Examining Brain Responses Linked to Emotion in Individuals Who Smoke Cigarettes
Phase: NA
Conditions: Smoking, Tobacco
Sponsor: Penn State University

 
 
 
Examining Brain Responses Linked to Emotion in Individuals Who Smoke Cigarettes 
 
NCT04310735 
 
Document Date: June 20, 2024 
 

Study Protocol 
 
Study Background and Rationale 
Functional neuroimaging methods have played an increasingly important role in the study 
of drug use and addiction (Heitzeg, Cope, Martz, & Hardee, 2015; Parvaz, Alia-Klein, 
Woicik, Volkow, & Goldstein, 2011). Functional neuroimaging has had a particularly large 
impact in the ﬁeld of research on cigarette smoking (McClernon & Gilbert, 2004). Much of 
the research using neuroimaging to examine smoking and other addictive behaviors has 
focused on brain activity associated with drug craving, which can be deﬁned as a strong 
desire or motivation to use drugs (Wilson & Sayette, 2015). This emphasis reﬂects 
widespread agreement that craving is a clinically signiﬁcant feature of drug addiction 
(TiTany & Wray, 2012).  
 
The neuroimaging methods used to study drug craving have improved in several ways over 
the past three decades. On the quantitative front, data analysis techniques have become 
far more sophisticated in recent years, paving the way for a deeper understanding of the 
relationship between complex aspects of brain functioning and the craving to use drugs. 
For example, researchers have used cutting-edge functional connectivity approaches to 
examine how activity within and between large-scale brain networks changes under 
conditions designed to increase or decrease craving (Sutherland, McHugh, Pariyadath, & 
Stein, 2012). The tools that are available to addiction researchers have grown substantially 
in many other ways. For instance, investigators can now take advantage of a diverse array 
of methods for inducing craving while collecting neuroimaging data (e.g., using 
multisensory cues; Yalachkov, Kaiser, & Naumer, 2012), creative strategies for connecting 
craving-related brain activity to subsequent behavior (e.g., combining fMRI and experience 
sampling methods; Berkman & Falk, 2013), and emerging technologies for producing 
targeted changes in brain activity to help reduce urges (e.g., real-time neurofeedback; 
Hartwell et al., 2013).  
 
In contrast to the advances described above, progress in the functional neuroimaging of 
craving has lagged in one crucial domain – the methods used to assess subjective aTective 
experience. Other than self-report measures, which have been available since the earliest 
days of neuroimaging craving research, investigators currently have few options when it 
comes to measuring subjective aTect in brain imaging studies. Self-report can provide very 
useful information about what participants are experiencing. However, self-report 
measures typically lack the sensitivity and precision needed to relate momentary aTective 
responses to simultaneous brain activity. This stems in part from the compromises that 
researchers often must make to collect self-report data in neuroimaging studies. In our 
fMRI studies of craving, for example, participants commonly rate their aTect before and 
after, but not during, the scan to reduce unwanted movement (e.g., Wilson, Sayette, & Fiez, 
2013). This asynchrony is far from ideal, as meaningful relationships may be missed if 
initial aTective responses fade or otherwise change with passing time. Even when self-
report measures are administered while brain imaging data are being acquired, ratings are 
frequently made using devices with a very small number of possible responses (e.g., 

handheld units with ﬁve buttons). As a result, researchers routinely ﬁnd it necessary to rely 
upon coarse Likert scales that fail to fully capture the continuous nature of aTective 
experience. 
 
The lack of objective, sensitive methods for measuring aTective experience in 
neuroimaging craving research is an important limitation given the strong evidence that 
craving and aTect are closely interrelated (TiTany, 2010). Indeed, some have argued that 
craving is essentially an aTective process (Baker, Morse, & Sherman, 1986; Giuliani & 
Berkman, 2015). Regardless of whether craving and aTect are separate but tightly 
connected or craving is inherently an aTective state, it is clear that the ﬁeld needs 
alternative strategies for assessing aTect – particularly nonverbal methods – that can serve 
as a complement to self-report measures.  
 
This project is based on the premise that neuroimaging craving research has been hindered 
in important ways by having to rely exclusively on self-report measures of aTect, and that 
an alternative approach that involves using facial coding analysis to assess aTective 
responses holds substantial promise for addressing this barrier to progress. Successful 
completion of the aims of the project would provide valuable data regarding the feasibility 
of measuring aTect during brain imaging using facial coding. This comprehensive and 
multimodal assessment approach has the potential to make a signiﬁcant impact on the 
ﬁeld by providing addiction researchers with a powerful new tool for characterizing the 
relationship between craving-related brain activity and aTect. More broadly, facial coding 
would serve as a potent supplement to self-report in any area using neuroimaging to study 
aTective responses (e.g., studies of depression, basic research on emotion and decision 
making). 
 
Study Objectives 
The goal of this project is to combine functional magnetic resonance imaging (MRI) and 
facial expression analysis to examine associations between moment-to-moment changes 
in brain activity and emotional responses in individuals who smoke cigarettes. These 
associations will be assessed under conditions designed to increase the motivation to 
smoke. The speciﬁc aims of the project are: 1) to demonstrate the feasibility of measuring 
aTect by coding facial expressions displayed during functional MRI; and 2) to demonstrate 
that moment-to-moment changes in aTect are meaningfully associated with ongoing brain 
activity in individuals who are motivated to smoke. It is hypothesized that facial coding will 
be eTective for quantifying the positive and negative aTect exhibited by smokers in the MRI 
scanner. It is also hypothesized that emotional responses will be associated with brain 
activity in areas previously linked to cigarette craving (e.g., the ventromedial prefrontal 
cortex and anterior cingulate cortex). If successful, the proposed project will provide a 
foundation for using this new method to explore a variety of questions that are currently 
very diTicult to address (e.g., characterizing how aTect changes dynamically in relation to 
brain activity when smokers attempt to regulate their craving). 
 

In addition to these primary objectives, the study also includes behavioral testing with the 
following goals: ﬁnalizing initial study procedures and subsequent modiﬁcations required 
due to the COVID-19 pandemic through pilot testing; allowing progress toward the aims of 
the project while research was initially shut down and then subsequently restricted due to 
the COVID-19 pandemic; and troubleshooting technical challenges. This includes 
behavioral testing to identify a subset of stimuli from the set that reliably elicit aTective 
facial expressions for use during fMRI scanning. To facilitate the ability to interpret the 
emotional facial expressions exhibited by participants experiencing cigarette craving, we 
will also examine the facial reactions that they exhibit during basic positive and negative 
emotional states induced by experimental stimuli. Various methods have been used to 
induce emotions in the laboratory, but relatively little is known about the relative 
eTectiveness of these approaches. This is particularly true when it comes to produce target 
emotional states in individuals who smoke cigarettes and who are experiencing a craving to 
smoke. As a result, it is not clear which method for inducing emotion would be best to 
include in the fMRI study. To address this gap, behavioral testing will be conducted to 
evaluate the eTectiveness of the following types of stimuli: “neutral” pictures and videos 
designed to elicit minimal changes in the urge to smoke; smoking-related pictures and 
videos designed to elicit increases in the urge to smoke; smoking-unrelated pictures and 
videos designed to elicit strong negative aTect; and smoking-unrelated pictures and videos 
designed to elicit strong positive aTect. Participants' facial reactions will be recorded and 
coded to determine which stimuli elicit more robust aTective facial expressions. 
 
Participant Identiﬁcation and Recruitment 
Participants will be recruited using the following methods: radio advertisements, 
newspaper advertisements, posted ﬂyers at approved locations on PSU campuses 
(including branch campuses) and businesses (local and in surrounding townships), 
website ads, social media (e.g., Facebook and Twitter), and email listservs. In addition to 
being placed directly by the study PI or other study personnel, the project will use the 
services of a company called BuildClinical to post recruitment ads that will be run across 
many diTerent digital platforms (e.g., Facebook, Instagram, Google, Bing, WebMD, 
YouTube, Snapchat, Reddit, Twitter, and banner ads). We will also advertise the study on 
www.researchmatch.org and StudyFinder. 
 
Advertisements posted directly by the study PI or other study personnel will invite potential 
participants to email or phone the PI's laboratory.  Or, as an alternative when relevant (e.g., 
for posted ﬂyers), individuals can scan a QR code with their smartphone and ﬁll out a very 
brief REDCap prescreening questionnaire (REDCap_PrescreeningForm.pdf). If they qualify 
based on the preliminary screening, they will then be called by the lab for additional 
information and, if interested, to see if they are eligible. In addition, we will contact 
individuals who have expressed interest in being contacted for future studies conducted by 
our laboratory by answering “yes” to a question asking them whether or not they would like 
to be contacted for future studies during a telephone screening and/or by giving permission 
for such contact on an informed consent form. 
 

Study Design 
The primary study is comprised of two parts: (1) a screening/baseline session and (2) a 
functional MRI experimental visit. This is a between-groups experimental design in which 
participants will be randomly assigned to two conditions (Expect-Yes and Expect-No). The 
study will use the following modiﬁed design while revised standards are in place due to the 
COVID-19 pandemic: (1a) remote screening/baseline session; (1b) an abbreviated in-
person visit to biochemically verify smoking status, and (2) a functional MRI experimental 
visit. The study will also include behavioral testing using a within-subjects experimental 
design with one independent variable: (1) stimulus type (neutral vs. smoking-related 
pictures and videos, negative vs. positive pictures and videos). 
 
Study Procedures 
Screening/baseline session 
• Upon arrival, participants will be asked to turn oT or silence their cell phone and/or 
any other personal electronic devices and to refrain from using them during the 
session, except for during breaks or to record pertinent information (e.g., entering 
the date and time for the next scheduled visit into a calendar). (They will be given 
similar instructions at the start of the functional MRI experimental visit.)  
• After informed consent is obtained, participants will be asked to complete a brief 
Demographics questionnaire and the Fagerström Test for Nicotine Dependence.  
• Next, participants will be asked to provide a carbon monoxide sample, which is a 
screening procedure that is used to verify their smoking status. To provide a CO 
sample, participants will be asked to hold their breath for 20 seconds and then 
exhale into a disposable mouthpiece attached to a carbon monoxide device. The 
device will produce a CO reading in parts per million immediately.  
• Next, participants will be given an overview of the key information covered in the 
informed consent form to ensure that they fully understand the timeline and 
requirements of the study. They will be given a chance to ask any questions that they 
have about the study. 
• Next, participants will be administered a battery of baseline measures.  
• Following screening, they will be introduced to MRI through an orientation 
conducted in the Mock Scanner room of the 3T MRI Facility in the basement of 
Chandlee Lab. The participant will be asked to lie on a table and slid into the mock 
scanner to become accustomed to the size of the bore, as well as the sounds of the 
magnet. They will also be informed about the importance of remaining still while in 
the scanner. 
• After completing the practice, participants will be removed from the mock scanner. 
They will then be told to abstain from smoking cigarettes or using any other nicotine 
products for 12 hours and from using alcohol/recreational drugs for 24 hours before 
the functional MRI experimental visit. Participants will also be asked to bring at least 
one of their cigarettes with them to the experimental visit because they may be 
given an opportunity to smoke during the session.  

• The screening/baseline session will then conclude, and participants will be 
compensated via cash payment. 
 
Functional MRI experimental visit 
• Participants will complete one functional MRI experimental visit, which will be held 
on a separate day. 
• At the start of each session, participants will be asked to report the last time that 
they have used any of the following: cigarettes, other nicotine products, alcohol, 
and recreational drugs. They will also provide a CO sample to verify 12-hour 
abstinence from cigarettes, based upon a cutoT derived from prior research 
(Cropsey et al., 2014; Javors, Hatch, & Lamb, 2005).  
• Participants will then complete computerized measures assessing nicotine 
withdrawal, craving, and state aTect. 
• Next, participants will be told that they will be given a 15-minute break immediately 
following the functional MRI portion of the session and that they will be informed 
whether or not they will be given the opportunity to smoke during the break shortly 
before it begins. 
• Next, participants will be escorted to the SLEIC and placed in the MRI scanner. 
• While in the MRI scanner, participants will complete the following functional tasks 
(in addition to the collection of anatomical images). First, participants will be shown 
several video clips (each approximately 20-30 seconds). Participants will be 
instructed to watch and respond naturally to the videos, and they will be asked to 
rate how they are feeling after each clip. These videos consist of short clips of real-
life situations from a research database recently developed by Samson et al. (2016). 
Some of these videos are designed to produce negative aTect (mostly painful 
accidents). The remaining videos are designed to produce positive aTect (e.g., 
children dancing). Next, participants will be randomly assigned to two groups. 
Speciﬁcally, one group (those assigned to the Expect-Yes condition) will be informed 
that they will be given an opportunity to smoke during a 15-minute break 
immediately following the functional MRI portion of the session. The other group 
(those assigned to the Expect-No condition) will be informed that they will not be 
given an opportunity to smoke during the study and will therefore have to wait until 
after the session has concluded before having a chance to smoke (although they 
will still be given a 15-minute break immediately following the functional MRI portion 
of the session).  
• Next, participants will be presented with two additional types of short videos (each 
approximately 20-30 seconds): (1) half designed to elicit minimal changes in aTect 
and the urge to smoke (“neutral” videos); and (2) half designed to elicit signiﬁcant 
changes in aTect and the desire to smoke (smoking-related videos). Participants 
will be instructed to watch and respond naturally to the videos, and they will be 
asked to rate how they are feeling after each clip. These videos were developed and 
validated by Tong et al. (2007) for use in smoking research.   

• Participants’ faces will be video recorded during functional MRI scanning using a 
commercially available MRI-compatible camera system (MR-Cam 12M-I, MRC 
Systems, Heidelberg, Germany) that was developed for various applications (e.g., 
patient monitoring, eye tracking). The cameras will be mounted to the head coil 
during fMRI data collection. The cameras contain an integrated LED for illumination 
and can be equipped with diTerent lenses to optimize the magniﬁcation, ﬁeld of 
view, and working distance. All parts and connections are shielded to prevent the 
camera from introducing artifacts into the MRI/fMRI data (and vice versa). The 50-Hz 
analog output from the cameras will be transmitted to a computer in the control 
room, where it will be converted to a digital signal using a frame grabber and 
recorded for subsequent facial coding analysis. 
• After completing the MRI scan, participants will be removed from the scanner and 
will be escorted to 308 Chandlee for a 15-minute break. The suite in 308 Chandlee 
houses the Penn State Smoking Behavior Research Facility, a shared resource at the 
University Park campus dedicated to facilitating the University’s developing strength 
in interdisciplinary tobacco-related research. The Smoking Behavior Research 
Facility contains four independently ventilated rooms that allow research 
participants to light and smoke cigarettes during research sessions while the 
remaining areas of the laboratory remain smoke-free. Participants assigned to the 
Expect-Yes condition (those told earlier that they would be given the opportunity to 
smoke before the end of the study), will be permitted to smoke one cigarette while 
in the testing room during this break. They will be oTered a cigarette of their 
preferred brand from a supply kept by the lab, although they will also be free to 
smoke one of their own as an alternative. Participants assigned to the Expect-No 
condition (those told earlier that they would not be given the opportunity to smoke 
before the end of the study) will also be given a 15-minute break, but they will not be 
given the opportunity to smoke during the break.   
 
• Participants will be asked to remain in the lab after the break before being excused. 
This is designed to maintain the integrity of the smoking expectancy manipulation, 
as participants often learn about the study through word-of-mouth. During this 
period, participants will be asked to provide ratings of how they are feeling and their 
urge to smoke periodically, as well as a questionnaire assessing personality traits.  
• The functional MRI experimental visit and study will then conclude, and participants 
will be compensated via cash payment. 
 
Behavioral testing only 
A subset of participants was asked to complete behavioral testing only for initial piloting, to 
allow progress toward the aims of the project while research was initially shut down and 
then subsequently restricted due to the COVID-19 pandemic, and to troubleshoot 
technical challenges. They completed the following procedures: 
• Participants will be presented with stimuli designed to elicit positive and negative 
aTect. Stimuli will consist of the following:  

o Videos of still photos from the International ATective Picture System (IAPS; 
Lang, 1988), with mood-congruent instrumental music played throughout 
the presentation of the images. Half of the videos contain images designed to 
produce negative aTect (e.g., children and adults looking upset and/or with 
serious injuries, dead animals). The remaining half of the videos contain 
images designed to produce positive aTect (e.g., romantic couples [there are 
no erotic images], smiling babies). 
o Video of short clips of real-life situations from a research database recently 
developed by Samson et al. (2016). Half of the videos contain images 
designed to produce negative aTect (mostly painful accidents). The 
remaining half of the videos contain images designed to produce positive 
aTect (e.g., children dancing). 
o Videos developed and validated by Tong et al. (2007) for use in smoking 
research. Half of the videos contain scenes designed to elicit signiﬁcant 
changes in aTect and the desire to smoke (smoking-related videos). The 
remaining half of the videos contain scenes designed to elicit minimal 
changes in aTect and the urge to smoke (“neutral” videos).  
• Participants will be instructed to watch and respond naturally to the videos, and 
they will be asked to rate how they are feeling after each clip.  
• Participants' faces will be recorded as they watch the videos.  
• After the completion of the video task, behavioral testing will conclude, and 
participants will be compensated via cash payment. 
 
Statistical Analysis Plan 
Recordings of participants’ facial movements will be analyzed using FaceReader software 
(Noldus Information Technology). FaceReader processes facial data using three automated 
steps. First, the software detects the presence of a face using a robust cascaded classiﬁer 
algorithm [61]. Second, an algorithm based on the Active Appearance method [62] is 
applied to create a three-dimensional model with over 500 points capturing the shape and 
texture of the face. Third, using this network of points, the software classiﬁes facial 
expressions using a three-layer feed-forward neural network trained on more than 10,000 
facial images depicting basic emotions that were coded manually by trained experts. 
 
FaceReader will be used to derive a time course (at a 50 Hz sampling rate) quantifying the 
valence of participants’ aTect during stimulus exposure (ranging from highly positive to 
highly negative). Valence will be calculated based on automated analysis of facial 
expressions linked to “felt” aTect for each video frame spanning the run in which the 
evocative stimuli are presented. 
 
Functional MRI data will be preprocessed using standard steps (including motion 
correction, non-brain removal, spatial smoothing, grand-mean intensity normalization, and 
high-pass temporal ﬁltering). Following preprocessing, statistical analysis of the functional 
MRI data will be conducted within the framework of the general linear model (GLM). 
Following model ﬁtting, subsequent analyses will compare the eTects of stimulus 

condition (e.g., smoking-related versus neutral cues) on brain activation as a function of 
smoking expectancy condition (Expect-Yes vs. Expect-No). As a primary outcome, we will 
focus on eTects in two a priori regions of interest (ROIs). The ﬁrst is the ventromedial 
prefrontal cortex (vmPFC), as there is strong evidence that vmPFC activity positively 
correlates with the subjective value of stimuli and actions, including during the anticipation 
of imminent rewards. We will create an ROI in the vmPFC ROI by generating a 10-mm 
sphere centered at the following MNI coordinates taken from a meta-analysis of 206 fMRI 
studies examining subjective valuation: x = -1, y = 46, z = -7 (Batra et al., 2013). The second 
region we will focus on is the dorsal anterior cingulate cortex (dACC), as research indicates 
that it is consistently activated under conditions that produce negative aTect, such as 
when there is a conﬂict between current and desired states. We will create an ROI in the 
dACC by generating a 10-mm sphere centered at the following MNI coordinates taken from 
a meta-analysis of 59 fMRI studies of negative aTect: x = -2, y = 10, z = 38 (Shackman et al., 
2011). 
 
Risks 
More than a million MRI studies have been performed around the world. We will be 
following standard MRI procedures. High magnetic ﬁeld inside of the scanner can be 
hazardous in the presence of some metallic devices, speciﬁcally: magnetic ﬁelds may 
dislodge metallic implants, causing bleeding and disruption of adjacent tissues. Magnetic 
ﬁelds may also cause problems for electrical pacemakers and stimulators. In addition, 
radio waves may heat the body and metallic objects within or on the body, possibly 
resulting in burns.  Finally, certain metallic objects may move toward the magnet at very 
fast speeds if attracted by the magnetic ﬁeld. Although highly unlikely, participants might 
experience dizziness, mild nausea, or tiny ﬂashing lights while in the magnet. These 
sensations are mostly due to movement while inside the magnet and can be minimized by 
holding still. All of these sensations should stop shortly after leaving the magnet. 
Additionally, because of the small space in the magnet, and the length of the study, some 
people ﬁnd the experiment to be uncomfortable. However, since participants will have a 
visual screen to look at, they are unlikely to experience such feelings. There are no known 
risks from MRI apart from those described above. However, there is always the possibility 
that there are unknown risks associated with this procedure. It is important that a baby 
(fetus) developing in the uterus not be exposed to any unnecessary risks. Therefore, to 
participate in this study, female participants must report that they are not pregnant.  
 
There is a risk that participants will be uncomfortable about answering some of the 
questions they are asked. Participants will be informed that they do not have to answer any 
questions that they do not wish to during both the phone screen and during the ﬁrst visit 
when consent is obtained.  
 
Some of the questions that participants will be asked during the study concern potentially 
illegal behavior, such as using illegal drugs.  This information could potentially be a risk if it 
became known and could be linked to the participant’s identity. While participants are 
asked to answer questions regarding their drug and alcohol use, all information gathered 

from participants will be kept completely conﬁdential.  Participants’ names and identifying 
information will not appear on any data forms to ensure conﬁdentiality.  The identity of 
participants will be indicated by a case number on collected records.  Participant data ﬁles 
will be accessible only to the PI and trained research staT. 
 
Participants may be given the option of smoking during the experimental session. The use 
of nicotine and tobacco products during pregnancy poses well-known risks to fetal 
development. However, participants will not be required to smoke a cigarette as a part of 
the study; that is, they are free to decline the opportunity to smoke. In addition, 
participants will already have indicated that they are not pregnant as a part of the standard 
MRI safety form that is administered as a part of SLEIC SOP before the fMRI portion of the 
session. Thus, we do not believe that this aspect of the study (i.e., providing participants 
with the option of smoking) involves any increase in risk in relation to pregnancy.  
 
Participants may experience symptoms of nicotine withdrawal (e.g., irritability, fatigue, 
diTiculty concentrating) when attempting to refrain from smoking before the functional MRI 
experimental visit. Participants are free to resume smoking at any time, however, which 
should eliminate any withdrawal symptoms. In sum, we do not anticipate that participants 
will experience any risks that are above what people experience in everyday life. 
 
Finally, there is a risk of loss of conﬁdentiality if participants’ information or your identity is 
obtained by someone other than the investigators, but precautions will be taken to prevent 
this from happening (as described below).  
The following steps will be taken to minimize risks: 
• Participants will ﬁll out a screening form to determine if they have any implants that 
would endanger them in the MRI (e.g., if a participant has a pacemaker or stimulator 
implanted, they will not be eligible to participate in this research).  
• Participants will be carefully checked by the experimenter or technologist for the 
presence of any metallic objects such as body piercings or items in pockets. 
• Participants will be asked to let the experimenter or technologist know if they feel 
any unusual warmth during the MRI scan.  
• Participants can discontinue the study at any time without penalty (e.g., to smoke a 
cigarette to alleviate symptoms of nicotine withdrawal). 
• As noted above, participants’ names and identifying information will not appear on 
any data forms to ensure conﬁdentiality; the identity of participants will be indicated 
by a case number on collected records; and participant data ﬁles will be accessible 
only to the PI and trained research personnel. 
• A list that matches participants’ names with their code number will be kept in a 
password-protected ﬁle on a secure computer server. 
• All task and questionnaire data ﬁles (including MRI data ﬁles) will be coded with a 
unique ID number and all names or other personal identiﬁable information will be 
removed. Only this code (and never participants’ names) will be used when 
analyzing or reporting data. 

• All data ﬁles will be stored and secured in Penn State Addiction Smoking and Health 
Lab of the Pennsylvania State University in a locked cabinet in a locked oTice (in 
Moore or Chandlee Building) or, for computer ﬁles, in a password-protected ﬁle on a 
secure computer server. Only members of the research team will have access to 
this information. 
• In the event of any publication or presentation resulting from the research, no 
personally identiﬁable information will be shared. 
• The conﬁdentiality of electronic data will be maintained to the degree permitted by 
the technology used.

References 
 
Baker, T. B., Morse, E., & Sherman, J. E. (1986). The motivation to use drugs: A 
psychobiological analysis of urges. Nebraska Symposium on Motivation, 34, 257-
323.  
Bartra, O., McGuire, J. T., & Kable, J. W. (2013). The valuation system: a coordinate-based 
meta-analysis of BOLD fMRI experiments examining neural correlates of subjective 
value. Neuroimage, 76, 412-427. doi:10.1016/j.neuroimage.2013.02.063. 
Berkman, E. T., & Falk, E. B. (2013). Beyond Brain Mapping. Current Directions in 
Psychological Science, 22(1), 45-50. doi:10.1177/0963721412469394. 
Cropsey, K. L., Trent, L. R., Clark, C. B., Stevens, E. N., Lahti, A. C., & Hendricks, P. S. 
(2014). How low should you go? Determining the optimal cutoff for exhaled carbon 
monoxide to confirm smoking abstinence when using cotinine as reference. Nicotine 
& Tobacco Research, 16(10), 1348-1355. doi:10.1093/ntr/ntu085 
Giuliani, N. R., & Berkman, E. T. (2015). Craving Is an Affective State and Its Regulation Can 
Be Understood in Terms of the Extended Process Model of Emotion Regulation. 
Psychological Inquiry, 26(1), 48-53. doi:10.1080/1047840X.2015.955072. 
Hartwell, K. J., Prisciandaro, J. J., Borckardt, J., Li, X., George, M. S., & Brady, K. T. (2013). 
Real-time fMRI in the treatment of nicotine dependence: A conceptual review and 
pilot studies. Psychology of Addictive Behaviors, 27(2), 501-509. 
doi:10.1037/a0028215. 
Heitzeg, M. M., Cope, L. M., Martz, M. E., & Hardee, J. E. (2015). Neuroimaging Risk Markers 
for Substance Abuse: Recent Findings on Inhibitory Control and Reward System 
Functioning. Current Addiction Reports, 2(2), 91-103. doi:10.1007/s40429-015-0048-
9. 
Javors, M. A., Hatch, J. P., & Lamb, R. J. (2005). Cut-off levels for breath carbon monoxide 
as a marker for cigarette smoking. Addiction, 100(2), 159-167. doi:10.1111/j.1360-
0443.2004.00957.x 
McClernon, F. J., & Gilbert, D. G. (2004). Human functional neuroimaging in nicotine and 
tobacco research: Basics, background, and beyond. Nicotine & Tobacco Research, 
6(6), 941-959. doi:10.1080/14622200412331337394. 
Parvaz, M., A., Alia-Klein, N., Woicik, P. A., Volkow, N. D., & Goldstein, R. Z. (2011). 
Neuroimaging for drug addiction and related behaviors. Reviews in the 
Neurosciences, 22(6), 609. doi:10.1515/RNS.2011.055. 

Samson, A. C., Kreibig, S. D., Soderstrom, B., Wade, A. A., & Gross, J. J. (2016). Eliciting 
positive, negative and mixed emotional states: A film library for affective scientists. 
Cognition and Emotion, 30(5), 827-856. doi:10.1080/02699931.2015.1031089. 
Shackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson, R. J. 
(2011). The integration of negative affect, pain and cognitive control in the cingulate 
cortex. Nature Reviews Neuroscience, 12(3), 154-167. doi: 10.1038/nrn2994 
Sutherland, M. T., McHugh, M. J., Pariyadath, V., & Stein, E. A. (2012). Resting state 
functional connectivity in addiction: Lessons learned and a road ahead. 
NeuroImage, 62(4), 2281-2295. doi: 10.1016/j.neuroimage.2012.01.117 
Tiffany, S. T. (2010). Drug craving and affect. In J. D. Kassel (Ed.), Substance abuse and 
emotion (pp. 83-108). Washington, DC: American Psychological Association. 
Tiffany, S. T., & Wray, J. M. (2012). The clinical significance of drug craving. Annals of the 
New York Academy of Sciences, 1248(1), 1-17. doi:10.1111/j.1749-
6632.2011.06298.x. 
Tong, C., Bovbjerg, D. H., & Erblich, J. (2007). Smoking-related videos for use in cue-
induced craving paradigms. Addictive Behaviors, 32(12), 3034-3044. 
doi:10.1016/j.addbeh.2007.07.010. 
Wilson, S. J., Creswell, K. G., Sayette, M. A., & Fiez, J. A. (2013). Ambivalence about 
smoking and cue-elicited neural activity in quitting-motivated smokers faced with an 
opportunity to smoke. Addictive Behaviors, 38(2), 1541-1549. doi: 
10.1016/j.addbeh.2012.03.020. 
Wilson, S. J., & Sayette, M. A. (2015). Neuroimaging craving: urge intensity matters. 
Addiction, 110(2), 195-203. doi:10.1111/add.12676. 
Yalachkov, Y., Kaiser, J., & Naumer, M. J. (2012). Functional neuroimaging studies in 
addiction: Multisensory drug stimuli and neural cue reactivity. Neuroscience & 
Biobehavioral Reviews, 36(2), 825-835. doi: 10.1016/j.neubiorev.2011.12.004.