Human Laboratory Paradigms in Alcohol Research
Jennifer G. Plebani, Lara A. Ray, Meghan E. Morean, William R. Corbin, James MacKillop,
Michael Amlung, and Andrea C. King
Background: Human laboratory studies have a long and rich history in the field of alcoholism.
Human laboratory studies have allowed for advances in alcohol research in a variety of ways, including
elucidating neurobehavioral mechanisms of risk, identifying phenotypically distinct subtypes of alcohol
users, investigating the candidate genes underlying experimental phenotypes for alcoholism, and testing
mechanisms of action of alcoholism pharmacotherapies on clinically relevant translational phenotypes,
such as persons exhibiting positive-like alcohol effects or alcohol craving. Importantly, the field of
human laboratory studies in addiction has progressed rapidly over the past decade and has built upon
earlier findings of alcohol’s neuropharmacological effects to advancing translational research on alco-
holism etiology and treatment.
Methods and Results: To that end, the new generation of human laboratory studies has focused on
applying new methodologies, further refining alcoholism phenotypes, and translating these findings to
studies of alcoholism genetics, medication development, and pharmacogenetics. The combination of
experimental laboratory approaches with the recent developments in neuroscience and pharmacology
has been particularly fruitful in furthering our understanding of the impact of individual differences in
alcoholism risk and in treatment response.
Conclusions: This review of the literature focuses on human laboratory studies of subjective intoxi-
cation, alcohol craving, anxiety, and behavioral economics. Each section discusses opportunities for
phenotype refinement under laboratory conditions, as well as its application to translational science of
alcoholism. A summary and recommendations for future research are also provided.
Key Words: Human Laboratory, Alcohol Phenotypes, Alcohol and Stress, Alcohol Craving,
been utilized since the end of prohibition. Methods vary in
these paradigms including alcohol administration by either
the researcher (O’Connor et al., 1998) or the subjects them-
selves (King et al., 1997), cue administration directly related
to alcohol (Monti et al., 1987) or to increase stress levels and
subsequent desire to drink (Sinha, 2009), or administration
of self-report rating scales on craving, impulsivity and anxi-
ety in the presence of alcohol ingestion or alcohol cues
(Petry, 2001). Human laboratory studies of alcohol have
been used to understand the mechanisms underlying alcohol
UMAN LABORATORY STUDIES are not new to
the field of alcohol research, as these paradigms have
use, including reinforcement (Drobes and Anton, 2000),
craving (Monti et al., 1987), and stress induction (Sinha,
2009), as well as to evaluate potentially efficacious treatments
(Drobes et al., 2003). While clinical trials can tell us whether
a treatment is effective but not why, human laboratory stud-
ies allow for parsing alcohol and medication response into
discrete and quantifiable data. Expansion of such studies to
include other variables of interest such as impulsivity and
stress has allowed the field to address important and unique
questions about alcoholism etiology and treatment. In this
review, human laboratory phenotypes for alcoholism are dis-
cussed in the context of methodological advances, phenotype
refinement, and translation to treatment.
This review is based on recent findings from the alcohol
laboratory presented at the 2009 Annual Meeting of the
Research Society on Alcoholism. We begin with an examina-
tion of individual difference variables that are associated
with alcohol subjective responses measured in the human
laboratory (Dr. Plebani). Next, we discuss anxiety models
seeking to examine the negative reinforcing effects of alcohol
(Drs. Morean and Corbin). We then move into a discussion
of studies of alcohol craving, including cue-, alcohol-, and
stress-induced craving paradigms (Dr. Ray). Finally, we dis-
cuss impulsivity and behavioral economic models applied to
the elucidation of mechanisms of alcoholism risk (Dr.
MacKillop and Mr. Amlung). Dr. King provides a synthesis
of these findings in the context of human laboratory research
on alcoholism and offers recommendations for future
From the Departmentof Psychiatry(JGP), Universityof
Pennsylvania, Philadelphia, Pennsylvania; Department of Psychology
(LAR), University of California Los Angeles, Los Angeles, California;
Department of Psychology (MEM), Yale University, New Haven,
Connecticut; Department of Psychology (WRC), Arizona State
University, Tempe, Arizona; Department of Psychology (JM, MA),
University of Georgia, Athens, Georgia; and Department of Psychiatry
(ACK), University of Chicago, Chicago, Illinois.
Received for publication September 30, 2011; accepted October 12,
Reprint requests: Lara Ray, PhD, Department of Psychology, Univer-
sity of California Los Angeles, 1285 Franz Hall, Box 951563, Los Ange-
les, CA 90095-1563; Tel.: 310-794-5383; Fax: 310-206-5895; E-mail:
Copyright © 2012 by the Research Society on Alcoholism.
972 Alcohol Clin Exp Res, Vol 36, No 6, 2012: pp972–983
ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH
Vol. 36, No. 6
studies. Together, the studies discussed herein underscore the
empirical and clinical utility of laboratory models applied to
alcoholism, highlight opportunities for the new generation of
laboratory studies in the field, and provide a translational
framework for integrating experimental psychopathology,
neurobiology, and the clinical treatment of alcohol use dis-
LABORATORY STUDIES OF ALCOHOL EFFECTS:
INDIVIDUAL DIFFERENCES AND TRANSLATION TO
Alcohol self-administration studies have been widely used
to examine acute intoxication and alcohol reinforcement and
to examine the role of individual differences in such
responses. While historically alcohol administration studies
in humans examined social drinkers or persons at risk by
virtue of family history or personality characteristics, in
recent years, these studies have been expanded to include
other at-risk groups, such as heavy drinkers or non-treat-
ment-seeking alcohol-dependent individuals. During alcohol
challenge studies, alcohol can be administered via 1 of 2
routes—orally or intravenously. In addition, it can be either
self-administered by the subject or experimenter-adminis-
tered. Our focus here is on oral alcohol studies, which pro-
vide subjects with the cues normally associated with drinking
outside the laboratory (holding the drink, odor and taste,
etc.). Ecological validity is high as oral alcohol studies can be
designed to mirror alcohol use in the real world (Drobes
et al., 2003; O’Malley et al., 2002).
An important application of human laboratory models
of alcohol administration has been its use in the search for
risk genes for alcoholism, including tests of candidate genes
(e.g., Schuckit et al., 2005) as well as pharmacogenetic stud-
ies (Ray and Hutchison, 2007). This is an important next
step given that until recently, self-reported biologic family
history was the main method by which to establish linkage
between one’s alcohol responses and assumed inherited
predisposition to alcoholism. Prior studies have focused pri-
marily on the role of family history in predicting subjective
responses to alcohol in the laboratory and the subsequent
risk for the development of alcoholism. This approach has
also been used to examine mechanisms of medications for
alcoholism. To that end, a study by King and colleagues
(1997) showed that naltrexone (NTX) blunts the subjective
stimulation experienced after alcohol consumption only in
individuals with a positive family history of alcohol depen-
dence, but not among those with a negative family history.
Subsequent studies also demonstrated that NTX elevates
stress response, measured by adrenocorticotropic hormone
and cortisol release among those with positive family
history relative (King et al., 2002). More recent studies
extended these findings from family history to candidate
gene studies by demonstrating differential alcohol-induced
subjective experiences of reward based on genotype (cf.,
Ray and Hutchison, 2004).
While alcohol administration studies have produced
robust phenotypes capturing multiple dimensions of alcohol
intoxication as well as theoretical models to explain these
constructs (e.g., Newlin and Thomson, 1990), there is signifi-
cant variability in the samples used in this line of research.
For example, young adults have the highest rates of heavy
drinking and are overall the healthiest, which allow for safe
administration of higher doses of alcohol, making them a
convenient population for alcohol challenge studies (cf.,
King et al., 1997; Ray and Hutchison, 2004). However, the
treatment-seeking population is older and often has associ-
ated health problems. As such, more methodologically chal-
lenging laboratory studies of clinical groups is critical to
generalizing to clinical populations (Blazer and Wu, 2009).
So while older adults (55+) have traditionally been over-
looked in alcohol administration studies, they comprise a
large part of the treatment-seeking population (Verges et al.,
Another methodological and sampling issue is the fact
that the majority of human laboratory studies to date have
enrolled predominantly European American samples. As
such, questions regarding the generalizability of study find-
ings to more racially diverse populations have not been suf-
ficiently addressed. Data from the National Epidemiologic
Survey on Alcohol and Related Conditions reveal that the
overall proportion of African Americans with AUDs is
almost identical to the proportion of Caucasians with
AUDs (3.57 vs. 3.83%) (Grant et al., 2004). However, the
likelihood of being alcohol dependent at a given age appears
to differ by race, with a larger proportion of African Ameri-
cans being alcohol dependent in their later years as com-
pared to individuals of other races. There are only a few
published studies of subjective alcohol responses in African
Americans to date. This first study found a link between
subjective responses to alcohol and the risk of heavy drink-
ing and alcohol-related problems, such that acute simulation
from alcohol administration was associated with increased
risk (Pedersen and McCarthy, 2009). A recent study
extended this research to the identification of candidate
genes underlying subjective responses to alcohol in African
Americans and found that the ADH1B*3, an alcohol
metabolizing gene, was associated with higher levels of alco-
hol sedation, which in turn represents a protective factor
against the development of alcoholism (McCarthy et al.,
2010). Further, a reanalysis of the COMBINE Study focus-
ing only on African Americans did not find a significant
NTX effect, as reported for the full sample (Ray and Oslin,
2009). Together, these studies highlight recent progress and
opportunities to apply alcohol administration models, and
medication development efforts, to a wide range of patient
populations and in combination with genetic variables.
A recently completed alcohol self-administration study
among African Americans examined the effects of NTX on
subjective intoxication in this population (Plebani et al.,
2011). Non-alcohol-dependent adults of African descent
(n = 40) were recruited for participation. After consenting,
HUMAN LABORATORY PARADIGMS
genotyping, and completing the baseline assessment, each
participant completed 4 separate alcohol challenge sessions
separated by at least 10 days. During each of the sessions,
participants were administered alcohol or sham drinks, after
pretreatment with either NTX (50 mg/d) or placebo in a
double-blind and crossover fashion. The order of the 4 ses-
sions was randomly assigned. During each session, physio-
logical and subjective responses were measured.
It was hypothesized that there would be effects, as mea-
sured by self-report measures, and by breath alcohol levels,
of alcohol relative to sham drink. We further hypothesized
that pretreatment with NTX would lead to a blunting of the
reinforcing effects of alcohol relative to pretreatment with
placebo, consistent with previous reports in Caucasian sam-
ples (King et al., 1997; Ray and Hutchison, 2007). Results
supported the main effect of alcohol on measures of stimula-
tion and sedation. However, there was no significant effect of
NTX in blunting the rewarding subjective effects of alcohol
in this social drinking population. Additional studies on the
subjective effects of alcohol in African Americans who meet
alcohol dependence criteria are needed. The study had sev-
eral important strengths, including a sample comprised of
African Americans of broader age range than typical alcohol
In sum, there are important methodological issues and
recent developments in the field of alcohol challenge studies.
This line of research has refined to our understanding of how
sample characteristics, study design, or both can be used to
examine mechanisms of alcohol response in the human labo-
ratory. Each of these, either alone or in combination, can
help to parse out differences in alcohol response, which may
ultimately lead to the development of targeted treatments for
alcohol-dependent individuals with a given set of behavioral
and genetic markers.
LABORATORY MODELS OF ANXIETY AND DRINKING:
REEVALUATING THE TENSION REDUCTION MODEL
The Tension Reduction Model (TRM) of alcohol use
focuses on principles of negative reinforcement, positing
that individuals learn to drink to avoid the aversive experi-
ence of stress-induced negative emotional states (for a
review, see Conger, 1951; Greeley and Oei, 1999). As such,
risk for heavy drinking, the experience of alcohol-related
problems, and relapse is thought to increase with the num-
ber of stressful life events an individual experiences. In this
section, we will: (i) briefly describe expectancy (beliefs about
alcohol effects) and pharmacology as bases for the tension-
reducing effects of alcohol and (ii) review 2 recent studies
examining the impact of sedative alcohol effects on alcohol
Consistent with the TRM, research has identified tension
reduction expectancies as important determinants of drink-
ing behavior (for a review, see Jones et al., 2001). Rather
than exerting a direct effect on drinking, strong beliefs that
alcohol will reduce tension are thought to give rise to moti-
vation to drink (e.g., Kuntsche et al., 2006), such that indi-
viduals who drink specifically to cope with negative affect,
like anxiety, are at increased risk for heavy use and alcohol-
related problems (e.g., Catanzaro and Laurent, 2004; Kassel
et al., 2000; Neighbors et al., 2007; Rafnsson et al., 2006).
Although the research literature relating tension reduction
expectancies to drinking behavior is convincing, it tells us
little about the origins or veracity of these beliefs. The clas-
sification of alcohol as a sedative drug is consistent with the
notion that tension reduction expectancies develop through
the experience of pharmacological alcohol effects. However,
laboratory-based studies suggest that the pharmacological
effects of alcohol comprise both stimulant and sedative
properties (Earleywine and Martin, 1993). Further, alcohol
expectancies begin to develop well before alcohol use com-
mences (Dunn and Goldman, 1998). Thus, to establish a
pharmacological basis for the TRM, 2 critical lines of evi-
dence must be demonstrated: (i) consuming alcohol must
result in greater tension reduction than consuming placebo
and (ii) experiences of tension reduction after consuming
alcohol must predict subsequent drinking more strongly
than experiences of tension reduction after consuming
With respect to the first issue, a review of the relationship
between anxiety and alcohol use conducted over 20 years
ago (Wilson, 1988) provides timely insight into the question
“does alcohol reduce anxiety?” Wilson (1988, p. 371) argued
that a more accurate phrasing of the question is: “At what
dose, under which conditions, in whom, and on what meas-
ures does alcohol reduce anxiety?” Based on these factors,
alcohol can create, exacerbate, reduce, or have no effect on
anxiety. A large body of research supports this statement, as
do prominent theories of the acute effects of alcohol on
mood, cognition, and behavior [e.g., alcohol myopia (Steele
and Josephs, 1990); appraisal disruption (Sayette et al.,
2001); and stress response dampening (Sher et al., 2007)].
Although there is substantial research on the tension
reduction properties of alcohol, there is a paucity of research
examining the extent to which tension reduction increases
subsequent drinking behavior in the human laboratory.
However, 2 recent studies addressed the nature of the rein-
forcing properties of alcohol and evaluated the utility of con-
ceptualizing tension reduction as a motivational influence for
alcohol use. The first study (Corbin et al., 2008) evaluated
the extent to which experiencing sedative alcohol effects (pre-
sumably including tension reduction) during an alcohol
priming session motivated future ad libitum drinking under
conditions of anticipatory anxiety. One hundred and sev-
enty-four moderate-to-heavy drinking
(50.3% male) were randomly assigned to consume either a
placebo or a priming dose of alcohol. A target breath alcohol
concentration (BrAC) of 0.06 g% was used to increase confi-
dence that priming was not because of expectancies alone
(e.g., Fillmore and Rush, 2001). Participants consumed 3
drinks over 30 minutes to reach the target BrAC. Fifteen
minutes after consuming their final drink, participants rated
PLEBANI ET AL.
the extent to which they experienced a range of alcohol
effects and, as a marker of reinforcement value, indicated
how enjoyable they found the experience of each effect. Par-
ticipants were then informed that they would be preparing
and delivering a brief speech, a manipulation that has been
shown to increase ad libitum consumption of alcohol (Hig-
gins and Marlatt, 1975) and that was expected to increase the
salience and desirability of the experience of sedative effects
as a result of eliciting anticipatory anxiety. Before giving
their speeches, participants were given ad libitum access to
alcohol for 20 minutes or until they reached a BrAC of
0.12 g%. Based on the TRM, individuals who experienced
pleasurable sedative effects during the alcohol prime were
expected to consume more alcohol during the ad-lib session
to modulate the anticipatory anxiety associated with giving a
speech. Unexpectedly, the exact opposite pattern of results
emerged. Participants universally evaluated sedative effects
more negatively than stimulant effects, and neither expecting
nor experiencing sedative effects during the priming dose pre-
dicted ad-lib drinking. Thus, to the extent that increased ad-
lib consumption is a marker of reward or reinforcement, the
study results suggested that stimulant effects are more rein-
forcing than sedative effects even under conditions of antici-
patory anxiety. While inconsistent with the TRM, these
findings are consistent with research suggesting that experi-
encing increases in alertness or positive mood after consum-
ing alcohol primes further consumption both within the
laboratory context (Corbin et al., 2008; Duka et al., 1998;
Kirk and de Wit, 2000) and prospectively predicts future
heavy drinking over time (King et al., 2011).
One possible explanation for the lack of support for the
TRM in the study of Corbin and colleagues (2008) is that
sedative alcohol effects are only reinforcing for individuals
with strong beliefs about tension reduction or for those with
high-level trait anxiety, anxiety sensitivity (Novak et al.,
2003; Stewart et al., 1996), or neuroticism (Kuntsche et al.,
2006). To explore this possibility, a second placebo-
controlled study (Corbin et al., unpublished manuscript)
examined the reinforcement value of sedative effects of
alcohol for individuals who scored low, moderate, or high in
trait anxiety on the Beck Anxiety Inventory (Beck et al.,
1988). Participants consumed 3 drinks over 30 minutes,
reaching a target BrAC of 0.08 g% in the alcohol condition.
Fifteen minutes after their final drink, participants rated the
extent to which they experienced a range of alcohol effects.
Unlike the previous study, there was no anxiety manipula-
tion or ad-lib drinking session. Instead, participants’
self-reported craving for more alcohol following beverage
administration served as the index of reinforcement value of
alcohol effects. Within the alcohol condition, highly anxious
individuals (relative to those low in anxiety) were expected to
experience greater sedation, which, relative to the experience
of other alcohol effects, was expected be most strongly tied
to increases in craving for alcohol. Once again, results from
this study did not support the TRM. Individuals high in
anxiety did not report stronger experiences of sedation than
their less anxious counterparts, and sedative effects were not
associated with wanting more alcohol.
Although these 2 studies failed to support the TRM, the
results must be considered in light of a number of important
limitations. For both studies, the alcohol administration ses-
sions occurred in a simulated bar laboratory. The novel,
social drinking environment may have been more conducive
to the experience of positive, stimulant effects than sedative
effects—likely through a combination of expectancies and
subjective experiences of pharmacological effects. It is possi-
ble that the utility of the TRM may be limited to certain set-
tings or contexts (e.g., drinking alone or at home). Although
the second study included individuals high in trait anxiety, it
was not a clinical sample and diagnostic measures of anxiety
disorders were not included. Future research is needed to
determine whether a pharmacological basis for the TRM
applies only to those with anxiety disorders or clinically sig-
nificant anxiety symptoms.
In addition to the aforementioned methodological issues,
existing measures simply may not provide an adequate test
of the TRM because most do not assess a comprehensive
range of alcohol effects. For example, the Subjective High
Assessment Scale (Schuckit and Gold, 1998) focuses on
negative sedative effects (slow, drowsy), while the Biphasic
Alcohol Effects Scale (Martin et al., 1993) focuses on posi-
tive stimulant effects (elated, excited) and negative sedative
effects (down, sedated). Measures fail to assess positive low
arousal effects like anxiolysis as well as negative high arousal
effects like anxiety that are central to the TRM. However,
when mood measures, not specific to alcohol’s effects, are
added to an alcohol administration battery, a dimension of
negative reinforcement emerged in factor analysis (Ray
et al., 2009). Development of a more comprehensive subjec-
tive response measure may permit more complete tests of the
pharmacological basis for the TRM.
In sum, recent alcohol administration studies have
challenged the veracity of the TRM even within situations
in which the model seems most likely to apply and for
groups of individuals for whom the model seems most rel-
evant; sedative effects do not appear to be experienced as
desirable or to motivate alcohol use even under conditions
of anticipatory anxiety or for individuals high in trait anxi-
ety. While there is mounting evidence against a pharmaco-
logical basis for the TRM, current measures may not
adequately capture the effects that are most relevant to
evaluating the veracity of the TRM (e.g., relaxation, anxi-
ety). Development of a more comprehensive subjective
response measure will permit more complete tests of the
pharmacological basis for the TRM and may also have
additional utility. For example, high arousal negative
effects of alcohol like aggression may be important predic-
tors of alcohol-related risk-taking and negative conse-
quences. Thus, a comprehensive measure of alcohol effects
may contribute to our understanding of both internalizing
and externalizing pathways to heavy drinking and related
HUMAN LABORATORY PARADIGMS
LABORATORY MODELS OF ALCOHOL CRAVING
Craving for alcohol is defined as a strong desire to con-
sume alcohol. The proposed revisions to DSM-V have recog-
nized craving as a symptom of AUDs, defined as “a strong
desire or urge to use a specific substance” (www.dsm5.org).
A longitudinal study found that alcohol craving was associ-
ated with the highest relative risk of alcohol dependence (de
Bruijn et al., 2005). In addition, recent studies have
advanced our understanding of the genetic bases of craving
using self-report data in family-based genetic studies (e.g.,
Foroud et al., 2007), experimental designs in the laboratory
(e.g., Hutchison et al., 2005), and neuroimaging paradigms
(e.g., Filbey et al., 2008). Pharmacological studies have
also used craving paradigms to screen (Mason et al., 2009)
and to test (Hutchison et al., 2005) promising medications
for alcoholism. Given the role of craving in the phenome-
nology and treatment of alcohol dependence, several
approaches have been used to assess alcohol craving in the
In this section, we will: (i) briefly review the 3 methods for
assessing alcohol craving, namely cue-induced, alcohol-
induced, and stress-induced craving and (ii) describe a recent
study seeking to dissociate stress-induced from cue-induced
There is increased recognition that alcohol craving may be
elicited through multiple methods, including cue exposure,
stress induction, and alcohol administration. This is consis-
tent with preclinical models of relapse (Epstein and Preston,
2003). Next, we review human laboratory models of craving.
The cue-reactivity assessment paradigm is largely predi-
cated on Pavlovian conditioned responses. Specifically, when
an individual experiences repeated pairing of alcohol cues
(e.g., sight,smell, and taste of the beverage)with alcohol con-
sumption, over time, the alcohol cues themselves become
conditioned stimuli, which elicit alcohol craving. These
learned processes have been well documented in both human
(O’Brien et al., 1990) and animal (Rodd et al., 2004) models.
In the human laboratory, the cue-exposure paradigm con-
sists of systematically exposing individuals to alcohol cues
and assessing their associated urge to drink. Cue-reactivity
procedures have been found to elicit craving among most
heavy drinkers and alcohol-dependent individuals (Monti
et al., 1987) and to yield valid and reliable assessments of
alcohol craving (Monti et al., 2000, 2004; Payne et al., 1992).
However, studies have suggested thatonly 50 to 65% of alco-
hol-dependent individuals display cue reactivity defined as a
?1 standard deviation greater alcohol than water-elicited
craving (Cooney et al., 1997; Litt et al., 1990; Rubonis et al.,
The neural bases of cue reactivity have been highlighted in
prominent neurobiological models of addiction (Kalivas
and Volkow, 2005; Koob and Le Moal, 2008). Conditioned
stimuli (cues) have been shown to trigger the release of
dopamine in the ventral tegmental area, to the point where
reward itself may no longer elicit dopamine release (Schultz
et al., 1997). The nucleus accumbens is thought to mediate
responses to alcohol cues via glutamatergic projections from
the prefrontal cortex (Kalivas and Volkow, 2005). The con-
ceptualization of cue-induced craving as “wanting” is consis-
tent with the neural dissociation of reward proposed by
Berridge and Robinson (2003; Berridge et al., 2009). In
short, cue-elicited alcohol craving represents a useful transla-
tional paradigm for alcoholism.
There is considerable evidence that small “priming” doses
of alcohol increase the desire for alcohol (de Wit, 1996) and
its consumption (de Wit, 2000). From a biologic standpoint,
alcohol-induced craving has been posited to be associated
with dopaminergic brain activity, primarily in the mesolim-
bic area (de Wit, 1996). A priming dose of alcohol has been
used to induce craving in the laboratory and in brain imaging
paradigms (Filbey et al., 2008). Priming paradigms represent
an ideal analog for controlled drinking, which may be a
treatment goal particularly among first-time treatment seek-
ers (Locastro et al., 2008) or those with alcohol abuse or
mild alcohol dependence (Marlatt and Witkiewitz, 2002).
Sample characteristics, however, are critically important to
the expression of the alcohol-induced craving as priming
doses of alcohol have been shown to produce greater craving
among heavier drinkers, as compared to social drinkers
(Kirk and de Wit, 2000; de Wit, 2000). To date, the priming
effects of small doses of and the effects of alcohol cues have
been inextricably combined in oral alcohol administration
procedures in which alcohol’s pharmacology and alcohol
cues are presented in tandem. Additional studies are needed
to more fully dissociate alcohol cues from the pharmacologi-
cal effects of alcohol. To that end, intravenous alcohol
administration studies are ideally suited to dissociate alco-
hol’s pharmacology from alcohol cues and to parse different
aspects of motivation to drink induced through interoceptive
and exteroceptive cues. Additional research is also needed to
examine the effects of priming doses of alcohol on the course
of drinking episodes among treatment-seeking individuals.
Such approaches would help elucidate the pathway through
which social drinking episodes turn into heavy drinking epi-
sodes, hence jeopardizing recovery efforts.
The association between stress and alcohol use has been
well documented in both the preclinical (Koob and Kreek,
2007) and human literature (Uhart and Wand, 2009). Labo-
ratory models of stress and addiction have focused primarily
on 2 methodologies, the use of an acute social stressor (e.g.,
the Trier Social Stress Test [TSST]; Kirschbaum et al., 1993)
or the use of guided imagined exposure to stressful events
PLEBANI ET AL.
(Sinha, 2009). Studies using the TSST have suggested that
stress produces mild increases in alcohol consumption (de
Wit et al., 2003), decreases in subjective stimulant effects of
alcohol (Soderpalm and de Wit, 2002; de Wit et al., 2003),
and increases in the sedative effects of alcohol, but does not
increase self-reported desire for alcohol following alcohol
administration (Soderpalm and de Wit, 2002). A study found
that males showed greater skin conductance and higher
alcohol consumption to alcohol cues presented after stress
induction (i.e., TSST) than females (Nesic and Duka, 2006).
Although the TSST reliably produces elevations in cortisol
and subjective stress, it has been criticized for its lack of
external validity as the effects may be confined to social
The second paradigm consists of guided-imagery exposure
and is based largely on Lang’s emotional imagery methodol-
ogy (Lang, 1979; Lang et al., 1980). Specifically, this
approach consists of obtaining information about recent
stressful, neutral, and alcohol-/drug-related events in partici-
pants’ lives and using that information to develop individual-
ized scripts that are used to elicit stress under laboratory
conditions. This approach has proven to be valid, reliable,
and useful in advancing research on stress and addiction
(Sinha, 2008) and may be particularly useful in explaining
relapse (Sinha, 2007). As with the cue-induced craving para-
digms, the integration of stress pathways into laboratory
models is promising from a neurobiological perspective as
theories of addiction have highlighted disruption in stress
pathways as a central feature of addictive disorders (Koob
and Kreek, 2007).
While these 3 methods reviewed above reliably produce
the subjective experience of the craving in the human labora-
tory, less is known about how these methods interact.
Preclinical studies often dissociate stress-induced from
alcohol-induced reinstatement (Epstein et al., 2006; Heilig
and Koob, 2007). Likewise, human laboratory models have
investigated the relationship between stress and cue-induced
craving. In particular, studies examined whether exposure to
a stressor potentiates the experience of cue-induced craving.
A study by Litt and colleagues (2000) using experience sam-
pling found that participants reporting the most frequent
urges were characterized as having more severe alcohol
dependence as well as concurrent negative, high arousal
mood states (anger or anxiety), which was the most powerful
predictor of momentary urge to drink. Early work by
Cooney and colleagues (1997) combining a negative mood
induction with alcohol cue exposure found that both led to
an increase in self-reported craving, yet their effects were
additive, not interactive (or multiplicative). Similar findings
have been recently reported by Thomas and colleagues
(2011), who combined the TSST (or no stress condition) to
alcohol cue exposure in a sample of non-treatment-seeking
alcohol-dependent patients.Results revealedthatthe psycho-
logical stressor did not make the presentation of alcohol cues
more potent and that stress had no effect on self-reported
craving. Further research by Fox and colleagues (2007) using
guided exposure to situations involving stress and alcohol
cues found that while both stress and alcohol cues increased
alcohol craving, each produced a dissociable psychobio-
logical state. This dissociation suggested that while both
parameters produced physiological arousal, a blood pressure
increase was seen in the stress condition, whereas an increase
in salivary cortisol was observed in the alcohol cue condition.
Together, these results suggest that while the effects of
alcohol cues and stress exposure are likely additive, they
are not interactive as they do not potentiate one another.
Instead, there is some evidence of dissociation between stress
and cues at the psychobiological level of analysis.
To further this line of research, a recent laboratory study
(Ray, 2011) combined imaginal stress exposure with alcohol
cue exposure to assess the singular and additive effects of
stress and cues in producing alcohol craving in heavy drink-
ers (n = 64). Results suggested dissociation between stress-
induced and cue-induced craving for alcohol. Overall, indi-
viduals reached higher levels of craving upon exposure to
alcohol cues and participants for whom alcohol cues were
preceded by stress induction reported their craving to be at
an intermediate point between baseline and post-cue expo-
sure. Conversely, following the neutral imagery condition,
subjective craving did not change until cues were presented.
Similar results were found for mood variables, such as ten-
sion, which is often associated with the subjective experience
These findings suggest that stress and alcohol cues may
not have interactive or even additive effects and instead may
be dissociable in humans. This is also consistent with earlier
work, suggesting that the presence of negative mood alone,
following a mood induction, was sufficient to elicit alcohol
craving regardless of cue exposure (Litt et al., 1990) and that
negative mood predicted urges to drink (Litt et al., 2000)
and relapse (Cooney et al., 1997). Likewise, a recent labora-
tory study found that an acute psychosocial stressor
increased drinking in non-treatment-seeking alcoholics (Tho-
mas et al., 2011). This study also examined genetic determi-
nants of stress and cue-induced craving and found that a
polymorphism of the corticotropin-releasing hormone-
binding protein gene was associated with greater stress
reactivity, while the Asp40 allele of the mu opioid receptor
(OPRM1) gene was associated with stronger cue-induced
craving for alcohol (Ray, 2011). Together, these findings pro-
vide an experimental framework for combining assessments
of stress and cue-induced alcohol craving, which in turn can
be used to interrogate genetic and pharmacological factors
underlying these phenotypes. This approach has important
translational value as it more closely parallels the preclinical
literature and may be especially useful for testing mecha-
nisms of medication effects, which may be more selective for
stress or cue-induced mechanisms of craving (Heilig and
Last, while a variety of procedures have been used to
elicit alcohol craving, including the presentation of alcohol
stimuli via pictures, imagery, and smell taste cues, different
HUMAN LABORATORY PARADIGMS
methodological approaches may be better suited for differ-
ent research questions, such as brain imaging studies, and
may be uniquely informative in experimental and clinical set-
tings. For instance, a treatment study of alcohol-dependent
patients comparing 2 measures of craving, cue-elicited versus
self-reported using the Obsessive Compulsive Drinking Scale
(Anton et al., 1996), found that cue-elicited craving at base-
line was uniquely and positively associated with total num-
ber of drinks per drinking occasion over the course of
treatment, suggesting that cue-elicited craving measured in
the human laboratory may capture loss of control over
drinking during treatment (Ray et al., 2006). In sum, the
assessment of cue-induced craving in the human laboratory
has proven to be a valid and efficient tool for research on
BEHAVIORAL ECONOMIC PARADIGMS IN THE
The field of behavioral economics is a hybrid discipline
that integrates insights from economics and psychology to
understand human behavior. This approach has been exten-
sively applied not only to both normative behavior (Kahn-
eman and Tversky, 2000)
overconsumption, such AUDs and other types of addictive
behavior (Vuchinch and Heather, 2003). According to the
approach, alcohol and other drugs are powerful positive and
negative reinforcers that are akin to any other reinforcers,
comprising both benefits and costs. In the natural environ-
ment, where many concurrent behavioral opportunities are
available, an individual’s motivation to drink putatively
reflects the value of alcohol compared with the values of all
other potential opportunities in that environment (i.e., its
relative value). In turn, AUDs reflect an acquired overvalua-
tion of alcohol despite its negative physical and psychosocial
consequences, although this overvaluation may result from a
diversity of variables, including both intraindividual factors
(e.g., intense subjective cravings) and environmental factors
(e.g., absence of alternative reinforcers). In this section, we
will review the methods and insights gained from 2 primary
demand curve analysis and delayed reward discounting.
but also to pathological
Quantifying the Relative Value of Alcohol via Demand Curve
A widely used behavioral economic approach to assessing
the relative value of alcohol and other psychoactive drugs is
the assessment of substance demand and, more specifically,
demand curve analysis (for a review, see Hursh et al., 2005).
Demand is an essential concept in economics and can be
defined as the desired or actual level of consumption of a
commodity at a single price or across prices. In the latter
case, assessing demand across prices permits demand curve
analysis, or the quantitative characterization of the relation-
ship between consumption and cost. At zero or very low
prices, demand for a reinforcer is at its maximum and tends
to be relatively insensitive to initial increases in price; this
portion of the demand curve is defined as “inelastic.” How-
ever, as price increases, demand typically reaches a point at
which the decreases in consumption outpace the increases in
price; this portion of the demand curve is referred to as “elas-
tic.” Finally, beyond a certain price, consumption is com-
pletely suppressed. Across the 2 curves, individual features of
demand and expenditure provide quantitative indices of rela-
tive value. In human laboratory studies on alcohol, demand
for alcohol can be assessed using either progressive-ratio
operant schedules (Hodos, 1961), where price is defined by
increasing the behavioral response requirement, or an alco-
hol purchase task (APT; Jacobs and Bickel, 1999; Murphy
and MacKillop, 2006), in which participants estimate their
alcohol consumption at escalating monetary prices.
There is a large body of evidence indicating the impor-
tance of the relative value of alcohol as a determinant of con-
sumption and problems. Early studies using residential
laboratory approaches demonstrated that alcohol consump-
tion is substantially determined by its behavioral costs and
the presence of alternative reinforcers (for a review, see Bige-
low, 2001). More recently, studies using APTs have revealed
that indices of alcohol demand are significantly associated
with level of alcohol use, alcohol problems, and severity of
AUD symptoms (MacKillop et al., 2009, 2010a; Murphy
and MacKillop, 2006; Murphy et al., 2009). These studies
are further complemented by more naturalistic investigations
that have alcohol use has been demonstrated to inversely
vary with the availability of alcohol-free rewards in the natu-
ral environment (Tucker et al., 1994, 1995; Vuchinich and
A recent development in this area is a focus on state
changes in the relative value of alcohol. A recent study used
a state-oriented APT and found that, compared to neutral
cues, the presence of alcohol cues increased both craving
and the value of alcohol (MacKillop et al., 2010b). This
converges with several previous studies reporting correla-
tions between subjective craving and the relative value of
alcohol (MacKillop et al., 2007; McKee et al., 2008, 2009;
O’Malley et al., 2002), but extends those findings in demon-
strating that alcohol cues dynamically alter the value of
alcohol. From a clinical standpoint, this provides a behav-
ioral economic mechanism for the commonly observed
shifts in preferences following treatment: although a person
may aver the value of sobriety under neutral conditions,
alcohol cues may drive up the value of drinking and, in turn,
the probability of drinking itself. Further, a laboratory-
based APT has been used to test the relative reinforcing
value of alcohol and to serve as a drinking analog under
laboratory conditions. For example, a study by O’Malley
and colleagues (2002) gave participants the opportunity to
drink up to 8 drinks or to receive US$3 for each drink
not consumed over a 2-hour period. Results revealed that
NTX-treated participants consumed fewer drinks than
placebo-treated individuals. In short, a behavioral economic
PLEBANI ET AL.
approach to understanding alcohol consumption is both
feasible and a useful tool to examining pharmacotherapy
mechanisms of action, which may aid in screening and test-
ing novel medications.
Delay Discounting: A Behavioral Economic Index of
A second widely used behavioral economic laboratory
approach is delay discounting, an assay of impulsivity that
measures how much a future reward is discounted based on
its delay in time and putatively reflects an individual’s capacity
to delay gratification. In the laboratory, delay-discounting
tasks typically involve participants choosing between smaller
amounts of immediately available money and a constant
larger delayed amount of money over several delay time
intervals (e.g., $99 immediately vs. $100 in 1 week, $10
immediately vs. $100 in 2 weeks) (Bickel and Marsch, 2001;
Reynolds, 2006). This permits the systematic identification of
an individual’s delay-discounting function, or the internal
cognitive algorithm reflecting how rapidly the reward loses
value because of its delay in time.
Numerous studies using healthy and clinical samples have
characterized trait-level delay discounting as a behavioral
process. In reference to alcohol misuse, a number of studies
have revealed significantly more impulsive delay discounting
in problematic or clinically diagnosed drinkers compared
with healthy controls (Bjork et al., 2004; MacKillop et al.,
2010a; Mitchell et al., 2005, 2007; Petry, 2001; Vuchinich
and Simpson, 1998). Compared with controls, significantly
greater discounting has also been consistently reported in
individuals dependent on nicotine (e.g., Baker et al., 2003),
opiates (e.g., Madden et al., 1997), and stimulants (e.g., Cof-
fey et al., 2003) and exhibiting symptoms of pathological
gambling (e.g., MacKillop et al., 2006). Moreover, there is
increasing evidence that differences in discounting predate
problems with addictive behavior. For example, in animal
models, greater discounting is associated with drug use
acquisition (Anker et al., 2009; Marusich and Bardo, 2009;
Perry et al., 2005, 2007) and, in preschoolers, greater dis-
counting is associated with adult drug use 20 years later
(Ayduk et al., 2000). Importantly, discounting represents a
potential translational phenotype in addiction. For example,
a recent fMRI study has examined the neural substrates of
impulsive choice in problem drinkers using a delay-discount-
ing paradigm (Claus et al., 2011). This study found that indi-
viduals reporting greater alcohol problems showed stronger
activation of the right cuneus, left anterior insula/orbitofron-
tal gyrus, right inferior frontal gyrus, inferior parietal lobe,
left supplementary motor area, and middle temporal gyrus,
during selection of larger delayed rewards. These findings
suggest an increase in effort and neural resources needed to
delay gratification among individuals with greater alcohol
problem severity (Claus et al., 2011).
Interestingly, a number of laboratory studies have also
revealed dynamic state changes in delay discounting. Acute
withdrawal has been shown to augment impulsive discount-
ing in primate models (Carroll et al., 2009) and in both
opiate- and nicotine-dependent individuals (Badger et al.,
2007; Field et al., 2006; Mitchell, 2004). Alterations in
physiological states, such as sleep deprivation, also increase
impulsive delay discounting (Reynolds and Schiffbauer,
2004). Studies on alcohol’s effects on delay discounting have
revealed somewhat ambiguous findings, with evidence that
alcohol intoxication does not increase delay discounting
(Richards et al., 1999) or actually makes discounting less
impulsive (Ortner et al., 2003). Most recently, however, Rey-
nolds and colleagues (2006) found evidence that alcohol
intoxication does result in more impulsive delay discounting
using a real-time discounting paradigm. In this study,
healthy social drinkers completed the discounting task at 0.0
(placebo), 0.4, and 0.8 g/kg alcohol doses, and alcohol was
found to increase impulsive responding measured by the
experiential discounting task. While further studies are neces-
sary to clarify these conflicting findings, emerging evidence
supports the utility of this paradigm under a wide range of
human laboratory conditions.
CONCLUSIONS AND FUTURE DIRECTIONS
Laboratory studies of acute responses to alcohol, alcohol
cues, or other pharmacological and/or experimental manipu-
lations have progressed in important ways and have the
potential to greatly advance our understanding neurobehav-
ioral mechanisms of alcohol effects on behavior. Such para-
digms may (i) help identify important individual difference
factors affecting alcohol response, such as personal traits,
drinking characteristics, and genotype, (ii) aid in our under-
standing of the variability in cue and stress response and
craving states, and (iii) inform and augment both clinical
treatment trials and basic science and animal studies. In the
next decade, advances from molecular, psychophysiological,
and behavioral animal-based studies will need extensive
translational cross-talk to human laboratory studies, as they
represent an important bridge to establishing relevance of
preclinical findings to humans. Similarly, phenomena discov-
ered in the human laboratory will also need increased basic
science translation in the future to examine precise genetic
and epigenetic factors, neural mechanisms, and early devel-
opmental processes, many of which may be too invasive or
unethical to study in human studies. A good example of such
reverse translational approach has been recently published in
which animal models have been used to elucidate the neural
underpinnings of the genetic association between a poly-
morphism of the OPRM1 gene and subjective responses to
alcohol in the human laboratory (Ramchandani et al.,
2011). Finally, looking forward, the importance and rele-
vance of translational studies between the human laboratory
and intervention trials cannot be sufficiently underscored. In
future studies, there needs to be better synergy between the
goals of these studies, as well as their methods and partici-
pant selection, in order to more fully understand alcohol’s
HUMAN LABORATORY PARADIGMS
effects in particular subgroups, mechanisms of action of alco-
holism pharmacotherapies, and the convergence of evidence
from laboratory, proof-of-concept, to the placebo-con-
trolled, double-blinded randomized trials. Moreover, human
laboratory studies are an excellent fit for phase 2 medication
development studies, given the feasibility and clinical rele-
vance of the human laboratory models discussed above.
While over the past few decades, laboratory measures and
paradigms have expanded with increased specification,
sophistication, and validity, a number of unresolved issues
and areas for further development remain. For example,
while advances have been made in subjective assessment
tools, further refinements are warranted. As discussed earlier
in this paper, while alcohol may increase positive-like and
stimulating effects in some drinkers, it also may increase
positive sedating effects, such as feeling relaxed or calm, or
negative stimulating effects (e.g., aggression). Development
of psychometrically sound instruments to measure these, and
other subjective effects sensitive to alcohol, will increase our
scope and understanding of the differential effects of alcohol
both across and within individuals. Finally, in the next dec-
ade, further research should more clearly establish which
(and how) phenotypes derived from human laboratory para-
digms are predictive of future drinking behavior, alcohol-
related negative consequences, clinical diagnoses, and com-
orbidity. These methods will call for larger sample sizes and
more diverse samples. There is also increasing need for con-
sensus on what constitute gold standard laboratory methods
and measures to assess predisposing factors such as subjec-
tive intoxication, alcohol craving, impulsivity, stress reactiv-
ity, and stress-response dampening. Common methods will
increase consistency and allow for much needed replication
of findings across studies.
On balance, human laboratory models of alcoholism have
come a long way over the past 2 decades. In an increasingly
interdisciplinary field, these models allow for much needed
translation of preclinical findings to human samples. Like-
wise, these models allow for more mechanistic interrogation
of clinical samples (e.g., mechanisms of medication response,
mechanisms of relapse risk). Reverse translational appro-
aches are also warranted. In sum, the successful application
of human laboratory models in translational science hinges
upon the effective dialog between clinical and preclinical
scientists and upon the careful selection of methods and
samples that can cut across disciplines.
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