects on drug choice in animals andhumans [55, 85, 89–91].

2.4.3. Effect of Other Environmental Variables. An emergingbody of research has also addressed the degree to which non-pharmacological environmental variables might alter drugchoice. In one example, monkeys were housed in a socialcontext to establish a dominant-subordinate hierarchy toexamine the effects of social rank on cocaine versus foodchoice [92]. One main rationale for this study was thatthe initial differences between dominant and subordinatemonkeys in cocaine-maintained responding under a simple

FR schedule disappeared over time as the cocaine self-administration history progressed. Under the concurrentFR: FR schedule of cocaine and food reinforcement, thedifferences between dominant and subordinate monkeyswere recaptured. Furthermore, cocaine choice in sociallyhoused monkeys was decreased by manipulations of envi-ronmental variables that were perceived to be enriching(increased cage size), whereas cocaine choice was decreasedby environmental variables that were perceived to be stressful(exposure to rubber snake) [56]. Another study examinedthe effects of ambient temperature on choice between 3,4-methylenedioxymethamphetamine (MDMA) and food inrhesus monkeys [93]. Compared to room temperature, coolambient temperatures decreased MDMA choice and warmambient temperatures increased MDMA choice. Similarstudies on these and other environmental variables willplay a key role in future research to identify environmentalmechanisms that may differentially affect the reinforcingstrength of drugs and underlie vulnerability to or protectionfrom drug addiction.

2.4.4. Effect of Subject-Related Biological Variables. Intraven-ous drug choice procedures have been conducted in var-ious species including, rats [62], squirrel monkeys [82],cynomolgus [92] and rhesus [29] macaques, and baboons[66]. However, there is substantial opportunity for moresystematic research on the role of these and other subject-related variables, such as gender, genotype, or physiologicalstate. To the best of our knowledge, there is only one examplewhere a subject-related variable was manipulated in thecontext of drug choice. In this study, exogenous thyroidhormone was administered to induce a hyperthyroid stateduring MDMA versus food choice [94]. Although thyroidhormone treatment enhanced the thermogenic effects ofMDMA, this treatment did not significantly alter MDMAchoice. Moreover, drug choice studies can be expected tocontribute important insights that might not be apparentfrom single-response or active/inactive-response procedures.Specifically, as has been emphasized repeatedly above, drugchoice is strongly determined by factors that influence thereinforcing strength of alternative reinforcers. Consequently,it should be anticipated that some subject-related variableswould have profound effects on drug choice by modulatingthe reinforcing strength of alternative reinforcers whileproducing little or no direct changes in the reinforcingstrength of the drug.

3. Implications and Future Directions

Research on the reinforcing effects of drugs has been slowto adopt concurrent schedules of reinforcement; however,this paper has argued that choice procedures can play auseful role in preclinical research on drug reinforcementand determinants of drugs use. There are still critical gapsin our knowledge, and there remains much intellectualspace to be explored. One future direction might be theestablishment of drug versus nondrug alternative choiceprocedures involving abused drugs other than the classicalcompounds cocaine and heroin. The degree to which drug


choice can be maintained by other novel drug class such asbenzodiazepines, cannabinoids, and nicotine remains to beelucidated. Another future direction might be to examinethe impact of nondrug alternative reinforcers other thanfood. Food is an easy alternative reinforcer to controlin preclinical laboratories, but there are certainly othernondrug reinforcers (e.g., access to receptive mate or socialinteractions) that are available as research tools that have yetto be fully explored. As one example of a choice procedureusing a nondrug alternative reinforcer other than food,one intriguing study examined effects of putative anorecticdrugs on choice between food and visual access to a roomcontaining other monkeys [95]. This type of social reinforcerhas yet to be manipulated in studies of drug choice. Finally,a third potential future direction is the integration of drugreinforcers into decision-making “choice” tasks commonlyused to assess cognitive function. For example, impaireddelay discounting is a cognitive trait commonly linkedto drug abuse [96, 97], and delay discounting is oftenassessed preclinically in assays that compare choice betweena delayed high-magnitude reinforcer and an immediate low-magnitude reinforcer [98]. Strikingly, preclinical researchwith this type of assay has relied exclusively on food asthe consequent stimulus. The introduction of drugs asreinforcers into delay discounting and other cognitive tasksmay provide new insights into the relationship betweencognitive function and drug use. Overall, the body ofliterature cited in this paper supports the notion that choiceprocedures can facilitate data interpretation by providing arate-independent measure of drug reinforcement, improveconcordance between preclinical and clinical studies intranslational research, and provide experimental access tocritical independent variables that influence drug choice anddrug addiction in natural environments.

Acknowledgments

The authors would like to acknowledge funding from theNational Institute on Drug Abuse, National Institutes ofHealth under Grants R01-DA026946 and R01-DA031718.

References

[1] N. A. Ator and R. R. Griffiths, “Principles of drug abuseliability assessment in laboratory animals,” Drug and AlcoholDependence, vol. 70, no. 3, pp. S55–S72, 2003.

[2] L. P. Carter and R. R. Griffiths, “Principles of laboratoryassessment of drug abuse liability and implications for clin-ical development.,” Drug and Alcohol Dependence, vol. 105,supplement 1, pp. S14–S25, 2009.

[3] B. F. Skinner, The Behavior of Organisms, Appleton-Century-Crofts, New York, NY, USA, 1938.

[4] C. B. Ferster and B. F. Skinner, Schedules of Reinforcement,Appleton-Century-Croft, New York, NY, USA, 1957.

[5] J. R. Weeks, “Experimental morphine addiction: method forautomatic intravenous injections in unrestrained rats,” Sci-ence, vol. 138, no. 3537, pp. 143–144, 1962.

[6] J. R. Weeks and R. J. Collins, “Factors affecting voluntarymorphine intake in self-maintained addicted rats,” Psy-chopharmacologia, vol. 6, no. 4, pp. 267–279, 1964.

[7] A. Young and S. Herling, “Drugs as reinforcers: studies in lab-oratory animals,” in Behavioral Analysis of Drug Dependence,S. Goldberg and I. Stolerman, Eds., pp. 9–67, Academic Press,Orlando, Fla, USA, 1986.

[8] J. Katz, “Drugs as reinforcers: pharmacological and behav-ioral factorsin,” in The Neuropharmacological Basis of Reward,J. Leibman and S. Cooper, Eds., pp. 164–213, ClarendonPress, Oxford, UK, 1989.

[9] C. Iglauer and J. H. Woods, “Concurrent performances:reinforcement by different doses of intravenous cocaine inrhesus monkeys,” Journal of the Experimental Analysis ofBehavior, vol. 22, no. 1, pp. 179–196, 1974.

[10] C. E. Johanson and C. R. Schuster, “A choice procedurefor drug reinforcers: cocaine and methylphenidate in therhesus monkey,” Journal of Pharmacology and ExperimentalTherapeutics, vol. 193, no. 2, pp. 676–688, 1975.

[11] N. K. Mello and S. S. Negus, “Preclinical evaluation ofpharmacotherapies for treatment of cocaine and opioidabuse using drug self-administration procedures,” Neuropsy-chopharmacology, vol. 14, no. 6, pp. 375–424, 1996.

[12] G. Zernig, G. Wakonigg, E. Madlung et al., “Do vertical shiftsin dose-response rate-relationships in operant conditioningprocedures indicate ‘sensitization’ to ‘drug wanting’?” Psy-chopharmacology, vol. 171, no. 3, pp. 349–363, 2004.

[13] R. Meisch and G. Lemaire, “Drug self-administration,” inMethods In Behavioral Pharmacology, F. Van Haaren, Ed., pp.257–300, Elsevier, Amsterdam, The Netherlands, 1993.

[14] G. Deneau, T. Yanagita, and M. H. Seevers, “Self-admin-istration of psychoactive substances by the monkey-a mea-sure of psychological dependence,” Psychopharmacologia, vol.16, no. 1, pp. 30–48, 1969.

[15] R. T. Kelleher and S. R. Goldberg, “General introduction:control of drug taking behavior by schedules of reinforce-ment,” Pharmacological Reviews, vol. 27, no. 3, pp. 291–299,1975.

[16] R. Pickens and T. Thompson, “Cocaine-reinforced behaviorin rats: effects of reinforcement magnitude and fixed-ratiosize.,” Journal of Pharmacology and Experimental Therapeu-tics, vol. 161, no. 1, pp. 122–129, 1968.

[17] M. L. Banks, B. E. Blough, and S. S. Negus, “Effects ofmonoamine releasers with varying selectivity for releas-ing dopamine/norepinephrine versus serotonin on choicebetween cocaine and food in rhesus monkeys,” BehaviouralPharmacology, vol. 22, no. 8, pp. 824–836, 2011.

[18] S. S. Negus and N. K. Mello, “Effects of chronic methadonetreatment on cocaine- and food-maintained respond-ing under second-order, progressive-ratio and concurrent-choice schedules in rhesus monkeys,” Drug and AlcoholDependence, vol. 74, no. 3, pp. 297–309, 2004.

[19] S. S. Negus and M. L. Banks, “Making the right choice:lessons from drug discrimination for research on drugreinforcement and drug self-administration,” in Drug Dis-crimInation: Applications To MedicInal Chemistry and DrugStudies, R. A. Glennon and R. Young, Eds., pp. 361–388, JohnWiley and Sons, Holboken, NJ, USA, 2011.

[20] S. D. S. Spragg, “Morphine addiction in chimpanzees,” inComparative Psychology Monographs, pp. 1–132, The JohnHopkins Press, Baltimore, Md, USA, 1940.

[21] J. R. Nichols and W. M. Davis, “Drug addiction. II. Variationof addiction,” Journal of the American Pharmacists Associa-tion, vol. 48, pp. 259–262, 1959.

[22] G. M. Heyman, “Ethanol regulated preference in rats,”Psychopharmacology, vol. 112, no. 2-3, pp. 259–269, 1993.


[23] S. D. Comer, J. B. Ashworth, R. W. Foltin, C. E. Johanson,J. P. Zacny, and S. L. Walsh, “The role of human drug self-administration procedures in the development of medica-tions,” Drug and Alcohol Dependence, vol. 96, no. 1-2, pp. 1–15, 2008.

[24] M. Haney and R. Spealman, “Controversies in translationalresearch: drug self-administration,” Psychopharmacology, vol.199, no. 3, pp. 403–419, 2008.

[25] G. H. Heyman, Addiction: A Disorder of Choice, HarvardUniversity Press, Cambridge, Mass, USA, 2009.

[26] R. Hernstein and D. Prelec, “A theory of addiction,” in ChoiceOver Time, G. Loewenstein and J. Elster, Eds., pp. 331–360,Russell Sage Press, New York, NY, USA, 1992.

[27] American Psychiatric Association, Diagnostic and StatisticalManual of Mental Disorders, vol. 992, American PsychiatricAssociation, Washington, DC, USA, Fourth edition, 2000.

[28] America Psychiatric Association, 2012, http://www.dsm5.org/proposedrevision/Pages/SubstanceUseandAddictiveDis-orders.aspx.

[29] J. D. Findley, W. W. Robinson, and L. Peregrino, “Addictionto secobarbital and chlordiazepoxide in the rhesus monkeyby means of a self-infusion preference procedure,” Psy-chopharmacologia, vol. 26, no. 2, pp. 93–114, 1972.

[30] C. Iglauer, M. E. Llewellyn, and J. H. Woods, “Concurrentschedules of cocaine injection in rhesus monkeys: dosevariations under independent and non independent variableinterval procedures,” Pharmacological Reviews, vol. 27, no. 3,pp. 367–383, 1975.

[31] C. E. Johanson, “Pharmacological and environmental vari-ables affecting drug preference in rhesus monkeys,” Pharma-cological Reviews, vol. 27, no. 3, pp. 343–355, 1975.

[32] K. G. Anderson and W. L. Woolverton, “Effects of doseand infusion delay on cocaine self-administration choice inrhesus monkeys,” Psychopharmacology, vol. 167, no. 4, pp.424–430, 2003.

[33] K. G. Anderson and W. L. Woolverton, “Dose and scheduledeterminants of cocaine choice under concurrent variable-interval schedules in rhesus monkeys,” Psychopharmacology,vol. 176, no. 3-4, pp. 274–280, 2004.

[34] M. E. Llewellyn, C. Iglauer, and J. H. Woods, “Relativereinforcer magnitude under a nonindependent concurrentschedule of cocaine reinforcement in rhesus monkeys,”Journal of the Experimental Analysis of Behavior, vol. 25, no.1, pp. 81–91, 1976.

[35] C. W. Schindler, L. V. Panlilio, and E. B. Thorndike, “Effect ofrate of delivery of intravenous cocaine on self-administrationin rats,” Pharmacology Biochemistry and Behavior, vol. 93, no.4, pp. 375–381, 2009.

[36] R. E. Sorge and P. B. S. Clarke, “Rats self-administer intra-venous nicotine delivered in a novel smoking-relevant pro-cedure: effects of dopamine antagonists,” Journal of Pharm-acology and Experimental Therapeutics, vol. 330, no. 2, pp.633–640, 2009.

[37] W. L. Woolverton and K. G. Anderson, “Effects of delay toreinforcement on the choice between cocaine and food inrhesus monkeys,” Psychopharmacology, vol. 186, no. 1, pp.99–106, 2006.

[38] W. L. Woolverton and J. K. Rowlett, “Choice maintained bycocaine or food in monkeys: effects of varying probability ofreinforcement,” Psychopharmacology, vol. 138, no. 1, pp. 102–106, 1998.

[39] W. L. Woolverton, “Intravenous self-administration ofcocaine under concurrent VI schedules of reinforcement,”Psychopharmacology, vol. 127, no. 3, pp. 195–203, 1996.

[40] W. L. Woolverton and K. Alling, “Choice under concurrentVI schedules: comparison of behavior maintained by cocaineor food,” Psychopharmacology, vol. 141, no. 1, pp. 47–56,1999.

[41] K. G. Anderson and W. L. Woolverton, “Concurrent variable-interval drug self-administration and the generalized match-ing law: a drug-class comparison,” Behavioural Pharmacol-ogy, vol. 11, no. 5, pp. 413–420, 2000.

[42] M. N. Koffarnus and J. H. Woods, “Quantification of drugchoice with the generalized matching law in rhesus mon-keys,” Journal of the Experimental Analysis of Behavior, vol.89, no. 2, pp. 209–224, 2008.

[43] S. R. Hursh, “Economic concepts for the analysis of behav-ior,” Journal of the Experimental Analysis of Behavior, vol. 34,no. 2, pp. 219–238, 1980.

[44] W. K. Bickel, R. J. DeGrandpre, and S. T. Higgins, “Thebehavioral economics of concurrent drug reinforcers: areview and reanalysis of drug self administration research,”Psychopharmacology, vol. 118, no. 3, pp. 250–259, 1995.

[45] S. R. Hursh and R. Bauman, “The behavioral analysis ofdemand,” in Advances In Behavioral Economics, L. Greenand J. Kagel, Eds., pp. 117–165, Ablex Publishing, Norwood,Mass, USA, 1987.

[46] C. E. Johanson and T. Aigner, “Comparison of the reinforcingproperties of cocaine and procaine in rhesus monkeys,”Pharmacology Biochemistry and Behavior, vol. 15, no. 1, pp.49–53, 1981.

[47] W. L. Woolverton and C. E. Johanson, “Preference in rhesusmonkeys given a choice between cocaine and d,l-cathinone.,”Journal of the Experimental Analysis of Behavior, vol. 41, no.1, pp. 35–43, 1984.

[48] A. M. Manzardo, J. A. Del Rio, L. Stein, and J. D. Belluzzi,“Rats choose cocaine over dopamine agonists in a two-leverself-administration preference test,” Pharmacology Biochem-istry and Behavior, vol. 70, no. 2-3, pp. 257–265, 2001.

[49] A. M. Manzardo, L. Stein, and J. D. Belluzzi, “Rats prefercocaine over nicotine in a two-lever self-administrationchoice test,” Brain Research, vol. 924, no. 1, pp. 10–19, 2002.

[50] J. A. Lile, D. Morgan, A. M. Birmingham et al., “Thereinforcing efficacy of the dopamine reuptake inhibitor 2β-propanoyl-3β-(4-tolyl)-tropane (PTT) as measured by aprogressive-ratio schedule and a choice procedure in rhesusmonkeys,” Journal of Pharmacology and Experimental Thera-peutics, vol. 303, no. 2, pp. 640–648, 2002.

[51] T. Wade-Galuska, G. Winger, and J. H. Woods, “A behav-ioral economic analysis of cocaine and remifentanil self-administration in rhesus monkeys,” Psychopharmacology, vol.194, no. 4, pp. 563–572, 2007.

[52] D. Caprioli, M. Celentano, A. Dubla, F. Lucantonio, P.Nencini, and A. Badiani, “Ambience and drug choice:cocaine- and heroin-taking as a function of environmentalcontext in humans and rats,” Biological Psychiatry, vol. 65, no.10, pp. 893–899, 2009.

[53] T. G. Aigner and R. L. Balster, “Choice behavior in rhesusmonkeys: cocaine versus food,” Science, vol. 201, no. 4355,pp. 534–535, 1978.

[54] C. A. Paronis, M. Gasior, and J. Bergman, “Effects of cocaineunder concurrent fixed ratio schedules of food and IV drugavailability: a novel choice procedure in monkeys,” Psycho-pharmacology, vol. 163, no. 3-4, pp. 283–291, 2002.

[55] S. S. Negus, “Rapid assessment of choice between cocaine andfood in rhesus monkeys: effects of environmental manipula-tions and treatment with d-amphetamine and flupenthixol,”Neuropsychopharmacology, vol. 28, no. 5, pp. 919–931, 2003.


[56] P. W. Czoty and M. A. Nader, “Individual differences in theeffects of environmental stimuli on cocaine choice in sociallyhoused male cynomolgus monkeys,” Psychopharmacology,vol. 224, no. 1, pp. 69–79, 2012.

[57] M. A. Nader and W. L. Woolverton, “Effects of increasingthe magnitude of an alternative reinforcer on drug choice ina discrete-trials choice procedure,” Psychopharmacology, vol.105, no. 2, pp. 169–174, 1991.

[58] M. A. Nader and W. L. Woolverton, “Effects of increasingresponse requirement on choice between cocaine and foodin rhesus monkeys,” Psychopharmacology, vol. 108, no. 3, pp.295–300, 1992.

[59] M. A. Nader and W. L. Woolverton, “Choice between cocaineand food by rhesus monkeys: effects of conditions of foodavailability,” Behavioural Pharmacology, vol. 3, no. 6, pp. 635–638, 1992.

[60] T. F. Elsmore, G. V. Fletcher, D. G. Conrad, and F. J. Sodetz,“Reduction of heroin intake in baboons by an economicconstraint,” Pharmacology Biochemistry and Behavior, vol. 13,no. 5, pp. 729–731, 1980.

[61] M. Thomsen, A. Fink-Jensen, D. P. D. Woldbye et al., “Effectsof acute and chronic aripiprazole treatment on choicebetween cocaine self-administration and food under a con-current schedule of reinforcement in rats,” Psychopharmacol-ogy, vol. 201, no. 1, pp. 43–53, 2008.

[62] M. E. Carroll, S. T. Lac, and S. L. Nygaard, “A concurrentlyavailable nondrug reinforcer prevents the acquisition ordecreases the maintenance of cocaine-reinforced behavior,”Psychopharmacology, vol. 97, no. 1, pp. 23–29, 1989.

[63] S. I. Dworkin, S. Mirkis, and J. E. Smith, “Reinforcer inter-actions under concurrent schedules of food, water, andintravenous cocaine,” Behavioural Pharmacology, vol. 1, no.4, pp. 327–338, 1990.

[64] A. Ping and P. J. Kruzich, “Concurrent access to sucrose pel-lets decreases methamphetamine-seeking behavior in Lewisrats,” Pharmacology Biochemistry and Behavior, vol. 90, no. 3,pp. 492–496, 2008.

[65] M. Lenoir, F. Serre, L. Cantin, and S. H. Ahmed, “Intensesweetness surpasses cocaine reward,” PloS one, vol. 2, no. 1,p. e698, 2007.

[66] R. M. Wurster, R. R. Griffiths, J. D. Findley, and J. V. Brady,“Reduction of heroin self-administration in baboons bymanipulation of behavioral and pharmacological condi-tions,” Pharmacology Biochemistry and Behavior, vol. 7, no.6, pp. 519–528, 1977.

[67] S. S. Negus, “Interactions between the reinforcing effects ofcocaine and heroin in a drug-vs-food choice procedure inrhesus monkeys: a dose-addition analysis,” Psychopharmacol-ogy, vol. 180, no. 1, pp. 115–124, 2005.

[68] S. J. Ward, D. Morgan, and D. C. S. Roberts, “Comparisonof the reinforcing effects of cocaine and cocaine/heroincombinations under progressive ratio and choice schedulesin rats,” Neuropsychopharmacology, vol. 30, no. 2, pp. 286–295, 2005.

[69] K. B. Freeman and W. L. Woolverton, “Self-administration ofcocaine and remifentanil by monkeys: choice between singledrugs and mixtures,” Psychopharmacology, vol. 215, no. 2, pp.281–290, 2011.

[70] G. W. Stevenson, J. E. Folk, K. C. Rice, and S. S. Negus,“Interactions between δ and μ opioid agonists in assays ofschedule-controlled responding, thermal nociception, drugself-administration, and drug versus food choice in rhesus

monkeys: studies with SNC80 [(+)-4-[(αR)-α-((2S,5R)-4-allyl-2,5-dimethyl-1-piperazinyl) -3-methoxybenzyl]-N,N-diethylbenzamide] and heroin,” Journal of Pharmacologyand Experimental Therapeutics, vol. 314, no. 1, pp. 221–231,2005.

[71] C. E. Johanson, “The effects of electric shock on respondingmaintained by cocaine injections in a choice procedure in therhesus monkey,” Psychopharmacology, vol. 53, no. 3, pp. 277–282, 1977.

[72] S. S. Negus, “Effects of punishment on choice betweencocaine and food in rhesus monkeys,” Psychopharmacology,vol. 181, no. 2, pp. 244–252, 2005.

[73] W. L. Woolverton, K. B. Freeman, J. Myerson, and L. Green,“Suppression of cocaine self-administration in monkeys:effects of delayed punishment,” Psychopharmacology, vol.220, no. 3, pp. 509–517, 2012.

[74] R. R. Griffiths, R. M. Wurster, and J. V. Brady, “Discretetrial choice procedure: effects of naloxone and methadone onchoice between food and heroin,” Pharmacological Reviews,vol. 27, no. 3, pp. 357–365, 1975.

[75] R. R. Griffiths, R. M. Wurster, and J. V. Brady, “Choicebetween food and heroin: effects of morphine, naloxone,and secobarbital.,” Journal of the Experimental Analysis ofBehavior, vol. 35, no. 3, pp. 335–351, 1981.

[76] S. S. Negus, “Choice between heroin and food in non-dependent and heroin-dependent rhesus monkeys: effectsof naloxone, buprenorphine, and methadone,” Journal ofPharmacology and Experimental Therapeutics, vol. 317, no. 2,pp. 711–723, 2006.

[77] S. S. Negus, “Opioid antagonist effects in animal modelsrelated to opioid abuse: drug discrimination and drug self-administration,” in Opiate RecepTors and Antagonists: FromBench To Clinic, R. Dean, E. J. Bilsky, and S. S. Negus, Eds.,pp. 201–226, Humana Press, New York, NY, USA, 2009.

[78] T. Wade-Galuska, C. M. Galuska, and G. Winger, “Effectsof daily morphine administration and deprivation on choiceand demand for remifentanil and cocaine in rhesus mon-keys,” Journal of the Experimental Analysis of Behavior, vol.95, no. 1, pp. 75–89, 2011.

[79] S. S

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