Clinical Relevance of Stress Neuroadaptation in Tobacco Dependence
Phase: PHASE4
Conditions: Nicotine Dependence
Sponsor: University of Wisconsin, Madison

TITLE PAGE 
Title:  Stress neuroadaptation in smokers: treatment and cessation effects 
PI Name and Institutional Affiliation:  John J. Curtin, Ph.D.  Department of Psychology, UW-Madison 
Protocol Version Date: 05/30/17 
Co-Investigators (if applicable):  Megan Piper, Tim Baker, Daniel Bolt 
Study Coordinator (if applicable): Katherine Magruder 
Funding Sponsor (if applicable):  NIDA  
 
 
 
 

PROJECT SUMMARY 
Neuroscience research with animal models implicates neuroadaptation in the stress response as a 
critical mechanism in the etiology of addiction across multiple classes of drugs including nicotine.  Repeated 
homeostatic adjustments in the brain’s stress systems due to chronic drug administration eventually lead to 
persistent compensatory adaptations in the structures involved in emotional response and its regulation.  
Among smokers, these stress neuroadaptations result in dysregulated negative affect when nicotine-deprived 
and provide the strong motivational press for further smoking that manifests as urge and increased risk for 
smoking cessation failure. 
Animal models have provided substantial evidence to support this stress neuroadaptation thesis in 
addiction However, programmatic laboratory research that examines the stress response in nicotine deprived 
and non-deprived smokers is necessary to confirm that our understanding of stress neuroadaptations from 
animal models translate to addiction etiology in smokers.  Negative affect is the core motivational element of 
the human drug withdrawal syndrome across additive drugs including nicotine.  Unfortunately, much of what 
we know about these motivationally critical affective processes in humans is based on a narrow range of 
measures collected in isolation.  The examination of the characteristics and neurobiological substrates of 
negative affect has not kept pace with the rapid conceptual, methodological, and measurement advances in 
the affective sciences over the past decade.  Moreover, complementary methods (e.g., laboratory task 
manipulations, clinical treatment interventions) and measurement approaches (e.g., psychophysiology, 
ecological momentary assessment) are rarely combined. 
The research in this application capitalizes on recent research with both animals and humans that has 
synthesized precise laboratory manipulations of stress with sensitive psychophysiological measurement of 
startle reflex potentiation to parse the affective response to stress into its constituent components.  In 
particular, startle potentiation during uncertain (vs. certain) threats holds promise as a biomarker of stress 
neuroadaptation following chronic nicotine or other drug use.  We propose to measure stress neuroadaptation 
in the laboratory via startle potentiation during uncertain threat in a validated cued threat task among nicotine 
deprived and non-deprived smokers.  Smokers will be assigned to combo NRT or placebo NRT with 
counseling during smoking cessation treatment and will report on episodic stressors, negative affect, smoking 
urge, and smoking via ecological momentary assessment procedures.  Treatment outcome will be assessed at 
2 weeks post-quit. 
The broad goals of this research are to identify etiologically relevant psychophysiological biomarkers of 
stress neuroadaptation that results from chronic smoking.  We evaluate the impact of this stress 
neuroadaptation on smokers’ real-world affect, urge and smoking during smoking cessation treatment.  We 
also evaluate if NRT can attenuate the influence of this stress neuroadaptation on smoking cessation 
outcomes via its effects on withdrawal. 
 
 
 

BACKGROUND AND SIGNIFICANCE 
 
A1:  STRESS NEUROADAPTATION AND RELATED NEGATIVE AFFECT IN SMOKING AND OTHER ADDICTIONS 
Classic and contemporary theories of addiction indicate that drug addiction results from compensatory 
changes in the neural circuitry involved in emotion and motivation (35,36).  Many of these theories specifically 
implicate neuroadaptation in the stress response as one critical mechanism in the development of addiction 
across drugs including nicotine (22–24).   Repeated homeostatic adjustments in the brain’s stress systems 
during periods of drug use eventually lead to chronic compensatory adaptations in the structures involved in 
emotional response and its regulation.  These adaptations persist beyond periods of acute use and result in 
dysregulated negative affect (e.g., increased anxiety) on cessation of use and increased risk of relapse (22).   
 
Animal models have provided substantial evidence to support this stress neuroadaptation thesis in addiction 
(22–24,26–28).  However, programmatic laboratory research that examines the stress response of drug-
deprived humans is necessary to confirm that stress neuroadaptations observed in animal models generalize 
to human addiction etiology and to explore the clinical relevance of these neuroadaptations.   
 
Stress is a broad and often ill-defined construct in both the research and clinical domains.  The stress 
response involves many systems and organs, both central and peripheral (37–42).  In this application, we 
carefully focus on only one clearly defined and operationalized component of the stress response - the 
negative affective response (anxiety) to uncertain aversive stressors.  Negative affect appears to be the 
core motivational element of the human drug withdrawal syndrome across additive drugs including nicotine 
(21,29).  Numerous studies have documented that nicotine dependent smokers in tobacco withdrawal do 
indeed report increased negative affect consistent with the stress neuroadaptation thesis (43).  In addition, self-
report questionnaires that specifically assess motives for smoking consistently identify negative affect 
reduction as an important motive for dependent smokers’ use of nicotine (44) and relative endorsement of this 
motive is a reliable predictor of smoking behavior (45).  Nicotine dependent smokers report greater expectation 
that smoking will successfully alleviate negative affect than do occasional smokers, ex-smokers, and non-
smokers (44).  Sizable correlations are typically noted between self-report measures of mood and nicotine 
withdrawal (46,47).  Factor analytic studies indicate that affective items capture much of the reliable variance in 
nicotine withdrawal measures (48).  Self-report of smoking urge has also been consistently observed to covary 
with smokers’ affective state, regardless of whether affect is manipulated experimentally or varies naturally 
(49).  Increased negative affectivity is associated with reduced smoking cessation success (50) and is a potent 
setting event for relapse to nicotine use as well (51).  Negative affective symptoms (e.g., anxiety, irritability, 
dysphoria/depressed mood) are also key criteria for nicotine withdrawal in DSM-IV.  Thus, it is clear that 
smokers report difficulty with negative affect and that this negative affect is motivationally significant as 
expected given the stress neuroadaptation thesis.   
 
Unfortunately, much of what we know about these motivationally critical affective processes in humans is 
based on a narrow range of measures.  The examination of the characteristics of negative affect has not kept 
pace with the rapid conceptual, methodological, and measurement advances in the affective sciences over the 
past decade.  In fact, the majority of the empirical research on affect during tobacco withdrawal has been 
limited to self-report methods.  Clearly, the experiential component of affect that is available to self-report is 
important and represented a tractable starting point to address theoretical questions about the  contribution of 
negative affective to nicotine dependence.  However, many affective processes are non-conscious and may 
not be available to self-report methods (52).  Moreover, self-report methods may not offer the precision 
necessary to examine important components of overall affective response (53).  Furthermore, self report is not 
ideally situated to facilitate identification of neurobiological mechanisms or to bridge between animal and 
human addiction models. 
 
Therefore, the program of research described in this application has selected a validated laboratory task (a 
cued threat task that manipulate threat uncertainty) and dependent measures (e.g., startle potentiation) from 
contemporary affective neuroscience and psychophysiology in humans and animals (see sections A2, C3).   
Preliminary research has demonstrated the promise of these tasks and measures to examine stress 
neuroadaptations in negative affective response to uncertain stressors in human addiction (see section A3).  

Similar tasks and measures have been used to detail the relevant neurocircuitry of these stress 
neuroadaptations in animal addiction models (see section A4).   
 
A2:  CUED THREAT TASKS, CERTAIN VS. UNCERTAIN THREAT, AND STARTLE POTENTIATION 
Research in affective neuroscience has relied extensively on cued threat tasks to explicate psychological and 
neurobiological mechanisms involved in the negative affective response to stressors in animals and humans 
(30,54–57).  In these tasks, visual or auditory cues are repeatedly paired with electric shock administration.  
Mechanisms involved in affective learning can be investigated via “fear conditioning” procedures in these tasks 
(52).  In humans, the cue-shock relationship can be established via instruction to examine differences in the 
expression of affective response among psychiatric groups or during drug intoxication or deprivation 
(33,34,58–60).  These flexible cued threat tasks allow for careful, parametric manipulation of cue 
characteristics, cue-shock contingencies, and participant response requirements to examine important 
influences on affective response such as the role of threat uncertainty (34,61,62), threat intensity (63), and 
attention to threats (64–66).  Comparable tasks can be used with animals and humans to facilitate identification 
of neurobiological mechanisms and encourage translation of findings from animal models to humans 
(54,57,67,68).  As such, cued threat tasks provide an attractive paradigm within which to systematically 
evaluate stress neuroadaptations critical to the etiology and treatment of nicotine dependence. 
 
Much of the affective neuroscience research with cued threat of shock tasks has relied on startle potentiation 
as the primary measure of defensive system activation in response to threat (30,31).  The use of startle 
potentiation to index affective response to threat among rodents, non-human primates, and humans has 
provided an important animal-human translational bridge in this research (30,67,68).  The use of startle 
potentiation to examine stress neuroadaptations in nicotine dependence offers the promise of similar benefit.  
Programmatic research that measures startle reflex potentiation during cues that were contingently paired with 
shock (100% cue-contingent shock) has provided clear evidence that the central nucleus of the amygdala 
(CeA) mediates defensive system activity during unambiguous, high probable, imminent threat (67).  
Systematic measurement of startle potentiation during these certain threats (e.g., 100% cue-
contingent/predictable shock) in rodents, non-human primates, and humans has provided an important animal-
human translational bridge to study fear responding.   
 
Additional manipulations that potentiate the startle reflex have been identified.  Bright light, temporally 
uncertain shock, and infusions of the anxiogenic peptide corticotropin-releasing factor (CRF) potentiate the 
startle response in rats (69–72).  In humans, darkness and unpredictable/non-contingent shock have been 
shown to potentiate startle response (62,73).  These threats are more ambiguous or otherwise uncertain 
relative to 100% cue-contingent shock; such uncertain threats produce more sustained rather than phasic 
startle potentiation in both humans and animals.  Basic neuroscience research in animals indicates that CRF 
and norepinephrine (NE) sensitive pathways through the lateral division of the bed nucleus of the stria 
terminalis (BNST) appear to be responsible for observed increases in startle potentiation to uncertain threats 
(30,74).  Indeed, affective neuroscientists suggest that paradigms assessing startle potentiation to uncertain 
threats provide valuable laboratory models in which to study anxiety (30–32,72,74,75).   
 
In the following two sections we describe emerging evidence that suggests increased negative affective 
response (anxiety) to uncertain threats/stressors indexed via startle potentiation may represent a 
promising biomarker of anxiety-relevant stress neuroadaptations that result from chronic drug use.  
The inclusion of a comparison condition to measure negative affective response (fear) to certain 
threats/stressors is an attractive design feature associated with our cues threat tasks.  
 
A3: PRELIMINARY FINDINGS: UNCERTAIN THREAT, ANXIETY, STARTLE POTENTIATION, AND DRUGS 
Christian Grillon at the NIH and his colleagues have provided substantial evidence using his NPU task (No 
shock/Predictable shock/Unpredictable shock) that startle potentiation during uncertain threat can be used to 
sensitively study anxiety relevant processes in the laboratory (31,62).  He has also demonstrated the clinical 
utility of this approach in his studies of patients with various anxiety disorders (59,76–78).  In parallel, Michael 
Davis and his colleagues have conducted elegant experiments primarily with rodents to detail the distinct 
neurobiological substrates of fear vs. anxiety using animal models of certain (cue contingent shock) and 
uncertain threats (e.g., temporally uncertain shock, light enhanced startle) (30,72,74)[for comparable research 
with non-human primates, see (68)].  Our own program of research examining drug administration and drug 

deprivation effects on fear vs. anxiety in non-clinical and drug addicted populations has benefited greatly from 
this programmatic research. 
 
We have recently completed a series of experiments that demonstrate responding to uncertain but not certain 
threats is sensitive to alcohol’s anxiolytic effects in humans.  In a preliminary experiment published in the 
Journal of Abnormal Psychology (34), we examined alcohol’s effect on uncertain vs. certain threat using 
Grillon’s NPU task (62).  We confirmed that alcohol selectively reduced startle potentiation during 
unpredictable shock administration (i.e., uncertain threat) but not during 100% predictable shock administration 
(i.e., certain threat).   
 
In our opinion, an important limitation of the threat uncertainty manipulation (i.e., unpredictable shock) in the 
NPU task is that it conflates the probability of threat with threat imminence by varying both the probability and 
temporal precision of shock administration.  This potentially leaves crucial questions as to which stimulus 
characteristics are necessary to elicit anxiety and the underlying neurobiological mechanisms unanswered.  To 
disentangle these two characteristics of probability and temporal precision of shock, we have developed two 
novel cued threat tasks that each parametrically vary one of these dimensions (i.e., probability uncertainty or 
temporal uncertainty) while holding the second dimension constant.  We have now completed alcohol 
administration experiments with each of these two tasks.  Using our Threat Probability task, we demonstrated 
that alcohol selectively reduced startle potentiation when shock threat was probabilistically uncertain (20% 
shock-cue pairings) but not when shock threat was certain (100% shock cue pairing)(79).  Similarly, using our 
Threat Duration task, we demonstrated that alcohol selectively reduced startle potentiation when shock threat 
was temporally uncertain (shocks administered anywhere from 5 seconds to 3 minutes post cue onset) but not 
when shocks threat was temporally certain (all shocks administered 5 seconds post-cue onset  (80)).  These 
results provide further evidence that the anxiolytic effects of alcohol are sensitively measured via startle 
potentiation during uncertain threat, lending additional support to the growing body of evidence that uncertain 
threats (vs. certain threats) provide an attractive laboratory model for anxiety.  Furthermore, these results 
provide preliminary validation of our manipulations of threat uncertainty in the Threat Probability and Threat 
Duration tasks that are used in the laboratory component of the research in this application.   
 
We have recently completed two experiments that used our Threat Probability and Threat Duration tasks to 
examine negative affect during marijuana withdrawal (81).   We recruited a sample of heavy daily marijuana 
smokers who were randomly assigned to either marijuana deprived (three days) or non-deprived groups.  We 
also recruited a comparable sample of non-smokers for comparison.  Marijuana deprivation significantly 
increased startle potentiation in both our Threat Probability and Threat Duration tasks.   These results 
demonstrate that startle potentiation in these two tasks is sensitive to negative affective dysregulation during 
drug withdrawal from a drug (marijuana) that has been suggested to have a withdrawal syndrome comparable 
to that of nicotine (82–85). 
 
The most direct preliminary evidence from our laboratory for the aims of the research in this application is 
provided by a series of experiments that have been published in Biological Psychiatry (33), Journal of 
Abnormal Psychology (86), and Psychophysiology (58).  This preliminary research that used the startle 
response to examine the effects of nicotine deprivation has documented comparable affective response among 
nicotine deprived and non-deprived smokers during brief, unpleasant events and punctate, imminent, cued 
threats.  For example, nicotine deprivation did not increase startle potentiation during brief presentation of 
unpleasant relative to neutral photographic images (86) [see also (87)].  With respect to potent, punctate 
certain threats (i.e., cue contingent electric shock), nicotine deprivation did not increase startle potentiation 
during predictable electric shock administration in two experiments (33,58).  Thus, nicotine deprivation 
following chronic tobacco use does not appear to alter phasic “fear” potentiation of the startle reflex during 
certain threats. However, these latter two reports offered intriguing evidence that nicotine deprivation may 
increase negative affective response during uncertain threat.  Specifically, nicotine deprivation did increase 
startle potentiation in the period between threat cues when the smokers are likely anticipating the onset of the 
next cue at some uncertain time in the near future (58).  Furthermore, deprived smokers displayed greater 
overall startle response than non-deprived smokers during unpredictable shock administration (33).  In 
addition, startle response during unpredictable shock co-varied with smokers self-report of withdrawal 
symptoms, and was independently predicted by earlier initiation of tobacco use and years of daily cigarette use 
(33). 

 
In aggregate, this preliminary research supports the following four conclusions.  First, anxiety and fear can be 
sensitively parsed using laboratory tasks and psychophysiological measures.  Second, startle potentiation 
during uncertain threat (vs. certain threat) is sensitive to the effects of a known anxiolytic drug (alcohol) [for 
other anxiolytic drugs, see (88–90)].  This provides evidence for the validity of both startle potentiation and our 
two novel manipulations of threat uncertainty to selectively index anxiety relative to other forms of negative 
affective response (e.g., fear).  Third, startle potentiation in these same two tasks is sensitive to drug 
deprivation for a drug (marijuana) with a comparable withdrawal syndrome to tobacco.  Fourth, preliminary 
evidence exists to suggest that startle potentiation during uncertain threat may be a biomarker for increased 
anxiety resulting from stress neuroadaptations following chronic tobacco use.   
 
 
A4: ANIMAL MODELS IMPLICATE STRESS NEUROADAPTATIONS TO UNCERTAIN THREAT IN ADDICTION 
As reviewed earlier, affective neuroscience research has acknowledged a critical role for the BNST and CRF 
and NE pathways in the extended amygdala in anxiety during uncertain threat (30,72,74).  This ‘anxiety” 
system also has been implicated in animal models of drug administration, drug withdrawal, and stress-induced 
reinstatement of drug use (24,27,28,32).   
 
Much of this research has been conducted with drugs other than nicotine.  For example, Walker et al. (91) 
observed that microinjections of an opiate receptor antagonist into the BNST dose-dependently suppressed 
heroin self-administration among opiate dependent rats.  Goeders & Guerin (92) demonstrated that uncertain 
(non-contingent) but not certain (contingent) footshock facilitated acquisition of cocaine administration.  
Precipitated withdrawal from opiates produces strong activation of the BNST and neurochemical lesions of the 
BNST-projecting ventral noradrenergic bundle reduces conditioned place aversion associated with this 
withdrawal from opiates (93,94).  Shaham, Erb, & Stewart (28) document that NE and CRF systems in the 
BNST are critically involved in stress induced reinstatement to cocaine and heroin use in rats. Neurochemical 
lesions of the BNST-projecting ventral noradrenergic bundle block stress-induced reinstatement heroin seeking 
(95).  Injections of a CRF antagonist (D-PheCRF12-41) into the BNST blocks stress-induced reinstatement of 
level-pressing for cocaine (96). 
 
A comparable body of research findings has begun to emerge specifically for nicotine as well.  Jonkman et al 
(97) have recently reported selectively increased light-enhanced startle (an uncertain threat) after 20-28 hrs of 
nicotine deprivation in rats following 28 days of continuous nicotine administration.  Similarly, precipitated 
nicotine withdrawal increases anxious behavior and CRF in the CeA and pretreatment with a specific CRF1 
antagonist blocks associated increased nicotine intake (98).  Plaza-Zabala et al (99) found that non-contingent 
(uncertain) footshock precipitates reinstatement of nicotine seeking behavior in nicotine-dependent mice that 
had previously extinguished nicotine-seeking behavior. Furthermore, uncertain shock-induced nicotine 
reinstatement was extinguished by a CRF antagonist. Clearly, there is a growing body of evidence that 
specifically implicates the BNST (and more generally, NE and CRF pathways in the extended amygdala) in 
anxiety broadly, and neuroadaptations in this system’s response to uncertain threats are increasingly 
highlighted in addiction etiology generally and nicotine dependence more specifically.  Synthesis of this 
research with our findings with tobacco and marijuana smokers suggests that startle potentiation during 
uncertain threat may be a valuable cross-species biomarker of the neuroadaptive changes in anxiety that result 
from chronic nicotine and other drug use and that increases risk for relapse.  It appears that there is now ample 
evidence to justify systematic study of this potential target for treatment in human smokers.  A broad goal of 
our proposed research is to translate findings of stress neuroadaptation in animal models to humans 
by testing for neuroadaptation in the negative affective response (anxiety) to uncertain threats in 
smokers using tasks and measures initially developed in these animal models. 
 
A5: STRESS NEUROADAPTATIONS:  IMPLICATIONS FOR SMOKING CESSATION 
In addition to the animal-model to human-laboratory translation described above, a second broad goal 
of this research is to translate our laboratory markers of stress neuroadaptation to smokers’ “real 
world” during a smoking cessation attempt.  For 3 weeks (one week pre-quit, 2 weeks post-quit) following 
their laboratory visit, smokers will complete 4x daily reports of episodic stressors, affective response, smoking 
urge, actual smoking, and medication use via  ecological momentary assessment (EMA) methods.  This will 
provide us with the opportunity to directly connect  individual differences in smokers negative affective 

response to uncertain stressors in the laboratory (both when nicotine deprived and non-deprived) to clinically 
relevant individual differences in smoking as well as stressor-affect, stressor-urge, and stressor-relapse 
relationships in our smokers’ day-to-day lives during a smoking cessation attempt.  Laboratory 
psychophysiological experiments offer unequaled precision and control to examine the affective response to 
stressors and its neurobiological substrates using methods to facilitate animal model to human translational 
research.  However, this precision and control comes at the cost of the artificial setting of the laboratory and 
use of methods and measures for which external validity must be verified to increase clinical utility.  Our use of 
EMA is designed to address this concern and provide an equally important bridge between human laboratory 
research and real-world experiences of stressors, affect, urge and smoking.  There have been recent strong 
calls to increase the use of EMA methods in clinical psychopharmacology (100).  We take these 
recommendations one step further by collecting these vital EMA data but also combining laboratory 
psychophysiological and EMA methods in the same sample.   
 
Our focus on smoking cessation outcome after 2 weeks follows important developments in the biomedical 
sciences.   For example, David Kessler, former FDA Commissioner, has observed that the considerable 
advances in AIDs research can be attributed, in part, to the development of “surrogate endpoints” such as 
HIV viral load that index treatment effects in randomized clinical trials (RCT) far earlier than the obvious clinical 
endpoint of survival duration (13,14).   Kessler advocated the development of such surrogates for other 
diseases:  measures that would index effects that are linked with ultimate outcomes, but that can be obtained 
relatively quickly and cheaply relative to such outcomes.  To this end, our two-week endpoint in this application 
was chosen to completely capture the “Cessation phase” of a quit attempt (14).  The Cessation phase is a 
period when withdrawal symptoms (negative affect, urge to smoke) tend to be at their peak levels for many 
smokers (47,101,102) and play an important role in precipitating lapses back to smoking (103,104).  Stressors 
also increase the likelihood that a person will lapse during this period (51,105).  Initial smoking lapses are more 
likely in these first 2 weeks of the quit attempt than at other times, and such lapses are highly likely to transition 
into full relapse (106).   As such, we believe that detailed momentary assessment of the first two weeks post-
quit is most critical to evaluate the relationship between stressors, affect, urge, and cigarette use, and our 
psychophysiological indices of negative affective response to uncertain stressors from the laboratory.  
Although innovative, this focus on a two-week surrogate endpoint as a resource efficient proxy for long term 
smoking cessation  outcome  is also not without precedent in the smoking literature (15–19).  For example, 
Perkins, Lerman and others have validated a new procedure to develop and screen medications for tobacco 
dependence that involves measuring number of days of abstinence during two weeks of mediation use vs. 
placebo.  They have validated the sensitivity of this surrogate two week endpoint in detecting efficacy for both 
NRT and varenicline (17,18).  We propose similar  quantification of smoking (number of days of abstinence), 
as well as stressor-affect, stressor-urge, and stressor-relapse relationships across this two week Cessation 
Phase as a surrogate endpoint to validate the clinical importance of our laboratory measures of negative 
affective response (anxiety) to uncertain stressors in the laboratory.   
 
We will measure smoking cessation outcome in two groups of smokers assigned to either combination Nicotine 
Replacement Therapy (combo NRT; patch and lozenge) with counseling, vs placebo NRT with counseling.  
Nicotine replacement therapy is the most common pharmacotherapy for smoking cessation and it results in an 
approximate doubling of the likelihood of long term smoking abstinence (107,108).  Our selection of combo 
NRT for the active medication treatment group was motivated by three reasons.  First, we wanted to use a 
medication with demonstrated efficacy that is recommended as a first line treatment for tobacco dependence.  
NRT, Bupropion, and Varenicline are all recommended as first line medications (20).  Second, we wanted to 
use medication that specifically targeted withdrawal symptoms.  As noted above, negative affect that emerges 
during withdrawal has been identified as providing a critical motivational press for tobacco use and relapse 
among smokers during a cessation attempt (21).  NRT’s primary mechanism of action is to replace partially the 
nicotine that would normally be delivered via smoking to reduce the severity of withdrawal symptoms (109).  
There is evidence that combination NRT may be particularly effective in suppressing tobacco withdrawal 
symptoms, including negative affect (20,110,111).  This provides an opportunity to determine if combo NRT 
reduces negative affective response (anxiety) to uncertain stressors among smokers during smoking 
cessation.  Finally, combo NRT is preferred over Bupropion and Varenicline for practical reasons including less 
restrictive exclusion criteria for use and its status as an over-the-counter medication.   
 

In summary, following smokers during the first two weeks of a smoking cessation attempt provides important 
laboratory-to-clinical translational benefits.  The use of a two week surrogate endpoint for measuring cessation 
outcomes is innovative and also resource efficient.  The use of EMA to track smoking as well as stressor-
smoking, stressor-affect and stressor-urge relationships is also innovative in the combination with laboratory 
measures.  These data will allow us to directly examine if 1) our laboratory measures of negative affective 
response to stressors predict individual differences in stressor coupling with negative affect, urge, and smoking 
(AIM 2), 2) our laboratory measures predict smoking cessation outcomes across all smokers, regardless of 
medication group (AIM 3), 3) our laboratory measures differentially predict smoking cessation outcomes across 
combo NRT vs. placebo as would be expected if combo NRT reduces the influence of negative affect on 
smoking (AIM 4).  To further evaluate AIM 4, we will also re-administer our laboratory cued threat task at 2 
weeks post-quit to determine if combo NRT alters negative affective response to stressors and to test if this 
laboratory measure obtained during treatment mediates combo NRT effects (relative to placebo NRT with 
counseling) on smoking cessation outcome.   
 
 
 
 
 

SPECIFIC AIMS 
Neuroscience research with animal models implicates neuroadaptation in the stress response as a critical 
mechanism in the etiology of addiction across multiple classes of drugs including nicotine (22–24).  Repeated 
homeostatic adjustments in the brain’s stress systems due to chronic drug administration eventually lead to 
persistent compensatory adaptations in the structures involved in emotional response and its regulation.  
Among smokers, these stress neuroadaptations result in dysregulated negative affect when nicotine-deprived 
and provide the strong motivational press for further smoking that manifests as urge and increased risk for 
relapse (21,25). 
 
Animal models have provided substantial evidence to support this stress neuroadaptation thesis in addiction 
(22–24,26–28).  However, programmatic laboratory research that examines the stress response in nicotine 
deprived and non-deprived smokers  is necessary to confirm that our understanding of stress neuroadaptations 
from animal models translate to addiction etiology in smokers.  In particular, this application focuses on the 
negative affective response to aversive stressors.  Timothy Baker and his colleagues have argued 
persuasively that negative affect is the core motivational element of the human drug withdrawal syndrome 
across additive drugs including nicotine (21,29).  Unfortunately, much of what we know about these 
motivationally critical affective processes in humans is based on a narrow range of measures collected in 
isolation.  Moreover, complementary methods (e.g., laboratory task manipulations, clinical treatment 
interventions) and measurement approaches (e.g., psychophysiology, ecological momentary assessment) are 
rarely combined. 
 
The research in this application capitalizes on recent research with both animals and humans that has 
synthesized precise laboratory manipulations of stress with sensitive psychophysiological measurement of 
startle reflex potentiation to parse the negative affective response to stressors into its constituent components 
(30,31).  In particular, startle potentiation during uncertain (vs. certain) threats holds promise as a biomarker of 
stress neuroadaptation following chronic nicotine or other drug use (32–34). 
 
We propose to measure stress neuroadaptation in the laboratory via startle potentiation during uncertain threat 
in a validated cued threat task among nicotine deprived and non-deprived smokers.  Smokers will be 
subsequently assigned to receive active or placebo combination Nicotine Replacement Therapy with 
counseling only.  Smokers will report (4x daily) on their experience of episodic stressors, negative affect, 
smoking urge, and smoking during 3 weeks (1 week pre-quit/2 weeks post quit) of a smoking cessation attempt 
via ecological momentary assessment.  
 
AIM 1:  
Confirm stress neuroadaptation in smokers following chronic tobacco use.  This stress 
neuroadaptation will be manifest in two contrasts for startle potentiation measured in a laboratory cued threat 
task that manipulates threat uncertainty. 
    1.1:  Nicotine deprived smokers will display selectively increased negative affect measured via startle 
potentiation during uncertain (vs. certain) threat relative to non-deprived smokers. 
 
AIM 2:  Examine the impact of stress neuroadaptation on negative affect, smoking urge, and smoking 
in response to stressors.  Laboratory startle potentiation measures of stress neuroadaptation will predict 
ecological momentary assessment measures of:  
    2.1  ...overall levels of negative affect and urge 
    2.2  …within-smoker covariation (i.e., coupling) of episodic stressors with negative affect, urge, and smoking 
(i.e.,   stressor-induced negative affect, urge and smoking). 
 
AIM 3:  Examine the impact of this stress neuroadaptation on smoking during the first two weeks of 
smoking cessation.   
    3.1:   Laboratory startle potentiation measures of stress neuroadaptation will predict overall smoking during 
the first two weeks post-quit as well as measures of point prevalence abstinence and continuous abstinence 
measured at 2 weeks post-quit. 
 
AIM 4:  Determine if treatment of withdrawal via NRT reduces the influence of stress neuroadaptation.   
   4.1:    Combo NRT with counseling (vs. placebo NRT with counseling) will reduce startle potentiation 
measures obtained at one week post-quit.   

   4.2:    The effect of combo NRT (vs. placebo NRT with counseling) on smoking and related outcome 
measures will be mediated by change in startle potentiation measures from pre-quit to post-quit.   
   4.3:    Treatment of withdrawal symptoms via combo NRT will attenuate the predictive strength of pre-quit 
startle potentiation measures with respect to overall levels of negative affect, urge, and smoking and stressor- 
induced negative affect, urge, and smoking.    
 
RESEARCH DESIGN AND METHODS 
 
C1:  BRIEF OVERVIEW 
Three hundred participants (identified as heavy smokers) will be recruited.  All participants will complete an 
experimental cued threat task (No shock/Predictable shock/Unpredictable shock, or NPU, as described above) 
designed to assess the affective components (fear, anxiety) of their response to stressors in the laboratory to 
test for stress neuroadaptation resulting from chronic smoking.   Participants will complete the task twice in two 
separate experimental sessions on separate days. The first time they will be either nicotine deprived and/or 
non-deprived (counterbalanced).  Participants are randomly assigned to one of two treatments (Combo NRT 
with counseling or placebo NRT with counseling) and schedule a quit date.  All participants will provide 3 
weeks (1 week pre-quit; 2 weeks post-quit) of 4x daily, real-time report of stressors, affective state, urge to 
smoke, actual cigarette use, and study medication adherence.  Participants return to the laboratory at 2 weeks 
post-quit.  At this follow-up visit, stressor exposure, affective status, withdrawal symptoms, smoking urge, 
tobacco use, and medication adherence will be measured.  Biological confirmation (CO measurement) of 
recent smoking is also obtained.  At the 2 week post quit visit, they complete the second administration of the 
experimental cued threat task. 
 
C2:  GENERAL METHODS AND MEASURES 
This section provides detail on the general methods and measures in this application.  A separate section (C3) 
details the experimental cued threat task.   
 
C2.1: Participants.  Three hundred smokers (approximately 1/3 female as represented in the Madison 
smoking community) will be recruited.  Inclusion criteria include cigarette use >10 cigarettes/day >two years, 
smoke within the first 30 minutes of waking up, expired air carbon monoxide (CO) level >6 ppm, self-reported 
motivation to quit smoking, ability to read and write English, and an agreement to respond to EMA prompts 
throughout the day for three weeks.  Health screening via will ensure that participants can safely use the 
nicotine patch and lozenge.  Specifically, participants will be excluded for FDA contraindications for NRT (e.g., 
no uncontrolled hypertension, recent myocardial infarction, diabetes, heart disease, asthma, stomach ulcers).  
All women of child-bearing potential will be required to agree to use an approved method of birth control to 
prevent pregnancy during the course of the study. 
 
All participants will report no medical or psychiatric condition that would contraindicate exposure to electric 
shock. Participants with uncorrected auditory or visual problems will be excluded. Anyone under the age of 18 
or over 60 will be excluded. 
 
All participants will be recruited from the community via email, internet (Craigslist, Facebook), newspapers, 
radio, television, and physical posters/flyers (billboards, rolling ads, community flyers, etc.).  Our past 
experience shows that such recruitment strategies yield over 500 smoker enrollees per year. In addition, over 
the last two years, the Wisconsin Tobacco Quit Line has received approximately 1400 calls from smokers in 
the Madison area.  We will not run this study at this rate, but it is important to note that our proposed sample 
size is quire feasible to obtain given these data.  Advertisements will contain a phone number for individuals to 
contact study staff.  Participants will undergo initial phone screening to rule out those with clear 
contraindications.  Potentially qualifying individuals will be invited to attend a Laboratory Screening Session 
(see C2.2 below).   
 
C2.2:  Laboratory Screening Session 
All participants sign consent forms following detailed description of all study requirements and procedures.  
Next, they provide an initial measurement of their CO level (Micro Smokerlyzer CO monitor, Bedfont Scientific, 
Ltd) and complete a health screening questionnaire developed by our Co-Is at the Center for Tobacco 

Research and Intervention (CTRI) to confirm study eligibility.  Following this, participants provide detailed 
history of their tobacco use on a Smoking History Questionnaire developed at CTRI.  Participants complete two 
measures of nicotine dependence: the Fagerstrom Test for Nicotine Dependence (FTND; (117)) and the 
Wisconsin Index of Smoking Dependence Motives (WISDM; (3,12)).  They also report on their current nicotine 
withdrawal symptoms (Wisconsin Smoking Withdrawal Scales- WSWS; (48), current smoking urge (Brief 
Questionnaire of Smoking Urges- QSU; (118), and questions about their motivation to quit and quit self-
efficacy (119). 
 
All participants report some demographic information, their current affective state (Positive and Negative Affect 
Scales-PANAS (120), provide information on a broad-band personality measure (Brief Multidimensional 
Personality Questionnaire- bMPQ); (121) and supplemental measures of trait affectivity relevant to individual 
differences in anxiety including the Intolerance of Uncertainty Inventory, (122), and the Anxiety Sensitivity 
Inventory (123).  Individual differences in depressive symptoms will also be recorded Center for Epidemiologic 
Studies Depression Scale Revised (CESD-R; 125) and the Depression Anxiety Stress Scale-21 (DASS-21). 
 
These measures are available to serve as covariates to increase power to test for focal effects on relevant 
outcome measures.  They are also available as possible individual difference moderators in supplemental 
analyses.  After completing the self-report measures, participants schedule their first experimental session. 
Participants are randomized to either a nicotine deprived or non-deprived condition and instructed to abstain 
from all nicotine containing products for 24 hours prior to their nicotine deprived session or to continue their 
normal pattern of smoking prior to their non-deprived session. 
 
Finally, participants receive brief cessation counselling, schedule their experimental visits and quit date, and 
are provided with verbal and written instructions about the 3-week daily EMA survey that begins one week 
before their quit date.  
 
C2.3:  Laboratory Experimental Session(s) 
All participants complete the cued threat task (NPU; see section C3 below) in each of two separate 
experimental sessions. Their first session is either nicotine deprived and non-deprived in a counterbalanced 
order, the final is 2 weeks post-quit. The deprived group completes their first experimental session the day 
after the start of their quit attempt, and the non-deprived group completes it before the start of their quit 
attempt. Data across the two experimental sessions will be used to provide sensitive within-subjects tests of 
deprivation effects on startle potentiation measures of stress neuroadaptation (Aim 1) and to address all 
subsequent Aims (2-4).   
 
On arrival at the laboratory for each of both experimental sessions, participants report the time of their last 
cigarette and have their CO level measured.  For the nicotine deprived session, participants must self-report no 
tobacco use within the last 24 hours and have a CO level < 6ppm.  If they fail to abstain from tobacco products, 
they are rescheduled once.  Our experience across many previous nicotine deprivation studies 
(33,58,86,126,127) with similar monetary incentives suggest fewer than 5% of participants will fail to abstain for 
their first scheduled deprivation session and require rescheduling.  The majority of these participants will 
succeed in their second attempt.  If they fail to abstain a second time, their participation is discontinued.  These 
estimates are likely conservative given that the current sample is motivated to quit.  As such, we do not expect 
attrition due to failure to abstain to bias the sample substantially.  Following this, all participants complete a 
measure of their current affective state (PANAS), smoking urge (QSU) and withdrawal (WSWS) described 
earlier.  
 
On completion of the task, participants receive brief cessation counseling, and combo NRT or placebo NRT 
according to their randomized treatment condition (see below).  
 
C2.4 Treatment Groups 
Participants are randomly assigned to one of two treatment groups: combination NRT (patch and lozenge) vs 
placebo NRT, both accompanying by motivational enhancement counseling.  Due to the different visit 
calendars required for the two arms, study staff are not blinded to treatment arm. 
 

Combination NRT:  Participants assigned to the combo NRT arm will use 21-mg nicotine patches for 2 weeks.  
Participants will be given instructions on how to use the patch consistent with recommended use (20).  They 
will be told to apply one patch each morning to a non-hairy body surface between the neck and waist.  
Moreover, they will be encouraged to report any side effects promptly so that steps may be taken to facilitate 
effective medication use (e.g., use of cortisone cream for skin reactions).  Participants will also be provided 
with nicotine lozenges (2-mg). Participants will be instructed on recommended lozenge use (20).  They will be 
encouraged to use at least one piece every 1-2 hours and to establish a consistent schedule to prevent rather 
than ameliorate craving and/or withdrawal symptoms. Both NRT patches and lozenges are over-the-counter 
“Up and Up” brand (purchased through Target.com). 
 
Participants assigned to the placebo NRT arm receive identical instructions. However, the placebo NRT is 
“Altoids” brand Spearmint mints (purchased through Amazon.com) and custom-made placebo patches 
manufactured by American Custom Technologies. The placebo patches are identical in appearance to the real 
patches except for the absence of the faint stamp reading “21 mg nicotine” on the active product. 
 
Both placebo and active NRT lozenges are removed from their original packaging and repackaged in amber 
medication vials, to assist with the believability of the placebo manipulation. Similarly, both placebo and active 
patches are removed from their original packaging and distributed to participants in 2”x3” reclosable food-
grade storage baggies. 
 
Medication use for both groups during the two weeks of medication use will be monitored by daily reports via 
Ecological Momentary Assessment methods (see Ecological Momentary Assessment section below).     
 
Counselling: Participants receive 30 minutes of in-person counseling at three points through their participation 
in the study: during their screening session approximately one week before the start of their quit attempt, 24-
hours into their quit attempt, and at the end of their follow-up visit to the laboratory at two weeks into their quit 
attempt.    
 
At their final visit, participants, if interested, are also put in touch with the Wisconsin Tobacco QuitLine’s 
program (http://www.ctri.wisc.edu/quitline.htm). This final visit represents our last contact with the participant 
and provides an ideal opportunity to reinforce successful quit attempts or encourage a new quit attempt if 
needed for both treatment groups. Although not part of the scientific protocol per se, we provide this final 
counseling session at the end of this visit to further aid our participants in their attempt to maintain smoking 
abstinence.   
 
All three counseling contacts by our laboratory staff will emphasize those elements shown to be efficacious in 
the PHS Clinical Practice Guidelines for the treatment of Tobacco Dependence (20).  Our Co-Is, Drs. Baker & 
Piper, who are both co-authors of the PHS Clinical Practice Guidelines, have long histories of successfully 
conducting such interventions. Counselors will be doctoral student RAs supervised by Dr. Piper, a licensed 
clinical psychologist. Some of the counseling sessions may be audio taped for quality control and to ensure 
consistency of content.   Participants will not personally be identified in these recordings and they will be 
destroyed after quality control analysis. 
 
Counselling is conducted in a private room in the Addiction Research Lab. The participant is greeted by the 
counsellor and the outline of the counselling purpose (helping participants prepare for their quit attempt, and 
follow through with it) is discussed at each visit. Specifically, the counselling acts as a motivational 
enhancement to assist the participant with their own intent to quit.  
 
At the screening session the topics covered in counselling include reasons for quitting, previous quit attempts, 
social support networks, and things to do the day before their quit attempt (discarding cigarettes, hiding 
ashtrays, etc). At the post-quit session, discussion focusses on how the participant is feeling about their quit 
day, strategies for handling cravings, a second review of how the NRT product can be used to help with 
cravings, and identifying danger situations for the two week quit attempt. At the final visit, counselling focusses 
on re-framing lapses, evaluating and re-motivating for continuing abstinence, planning for relapse prevention, 
and participant’s feelings/expectations for continuing their abstinence.  
 

This counseling will emphasize those elements shown to be efficacious in the PHS Clinical Practice Guidelines 
(20).  Drs. Baker & Piper have a long history of successfully conducting such interventions (128). Counselors 
will be graduate student or staff RAs supervised by Dr. Piper. 
 
 
C2.4.1:  Design Considerations and Justification:  We discussed our careful considerations regarding 
our focus on the Cessation period and the use of this surrogate endpoint during a smoking cessation attempt in 
section A5 earlier.  We also carefully considered an alternative design where we measured negative affective 
response during a single session of NRT administration to deprived smokers in the laboratory rather then at 
one week into a quit attempt.  Although this alternative would be simpler, it may fail to capture a number of 
critical elements that are relevant to real-world quit attempts.  In particular, the affective experience is likely 
quite different during a temporary deprivation period vs. a similar duration of deprivation in the context of an 
intended permanent cessation of use.  Furthermore, the effects of deprivation likely vary over time during the 
cessation attempt as regulatory resources become drained and homeostatic adaptation processes are 
recruited (104,129–131). Our current design indexes negative affect both early in deprivation (during the pre-
quit deprived session) and after one week of cessation.  In addition, the 2 week quit period provides the 
opportunity for detailed real world measurement of stressor-affect, stressor-urge, and stressor-smoking 
relations via EMA (see below) that would not be available with the single NRT administration in the laboratory.  
We believe these benefits justify our current design. 
 
Participants are instructed to continue NRT even if they fail to maintain complete abstinence during their quit 
attempt.   There is evidence that participants benefit from reduced smoking on NRT even if full abstinence is 
not obtained or maintained (20).   This procedure will allow all participants to be included in analyses of EMA 
cessation measures.  Furthermore, analyses of the cued threat task that is administered at one week post-quit 
can retain all participants but include regressors/covariates to model the amount of smoking (and medication 
use) during the first week. 
 
C2.5:  Three week Ecological Momentary Assessment (EMA).  Participants will provide three weeks of 
daily, real-time report of stressors, current affective state, urge to smoke, actual cigarette use, and medication 
use.  These reports will be conducted 4x per day via Qualtrics surveys sent by text messages over cell phones.  
Loaner cell phones (iPhone s5, with unlimited text, voice and data) are provided if the participant does not own 
a cell phone, must pay for text messages, or simply prefers not to use their own phone for the study.  
Participants will provide one week of baseline (pre-quit) reports and 2 weeks of post-quit date reports.  The 
reports are designed to capture experiences in a distributed fashion throughout the day. The first report is 
programmed to occur at the participant’s normal wake-up time. The second report will occur at a random time 
between wake-up and their midday, but at least one hour after their wake-up report. The third report will occur 
at a random time between their midday and one hour before bedtime, and the fourth report will occur at the 
participant’s normal bedtime.  If not available, participants can complete surveys for up to 60 minutes after 
prompt, after which the report is coded as missing.  The reports are made via a brief (30 second) mobile-
optimized Qualtrics survey.  EMA research with similar parameters in our own and other laboratories 
(5,104,132,133) have met or exceeded guidelines that recommend > 80% response rate for valid assessment 
(134). 
 
At all 4 time points, participants report their current affective state (tense, anxious, or worried; irritable, 
frustrated, or easily angered; sad or depressed; happy, calm, or content) on a five point Likert scale (anchors: 
0=Not at all, 4=Extremely).  These affect items were selected from the Wisconsin Smoking Withdrawal Scale 
and have been demonstrated to load reliably on an affective distress factor associated with tobacco withdrawal 
(48,132).  Participants also report if any positive or negative stressful events (separate questions) occurred 
since their last report (i.e., hassle or other stressful event; pleasant or positive event).  If a positive or negative 
event occurred, they rate its intensity as well.  If more than one event occurred in either category, they rate the 
most intense event in the category.  Participants also report their current urge to smoke (on the Likert scale 
describe above) and how many cigarettes (if any) they have smoked since their last report.  Participants also 
report if they are wearing the patch (yes or no) and how many lozenges they have used since their last report. 
 
These EMA methods follow directly from recent (and ongoing) published research on smokers’ stress, affect, 
and cigarette usage in our Co-Is’ (Baker, Piper) laboratories at the Center for Tobacco Research and 
Intervention (5,8,104,132).  In these studies, community smokers performed 4x per day reports for up to 10 

weeks with high compliance rates, which demonstrates the clear feasibility of this method.   CTRIs IVR 
infrastructure is available to us through our collaboration with Drs. Baker & Piper. 
 
These EMA data are collected to evaluate the relationships between individual differences in 
psychophysiologically indexed affective response in our cued threat task (overall and deprived vs. non-
deprived negative affect generally and fear/anxiety selectively) and real time, in vivo, affective response, 
smoking urge, and cigarette use.  We will test if our laboratory-assessed psychophysiological individual 
differences predict individual variability in affective response, urge, and cigarette use recorded via EMA.  We 
will also examine stress-affect, stress urge, and stress-smoking coupling (i.e., temporal covariation over 2 
weeks post-quit between stressor experience, strength of affective response, and cigarette urge and use).  We 
will also examine if any of these relationships differ across (i.e., are moderated by) Treatment Groups (Combo 
NRT with counseling vs. placebo NRT with counseling). 
 
 
C2.5.1: Design Considerations and Justification.  The use of EMA methods with 4X daily reports allows 
for increased precision with respect to temporal ordering of stressors, affect, smoking urge, and cigarette use.  
The survey was kept brief to decrease assessment burden.  Similar (and longer) length surveys have been 
completed with high compliance (> 80% response rates) in Drs. Baker and Piper’s research with community 
smokers. We acknowledge that these reports are subjective based on the participants’ individual appraisal of 
stressor severity and their own affective response to these stressors.  However, these individual differences 
are at the core of our predictions regarding increased negative affective response across stressors among 
smokers, particularly when nicotine deprived.  We predict that our laboratory measures will identify the 
smokers who will show consistently strong negative affect generally and in response to aversive stressors, and 
that these smokers will have poorer smoking cessation outcomes. 
 
 
C2.6: Post-Quit Laboratory Visit 
We will measure treatment adherence, additional treatment/medication usage, stressors, affective status, 
withdrawal, urge, and cigarette use for smokers at a follow-up laboratory visit at 2 weeks post-quit.  This visit 
will also allow for biological confirmation of smoking status via CO measurement (CO < 6ppm).   
 
During this visit, smokers will complete their second administration of the two NPU Task that was completed at 
their previous visit session.  This assessment during combo NRT (or placebo) use will allow for tests of the 
effects of medication on our laboratory measures of negative affective response to uncertain threats.  
Furthermore, by measuring negative affective response to threats during medication use, we can now test if 
response on these tasks during medication use mediates smoking cessation outcomes associated with 
treatment of withdrawal symptoms via combo NRT.   
 
C2.6.1: Design Considerations and Justification.  We considered measuring cessation outcomes at later 
time points.   However, the resources necessary to measure cigarette use after the EMA period has ended 
and/or to obtain biological confirmation of smoking status at later points was considered too large.  As noted 
earlier, our primary focus is on the Cessation phase during the first 2 weeks.   We expect the negative affective 
processes that are the focus of this application to have their greatest influence on cessation success during the 
first two weeks post-quit when withdrawal symptoms are most robust.  Furthermore, smoking at later time 
points is expected to be increasing influenced by factors outside the focus of this application and therefore will 
display reduced relationships with our laboratory measures of negative affect.  In addition, as the proportion of 
the sample that has relapsed increases with time since quit, power will be diminished to test our aims.  For 
these reasons, we have focused our resources on this two week cessation period.   
 
C3: EXPERIMENTAL CUED THREAT TASK 
Building on basic affective neuroscience research with humans and animals reviewed earlier (30,31,62,75), we 
have developed and validated a laboratory task that is designed to measure negative affective response to 
threats broadly as well as selectively parse fear and anxiety.  Consistent with current conceptualizations of fear 
and anxiety, the task presents participants with threats that are either certain or uncertain to assess their fear 
and anxiety, respectively.  We manipulate uncertainty in the temporal domain by including conditions of 
imminent threat (shocks administered 5s post cue onset; certain threat) vs. distal/temporally uncertain threat 
(shocks administered anywhere post cue onset or during ITIs; uncertain threat).  As per standard procedures in 

our and other laboratories, shock intensity during these tasks is calibrated to each participant’s individual 
sensitivity threshold, which is assessed prior to the main task during each experimental session to reduce 
individual differences (34,62,64,135).  Startle potentiation is the primary dependent measure of affective 
response.  As reviewed earlier, basic affective neuroscience research has indicted that startle potentiation is a 
sensitive and selective index of the neurobiological substrates of fear and anxiety, respectively, during 
conditions of certain vs. uncertain threat (30,72,74).   
 
Participants in the non-deprived group will complete the task once pre-quit; in the deprived group, immediately 
post-quit, while both groups will also complete the task 2 weeks post-quit (counterbalanced) in separate 
experimental sessions separated by approximately two weeks.  Task details are provided below.  Task order 
within an experimental session is counterbalanced across all participants. We have preliminary data among 23 
smokers in the context of an ongoing study that verify that smokers will tolerate multiple administrations across 
separate days of similar cued threat tasks. 
 
 
 
C3.1: No-Shock/Predictable/Unpredictable (NPU) Threat Task.  In this task, participants will view a series of 
colored square cues” displayed in the center of a computer 
screen with a black background. We presented cues in a 
blocked design with  three  conditions:  no-shock  (N),  
predictable  shock  (P),  and unpredictable shock (U). Each 
shock condition is presented twice and separated by no-shock 
condition. Condition order is counterbalanced both within and 
between subjects (i.e., two condition orders:  PNUNUNP,  
UNPNPNU),  and  participants  complete  the same order at 
both study visits. All blocks include six cues presented for 5 s 
separated by a variable intertrial interval (ITI; mean17 s, range 
14–20 s). A white fixation cross remains in the center of the 
monitor during the cues and ITI. We administer a 200-ms 
electric shock 200 ms prior to cue offset during every cue in the predictable  shock  condition,  so  that  the  
appearance  of  the  cue “predicts”  that  the  shock  will  occur  in  several  seconds.  We administer  electric  
shock  at  pseudorandom  times  during  both cues  and  ITIs  in  the  unpredictable  shock  conditions,  so  that  
the occurrence  of  the  shock  is  unpredictable  by  the  participant. Shocks occur 2 or 4.8 s postcue onset 
and 4, 8, or 12 s post cue offset in the unpredictable condition. Twelve electric shocks are administered  in  
each  predictable  and  unpredictable  shock  condition.  No  electric  shock  occurs  during  the  no-shock  
condition. Each  block  lasts  approximately  150 s,  and  the  entire  NPU  task lasts approximately 20 min..  
 
Startle probes occur at 4.5 s post cue onset on a random subset of eight cues and 13, 14, or 15 s postcue 
offset during four ITIs in both shock conditions (no-shock condition: twelve cues and six ITIs). Startle probes 
occur a minimum of 12.5 s after another startle-eliciting event (e.g., shock or startle probe). Serial position of 
startle probes across the three conditions for both cues and it is counterbalanced  within  subjects  to  account  
for  habituation. We use two different orders of the serial position of startle probe, counterbalanced between 
subjects. 
 
C3.2:  Psychophysiological Measurement.  Startle potentiation is the primary dependent measure from the 
cued threat tasks.  Acquisition and scoring of the eyeblink startle response will follow well-established 
procedures described in the Society for Psychophysiological Research guidelines paper (136).  The startle 
response will be elicited by acoustic probes (50 ms, 105 dB white noise with near instantaneous rise time) and 
measured by recording electromyographic (EMG) activity in the orbicularis oculi muscle.  Startle 
electromyographic activity will be sampled (2500 Hz) and filtered (500 Hz low-pass) online with Neuroscan 
Synamps II amplifiers.  Offline processing includes high-pass filtering (28 Hz high-pass 4th order Butterworth 
filter), signal epoching (-50ms to 250ms relative to acoustic probe), rectification, and smoothing (30 Hz low-
pass 4th order Butterworth filter).  Peak eyeblink startle response is scored between 20-100 ms post-probe 
onset relative to mean 50 ms pre-probe baseline.  Our laboratory has used these procedures in published 
research involving drug administration and deprivation for over a decade (33,34,58,64,86,137,138).  Startle 

potentiation scores are calculated as the increase in startle response during threat vs. no-threat conditions 
separately for certain and uncertain threat conditions. 
 
We will also collect two secondary measures of affective response (corrugator electromyographic activity, and 
electroencephalography (EEG)) to measure facial display of affect and general arousal, respectively, in 
response to certain and uncertain threat cues. Participants will be prepared for recording by using AgAgCl 
sensors filled with a conductive gel and placed on various facial muscles (EMG includes orbicularis oculi –
under left eye; corrugator –over left eyebrow) as well as on the scalp (EEG). Additionally two AgAgCl sensors 
will be placed on the forehead to act as ground and reference sensors.  Acquisition and scoring of these 
measures will also follow well established procedures (139–141).  Our laboratory has regularly collected these 
measures as part of a standard battery of peripheral psychophysiological measures of negative affective 
response (137,142–145).  
 
C3.3  Design Considerations and Justification: We carefully considered the experimental task to elicit 
negative affective response in the laboratory.  In contrast to stressor tasks involving staged social interactions 
with confederates, self-disclosing speeches, or other similar tasks commonly used in social and health 
psychology research with humans, affective neuroscience has relied extensively on cued threat of electric 
shock (30,54,55,146).  The cued threat task allows for increased precision/control over and parametric 
manipulation of cue characteristics (e.g., cue duration, cue-shock contingencies) and repeated presentation of 
trials that facilitate identification of psychological and neurobiological mechanisms involved in the affective 
response to stressors.  Furthermore, comparable tasks can be used with animals and humans to encourage 
translation of findings from animal models to humans.  In addition, a growing body of affective neuroscience 
research that explicitly manipulates threat uncertainty in cued threat tasks with animals and humans provides 
an attractive platform on which to examine etiologic mechanisms in tobacco dependence as they are relevant 
for treatment (see earlier reviews). Finally, we have pilot data that demonstrates the feasibility of multiple 
administrations of the cued threat task.  In contrast, it is not clear that social stress tasks can be validly 
administered repeatedly (i.e.., deprived or non-deprived and 2 weeks post-quit during medication) and 
therefore cannot fully address any but our first Aim. We believe the opportunity for conceptual replication will 
increase confidence in results and to extend understanding of the role of threat uncertainty in fear/anxiety.   
 
For these reasons, we believe that the novel use of our cued threat task in this application is an innovative and 
impactful feature of the design.  In contrast, given these limitations associated with the social stress tasks, we 
judged that the costs (monetary, staff resources, and participant burden) were not justified to add a social 
stress task to the experimental procedure at this stage of this research program. 
 
Identification of and Protection against Risk 
There are several areas of potential risk that might be identified in connection with this project, but these are 
judged to be minimal, both individually and collectively.  Nonetheless, to the extent that any risks do exist, each 
is described, together with procedures for its management.  The areas of possible concern are as follows:  (a) 
confidentiality, (b) adverse response to study medications, (c) unpleasant sensations associated with tobacco 
withdrawal, (d) adverse reaction to physiological sensor gel or application process (e) exposure to noise bursts 
to elicit startle reflex, (f) adverse physical or psychological response to exposure to electric shock.  Each of 
these will be addressed in turn. 
 
 
 Confidentiality.  The survey, EMA and psychophysiological measures to be used in the proposed 
research are generally of a benign nature.  However, some self-report questionnaires could yield sensitive 
information.  Consequently, all data will be coded by participant number only and any personal identifiers 
linking participants to their reports on surveys and questionnaires will be detached and destroyed as soon as 
participation is completed or disqualification occurs.  All data are stored electronically on a secure server in the 
department of Psychology.  These measures are being used to assess individual differences in smoking 
history, dependence, and other relevant characteristics (e.g., state and trait negative affect).   Although some 
of these measures (e.g., CESD-R, DASS21) obtain reports about individual differences in depression and 
other psychiatric symptoms, these measures are NOT sufficient to diagnosis clinical depression or other 
psychiatric illness in isolation or to identify imminent threat of harm to self or others.  As such, these data are 

not routinely reviewed at time of data collection or used for any further intervention or clinical recommendation 
to the research participant. 
A.  Adverse response to study medications.  Participants will be made aware of the common side 
effects of the nicotine patch and lozenge that they are assigned to receive before they consent to 
participate in the study.  It should be noted that the nicotine patch and lozenge are available over the 
counter, suggesting minimal risk. The nicotine patch has very few side effects, but up to 50% of 
participants may have a local skin reaction.  Participants are instructed to stop using the patch or 
lozenge and inform us immediately if they experience nausea, dizziness, weakness, vomiting, fast or 
irregular heartbeat, mouth problems with the lozenge, or redness or swelling of the skin around the 
patch that does not go away.  Participants are instructed to contact us if they experience any notable 
side effects from NRT.   Participants are queried in person about side effect symptoms during their 1 
and 2 week post-quit visits to the laboratory.  Dr. Piper (a licensed psychologist and expert on the 
treatment of tobacco  use disorder) is available if any psychiatric concerns emerge among study 
participants or if they have questions about the use of NRT. 
 
B. Tobacco withdrawal.  Tobacco withdrawal is associated with a number of unpleasant symptoms, such 
as sleep disturbance, hunger, craving, and negative mood.  Though unpleasant, tobacco withdrawal 
symptoms pose no acute health risk.  Most smokers have tried to quit in the past and are familiar with 
these phenomena.  All smokers will be forewarned about these symptoms.  Of course, smokers who 
are successful at quitting smoking cigarettes during the study will ultimately have reduced risk of a 
number of smoking-related health problems. 
 
C.  Adverse reaction to physiological sensor gel or application process.  The sensor gel used is 
similar in salt concentration to human perspiration, reducing the possibility of this risk.  In addition, 
research assistants will attend multiple training sessions including direct practice with sensor 
application prior to being cleared by the principal investigator to attach sensors to research participants. 
 
D. Exposure to noise bursts to elicit startle reflex.  At a maximum of 105dB, the intensity of these 
noise stimuli is safely below levels at which there might be any risk of pain or physical damage as 
established by OSHA and NIOSH guidelines. Specifically, risk associated with noise exposure is 
reduced in the current experiment by limiting noise intensity to 105dB, limiting total noise exposure time 
to no more than 4s, and using broad spectrum noise (i.e., white noise). 
 
The portion of the experiment in which white noise bursts will be delivered to participants will last 
approximately < 40 minutes. During this period, participants will be exposed to no more than 75 50-
millisecond bursts of white noise for a total of 3.75s seconds of exposure. The noises will be delivered 
via Sennheiser HD-280 headphones (http://www.sennheiserusa.com/). The signal will be calibrated 
with a slow response meter with A-weighting (B&K sound level meter model 2203). The acoustical 
environment in which the sounds will be presented is a standard laboratory room that is 9' X 13'. The 
OSHA recommended limit for noise exposure at 105 dB is no more than 1 hour/day (OSHA section 
1910-95). According to the more conservative National Institute for Occupational Safety and Health 
(NIOSH) guidelines (http://www.cdc.gov/niosh/docs/98-126/), workers should not be exposed to 105 dB 
for more than 4 min and 43 sec per 8 hour day. As such, the exposure in the current experiment is far 
under the more conservative limit recommended by NIOSH. By comparison, noise levels in small music 
venues (e.g., bars) often exceed 105 dB, and noise levels at rock and roll shows often exceed 115 dB. 
Participants are occasionally in these environments for more than 1 hour. 
 
An additional safety factor is that "white noise" is being employed. White noise is full spectrum, so there 
is no single frequency with concentrated energy. This acts as further protection to the subject by 
preventing the focus of energy to a limited area of the basilar membrane in the subject's cochlea. 
 
E.  Adverse physical or psychological response to exposure to electric shock.  An additional 
possible area of concern involves transient psychological discomfort that might occur in connection with 
the administration of electric shock.  Indeed, it is precisely such a moderately distressed acute mood 
state that the threat is intended to produce in order to permit examination of the central hypotheses 
about affective response to stress in the research project.  There is no reason to believe that the 

magnitude of this distress exceeds that normally encountered in everyday life.  Moreover, participants 
are forewarned that they will receive these electric shocks during the experiment and that they can 
terminate their participation without prejudice at any time during the procedure. 
 
The risk of physical harm associated with the administration of electric shock is minimal.  The shock 
parameters and procedures have been used in previous work that in the PI’s and other laboratories.  
The shocks will have an intensity ranging from 0.5 to 7.0 milliamperes and duration of 250 milliseconds.   
The shocks will be delivered via finger electrodes placed on the index and pointer fingers of the non-
dominant hand.  These electrodes are specially designed to prohibit the possibility of connecting to 
fingers on opposite hands.  A complex digital input to the shock unit is required to trigger shock 
administration.  This prevents unintended shock administration in the event of computer failure.  
Moreover, the shock unit is current-limited and designed to automatically shut-off if current is 
administered for longer than 1000ms.  The shock unit has two levels of optical isolation from 
connections to the computer and the participant will be isolated from any AC current source at all times. 
 
 
 
DATA SAFETY AND MONITORING PLAN 
 
 
A.  Monitoring the progress of study and the safety of participants.   
The Principal Investigator will be responsible for routine monitoring of the study’s progress.  This includes 
scheduled monthly meetings with study staff and review of written documentation.  Data that are reviewed at 
these meetings include the number and type of participants enrolled, the number and reasons for exclusions 
from enrollment, the number treated and the stage of treatment, summary of adverse events, individual review 
of serious adverse events and study participation and outcome data.  In addition, any unanticipated health 
events that raise concerns (e.g., serious mood or behavioral changes, suicidal ideation) will be immediately 
reported to the PI and the study physician.   
 
To facilitate participant safety, study participants must meet study inclusion criteria.  Once enrolled, study 
protocol will assess for the presence of adverse events at Week 2 post quit by querying participants as to 
whether they have experienced any adverse side effects associated with study medications.  Participants will 
be queried about changes to health status, or experience with adverse events, at every study visit. Participants 
who report development of severe side effects associated with combo NRT (which is unlikely) will be instructed 
to discontinue study medication immediately and they will not be given more study medication. Such events 
will be immediately reported to the PI and study physician.  If significant psychiatric or medical symptoms are 
reported verbally by participants during the regular questioning by study staff or study counsellors, the 
participant will be referred by the study staff, PI, and/or study physician, as needed, to the appropriate 
emergency medical or psychiatric services. Said services include the participant’s primary care doctor, local 
therapy centers, urgent care clinics, UW walk-in clinics, or 911, depending on nature & severity. 
 
B.  Plans for assuring compliance with requirements regarding the reporting of adverse events.   
This DSMP requires that investigators notify NIH and the University of Wisconsin IRB of the occurrence of any 
serious adverse event (SAE), or any adverse event (AE) which is severe, unexpected, and possibly related to 
study medication or protocol.  Such notification must occur within five days of investigators becoming aware of 
the event.  If the serious adverse event might be related to drug use, both the Food and Drug Administration 
and the manufacturer will also be notified within five days of investigators becoming aware of the event.  
Examples of serious adverse events would be untoward medical or treatment occurrences that result in death, 
are life-threatening, require hospitalization or prolonging of existing hospitalization, create persistent or 
significant disability/incapacity, or involve congenital abnormality/birth defects.  Unanticipated adverse events 
would include less serious problems that merit reporting because they are severe, unexpected, and possibly 
related to study participation.  Any serious adverse event (SAE) will be queried and reported even if it appears 
that the serious adverse event is unrelated to treatment participation.  The PI will be responsible for the 
accurate documentation, investigation and follow-up of all study-related adverse events. 
 

Adverse event assessment, recording, reporting and investigation will be accomplished through staff training, 
structured or standardized assessments of untoward occurrences/events, and regular monitoring by study 
investigators.  The Principal Investigator has ultimate responsibility for ensuring that serious adverse events 
are detected and reported in a timely manner.  Additionally, the IRB will receive an annual report of all serious 
adverse events and adverse events meeting the criteria listed above. 
 
C.  Plans for assuring that any action resulting in a temporary or permanent suspension of an NIH-
funded clinical trial is reported to the NIH grant program director responsible for the grant.   
The NIH grant program director will be notified within five days if the Principal Investigator deems it necessary 
to suspend the study.  In the case of a temporary suspension, the Principal Investigator will develop a plan for 
continuation of the study and discuss this plan with the NIH grant program director in a reasonable time frame.   
 
D.  Plans for assuring data accuracy and confidentiality and protocol compliance.   
The Principal Investigator will refine existing protocols for assuring data accuracy and protocol compliance.  
Such protocols will include data verification and protocol compliance checks as well as other quality assurance 
procedures.  The Principal Investigator will also be responsible for ensuring that the data for the project are 
securely stored, that storage is in compliance with University and federal regulations and that no unauthorized 
persons have access (electronic or physical) to any participant-identifiable data.   
 
STATISTICAL CONSIDERATIONS 
 
In this section, we outline general strategies for analysis of startle potentiation, EMA, and treatment outcome 
that are used to address our four aims.  We sketch out clear exemplars of analysis options for this rich dataset.  
Of course, there are numerous supplemental analyses that space constraints prevent describing here. 
 
ANALYSIS OF STARTLE POTENTIAION (AIM 1).   The analysis of startle potentiation for Aims 1 & 1.1 
across experimental tasks can be accomplished within very similar General Linear Models (GLMs).  In each 
analysis, startle potentiation will be analyzed in a GLM with Threat Uncertainty (low vs. high probability for 
Threat Probability task; fixed vs. variable duration for Threat Duration task) as the focal within-subject factor.  
Analysis of Aim 1.1 will use the full sample as a focal between-subject factor.  Support for the stress 
neuroadaptation thesis following chronic tobacco use would be offered by a Smoking Group X Threat 
Uncertainty interaction with selectively greater startle potentiation among smokers in uncertain threat for each 
task.  Analysis of Aim 1.2 will use both pre-quit sessions and include Deprivation Status (nicotine deprived vs. 
non-deprived) as a focal within subject factor.   Support for the stress neuroadaptation thesis when nicotine 
deprived would be offered by a Deprivation Status X Threat Uncertainty interaction with selectively greater 
startle potentiation among deprived smokers in uncertain threat for each task. 
 
Additional covariates will be considered for each GLM to reduce error variance and increase power (e.g., 
resting startle response, task order, block order).  All experiments include equal numbers of men and women 
to allow for preliminary examination of possible sex effects.  Trait individual difference variables (e.g., individual 
differences in anxiety, depression, levels of tobacco dependence; see section C2.2) can be included in the 
GLMs to provide exploratory tests for potentially interesting moderators.  Quantitatively measured withdrawal 
symptoms (WSWS) and smoking urge (QSU) can be included in supplemental analysis to clearly link 
deprivation status effects on startle potentiation to these proximal processes.  Given that all participants 
complete both threat tasks, follow-up GLMs can include task as a within-subject factor to determine if effects 
are consistent across tasks that involve different manipulations of anxiety (i.e., low probability vs. temporally 
uncertain threat).  This will provide important construct validation and potential conceptual replication of 
possible anxiety findings. 
 
Analysis of Ecological Momentary Assessments of Stressors, Affect, Urge and Smoking (AIMS 2, and 
4.3) 
Analysis of EMA data will follow directly from procedures described by our Co-I, Dr. Baker, in McCarthy, 
Piasecki, Fiore, & Baker (2006).  Although the focal questions in McCarthy et al (2006) were different, the 
nature of that dataset was very similar in that it included multiple weeks of 4X daily EMA reports of stressors, 

affect, cigarette use, and withdrawal symptoms.  The within-subjects, repeated measures design associated 
with EMA survey make it suitable for growth-curve modeling, a technique that estimates change over time 
via multilevel modeling (147,148).  Although time is not a focal factor in our analysis, growth curve modeling 
is well-suited for these data and our questions because it can easily accommodate missing data and unequal 
intervals between assessments that result from pseudo-randomly selecting assessment times during each day.  
This multilevel model allows us to predict “occasion-level” (level 1) responding associated with affective 
response, urge, or smoking with other occasion-level variables (e.g., stressor occurrence), or “person-level” 
(level 2) variables (e.g., startle potentiation measures from cued threat task).  Therefore, these models will 
provide clear and powerful tests to determine if laboratory startle potentiation “biomarkers” of stress 
neuroadaptations predict individual differences in overall levels of negative affect, urge, or smoking over the 3-
weeks of EMA controlling for stressor exposure (AIM 2.1).  Furthermore, these same models will provide tests 
if startle potentiation measures of stress neuroadaptation predicts individual differences in the size of the 
occasion-level stressor effects on negative affect, urge and smoking (i.e., stress-induced negative affect, urge, 
and smoking).  In other words, do our laboratory stress neuroadaptation measures predict stressor-affect, 
stressor-urge, and stressor-smoking covariation or coupling over time (AIM 2.2).  Treatment condition can be 
included as a moderating between-subject factor to test if the relationship between startle potentiation and 
overall levels and coupling of EMA measured affect, urge and smoking differ generally when withdrawal 
symptoms are treated via combo NRT (AIM 4.3).  As with GLM analyses, these multilevel models can 
accommodate other exploratory person-level moderators of these effects (e.g., trait anxiety, depression, level 
of dependence, sex).  As before, the models can also include task as a factor to determine if anxiety as 
measured in the laboratory task displays comparable relationships with occasion-level EMA data  
 
Analysis of Treatment Outcome (AIMS 3, 4.1, 4.2):  Number of cigarettes smoked (17,18), point prevalence 
abstinence and continuous abstinence (as defined by the SRNT Workgroup on Biochemical Confirmation 
(149)) will be analyzed in Generalized Linear Models with time (1 week vs. 2 weeks) as a within subject factor.  
Startle potentiation measures from the cued threat task will be included as quantitative regressors to test if our 
laboratory stress neuroadaptation biomarkers predict treatment outcome measures (Aim 3).  As above, 
treatment condition can be included as a moderating between subject factor to test if the relationships between 
startle potentiation and treatment outcome differ generally when withdrawal symptoms.  Finally, mediation 
analyses can be conducted to determine if NRT alters startle potentiation measures at one-week post quit (AIM 
4.1) and the startle potentiation measures mediate NRT effects on smoking outcome measures (AIM 4.2).   
 
C4.3:  Sample Size Justification.  The primary analyses of startle potentiation will be accomplished within the 
General Linear Model (GLM).  The analyses of smokers test for a two way interaction between Deprivation 
Status and Threat Uncertainty.  Cohen (150) defines 0.15 for the squared multiple partial correlation as a 
medium effect size for GLM analyses.  To be conservative, we powered our experiments to provide 90% power 
to detect a somewhat smaller (0.10) effect size.  N=142 will provide 90% power to detect a squared multiple 
partial correlation of 0.10 for the interaction in a model that contains the two main effects and interaction based 
on formula provided by Cohen.  We then increased this sample size to the round 150 within each Treatment 
Group to provide flexibility to counterbalance all relevant additional task factors.  This yields N=300 across the 
two Treatment Groups.  Given that the multilevel models that will be used to test questions about the EMA data 
are essentially GLMs fit at two separate levels of analysis (occasion and person levels), N=150 within each 
Treatment Group will provide comparable high power to test person-level predictors of both occasion-level 
intercepts (e.g., overall smoking, levels of negative affect) and stressor coefficients (e.g., stress-instigated 
smoking or negative affect). 
 
 
 

DATA AND RECORD KEEPING 
 
All data will be obtained directly from research participants.  No access to medical records or other sources of 
information is required.  Data include participants’ self reports on questionnaires, via text messages (see 
section on EMA) and physiology in the laboratory.  All data are digitally stored with ID number only.  Data are 
managed by the PI.  Consent forms are separated from other data and stored in a locked room in a locked file 
cabinet. 
 
We will register this study at the Open Science Framework (osf.io). The Open Science Framework (OSF) is a 
free, open source web application that connects and supports the research workflow, enabling scientists to 
increase the efficiency and effectiveness of their research. Researchers use the OSF to collaborate, document, 
archive, share, and register research projects, materials, and data. OSF is used as a data repository for 
sharing de-identified study data from published analyses with other researchers as recommended by NIH. OSF 
is also a recommended data management site per UW Research Data Services 
(http://researchdata.wisc.edu/).  
 
We will make de-identified processed data, study materials (e.g., questionnaires), and data analysis code from 
this study publicly available to share with the research community. We plan to share these data in online 
repositories on the Open Science Foundation (OSF: https://osf.io/ukhcf/). Specifically, the data that we will 
share include physiological measures (e.g., EMG startle response) and self-report surveys/questionnaires. All 
participants' data will be de-identified. 
 
 
 
 
 
 
 

REFENCES CITED 
 
1.  
Bolt DM, Piper ME, Theobald WE, Baker TB. Why two smoking cessation agents work better than one: 
Role of craving suppression. Journal of Consulting and Clinical Psychology [Internet]. 2011 Nov 21 [cited 2011 
Dec 5];Available from: http://www.ncbi.nlm.nih.gov/pubmed/22103958 
2.  
Japuntich SJ, Piper ME, Leventhal AM, Bolt DM, Baker TB. The effect of five smoking cessation 
pharmacotherapies on smoking cessation milestones. J Consult Clin Psychol. 2011 Feb;79(1):34–42.  
3.  
Smith SS, Piper ME, Bolt DM, Fiore MC, Wetter DW, Cinciripini PM, et al. Development of the Brief 
Wisconsin Inventory of Smoking Dependence Motives. Nicotine Tob. Res. 2010 May;12(5):489–99.  
4.  
Bolt DM, Piper ME, McCarthy DE, Japuntich SJ, Fiore MC, Smith SS, et al. The Wisconsin Predicting 
Patients’ Relapse questionnaire. Nicotine Tob. Res. 2009 May;11(5):481–92.  
5.  
Japuntich SJ, Piper ME, Schlam TR, Bolt DM, Baker TB. Do Smokers Know What We’re Talking 
About? The Construct Validity of Nicotine Dependence Questionnaire Measures. Psychological Assessment. 
2009;21(4):595–607.  
6.  
Baker TB, Weiss RB, Bolt D, von Niederhausern A, Fiore MC, Dunn DM, et al. Human neuronal 
acetylcholine receptor A5-A3-B4 haplotypes are associated with multiple nicotine dependence phenotypes. 
Nicotine Tob. Res. 2009 Jul;11(7):785–96.  
7.  
Piper ME, Bolt DM, Kim S-Y, Japuntich SJ, Smith SS, Niederdeppe J, et al. Refining the tobacco 
dependence phenotype using the Wisconsin Inventory of Smoking Dependence Motives. J Abnorm Psychol. 
2008 Nov;117(4):747–61.  
8.  
Piper ME, Federman EB, McCarthy DE, Bolt DM, Smith SS, Fiore MC, et al. Using Mediational Models 
to Explore the Nature of Tobacco Motivation and Tobacco Treatment Effects. Journal of Abnormal. 
2008;117:94–105.  
9.  
Piper ME, McCarthy DE, Bolt DM, Smith SS, Lerman C, Benowitz N, et al. Assessing dimensions of 
nicotine dependence: an evaluation of the Nicotine Dependence Syndrome Scale (NDSS) and the Wisconsin 
Inventory of Smoking Dependence Motives (WISDM). Nicotine Tob. Res. 2008 Jun;10(6):1009–20.  
10.  
Baker TB, Piper ME, McCarthy DE, Bolt DM, Smith SS, Kim S-Y, et al. Time to first cigarette in the 
morning as an index of ability to quit smoking: implications for nicotine dependence. Nicotine Tob. Res. 2007 
Nov;9 Suppl 4:S555–70.  
11.  
Piper ME, Federman EB, McCarthy DE, Bolt DM, Smith SS, Fiore MC, et al. Efficacy of bupropion 
alone and in combination with nicotine gum. Nicotine Tob. Res. 2007 Sep;9(9):947–54.  
12.  
Piper ME, Piasecki TM, Federman EB, Bolt DM, Smith SS, Fiore MC, et al. A Multiple Motives 
Approach to Tobacco Dependence: The Wisconsin Inventory of Smoking Dependence Motives (WISDM-68). 
Journal of Consulting & Clinical Psychology. 2004;72(2):139–54.  
13.  
Thornton M. The next front on the war on cancer. Wall Street Journal. 2009; 
14.  
Baker TB, Mermelstein R, Collins LM, Piper ME, Jorenby DE, Smith SS, et al. New methods for 
tobacco dependence treatment research. Ann Behav Med. 2011 Apr;41(2):192–207.  
15.  
Lerman C, LeSage MG, Perkins KA, O’Malley SS, Siegel SJ, Benowitz NL, et al. Translational research 
in medication development for nicotine dependence. Nat Rev Drug Discov. 2007 Sep;6(9):746–62.  

16.  
Perkins KA, Lerman C. Early human screening of medications to treat drug addiction: novel paradigms 
and the relevance of pharmacogenetics. Clin. Pharmacol. Ther. 2011 Mar;89(3):460–3.  
17.  
Perkins KA, Lerman C, Fonte CA, Mercincavage M, Stitzer ML, Chengappa KNR, et al. Cross-
validation of a new procedure for early screening of smoking cessation medications in humans. Clin. 
Pharmacol. Ther. 2010 Jul;88(1):109–14.  
18.  
Perkins KA, Lerman C, Stitzer M, Fonte CA, Briski JL, Scott JA, et al. Development of procedures for 
early screening of smoking cessation medications in humans. Clin. Pharmacol. Ther. 2008 Aug;84(2):216–21.  
19.  
Perkins KA, Stitzer M, Lerman C. Medication screening for smoking cessation: a proposal for new 
methodologies. Psychopharmacology (Berl.). 2006 Mar;184(3-4):628–36.  
20.  
Fiore MC, Jaen CR, Baker TB, Bailey WC, Benowitz NL, Curry SJ, et al. A clinical practice guideline for 
treating tobacco use and dependence: 2008 update. A U.S. Public Health Service report. Rockville, MD: U.S. 
Department of Health and Human Services, U.S. Public Health Service; 2008.  
21.  
Baker TB, Piper ME, McCarthy DE, Majeskie MR, Fiore MC. Addiction motivation reformulated: an 
affective processing model of negative reinforcement. Psychological Review. 2004;111(1):33–51.  
22.  
Koob GF, LeMoal ML. Addiction and the Brain Antireward System. Annual Review of Psychology. 
2008;59:29–53.  
23.  
Weiss F. Compulsive drug-seeking behavior and relapse: neuroadaptation, stress, and conditioning 
factors. Annals New York Academy of Sciences. 2001;:1–26.  
24.  
Shaham Y, Hope BT. The role of neuroadaptations in relapse to drug seeking. Nature Neuroscience. 
2005;8(11):1437–9.  
25.  
Parrott AC. Does cigarette smoking cause stress? Am Psychol. 1999;54(10):817–20.  
26.  
Koob GF. Brain stress systems in the amygdala and addiction. Brain Research. 2009;1293:61–75.  
27.  
Shalev U, Erb S, Shaham Y. Role of CRF and other neuropeptides in stress-induced reinstatement of 
drug seeking. Brain Res. 2010 Feb 16;1314:15–28.  
28.  
Shaham Y, Erb S, Stewart J. Stress induced relapse to heroin and cocaine seeking in rats: A review. 
Brain Research Reviews. 2000;33(1):13–33.  
29.  
Curtin JJ, Mccarthy DE, Piper ME, Baker TB. Implicit and explicit drug motivational processes: A model 
of boundary conditions. In: Wiers RW, Stacy AW, editors. Handbook of Implicit Cognition And Addiction. Sage 
Publications Inc; 2006.  p. 233–50. 
30.  
Davis M, Walker DL, Miles L, Grillon C. Phasic vs Sustained Fear in Rats and Humans: Role of the 
Extended Amygdala in Fear vs Anxiety. Neuropsychopharmacology Reviews. 2010;35:105–35.  
31.  
Grillon C. Models and mechanisms of anxiety: evidence from startle studies. Psychopharmacology 
(Berl). 2008 Aug;199(3):421–37.  
32.  
Walker DL, Toufexis DJ, Davis M. Role of the bed nucleus of the stria terminalis versus the amygdala in 
fear, stress, and anxiety. European Journal of Pharmacology. 2003;463:199–216.  
33.  
Hogle JM, Kaye JT, Curtin JJ. Nicotine withdrawal increases threat-induced anxiety but not fear: 
neuroadaptation in human addiction. Biological Psychiatry. 2010;68:719–25.  

34.  
Moberg CA, Curtin JJ. Alcohol selectively reduces anxiety but not fear: startle response during 
unpredictable versus predictable threat. J Abnorm Psychol. 2009 May;118(2):335–47.  
35.  
Koob GF, Volkow ND. Neurocircuitry of Addiction. Neuropsychopharmacology Reviews. 2010;35:217–
38.  
36.  
Solomon RL, Corbit JD. An opponent-process theory of motivation: I. Temporal dynamics of affect. 
Psychological Review. 1974;81(2):119–45.  
37.  
Calabrese EJ, Bachmann KA, Bailer AJ, Bolger PM, Borak J, Cai L, et al. Biological stress response 
terminology: Integrating the concepts of adaptive response and preconditioning stress within a hormetic dose-
response framework. Toxicol. Appl. Pharmacol. 2007 Jul 1;222(1):122–8.  
38.  
Rodrigues SM, LeDoux JE, Sapolsky RM. The influence of stress hormones on fear circuitry. Annual 
Review of Neuroscience. 2009;32:289–313.  
39.  
Sapolsky RM. Stress and plasticity in the limbic system. Neurochem. Res. 2003 Nov;28(11):1735–42.  
40.  
McEwen BS. From molecules to mind. Stress, individual differences, and the social environment. Ann N 
Y Acad Sci. 2001;935:42–9.  
41.  
McEwen BS. The neurobiology of stress: From serendipity to clinical relevance. Brain Research. 
2000;886(1-2):172–89.  
42.  
McEwen BS, Eiland L, Hunter RG, Miller MM. Stress and anxiety: structural plasticity and epigenetic 
regulation as a consequence of stress. Neuropharmacology. 2012 Jan;62(1):3–12.  
43.  
Hughes JR, Higgins ST, Bickel WK. Nicotine withdrawal versus other drug withdrawal syndromes: 
Similarities and dissimilarities. Addiction. 1994;89(11):1461–70.  
44.  
Brandon TH, Baker TB. The Smoking Consequences Questionnaire: The subjective expected utility of 
smoking in college students. Psychological Assessment. 1991;3(3):484–91.  
45.  
Brandon TH, Juliano LM, Copeland AL. Expectancies for tobacco smoking. In: Kirsch I, editor. How 
expectancies shape experience. Washington, DC, US: American Psychological Association; 1999.  p. 263–99. 
46.  
Hall SM, Muñoz RF, Reus VI, Sees KL. Nicotine, negative affect, and depression. J Consult Clin 
Psychol. 1993 Oct;61(5):761–7.  
47.  
Piasecki TM, Fiore MC, Baker TB. Profiles in discouragement: two studies of variability in the time 
course of smoking withdrawal symptoms. Journal of Abnormal Psychology. 1998;107(2):238–51.  
48.  
Welsch SK, Smith SS, Wetter DW, Jorenby DE, Fiore MC, Baker TB. Development and Validation of 
the Wisconsin Smoking Withdrawal Scale. Experimental and Clinical Psychopharmacology. 1999;7(4):354–61.  
49.  
Zinser MC, Baker TB, Sherman JE, Cannon DS. Relation between self reported affect and drug urges 
and cravings in continuing and withdrawing smokers. Journal of Abnormal Psychology. 1992;101(4):617–29.  
50.  
Patton DB. A personality typology of smokers. Addictive Behaviors. 1997;22(2):269–73.  
51.  
Brandon THT. Postcessation cigarette use: The process of relapse. Addictive Behaviors. 
1990;15(2):105–14.  
52.  
LeDoux JE. Emotion Clues from the brain. Annual Review of Psychology. 1995;46:209–35.  

53.  
Davidson RJ, Jackson DC, Kalin NH. Emotion, plasticity, context, and regulation: perspectives from 
affective neuroscience. Psychological Bulletin. 2000;126(6):890–909.  
54.  
Delgado MR, Olsson A, Phelps EA. Extending animal models of fear conditioning to humans. Biological 
Psychology. 2006;73:39–48.  
55.  
LeDoux J. Fear and the brain: Where have we been, and where are we going? Biological Psychiatry. 
1998;44(12):1229–38.  
56.  
Phelps EA. Emotion and cognition: Insights from studies of the human amygdala. Annual Review of 
Psychology. 2006;57:27–53.  
57.  
Phelps EA, LeDoux JE. Contributions of the Amygdala to Emotion Processing: From Animal Models to 
Human Behavior. Neuron. 2005;48:175–87.  
58.  
Hogle JM, Curtin JJ. Sex differences in negative affective response during nicotine withdrawal. 
Psychophysiology. 2006;43(4):344–56.  
59.  
Grillon C, Baas JM. A review of the modulation of the startle reflex by affective states and its application 
in psychiatry. Clinical Neurophysiology. 2003;144(9):1557–79.  
60.  
Baas JM, Nugent M, Lissek S, Pine DS, Grillon C. Fear Conditioning in Virtual Reality Contexts: A New 
Tool for the Study of Anxiety. Biological Psychiatry. 2004;55(11):1056–60.  
61.  
Mol N, Baas JMP, Grillon C, van Ooijen L, Kenemans JL. Startle potentiation in rapidly alternating 
conditions of high and low predictability of threat. Biological Psychiatry. 2007;76:43–51.  
62.  
Grillon C, Baas JP, Lissek S, Smith K, Milstein J. Anxious Responses to Predictable and Unpredictable 
Aversive Events. Behavioral Neuroscience. 2004;118(5):916–24.  
63.  
Moberg CA, Weber S, Curtin JJ. Alcohol dose effects on stress response to cued threat vary by threat 
intensity. Psychopharmacology. in press; 
64.  
Curtin JJ, Patrick CJ, Lang AR, Cacioppo JT, Birbaumer N. Alcohol affects emotion through cognition. 
Psychological Science. 2001;12(6):527–31.  
65.  
Dvorak-Bertsch JD, Curtin JJ, Rubinstein TJ, Newman JP. Psychopathic traits moderate the interaction 
between cognitive and affective processing. Psychophysiology. 2009 Sep;46(5):913–21.  
66.  
Newman JP. Attention Moderates the Fearlessness of Psychopathic Offenders. BIOL PSYCHIATRY. 
2009;XX (in press)(XX (in press)):XX (in press).  
67.  
Davis M. Neural systems involved in fear and anxiety measured with fear-potentiated startle. American 
Psychologist. 2006;:741–56.  
68.  
Davis M, Antoniadis E, Amaral D, Winslow J. Acoustic startle reflex in rhesus monkeys: A review. 
Reviews in the Neurosciences. 2008;19:171–85.  
69.  
Liang KC, Melia KR, Miserendino MJD, Falls WA, Campeau S, Davis M. Corticotropin-releasing Factor: 
Long-lasting Facilitation of the Acoustic Startle Reflex. The Journal of Neuroscience. 1992;12(6):2303–12.  
70.  
Swerdlow NR, Geyer MA, Vale WW, Koob GF. Corticotropin-releasing factor potentiates acoustic 
startle in rats: Blockade by chlordiazepoxide. Psychopharmacology. 1986;88:142–52.  

71.  
Walker DL, Davis M. Anxiogenic Effects of High Illumination Levels Assessed with the Acoustic Startle 
Response in Rats. Society of Biological Psychiatry. 1997;42:461–71.  
72.  
Walker DL, Miles LA, Davis M. Selective participation of the bed nucleus of the stria terminalis and CRF 
in sustained anxiety-like versus phasic fear-like responses. Progress in Neuro-Psychopharmacology & 
Biological Psychiatry. 2009 Nov 13;33(8):1291–308.  
73.  
Grillon C, Pellowski M, Merikangas KR, Davis M. Darkness facilitates the acoustic startle reflex in 
humans. Biological Psychiatry. 1997;42(6):453–60.  
74.  
Walker DL, Davis M. Role of the extended amygdala in short-duration versus sustained fear: a tribute to 
Dr. Lennart Heimer. Brain Structure and Function. 2008;213(1-2):29–42.  
75.  
Alvarez RP, Chen G, Bodurka J, Kaplan R, Grillon C. Phasic and sustained fear in humans elicits 
distinct patterns of brain activity. NeuroImage. 2011 Mar 1;55(1):389–400.  
76.  
Grillon C, Baas JMP, Cornwell B, Johnson L. Context Conditioning and Behavioral Avoidance in a 
Virtual Reality Environment: Effect of Predictability. Biological Psychiatry. 2006;60(7):752–9.  
77.  
Grillon C. Startle reactivity and anxiety disorders : Aversive conditioning, context, and neurobiology. 
Biological Psychiatry. 2002;52(10):958–75.  
78.  
Lissek S, Pine DS, Grillon C. The strong situation: A potential impediment to studying the 
psychobiology and pharmacology of anxiety disorders. Biological Psychology. 2006;72(3):265–70.  
79.  
Hefner KR, Curtin JJ. Alcohol stress response dampening: Selectivereduction of anxiety in the face of 
uncertainthreat. Journal of Psychopharmacology.  
80.  
Hachiya LY, Moberg CA, Curtin JJ. Alcohol effects on affective response during variable and fixed 
duration threat. Alcoholism: Clinical & Experimental Research. 2010;34:117A.  
81.  
Gloria R, Jaber JN, Baker TB, Curtin JJ. The effect of temporal precision and probability on the 
response to threat of shock: a fear-potentiated startle study. Psychophysiology. 2009;46(s1):s80.  
82.  
Budney AJ, Moore BA, Vandrey RG, Hughes JR. The time course and significance of cannabis 
withdrawal. J Abnorm Psychol. 2003 Aug;112(3):393–402.  
83.  
Budney AJ, Vandrey RG, Hughes JR, Thostenson JD, Bursac Z. Comparison of cannabis and tobacco 
withdrawal: severity and contribution to relapse. J Subst Abuse Treat. 2008 Dec;35(4):362–8.  
84.  
Haney M, Ward AS, Comer SD, Foltin RW, Fischman MW. Abstinence symptoms following smoked 
marijuana in humans. Psychopharmacology (Berl.). 1999 Feb;141(4):395–404.  
85.  
Kouri EM, Pope HG Jr. Abstinence symptoms during withdrawal from chronic marijuana use. Exp Clin 
Psychopharmacol. 2000 Nov;8(4):483–92.  
86.  
Piper ME, Curtin JJ. Tobacco Withdrawal and Negative Affect: An Analysis of Initial Emotional 
Response Intensity and Voluntary Emotion Regulation. Journal of Abnormal Psychology. 2006;115(1):96–102.  
87.  
Geier A, Mucha RF, Pauli P. Appetitive nature of drug cues confirmed with physiological measures in a 
model using pictures of smoking. Psychopharmacology (Berl). 2000;150(3):283–91.  
88.  
Baas JMP. Validating a human model for anxiety using startle potentiated by cue and context: the 
effects of alprazolam, pregabalin, and diphenhydramine. Psychopharmacology. 2009;(205):73–84.  

89.  
Grillon C, Baas JMP, Pine DS, Lissek S, Lawley M, Ellis V, et al. The Benzodiazepine Alprazolam 
Dissociates Contextual Fear from Cued Fear in Humans as Assessed by Fear-potentiated Startle. Biological 
Psychiatry. 2006;60(7):760–6.  
90.  
Miles L, Davis M, Walker D. Phasic and Sustained Fear are Pharmacologically Dissociable in Rats. 
Neuropsychopharmacology. 2011 Jul;36(8):1563–74.  
91.  
Walker JR, Ahmed SH, Gracy KN, Koob GF. Microinjections of an opiate receptor antagonist into the 
bed nucleus of the stria terminalis suppress heroin self-administration in dependent rats. Brain Research. 
2000;854:85–92.  
92.  
Goeders NE, Guerin GF. Non-contingent electric footshock facilitates the aquisition of intravenous 
cocaine self-administration in rats. Psychopharmacology. 1994;:63–71.  
93.  
Aston-Jones G, Delphs JM, Druhan J, Zhu Y. The Bed Nucleus of the Stria Terminalis: A Target Site for 
Noradrenergic Actions in Opiate Withdrawal. Annals of the New York Academy of Sciences. 
1999;877(Advancing from the ventral striatum to the extended amygdala: implications for neuropsychiatry and 
drug abuse.):486–98.  
94.  
Delfs JM, Zhu Y, Druhan JP, Aston-Jones G. Noradrenaline in the ventral forebrain is critical for opiate 
withdrawal-induced aversion. Nature. 2000 Jan 27;403(6768):430–4.  
95.  
Shaham Y, Highfield D, Delfs J, Leung S, Stewart J. Clonidine blocks stress-induced reinstatement of 
heroin seeking in rats: an effect independent of locus coeruleus noradrenergic neurons. European Journal of 
Neuroscience. 2000;12(1):292–302.  
96.  
Erb S, Stewart J. A role for the bed nucleus of the stria terminalis, but not the amygdala, in the effects 
of corticotropin-releasing factor on stress-induced reinstatement of cocaine seeking. J. Neurosci. 1999 Oct 
15;19(20):RC35.  
97.  
Jonkman S, Risbrough VB, Geyer MA, Markou A. Spontaneous nicotine withdrawal potentiates the 
effects of stress in rats. Neuropsychopharmacology. 2007;:1–8.  
98.  
George O, Ghozland S, Azar MR, Cottone P, Zorrilla EP, Parsons LH, et al. CRF–CRF1 system 
activation mediates withdrawalinduced increases in nicotine self-administration in nicotine-dependent rats. 
PNAS. 2007;104(43):17198–203.  
99.  
Plaza-Zabala A, Martín-García E, de Lecea L, Maldonado R, Berrendero F. Hypocretins regulate the 
anxiogenic-like effects of nicotine and induce reinstatement of nicotine-seeking behavior. J. Neurosci. 2010 
Feb 10;30(6):2300–10.  
100.  Moskowitz DS, Young SN. Ecological momentary assessment: what it is and why it is a method of the 
future in clinical psychopharmacology. J Psychiatry Neurosci. 2006 Jan;31(1):13–20.  
101.  Hughes JR. Effects of abstinence from tobacco: Etiology, animal models, epidemiology, and 
significance: A subjective review. Nicotine & Tobacco Research. 2007 Mar;9(3):329–39.  
102.  Jorenby DE, Hatsukami DK, Smith SS, Fiore MC, Allen S, Jensen J, et al. Characterization of tobacco 
withdrawal symptoms: transdermal nicotine reduces hunger and weight gain. Psychopharmacology. 1996 Nov 
15;128(2):130.  
103.  Baker TB, Brandon TH, Chassin L. Motivational Influences on Cigarette Smoking. Annu. Rev. Psychol. 
2004 Feb;55(1):463–91.  

104.  McCarthy DE, Piasecki TM, Fiore MC, Baker TB. Life Before and After Quitting Smoking: An Electronic 
Diary Study. Journal of Abnormal Psychology. 2006;115(3):454–66.  
105.  Shiffman S. Smoking relapse crises: The Stay Quit Line project. In: Loberg TM, editor. Addictive 
behaviors: Prevention and early intervention. Bristol, PA, US: Swets & Zeitlinger Publishers; 1989.  p. 253–73. 
106.  Kenford SL, Fiore MC, Jorenby DE, Smith SS, Wetter D, Baker TB. Predicting Smoking Cessation. 
JAMA: The Journal of the American Medical Association. 1994 Feb 23;271(8):589–94.  
107.  Polosa R, Benowitz NL. Treatment of nicotine addiction: present therapeutic options and pipeline 
developments. Trends Pharmacol. Sci. 2011 May;32(5):281–9.  
108.  Stead LF, Perera R, Bullen C, Mant D, Lancaster T. Nicotine replacement therapy for smoking 
cessation. Cochrane Database Syst Rev. 2008;(1):CD000146.  
109.  Gross J, Stitzer ML. Nicotine replacement: ten-week effects on tobacco withdrawal symptoms. 
Psychopharmacology (Berl.). 1989;98(3):334–41.  
110.  Sweeney CT, Fant RV, Fagerstrom KO, McGovern JF, Henningfield JE. Combination nicotine 
replacement therapy for smoking cessation: rationale, efficacy and tolerability. CNS Drugs. 2001;15(6):453–67.  
111.  Shiffman S, Dresler CM, Hajek P, Gilburt SJA, Targett DA, Strahs KR. Efficacy of a nicotine lozenge for 
smoking cessation. Arch. Intern. Med. 2002 Jun 10;162(11):1267–76.  
112.  Morgan G, Backinger C, Lerman C, Vocci F. Translational medication development for nicotine 
addiction. Am J Health Behav. 2010 Jun;34(3):267–74.  
113.  Norberg MM, Krystal JH, Tolin DF. A meta-analysis of D-cycloserine and the facilitation of fear 
extinction and exposure therapy. Biol. Psychiatry. 2008 Jun 15;63(12):1118–26.  
114.  Ressler KJ, Rothbaum BO, Tannenbaum L, Anderson P, Graap K, Zimand E, et al. Cognitive 
enhancers as adjuncts to psychotherapy: use of D-cycloserine in phobic individuals to facilitate extinction of 
fear. Arch. Gen. Psychiatry. 2004 Nov;61(11):1136–44.  
115.  Erb S, Salmaso N, Rodaros D, Stewart J. A role for the CRF-containing pathway from central nucleus 
of the amygdala to bed nucleus of the stria terminalis in the stress-induced reinstatement of cocaine seeking in 
rats. Psychopharmacology (Berl.). 2001 Dec;158(4):360–5.  
116.  Missig G, Ayers LW, Schulkin J, Rosen JB. Oxytocin reduces background anxiety in a fear-potentiated 
startle paradigm. Neuropsychopharmacology. 2010 Dec;35(13):2607–16.  
117.  Heatherton TF, Kozlowski LT, Frecker RC, Fagerstroem KO. The Fagerstroem Test for Nicotine 
Dependence: A revision of the Fagerstroem Tolerance Questionnaire. British Journal of Addiction. 
1991;86(9):1119–27.  
118.  Cox LS, Tiffany ST, Christen AG. Evaluation of the brief questionnaire of smoking urges (QSU-brief) in 
laboratory and clinical settings. Nicotine & Tobacco Research. 2001 Feb;3(1):7–16.  
119.  Sciamanna CN, Hoch JS, Duke GC, Fogle MN, Ford DE. Comparison of Five Measures of Motivation 
to Quit Smoking Among a Sample of Hospitalized Smokers. J Gen Intern Med. 2000 Jan;15(1):16–23.  
120.  Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative 
affect: The PANAS scales. Journal of Personality & Social Psychology. 1988;54(6):1063–70.  

121.  Patrick CJ, Curtin JJ, Tellegen A. Development and validation of a brief form of the Multidimensional 
Personality Questionnaire. Psychological Assessment. 2002;14(2):150–63.  
122.  Gosselin P. Evaluation of intolerance of uncertainty: Development and validation of a new self-report 
measure. Journal of Anxiety Disorders. 2008;(22):1427–39.  
123.  Reiss S, Peterson RA, Gursky DM, McNally RJ. Anxiety sensitivity, anxiety frequency and the 
prediction of fearfulness. Behavior Research and Therapy. 1986;24(1):1–8.  
124.  Spielberger CD, Sydeman SJ. State-Trait Anxiety Inventory and State-Trait Anger Expression 
Inventory. The use of psychological testing for treatment planning and outcome assessment. 1994;:292–321.  
125.  Radloff LS. The CES-D Scale: A self-report depression scale for research in the general population. 
Applied Psycholological Measurement. 1977;1:385–401.  
126.  Schlam TR, Japuntich SJ, Piper ME, Gloria R, Baker TB, Curtin JJ. Cognitive conflict following 
appetitive versus negative cues and smoking cessation failure. Psychopharmacology. 2010 Nov;214(3):603–
16.  
127.  McCarthy DE, Gloria R, Curtin JJ. Attention bias in nicotine withdrawal and under stress. Psychol 
Addict Behav. 2009 Mar;23(1):77–90.  
128.  Fiore MC, Kenford SL, Jorenby DE, Wetter DW, Smith SS, Baker TB. Two studies of the clinical 
effectiveness of the nicotine patch with different counseling treatments. Chest. 1994 Feb;105(2):524–33.  
129.  Piasecki TM, Jorenby DE, Smith SS, Fiore MC, Baker TB. Smoking withdrawal dynamics: II. Improved 
tests of withdrawal-relapse relations. J Abnorm Psychol. 2002;112(1):14–27.  
130.  Piasecki TM, Jorenby DE, Smith SS, Fiore MC, Baker TB. Smoking withdrawal dynamics: I. Abstinence 
distress in lapsers and abstainers. Journal of Abnormal Psychology. 2003;112(1):3–13.  
131.  Piasecki TM, Jorenby DE, Smith SS, Fiore MC, Baker TB. Smoking Withdrawal Dynamics: III. 
Correlates of Withdrawal Heterogeneity. Exp Clin Psychopharmacol. 2003;11(4):276–85.  
132.  McCarthy DE, Piasecki TM, Lawrence DL, Jorenby DE, Shiffman S, Baker TB. Psychological mediators 
of bupropion sustained-release treatment for smoking cessation. Addiction. 2008;103:1521–33.  
133.  Csikszentmihalyi M, Larson R. Validity and reliability of the Experience-Sampling Method. J. Nerv. 
Ment. Dis. 1987 Sep;175(9):526–36.  
134.  Stone AA, Shiffman S. Capturing momentary, self-report data: a proposal for reporting guidelines. Ann 
Behav Med. 2002;24(3):236–43.  
135.  Hogle JM, Kaye JT, Curtin JJ. Nicotine withdrawal increases threat-induced anxiety but not fear: 
neuroadaptation in human addiction. Supplemental Information. 2010; 
136.  Blumenthal TD, Cuthbert BN, Filion DL, Hackley S, Lipp OV, van Boxtel A. Committee report: 
Guidelines for human startle eyeblink electromyographic studies. Psychophysiology. 2005 Jan;42(1):1–15.  
137.  Curtin JJ, Lang AR, Patrick CJ, Stritzke WGK. Alcohol and fear-potentiated startle: The role of 
competing cognitive demands in the stress-reducing effects of intoxication. Journal of Abnormal Psychology. 
1998;107(4):547–65.  

138.  Donohue KF, Curtin JJ, Patrick CJ, Lang AR. Intoxication Level and Emotional Response. Emotion. 
2007;7(1):103–12.  
139.  Fowles DC, Christie MJ, Edelberg R, Grings WW, Lykken DT, Venables PH. Committee report. 
Publication recommendations for electrodermal measurements. Psychophysiology. 1981 May;18(3):232–9.  
140.  Handbook of Psychophysiology. 3rd ed. Cambridge [England] ; New York: Cambridge University Press; 
2007.  898 p. 
141.  Fridlund AJ, Cacioppo JT. Guidelines for human electromyographic research. Psychophysiology. 1986 
Sep;23(5):567–89.  
142.  Miller MW, Curtin JJ, Patrick CJ. A startle probe methodology for investigating the effects of active 
avoidance on negative emotional reactivity. Biological Psychology. 1999;50(3):235–57.  
143.  Verona E, Patrick CJ, Curtin JJ, Bradley MM, Lang PJ. Psychopathy and Physiological Response to 
Emotionally Evocative Sounds. Journal of Abnormal Psychology. 2004;113(1):99–108.  
144.  Verona E, Curtin JJ. Gender differences in the negative affective priming of aggressive behavior. 
Emotion. 2006;6(1):115–24.  
145.  Verona E, Reed II A, Curtin JJ, Pole M. Gender differences in emotional and overt/covert aggressive 
responses to stress. Aggressive Behavior. 2007;33:261–71.  
146.  Phelps EA, LeDoux JE. Contributions of the amygdala to emotion processing: from animal models to 
human behavior. Neuron. 2005 Oct 20;48(2):175–87.  
147.  Bryk AS, Raudenbush DSW. Hierarchical Linear Models: Applications and Data Analysis Methods. 
Sage Publications, Inc; 1992.  
148.  Snijders PTAB, Bosker PR. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel 
Modeling. Second Edition. Sage Publications Ltd; 2011.  
149.  Hughes JR, Keely JP, Niaura RS, Ossip-Klein DJ, Richmond RL, Swan GE. Measures of abstinence in 
clinical trials: issues and recommendations. Nicotine & Tobacco Research. 2003 Feb;5(1):13.  
150.  Cohen J. A power primer. Psychological Bulletin. 1992;112(1):155–9.  
151.  Lissek S, Biggs AL, Rabin SJ, Cornwell BR, Alvarez RP, Pine DS, et al. Generalization of conditioned 
fear-potentiated startle in humans: Experimental validation and clinical relevance. Behaviour Research and 
Therapy. 2008;46:678–87.  
152.  Hanson K, Allen S, Jensen S, Hatsukami D. Treatment of adolescent smokers with the nicotine patch. 
Nicotine Tob. Res. 2003 Aug;5(4):515–26.  
153.  Houtsmuller EJ, Henningfield JE, Stitzer ML. Subjective effects of the nicotine lozenge: assessment of 
abuse liability. Psychopharmacology (Berl.). 2003 Apr;167(1):20–7.  
154.  Moolchan ET, Robinson ML, Ernst M, Cadet JL, Pickworth WB, Heishman SJ, et al. Safety and efficacy 
of the nicotine patch and gum for the treatment of adolescent tobacco addiction. Pediatrics. 2005 
Apr;115(4):e407–14.