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CANNABIS CUE REACTIVITY Supplemental Materials 1

Supplemental Methods

Participants

Participants were recruited via flyers posted on campus and university mass email

announcements. In addition to self-reported cannabis use, participants were screened for a

history of head trauma, neurological disorder, or the use of prescription medication (with the

exception of oral contraceptives or medical cannabis). Individuals experiencing any of these

characteristics were excluded from the study.

Self-Report Measures

Substance Use.

Cannabis Dependence. Cannabis dependence symptoms within the past 12 months were

assessed using the Marijuana Dependence Scale (MDS) (Stephens et al., 2000), a 10-item scale

based on DSM-IV criteria for dependence that were converted to a paper and pencil measure.

Individuals responded ‘yes’ or ‘no’ to each dependence item (e.g., “When I smoked marijuana, I

often smoked more or for longer periods of time than I intended”; “I need to smoke more

marijuana to achieve the same ‘high’; α = .84).

Problems Associated with Cannabis Use. The Marijuana Problems Index (MPI; Johnson &

White, 1989) is a 29-item questionnaire asking how many times an event or experience occurred

as a result of smoking cannabis with the past 12 months in a number of domains, including

school (e.g., “Not able to do your homework or study for a test”), social relations (e.g., “Had a

fight, argument, or bad feelings with a friend”), and personal issues (e.g., “Noticed a change in

your personality”). These items were assessed using a 5-point likert scale (ranging from “Never”

to “More than 10 times”; α = .94).

Cannabis, Tobacco, and Alcohol Use. Self-reported cannabis use during the past 30 days was


assessed using the Time-Line Follow Back (TLFB; Sobell & Sobell, 1992). The TLFB is a

calendar assisted structured interview in which participants were asked to indicate over the past

30 days the quantity of cannabis, tobacco, alcohol, other illicit drugs, and prescription drugs used

for recreational purposes.1 Cannabis and alcohol use were assessed in total number of days

participants reported using each substance in the 30 days prior to their laboratory session.

Tobacco use was assessed in total number of cigarettes participants reported smoking in the 30

days prior to their laboratory session.

Cannabis Craving. Cannabis craving was assessed using an 8-item measure adapted from the

Alcohol Urge Questionnaire (Bohn et al., 1995). Participants rated the extent to which they were

craving cannabis “right now” (e.g., “ All I want to do now is have a hit”) on a 7-point likert scale

ranging from “Strongly Disagree” to “Strongly Agree” (α = .90).

Personality. The Temperament and Character Inventory (TCI; Cloninger, 1993) was used to

assess novelty seeking, harm avoidance, and reward dependence. Novelty seeking was assessed

with 35 items (e.g., “I often try new things just for fun or thrills, even if most people think it is a

waste of time.”; α = .86). Harm avoidance was assessed with 33 items (e.g., “Usually I am more

worried than most people that something might go wrong in the future.”; α = .92). Finally,

reward dependence was assessed with 30 items (e.g., “I am more sentimental than most people.”;

α = .88), All items were assessed on a 5-point scale ranging from “Definitely False” to

“Definitely True”.

Psychopathology.

Childhood and Current ADHD. Participants completed the Self-Report form of the ADHD

Current and Childhood Symptom Scales (Barkley & Murphy, 1998). Participants were first

asked to indicate how often each of the 18 DSM-IV ADHD symptoms is currently true on a 4-


point scale with the anchors “Not at All”, “Once in a While”, “Often” and “Very Often” (α

= .82), then rated the extent to which each symptom was true when she or he was a child 5-12

years of age (α = .91). The higher of the two ratings was used to assess lifetime severity of the

symptom (α = .89; e.g., Willcutt & Bidwell, 2011).

Internalizing/Externalizing Problems. The Achenbach System of Empirically Based

Assessment (Adult Self-Report Form, ASRF; Achenbach, 2009) was used to assess internalizing

and externalizing problems. Internalizing was assessed with 39 items that address three types of

problems within the self: (1) anxiousness/depression (e.g., lonely, sad), (2) withdrawal (e.g.,

rather be alone, not liked, secretive), and (3) somatic complaints (e.g., dizzy, aches, eye

problems). Externalizing was assessed with 32 items. Three items referring to substance use and

law breaking were excluded from the ASRF Externalizing variable to prevent overlap with

smoking group characteristics (i.e., uses drugs, gets drunk, trouble with the law). The remaining

items address three aspects of conflict with other people and social mores: (1) aggressive

behavior (e.g., argues, blames, is mean), (2) rule-breaking behavior (e.g., breaks rules, lacks

guilt, lies/cheats), and (3) intrusiveness (e.g., brags, demands attention, teases). All items were

assessed on a 3-point scale ranging from “Not True” to “Very True” (Externalizing α = .84;

Internalizing α = .86).

Cue Reactivity Task

Cannabis cue reactivity was assessed with a modified visual oddball paradigm (e.g., Ito et

al., 1998) in which participants saw frequently presented neutral pictures (e.g., towel, rolling pin,

electrical outlet) and equally infrequent cannabis and exercise pictures (6.67% probability). Each

trial consisted of five images displayed sequentially for 1000 ms each with an interstimulus

interval (ISI) of 1000 ms. In order to establish the neutral context, at least four of the pictures


within each set of five were neutral. The remaining fifth picture is referred to as the target

picture. On one third of the trials, the target picture was a cannabis picture. On another third of

the trials, the target picture was an exercise picture, and in the remaining trials, the fifth picture

was another neutral image. Within each set of five stimuli ERPs were recorded during the

presentation of a single cannabis, exercise, or neutral target stimulus, which randomly appeared

in either the third, fourth, or fifth position in a sequence (cf., Ito et al., 1998). Thus, on trials in

which all pictures were neutral, one was designated as the target trial. Because neutral context

images are so much more frequent, only ERPs to target trials were analyzed to equate the

number of cannabis, exercise, and neutral trials.

Participants’ task was to categorize each image as related to either cannabis or exercise,

via a right button press, or other, via a left button press. Participants were instructed to wait until

the image was no longer on the screen to respond to minimize movement artifacts. In cases

where the participant’s response exceeded the 1000 ms ISI, the ISI equaled the time it took the

participant to respond. After a series of five pictures the word “Pause” was displayed on screen

until participants pressed a green button to begin the next trial.

Our selection of cannabis images was guided by past ERP studies of cue-reactivity (Littel

& Franken, 2007) and focused on images of the actual substance, related paraphernalia, and

actual use of the substance. Cues were sourced from high-resolution images from the internet

and consisted of a person smoking a joint, several joints and a pipe filled with cannabis, a joint

being rolled, a person smoking a pipe, a bong, and a person smoking a bong. Exercise pictures

were selected to match the cannabis ones in terms of number of people shown and the degree to

which the activity (actually exercising) versus the objects associated with it were shown. The

exercise images consisted of a weight lifting system, a weight being held, a treadmill, a person


doing sit-ups, and two images of a person lifting a weight. Neutral pictures consisted of 39

pictures from the International Affective Picture System (IAPS; Lang et al., 1993) with a mean

normative valence rating of 5.01 and a mean arousal rating of 3.05 (both on a 1 – 9 scale). The

specific images selected were images 2575, 2840, 2880, 5395, 5731, 6150, 7000, 7002, 7004,

7010, 7020, 7030, 7034, 7050, 7080, 7090, 7100, 7130, 7150, 7160, 7170, 7175, 7180, 7182,

7184, 7185, 7187, 7207, 7211, 7217, 7233, 7235, 7491, 7500, 7590, 7640, 7705, 7710, and 7830.

All images were presented in the center of a computer monitor approximately 90 cm away from

the participant.

Auditory Oddball Task

Before starting the experimental trials, participants engaged in 30 practice trials identical

to the main task, but with a higher proportion of oddball tones compared to white noise tones.

Participants heard infrequent task-relevant tones (oddballs: 1000 Hz, 60 dBs for 70 ms),

infrequent task-irrelevant white noise (novel sound: 55 dBs for 100 ms) and a frequent context

tone (standard: 500 Hz, 60 dBs for 70 ms). The duration of the white noise burst was longer

compared to the other tones to make it distinguishable. All tones were presented over

headphones in a pseudorandom order, such that oddball and white noise tones were never

presented sequentially (i.e., there was always at least one standard tone between them).

As with the Cue Reactivity task, trials involving the standard tone are much more

numerous. In order to equate the number of content trials analyzed to the less frequent oddballs

and novel tones, we randomly designated 50 standard tones for analysis. ERP data from these

designated context tones were analyzed for all participants. There was a 1300 ms ISI between all

stimuli.

Electrophysiology Recording


The electroencephalogram (EEG) was recorded from 64 tin electrodes fixed in a stretch-

lycra cap (Electro-cap International, Easton, OH) and placed according to standard locations

(American Encephalographic Society, 1991). All electrodes were referenced online to the left

mastoid. Vertical and horizontal electrooculographic activity was recorded with electrodes

placed above and below the left eye and approximately 2 cm outside the outer canthus of each

eye. A ground electrode was seated along the frontal midline. All signals were amplified with a

Neuroscan SynampsRT amplifier (Compumedics-Neuroscan, El Paso, TX), filtered online at .1

to 30 Hz, and sampled at 1000 Hz. Impedance was kept below 10KΩ. Offline, data were

reference to an average of both mastoids. Ocular artifacts (i.e., blinks) were next corrected from

the EEG signal with a regression-based procedure (Semlitsch et al., 1986). Epochs 1100 ms in

length were created, starting 100 before stimulus onset, then data were corrected to the mean

voltage of the 100 ms prestimulus baseline. Trials with remaining artifact were removed, then

data were filtered with a 9 Hz low pass filter. EEG data from correct trials were then averaged

according to participant, electrode, and stimulus conditions. After dropping trials that were

incorrect or contained excessive artifact, analyses were based on an average of 32 trials (SD =

3.42) per participant per condition in the Cue Reactivity task and 43 trials (SD = 6.19) in the

Auditory Oddball task. In total, 5 participants were dropped from analyses due to excessive

artifact (Cue Reactivity, n = 3; Auditory Oddball, n = 2). All participants had minimum of 15

trials/condition in both tasks.

The P300 was scored by following a frequently-used convention of identifying a time

window in which the P300 occurs based on the morphology of the waveform in the grand

average (i.e., average across all conditions and subjects) (e.g., Cacioppo et al., 1993; Ito et al.,

1998; Ito & Cacioppo, 2000; Schupp et al., 2006). For the Cue Reactivity Task, the P300 was


scored as the mean amplitude and latency of the largest positive potential between 450 and

500ms following stimulus onset. Similarly, the P300 in the Auditory Oddball Task was scored as

the mean amplitude and latency of the largest positive potential between 270 and 400ms

following stimulus onset.

Supplemental Results

Cue Reactivity

Behavioral Accuracy. Participants were performing a relatively simple task, so we

expected high accuracy in all conditions. Consistent with this, average response accuracy was

98%. We tested for possible smoking group differences with a 3 (Smoking Group: Never,

Infrequent, Frequent) x 3 (Picture Type: Cannabis, Exercise, Neutral) x 2 (Gender) mixed

factorial analysis with repeated measures on Picture Type. The only significant effect was a

Picture Type main effect, F(2, 694)=346.64, p<.001. Although accuracy differences were quite

small, participants were more accurate to neutral images (M =1.00) compared to both exercise

(M =0.99; t(352)=7.00, p<.001) and cannabis image (M =0.96; t(352)=34.00, p<.001). Accuracy

was also significantly greater for exercise compared to cannabis images, t(352)=27.00, p<.001.

No other effects were significant, Fs<2.05, ps>.08.

P300. In addition the Picture main effect, Smoking Group main effect, and Smoking

Group x Picture interaction reported in the main text, the ANCOVA on P300 amplitude revealed

a main effect of Gender, F(1, 340)=11.42, p=.001, and Picture x Gender interaction, F(2,

680)=19.65, p<.001. Women had significantly larger P300s to exercise (M=10.89 V) and

cannabis images (M=12.50 V) compared to men (Me= 8.57 V, t(352)=4.83 V, p<.001;

Mc=10.54 V, t(352)=3.59, p<.001). However, P300 amplitudes did not differ to neutral images

as a function of gender, t(352)=.23, p=.82


The only significant effect involving a covariate was the Picture x ADHD interaction,

F(2, 680)=5.61, p<.01. Inspection of this interaction indicated that individuals higher on ADHD

showed smaller P300 amplitudes to cannabis images.

We also conducted an additional focused test of the cannabis cue reactivity effect by just

examining the difference in P300s to the equally rare cannabis and exercise pictures. This was

tested in in an ANCOVA in which the dependent variable was a contrast score that represented

the difference in P300s to cannabis versus exercise. We obtained the expected Smoking Group

main effect, F(2, 343)=3.75, p=.02. Both frequent (Mdifference=2.29 V) and infrequent

(Mdifference=2.11 V) cannabis users showed relatively larger P300s to cannabis than exercise

images as compared to never users (Mdifference=0.96 V, t(352)=2.23, p<.03), t(352)=2.57, p<.02).

Frequent and infrequent users did not differ in the magnitude of their cue reactivity in this

analysis, t(352)=.36, p=.72.

As noted in the main text, simple effects tests of the significant Smoking Group x Picture

interaction showed that P300s to neutral images were significant larger among frequent than

infrequent users. We had no reason to expect this effect and while we think cue-reactivity is most

appropriately represented by comparing P300 amplitudes to the equally infrequent cannabis and

exercise images, we nevertheless conducted ancillary analyses to ensure that cannabis use was

also related to cue-reactivity as represented by the difference in P300s to cannabis as compared

to neutral images. Specifically, we examined the correlation between our continuous measure of

cannabis use (number of days cannabis was used in the past 30 days) and a cannabis versus

neutral contrast score computed as the difference in P300 amplitude between cannabis and

neutral images. We obtained a significant correlation, r=.13, p<.02. This relation shows that even


when the expectedly larger P300s to neutral images among frequent users is taken into account,

relatively greater P300s to cannabis images is associated with use.

Finally, because the ASRF items can also be scored as reflecting eight syndromes of

anxiety/depression, withdrawal, somatic complaints, thought problems, attention problems,

aggressive behavior, rule-breaking behavior, and intrusiveness, we repeated our ANCOVA on

P300 amplitude using the syndrome scales instead of the internalizing and externalizing scores.

This analysis revealed similar Smoking Group x Picture effects as reported in the main text.

Early Posterior Negativity (EPN). The P300 analyses show clear cue reactivity effects

manifesting 450-650 ms after stimulus onset. A recent review Littel et al. (2012) argued for the

importance of examining whether cue reactivity effects are seen earlier in processing. We

assessed this by examining responses in the EPN, a component typically occurring 200-300 ms

after stimulus onset that is sensitive to motivationally relevant stimuli (Foti et al., 2009; Schupp

et al., 2006).

Reduction of EPN data was identical to that for the P300 analyses except the data were

filtered offline with a 30 Hz low pass filter. Previous research indicates that the EPN is largest at

occipital electrodes sites, occurring roughly 200 – 300 ms after stimulus onset (Dunning et al.,

2011) so we quantified the EPN as the mean amplitude between 220 and 320 ms after stimulus

onset at electrode sites O1, Oz, and O2.

We analyzed EPN data using a 3 (Smoking Group) x 3 (Picture) x 2 (Gender) x 3

(Electrode: O1, Oz, O2) mixed factorial analysis with repeated measures on the Picture Type and

Electrode factors. EPN waveforms are shown in Figure S1. Results show a main effect of

Picture, F(2, 694)=26.73, p<.001, indicating that the EPN was significantly larger (i.e., more

negative) to cannabis images (M=3.80 V) compared to both exercise (M=4.92 V; t(352) 6.95,


p<.001) and neutral images (M=4.27 V; t(352)=2.96, p<.01). Additionally, neutral images

elicited larger EPNs than exercise images, t(352)=4.61, p<.001. These results are somewhat

similar to the P300 results in showing generally greater motivational responses to cannabis cues.

However, this effect was not moderated by smoking group as the Smoking Group x Picture e

interaction was not significant, F(4, 694)=1.39, p=.24. This indicates that motivational responses

to cannabis cues did not vary as a function of smoking history at this earlier point in processing.

There were three additional a-theoretical effects in the EPN analysis. The first was the

main effect of Electrode, F(2, 694)=180.96, p<.001, indicating the EPN was significantly larger

at Oz (M=3.08 V) compared to both O1 (M=4.50 V; t(352)=13.76, p<.001) and O2 (M=5.41

V; t(352)=22.12, p<.001). EPN amplitudes at O1 were also larger than at O2, (t(352)=5.88,

p<.001). There was also a Picture x Gender interaction, F(2, 694)=7.28, p=.001, and Picture x

Gender x Electrode interaction, F(4, 1388)=3.62, p<.02. Follow up analyses revealed that for

cannabis and neutral images, EPN amplitudes were larger for women (Mc=3.15 V, Mn=3.74

V) compared to men (Mc=4.46 V, Mn=4.80 V; tc (352)=2.39, p=.02; tn (352)=1.99, p=.05).

This effect manifested at all electrodes for cannabis images, but only at O1 and Oz for neutral

pictures.

Auditory Oddball

Behavioral Accuracy. Out of the 353 participants included in the Cue Reactivity

analyses, 5 participants were dropped from the auditory oddball analysis due to equipment

malfunction (n=3) and excessive artifact (n=2); thus, auditory oddball analyses are based on data

from 348 participants. As expected, overall accuracy was high (M=99%). A 3 (Smoking Group)

x 3 (Tone: Oddball, White Noise, Standard) x Gender mixed factorial analysis with repeated

measures on the Tone factor revealed a main effect of Tone, F(2, 684)=132.19, p<.001, such that


participants were most accurate to standard tones (M=1.00) compared to both the oddball

(M=0.99; t(347)=8.00, p<.001) and white noise (M=0.97; t(347)=13.50, p<.001). Participants

were also significantly more accurate to oddball tones compared to white noise, t(347)=9.50,

p<.001. No other behavioral effects were significant, Fs<1.95, ps>.10.

P300. In addition to the Tone Type main effect reported in the main text, this analysis

revealed a Tone x Gender interaction, F(2, 684)=8.78, p<.001, qualified by a Smoking Group x

Tone x Gender interaction, F(4, 684)=2.51, p<.05. Follow up analyses of this interaction

revealed that women never users exhibited significantly larger P300 amplitudes to White Noise

tones (M=14.29 V) compared to men (M=10.60 V; t(347)=3.95, p<.001). Additionally,

women infrequent users showed smaller P300 amplitudes to standard tones (M=-0.09 V)

compared to men (M=0.79 V; t(347)=2.16, p<.05). Importantly, results did not show a

significant Smoking Group x Tone interaction, F(4, 684)=0.33, p=.86, further indicating that the

use differences to cannabis cues in the Cue Reactivity Task are specific to cannabis use and not

generalized cue reactivity. We also ran this analysis controlling for the covariates used in the

Visual Oddball P300 analysis (i.e., Novelty Seeking, Alcohol and Tobacco use, Internalizing,

Externalizing, and Lifetime ADHD), which yielded similar results.


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Figure Caption

Figure S1. Early posterior negativity waveforms elicited by neutral, exercise, and cannabis cues

as a function of cannabis use group at Oz. Stimulus onset occurred at 0 ms. Three dimensional

presentation of topographic distribution of ERP activity in the EPN window from the back right

and back of the head.


1 On average, participants’ reported illicit (M = 0.42 days/month, SD = 1.15) and prescription (M = .49 days/month,

SD = 1.72) drug use was low.

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