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Nature Mental Health
nature mental health
https://doi.org/10.1038/s44220-023-00184-zArticle
Stanford Hypnosis Integrated with
Functional Connectivity-targeted
Transcranial Stimulation (SHIFT): a
preregistered randomized controlled trial
Hypnotizability, one’s ability to experience cognitive, emotional, behavioral
and physical changes in response to suggestions in the context of hypnosis,
is a stable neurobehavioral trait associated with improved treatment
outcomes from hypnosis-based therapy. Increasing hypnotizability in
people who are low-to-medium hypnotizable individuals could improve
both the ecacy and eectiveness of therapeutic hypnosis as a clinical
intervention. Hypnotizability is associated with dorsolateral prefrontal cortex
(DLPFC) functions and connectivity with the salience network, yet there is
conicting evidence as to whether unilateral inhibition of the DLPFC changes
hypnotizability. We hypothesized that using personalized neuroimaging-
guided targeting to non-invasively stimulate the left DLPFC with transcranial
magnetic stimulation (TMS) would temporarily increase hypnotizability. In
a preregistered, double-blinded, randomized controlled trial, we recruited a
sample of 80 patients with bromyalgia syndrome, a functional pain disorder
for which hypnosis has been a demonstrated benecial n on -p ha rm ac ol o-
gical t re at ment option. All participants were TMS-naive. Participants were
randomly assigned to active or sham continuous theta-burst stimulation
over a personalized neuroimaging-derived left-DLPFC target, a technique
termed SHIFT (Stanford Hypnosis Integrated with Functional Connectivity-
targeted Transcranial Stimulation). We tested our hypothesis using the
hypnotic induction prole scores, a standardized measure of hypnotizability.
Pre-to-post SHIFT change in the hypnotic induction prole scores was
signicantly greater in the active versus sham group after 92 s of stimulation
(P = 0.046). Only the active SHIFT group showed a signicant i n c r e ase i n
hypnotizability following stimulation (active: P < 0.001; sham: P = 0.607). As
such, modulation of trait hypnotizability is possible in humans using non-
invasive neuromodulation. Our ndings support a relationship between the
inhibition of the left DLPFC and an increase in hypnotizability. Dose–response
optimization of spaced SHIFT should be explored to understand the optimal
dose–response relationship. ClinicalTrials.gov registration: NCT02969707.
Received: 28 February 2023
Accepted: 14 November 2023
Published online: xx xx xxxx
Check for updates
e-mail: nolanw@stanford.edu; dspiegel@stanford.edu
A list of authors and their afiliations appears at the end of the paper
Nature Mental Health
Article https://doi.org/10.1038/s44220-023-00184-z
A previous study by Dienes and Hutton29 demonstrated that a short
application (300 pulses) of inhibitory (1 Hz) rTMS when applied to the
L-DLPFC increased both objective and subjective reports of hypnotic
responsiveness in a small cohort of medium-hypnotizable individuals.
A replication study by Coltheart et al.
30
did not replicate this finding
but found that inhibition of the right DLPFC resulted in a significant
increase in objective (but not subjective) responses to hypnotic sug-
gestions, interpreted as driven by interrupting networks involved in
belief formation. A potential explanation for the contradicting findings
may also lie in the modest stimulation parameters and the skull-based
targeting approach used in both studies. In this study, we elected to
utilize an optimized non-invasive neurostimulation technique, termed
SHIFT (Stanford Hypnosis Integrated with Functional Connectivity-
targeted Transcranial Stimulation), to modulate trait hypnotizabil-
ity. On the basis of our previous finding that high hypnotizability is
associated with increased L-DLPFC–dACC functional connectivity
3
,
as well as L-DLPFC functions29, we hypothesized that the application
of active spaced SHIFT over the individualized L-DLPFC target that
shows the greatest resting-state functional connectivity with the dACC
would significantly increase trait hypnotizability as measured by the
hypnotic induction profile (HIP), as well as the subjective hypnotic
experience using the hypnotic intensity scale (HIS), compared with
sham stimulation. We conducted a double-blind, randomized, sham-
controlled trial to determine whether SHIFT can be utilized to modulate
hypnotizability.
Results
Eighty participants were included in the analyses (93.8% female, mean
age 48.3 ± 12.4 years). See Table 1 for the reported demographic infor-
mation by treatment group. In both groups, most participants guessed
receiving active treatment, and the guesses were not associated with
the actual treatment received (χ² = 2.257, P = 0.133) or with the pre-to-
post change in HIP scores (U = 510.5, P = 0.152). The correlation between
HIP scores during the screening appointment and the initial hypnotiz-
ability testing at the treatment visit was ρ = 0.73 (P < 0.001), in line
with known HIP test–retest reliability
30
(0.76). In addition, baseline
HIP scores were not significantly different (U = 679, P = 0.242) between
the active (mean ± s.d. = 4.9 ± 3.4, median = 6, range: 0–10) and sham
(mean ± s.d. = 5.7 ± 3.3, median = 7, range: 0–10) groups. Similarly,
baseline HIS scores were correlated with baseline HIP scores (ρ = 0.51,
P < 0.001) and were not significantly different (U = 790, P = 0.921)
between the active (mean ± s.d. = 3.45 ± 2.76, median = 3, range: 1–10)
and sham (mean ± s.d. = 3.47 ± 2.55, median = 3, range: 1–8) groups.
Within-group Wilcoxon signed-ranks tests indicated that,
although the active group had a statistically significant change in HIP
scores from pre- to immediate post-SHIFT (Z = −3.305, P < 0.001; large
effect size: r = 0.52), the sham group did not show a significant differ-
ence (Z = −0.514, P = 0.607; small effect size: r = 0.08). Based on the
intention-to-treat comparison, ΔHIP scores were significantly greater
in the active SHIFT group compared with the sham group (U = 601,
P = 0.046; small effect size: r = 0.25; Fig. 1). Additionally, there were
no significant differences in pre- to post-SHIFT in HIS ratings between
the groups (U = 702.5, P = 0.412). See Figs. 2–4 for detailed information
about recruitment, target selection and intervention.
Time effects
When tested again approximately one hour post-SHIFT, the pre- to post-
SHIFT difference in HIP (ΔHIP) scores was smaller but still significant in
the active group (Z = −2.336, P = 0.020, medium effect size: r = 0.37) and
not significant in the sham group (Z = −1.898, P = 0.058, medium effect
size: r = 0.30; one participant was missing one-hour post-SHIFT HIP
scores). Although the one-hour post-SHIFT ΔHIP scores were greater
in the active SHIFT group compared with the sham group, the differ-
ence between the groups at one hour post-SHIFT was not statistically
significant (U = 764.5, P = 0.876; small effect size: r = 0.02).
Hypnosis, the first Western conception of psychotherapy
1
, can facilitate
treating and managing a host of psychiatric and neurological symp-
toms
2
. However, not all people respond equally to hypnosis. Hypno-
tizability, an individual’s capacity to respond to suggestions given in
hypnosis, is a stable neurobehavioral trait comprised of cognitive,
neural and behavioral components3,4. Hypnotizability has been dem-
onstrated to moderate the effects of hypnosis-based interventions
5
,
particularly in the reduction of both clinical6 and experimental7 pain.
Approximately two-thirds of the general adult population is estimated
to be at least somewhat hypnotizable, and 15% are highly hypnotiz-
able8, able to manage clinical pain6 and even undergo surgery without
chemical anesthesia using hypnotic analgesia9,10. Hypnotizability has
been shown to be a stable trait in individuals throughout adulthood,
with 0.7 test–retest correlations over a 25 year interval (from a mean
age of 19.5 to 45 years)11. By comparison, test–retest correlations of
personality traits and IQ (intelligence quotient) at corresponding
ages range between 0.51 and 0.62 (ref. 12). Attempts to modulate trait
hypnotizability have been tried for decades. Previous studies have
attempted to modify hypnotic responsiveness using psychoactive
drugs and other pharmaceutical substances, but with little effect
13
.
Further efforts to enhance hypnotizability using behavioral training
approaches
14
yielded inconsistent results
15
and have generally failed to
elicit increases in responsiveness in large numbers of individuals16, with
inconsistent results across different laboratories. Lynn and colleagues
argued that inherent neurocognitive differences between ‘naturally’
high-hypnotizable and low-hypnotizable individuals had been thought
to explain the limits of modifying hypnotizability behaviorally17.
High hypnotizability is associated with altered activations of the
prefrontal and anterior cingulate cortices, although other brain regions
are involved in hypnosis based on task demands18. Responsiveness to
suggestions in hypnosis is a top-down process that is driven primar-
ily by the executive control and salience networks18. Consistent with
this, previous work from our group3 found high hypnotizability to be
associated with increased functional connectivity between the left dor
-
solateral prefrontal cortex (L-DLPFC) and the dorsal anterior cingulate
cortex (dACC), whereas low hypnotizability was associated with low
L-DLPFC–dACC connectivity. Whereas previous neuroimaging findings
centered on the role of the anterior cingulate cortex in responding to
suggestions in hypnosis via its involvement in attentional processes,
a recent systematic review emphasized the complex integration of
high-order cognitive processes in hypnotizability (primarily managed
by frontal brain structures) beyond the attentional component and spe-
cific task demands
18
(for example, as seen in hypnotic analgesia). Dur-
ing hypnosis, the dACC shows reduced activation, while the L-DLPFC
increases its functional connectivity with the insula (a central node of
the salience network) and reduces its connectivity with the posterior
cingulate cortex (a key node in the default mode network)19. Notably,
the involvement of frontal functions in hypnotizability is potentially
moderated by individual differences
20
, emphasizing the benefit for
future research to take a ‘precision medicine’ approach and individual-
ize relevant interventions.
Transcranial magnetic stimulation (TMS) non-invasively modu-
lates neuronal activity and functional connectivity21–23 using a high-
intensity magnetic field to induce a brief, focal electric field in the
cortex that can either activate or inhibit neurons depending on the
pattern of the stimulation approach. Repetitive TMS (rTMS) produces
periods of lasting facilitation or inhibition that persist after stimula-
tion
24
. Inhibitory rTMS applied to the DLPFC, beyond its inhibiting
effects on the DLPFC itself, is associated with decreased DLPFC activity
and increased functional connectivity with the dACC
21,25
. Spaced forms
of a highly efficient form of rTMS, such as continuous theta-burst
stimulation (cTBS), produce more durable changes in cortical excit-
ability26,27. A modified form of cTBS (cTBSmod) is capable of consistently
producing inhibition in the motor cortex compared with conventional
cTBS, which produces these changes inconsistently28.
Nature Mental Health
Article https://doi.org/10.1038/s44220-023-00184-z
Discussion
SHIFT, a novel neuromodulation approach, demonstrated immediate
modulation of hypnotizability—a stable, clinically relevant neurobe-
havioral trait. Building on our group’s previous work on the neural
bases of hypnotizability3,19,31, our results provide further support for a
relationship between the L-DLPFC and hypnotizability, as its inhibition
produced changes in a hypnotizability measure. As hypnotizability was
previously associated with L-DLPFC–dACC functional connectivity
3
,
we chose a neurostimulation approach that has been demonstrated
to inhibit DLPFC activity and increase functional connectivity with
the dACC
21,25
. To modulate the targeted network temporarily, we uti-
lized SHIFT, as convergent data suggest that two spaced cTBS sessions
increase the durability of the cTBS effect over a single cTBS session28.
To address the need for personalized intervention, we targeted the
region of the L-DLPFC with the highest functional connectivity to the
dACC. These findings are also consistent with the predictions of some
theories of hypnosis. For example, the dissociated control theory
32
equated the response to hypnosis to frontal lobe damage, by which
account inhibition of the DLPFC (although not laterally specified) could
result in increased hypnotic response. In addition, updated predic-
tions of the cold control theory of hypnosis
29,33
argue that prefrontal
inhibition will reduce metacognitive awareness of intentions, thereby
increasing the likelihood of successful responsiveness to suggestions
to be experienced as involuntary.
Our approach achieved medium-to-large effect sizes after 92 s of
non-invasive neurostimulation, a notably shorter approach than the
20 min stimulation protocol used in previous studies
29,30
. Whereas the
increase in hypnotizability scores was inconsistent across subjects
(Fig. 1), the effects per unit of time are quite notable. Providing evidence
of a perturbation technique that is capable of transiently modulating
stable traits is quite encouraging, as our technique can be further engi-
neered for the intended effect. Certainly, the large pre–post effect size
(r = 0.52) achieved with our brief SHIFT protocol is in line with the effect
sizes of conventional rTMS for major depressive disorder (MDD), where
10 Hz rTMS is applied over 1,200 min across six weeks
34
. Furthermore,
the open-label effect of this approach is unknown and could be even
larger, given the differences between the controlled and open-label
data in depression34,35. When comparing the effects of SHIFT with the
placebo stimulation, we found a small effect (despite there being no
significant differences in treatment expectancy between the groups or
association of expectancy with a change in hypnotizability), suggesting
that open-label treatments may yield greater effects.
Whereas we did not observe significant pre–post changes in the
subjective experience of hypnotic depth, this may be explained by
the time effects we identified. When compared with the immediately
post-SHIFT results, the change in hypnotizability was not significantly
different between the groups after one hour. This finding suggests that
SHIFT produces a transient effect. As such, future clinical applications
should prioritize scheduling the bulk of post-SHIFT interventions as
close as possible to the stimulation. Nevertheless, given that the HIS
was administered at baseline and approximately one hour post-SHIFT,
if the effects on subjective hypnotic experiences are also transient, we
would not expect a substantial change at this time point.
Lastly, alongside our evidence for the feasibility of altering a stable
neurobehavioral trait through neuromodulation, previous research
has demonstrated the ability to modulate other neurobehavioral traits.
In a small study, Spronk et al.36 observed a significant decrease in trait
neuroticism and an increase in extraversion following 15–25 rTMS ses-
sions applied to the L-DLPFC. The modulation of trait neuroticism was
later replicated by Berlim and co-workers37. This is notable as, beyond
time-dependent changes in trait neuroticism, treatment for depression
largely fails to modulate it
38
. Together with our findings, SHIFT may be
able to modulate clinically relevant neurobehavioral traits associated
with psychopathology and responsiveness to treatment.
Limitations
The interpretation of the current results involves caveats that could
be addressed in future trials. In addition, this trial did not assess any
outcome measures involving the modification of disease symptoms
as this was designed to be a mechanistic study; future studies should
build on these findings to evaluate the use of the neuromodulation of a
neurobehavioral trait to assess clinical outcome measures in a patient
population directly. Although HIP assessors were blind to intervention,
their blinding was not evaluated via a questionnaire, as was done with
Table 1 | Participant characteristics
Active group (n=40)
n (%) Sham group (n=40)
n (%)
Gender 39 (97.5%) female 36 (90.0%) female
Race/ethnicity
White/of European descent 30 (75.0%) 27 (67.5%)
Hispanic 3 (7.5%) 7 (17.5%)
Asian 6 (15.0%) 3 (7.5%)
African American/Black 0 (0.0%) 1 (2.5%)
Native American/Paciic Islander 1 (2.5%) 1 (2.5%)
Other 0 (0.0%) 1 (2.5%)
Education (highest)
Obtained/pursuing graduate
degree 7 (17.5%) 11 (27.5%)
Some graduate school 3 (7.5%) 4 (10.0%)
Completed college 9 (22.5%) 10 (25.0%)
Some college/two-year college 17 (42.5%) 7 (17.5%)
Completed trade school 1 (2.5%) 4 (10.0%)
Completed high school/GED 1 (2.5%) 1 (2.5%)
Less than high school 1 (2.5%) 1 (2.5%)
Did not report 1 (2.5%) 2 (5.0%)
Age (mean±s.d.) 47.8±13.5 48.8±11.5
GED, General Education Diploma.
2
–2
∆HIP
Sham Active
0
Fig. 1 | ΔHIP scores comparing baseline with immediately post-SHIFT in
the active (n = 40) and sham (n = 40) groups. Individual ΔHIP points are
presented in blue if increased, red if decreased or gray if there was no change
from baseline to post-SHIFT. Immediate ΔHIP scores showed a significant
difference from baseline in the active SHIFT group but not in the sham group.
Similarly, ΔHIP scores were significantly greater in the active SHIFT group
than in the sham group. Four participants (two in each group) had ΔHIP scores
of >3. The center lines represents the median; the boxes represent the 25th
and 75th percentiles; the error bars represent outlier estimation based on
1.5 × interquartile range.
Nature Mental Health
Article https://doi.org/10.1038/s44220-023-00184-z
In-person screening (n = 157)
Excluded (n = 56)
Did not meet inclusion criteria (n = 52)
Declined to participate (n = 3)
Unusable MRI (n = 1)
Analyzed (n = 40)
Excluded from analysis (n = 0)
Received sham intervention (n = 40) Received active intervention (n = 40)
Analysis
Randomized (n = 101)
Complete online interest survey (n = 1,058)
Unable to be reached (n = 770)
Excluded (n = 131)
Completed after enrolment closed (n = 60)
Did not meet inclusion criteria (n = 49)
Declined to participate (n = 16)
Duplicate survey entries (n = 6)
Intervention
Enrolment
Analyzed (n = 40)
Excluded from analysis (n = 0)
Allocation
Allocated to sham treatment (n = 52)
Excluded pre-collection (n = 12)
Decided to withdraw from study (n = 5)
Severe anxiety (n = 1)
Positive toxicology screen (n = 2)
Claustrophobia (n = 2)
Non-compliance (n = 2)
Baseline data collection (n = 40)
Allocated to active treatment (n = 49)
Excluded pre-collection (n = 9)
Decided to withdraw from study (n = 6)
Claustrophobia (n = 2)
Non-compliance (n = 1)
Baseline data collection (n = 40)
Fig. 2 | Recruitment CONSORT diagram. The diagram shows a summary of the number of participants who showed interest, underwent screening and were recruited,
randomized and analyzed.
Fig. 3 | Intervention day summary. The timeline of study events included the
participants undergoing a one-hour baseline MRI scanning session in which
both structural and functional MRI sequences were completed. These magnetic
resonance images were then used to individually target the TMS (SHIFT)
treatment. Participants then received either active or sham SHIFT targeted to the
L-DLPFC. Hypnotizability was assessed pre-SHIFT, immediately post-SHIFT and
one hour post-SHIFT using the HIP.
Nature Mental Health
Article https://doi.org/10.1038/s44220-023-00184-z
the participants. Moreover, future studies could benefit from assessing
the attitudes of participants towards hypnosis to understand potential
contextual factors further.
Even though we showed that this trait could be modulated with
SHIFT in this population, lower baseline connectivity in our fibromyal-
gia syndrome (FMS) sample may render hypnotizability enhancement
via this route rather challenging. Persons who are innately more highly
hypnotizable show greater functional connectivity between the DLPFC
and the dACC3, and conditions that influence connectivity, such as
fibromyalgia, may influence the degree to which the trait may be modu-
lated
39
. As such, depending on the underlying neuropathophysiology
of the intended condition, alternative neurostimulation models may
be warranted to enhance hypnotizability.
The results achieved in this study provide evidence that hypnotiz-
ability, a stable neurobehavioral trait, can be directionally and measur-
ably modulated using non-invasive brain stimulation. Further studies
are needed to build on these findings to assess the dose–response
relationships of SHIFT as well as the added efficacy of functional con-
nectivity magnetic resonance imaging (MRI) targeting. Furthermore, to
better understand the individual elements driving mechanistic change
in neurobehavioral traits, future neuromodulation trials are needed
to further explore the parameter space within the current technique
with the aim of optimizing the dosing as a method for modulating the
neural circuitry underlying trait-based disorders as well as enhancing
trait-based interventions.
Lastly, future studies should examine other targeted neuro-
stimulation approaches to test different stimulation mechanisms. A
more portable yet less personalized, more dispersed neurostimula-
tion approach, transcranial direct current stimulation (tDCS)40–42,
could also be used to generate an increase in hypnotizability43, albeit
requiring 18 min of stimulation. In addition, neither TMS nor tDCS can
stimulate deeper hypnotizability-related circuits, such as the dACC,
directly. An emerging non-invasive brain stimulation approach that
can be individually targeted based on neuroimaging data is transcra-
nial focused ultrasound (or tFUS), which has been demonstrated to
successfully target the anterior cingulate cortex in both animal44 and
human45 studies and may offer a viable solution.
Methods
Participants
To test our hypotheses in a clinical population that is likely to benefit
from a temporary increase in hypnotizability, we recruited individuals
with FMS46, a central pain disorder of unclear etiology and mechanism
that affects up to 8% of the general population
47
. Hypnosis-based
treatments have shown success in pain management for patients with
FMS48, and hypnotic pain reduction is sensitive to hypnotizability6.
In FMS, functional connectivity is altered in the salience network and
the default mode network, both of which are involved in hypnosis19.
Hyperactivity in the endogenous opioid system in FMS renders opioid
medications less effective in reducing pain49,50, making FMS a prime
candidate for non-pharmacological interventions. As such, low to
moderately hypnotizable male and female participants with FMS
aged 18–69 years were recruited for this study starting in February
2017, with both recruitment and data collection reaching the targeted
enrolment number in December 2019 (the trial was registered on
ClinicalTrials.gov (NCT02969707)
51
; see Fig. 2 for the Consolidated
Standards of Reporting Trials (CONSORT) recruitment diagram). The
study was approved by the Stanford University Institutional Review
Board; all participants provided informed consent and all enroled
participants were financially compensated. Before enrolment, par-
ticipants underwent phone and in-person screening procedures
to determine their eligibility. Hypnotizability was assessed during
the in-person screening by trained study personnel using the HIP
(see below). Low to moderately hypnotizable individuals (with a HIP
score of ≤8 out of 10) were eligible to participate in the study, and
highly hypnotizable individuals (with a HIP score of >8 out of 10)
were excluded after the screening appointment. All participants had
a primary diagnosis of FMS, which a study clinician confirmed during
the in-person screening. Diagnostic criteria were determined based
on the American College of Rheumatology preliminary diagnostic
criteria for FMS
52
, and participants provided results of a blood test
completed within a year to confirm a normal complete blood count
and inflammatory panel (including a complete blood count with dif-
ferential, the erythrocyte sedimentation rate (ESR) and a metabolic
panel; to exclude evidence from potential comorbid rheumatologic
conditions). Participants who did not have a recent blood test com-
pleted this as part of the study screening visit. Exclusionary criteria
included standard MRI contraindications (for example, ferromagnetic
implants or claustrophobia), contraindications to TMS as measured
by the TMS Adult Safety Screen, neurological disorders (for example,
seizure disorder) and serious primary psychiatric disorders that,
when present, could necessitate a psychiatric hospitalization. These
comorbid psychiatric disorders included psychotic disorders, bipolar
disorder, post-traumatic stress disorder with suicidal ideation and
severe MDD with suicidal ideation (dysthymia, mild to moderate
MDD and anxiety disorders were not exclusionary). Participants
with FMS currently prescribed psychoactive medications underwent
a voluntary washout period before neuroimaging and TMS (that
is, a five-week washout for fluoxetine and a two-week washout for
all other antidepressant medications; the washout periods were
designed based on half-life values and were individually tailored to
the participant by their prescribing physician). If participants were
unable to see their prescribing physician, a study physician oversaw
this medication washout. To assure blinding, only participants with
no previous exposure to TMS were eligible for the study.
Neuroimaging for transcranial magnetic stimulation
targeting
MRI data were collected using a research-dedicated 3.0T Discovery
MR750 instrument (General Electric) with a 32-channel head coil (Nova
Medical). Individualized neuroimaging for subsequent TMS targeting
consisted of both structural and functional MRI sequences.
Personalized L-DLPFC targets were generated for each participant
using resting-state functional MRI (fMRI) hierarchical clustering to
determine the anatomical location within the L-DLPFC that exhib-
ited the greatest functional connectivity to the dACC (Fig. 4). The
dACC region of interest (ROI) was based on a previous coordinate-
based meta-analysis aimed at determining the areas of the brain most
Baseline HIP
Baseline MRI TMS fMRI
Screening
Immediate
post-TMS HIP
One hour
post-TMS HIP
Fig. 4 | Personalized neurostimulation targets. Personalized L-DLPFC
neurostimulation targets (blue) for all participants were used in comparison with
the commonly used Beam F3 skull-based measurement coordinates (−35.5, 49.4,
32.4). Although shown here in Montreal Neurological Institute standard space for
illustration purposes, individual targets were analyzed and identified in native
subject space representing the greatest L-DLPFC–dACC functional connectivity.
Nature Mental Health
Article https://doi.org/10.1038/s44220-023-00184-z
functionally relevant to hypnotizability31. This general approach was
previously reported in a clinical trial using the Stanford Accelerated
Intelligent Neuromodulation Therapy for the treatment of depres-
sion53 and subsequently validated in a follow-up study54. Resting-
state fMRI scans were acquired over ~8.5 min using a simultaneous
multi-slice echo-planar imaging (EPI) sequence with the following
parameters: time to echo (TE) = 30 ms, repetition time (TR) = 2,000 ms,
flip angle = 77°, slice acceleration factor = 3, matrix = 128 × 128,
1.8 × 1.8 mm in-plane resolution, slice thickness = 1.8 mm, field of
view (FOV) = 230 × 230 mm and 87 contiguous axial slices—see Sup-
plementary Information for a detailed description of the target
generation method.
Transcranial magnetic stimulation
Participants were randomized using a permuted-block design with
varying block sizes to receive either sham or active cTBS, an effi-
cient form of rTMS that is capable of producing inhibition of corti-
cal excitability in the motor cortex
26,28,55
. Stimulation was delivered
using a MagPro X100 system (MagVenture) with a Cool-B65 A/P coil.
Specifically, we utilized a modified form of cTBS (termed SHIFT)
applied in a spaced manner with two applications of ~46 s that were
each comprised of 800 pulses, 200 pulses for ramping up slowly
with 600 pulses at full intensity, delivered in a continuous train
with each burst containing three pulses at 30 Hz repeated at 6 Hz
(refs. 28,56).
Following the application of spaced SHIFT, participants were asked
to refrain from discussing information pertaining to the subjective
stimulation experience (for example, discomfort, facial movement
or scalp sensation) with study personnel, including those conducting
HIP assessments. Study personnel (not conducting behavioral assess-
ments) administered a questionnaire to assess participant blinding
after cessation of stimulation for the day, which included a binary ques-
tion of whether they thought they received active or sham stimulation.
See Fig. 3 for a neurostimulation summary.
Study objectives
This study addresses the hypnotizability-related outcomes of Sec-
ondary Objective B, testing the study’s behavioral hypotheses, which
include a change in hypnotizability—the key behavioral variable in
the project—to determine the effect of active, inhibitory rTMS (cTBS)
over the L-DLPFC on enhancing the hypnotizability and the subjective
experience of hypnosis (that is, hypnotic intensity). Secondary out-
come measure 2 in the preregistered protocol is one of five secondary
objectives, which are to determine the effect of active, inhibitory cTBS
over the L-DLPFC on (1) the neural network that underlies hypnosis
phenomena, (2) hypnotizability, (3) the neural network that underlies
conflict regulation, (4) the neural network that underlies hypnotic
modulation of the Stroop effect and (5) the neural network that under-
lies hypnotic analgesia.
Measures
Hypnotic induction proile. The HIP is a validated measure of hypno-
tizability2,57; it includes a standardized hypnotic induction followed by a
set of specific suggestions. The HIP is scored by the administering clini-
cian based on behavioral responsiveness and reports of the examinee’s
subjective experience. HIP scores range from 0 (no responsiveness) to
10 (most responsive), with scores above 8 representing highly hypno-
tizable individuals. In the current study, the HIP was first administered
immediately before L-DLPFC stimulation, immediately following the
SHIFT stimulation and then again after the MRI, approximately one
hour following SHIFT stimulation. To ensure assessor blinding, asses-
sors waited and completed the HIP in a room that was separate from
where the TMS machine and the stimulation took place. Furthermore,
participants were requested not to share information about the stimu-
lation with the assessors.
Hypnotic intensity scale. The HIS is a single self-report scale of 1–10
of the perceived ‘depth’ of the hypnotic experience during the fMRI
hypnosis task19, ranging from ‘not hypnotized at all’ (1) to ‘deeply hyp-
notized’ (10). The HIS is rated in hindsight after participants completed
their MRI scans. As such, whereas baseline HIS was administered imme-
diately before the baseline HIP, the post-SHIFT HIP was administered at
the end of the second MRI scan (approximately one hour post-SHIFT).
The HIS is not a standardized scale and has been described by other
names (for example, hypnotic depth scale or Long Stanford Scale)
58
.
Here we used the scale as described by Deeley et al.
58
and utilized in
our previous work19.
Data analysis
Data were collected and organized using the REDCap methodology59,
and analysis was performed in the SPSS v.26.0 environment
60
. Accord-
ing to our preregistered plan, analyses were completed within the
intention-to-treat principle, and reported P values are nominal. To test
the change in HIP scores following SHIFT, pre- to post-SHIFT changes in
HIP scores (ΔHIP) were calculated by subtracting the immediate post-
spaced SHIFT score from the pre-spaced SHIFT score. Neither the pre-
or post-spaced SHIFT HIP variables nor the ΔHIP scores met the criteria
for the assumption of normality (all Shapiro–Wilk P values < 0.001),
rendering the first step in our preregistered plan of testing our hypoth-
eses using analysis of variance (ANOVA) inappropriate. As such, we
used non-parametric tests; within-group pre/post-SHIFT changes in
HIP scores were tested using a two-tailed Wilcoxon signed-rank test.
Two-tailed Mann–Whitney U-tests were used for group comparisons
of ΔHIP scores between the active and sham groups. Effect sizes for the
non-parametric tests were calculated using Cohen’s r statistic
61,62
. The
study blind was tested using the chi-squared test.
Reporting summary
Further information on research design is available in the Nature Port-
folio Reporting Summary linked to this article.
Data availability
Owing to the sensitivity of psychiatric patient data, the Stanford Uni-
versity Institutional Review Board requires individualized review before
the sharing of data. We have produced anonymized data related to
the present findings for sharing with all scientists, where the research
plans and data-safeguarding plans comport with Stanford University
guidelines. Data-sharing requests should be directed to the corre
-
sponding authors.
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Acknowledgements
This work was supported by the National Institutes of Health (NIH)
Center for Complementary and Integrative Health (NCCIH) grant
Innovation Award for Mechanistic Studies to Optimize Mind and Body
Interventions (R33AT009305–03; D.S. and N.R.W.). This trial was
preregistered on ClinicalTrials.gov (NCT02969707). We thank
K. Sudheimer for his technical assistance.
Author contributions
A.F., J.H.B., K.H.S., N.R.W. and D.S. contributed to project
administration, writing, data curation and investigation. A.F. and B.J.
contributed to formal analysis, validation and revision. J.H.B., K.H.S.,
D.D.D., E.K., N.R.W. and D.S. contributed to conceptualization and
methodology. A.P., M.G., H.A., R.N. and A.D.G. contributed to data
curation and investigation. All authors contributed to the writing of
this paper.
Competing interests
N.R.W. is a named inventor on Stanford-owned intellectual
property relating to accelerated TMS pulse pattern sequences and
neuroimaging-based TMS targeting; he has served on scientiic
advisory boards for Otsuka, NeuraWell, Magnus Medical and Nooma
as a paid advisor; he also has equity/stock options in Magnus
Medical, NeuraWell and Nooma. There were no inancial conlicts
during the conduct of the trial or analysis of the data in this Article.
D.S. is a co-founder of Reveri Health, Inc., an interactive hypnosis
app (not utilized in the current study). A.F. is a consultant for Reveri
Health, Inc. The other authors declare no competing interests.
Additional information
Supplementary information The online version contains supplementary
material available at https://doi.org/10.1038/s44220-023-00184-z.
Correspondence and requests for materials should be addressed
to Nolan R. Williams or David Spiegel.
Peer review information Nature Mental Health thanks Bence Pali,
Vilfredo De Pascalis and the other, anonymous reviewer(s) for their
contribution to the peer review of this work.
Reprints and permissions information is available at
www.nature.com/reprints.
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Open Access This article is licensed under a Creative Commons
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© The Author(s) 2024
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA. 2Department of Psychology, Palo Alto University, Palo Alto,
CA, USA. 3United States Department of Veterans Affairs, Palo Alto, CA, USA. 4Department of Neurology and Neurological Sciences, Stanford University,
Palo Alto, CA, USA. 5These authors contributed equally: Aik Faerman, James H. Bishop, Katy H. Stimpson. 6These authors jointly supervised this work:
Nolan R. Williams, David Spiegel. e-mail: nolanw@stanford.edu; dspiegel@stanford.edu
Aik Faerman 1,5, James H. Bishop1,5, Katy H. Stimpson1,2,5, Angela Phillips1,3, Merve Gülser 1, Heer Amin1,
Romina Nejad1, Danielle D. DeSouza4, Andrew D. Geoly1, Elisa Kallioniemi 1, Booil Jo1, Nolan R. Williams 1,6 &
David Spiegel 1,6
1
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Corresponding author(s): Afik Faerman
Last updated by author(s): Jul 28, 2023
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Recruitment Recruitment was done via online advertisement, local flyers at the Stanford Medical School clinics, and at community events.
Participants were individuals with fibromyalgia syndrome (following the American College of Rheumatology Preliminary
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Study description Preregistered, double-blinded, randomized controlled trial (quantitative).
Research sample A random sample of patients with fibromyalgia syndrome (FMS), a functional pain disorder for which hypnosis has consistently been
shown to be beneficial as a nonpharmacological treatment option. All participants were TMS-naïve.
Sampling strategy Preregistered, double-blinded, randomized controlled trial. Power was calculated for main hypothesis of greater pre/post-rTMS
change in a neurobehavioural trait (hypnotizability) in the active (experimental) compared to sham (control) stimulation.
Data collection Data were collected by trained assessors on pen & paper, then coded on REDCap data management system. Data analysis was done
in SPSS V.26.
Timing Data were collected between February 2017 and December 2019.
Data exclusions No data were excluded from the analyses.
Non-participation Overall, 101 participants were recruited, and 21 participants did not complete the full study protocol. A detailed COSORT diagram is
provided in the manuscript (Figure 2).
Randomization Participant were randomly allocated to either Active (experimental) or Sham (control) simulation groups. Assessors, participants, and
statisticians were all blinded to group assignment. Only TMS technicians were not blinded to group assignment (they entered either
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Clinical trial registration ClinicalTrials.gov NCT02969707
Study protocol Available on ClinicalTrials.gov.
Data collection Data were collected at Stanford University between February 2017 and December 2019.
Outcomes This study addresses the hypnotizability-related outcomes of Secondary Objective B, one of five secondary objectives in the
preregistered protocol.
