Supplemental Information
Hippocampal and Insular Response to Smoking-Related Environments: Neuroimaging Evidence
for Drug Context Effects in Nicotine Dependence
F. Joseph McClernon, Cynthia A. Conklin, Rachel V. Kozink, R. Alison Adcock, Maggie M. Sweitzer, Merideth A. Addicott, Yinghui Chou, Nan-kuei Chen, Matthew B. Hallyburton, Anthony M. DeVito
Appendix: Supplemental Methods
Table S1: Demographics
Table S2: Whole Brain Analyses Results
Figure S1: Examples of Personal Smoking and Nonsmoking Environments
Figure S2: In-scanner Craving Scores
Figure S3: ROI Locations and Results
Table S3: ROI Effect Sizes
Figure S4: ICA Components
Supplemental References
1
Appendix: Supplemental Methods
Additional information regarding the acquisition and nature of personal environment cues. Using methods validated in a
previous study (1) each participant was interviewed to determine four to five specific environments in which they frequently smoke
(i.e. smoke at least 7 out of 10 times they are there) or abstain (smoke less than 3 out of 10 times there) and then were trained to
acquire images using a digital camera. As in previous studies, four pictures of each environment (2 approaching the environment, 2
from within the environment) were acquired. Upon returning the camera an experimenter reviewed and edited, as necessary, each
picture to remove proximal smoking cues (e.g. ashtrays, packs of cigarettes) and any people. Participants took between 7 to 21 days to
complete the picture-taking phase.
Additional information on scanning parameters. Imaging was conducted using a 3T General Electric MR750 scanner equipped
with 50 mT/m gradients. Prior to imaging, the anterior and posterior commissures were identified in the midsagittal slice of a localizer
series. Blood oxygen level dependent (BOLD) imaging were acquired using gradient-recalled inward spiral pulse imaging with Kspace trajectory (34 slices, TR = 1500 ms, TE = 30 ms, FOV = 24.0 cm, matrix = 64x64, flip angle = 60°, slice thickness = 4 mm,
resulting in 3.75x3.75x4 mm voxels). This sequence increases signal to noise ratio and reduces dropout artifacts at the tissue-air
interface (2). High resolution anatomical imaging was conducted at the end of the fMRI session using a high resolution 3-dimensional
fast spoiled gradient recalled echo anatomical sequence with a 1 mm isotropic voxel size.
Additional information on participant eligibility. A total of 67 individuals were screened for the study, of which 50 met eligibility
criteria; 10 individuals were either withdrawn, dropped out, or lost to contact prior to the scanning session. At screening, serious
health problems were assessed by a self-report questionnaire which included items asking about illnesses, operations, hospitalizations,
serious injuries/accidents, heritable diseases, and medications.
Additional information on data preprocessing, quality control and censoring. Nine subjects were excluded from imaging analysis
due to excessive motion (i.e. motion in any direction exceeded voxel dimension length). In addition, one subject was excluded for
excessive drowsiness during presentation of cue-reactivity task while in the scanner. Two participants were excluded from the
analyses of lab based measures due to noncompliance during the cue-exposure session (i.e. spoke on cell phone during task; n=2) and
one participant dropped from the study prior to completing the cue-exposure sessions (n=1).
Additional information on outlier detection. Prior to conducting the correlational analyses, data were evaluated for outliers using
studentized residuals and Cook’s D values. In addition, a robust regression with M estimation was run to identify outliers. Within the
data set used for the correlation analyses, one individual was identified as an outlier consistently across all outlier detection methods
and was excluded from the analysis.
Additional information on Independent Component Analysis. We used the probabilistic independent component analysis (PICA)
with multi-session temporal concatenation approach, implemented in MELODIC tool of the FSL (www.fmrib.ox.ac.uk/fsl), to
decompose task-related, multiple 4D data sets into 20 independent components (IC) (Beckmann and Smith, 2004). Data
preprocessing consisted of 1) motion correction, 2) slice time correction, 3) removal of non-brain structures, 4) spatial smoothing (5
mm FWHM Gaussian kernel), 5) registration to the MNI 152 standard space, 6) resampling data to 4 mm isotropic resolution, 7)
regressing out time course profiles of the white matter and cerebrospinal fluid regions, and 8) high-pass filtering with a frequency cutoff at 150 s. In inspecting the maps associated with each of the 20 components, we identified one—IC 7—that overlapped both with
our bilateral insula (centered on +/-38,10,6) and posterior hippocampus ROIs (see Figure S4).
We then used FSL’s dual regression to calculate the subject specific orthogonal timecourses and spatial maps for each independent
component (IC) (Beckmann et al., 2009). We then extracted the average connectivity values from the central voxel for each of the four
ROIs for each individual for IC 7. The extracted values, expressed as a Fisher’s z transformed r-value, represent the connectivity
between each ROI and IC 7 for each participant. The relationship between these values and smoking behavior were then assessed with
Pearson correlation analysis (see Figure 5).
Reference: Beckmann, C. F., Mackay, C. E., Filippini, N., and Smith, S. M. (2009). Group comparison of resting-state FMRI data
using multi-subject ICA and dual regression. Neuroimage 47, S148.
Table S1. Demographics.
Demographic information is displayed for the full sample, the sample of participants used in the analyses of behavioral data, and the
sample of participants who provided useable imaging data.
2
Full Sample
(n=40)
Age
Cigarettes/Day
FTND
Female
Race
White
Black
Asian
Other
Behavior SubSample (n=37)
23 (59.0)
Mean (SD)
35.5 (11.3)
14.9 (6.6)
4.4 (1.9)
n (%)
23 (62.1)
14 (35.0)
20 (50.0)
5 (12.5)
1(2.5)
13 (35.1)
18 (48.6)
5 (13.5)
1(2.7)
35.0 (11.1)
14.8 (6.5)
4.2 (2.0)
fMRI SubSample (n=30)
35.4 (11.5)
14.9 (6.7)
4.1 (1.9)
17 (56.7)
13 (43.3)
12 (40.0)
5 (16.7)
0 (0.0)
3
Table S2. Whole Brain Analyses Results.
Brain regions identified for each of the planned whole-brain analyses: 1) Personal Smoking Environments > Personal Nonsmoking
Environments (PSE>PNE) 2) Personal Smoking Environments > Standard Smoking Environments, relative to nonsmoking
environments (Personal > Standard), and 3) Smoking Environments > Proximal Smoking Cues, relative to nonsmoking environments
and cues (Environment > Proximal). Cluster size, brain region, Z-value and coordinates are provided for each peak voxel. S>N =
Smoking > Nonsmoking.
Cluster Size
Hemisphere
Region
Z
Personal Smoking Environments > Personal Nonsmoking Environments
17764 Left
Superior Parietal L.
Left
Precuneous
Right
SMA
Right
Posterior Cingulate G.
1423 Right
Cerebellum
860 Right
Planum Temporale
Right
Supramarginal G.
Right
Superior Temporal G.
Right
Middle Temporal G.
541 Right
Frontal Operculum/Insula
Right
Insula
Right
WM/Putamen
Right
Caudate
Right
Insula
445 Right
Supramarginal G.
441 Left
Cerebellum
x
y
z
4.87
4.77
4.68
4.58
4.32
4.15
3.96
3.94
3.75
3.97
3.6
3.58
3.54
3.54
4.22
3.85
-8
-10
4
14
24
56
56
62
48
34
42
26
16
36
64
-8
-54
-70
-6
-34
-50
-30
-40
-28
-28
16
8
10
12
8
-24
-38
72
46
68
44
-50
16
6
10
-4
10
-4
12
20
-4
44
-44
Personal (Smoking >Nonsmoking) > Standard (Smoking>Nonsmoking)
565 Left
Putamen
Left
Insula
Left
WM
3.84
3.82
3.25
-30
-36
-22
-4
-2
0
10
-4
24
Environment (Smoking>Nonsmoking) > Proximal (Smoking >Nonsmoking)
2641 Right
Lateral Occipital C.
1551 Left
Lateral Occipital C.
482 Right
Planum Temporale
Right
WM
434 Right
Lateral Occipital C.
Right
Superior Parietal L.
Right
Precuneous
5
5.11
4.48
3.24
4.33
3.81
3.67
40
-40
56
42
18
10
10
-64
-68
-30
-26
-56
-50
-56
10
8
14
-4
72
72
50
4
Figure S1. Examples of Personal Smoking and Nonsmoking Environments.
Stimuli employed in the study consisted of smoking and nonsmoking proximal, standard environment and personal environment cues.
Proximal cues depicted smoking (e.g. cigarette in an ashtray) and nonsmoking (e.g. pencils, notepads) objects. Standard environment
cues were those developed and validated in prior research (1, 3) and depicted settings associated with either a high (e.g. bus stop) or
low probability (e.g. school) of smoking. These environments were devoid of proximal smoking cues and people and were shown in
previous studies to result in robust cue-provoked craving (1, 3). All participants viewed the same set of standard environment cues.
Examples of personal smoking and nonsmoking environment cues acquired by each participant using the protocol described above are
shown.
Nonsmoking
Smoking
Example Personal Environment Cues
5
Figure S2: In-scanner Craving Scores.
Craving was evaluated following each stimulus block in the scanner with the question “While focusing on the place/object, I craved a
cigarette”. Participants responded with a bi-manual response pad on a scale of 1 (Do not agree) to 8 (Strongly agree). GLMM on mean
in-scanner craving scores indicated significant main effects of CATEGORY (F2,140=24.84, p<.0001) and CUE (F1,140=499.45,
p<.0001) and a CATEGORY x CUE interaction (F2,140=5.88, p=.0035). Post hoc paired t-tests revealed higher craving ratings in
response to smoking versus nonsmoking cues for each cue category (all p’s<.001). In examining, cue-reactivity (craving in response to
smoking minus nonsmoking cues), a main effect of CATEGORY (F2,54=7.53, p=0.0013) was observed for the change in craving in
response to viewing smoking (relative to nonsmoking) cues. Post hoc paired t-tests indicate cue-reactivity in the personal
environments condition was similar to the proximal cue condition (t=-1.23, p=0.224), but greater than that observed in the standard
environment condition (t=2.74, p=0.008).
6
Figure S3. ROI Locations and Results.
Table displays (1) ROI name, (2) ROIs viewed in two planes, (3) significant statistical findings and (4) graphs displaying findings
separately for left and right hemisphere. P values are presented for all statistical tests. Tests were considered significant at α = .05 for
hippocampal ROIS, all other ROIs were tested at α= .05/10 = .005. Legend as displayed in Figure S2. See Table S3 for effect sizes.
Name
ROI
Left Statistics
(α=.05)
Left % Signal
Change
Right Statistics
(α=.05)
anterior
hippocampus
(aHPC)
CAT: F=4.0,
p=.0187
CUE: F=7.1,
p=.008
CAT: F=7.8,
p<.0005
CUE: F=4.1,
p<.043
posterior
hippocampus
(pHPC)
CAT: F=30.7,
p<.0001
CUE: F=7.8,
p=.0054
CAT: F=27.3,
p<.0001 CUE:
F=3.9, p=0.048
CATxCUE:
F=3.7, p=.024
Name
ROI
Left Statistics
(α=.005)
Left % Signal
Change
Right Statistics
(α=.005)
amygdala
(AMG)
CUE: F=8.3,
p=.0042
insula (INS)
CAT: F=12.7,
p<.0001
CUE: F=11.4,
p=.0008
CATxCUE:
F=6.9, p=.0011
CAT: F=21.3,
p<.0001
CATxCUE:
F=5.34, p=.005
CAT: F=23.2,
p<.0001
CUE: F=8.4,
p=.0039
CAT: F=15.4,
p<.0001
precuneus
(pc)
Right % Signal
Change
CAT: F=8.7,
p=.0002
ventral
striatum
(vSTR)
medial
prefrontal
cortex
(mPFC)
Right % Signal
Change
CAT: F=122.1,
p<.0001
CAT: F=129.4,
p<.0001
7
Table S3: ROI Effect Sizes
Effect sizes (Cohen’s d) are shown for smoking compared to nonsmoking stimuli for proximal cues as well as standard and personal
environments for each of the ROIs in Figure S3.
LEFT
REGION
Prox
Stnd
RIGHT
Prsnl
Prox
Stnd
Prsnl
anterior hippocampus (aHPC)
posterior hippocampus (pHPC)
ventral striatum (vSTR)
0.23
0.13
0.29
0.28
0.24
0.26
0.40
0.46
0.40
0.31
0.25
0.02
0.19
0.15
0.28
0.13
0.55
0.59
amygdala (AMG)
insula (INS)
0.26
0.19
0.16
0.01
0.59
0.90
0.28
0.11
0.14
0.26
0.40
0.59
medial prefrontal cortex (mPFC)
0.45
0.27
0.33
0.18
0.18
0.34
precuneus (pc)
0.20
0.38
0.14
0.10
0.29
0.12
8
Figure S 4. ICA Components
z = -7
8
23
38
53
1
2
3
4
5
6
9
7
8
9
10
11
12
10
13
14
15
16
17
18
11
19
20
12
References
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Conklin CA, Perkins KA, Robin N, McClernon FJ, Salkeld RP. Bringing the real world into the laboratory: personal smoking
and nonsmoking environments. Drug Alcohol Depend. 2010;111(1-2):58-63.
2.
Guo H, Song AW. Single-shot spiral image acquisition with embedded z-shimming for susceptibility signal recovery. J Magn
Reson Imaging. 2003;18(3):389-95.
3.
Conklin CA, Robin N, Perkins KA, Salkeld RP, McClernon FJ. Proximal versus distal cues to smoke: the effects of
environments on smokers' cue-reactivity. Exp Clin Psychopharmacol. 2008;16(3):207-14.
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