A Preliminary Investigation of Two Repetitive Transcranial Magnetic Stimulation (rTMS) Strategies to Treat Cannabis Use Disorder
Phase: NA
Conditions: Cannabis Use Disorder
Sponsor: Stanford University

 
 
 
 
A Preliminary Investigation of Two Repetitive Transcranial 
Magnetic Stimulation (rTMS) Strategies to Treat Cannabis 
Use Disorder 
Study Protocol and Statistical Analysis Plan 
NCT05720312 
August 28, 2023 

 
 
 
1 of  26 
Refine rTMSCUD_Protocol_v1.1 28 August 2023 
 
 
 
PD Name: Gregory Sahlem 
 
A Pilot Trial Refining the Protocol for the Use of Repetitive Transcranial Magnetic Stimulation (rTMS) 
for the Treatment of Cannabis Use Disorder: Testing Two Different Treatment Locations and 
NeuroImaging Based Targeting. 
TABLE OF CONTENTS –  
Page 2 Specific AIMS 
Page 3-4 Background and Significance 
Page 4 Preliminary Studies 
Page 4-9 Research Design and Methods 
Page 9-17 Protection of Human Subjects 
Page 17-26 References and Literature citations 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Protocol 

 
 
 
2 of  26 
SPECIFIC AIMS___________________________________________________________________________ 
     Cannabis Use Disorder (CUD) is a prevalent condition1 with substantial negative impacts on social, 
occupational, and health domains2. Further, ongoing legalization efforts may make CUD more common and 
impactful in the future3. Behavioral treatments for CUD have yielded moderate treatment effects but are not 
100% effective4, and despite some promising medications in the pipeline, a clearly effective pharmacologic 
agent has yet to emerge5–12. As such new treatment paradigms are needed for CUD.  
     Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that is 
FDA-approved / cleared as a treatment for Major Depressive Disorder (MDD)13–15, Obsessive Compulsive 
Disorder (OCD)16, and Smoking Cessation (SC)17. There has been much study in the potential application of 
varying rTMS paradigms in the treatment of addictive disorders18–21—with relatively consistent clinical-
behavioral effects seen when serial sessions are applied to the left dorsolateral prefrontal cortex (L-DLPFC)22–
26. Based on this ongoing promising literature across addictive disorders our group has been developing L-
DLPFC-applied rTMS as a treatment for CUD27,28. We recently completed a phase-2 trial which recruited N=72 
treatment interested participants with CUD (mean age 30.2±9.9SD, 37.5% women) and applied 20-sessions of 
either active or sham rTMS as adjunctive therapy to a three session Motivational Enhancement Therapy 
behavioral intervention. Our preliminary results suggest a potential therapeutic effect, however prior to 
launching a larger phase-3 study we hope to optimize our paradigm, and also determine the feasibility and 
preliminary efficacy of a second promising rTMS treatment target—the ventromedial prefrontal cortex 
(vmPFC)—in hopes of seeing suggestions that treatment can be personalized. 
     Our phase-2 trial found suggestions of clinical efficacy, with those participants treated with active rTMS 
reporting more weeks of abstinence from cannabis following the delivery of 16-study treatments (14.86% 
active; 9.05% sham; RR 1.64 [0.97,2.79]) and numerically fewer days per week of cannabis use in the final two 
weeks of follow-up (3.67±3.09SD and 3.59±2.75SD-active; 4.67±2.50SD and 5.00±2.45SD-sham; Cohen’s D 
at week 4 = 0.54; among completers) than those treated with sham-rTMS. Our paradigm, however, was 
designed to maximize feasibility and participant retention, given high levels of drop-out in early pilot work28. 
Specifically, we delivered only a total of 20-study treatments, which is a dose known to have efficacy in MDD—
but lower efficacy than 36-treatments. We additionally elected to deliver treatments using a scalp-based 
targeting method29 that is quickly completed, but may not target the relevant neural circuits as precisely as 
functionally derived targets which use functional magnetic resonance imaging (fMRI)18,30. Finally, there is 
recent data suggesting that there may be relevant variability between subjects based on which deep-brain 
structures are responsive to pictures of drug-cues (namely the ventral or dorsal striatum)31–33, and that a 
different treatment target may be more effective at engaging the differentially dysfunctional circuitry34,35. 
     In this proposed pilot trial, we subsequently hope to build on our promising results suggesting that a 
relatively low dose of simply-targeted L-DLPFC applied rTMS may help treatment seeking participants with 
CUD reduce their cannabis use—by testing the feasibility and preliminary efficacy of three refinements. The 
three refinements include: a) increasing the number of study-treatments delivered from 20 to 36; b) testing the 
ability of an fMRI task we developed (based on prior similar tasks36,37) to generate functional rTMS targets 
(which we will use for more precise targeting at two established treatment sites); and c) the preliminary 
comparative efficacy of applying rTMS to a second commonly targeted cortical site/circuit which may have 
efficacy in a different sub-type of addictions. In order to do so, we plan on recruiting N=30 treatment-interested 
participants with ≥moderate CUD and randomizing them to receive 36-study-treatments of rTMS applied to 
either the L-DLPFC or vmPFC, delivered over 6-9 weeks (two-study-treatments per visit, 18-study-treatment 
visits, two or three visits per week), and following them for 6-weeks. We will perform fMRI before and after 
study-treatment and attempt to use the pre-treatment fMRI to derive a functional rTMS target. 
Aim-1 will determine the feasibility and acceptability of delivering our expanded study-treatment paradigm. We 
will quantify acceptibility26, and consider our paradigm feasible if we retain >60% of our randomized sample. 
Aim-2 will determine if our fMRI task is able to reliably generate a functional rTMS treatment target within the 
broader L-DLPFC and vmPFC structures. We will consider our task effective if the generated center of mass 
falls within the broader structures that we have targeted in >2/3rds of scans. We will use anatomically-derived 
targets18,29 as backup should one or more participants not have a clear fMRI center of mass to target. 
Aim-3 will determine the preliminary efficacy of the above study-treatment paradigm. We will determine 
whether participants treated in this pilot trial have a comparable number of weeks of abstinence and days per 
week of cannabis use following the delivery of 14-study-treatments, and qualitatively look at whether more 
dorsal or ventral striatal cue-reactivity distinguishes those who respond to L-DLPFC or vmPFC rTMS. We will 
also compare the results of this trial to the results of our previous Phase-2 trial. 

 
 
 
3 of  26 
1. BACKGROUND AND SIGNIFICANCE_________________________________________________________ 
     Cannabis Use Disorder (CUD) is a common condition with well documented adverse social, occupational, 
and health effects2,38,39. The incidence of frequent cannabis use and CUD may be increasing in the United 
States and worldwide3,40 with increasing legalization and a decrease in perceived risk as potential reasons for 
this increase41. The frequency of daily cannabis use has also continually increased in prevalence in recent 
years in the United States—potentially further increasing the risk of an increased incidence of CUD in the 
future 42. Of note, the number of people seeking treatment for CUD appears to be increasing43, and 
subsequently there is likely to be an increase in demand for effective treatment in the future. Though there are 
promising pharmacologic treatments in the pipeline5,6,10,44, no medication has distinguished itself as clearly 
effective in the treatment of CUD, and though consistently demonstrating a beneficial effect, studies testing 
behavioral therapies for CUD have resulted in only moderate effects to date4. As such, there remains a need to 
develop new therapeutics for CUD.  
     Repetitive transcranial magnetic stimulation (rTMS) works via the principles of magnetic induction and long 
term potentiation / depression45–47, and is capable of focally altering circuit function in the brain34,35,48. Trials 
applying serial applications of rTMS in a variety of neuropsychiatric conditions have demonstrated that by 
varying the location of stimulation and the treatment paradigm it is possible to derive a therapeutic benefit in 
different illnesses, and rTMS is now approved / cleared by the US Food and Drug Administration for the 
treatment of Major Depressive Disorder (MDD)15,49,50, Obsessive Compulsive Disorder (OCD)16, and Smoking 
Cessation (SC)17. In line with the several indications for treatment with rTMS, there has been increasing 
promise that rTMS may become a therapeutic option across addictions including CUD21. Studies across 
addiction have suggested rTMS has the potential to effect behavioral aspects of addiction25,30,51,52, engage its 
neurocircuitry48,53,54, and when serial sessions of rTMS are applied have therapeutic effects. Several 
neurocircuit targets have emerged for study in therapeutic trials, with early promising results for the left 
dorsolateral prefrontal cortex (L-DLPFC)22, the ventromedial prefrontal cortex (vmPFC)18, the dorsomedial 
prefrontal cortex19, and the anterior-insula / inferior frontal gyrus17—though not all trials have resulted in a 
beneficial effect20.   
     One of the most commonly targeted cortical sites has been the L-DLPFC, which is also the most common 
target for MDD. Our group has since adapted the general anti-depressant treatment paradigm to treat CUD, 
first in non-treatment seeking participants with CUD55, and then participants with CUD who were interested in 
reducing their use of cannabis28. Our early findings suggested that a single-session of rTMS could be feasibly 
applied to participants with CUD, was generally well tolerated, and may reduce the purposefulness aspect of 
craving55. In subsequent study, we found that it was infeasible to deliver daily sessions of rTMS for two-weeks 
in treatment interested participants with CUD, but that those participants who did attend daily sessions 
reported less craving and reduced cannabis use that persisted 4-weeks after receiving rTMS28.  
     The findings from our preliminary work as well as therapeutic studies applying 
rTMS to the DLPFC of other addictive disorders21,22,26 suggest therapeutic promise 
for CUD, though the need for a treatment-paradigm  that differs from daily 
applications. Both data56,57 and clinical experience suggest it is possible to get a 
therapeutic effect from rTMS even if treatments are delivered less frequently then 
daily, and so we completed a Phase 2 trial that randomized N=72 (mean age 
30.2±9.9SD, 37.5% women) treatment-interested participants with ≥moderate CUD 
(8.5±1.5SD CUD criteria, 6.6±1.1SD days per week of use, 4.3±3.3SD use sessions 
per day) to active or sham rTMS, where study-treatments were delivered twice 
weekly for five-weeks. On each treatment-visit we delivered two study-treatments in 
the presence of cannabis-cues58, separated by 30-minutes, for a total of 20 sessions 
of rTMS. We also delivered a three-session Motivational Enhancement Therapy 
(MET) behavioral intervention59. We reasoned that this lower participant burden 
paradigm maximized feasibility while delivering the minimum amount of rTMS 
needed to produce a therapeutic effect. In order to maximize future potential 
translation we used the original rTMS for depression treatment paradigm (10Hz, scalp-based measurement), 
and used a low-intensity behavioral platform. We found that the paradigm was feasible with 51 of the 72 
participants completing study-treatment (28 of 37 active, 23 of 35 sham), and that those treated with active 
rTMS had more numeric weeks of abstinence beginning after the delivery of 16-study treatments (14.86% 
active; 9.05% sham; RR 1.64 [0.97,2.79]; missing data coded as non-abstinent) and numerically fewer days 
per week of cannabis use in the final two weeks of follow-up (3.67±3.09SD and 3.59±2.75SD-active; 

 
 
 
4 of  26 
4.67±2.50SD and 5.00±2.45SD-sham; Cohen’s D at week 4 = 0.54; among completers) than those treated with 
sham-rTMS.                  
     Despite these promising findings, there are three clearly identifiable refinements that might result in a larger 
effect but need to be piloted before replacing aspects of the current paradigm. First, the rTMS for MDD 
literature consistently suggests that there is a dose-response effect for number of delivered treatments and 
remission rates. Early studies specifically found that 15-20 treatments of rTMS13,60 are sufficient for an effect 
(remission rates of 14-18%), but that 30-treatments are more effective (24-30%)13,61. A similar result is found in 
the single addiction trial that explores dose26, which showed that increasing the number of treatment sessions 
has a large effect-size on abstinence. Next, though scalp-based measurement targeting for rTMS is a valid 
method, and represents the clinical-backbone of targeting, an increasing body of literature suggests that 
anatomical and functional regions do not fully overlap62, that treatment response in depression may be 
mediated by engaging sub-sections of the DLPFC connected to a deep brain structure(the sgACC)63, and more 
precise targeting of this deep brain structure using functional Magnetic Resonance Imaging (fMRI) may result 
in a larger antidepressant effect64–66. Recent studies in addictions using task-based fMRI have also shown that 
rTMS delivered closer to an fMRI center of mass has a larger effect than when delivered further from the 
functional center of mass (personal correspondence related to18,30). We subsequently developed an fMRI task, 
based on these two paradigms36,37, both of which appear to produce a strong signal in the L-DLPFC and 
vmPFC in response to drug cues (when one is thinking about the long-term and short-term consequences of 
substance use), that may provide a more precise target for rTMS. Finally, several studies have suggested that 
there is a progression in addiction from reward based drug use (mediated by incentive salience circuitry) to 
habit based drug use (mediated by habit circuitry) and can be distinguished by a shift from ventral striatal 
reactivity to drug cues (primary deep reward center of the brain) to dorsal striatal reactivity (primary deep habit 
center of the brain)31–33. TMS delivered to the L-DLPFC and vmPFC differentially engage the dorsal and ventral 
striatum respectively34,35, and preferential ventral striatal reactivity may distinguish those who have an effect 
from vmPFC stimulation67. We subsequently plan on building upon our paradigm by increasing the number of 
treatment’s from 20 to 36, attempting to use an fMRI task for functional targeting, and treating at two 
established treatment targets to determine if there is a signal in the striatal reactivity that distinguishes which 
might be more effective for a given individual. 
 
2. Innovation and Public Health Impact: CUD impacts more than 14-million Americans with well-known 
consequences, and few treatment options1. As described above, rTMS has promise as a treatment for CUD, 
and further refinement, as proposed in this pilot trial may further its development to a point where a phase-3 
efficacy trial is warranted. As such, completing the proposed trial has the potential to further develop a new 
treatment for CUD, and open up a new treatment to the 14-million Americans it might benefit. 
PRELIMINARY STUDIES___________________________________________________________________ 
The study team is well experienced in rTMS28,55, fMRI54, and treatment trials6 in addictive disorders. As 
mentioned in the body of the background and significance section, the study team has led the three trials 
applying L-DLPFC rTMS for cannabis use disorder28,55,68, which have served as the justification for the present 
pilot trial. 
 
3. RESEARCH DESIGN AND METHODS (including data analysis) __________________________________ 
General Overview: The primary aims of this pilot investigation are to: a) determine whether delivering an 
extended course of rTMS (36 treatments instead of 20) is feasible for treatment-interested participants with 
CUD, b) to determine if we are able to generate an fMRI-generated target for rTMS in the L-DLPFC and 
vmPFC that falls within the larger anatomical structures, and to determine the preliminary efficacy / tolerability 
of a course of functionally-targeted rTMS in the treatment of CUD. In order to achieve these aims we plan on 
recruiting N=30 treatment interested participants with ≥moderate CUD from Stanford Addictions Medicine 
clinics (referred by providers), and also via media advertisements in the community. We will perform a phone-
screen to determine preliminary eligibility, and those participants who are likely to qualify and are interested in 
participating in the study will undergo a comprehensive screening visit. Participants who meet enrollment 
criteria will then be invited to attend a baseline targeting fMRI visit where we will perform an fMRI which will 
generate an rTMS target. Participants will then be invited to attend a total of 18-rTMS visits (most often two or 
three visits per week) where we will deliver study-treatment and three sessions of MET-therapy. Finally, we will 
invite participants to attend four follow-up visits over the 6-weeks following their last study-treatment. 

5 of  26
N=30 treatment-seeking participants with ≥moderate CUD
Inclusion: Identified problems related to cannabis use, desire to quit or reduce 
cannabis use, +UDT for cannabinoids
Exclusion: Other SUD, BPAD, Psychosis, psychiatric illness needing treatment, or if 
rTMS or MRI would be unsafe for them
36-sessions
Active rTMS to
vmPFC
3-sessions MET
Active 
treatment
2 – 3 visits 
/ week, 18-
total visits 
36-sessions
Active rTMS to 
L-DLPFC
3-session MET
N=15
N=15
Follow-up phase: Clinical follow-up 2- 4- and 6- weeks following last treatment
Assessments: Pre- Post- fMRI, TLFB (days per week of use, use sessions per day),
Quantified DSM5, craving, urine cannabinoids, & Q-LES-Q-SF
Primary Outcomes: % Retention, % successful functional target, %Weeks of 
abstinence following 7-treatment visits (6 final weeks of active treatment, and 6-
follow-up weeks).
Secondary outcomes: Q-LES-Q, days / week of cannabis use, cannabis use-
sessions / day, & 4-week continuous quit rate, all during follow-up  
5
Baseline Targeting fMRI visit
Immediate-Post fMRI visit, and 1-week post follow-up
Screening (see assessments below for 
further details): Participants will meet with the 
study team either in person (in a private office), 
or via Stanford Secure Zoom, and complete
both self-report and clinician guided measures 
that will assess substance use, psychiatric
history, and medical history. Participants that 
remain eligible after the initial series of 
assessments will provide a urine sample for 
drug screening. For females of child-bearing 
potential, a pregnancy test will be done prior to 
the drug screen. Pregnant women will not be 
allowed to participate. Urine testing will occur 
at the baseline visit in the instance of a virtual 
(zoom) screening visit.
fMRI Visits: Participants will undergo two fMRI 
scans (prior to the first rTMS treatment in a 
Baseline targeting visit and 1-week following 
their final rTMS treatment visit). Participants
will be instructed to abstain from cannabis and 
alcohol for 24 hours prior to scanning to avoid 
acute intoxication during procedures and will 
be asked to provide a saliva sample to verify 
abstinence from recent cannabis use through 
use of SalivaConfirm® testing (Confirm 
Biosciences, Inc.). Pre- and post- fMRI state 
craving measures will be collected. Prior to 
each fMRI, participants will be trained in each 
of the tasks being utilized. Each imaging 
session will include high resolution T1-
weighted structural images (magnetization 
prepared rapid gradient echo), Echoplanar-Imaging (EPI) functional scans during task, and magnetic 
fieldmaps to allow geometric unwarping and cost-function masking of EPI images induced by magnetic field 
inhomogeneities. Total scanning time at each visit will be ≈1-hour.
    Reassessment of Craving Task (ROC): We have adapted a validated 
fMRI36,37 task both to target rTMS and also as an outcome measure. The ROC
task is an adaptation of standard cue-reactivity (where pictures of drug cues 
and matched neutral images are displayed, and participants are asked to 
passively view the images—see example photos). The reassessment of 
craving task, however, differs from standard cue-reactivity in that rather than 
passively viewing images, participants are trained to consider the short-term
consequences of using the substance in a ‘Now’ condition (e. g. that they will 
enjoy being high) or the longer-term consequences of using the substance in a 
‘Later’ condition (e.g. I won’t do well in school) on different runs of the task. Prior studies have reported strong 
incentive-salience (e.g. vmPFC) activation during the ‘Now’ runs, and strong central-executive activation (e.g. 
L-DLPFC) during the ‘later’ runs—and that activation of the central-executive circuitry mediates reduction in 
incentive-salience structures. We will closely adapt this validated task (which was initially validated for 
cigarettes), by adopting the same paradigm [where a fixation cross is jittered around 4-seconds, followed by an 
instructional frame for 2-seconds (either ‘Now’ or ‘Later’), followed by a cannabis image for 6-seconds, followed 
by a fixation cross jittered around 3-seconds, followed by a hand-pad rating for 3-seconds] and perform half of 
the runs as ‘Now’ and half as ‘Later’ in a pseudorandomized order. We will use a validated cannabis-cue slide-
set that is customized to the individuals most common means of marijuana use (e. g. blunt, bong, vape)69. We 

 
 
 
6 of  26 
will initially use 9-minute runs of this task and perform up to 3-total runs separated by a rest-period for the 
participant. We may slightly increase or decrease the duration of each run based on how many trials are 
needed for a consistent signal but will not exceed 12-minutes during a run without a break for the participant. 
We will also include neutral images (such as the pinecone or trombone pictures above) and have participants 
passively view them in ‘Look’ or ‘Rest’ or ‘Watch’ runs, and may include runs of passively viewed cannabis 
images in ‘Look’ or ‘Rest’ or ‘Watch’ runs as well. We will train participants on this task prior to each scan by 
having them complete the task on a computer (outside of the scanner) until they report they are reliably able to 
think about the short- and long- term consequences of their cannabis use during the appropriate run, and 
passively view the neutral or cannabis images in the ‘Look’ or ‘Rest’ or ‘Watch’ runs. Primary Contrast: ‘Now’ 
vs. ‘Later’ runs. 
Standard Passive Cannabis Cue-reactivity Task: Time permitting, we may also use the validated fMRI 
passive cannabis cue reactivity task70 that we used in our previous trial, or parts of this task passively in blocks 
of the reassessment of craving task as described above. During the passive cannabis CR task, we will show 
participants pseudo-randomly interspersed images of cannabis (i.e., cannabis plant, cannabis-related 
paraphernalia) and neutral (e.g., pinecone, trumpet) images, visual control images (i.e., blurred images), and a 
fixation cross. The cannabis stimuli are matched by color, hue, and complexity. Blurred images and the fixation 
crossed trials are used as contrasts to evaluate attention and non-cannabis specific effects. Stimuli are 
presented in six 120-s epochs, each consisting of four 24-s blocks of an image type (one block each of 
cannabis, non-cannabis control, and fixation). Each block is followed by a 6-s washout period where 
participants will rate their cannabis craving, allowing the hemodynamic response from the previous block to 
decline before the next is presented. Primary Contrast: Cannabis images vs. Neutral images. 
Emotional Responsivity Task: We may, time permitting, use a validated emotional-responsivity task to 
measure the negative affect / stress-hyperresponsivity associated with addiction and withdrawal. This task 
consisting of two brief (5min 8sec) substasks71,72, presents images of neutral, positive (happy faces) and 
negative (fear, anger, disgust, sadness) emotional faces either during conscious awareness (unmasked 
conscious awareness, stimuli presented for 500ms with a 750ms interstimulus interval), or unconscious 
awareness (stimuli presented for ≈10-20ms and then masked by a neutral face for 150ms and an interstimulus 
interval of 1233.3ms). In both cases a total of 240 stimuli will be presented in blocks of 8 consecutive images of 
the same emotion, with each block repeated 5 times in a pseudorandomized order. Primary Contrasts: 
Negative emotion (anger, fear, sad, disgust) vs neutral (to assess emotion reactivity to negative stimuli), and 
positive emotion (happy) vs neutral. 
GoGo/NoGo task: We may, time permitting, also use a validated GoGo/NoGo fMRI task30,73 or72 to test 
inhibitory control. In the GoGo/NoGo task participants press a button in response to common, gray-colored 
circles (75%) and rare yellow-colored circles (12.5%), but inhibit responding when seeing blue-colored “NoGo” 
circles (12.5%). Primary Contrast: NoGoCorrect - RareGoCorrect. Participants will undergo a behavioral training 
session prior to each fMRI then practice the task off-line until achieving proficiency (<5% performance 
improvement over two trials). 
N-Back / CPT tasks: We may, time-permitting, also use validated tasks of working memory / executive 
function via the N-Back or CPT task74. In the N-Back task participants will be presented a series of letters and 
will be asked to press a trigger every-time the same letter is presented a certain number-back (i.e. 0 back, 1 
back, and 2 back). Primary Contrast: 2-back vs. 0-back. Participants will undergo a behavioral training session 
prior to each fMRI then practice the task off-line until achieving proficiency (<5% performance improvement 
over two trials). 
 
rTMS Sessions: We will deliver rTMS via a MagPro X100 or R30 double-blinded rTMS research device 
(MagVenture, Denmark) with a Cool-B65 coil equipped with a Localite Neuronavigation System (Sankt 
Augustin, Germany). We will use a standard resting motor threshold (rMT) determination to determine the TMS 
dose75. Treatment will be delivered at 120% rMT. The rTMS strategies differ in terms of the two different target 
circuits. In addictions there are suggestions that the incentive-salience circuitry is over-engaged in response to 
the substance in question and the central executive circuitry is under-engaged. Subsequently, the delivered 
stimulus pattern will differ by target. In one group of participants we will attempt to strengthen central-executive 
circuitry in response to cannabis cues by applying ‘excitatory’ 10Hz stimulation (5s-on,10s-off), 3000 pulses 

 
 
 
7 of  26 
per study-treatment—in a similar fashion to our phase-2 study. Stimulation will be delivered to the portion of 
the L-DLPFC that most activates during the ‘Later’ run of the ROC fMRI task. If there are any participants who 
do not generate such a target we will deliver stimuli to an anatomical location for the L-DLPFC such as22,26,29. 
In the other group we will attempt to reduce incentive-salience circuitry activation to cannabis cues using 
‘inhibitory’ 1Hz stimulation. To match treatment-time we will deliver 900 pulses per study-treatment. Stimulation 
will be delivered to the area of the vmPFC that most activates during the ‘Now’ run of the ROC task or the 
passive cue-reactivity task70. If there are any participants who do not generate such a target we will deliver 
stimuli to an anatomical location for the vmPFC such as18. 
  Prior to each session of rTMS we will present physical cannabis cues and play a brief induction script 
instructing participants to think of their last pleasurable cannabis use session76, similar to what we did in our 
prior Phase-2 trial. Following each study-treatment we will remind participants of the downside of using 
cannabis as they report to us similar to17. We chose to administer cannabis cues prior to rTMS treatments 
given data suggesting that doing so increases rTMS’s efficacy58, and remind participants of the downside of 
using cannabis after treatment due to its use in the recent positive pivotal trial for smoking cessation20. 
    A total of 36 study-treatments will be delivered as two study-treatments each study-treatment-visit separated 
by approximately 45-minutes. Study-treatments will be delivered in as little time as four-weeks (2 study-
treatments each day, five treatment-days per week, 18-study-treatment-visits), but will be most often delivered 
over six to nine-weeks (two to three study-treatment-visits each week, two rTMS-sessions each study-
treatment-visit). We have adapted a flexible study-treatment delivery paradigm given clinical data that 
consistently reports that the total number of rTMS-treatments delivered is more important than the number of 
treatments delivered per week56,77, that rigid treatment delivery paradigms reduce the feasibility of rTMS28 
delivery in CUD, and that even highly accelerated rTMS paradigms are safe, tolerable, and efficacious64–66. In 
addition to the pre-specified urine drug testing paradigm in this study, urine drug tests may be done at 
additional visits at the investigator’s discretion based on concerns of drug or alcohol use that may reduce the 
safety of study-treatment. 
Behavioral Platform: We will use a three-session version of Brief Marijuana Dependence Counseling (BMDC) 
for our behavioral platform (similar to our last study), and will follow the protocol outlined in the manual 
published by NIDA59. Briefly, we will generate personalized feedback reports (PFRs) by collecting the following 
measures: Marijuana Use Summary Sheet, Self-Efficacy Questionnaire, Marijuana Problem Scale, and 
Reasons for Quitting Questionnaire during the screening visit. The PFRs will be used by the clinician to 
facilitate discussion in the three MET sessions, which will occur most often on rTMS-study-treatment visits 1, 5, 
and 10. Discussions will center around participants’ frequency of cannabis use, concerns related to use, 
possible reasons for changing use, high risk use situations, and short and long-term goals related to reduction 
of use. To ensure our behavioral platform is delivered with fidelity, we may audio-tape sessions for review and 
fidelity ratings.  
Follow-up: There will be follow up visits one (where the post-fMRI will be completed), two, four, and six weeks 
after study-treatment completion. Participants will be asked about cannabis use, symptoms of CUD, craving, 
withdrawal, and may undergo behavioral cognitive tests (delayed discounting, n-back, CPT, GoGo/NoGo). 
Cross-Over: Those participants who complete the trial above with one of the treatment targets who meet entry 
criteria following the last follow-up visit may be considered for re-enrollment for the second treatment-target. 
The experiment will be completed in an identical fashion including all visits, assessments, and remuneration. 
Recruitment and Participant Population: 
Recruitment: Participants will be recruited through, a) media advertisements (such as Craigslist and 
facebook), b) using Trialfacts, a professional recruitment agency (similar to our last trial), and c) via referrals 
from addictions medicine clinics. Ads will recruit heavy cannabis users who are interested in quitting or 
substantially reducing their use of cannabis. Participants will undergo a phone screen to ensure they meet 
basic eligibility criteria (see included phone screen), and those who do will be invited for a full screening visit. 
Participant Population: 

 
 
 
8 of  26 
Inclusion Criteria: 1) Participants must be able to provide informed consent and function at an intellectual 
level sufficient to allow accurate completion of all assessment instruments. 2) Participants must be between 
the ages of 18 and 65. 3) Participants must meet DSM-5 criteria for at least moderate Cannabis Use Disorder, 
with use of at least 20 / last 28 days. 4) Participants must express a desire to reduce cannabis use or quit. 5) 
Participants must have a positive UDT for cannabis during their enrollment visit (confirming they are regular 
users). 6) The investigative team must believe each participant is a good study-candidate. 
Exclusion Criteria: 1) Participants must not be pregnant or breastfeeding. 2) Participants must not meet 
moderate or severe use disorder of any other substance with the exception of Tobacco Use Disorder. 3) 
Participants must not be regularly taking any medications that have central nervous system effects that have 
changed in the past 6-weeks. 4) Participants must not have a history of/or current psychotic disorder or bipolar 
disorder. 5) Participants must not have any other Axis I condition requiring current treatment. 6) Participants 
must not have a history of dementia or other cognitive impairment. 7) Participants must not have active suicidal 
ideation or a suicide attempt within the past 180 days. 8) Participants must not have any contraindications to 
receiving rTMS or MRI (e.g. metal implanted above the head, history of seizure, any known brain lesion). 9) 
Participants must not have any unstable general medical conditions. 
DATA MANAGEMENT AND STATISTICAL ANALYSIS: Behavioral data will be managed using REDCap and 
all data entry will take place directly in REDCap. We will use e-consents through Adobe sign, and these 
documents will be uploaded into REDCap. There will however be emergency paper backups of the database 
should it be unavailable for any reason. If data is collected on paper, the information will be immediately 
transferred to the REDCap database, and the paper record will be safe-shredded. Video and Audio recordings 
will be uploaded to Stanford Medicine Box, as will be backup copies of MRI files. 
Statistical Analysis: The primary outcomes for this study are generally qualitative in nature and will serve as 
pilot data to power a larger trial if indicated. We will subsequently not perform formal hypothesis testing. We 
will, however, generate proportions of success for retention (Aim1) and fMRI target generation of our ROC-task 
for both vmPFC and L-DLPFC (Aim2). We will further calculate effect sizes for clinical, behavioral, and fMRI 
outcomes (Aim3), and compare them qualitatively to the results of our phase-2 trial (where we have complete 
data for N=28 participants who received anatomically targeted L-DLPFC stimulation and 23 participants who 
received sham stimulation)—assuming we find this paradigm to be feasible, and our functional-targeting 
development successful, we believe we will have a sufficient sample size to compare effect sizes between the 
two open-label conditions, our prior active condition, and our prior sham condition—acknowledging that the 
comparison will be imperfect with this trial being open-label, and the previous trial being double-blind. All 
statistical analysis will be conducted using SAS/STAT version 9.4 (SAS Institute Inc. 2015. SAS® 9.4 
Statements: Reference, Fourth Edition. Cary, NC: SAS Institute Inc.).    
    Missing Data and Attrition. Missing data in longitudinal studies can be a problematic feature but can be 
mitigated through study design considerations. In order to minimize missing data and study attrition, study 
simplification and enhanced communication between study staff and participants will be emphasized. We will 
make every effort to prevent attrition (e.g., phone/text visit reminders, participation compensation, reinforcing 
adherence to the study protocol at each visit). In addition, in keeping with the Intent to Treat Principle, we will 
make every effort to continue assessments for the entire course of randomized treatment, even among those 
who fail to adhere to randomized assignment or stop participating in the study assigned intervention. 
    Sample Size Justification: The primary focus of this study is to show evidence, with sufficient strength, that 
our proposed treatment paradigm is feasible, that we can generate functionally derived rTMS targets, and that 
our new, refined, protocol has suggestions of improved efficacy relative to our lower burden/complexity 
paradigm. We reasoned that we must be able to retain approximately 60% of the study sample to design a 
reasonable Phase-3 trial with an expanded number of treatments (10% lower retention rate than our Phase-2 
trial), and that we must be able to generate functional targets for 2/3rds of participants to justify the increased 
complexity of the paradigm. Finally, assuming a 60% retention rate, we reasoned we would need at least 9-
participants per cell to generate a meaningful effect size (Aim3, weeks of abstinence and days per week of 
cannabis use in the 12-weeks following the delivery of 14-study treatments) with which to judge whether the 
new paradigm is an improvement relative to the old paradigm.  
 

 
 
 
9 of  26 
Relapse, Drop-Out and Clinical Deterioration: Every effort will be made to re-engage participants who miss 
appointments. Clinical deterioration, such as exacerbation of psychiatric or substance use disorder, will be 
assessed on a case-by-case basis by one of the study clinicians, most often Dr. Sahlem (a licensed and board-
certified psychiatrist) and appropriate referral will be made. Participants will be considered dropouts if they do 
not come back to treatment after receiving three phone calls.  
Strategies to ensure a robust and unbiased approach: The proposed study will achieve robust and 
unbiased results via several design features including: explicit inclusion/exclusion criteria; randomization of 
treatment condition; use of validated laboratory and interview/self-report measures and methods; explicit 
hypotheses and corresponding planned statistical analyses; power estimates; planned handling of 
retention/attrition and missing data; and careful consideration of potential confounds. All experimental details 
are reported in a detailed and fully transparent manner to support replication. 
Consideration of gender as a biological variable: Though this trial is not powered to detect gender 
differences, we will perform our analysis using gender as a potential covariate, and should there be a potential 
gender difference found, we will be able to use that data to power a larger trial. 
 
E. PROTECTION OF HUMAN SUBJECTS________________________________________________________ 
a. Participant description and compensation 
 
Targeted/Planned Enrollment Table 
Total Planned Enrollment 30 (Randomized) 
 
 
TARGETED/PLANNED ENROLLMENT: Number of Subjects 
Ethnic Category 
Sex/Gender 
Females 
Males 
Total 
Hispanic or Latino 
   2 
    3 
      5 
Not Hispanic or Latino 
   9 
    16 
      25 
Ethnic Category: Total of All Subjects* 
30 
Racial Categories 
 
American Indian/Alaska Native 
0 
0 
0 
Asian 
1 
1 
2 
Native Hawaiian or Other Pacific Islander 
1 
1 
2 
Black or African American 
3 
4 
7 
White 
4 
9 
13 
Other / More than one race 
2 
4 
6 
Racial Categories: Total of All Subjects* 
11 
19 
30 
 
We will attempt to recruit all potential participants from the community. We will not exclude anyone based on 
gender, ethnicity, or race. The above estimated enrollment numbers are based on our experience with this 
clinical population as well as our recently completed phase-2 trial.   
 
Compensation and Retention:  Participants will be compensated based upon attending visits as well as given 
additional compensation using a Prize-Based Contingency Management (PB-CM) paradigm78–82. Participants 
who attend all visits as scheduled will receive $
 for visit attendance, and up to an additional $
 for PB-
CM (see below for a further description of each type of compensation). 
 
For visit attendance, participants will be compensated $
 for the screening visit, $
 for each fMRI visits (two-
fMRI visits), $
 for each rTMS/BMDC visits (18 rTMS-visits), $
 for attending the two-week follow-up visit, 
$
 for attending the four-week follow-up visit, and $
 for attending the 6-week follow-up visit—for a total of 
$
.  
 

 
 
 
10 of  26 
Prize-Based Contingency Management (PB-CM) will be used to reinforce visit attendance. In PB-CM 
participants pick a pre-specified number of numbered-chips out of a bowl. Each number corresponds to a 
dollar amount—in this case 250 chips will be used (230 chips will be worth $
 18 chips will be worth $
 one 
chip will be worth $
 and one chip will be worth $
 Participants will be given a chip pick for attending the 
initial MRI visit, and then every other visit that is attended on time and without rescheduling, the number of 
chips will escalate by 1. If a participant misses a scheduled visit or attends more than 10-minutes late the 
number of chip-picks reset to 1 and again escalate by a chip-pick every-other visit. The amount of 
compensation based on PB-CM, will by definition vary to some degree between participants, but fall within a 
predictable range. The average value of a chip is (230*$  + 18*$
 + 1*$
 + 1*$
 / 250 total chips is = 
$
 per chip). Using the escalation paradigm described above, participants who attend all visits as scheduled 
will receive 144 chip picks. Participants who attend all visits as scheduled will subsequently be compensated a 
minimum of $
 a mean / median (since chips are picked at random) of 144*$
 = $
, and we will 
cap PB-CM total compensation at $
 We used this strategy successfully in our prior Phase-2 trial (with 
fewer visits) and found the mean value of each chip pick was $
. 
The total estimated direct time commitment for the study is approximately 38.5 hours (not accounting for travel 
time), and so participants receiving the expected amount of PB-CM compensation will be compensated 
approximately $
 per hour—when including travel time and cost of travel we believe this is a reasonable 
amount of compensation and is not likely to be coercively high. 
 
 
 
b.  Sources of Materials  
Assessments: 
Data collection: 
Research Procedures Table 
 
Screening 
Visit 
Baseline 
fMRI Visit 
rTMS 
Visits 
Post- Tx 
fMRI Visit 
Follow-
up 
Visits 
Screening and Enrollment Eligibility 
Quick Structured Interview for the DSM-5 (Quick-SCID-5)83, 
Medical, Surgical, Social, Family, and Medication History 
X 
 
 
 
 
Brief Counseling for Marijuana Dependance Questionairres59: A 
series of measures used to complete the personal feedback form 
of the Motivational Enhancement Therapy behavioral intervention 
including the Marijuana Problem Scale, the Reasons for Quitting 
Questionnaire and the Self-Efficacy Questionnaire  
X 
 
 
 
 
Urine Pregnancy Test (bHCG) for participants of childbearing 
potential 
X 
 
 
 
 
Study Procedures: 
MRI-Procedures: 
 
X 
 
X 
 
Repetitive Transcranial Magnetic Stimulation (rTMS) study-
treatments 
 
 
X 
 
 
Brief Counseling for Marijuana Dependance sessions: 
 
X 
~5 & ~10 
 
 
Clinical Substance Use Measures: 
Craving Scale (CS)84: Validated brief measure of sub-acute 
craving (past 24-hours), that has predicted future use of 
X 
X 
X 
X 
X 

 
 
 
11 of  26 
substance in Alcohol, stimulants, and opioids. 
The Marijuana Craving Questionnaire (MCQ)85: Validated 
measure of immediate cannabis craving, for use at MRI visits.  
 
X 
X 
X 
 
Time Line Follow Back (TLFB)86: Calendar-based instrument 
designed to assess substance use. 
X 
X 
X 
X 
X 
Diagnostic criteria for Cannabis Use Disorder from the Structured 
Interview for the DSM-587, and additional quantifying questions via 
the Repeatable Clinician-Administered Diagnostic Interview for 
Substance Use Disorders (CADiSUDS)—recently developed by 
our team. *With participant permission we may videotape 
administrations of the CADiSUDS for QA, training, and 
dissemination purposes. 
X 
X 
#8 only 
X 
X 
Urine Drug Testing with creatinine corrected cannabinoid levels 
X 
X 
#16 only 
X 
X 
Cannabis Withdrawal Scale (CWS)88: Validated questionnaire that 
measures symptoms of cannabis withdrawal. 
X 
X 
X 
X 
X 
Participant Burden, Quality of Life, and Function / Functional Improvement: 
Marijuana Problem Scale (MPS)59 
X 
 
 
X 
X 
Q-LES-Q-SF89: Brief measure of quality of life and the Work 
Productivity and Activity Impairment (WPAI-SF) scale90 
X 
X 
Weekly 
X 
X 
Perceived Research Burden Assessment91 
 
 
Final Visit 
 
X 
Cognitive Tasks and Relevant Covarying Symptoms: 
Delayed Discounting Task: Participants choose between receiving 
hypothetical money / cannabis immediately or more money / 
cannabis if they wait longer. Determine whether participants favor 
smaller immediate rewards or larger delayed rewards.  
 
X 
#8 only 
X 
X 
Behavioral GoGo-NoGo Task / n-back / CPT: Behavioral version 
of the fMRI tasks described above. We may collect these, time 
permitting 
 
X 
#8 only 
X 
X 
We will measure relevant covarying symptoms including sleep92, 
depression93,94, ADHD, impulsivity95 and anxiety96. If there is 
question as to whether there is sufficient symptomatology in 
depression or anxiety to require separate treatment, we may 
perform the more extensive clinician rated measures97,98. 
X 
X 
#8 only 
X 
X 
 
PROTECTION OF HUMAN PARTICIPANTS 
 
1. PARTICIPANT CHARACTERISTICS AND RISK MITIGATION STRATEGIES 
Admission into the study is open to men and women and to all racial and ethnic groups. We will recruit a total 
of thirty cannabis use disordered participants from the community and randomize them to receive DLPFC or 
vmPFC study-treatment.  
 
a. General Inclusion / Exclusion Criteria 
Inclusion Criteria:  
1) Participants must be able to provide informed consent and function at an intellectual level sufficient to allow 
accurate completion of all assessment instruments.  
2) Participants must be between the ages of 18 and 60.  

 
 
 
12 of  26 
3) Participants must meet DSM-5 criteria for at least moderate Cannabis Use Disorder, with use of at least 20 
out of the last 28 days.  
4) Participants must express a desire to reduce cannabis use or quit.  
5) Participants must have a positive UDS for cannabis during their enrollment visit (confirming they are regular 
users). 
6) The investigative team must believe each participant is a good study-candidate. 
Exclusion Criteria:  
1) Participants must not be pregnant or breastfeeding.  
2) Participants must not meet moderate or severe use disorder of any other substance with the exception of 
tobacco.  
3) Participants must not be on any medications that have central nervous system effects that have changed in 
the past 6-weeks.  
4) Participants must not have a history of/or current psychotic disorder or bipolar disorder.  
5) Participants must not have any other Axis I condition requiring current treatment. 
6) Participants must not have a history of Dementia or other cognitive impairment.  
7) Participants must not have active suicidal ideation, or a suicide attempt within the past 180 days.  
8) Participants must not have any contraindications to receiving rTMS or MRI (e.g. metal implanted above the 
head, history of seizure, any known brain lesion).  
9) Participants must not have any unstable general medical conditions. 
b. Recruitment and Informed Consent 
    We will recruit from: a) social media platforms such as facebook or youtube and through media advertising 
platforms such as craigslist; b) we will work with addictions medicine clinics such as the Stanford Dual-
Diagnosis clinic to recruit appropriate and interested clinical patients with CUD. Participants meeting with 
study-team members remotely will be asked to find a private location, and those meeting with study-team 
members in person will do so in a private office. After referral we will first schedule a phone call to briefly 
describe the study to potential participants and then will ask basic screening questions to those who are 
interested. Those participants who meet basic inclusion/exclusion criteria based on the phone screen will be 
scheduled for either in-person or e- screening visits through Stanford’s secure Zoom account. First, 
participants will meet with study-team members to go through a second level of screening. During the second 
level screening visit participants will be given a screening consent to review, and if interested will go through it 
with a qualified study team member. If understanding all of the risks and benefits of proceeding with a 
screening visit, the research staff will collect information in order to determine preliminary eligibility. Those 
participants who remain eligible after the second level of screening will meet with one of the clinically trained 
study team-members, most often the PD, for a final level of screening. During the final level of screening 
participants will first review a full consent document. The informed consent form includes a detailed description 
of the study procedures, along with statements regarding participants’ rights to withdraw from the procedure at 
any time without consequences. After the participant reviews the informed consent document, one of the 
clinically trained study team-members, most often the PD, will cover all of the key elements of informed 
consent with the participant and ensure they have an understanding of the RBA of participating in this study. 
Consent will be documented by the signature of the participant on the informed consent agreement, 
accompanied by the signature of the individual obtaining the consent. Participants will then undergo the 
remainder of the screening items with the clinically-trained study-team member, and we will check the Stanford 
Epic chart for all participants who have an MRN and will create an MRN for all those participants who do not. 

 
 
 
13 of  26 
c. Sources of Materials 
    Research material obtained from individual participants includes urine samples, fMRI-data, questionnaires, 
interviews with study personnel, and potentially audio and video recordings of those interviews. Additional 
information will be obtained from the Stanford Epic chart if the participant has one. All behavioral data will be 
directly input into REDCap which is a secure, password protected web-based data collection system. With 
participant permission, we may video-record some parts of the interviews (for quality assurance, educational, 
and dissemination purposes), and may audio-record therapy sessions for later review for fidelity. In the 
instances of these recordings we will store data in secure Stanford Medicine Box folders. We will also record 
digital calendars for the Timeline Follow-Back which will also be stored in secure Stanford Medicine Box 
folders. Urine samples will be delivered to the Stanford laboratory labeled only by participant ID, age, and 
gender. The Stanford laboratory will process the urine samples and send them to the MUSC laboratory 
(contract submitted and approved), who will deliver results via secure email. MRI data will be kept in secure 
Stanford servers and backed up in Stanford Medicine Box. 
 
d. Potential Risks and Risk Mitigation Strategies: 
     Potential risks of rTMS: TMS and rTMS (repeated trains of TMS) has been in use for decades, and high-
frequency rTMS (10Hz) has been FDA-approved for depression and in common clinical use since 200850. One-
Hz stimulation has also been a common stimulation pattern used both experimentally and clinically61,99. There 
is subsequently extensive safety data on a number of paradigms including the 1-Hz and 10-Hz paradigms 
which we are proposing to use in this investigation. The 1Hz paradigm we are using has been applied in a 
number of investigations in depression61 and addictions100. The 10Hz paradigm we are using is nearly identical 
to the FDA-approved protocol and the one we used in our prior work in CUD27,28,68. A summary of the safety 
data for TMS and recommendations for the safe application of TMS are summarized in the following two 
comprehensive papers101,102. Both papers conclude that TMS can be safely applied to both healthy volunteers 
and clinical populations with little risk when appropriately excluding higher risk populations. The most 
substantial risk associated with rTMS is seizure (approximately 1: 30,000 treatments in high-frequency rTMS 
such as 10Hz)103 and presumably lower in low frequency, ‘inhibitory’ rTMS (such as 1Hz)102. Myriad 
investigations have applied rTMS to the L-DLPFC or vmPFC18,48,48,52,104,105, and there is no data suggesting any 
additional safety concerns beyond the standard low risk of seizure. Applying rTMS to the prefrontal cortex in 
general appears to be safe and well tolerated. Various paradigms have now applied stimulation to all areas of 
the brain anterior to the motor cortex without additional safety concerns15–17,106. Increasing the number of 
pulses delivered in a session of rTMS, or the number of total sessions of rTMS may increase efficacy, but does 
not appear to negatively effect safety, indeed a number of investigations have safely applied many more 
pulses per session, per day, and per course than we plan on applying in this investigation66,107. Even 
investigation of serial applications of rTMS over a number of years has not provided any indication of ill 
effect108. Please see below for a description of the major (and minor) risks associated with TMS as well as how 
we plan on mitigating these risks. 
Risk of Seizure: As mentioned above, the most serious risk associated with the use of rTMS is seizure. Since 
the adoption and widespread use of standard safety guidelines in 1997109, there have only been a few 
documented seizures. The risk of seizure has been estimated to be less than 1:30,000 treatments, (or less 
than 1:1000 courses of treatment). The risk of seizure is related to the various stimulation parameters 
(intensity, frequency, train duration), location of application, pre-existing risk of seizure, and 
substance/medication factors. In order to minimize the risk of seizure we will carefully individualize the intensity 
of stimulus (by performing a resting motor threshold determination), treat using standard treatment protocols 
(used safely in other studies such as 10Hz and 1Hz stimulation), and exclude potential participants at higher 
risk of seizure (those with a past history of seizures, those with known CNS lesions, those in withdrawal from 
alcohol or benzodiazepines, those with medical history suggestive of increased seizure risk, etc). Neither 
cannabis use or withdrawal are known to increase the risk of seizure, and subsequently we do not believe 
concurrent use of cannabis, or early abstinence from regular cannabis use will result in any increased risk of 
seizure. In the very rare event rTMS causes a seizure, removing the coil is sufficient to stop the seizure (all 
TMS related seizures have been self-limited to this point), and there does not appear to be an increased risk of 
subsequent seizures. 

 
 
 
14 of  26 
Risk of site discomfort, headache, and fatigue (see the AE table from our recently completed phase-2 trial): 
Three relatively common risks associated with the use of rTMS include the risk of mild transient site discomfort 
during treatment (most patients), the risk of mild, transient, post treatment headache (27% of our phase-2 trial 
participants reported at least one headache) and the risk of post-treatment fatigue (approximately 16% of our 
phase-2 trial participants reported fatigue on at least one day). All three of these potential side effects are 
typically mild. In terms of mitigating site discomfort, we will slowly ramp up stimulation intensity at a rate each 
participant can tolerate. In our experience both clinically and experimentally, ramping initial sessions results in 
improved tolerability of treatment. Additionally, due to the anti-pain effect of rTMS participants rapidly adjust to 
stimulation. Should an rTMS associated headache occur, over the counter analgesics are typically sufficient to 
alleviate it, and we will forewarn participants of the possibility of headache and the effectiveness of over-the-
counter analgesics. TMS associated fatigue is typically mild and transient. We will warn participants about the 
possibility they may have fatigue after treatments and educate them that the fatigue is self-limited. 
Table 2: This table represents the collected Adverse Events between groups in our recently completed Phase2 
trial. 
 
Total Sample, N, 
and (% of ITT 
sample—total / 72) 
Active condition, N, 
and (% of ITT 
sample—total / 37) 
Sham condition, N, 
and (% of ITT 
sample—total / 35) 
Significance (Chi-
square, or Fishers 
Exact) 
# of participants 
with Any Adverse 
Events (%) 
23 (31.9%) 
16 (43.2%) 
7 (20.0%) 
p=0.035 
Total number of 
Adverse events 
30 
19 
11  
p=0.047 
Headache (%) 
14 (19.4%) 
10 (27.0%) 
4 (11.4%) 
ns 
Fatigue (%) 
9 (12.5%) 
6 (16.2%) 
3 (8.6%) 
ns 
Eye Twitch 
1 (1.4%) 
1 (2.7%) 
0 (0) 
ns 
Jaw Pain 
1 (1.4%) 
1 (2.7%) 
0 (0) 
ns 
Persistent site 
discomfort 
1 (1.4%) 
1 (2.7%) 
0 (0) 
ns 
Insomnia 
1 (1.4%) 
0 (0) 
1 (2.9%) 
ns 
Irritability / mood 
swings 
1 (1.4%) 
0 (0) 
1 (2.9%) 
ns 
Hand numbness 
1 (1.4%) 
0 (0) 
1 (2.9%) 
ns 
Increased anxiety 
1 (1.4%) 
0 (0) 
1 (2.9%) 
ns 
 
Potential changes in auditory thresholds: The discharge of the TMS coil generates a high-energy click that may 
temporarily shift auditory temporarily thresholds (there has also been a single case of longer term shifting of 
auditory thresholds when ear protection was not used). Foam earplugs have proven effective at protecting 
against these changes and will be worn during rTMS sessions.  
Safety in the case of pregnancy:  This protocol will exclude pregnant women. Pregnancy status will be 
confirmed during the baseline visit with a urine pregnancy test, and we will only include participants if they are 
willing to use an effective form of birth control.  

 
 
 
15 of  26 
     Potential Risks of MRI: Participants will undergo a total of two MRI’s in this investigation each with a 
duration of approximately 60-minutes. MRI is thought to be a low-risk procedure110,111. The risks associated 
with MRI include the risk of injury if a participant enters the MRI bore with implanted ferromagnetic metal or an 
implanted device. Additionally, there is the potential for psychological distress in participants with severe 
claustrophobia. We will protect against these risks by rigorously screening participants and excluding those 
who have implanted metal / devices and those that are claustrophobic and unable to tolerate a “mock-scan”. 
Participants will be assessed for safety and claustrophobia via clinician assessment, and if needed will 
undergo a “mock-scan” which mimics the experience of MRI without actual scanning. MRI is likely safe in the 
case of pregnancy, however, as mentioned above, pregnant women will not be enrolled in this study.  
Safety of targeting methodology: As stated above, studies have applied serial sessions of rTMS to much of 
the cortex including all of the cortex anterior to the motor strip. There has been no suggestion that any 
treatment location is unsafe, and particularly within the confines of the larger L-DLPFC or vmPFC structures 
we will be targeting. Most of the existent clinical trials in addiction have used anatomical targeting, and so it is 
possible that the functional targeting that we are piloting might be less effective than the anatomical targeting 
that has so far been used. As described in the background and significance section, more precise functional 
targeting may have an advantage over anatomical targeting in terms of engaging the target circuitry, and that 
this may result in increased efficacy18,30,63. We subsequently believe our targeting method will result in 
increased efficacy, though we will carefully monitor participant response, and will be able to compare the 
results of our functionally targeted rTMS to the results of our anatomically targeted Phase-2 results. 
    Potential risks of cue Induced craving paradigms prior to rTMS treatments and during MRI: Prior to 
each session of rTMS we will perform an in-vivo cannabis provocation using a shortened version of this 
standardized paradigm76. In the cue-paradigm participants will listen to a brief induction script asking them to 
remember a time they used cannabis, and will then be presented with cannabis related items (e.g. a vape pen, 
fake joints, etc.). The use of in-vivo drug cues appear to enhance the efficacy of rTMS58, and has become a 
commonly employed approach prior to delivering rTMS17,22. Additionally, our MRI paradigms include exposure 
to cannabis related images. The risk associated with presenting cannabis cues is that exposure to these cues 
are likely to result in transiently increased craving. Our approach to this likely increased craving is as follows. 
Increased craving in this instance is likely to follow a predictable time-course, return to baseline within an hour 
(a shorter period than the visit duration)76, and will likely be of lower magnitude compared to “real-life” cues 
participants will encounter in their life. We will continually assess craving and will use a “talk-down” strategy to 
reduce excessive craving should it occur. Study staff will stay with each participant until their craving has 
returned to baseline levels. In the unlikely event that the individual has prolonged cue-induced craving, one of 
the study physicians will provide an appropriate referral. 
     Risks of Motivational Enhancement Therapy (MET): Motivational enhancement therapy is well tolerated, 
and rarely associated with adverse effects (owing to its supportive, non-judgmental approach). Nonetheless, it 
is possible that participants will feel distressed while discussing sensitive topics. We mitigate this risk by having 
a trained therapist deliver MET—most often the PD. The study-therapist has been, or will be, trained on 
techniques to reduce any distress experienced by the participant. 
     Safety plan for suicidal or decompensated participants: Should any patient report suicidality on the 
depression measures, the Quick-SCID, or in any other manor, the PD or covering clinician will evaluate the 
participant and make any appropriate referral. 
 
2. POTENTIAL BENEFITS OF THE PROPOSED RESEARCH TO THE SUBJECT AND OTHERS 
    All participants will receive a 3-session behavioral intervention with demonstrated efficacy in the treatment of 
Cannabis Use Disorder (Brief Marijuana Dependence Counseling). This treatment will be provided at no 
charge. Participants will also have the ability to receive study-rTMS, which may assist them reduce their use of 
cannabis or quit using cannabis. In addition to the potential direct benefits of participation in this study, 
participants will also help investigators understand the utility of rTMS as a potential treatment for Cannabis Use 
Disorder. 
 

 
 
 
16 of  26 
3. IMPORTANCE OF THE KNOWLEDGE TO BE GAINED 
    This study may provide important information that can improve treatment for future patients with Cannabis 
and other substance use disorders.  
 
4. RISK BENEFIT ASSESSMENT FOR THE PROPOSED RESEARCH 
All of the procedures we will perform as part of this trial are low-risk, and each said risk has been minimized. 
Each participant will receive a standard of care behavioral treatment for Cannabis Use Disorder, and a 
promising candidate-treatment. We subsequently believe that the risk-benefit ratio is favorable for each 
individual participant. We also believe the data obtained in this trial has the potential to benefit society by 
developing this candidate-treatment further.  
5. DATA AND SAFETY MONITORING PLAN This section is based on the recommendations in NIDA’s 
“Guidelines for Developing a Data and Safety Monitoring Plan” (www.drugabuse.gov/funding/dsmbsop.html). A 
detailed DSMP will be developed and approved by NIH program staff prior to study initiation.  
 
a.  Summary of the Protocol.   
    This application proposes to further refine a promising rTMS treatment paradigm for cannabis use disorder 
by increasing the dose of rTMS, adding in functional targeting, and testing the efficacy of a second treatment 
target. 
 
b. Trial Management.   
    The study will be managed from the Brain Stimulation Lab within the Department of Psychiatry and 
Behavioral Sciences at Stanford University. The target population is described above in the inclusion/exclusion 
criteria. 
 
c. Data Management and Analysis. 
    Data will be entered by research team-members directly into REDCap, and fMRI / video / audio data will be 
kept on secure Stanford servers. 
d. Quality Assurance. 
    We will conduct twice yearly data audits prior to DSMB meetings. Confidentiality protections are outlined 
above. 
e. Regulatory Issues. 
    Potential conflicts of interest will be reported using the NIH rules for disclosure. Adverse Events 
(AEs)/Serious Adverse Events (SAEs) occurring during the course of the project will be collected, documented, 
and reported in accordance with protocol and IRB reporting requirements. All research staff involved with 
adverse event reporting will receive general and protocol specific AE/SAE training including identification, 
assessment and evaluation, and documentation and reporting. A research specialist will identify any potential 
adverse events during the course of the study from participant self-report and administration of the visit 
assessments and procedures. The research specialist will provide information to a study clinician, who will be 
responsible for AE/SAE assessment and evaluation including a determination of seriousness and study 
relatedness.  
 
f. Definition of AE and SAE. 
    An Adverse Event (AE) is defined as any untoward medical occurrence in a study subject administered a 
medical treatment that does not necessarily have a causal relationship with this treatment (ICH GCP). Any 
unwanted change, physically, psychologically or behaviorally, that occurs in a study participant during the 
course of the trial is an adverse event. A Serious Adverse Event (SAE) is defined as an adverse event that has 
one of the following outcomes: 
• 
Results in death 
• 
Is life-threatening 
• 
Requires inpatient hospitalization or prolongation of existing hospitalization 
• 
Results in persistent or significant disability/incapacity 
• 
Is a congenital anomaly/birth defect OR 

 
 
 
17 of  26 
• 
Requires intervention to prevent one of the above outcomes. 
 
g. Documentation and Reporting. 
    AEs/SAEs are documented and reported as per protocol and IRB requirements. Research staff will identify 
adverse events and obtain all available information to assess severity, seriousness, study relatedness, 
expectedness, outcome and the need for change or discontinuation in the study intervention. Review of 
Adverse Events: Adverse events (AEs) will be assessed at each visit by study personnel. The type of AE, 
severity of AE, and the relationship to the application of rTMS will be recorded. AEs will be coded using 
Medical Dictionary for Regulatory Activities (MedDRA) rules. Adverse events are generally documented on AE 
Logs and AE Case Report Forms (CRFs). Additional relevant AE information if available should be 
documented in a progress note in the research record as appropriate to allow monitoring and evaluating of the 
AE. If the AE meets the definition for serious, appropriate SAE protocol specific reporting forms are completed 
and disseminated to the appropriate persons and within the designated timeframes as indicated above. For 
each AE/SAE recorded, the research staff will follow the AE/SAE until resolution, stabilization or until the 
participant is no longer in the study as stated in the protocol. When a reportable SAE is identified, the research 
team will notify the Stanford Institutional Review Board (IRB) within 24 hours.  
    Other adverse events will be reported to the Stanford IRB if the AE is unexpected AND related or possibly 
related AND serious or more prevalent than expected. All three criteria must be met for an AE to be reported to 
the Stanford IRB. The IRB definition of unexpected is that the AE is not identified in nature, severity or 
frequency in the current protocol, informed consent, investigator brochure or with other current risk information. 
The definition of related is that there is a reasonable possibility that the adverse event may have been caused 
by the intervention. Reportable AEs are reviewed by the IRB Chair and reported to the IRB Board at the next 
meeting. 
h. Trial Safety. 
    The potential risks and benefits and methods to minimize these risks are outlined above. The research team 
will report any unexpected AEs or any scores of “severe” on the side-effect symptom rating form or any FDA-
defined serious AEs to the PI within 24 hrs so that the PI can decide on the appropriate action. All unexpected 
AEs will be monitored while they are active to determine if treatment is needed. Study procedures will follow 
the FDA’s Good Clinical Practice Guidelines (www.fda.gov/oc/gcp). Any outside requests for information or any 
breaches in confidentiality will be reported to Dr.Sahlem.  
 
An interim analysis is not planned at this time. 
 
i. DSM Plan Administration. 
    Dr. Sahlem will be responsible for monitoring the study and will participate in weekly study team meetings.  
 
j. DSM Board.   
    A Data Safety and Monitoring Board will be formed to monitor both the rate and severity of adverse events.  
This panel will include an expert in addictions, an expert in brain stimulation, and an expert in neuroimaging. 
The DSM Board will meet twice-yearly while the study is recruiting. 
6. CLINICALTRIALS.GOV REQUIREMENTS 
    In accordance with Public Law 110-85, this project will be registered at the ClinicalTrials.gov Protocol 
Registration System Information Website prior to study initiation. 
F. REFERENCES/LITERATURE CITATIONS______________________________________________________ 
 
1. Key Substance Use and Mental Health Indicators in the United States: Results from the 2020 National Survey on Drug 
Use and Health. 156 (2020). 
2. Meier, M. H. Cannabis use and psychosocial functioning: evidence from prospective longitudinal studies. Curr. Opin. 
Psychol. 38, 19–24 (2021). 

 
 
 
18 of  26 
3. Hasin, D. S. et al. Prevalence of Marijuana Use Disorders in the United States Between 2001-2002 and 2012-2013. 
JAMA Psychiatry 72, 1235 (2015). 
4. Davis, M. L. et al. Behavioral Therapies for Treatment-Seeking Cannabis Users: A Meta-Analysis of Randomized 
Controlled Trials. Eval. Health Prof. 38, 94–114 (2015). 
5. Mariani, J. J. et al. Quetiapine treatment for cannabis use disorder. Drug Alcohol Depend. 218, 108366 (2021). 
6. McRae-Clark, A. L. et al. Varenicline as a treatment for cannabis use disorder: A placebo-controlled pilot trial. Drug 
Alcohol Depend. 229, 109111 (2021). 
7. McRae-Clark, A. L. et al. Buspirone treatment of cannabis dependence: A randomized, placebo-controlled trial. Drug 
Alcohol Depend. 156, 29–37 (2015). 
8. Gray, K. M. et al. A randomized placebo-controlled trial of N-acetylcysteine for cannabis use disorder in adults. Drug 
Alcohol Depend. 177, 249–257 (2017). 
9. McRae-Clark, A. L. et al. Vilazodone for cannabis dependence: A randomized, controlled pilot trial: Vilazodone for 
Cannabis Dependence. Am. J. Addict. 25, 69–75 (2016). 
10. 
Lintzeris, N. et al. Nabiximols for the Treatment of Cannabis Dependence: A Randomized Clinical Trial. JAMA 
Intern. Med. 179, 1242 (2019). 
11. 
Levin, F. R. et al. Dronabinol for the treatment of cannabis dependence: A randomized, double-blind, placebo-
controlled trial. Drug Alcohol Depend. 116, 142–150 (2011). 
12. 
Levin, F. R. et al. Dronabinol and lofexidine for cannabis use disorder: A randomized, double-blind, placebo-
controlled trial. Drug Alcohol Depend. 159, 53–60 (2016). 
13. 
O’Reardon, J. P. et al. Efficacy and safety of transcranial magnetic stimulation in the acute treatment of major 
depression: a multisite randomized controlled trial. Biol. Psychiatry 62, 1208–1216 (2007). 
14. 
Blumberger, D. M. et al. A randomized sham controlled comparison of once vs twice-daily intermittent theta burst 
stimulation in depression: A canadian rTMS treatment and biomarker network in depression (CARTBIND) study. Brain 
Stimulat. (2021) doi:10.1016/j.brs.2021.09.003. 
15. 
Levkovitz, Y. et al. Efficacy and safety of deep transcranial magnetic stimulation for major depression: a 
prospective multicenter randomized controlled trial. World Psychiatry 14, 64–73 (2015). 
16. 
Carmi, L. et al. Efficacy and Safety of Deep Transcranial Magnetic Stimulation for Obsessive-Compulsive 
Disorder: A Prospective Multicenter Randomized Double-Blind Placebo-Controlled Trial. Am. J. Psychiatry 176, 931–
938 (2019). 

 
 
 
19 of  26 
17. 
Zangen, A. et al. Repetitive transcranial magnetic stimulation for smoking cessation: a pivotal multicenter double-
blind randomized controlled trial. World Psychiatry 20, 397–404 (2021). 
18. 
McCalley, D. M. et al. Medial Prefrontal Cortex Theta Burst Stimulation Improves Treatment Outcomes in Alcohol 
Use Disorder: A Double-Blind, Sham-Controlled Neuroimaging Study. Biol. Psychiatry Glob. Open Sci. 
S2667174322000271 (2022) doi:10.1016/j.bpsgos.2022.03.002. 
19. 
Harel, M. et al. Repetitive Transcranial Magnetic Stimulation in Alcohol Dependence: A Randomized, Double-
Blind, Sham-Controlled Proof-of-Concept Trial Targeting the Medial Prefrontal and Anterior Cingulate Cortices. Biol. 
Psychiatry 91, 1061–1069 (2022). 
20. 
Perini, I. et al. Repetitive transcranial magnetic stimulation targeting the insular cortex for reduction of heavy 
drinking in treatment-seeking alcohol-dependent subjects: a randomized controlled trial. Neuropsychopharmacology 
45, 842–850 (2020). 
21. 
Ekhtiari, H. et al. Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A 
consensus paper on the present state of the science and the road ahead. Neurosci. Biobehav. Rev. 104, 118–140 
(2019). 
22. 
Li, X. et al. Two weeks of image-guided left dorsolateral prefrontal cortex repetitive transcranial magnetic 
stimulation improves smoking cessation: A double-blind, sham-controlled, randomized clinical trial. Brain Stimulat. 13, 
1271–1279 (2020). 
23. 
Terraneo, A. et al. Transcranial magnetic stimulation of dorsolateral prefrontal cortex reduces cocaine use: A pilot 
study. Eur. Neuropsychopharmacol. 26, 37–44 (2016). 
24. 
Mishra, B. R., Nizamie, S. H., Das, B. & Praharaj, S. K. Efficacy of repetitive transcranial magnetic stimulation in 
alcohol dependence: a sham-controlled study: Efficacy of rTMS in alcohol dependence. Addiction 105, 49–55 (2010). 
25. 
Sheffer, C. E. et al. Preventing relapse to smoking with transcranial magnetic stimulation: Feasibility and potential 
efficacy. Drug Alcohol Depend. 182, 8–18 (2018). 
26. 
Shevorykin, A. et al. Transcranial Magnetic Stimulation for Long-Term Smoking Cessation: Preliminary 
Examination of Delay Discounting as a Therapeutic Target and the Effects of Intensity and Duration. Front. Hum. 
Neurosci. 16, 920383 (2022). 
27. 
Sahlem, G. L., Baker, N. L., George, M. S., Malcolm, R. J. & McRae-Clark, A. L. Repetitive transcranial magnetic 
stimulation (rTMS) administration to heavy cannabis users. Am. J. Drug Alcohol Abuse 44, 47–55 (2018). 

 
 
 
20 of  26 
28. 
Sahlem, G. L. et al. A case series exploring the effect of twenty sessions of repetitive transcranial magnetic 
stimulation (rTMS) on cannabis use and craving. Brain Stimulat. 13, 265–266 (2020). 
29. 
Beam, W., Borckardt, J. J., Reeves, S. T. & George, M. S. An efficient and accurate new method for locating the 
F3 position for prefrontal TMS applications. Brain Stimulat. 2, 50–54 (2009). 
30. 
Newman-Norlund, R. D., Gibson, M., McConnell, P. A. & Froeliger, B. Dissociable Effects of Theta-Burst 
Repeated Transcranial Magnetic Stimulation to the Inferior Frontal Gyrus on Inhibitory Control in Nicotine Addiction. 
Front. Psychiatry 11, 260 (2020). 
31. 
Wetherill, R. R. et al. Early Versus Late Onset of Cannabis Use: Differences in Striatal Response to Cannabis 
Cues. Cannabis Cannabinoid Res. 1, 229–233 (2016). 
32. 
Zhou, X. et al. Cue Reactivity in the Ventral Striatum Characterizes Heavy Cannabis Use, Whereas Reactivity in 
the Dorsal Striatum Mediates Dependent Use. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 4, 751–762 (2019). 
33. 
Vollstädt-Klein, S. et al. Initial, habitual and compulsive alcohol use is characterized by a shift of cue processing 
from ventral to dorsal striatum: Striatal activation in compulsive drinking. Addiction 105, 1741–1749 (2010). 
34. 
Hanlon, C. A. et al. Probing the Frontostriatal Loops Involved in Executive and Limbic Processing via Interleaved 
TMS and Functional MRI at Two Prefrontal Locations: A Pilot Study. PLoS ONE 8, (2013). 
35. 
Hanlon, C. A., Dowdle, L. T., Moss, H., Canterberry, M. & George, M. S. Mobilization of Medial and Lateral 
Frontal-Striatal Circuits in Cocaine Users and Controls: An Interleaved TMS/BOLD Functional Connectivity Study. 
Neuropsychopharmacology 41, 3032–3041 (2016). 
36. 
Kober, H. et al. Prefrontal–striatal pathway underlies cognitive regulation of craving. Proc. Natl. Acad. Sci. U. S. A. 
107, 14811–14816 (2010). 
37. 
Hartwell, K. J. et al. Neural correlates of craving and resisting craving for tobacco in nicotine dependent smokers: 
Crave and resist. Addict. Biol. 16, 654–666 (2011). 
38. 
Budney, A. J., Sofis, M. J. & Borodovsky, J. T. An update on cannabis use disorder with comment on the impact 
of policy related to therapeutic and recreational cannabis use. Eur. Arch. Psychiatry Clin. Neurosci. 269, 73–86 (2019). 
39. 
Sahlem, G. L., Tomko, R. L., Sherman, B. J., Gray, K. M. & McRae-Clark, A. L. Impact of cannabis legalization on 
treatment and research priorities for cannabis use disorder. Int. Rev. Psychiatry 30, 216–225 (2018). 
40. 
UNITED NATIONS OFFICE ON DRUGS AND LABOR. WORLD DRUG REPORT 2020 (SET OF 6 BOOKLETS). 
(UNITED NATIONS, 2021). 

 
 
 
21 of  26 
41. 
Levy, N. S., Mauro, P. M., Mauro, C. M., Segura, L. E. & Martins, S. S. Joint perceptions of the risk and 
availability of Cannabis in the United States, 2002-2018. Drug Alcohol Depend. 226, 108873 (2021). 
42. 
Patrick, M. et al. Monitoring the Future Panel Study annual report: National data on substance use among adults 
ages 19 to 60, 1976-2021. (2022). 
43. 
Manthey, J., Freeman, T. P., Kilian, C., López-Pelayo, H. & Rehm, J. Public health monitoring of cannabis use in 
Europe: prevalence of use, cannabis potency, and treatment rates. Lancet Reg. Health - Eur. 10, 100227 (2021). 
44. 
Gray, K. M. et al. A Double-Blind Randomized Controlled Trial of N -Acetylcysteine in Cannabis-Dependent 
Adolescents. Am. J. Psychiatry 169, 805–812 (2012). 
45. 
Brown, J. C. et al. NMDA-receptor agonist reveals LTP-like properties of 10-Hz rTMS in the human motor cortex. 
Brain Stimulat. 14, 619–621 (2021). 
46. 
Deng, Z.-D., Lisanby, S. H. & Peterchev, A. V. Electric field depth–focality tradeoff in transcranial magnetic 
stimulation: simulation comparison of 50 coil designs. Brain Stimulat. 6, 1–13 (2013). 
47. 
Huang, Y.-Z., Chen, R.-S., Rothwell, J. C. & Wen, H.-Y. The after-effect of human theta burst stimulation is NMDA 
receptor dependent. Clin. Neurophysiol. 118, 1028–1032 (2007). 
48. 
Hanlon, C. A. et al. Left frontal pole theta burst stimulation decreases orbitofrontal and insula activity in cocaine 
users and alcohol users. Drug Alcohol Depend. 178, 310–317 (2017). 
49. 
Blumberger, D. M. et al. Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic 
stimulation in patients with depression (THREE-D): a randomised non-inferiority trial. The Lancet 391, 1683–1692 
(2018). 
50. 
O’Reardon, J. P. et al. Efficacy and Safety of Transcranial Magnetic Stimulation in the Acute Treatment of Major 
Depression: A Multisite Randomized Controlled Trial. Biol. Psychiatry 62, 1208–1216 (2007). 
51. 
McNeill, A. Continuous Theta Burst Transcranial Magnetic Stimulation of the Right Dorsolateral Prefrontal Cortex 
Impairs Inhibitory Control and Increases Alcohol Consumption. Cogn Affect Behav Neurosci 9 (2018). 
52. 
Rose, J. E. et al. Repetitive Transcranial Magnetic Stimulation of the Superior Frontal Gyrus Modulates Craving 
for Cigarettes. Biol. Psychiatry 70, 794–799 (2011). 
53. 
Kearney-Ramos, T. E. et al. Transdiagnostic Effects of Ventromedial Prefrontal Cortex Transcranial Magnetic 
Stimulation on Cue Reactivity. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 3, 599–609 (2018). 
54. 
Li, X. et al. Transcranial magnetic stimulation of the dorsal lateral prefrontal cortex inhibits medial orbitofrontal 
activity in smokers: rTMS Effects on Brain Circuity in Smokers. Am. J. Addict. 26, 788–794 (2017). 

 
 
 
22 of  26 
55. 
Sahlem, G. L., Baker, N. L., George, M. S., Malcolm, R. J. & McRae-Clark, A. L. Repetitive transcranial magnetic 
stimulation (rTMS) administration to heavy cannabis users. Am. J. Drug Alcohol Abuse 44, 47–55 (2018). 
56. 
Galletly, C., Gill, S., Clarke, P., Burton, C. & Fitzgerald, P. B. A randomized trial comparing repetitive transcranial 
magnetic stimulation given 3 days/week and 5 days/week for the treatment of major depression: is efficacy related to 
the duration of treatment or the number of treatments? Psychol. Med. 42, 981–988 (2012). 
57. 
Harel, E. V. et al. H-coil repetitive transcranial magnetic stimulation for treatment resistant major depressive 
disorder: An 18-week continuation safety and feasibility study. World J. Biol. Psychiatry 15, 298–306 (2014). 
58. 
Dinur-Klein, L. et al. Smoking Cessation Induced by Deep Repetitive Transcranial Magnetic Stimulation of the 
Prefrontal and Insular Cortices: A Prospective, Randomized Controlled Trial. Biol. Psychiatry 76, 742–749 (2014). 
59. 
Brief Counseling for Marijuana Dependence: A Manual for Treating Adults. 208. 
60. 
George, M. S. et al. Daily Left Prefrontal Transcranial Magnetic Stimulation Therapy for Major Depressive 
Disorder: A Sham-Controlled Randomized Trial. Arch. Gen. Psychiatry 67, 507 (2010). 
61. 
McDonald, W. M. et al. Improving the antidepressant efficacy of transcranial magnetic stimulation: maximizing the 
number of stimulations and treatment location in treatment-resistant depression. Depress. Anxiety 28, 973–980 (2011). 
62. 
Wang, D. et al. Parcellating cortical functional networks in individuals. Nat. Neurosci. 18, 1853–1860 (2015). 
63. 
Fox, M. D., Buckner, R. L., White, M. P., Greicius, M. D. & Pascual-Leone, A. Efficacy of TMS targets for 
depression is related to intrinsic functional connectivity with the subgenual cingulate. Biol. Psychiatry 72, 595–603 
(2012). 
64. 
Williams, N. R. et al. High-dose spaced theta-burst TMS as a rapid-acting antidepressant in highly refractory 
depression. Brain 141, e18–e18 (2018). 
65. 
Cole, E. J. et al. Stanford Accelerated Intelligent Neuromodulation Therapy for Treatment-Resistant Depression. 
Am. J. Psychiatry appi.ajp.2019.19070720 (2020) doi:10.1176/appi.ajp.2019.19070720. 
66. 
Cole, E. J. et al. Stanford Neuromodulation Therapy (SNT): A Double-Blind Randomized Controlled Trial. Am J 
Psychiatry 9 (2021). 
67. 
Kearney-Ramos, T. E. et al. State-Dependent Effects of Ventromedial Prefrontal Cortex Continuous Thetaburst 
Stimulation on Cocaine Cue Reactivity in Chronic Cocaine Users. Front. Psychiatry 10, 317 (2019). 
68. 
Sahlem, G. A Preliminary Investigation of Pre-Frontal repetitive Transcranial Magnetic Stimulation (rTMS) for the 
Treatment of Cannabis Use Disorder. NIH NIDA K23 DA043628,. 

 
 
 
23 of  26 
69. 
Macatee, R. J., Carr, M., Afshar, K. & Preston, T. J. Development and validation of a cannabis cue stimulus set. 
Addict. Behav. 112, 106643 (2021). 
70. 
Karoly, H. C. et al. Investigating a novel fMRI cannabis cue reactivity task in youth. Addict. Behav. 89, 20–28 
(2019). 
71. 
Williams, L. M. et al. Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-
Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial. Neuropsychopharmacology 40, 
2398–2408 (2015). 
72. 
Korgaonkar, M. S., Grieve, S. M., Etkin, A., Koslow, S. H. & Williams, L. M. Using Standardized fMRI Protocols to 
Identify Patterns of Prefrontal Circuit Dysregulation that are Common and Specific to Cognitive and Emotional Tasks in 
Major Depressive Disorder: First Wave Results from the iSPOT-D Study. Neuropsychopharmacology 38, 863–871 
(2013). 
73. 
Froeliger, B. et al. Association Between Baseline Corticothalamic-Mediated Inhibitory Control and Smoking 
Relapse Vulnerability. JAMA Psychiatry 74, 379 (2017). 
74. 
McClernon, F. J. et al. The effects of nicotine and non-nicotine smoking factors on working memory and 
associated brain function: Smoking and working memory. Addict. Biol. 21, 954–961 (2016). 
75. 
Borckardt, J. J., Nahas, Z., Koola, J. & George, M. S. Estimating Resting Motor Thresholds in Transcranial 
Magnetic Stimulation Research and Practice: A computer Simulation Evaluation of Best Methods. J ECT 22, 7 (2006). 
76. 
McRae-Clark, A. L. et al. Stress- and cue-elicited craving and reactivity in marijuana-dependent individuals. 
Psychopharmacology (Berl.) 218, 49–58 (2011). 
77. 
Kokdere, F. et al. Do deviations from the 5 sessions per week schedule impact outcomes of transcranial magnetic 
stimulation for major depressive disorder? Brain Stimulat. 13, 1491–1493 (2020). 
78. 
Petry, N. M., Martin, B., Cooney, J. L. & Kranzler, H. R. Give them prizes and they will come: Contingency 
management for treatment of alcohol dependence. J. Consult. Clin. Psychol. 68, 250–257 (2000). 
79. 
Rash, C. J. & DePhilippis, D. Considerations for Implementing Contingency Management in Substance Abuse 
Treatment Clinics: The Veterans Affairs Initiative as a Model. Perspect. Behav. Sci. 42, 479–499 (2019). 
80. 
Benishek, L. A. et al. Prize-based contingency management for the treatment of substance abusers: a meta-
analysis: Prize-based contingency management meta-analysis. Addiction 109, 1426–1436 (2014). 
81. 
Kelly, T. M., Daley, D. C. & Douaihy, A. B. Contingency Management for Patients With Dual Disorders in Intensive 
Outpatient Treatment for Addiction. J. Dual Diagn. 10, 108–117 (2014). 

 
 
 
24 of  26 
82. 
Litt, M. D., Kadden, R. M. & Petry, N. M. Behavioral treatment for marijuana dependence: Randomized trial of 
contingency management and self-efficacy enhancement. Addict. Behav. 38, 1764–1775 (2013). 
83. 
First, M. & Williams, J. Quick Structured Clinical Interview for DSM-5® Disorders (QuickSCID-5). (APPI 
Publishing, 2021). 
84. 
McHugh, R. K., Trinh, C. D., Griffin, M. L. & Weiss, R. D. Validation of the craving scale in a large sample of 
adults with substance use disorders. Addict. Behav. 113, 106651 (2021). 
85. 
Heishman, S. J. et al. Reliability and Validity of a Short Form of the Marijuana Craving Questionnaire. Drug 
Alcohol Depend. 102, 35–40 (2009). 
86. 
Sobell, L. C. & Sobell, M. B. Timeline Followback: A Technique for Assessing Self Reported Ethanol 
Consumption, Vol. 17. (1992). 
87. 
First, M. B., Williams, J. B. W., Karg, R. S. & Spitzer, R. L. Structured clinical interview for DSM-5—Research 
version (SCID-5 for DSM-5, research version; SCID-5-RV). Arlingt. VA Am. Psychiatr. Assoc. (2015). 
88. 
Allsop, D. J., Norberg, M. M., Copeland, J., Fu, S. & Budney, A. J. The Cannabis Withdrawal Scale development: 
Patterns and predictors of cannabis withdrawal and distress. Drug Alcohol Depend. 119, 123–129 (2011). 
89. 
Riendeau, R. P. et al. Factor structure of the Q-LES-Q short form in an enrolled mental health clinic population. 
Qual. Life Res. 27, 2953–2964 (2018). 
90. 
Reilly, M. C., Zbrozek, A. S. & Dukes, E. M. The Validity and Reproducibility of a Work Productivity and Activity 
Impairment Instrument: PharmacoEconomics 4, 353–365 (1993). 
91. 
Lingler, J. H., Schmidt, K., Gentry, A., Hu, L. & Terhorst, L. Perceived Research Burden Assessment (PeRBA): 
Instrument Development and Psychometric Evaluation. 18 (2015). 
92. 
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. & Kupfer, D. J. The Pittsburgh sleep quality index: A 
new instrument for psychiatric practice and research. Psychiatry Res. 28, 193–213 (1989). 
93. 
Rush, A. J. et al. The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), 
and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol. Psychiatry 54, 
573–583 (2003). 
94. 
Fantino, B. & Moore, N. The self-reported Montgomery-Åsberg depression rating scale is a useful evaluative tool 
in major depressive disorder. BMC Psychiatry 9, 26 (2009). 
95. 
Reise, S. P., Moore, T. M., Sabb, F. W., Brown, A. K. & London, E. D. The Barratt Impulsiveness Scale–11: 
Reassessment of its structure in a community sample. Psychol. Assess. 25, 631–642 (2013). 

 
 
 
25 of  26 
96. 
Spitzer, R. L., Kroenke, K., Williams, J. B. W. & Löwe, B. A Brief Measure for Assessing Generalized Anxiety 
Disorder: The GAD-7. Arch. Intern. Med. 166, 1092 (2006). 
97. 
Williams, J. B. W. & Kobak, K. A. Development and reliability of a structured interview guide for the Montgomery-
Åsberg Depression Rating Scale (SIGMA). Br. J. Psychiatry 192, 52–58 (2008). 
98. 
Shear, M. K. et al. Reliability and validity of a structured interview guide for the Hamilton Anxiety Rating Scale 
(SIGH-A). Depress. Anxiety 13, 166–178 (2001). 
99. 
Pascual-Leone, A. et al. Study and Modulation of Human Cortical Excitability With Transcranial Magnetic 
Stimulation. J. Clin. Neurophysiol. 15, 333–343 (1998). 
100. 
Rose, J. E. et al. Repetitive transcranial magnetic stimulation of the superior frontal gyrus modulates craving for 
cigarettes. Biol. Psychiatry 70, 794–799 (2011). 
101. 
Rossi, S., Hallett, M., Rossini, P. M. & Pascual-Leone, A. Safety, ethical considerations, and application 
guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin. Neurophysiol. 120, 
2008–2039 (2009). 
102. 
Rossi, S. et al. Safety and recommendations for TMS use in healthy subjects and patient populations, with 
updates on training, ethical and regulatory issues: Expert Guidelines. Clin. Neurophysiol. 132, 269–306 (2021). 
103. 
Zis, P. et al. Safety, Tolerability, and Nocebo Phenomena During Transcranial Magnetic Stimulation: A Systematic 
Review and Meta-Analysis of Placebo-Controlled Clinical Trials. Neuromodulation J. Int. Neuromodulation Soc. 23, 
291–300 (2020). 
104. 
Price, R. B. et al. Effect of Experimental Manipulation of the Orbitofrontal Cortex on Short-Term Markers of 
Compulsive Behavior: A Theta Burst Stimulation Study. Am. J. Psychiatry 178, 459–468 (2021). 
105. 
Hanlon, C. A. et al. What goes up, can come down: Novel brain stimulation paradigms may attenuate craving and 
craving-related neural circuitry in substance dependent individuals. Brain Res. 1628, 199–209 (2015). 
106. 
Williams, N. R. et al. Accelerated Neuromodulation Therapy for Obsessive-Compulsive Disorder. Brain Stimulat. 
S1935861X21000413 (2021) doi:10.1016/j.brs.2021.02.013. 
107. 
George, M. S. et al. A two-site pilot randomized 3 day trial of high dose left prefrontal repetitive transcranial 
magnetic stimulation (rTMS) for suicidal inpatients. Brain Stimulat. 7, 421–431 (2014). 
108. 
Li, X. et al. Safe Management of a Bipolar Depressed Patient With Prefrontal Repetitive Transcranial Magnetic 
Stimulation (rTMS) Over 7 Years and >2 Million Stimuli. Brain Stimulat. 7, 919–921 (2014). 

 
 
 
26 of  26 
109. 
Wassermann, E. M. Risk and safety of repetitive transcranial magnetic stimulation: report and suggested 
guidelines from the International Workshop on the Safety of Repetitive Transcranial Magnetic Stimulation, June 5–7, 
1996. Electroencephalogr. Clin. Neurophysiol. Potentials Sect. 108, 1–16 (1998). 
110. 
Expert Panel on MR Safety: et al. ACR guidance document on MR safe practices: 2013. J. Magn. Reson. Imaging 
37, 501–530 (2013). 
111. 
ACR Committee on MR Safety: et al. ACR guidance document on MR safe practices: Updates and critical 
information 2019. J. Magn. Reson. Imaging 51, 331–338 (2020).