Mindful attention reduces neural and self-reported cue-induced craving in smokers.
ABSTRACT An emerging body of research suggests that mindfulness-based interventions may be beneficial for smoking cessation and the treatment of other addictive disorders. One way that mindfulness may facilitate smoking cessation is through the reduction of craving to smoking cues. The present work considers whether mindful attention can reduce self-reported and neural markers of cue-induced craving in treatment seeking smokers. Forty-seven (n = 47) meditation-naïve treatment-seeking smokers (12-h abstinent from smoking) viewed and made ratings of smoking and neutral images while undergoing functional magnetic resonance imaging (fMRI). Participants were trained and instructed to view these images passively or with mindful attention. Results indicated that mindful attention reduced self-reported craving to smoking images, and reduced neural activity in a craving-related region of subgenual anterior cingulate cortex (sgACC). Moreover, a psychophysiological interaction analysis revealed that mindful attention reduced functional connectivity between sgACC and other craving-related regions compared to passively viewing smoking images, suggesting that mindfulness may decouple craving neurocircuitry when viewing smoking cues. These results provide an initial indication that mindful attention may describe a 'bottom-up' attention to one's present moment experience in ways that can help reduce subjective and neural reactivity to smoking cues in smokers.
- SourceAvailable from: PubMed Central
Article: The Addict in Us all.[Show abstract] [Hide abstract]
ABSTRACT: In this paper, we contend that the psychology of addiction is similar to the psychology of ordinary, non-addictive temptation in important respects, and explore the ways in which these parallels can illuminate both addiction and ordinary action. The incentive salience account of addiction proposed by Robinson and Berridge (1-3) entails that addictive desires are not in their nature different from many of the desires had by non-addicts; what is different is rather the way that addictive desires are acquired, which in turn affects their strength. We examine these "incentive salience" desires, both in addicts and non-addicts, contrasting them with more cognitive desires. On this account, the self-control challenge faced by addicted agents is not different in kind from that faced by non-addicted agents - though the two may, of course, differ greatly in degree of difficulty. We explore a general model of self-control for both the addict and the non-addict, stressing that self-control may be employed at three different stages, and examining the ways in which it might be strengthened. This helps elucidate a general model of intentional action.Frontiers in Psychiatry 10/2014; 5:139.
- [Show abstract] [Hide abstract]
ABSTRACT: Research suggesting the beneficial effects of yoga on myriad aspects of psychological health has proliferated in recent years, yet there is currently no overarching framework by which to understand yoga's potential beneficial effects. Here we provide a theoretical framework and systems-based network model of yoga that focuses on integration of top-down and bottom-up forms of self-regulation. We begin by contextualizing yoga in historical and contemporary settings, and then detail how specific components of yoga practice may affect cognitive, emotional, behavioral, and autonomic output under stress through an emphasis on interoception and bottom-up input, resulting in physical and psychological health. The model describes yoga practice as a comprehensive skillset of synergistic process tools that facilitate bidirectional feedback and integration between high- and low-level brain networks, and afferent and re-afferent input from interoceptive processes (somatosensory, viscerosensory, chemosensory). From a predictive coding perspective we propose a shift to perceptual inference for stress modulation and optimal self-regulation. We describe how the processes that sub-serve self-regulation become more automatized and efficient over time and practice, requiring less effort to initiate when necessary and terminate more rapidly when no longer needed. To support our proposed model, we present the available evidence for yoga affecting self-regulatory pathways, integrating existing constructs from behavior theory and cognitive neuroscience with emerging yoga and meditation research. This paper is intended to guide future basic and clinical research, specifically targeting areas of development in the treatment of stress-mediated psychological disorders.Frontiers in Human Neuroscience 09/2014; 8:770. · 2.90 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: It has been posited that self-regulation of behaviors, emotions, and temptations may all rely on a common resource. Recent reviews suggest this common resource may include the inferior frontal cortex (IFC). However, to our knowledge no single functional neuroimaging study has tested this hypothesis. We obtained fMRI scans as 25 abstinent treatment-seeking cigarette smokers completed motor, affective, and craving self-control tasks before smoking cessation treatment. We identified two regions in left IFC and a region in pre-supplementary motor area (preSMA) that were commonly activated in all three tasks. Further, PPI analyses suggest that IFC may involve dissociable pathways in each self-control domain. Specifically, the IFC showed negative functional connectivity with large portions of the thalamus and precentral gyrus during motor stopping, with the insula and other portions of the thalamus during craving regulation, and potentially with a small limbic region during emotion regulation. We discuss implications for understanding self-control mechanisms.Clinical psychological science : a journal of the Association for Psychological Science. 09/2014; 2(5):611-619.
Mindful attention reduces neural and self-reported
cue-induced craving in smokers
Cecilia Westbrook,1John David Creswell,2Golnaz Tabibnia,2Erica Julson,2Hedy Kober,3and
Hilary A. Tindle4
1University of Wisconsin, School of Medicine and Public Health, Madison, Wisconsin, USA,2Department of Psychology, Carnegie Mellon
University, Pittsburgh, PA, USA,3Department of Psychiatry, Yale University, New Haven, CT, USA, and4University of Pittsburgh, Medical
Center, Pittsburgh, PA, USA
An emerging body of research suggests that mindfulness-based interventions may be beneficial for smoking cessation and the
treatment of other addictive disorders. One way that mindfulness may facilitate smoking cessation is through the reduction
of craving to smoking cues. The present work considers whether mindful attention can reduce self-reported and neural markers of
cue-induced craving in treatment seeking smokers. Forty-seven (n¼47) meditation-nal ¤ve treatment-seeking smokers (12-h
abstinent from smoking) viewed and made ratings of smoking and neutral images while undergoing functional magnetic
resonance imaging (fMRI). Participants were trained and instructed to view these images passively or with mindful attention.
Results indicated that mindful attention reduced self-reported craving to smoking images, and reduced neural activity in a
craving-related region of subgenual anterior cingulate cortex (sgACC). Moreover, a psychophysiological interaction analysis
revealed that mindful attention reduced functional connectivity between sgACC and other craving-related regions compared to
passively viewing smoking images, suggesting that mindfulness may decouple craving neurocircuitry when viewing smoking
cues. These results provide an initial indication that mindful attention may describe a ?bottom-up? attention to one?s present
moment experience in ways that can help reduce subjective and neural reactivity to smoking cues in smokers.
Keywords: mindfulness; craving; fMRI
Nearly, half of the adult smokers attempt to quit each year,
but the majority of quit attempts are unsuccessful, even with
clinical intervention (Hughes et al., 2004; Center for Disease
Control and Prevention, 2008; United States Public Health
Service, 2008). Whether successful or not, smoking cessation
is a significant stressor, causing disturbances of mood, cog-
nition, sleep and cigarette craving, all of which may persist
long term (Piasecki et al., 1998; Gilbert et al., 1999, 2002).
Therefore, identifying novel behavioral treatments to reduce
these consequences is of the utmost importance.
Recently, interest has grown in the use of mindfulness-
based treatments for addictive disorders, including smoking
(Witkiewitz et al., 2005; Brewer et al., 2010). Mindfulness
is often defined as attention to moment-to-moment experi-
ence, coupled with a nonjudgmental, accepting attitude
toward that experience (Bishop et al., 2004). Mindfulness-
based approaches have demonstrated efficacy for a variety of
psychiatric concerns (Brown et al., 2007; Chiesa and Serretti,
2011; Fjorback et al., 2011). To date, mindfulness-based ad-
diction treatments have shown promise in nonrandomized
pilot studies for smoking cessation (Altner, 2002; Witkiewitz
et al., 2005, 2010; Davis et al., 2007; Bowen and
Marlatt 2009). In the first randomized, controlled trial
of a mindfulness-based intervention for smoking cessation,
Brewer et al. (in press) found that mindfulness training was
associated with reductions in smoking and improvements in
biochemically validated abstinence, both immediately after
treatment and at 17-week follow-up, in comparison to a
standard behavioral cessation paradigm.
One way mindful attention might help smokers is through
reductions in craving (Brewer et al., in press). Cigarette crav-
ing has been identified as an important factor in cessation
attempts, as individuals with high levels of craving are more
likely to relapse (e.g. Killen and Fortmann, 1997), and
craving often directly precedes relapse (Allen et al., 2008).
In the Buddhist tradition, craving is considered one of the
five hindrances, whose influence could be lessened by the
deployment of mindful attention (Fronsdal, 2005). Mindful
attention has been shown to help alleviate negative
Received 8 July 2011; Accepted 2 October 2011
The authors would like to acknowledge the following individuals for advice and help at various stages of
this project: Judd Brewer, James Bursley, Fadel Zeidan, the Pittsburgh Brain Imaging Research Center and the
Pittsburgh Mind Body Center; and to Jill Delaney and Courtney Watson for their research assistance. C.W.
would especially like to thank Dr Jennifer Silk for her guidance and support.
This work was supported in large part by the Pittsburgh Foundation Charles and Nancy Emmerling Fund to HT
and by the National Center for Research Resources (NCRR), a component of the National Institutes of Health
(NIH), and NIH Roadmap for Medical Research (KL2 RR024154-05 to H.T.). Its contents are solely the
responsibility of the authors and do not necessarily represent the official view of NCRR or NIH.
Information on NCRR is available at http://www.ncrr.nih.gov/. Information on Re-engineering the Clinical
Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overview-translational.
asp.; as well as a grant from the Pittsburgh Mind Body Center to HT, Mind and Life Institute Varela Awards to
H.T. and C.W., the Pittsburgh Life Sciences Greenhouse Opportunity Fund to G.T. and D.C., and T32 MH17140
Correspondence should be addressed to Cecilia Westbrook, 526 W. Washington Ave Apt. 1A, Madison, WI,
53703, USA. Email: firstname.lastname@example.org and John David Creswell, Department of Psychology, 5000 Forbes
Ave., Pittsburgh, PA, 15213. Email: email@example.com
doi:10.1093/scan/nsr076SCAN (2011) 1of12
? TheAuthor (201 1).Publishedby OxfordUniversity Press.For Permissions,pleaseemail:firstname.lastname@example.org
Social Cognitive and Affective Neuroscience Advance Access published November 22, 2011
by guest on November 27, 2011
emotional states, such as distress (e.g. Jain et al., 2007) and
may therefore have benefits against craving as well. (For a
theoretical and empirical review of mindfulness, see Brown
et al., 2007.)
Several studies have examined the relationship be-
Vidrine et al. (2009) found that among smokers enrolled
in a cessation study, dispositional mindfulness was linked
to lower baseline nicotine dependence, greater sense of
agency regarding cessation and other factors known to pre-
dict success in quitting. Bowen and Marlatt (2009) randomly
assigned smokers to receive mindfulness instructions or no
instructions during cue-induced craving. Mindfulness in-
structions were associated with significant decreases in
smoking over the subsequent 7 days. Similarly, Rogojanski
et al. (2011) randomly assigned smokers to apply either
mindfulness-based or suppression-based coping skills in re-
sponse to experimentally induced craving, and found that
smokers who applied mindfulness-based strategies reported
reductions in negative affect, depressive symptoms and nico-
tine dependence 1 week later.
Experimental methods for studying craving
Cue-induction methods have been developed to explore the
subjective experience of craving in drug-dependent popula-
tions (Carter and Tiffany, 1999). In these paradigms,
individuals view drug-related stimuli and report on their
craving (which can increase during cue exposure in abstinent
populations). Neuroimaging studies of cue-induced craving
have revealed increases in activity in anterior cingulate
cortex (ACC), ventromedial prefrontal cortex (VMPFC)
and orbitofrontal cortex (OFC), ventral striatum (VS),
precuneus and cuneus, motor control areas in the basal
ganglia and supplementary motor areas (e.g. Due et al.,
2002; David et al., 2005; Lee et al., 2005; McBride et al.,
2006; Smolka et al., 2006; Brody et al., 2007; McClernon
et al., 2008). A recent meta-analysis highlights a central
temporo-parietal junction and ACC, including the subgen-
ual region (sgACC), in nicotine dependence (Ku ¨hn and
Gallinat, 2011). Moreover, Sinha and Li (2007) suggest
that cue-induced activity in medial prefrontal cortex
(PFC), ACC (and posterior cingulate cortex), striatum and
posterior insula predict relapse after a cessation attempt.
Further evidence of the role of cue-induced craving networks
for cigarette smoking comes from pharmacalogical studies.
Bupropion (a prescription medication used to aid in smok-
ing cessation) was found to attenuate cigarette cue-induced
sgACC activity (Brody et al., 2004), and extinction-based
treatment with nicotine replacement therapy attenuates
cue-induced activity in amygdala (McClernon et al., 2007).
Cue-induced craving approaches have recently attracted
criticism due to the limited predictive ability of self-reported
craving in such paradigms (Perkins, 2009; see also Shiffman,
2009; Tiffany, 2009). Nevertheless, much evidence directly
links craving to drug taking (Shiffman et al., 1996, 1997;
Killen and Fortmann, 1997; Catley et al., 2000; O’Connell
et al., 2004; Allen et al., 2008; Epstein 2009, 2010; Preston
et al., 2009). Further, exposure to drug cues has been linked
to relapse following treatment (Shiffman et al., 1986; Bliss
et al., 1989). Finally, as patterns of cue-induced neural ac-
tivity and concomitant self-reported craving have been
increasingly studied in relation to both applied cognitive
strategies and smoking cessation treatments, cue-reactivity
paradigms have greater potential to inform a mechanistic
understanding of nicotine addiction (Brody et al., 2007;
McClernon et al., 2007; Sinha and Li, 2007; Janes et al.,
2010; Chua et al., 2011).
Interestingly, of two prior studies that have examined
mindful attention during a cue-induction paradigm, neither
(Bowen and Marlatt, 2009; Rogojanski et al., 2011).
However, to our knowledge, no cue exposure studies
have examined how mindful attention affects craving in a
Neural pathways linking mindful attention to reduced
craving: regulation vs reduced reactivity
There are two candidate neural pathways that link mindful
attention to reduced craving. First, mindful attention may
recruit ‘regulatory’ regions in a top-down manner. A large
body of work has identified the neural circuitry underlying
cognitive regulation of emotions (Ochsner et al., 2002;
Lieberman, 2007), comprising upregulation of prefrontal re-
gions such as dorsolateral PFC (DLPFC), and down-
regulation of subcortical limbic regions such as amygdala
and VS(Garavan etal.,
Heatherton and Wagner, 2011). There is some indication
that craving can be regulated in this manner as well
(Kober et al., 2010). In support of this regulatory pathway,
we have previously found that individuals high in disposi-
tional mindfulness show increased lateral PFC and decreased
amygdala activity when explicitly instructed to label affective
stimuli (Creswell et al., 2007). Likewise, Farb et al., (2007)
trained participants in an experiential attention (similar to
mindful attention), and found increased activity in executive
regions including DLPFC and ventral lateral PFC (VLPFC).
More recent work by this group likewise found increased
activity in attention-related regions such as dorsal anterior
cingulate and lateral PFC during negative emotion induction
in participants who received 8 weeks of mindfulness training
compared to controls (Farb et al., 2010). Supporting this
view, a recent review of neuroimaging studies of mindfulness
meditation concluded that alterations to top-down process-
ing underlie the beneficial effects of mindfulness for
psychiatric concerns (Chiesa et al., 2010).
Alternatively, however, mindful attention may reduce
‘reactivity’. Specifically, this perspective posits that mindful
attention operates in a more ‘bottom-up’ manner, through
2 of12 SCAN (2011) C.Westbrooketal.
by guest on November 27, 2011
a nonjudgmental stance toward one’s experience. Indeed,
several reviews have pointed out the difference between
(Shapiro et al., 2006; Chambers et al., 2009). Support for
this hypothesis comes from recent work demonstrating
that mindfulness practice improves bottom-up attentional
processes (Jha et al., 2007; Slagter et al., 2007). Recently,
van den Hurk et al. (2010) found that experienced medita-
tors showed decreased intersensory facilitation, directly
supporting the reduced reactivity account. Moreover, several
studies suggest that mindfulness can reduce activity in
craving related limbic and paralimbic regions without any
recruitment of PFC regulatory regions. For example, there is
reduced resting state activity in bilateral amygdala in mind-
ful individuals (Way et al., 2010), and mindful attention has
been found to reduce reactivity in pain-related regions in
experimentally induced pain (Kober et al., 2011; Zeidan
et al., 2011).
The purpose of the present study is to test the ‘regulation’
vs ‘reduced reactivity’ account for how mindful attention
may reduce craving among adult smokers. This study focuses
on tasks conducted prior to treatment delivery in a broader
smoking cessation trial. Specifically, we used a cue-induction
paradigm in meditation-naı ¨ve smokers who had been
abstinent for 12h (biochemically verified). An active ‘regu-
lation’ account predicts that mindful attention acts in a top-
down manner and will recruit lateral PFC regions (previous-
ly associated with regulation), which will modulate activity
in craving-related neural regions (e.g. ACC, VS). This ‘regu-
lation’ account would further predict that regions modulated
by mindful attention will be more strongly functionally con-
nected to lateral PFC regions during mindfulness. In con-
trast, a ‘reduced reactivity’ account posits that mindful
attention acts in bottom-up manner in ways where one
can nonjudgmentally experience craving-related stimuli
without reacting to it, thus directly reducing neural reactivity
in craving-related regions (e.g. sgACC, VS) without con-
comitant activation of PFC. This account further predicts
that regions modulated by mindful attention will be less
strongly connected to other craving-related regions, and
will not be more strongly connected to lateral PFC regions
Participants were 54 right-handed smokers recruited as part
of the Healthier Brains in Treating Smoking (HaBITS) study
(P.I. Tindle), conducted at the University of Pittsburgh.
All participants were adults ?18 years who smoked at least
10 cigarettes per day at baseline and expressed a strong desire
to quit smoking within the following month. Exclusion
criteria included medication that could affect the nervous
system during functional magnetic resonance imaging
(fMRI) scanning (such as ?-blocker, analgesic or any
psychotropic medication), pregnancy, history of brain
injury, cognitive impairment such as dementia, untreated
psychiatric illness such as hallucinations or active depression,
and concomitant substance use. Participants first completed
a telephone screen to determine eligibility, and within
2 weeks conducted an initial visit to deliver informed con-
sent and administer a baseline questionnaire. During the
phone screen and the baseline visit, participants were
screened verbally for psychiatric or substance abuse disorders
and informed that they would be screened for drugs at both
fMRI visits. They also completed the Beck Depression
Inventory II (Beck et al., 1996) as a means of assessing
depressive symptomatology. This study was approved
by both University of Pittsburgh and Carnegie Mellon
Internal Review Boards. All participants provided informed
consent and were reimbursed for their participation.
Participants viewed different types of pictures and were
instructed to think about them in different ways depending
on the instruction they were given. There were three types of
pictures (smoking, e.g. a lit cigarette; neutral, e.g. bookcases;
and aversive, e.g. injured people), preceded by one of three
instructions (Look, Mindfully Attend or Reappraise) for
a total of seven conditions (LookSmoking, LookNeutral,
ReappraiseSmoking and ReappraiseDistressing). Findings
associated with the reappraisal instruction and aversive
stimuli will be described in a separate paper and are not
Neutral and aversive stimuli were selected from the
International Affective Picture System (IAPS; Lang et al.,
1997). Smoking stimuli came from two sources: the
‘International Smoking Image Series’ (ISIS; Gilbert and
Rabinovich, 1999) and images purchased from istockphoto
.com. For the latter, a separate sample of cigarette smokers
viewed the pictures and provided ratings of craving on a
7-point scale; these were averaged and matched to the stan-
dardized ratings provided with the ISIS stimuli. The final
sample consisted of 12 pictures, all of which were >3 on
this scale; mean craving rating was 4.6 out of 7 in the
pilot. Smoking-related images were balanced between the
LookSmoking and MindfulSmoking conditions, such that
average craving score did not differ between the two condi-
tions. Stimuli for smoking and neutral conditions contained
roughly equal numbers of pictures of faces, balanced for
gender and were counterbalanced across the three types of
Procedure and training
Prior to scan day, participants were asked to abstain from
smoking for at least 12h. Abstinence (determined as
<13ppm) was biochemically validated upon arrival at the
scan facility using a carbon monoxide monitor (Bedfont,
Rochester, UK). Additionally, all participants were required
Mindfulness andcravingSCAN (2011)3 of12
by guest on November 27, 2011
to provide a negative a urine screen for cocaine, THC,
methamphetamine, and opiates at the scan site.
Before entering the scanner, a researcher conducted a brief
training session. After explaining the task instructions, the
researcher walked participants through a set of practice
pictures. Participants practiced each instruction [Look,
Mindfully Attend and Reappraise (not reported here)], ver-
balizing their thought processes, and the researcher gave cor-
rective feedback. For the LOOK instruction, participants
were asked simply to relax and view the picture as naturally
as possible. For the MINDFULLY ATTEND condition, par-
ticipants were instructed to actively focus on their responses
to the picture, including thoughts, feelings, memories and
bodily sensations, while maintaining a nonjudgmental
attitude toward those responses. MINDFULLY ATTEND
was not described as a strategy to reduce craving; rather,
researchers emphasized that whatever sensations the partici-
pant experienced?including craving?were to be noticed as
open-mindedly as possible. Instructions explicitly asked par-
ticipants to ‘notice and accept’ their internal experience.
Finally, participants practiced rating their craving and
The task consisted of four 7-min runs in an event-
related design. Within each run, each condition (e.g.
MindfulSmoking) was repeated three times for a total of
21 pictures. The order of conditions was pseudo-randomized
with the constraint that no two consecutive pictures
would be of the same type or instruction.
Each trial was constructed as follows: participants saw
a 2-s instruction slide (LOOK or MINDFULLY ATTEND),
a fixation cross of jittered duration (?1.5s), the stimulus
picture for 8s, two 4-s rating slides (the first for craving
and the second for negative emotion) and finally a 2-s rest
before the next trial began (Figure 1). Participants made
ratings using a data glove with a button for each finger
(Psychology Software Tools, Pittsburgh, PA, USA). Ratings
ranged from 1 (weak) to 5 (strong). Inter-stimulus intervals
were jittered from 0 to 2500ms, distributed exponentially;
the order of jitters was randomized and was the same for all
participants. The task was constructed using E-Prime 2.0
Professional (Psychology Software Tools). Stimuli were
viewed on a 6?900screen projected to a mirror mounted
on the head coil (approximating 1800distance from head).
Fig. 1 Scanning task design. Schematic illustration of a single trial. Each trial began with a 2500-ms long instruction (LOOK or MINDFULLY ATTEND or REAPPRAISE), followed
by a jittered interval. A photo was then presented onscreen for 8000ms (neutral, negative or smoking). Subsequently, participants were asked to rate the strength of their craving
and negative affect. Trials were separated by a 2000-ms intertrial interval.
4 of12SCAN (2011) C.Westbrooketal.
by guest on November 27, 2011
Data acquisition and analysis
All scans were performed at the Brain Imaging Research
Center in Pittsburgh. Data were collected on a Siemens
Allegra 3.0T scanner using a one-channel birdcage head
coil. Participants’ heads were restrained using foam padding
and surgical tape across the forehead. For each participant, a
high-resolution 3-dimensional T1-weighted gradient echo
TE¼2.48ms and flip angle¼88. This scan recorded
224 slices with acquisition matrix 256?256, field of
view¼205mm and voxel size of 0.8?0.8?0.8mm3.
Functional scans were acquired using an echo-planar pulse
sequence with TR¼2s, TE¼28ms and flip angle¼798. Each
pulse recorded 34 oblique axial slices with slice thickness
3.2mm (no gap); field of view was 205mm and matrix size
was 64?64 generating 3.2?3.2?3.2mm3voxels. Four runs
were acquired, each comprising 218 volumes.
Parametric Mapping (SPM8, Wellcome Department of
Cognitive Neurology, Institute of Neurology, London,
UK). The data were field-map corrected, slice-timing cor-
rected, realigned to the mean image of the first functional
run and smoothed with a 4-mm Gaussian kernel (FWHM)
to be in the preferred format for the motion correction
program, ArtRepair (Mazaika et al., 2009). ArtRepair applied
an algorithm to each run to suppress interpolation errors
due to large motion. Then, TRs with excessive fast motion
(>1.5mm/TR) or large global signal variation were repaired
using linear interpolation. This motion corrected data was
then co-registered to the T1structural image, which was
normalized to a standard stereotactic space as defined by
the Montreal Neurological Institute (MNI). Finally, the
normalization parameters were applied to the co-registered
functional images, and smoothed with a 7-mm Gaussian
For each participant, each condition (e.g. MindfulSmoking)
was modeled as an event convolved with the canonical hemo-
dynamic response function. The rest period after instruction
was modeled as an explicit baseline and rests between trials
were left unmodeled. Planned comparisons between condi-
tions of interest were computed in SPM8 as linear contrasts.
The single subject results were then submitted to a
second-level random-effects group analysis. A Monte Carlo
Simulation using AlphaSim implemented in AFNI (Cox,
1996) of our whole-brain volume demonstrated that a cluster
extent cutoff of at least 54 contiguous voxels exceeding a
voxel-wise threshold of P<0.001 provided a multiple-
comparison correction at P<0.05.
To further test our alternative hypotheses regarding the
mechanism by which mindful attention may modulate
craving, additional psychophysiological interaction (PPI)
analyses (Friston et al., 1997) were conducted using the
SPM PPI toolbox. For each subject, volumes of interest
were extracted and used
whole-brain PPI analyses. These were combined into a
as seedsin single-subject
group-level t-test to identify regions exhibiting connectivity
with the seed region.
Several participants (n¼7) were excluded in the imaging
analyses due to excessive head motion, errors with the
response glove, or failure to perform the task correctly,
and thus we present the self-reported craving results on
the full sample (n¼54) and on the neuroimaging subsample
(n¼47). The neuroimaging sample did not differ from the
full sample on demographic or nicotine dependence
variables. Self-reported craving was not associated with
SES, ethnicity, sex, income or grade level (all P’s>0.05).
Psychiatric comorbidity was not formally assessed, but
scores on the Beck Depression Inventory II (Beck et al.,
1996) were on average below the clinical cutoff for depres-
sion (13), suggestive of a low level of depressive mood
comorbidity within our sample. Participant characteristics
are reported in Table 1.
Behavioral analyses: self-reported craving
To determine whether mindful attention reduced self-
reported craving to smoking and neutral images, a repeated
measures analysis of variance (ANOVA) was conducted to
test for significant differences between the three conditions:
passively viewing neutral images (LookNeutral), passively
viewing smoking images (LookSmoking) or mindfully attend-
ing to smoking images (MindfulSmoking). We conducted
these tests first with the entire sample (n¼54). Consistent
with predictions, the repeated measures ANOVA indicated a
Table 1 Participant characteristics
Age [M (s.d.)] (years)
Sex (%), female
Completed high school (%)
Annual income (%)
Beck depression inventory IIascore [M (s.d.)]
Scored ?13 (%)
Nicotine dependence (FTND)b
Cigarettes per day
Years of smoking
Baseline CO level
aBeck et al., 1996.
Mindfulness andcravingSCAN (2011)5 of12
by guest on November 27, 2011
significant difference between conditions [F(2,53)¼14.57,
P<0.001, ?2¼0.36]. Specifically, looking at smoking images
s.d.¼1.07), followed by mindful attention (M¼2.70,
s.d.¼1.01), and looking at neutral images (M¼2.20,
s.d.¼0.90) (Figure 2). We then performed follow-up paired
samples t-tests between conditions. Consistent with predic-
tions, craving was greater for LookSmoking than for
LookNeutral [t(46)¼5.25, P<0.0001] or MindfulSmoking
[t(46)¼?2.09, P<0.05], indicating that mindful attention
helped to reduce self-reported craving. The same pattern
of results was observed in the neuroimaging subsample
(n¼47): the repeated measures ANOVA was significant
[F(2,46)¼22.63, P<0.001, ?2¼0.33], as was the paired t-
test between LookSmoking and LookNeutral [t(46)¼4.93,
P<0.0001]. The paired t-test comparing MindfulSmoking
to LookSmoking was marginally significant [t(46)¼?1.76,
P¼0.09] in this subsample.
A similar pattern emerged for ratings of distress to smok-
ing and neutral images. The repeated measures ANOVA was
significant [F(2,46)¼6.30, P<0.01, ?2¼0.12]. Paired t-tests
revealed that distress ratings were significantly lower in the
LookNeutral condition (M¼1.99, s.d.¼0.85) than in
t(46)¼2.90, P<0.01]. Distress was also decreased in
This pattern of behavioral results suggested that mindful
attention can reduce both craving and concomitant distress
that can accompany viewing smoking stimuli in 12-h
smoking images increases activity in craving-related regions
viewing smoking images activated craving-related neural
regionsin the LookSmoking>LookNeutral
were observed in right precuneus and left medial frontal
gyrus/ventral ACC, as previously reported (Brody et al.,
2004; Sinha and Li, 2007) (details displayed in Table 2).
We first examined whether
Mindfully attending to smoking images reduces craving-related
neural reactivity (MindfulSmoking>LookSmoking).
during the MindfulSmoking condition was contrasted with
the LookSmoking condition to determine which brain areas
showed increased or decreased activity while mindfully
attending to smoking images. In support of the reduced
reactivity account, we found a large region of bilateral
subgenual ACC/VMPFC to show reduced activity in the
MindfulSmoking>LookSmoking contrast (BA 32/24/10, 12,
34, ?4 Z¼?4.77, k¼279) (Figure 3). To test the regulation
account, namely that mindful attention would be associated
Fig. 3 Activations during MindfulSmoking>LookSmoking. Regions modulated by mindful attention. Sagittal (x¼14), coronal (y¼38) and axial slices (z¼?4) views of
sgACC, which was significantly less activated during mindful attention to smoking pictures, compared to passive viewing.
Fig. 2 Differences in self-reported craving. Mean cue-induced craving reported by
condition for the fMRI sample.
Table 2 Activations seen in the LookSmoking>LookNeutral contrast
Anatomic region BASide Cluster
Peak activation (MNI)t
Medial frontal gyrus
2 34 3.58
4.90Fusiform gyrus 37/19 R 111
6 of12SCAN (2011)C.Westbrooketal.
by guest on November 27, 2011
with increased activity in lateral PFC regions, we looked for
regions of relatively increased activity during mindful atten-
tion (in the MindfulSmoking>LookSmoking contrast), but
no areas in a whole-brain analysis showed increased activity.
To determine whether the region of ACC that was
(LookSmoking>LookNeutral), the deactivated region in
MindfulSmoking>LookSmoking was used to generate a
functional mask, which was applied to the LookSmoking>
LookNeutral contrast. Indeed, there was a significant cluster
in left sgACC that was active while viewing smoking images
and which was deactivated during mindful attention (BA
32/10, 8, 46, ?8, k¼53). This region is shown in Figure 4.
In the MindfulSmoking>LookNeutral contrast, however
this region showed neither activation nor deactivation.
Together these results suggest that this region was activated
by passive looking at smoking images (LookSmoking) com-
pared to neutral images (LookNeutral). Mindful attention to
smoking images (MindfulSmoking), however, appeared to
decrease activity back to the level of LookNeutral. This find-
ing supports the reduced reactivity account for mindful
attention, suggesting that mindful attention reduces neural
activation in a known craving-related region (sgACC).
Functional connectivity of sgACC.
lation vs reactivity hypotheses, PPI analysis was conducted
To further test our regu-
to identify neural regions that were functionally connected
with the sgACC cluster that was modulated during
mindful attention (MindfulSmoking). An 8-mm cluster
centered around the peak right sgACC cluster in the
MindfulSmoking>LookSmoking group contrast was func-
tionally defined as a seed region, and used in a group-level
PPI connectivity analysis. Consistent with the reduced
reactivity account, the sgACC cluster showed reduced
functional connectivity with other craving-related regions,
including bilateral insula and VS (Figure 5 and Table 3),
during the MindfulSmoking condition compared to the
LookSmoking condition. To help visualize this interaction,
we provide representative single-subject plots comparing
connectivity of sgACC with two regions (VS and insula)
between the MindfulSmoking and LookSmoking conditions
(Figure 6). This finding suggests that functional coupling in
craving neurocircuitry during passive viewing of smoking
images is reduced during mindful attention. This connectiv-
ity also did not support the regulation account, we found no
lateral PFC regions that were more strongly connected with
sgACC during mindfulness compared to passive viewing.
Mindful attention and reduced reactivity to craving
To our knowledge, the present study is the first to examine
the neural pathways linking mindful attention to reduced
Fig. 4 Region of overlap between MindfulSmoking>LookSmoking contrast and LookSmoking>LookNeutral contrast (BA 32/10, 8, 46, ?8, k¼53).
Mindfulness andcraving SCAN (2011) 7 of12
by guest on November 27, 2011
cigarette craving. Our self-report results provide supporting
evidence that mindful attention can reduce craving even
among smokers who have no formal meditation experience.
Furthermore, our imaging results suggest that mindful
attention decreases craving-related activity in sgACC, and
may reduce functional connectivity between the sgACC
and other craving-related regions.
With the fMRI data, we directly tested two competing
pathways by which mindful-attention may reduce craving.
Our findings lend support to the ‘reduced reactivity’
account, which suggests that mindfulness acts as a
‘bottom-up’ attention to one’s present moment experience
(‘bare attention’, cf. Brown et al., 2007). We found activity in
subgenual ACC increased for smoking images during passive
looking, but decreased activity to smoking images during
mindful attention. This suggests that nonjudgmental atten-
tion to one’s craving-related experience lessens not only
the subjective experience of craving, but also its neural
correlates. Conversely, we found no evidence supporting a
‘regulatory’ pathway in this study as there was no evidence
for increased recruitment of lateral PFC during mindful
attention in this meditation-naı ¨ve sample. The results of
the PPI analysis further support the ‘reduced reactivity’
Fig. 5 Functional connectivity in MindfulSmoking>LookSmoking. Regions that were
functionally connected to sgACC seed during mindful attention to smoking stimuli
compared to passive viewing. Highlighted regions are part of a network previously
associated with craving, including the VS and insula.
Fig. 6 Representative single-subject plots of functional connectivity in VS and insula.
Activity in VS and insula from two different subjects compared to ACC activity in
MindfulSmoking and LookSmoking conditions. Functional coupling between ACC and
insula (A) and VS (B) was greater in the LookSmoking condition than in the
Table 3 Regions showing negative PPI with right vACC during
Anatomic regionBASide Cluster
Peak activation (MNI)t
Middle frontal gyrus
Inferior parietal lobule
8 of12SCAN (2011) C.Westbrooketal.
by guest on November 27, 2011
account. We found that activity in sgACC seed region was
less functionally connected to other craving-related regions
during mindful attention, and not more strongly connected
to any lateral PFC regulatory regions.
Thus far, the ‘reduced reactivity’ account has received
relatively less consideration in the mindfulness literature.
However, we believe this is because most studies examining
the relationship between mindfulness and emotion have
included active self-regulatory tasks. For instance, Creswell
et al. (2007) used an affect-labeling technique, while the
paradigm employed by Farb et al. (2007) involved
reappraisal of words. Both of these tasks could be presumed
to activate regions involved in active self-regulation. On the
other hand, the current work compliments that of Zeidan
et al. (2011) and Kober et al. (2011), in which participants
are asked to notice and accept?but not ‘reappraise’?experi-
ences such as pain. In both cases, mindfulness was associated
with reductions in self-reported pain and pain-related brain
activity, without concomitant increases in lateral-PFC
regions, as predicted by the ‘active regulation’ account.
Consistently, we trained participants to ‘notice and accept’
any feelings, sensations, etc., but not to reappraise, let go of,
or distance themselves from any such perceptions. We feel
that this approach is similar to the deployment of mindful
attention used during meditation, and also encouraged in
mindfulness-based interventions. As other authors have
pointed out (Davidson, 2010; Williams, 2010; Chiesa et al.,
2011), this observation underscores the importance of
specifying how ‘mindfulness’ is defined and experimentally
manipulated in research studies.
Our finding of reduced activity in sgACC during mindful
attention is consistent with what is known about the func-
tional significance of this region to substance use disorders
and craving. Subgenual ACC appears to be directly involved
in craving (Kober et al., 2010; Heatherton and Wagner,
2011) as well as more generally in emotion (Kober et al.,
2008) and in mood psychopathology (Etkin and Wager,
2007; Drevets et al., 2009). The most direct evidence for
the role of sgACC in cue-induced craving has been from
Brody and colleagues, who found in several studies that
this region was more metabolically active in heavy smokers
during cue-induced craving (Brody et al., 2002), but this
neural effect, along with self-reported craving, was blunted
by treatment with buproprion (Brody et al., 2002). The
decrease in sgACC activity we observed during mindful at-
tention also extended to VMPFC, including the medial BA10
region. BA10 is posited to encode the subjective value of
goods, such as an appetitive snack or monetary gamble
(Damasio, 1994; Kable and Glimcher, 2007; Hare et al.,
In addition to decreased activity in sgACC during mindful
attention, we also found decreased functional connectivity
between this region and a network of other craving-related
areas including caudate, VS, premotor cortex and insula. All
of these have been related to cigarette craving and smoking
behavior in prior research (Naqvi and Bechara, 2010; Ku ¨hn
and Gallinat, 2011).VS, in particular, is a known substrate of
reward-related processing (Volkow et al., 2006; Franklin
et al., 2009) and has been associated with dependence on
nicotine as well as alcohol and cocaine (Ku ¨hn and
Gallinat, 2011). Caudate and premotor cortex have both
been reported in prior studies with cue-induced craving,
are associated withseverity
(McClernon et al., 2005, 2007) and are implicated in the
relationship between craving and smoking (Berkman et al.,
2011). These regions are involved in motor planning, and it
has been suggested that responses here reflect associations
between smoking cues and motivated actions learned
through repeated exposure (e.g. the act of smoking;
Smolka et al., 2006). Finally, insula appears to play a par-
ticularly important role in substance use disorders, as
damage to this region disrupts addiction to cigarettes
(Naqvi et al., 2007). It has been hypothesized that this
region may represent the interoceptive effects of craving
(Gray and Critchley, 2007; Garavan, 2010).
Strengths and limitations
Major strengths of the study include the large neuroimaging
sample size, the analytic approach, and the ecological and
face validity of our task and participants. Our sample of
smokers was abstinent and treatment seeking. They were
also naı ¨ve to meditation practices, which is representative
of most of the 46 million US adult smokers, only ?14% of
whom report having used mind body therapies such as
mindfulness (Tindle et al., 2005). Furthermore, our mindful
attention instructions were simple and fast to teach, making
them similar to what a clinician might use in a brief
intervention setting. Finally, the greatest strength of our
study was the use of fMRI to elucidate the regulatory vs
reduced reactivity mechanisms linking mindfulness to
reduced cue-induced craving.
We did not collect information on psychiatric comorbid-
ity within our sample, with the exception of the BDI-II (Beck
et al., 1996). We feel that our decision not to exclude
based on psychiatric comorbidity rendered our sample
more generalizable to smokers in the USA. Specifically,
current estimates indicate that 44% of all cigarettes sold in
the US are smoked by individuals with diagnosed psychi-
atric disorders (Lasser et al., 2000). However, having
more information about the psychiatric profile of our par-
ticipants by way of a diagnostic interview would have
provided more information about the psychiatric comor-
bidities in our sample, which is a limitation of the present
Given our design, one potential limitation is the possibil-
ity of an expectancy effect caused by our mindful attention
instructions (i.e. our participants may have expected their
craving to decrease, and therefore reported likewise in spite
of their actual experiences). However, we think this is
unlikely because we intentionally did not describe mindful
Mindfulness andcravingSCAN (2011)9 of12
by guest on November 27, 2011
attention as a craving–reduction strategy. Additionally,
evidence from prior research indicates that self-reporting
of affective changes in similar study designs is not
linked to measures of social desirability (Ochsner et al.,
2002). If anything, participants might expect the task to
‘increase’ their craving, following the general expectation
that directing attention toward a given experience will in-
crease the strength of that experience (Lieberman et al.,
We were limited in the number of conditions we were able
to assess while participants underwent neuroimaging. For
example, we did not include a condition exploring how
mindful attention affects neural and self-reported craving
response to neutral images. Previous research suggests that
mindful attention may increase self-reported positive affect
to neutral stimuli (Arch and Craske, 2006), suggesting the
possibility (to be assessed in future studies) that mindful
attention may affect craving responses to neutral images in
smokers. It is possible that carry-over neural activity may
have contributed to the present results (Siegle et al., 2002),
although we attempted to minimize this possibility through
counterbalancing the order of task trials across participants.
Finally, the present work describes the benefits of a brief
mindful attentional state on craving, and the extent to
which the observed effects may change or evolve over time
is unclear. A randomized controlled trial of mindfulness in
comparison to a rigorous control therapy would be required
to fully elucidate the effects of mindfulness training inter-
ventions on neural and self-reported craving in smoking
Overall, the present work suggests that mindful attention can
reduce craving, and does so by decreasing activity and func-
tional connectivity in regions of the brain known to subserve
cigarette craving. Our work provides a potential neural
mechanism for how mindfulness-based treatments improve
smoking cessation (Bowen and Marlatt, 2009; Brewer et al.,
in press), and suggests that the mechanism of action may be
via reduced reactivity rather than active self-regulation via
lateral PFC. Thus, the present results suggest that mindful
attention might be qualitatively distinct compared to cogni-
tive regulation strategies that have been studied thus far in
smokers (e.g. Kober et al., 2010). Although more research is
needed to explore these neural craving pathways in mindful-
ness training randomized controlled trials, the present work
corroborates Buddhist accounts of mindfulness and the
hindrance of craving (Fronsdal, 2005), suggesting that mind-
ful attention can reduce self-reported and neural reactivity to
Conflict of Interest
Allen, S.S., Bade, T., Hatsukami, D., Center, B. (2008). Craving, withdrawal,
and smoking urges on days immediately prior to smoking relapse.
Nicotine and Tobacco Research, 10(1), 35–45.
Altner, N. (2002). Mindfulness practice and smoking cessation: The Essen
hospital smoking cessation study (EASY). Journal for Meditation and
Meditation Research, 1, 9–18.
Arch, J.J., Craske, M.G. (2006). Mechanisms of mindfulness: emotion
regulation following a focused breathing induction. Behaviour Research
and Therapy, 44, 1849–58.
Beck, A.T., Steer, R.A., Ball, R., Ranieri, W.F. (1996). Comparison of Beck
Depression Inventories-IA and –II in psychiatric outpatients. Journal of
Personality Assessment, 67(3), 588–97.
Berkman, E.T., Falk, E.B., Lieberman, M.D. (2011). In the trenches of
real-world self-control: neural correlates of breaking the link between
craving and smoking. Psychological Science, 22(4), 498–506.
Bishop, S.R., Lau, M., Shapiro, S., et al. (2004). Mindfulness: A proposed
operational definition. Clinical Psychology: Science and Practice, 11,
Bliss, R.E., Garvey, A.J., Heinold, J.W., Hitchcock, J.L. (1989). The
influence of situation and coping on relapse crisis outcomes after
smoking cessation. Journal of Consulting and Clinical Psychology, 57(3),
Bowen, S., Marlatt, A. (2009). Surfing the urge: Brief mindfulness-based
intervention for college student smokers. Psychology of Addictive
Behaviors, 23(4), 666–71.
Brewer, J.A., Bowen, S., Smith, J.T., Marlatt, G.A., Potenza, M.N. (2010).
Mindfulness-based treatments for co-occurring depression and substance
use disorders: what can we learn from the brain? Addiction, 105(10),
Brewer, J.A., Mallik, S., Babuscio, T.A., et al. (2011). Mindfulness
Training for smoking cessation: results from a randomized controlled
trial. Drug and Alcohol Dependence, 119, 72–80.
Brody, A.L., Mandelkern, M.A., London, E.D., et al. (2002). Brain metabolic
changes during cigarette craving. Archives of General Psychiatry, 59,
Brody, A.L., Mandelkern, M.A., Lee, G., et al. (2004). Attenuation of
cue-induced cigarette craving and anterior cingulate cortex activation
in bupropion-treated smokers: a preliminary study. Psychiatry Research,
Brody, A.L., Mandelkern, M.A., Olmstead, R.E., et al. (2007). Neural
substrates of resisting craving during cigarette cue exposure. Biological
Psychiatry, 62(6), 642–51.
Brown, K.W., Ryan, R.M., Creswell, J.D. (2007). Mindfulness: theoretical
foundations and evidence for its salutary effects. Psychological Inquiry,
Catley, D., O’Connell, K.A., Shiffman, S. (2000). Absentminded lapses
during smoking cessation. Psychology of Addictive Behaviors, 14(1), 73–6.
Carter, B.L., Tiffany, S.T. (1999). Meta-analysis of cue-reactivity in
addiction research. Addiction, 94(3), 327–40.
Center for Disease Control and Prevention (2008). Cigarette Smoking
Among Adults – United States 2007. Morbidity and Mortality Weekly
Report, 57(45), 1221–6.
Chambers, R., Gullone, E., Allen, N.B. (2009). Mindful emotion regulation:
An integrative review. Clinical Psychology Review, 29, 560–72.
Chiesa, A., Serretti, A. (2011). Mindfulness based cognitive therapy for
psychiatric disorders: A systematic review and meta-analysis. Psychiatry
Research, 187(3), 441–53.
Chiesa, A., Brambilla, P., Serretti, A. (2010). Functional neural correlates
of mindfulness meditations in comparison to psychotherapy, pharmaco-
therapy and placebo effect: is there a link? Acta Neuropsychiatrica, 22(3),
Chiesa, A., Calati, R., Serretti, A. (2011). Does mindfulness training improve
cognitive abilities? A systematic review of neuropsychological findings.
Clinical Psychology Review, 31(3), 449–64.
10 of12 SCAN (2011)C.Westbrooketal.
by guest on November 27, 2011
Chua, H.F., Ho, S.S., Jasinska, A.J., et al. (2011). Self-related neural response
to tailored smoking-cessation messages predicts quitting. Nature
Neuroscience, 14, 426–27.
Cox, R.W. (1996). AFNI: Software for analysis and visualization of
functional magnetic resonance neuroimages. Computers and Biomedical
Research, 29, 162–73.
Creswell, J.D., Way, B.M., Eisenberger, N.I., Lieberman, M.D. (2007).
Neural Correlates of Dispositional Mindfulness During Affect Labeling.
Psychosomatic Medicine, 69(6), 560–5.
Damasio, A.R. (1994). Descartes’ Error: Emotion, Reason and the Human
Brain. New York: Avon Books, Inc.
David, S.P., Munafo `, M.R., Johansen-Berg, J., et al. (2005). Ventral
striatum/nucleus accumbens activation to smoking-related pictorial
cues in smokers and non-smokers: a functional magnetic resonance
imaging study. Biological Psychiatry, 58(6), 488–94.
Davidson, R.J. (2010). Empirical explorations of mindfulness: conceptual
and methodological conundrums. Emotion, 10(1), 8–11.
Davis, J.M., Fleming, M.F., Bonus, K.A., Baker, T.B. (2007). A pilot study on
mindfulness based stress reduction for smokers. Complementary and
Alternative Medicine, 7, 2.
Drevets, W.C., Savitz, J., Trimble, M. (2009). The subgenual anterior
cingulate cortex in mood disorders. CNS Spectrums, 13(8), 663–81.
Due, D., Huettel, S., Hall, W., Rubin, D. (2002). Activation in mesolimbic
and visuospatial neural circuits elicited by smoking cues: evidence from
functional magnetic resonance imaging. American Journal of Psychiatry,
Epstein, D.H., Willner-Reid, J., Vahabzadeh, M., Mezghanni, M., Lin, J.-L.,
Preston, K.L. (2009). Real-time electronic-diary reports of cue exposure
and mood in the hours before cocaine and heroin craving and use.
Archives of General Psychiatry, 66(1), 88–94.
Epstein, D.H., Marrone, G.F., Heishman, S.J., Schmittner, J., Preston, K.L.
(2010). Tobacco, cocaine, and heroin: Craving and use during daily life.
Addictive Behaviors, 35(4), 318–24.
Etkin, A., Wager, T.D. (2007). Functional neuroimaging of anxiety: a
meta-analysis of emotional processing in PTSD, social anxiety disorder,
and specific phobia. American Journal of Psychiatry, 164, 1476–88.
Fagerstrom, K.O. (1978). Measuring degree of physical dependence to
tobacco smoking with reference to individualization of treatment.
Addictive Behaviors, 3(34), 235–41.
Farb, N.A.S., Segal, Z.V., Mayberg, H., et al. (2007). Attending to the
present: mindfulness meditation reveals distinct neural modes of
self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313–22.
Farb, N.A.S., Anderson, A.K., Mayberg, H., Bean, J., McKeon, D., Segal, Z.V.
(2010). Minding one’s emotions: mindfulness training alters the neural
expression of sadness. Emotion, 10(1), 25–33.
Fjorback, L.O., Arendt, M., Ørnbøl, E., Fink, P., Walach, H. (2011).
Mindfulness-based stress reduction and mindfulness-based cognitive
therapy?a systematic review of randomized controlled trials. Acta
Psychiatrica Scandinavica, 124(2), 102–19.
Friston, K.J., Buechel, C., Fink, G.R., Morris, J., Rolls, E., Dolan, R.J. (1997).
Psychophysiological and modulatory interactions in neuroimaging.
Neuroimage, 6, 218–29.
Fronsdal, G. (2005). The Dhammapada: A New Translation of the Buddhist
Classic With Annotations. Boston, MA: Shambhala Publications, Inc.
Garavan, H., Pankiewicz, J., Bloom, A., et al. (2000). Cue-induced cocaine
craving: Neuroanatomical specificity for drug users and drug stimuli.
American Journal of Psychiatry, 157, 1789–98.
Garavan, H. (2010). Insula and drug cravings. Brain Structure and Function,
Gilbert, D.G., Rabinovich, N.E. (1999). International Smoking Image Series
(With Neutral Counterparts), version 1.2. Carbondale, Integrative
Neuroscience Laboratory, Department of Psychology, Southern Illinois
Gilbert, D.G., McClernon, F.J., Rabinovich, N.E., et al. (1999). EEG,
physiology, and task-related mood fail to resolve across 31 days of
smoking abstinence: relations to depressive traits, nicotine exposure,
and dependence. Experimental and Clinical Psychopharmagology, 7(4),
Gilbert, D.G., McClernon, F.J., Rabinovich, N.E., et al. (2002). Mood
disturbance fails to resolve across 31 days of cigarette abstinence in
women. Journal of Consulting and Clinical Psychology, 70(1), 142–52.
Gray, M.A., Critchley, H.D. (2007). Interoceptive basis to craving. Neuron,
Franklin, T.R., Lohoff, F.W., Wang, Z., et al. (2009). DAT genotype
modulates brain and behavioural responses elicited by cigarette cues.
Neuropsychopharmacology, 34, 717–28.
Hare., T.A., O’Doherty, J., Camerer, C.F., Schultz, W., Rangel, A. (2008).
Dissociating the role of the orbitofrontal cortex and the striatum in the
computation of goal values and prediction errors. Journal of Neuroscience,
Heatherton, T.F. (2011). Neuroscience of self and self-regulation. Annual
Review of Psychology, 62, 363–90.
Heatherton, T.F., Wagner, D.D. (2011). Cognitive neuroscience of
self-regulation. Trends in Cognitive Sciences, 15(3), 132–9.
Hughes, J.R., Keely, J., Naud, S. (2004). Shape of the relapse curve and
long-term abstinence among untreated smokers. Addiction, 99(1), 29–38.
Jain, S., Shapiro, S.L., Swanick, S., et al. (2007). A randomized controlled
trial of mindfulness meditation versus relaxation training: effects on
distress, positive states of mind, rumination, and distraction. Annals of
Behavioral Medicine, 33(1), 11–21.
Janes, A.C., Pizzagalli, D.A., Richardt, S., et al. (2010). Brain reactivity to
smoking cues prior to smoking cessation predicts ability to maintain
tobacco abstinence. Biological Psychiatry, 67(8), 722–9.
Jha, A.P., Krompiger, J., Baime, M.J. (2007). Mindfulness training modifies
subsystems of attention. Cognitive, Affective, and Behavioral Neuroscience,
Kable, J.W., Glimcher, P.W. (2007). The neural correlates of subjective value
during intertemporal choice. Nature Neuroscience, 10, 1625–33.
Killen, J.D., Fortmann, S.P. (1997). Craving is associated with smoking
relapse: findings from three prospective studies. Experimental and
Clinical Psychopharmacology, 5(2), 137–42.
Kober, H., Barrett, L.F., Joseph, J., Bliss-Moreau, E., Lindquist, K.,
Wager, T.D. (2008). Functional grouping and cortical-subcortical
interactions and emotion: a meta-analysis of neuroimaging studies.
Neuroimage, 42(2), 998–1031.
Kober, H., Mende-Siedlecki, P., Kross, E.F., Weber, J., Mischel, W.,
Hart, C.L., Ochsner, K.N. (2010). Prefrontal-striatal pathway underlies
cognitive regulation of craving. Proceedings of the National Academy of
Sciences, 107(33), 14811–6.
Kober, H., Mende-Siedlecki, P., Buhle, J., et al. (2011). Mindfulness
Modulates Pain and Negative Emotion: Evidence from Self Report and
fMRI. Garrison, NY: Mind and Life Summer Research Institute.
Ku ¨hn, S., Gallinat, J. (2011). Common biology of craving across legal and
illegal drugs?a quantitative meta-analysis of cue-reactivity for brain
response. European Journal of Neuroscience, 33, 1318–26.
Lang, P.J., Bradley, M.M., Cuthbert, B.N. (1997). International Affective
Gainesville, FL: NIMH Center for the Study of Emotion and Attention,
University of Florida.
McCormick, D., Bor, D.H. (2000). Smoking and mental illness: a
population-based prevalence study. Journal of the American Medical
Association, 284(20), 2606–10.
Lee, J.-H., Lim, Y., Wiederhold, B.K., Graham, S.J. (2005). A functional
magnetic resonance imaging (fMRI) study of cue-induced smoking
Biofeedback, 30, 195–204.
Lieberman, M.D. (2007). Social cognitive neuroscience: A review of core
processes. Annual Review of Psychology, 58, 259–289.
Lieberman, M.D., Inagaki, T.K., Tabibnia, G., Crockett, M.J. (2011).
Subjective responses to emotional stimuli during labeling, reappraisal,
and distraction. Emotion, 11(3), 468–80.
Mindfulness andcravingSCAN (2011) 11of12
by guest on November 27, 2011
Mazaika, P., Hoeft, F., Glover, G.H., Reiss, A.L. (2009). Methods and
Software for fMRI Analysis for Clinical Subjects. San Francisco, CA:
Human Brain Mapping.
McBride, D., Barrett, S.P., Kelly, J.T., Aw, A., Dagher, A. (2006). Effects of
expectancy and abstinence of the neural response to smoking cues
in cigarette smokers: an fMRI study. Neuropsychopharmacology, 31,
McClernon,F.J., Hiott,F.B., Huettel,
Abstinence-induced changes in self-report craving correlate with event-
related fMRI responses to smoking cues. Neuropsychopharmacology,
McClernon, F.J., Hiott, F.B., Liu, J., Salley, A.N., Behm, F.M., Rose, J.E.
(2007). Selectively reduced responses to smoking cues in amygdala fol-
lowing extinction-based smoking cessations: results of a preliminary
functional magnetic resonance imaging study. Addiction Biology,
McClernon, F.J., Kozink, R.V., Rose, J.E. (2008). Individual differences in
nicotine dependence, withdrawal symptoms, and sex predict transient
fMRI-BOLD responses to smoking cues. Neuropsychopharmacology, 33,
Naqvi, N.H., Bechara, A. (2010). The insula and drug addiction: an intero-
ceptive view of pleasure, urges, and decision-making. Brain Structure and
Function, 214(5–6), 435–50.
Naqvi, N.H., Rudrauf, D., Damasio, H., Bechara, A. (2007). Damage
to the insula disrupts addiction to cigarette smoking. Science, 315,
Ochsner, K.N., Bunge, S.A., Gross, J.J., Gabrieli, J.D. (2002). Rethinking
feelings: an FMRI study of the cognitive regulation of emotion. Journal
of Cognitive Neuroscience, 14, 1215–29.
O’Connell, K.A., Schwartz, J.E., Gerkovich, M.M., Marjorie, B., Shiffman, S.
(2004). Playful and rebellious states vs. negative affect in explaining the
occurrence of temptations and lapses during smoking cessation. Nicotine
and Tobacco Research, 6(4), 661–674.
Perkins, K.A. (2009). Does smoking cue-induced craving tell us
anything important about nicotine dependence? Addiction, 104(10),
Piasecki, T.M., Fiore, M.C., Baker, T.B. (1998). Profiles of discouragement:
two studies of variability in the time course of smoking withdrawal
symptoms. Journal of Abnormal Psychology, 107(2), 238–51.
Preston, K.L., Vahabzadeh, M., Schmittner, J., Lin, J.-L., Gorelick, D.A.,
Epstein, D.H. (2009). Cocaine craving and use during daily life.
Psychopharmacology, 207(2), 291–301.
Rogojanski, J., Vettese, L.C., Antony, M.M. (2011). Coping with cigarette
cravings: comparison of suppression versus mindfulness-based strategies.
Mindfulness, 2(1), 14–26.
Shapiro, S.L., Carlson, L.E., Astin, J.A. (2006). Mechanisms of mindfulness.
Journal of Clinical Psychology, 62, 373–86.
Siegle, G., Steinhauer, S.R., Thase, M.E., Stenger, V.A., Carter, C.S. (2002).
Can’t shake that feeling: Event-related fMRI assessment of sustained
amygdala activity in response to emotional information in depressed
individuals. Biological Psychiatry, 51(9), 693–707.
Shiffman, S. (2009). Responses to smoking cues are relevant to smoking and
relapse. Addiction, 104(10), 1617–22.
S.A., Rose, J.E. (2005).
Shiffman, S., Shumaker, S.A., Abrams, D.B., et al. (1986). Models of
smoking relapse. Health Psychology, 5(Suppl)13–27.
Shiffman, S., Paty, J.A., Gnys, M., Kassel, J.A., Hickcox, M. (1996). First
lapses to smoking: within-subjects analysis of real-time reports. Journal of
Consulting and Clinical Psychology, 64(2), 366–79.
Shiffman, S., Engberg, J.B., Paty, J.A., et al. (1997). A day at a time:
predicting smoking lapse from daily urge. Journal of Abnormal
Psychology, 106(1), 104–16.
Sinha, R., Li, C.-S.R. (2007). Imaging stress- and cue-induced drug and
alcohol craving: association with relapse and clinical implications. Drug
and Alcohol Review, 26(1), 25–31.
Slagter, H.A., Lutz, A., Greischar, L.L., et al. (2007). Mental training affects
distribution of limited brain resources. PLoS Biology, 5(6), e138.
Smolka, M.N., Bu ¨hler, M., Klein, S., et al. (2006). Severity of nicotine
dependence modulates cue-induced brain activity in regions involved
in motor preparation and imagery. Psychopharmacology, 184(3–4),
Tiffany, S. (2009). The continuing conundrum of craving. Addiction,
Tindle, H.A., David, R.B., Phillips, R.S., Eisenberg, D.M. (2005).
Trends in use of complementary and alternative medicine by US
adults: 1997-2002. Alternative Therapies in Health and Research, 11(1),
United States Public Health Service (2008). Treating Tobacco Use and
Dependence: 2008 Update. U. S. P. H. S. Department of Health and
Human Services. Rockville, MD, U.S.
van den Hurk, P.A.M., Janssen, B.H., Giommi, F., Barendregt, H.P.,
Gielen, S.C. (2010). Mindfulness meditation associated with alterations
in bottom-up processing: Psychophysiological evidence for reduced
reactivity. International Journal of Psychophysiology, 78, 151–7.
Vidrine, J.I., Businelle, M.S., Cinciripini, P., et al. (2009). Associations of
Substance Abuse, 30(4), 318–27.
Volkow, N.D., Wang, G.J., Telang, F., et al. (2006). Cocaine cues and dopa-
mine in dorsal striatum: Mechanism of craving in cocaine addiction.
Journal of Neuroscience, 26(24), 6583–8.
Way, B., Creswell, J.D., Eisenberger, N.I., Lieberman, M.D. (2010).
Dispositional mindfulness and depressive symptomatology: correlations
with limbic and self-referential neural activity during rest. Emotion, 10(1),
Williams, J.M.G. (2010). Mindfulness and psychological process. Emotion,
Witkiewitz, K., Marlatt, G.A., Walker, D. (2005). Mindfulness-based relapse
prevention for alcohol and substance use disorders. Journal of Cognitive
Psychotherapy, 19(3), 211–28.
Witkiewitz, K., Bowen, S. (2010). Depression, craving, and substance use
following a randomized trial of mindfulness-based relapse prevention.
Journal of Consulting and Clinical Psychology, 78(3), 362–74.
Zeidan, F., Martucci, K.T., Kraft, R.A., Gordon, N.S., McHaffie, J.G.,
Coghill, R.C. (2011). Brain mechanisms supporting the modulation
of pain by mindfulness meditation. Journal of Neuroscience, 31(14),
12 of12 SCAN (2011)C.Westbrooketal.
by guest on November 27, 2011