Effects of Expectations on Negative Affect, Perceived Cognitive Effort, and Pain
Phase: NA
Conditions: Placebo, Expectations
Sponsor: Trustees of Dartmouth College

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Effects of Expectations on Negative Affect, Perceived Cognitive Effort, and Pain  
 
NCT05425563  
 
Study IRB Protocol 
 
January 20, 2022 
 
 

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TITLE:  Individualized spatial topology in functional neuroimaging 
 
PRINCIPAL INVESTIGATORS (MPI):  
Name: Tor Wager 
Address: Psychological and Brain Sciences, HB 6207, Dartmouth College, Hanover, NH 03755   
Telephone: 303-398-1069 
Email: tor.d.wager@dartmouth.edu 
 
Name: Martin Lindquist 
Address: 615 N. Wolfe Street, Room E3634, Baltimore, MD 21205      
Telephone: 410-614-5107; 410-955-0958 
Email: mlindquist@jhu.edu 
I. 
OBJECTIVES 
Here we aim to develop a new functional alignment method for fMRI that both improves inter-
subject alignment and allows for topological inference. We will apply the methods to create a 
library of population-level reference spaces for task states and behaviors drawn from multiple 
psychological domains, and compare multivariate predictive models developed on data 
referenced to anatomical vs. functional reference spaces. This endeavor has two benefits critical 
to the field. First, it will greatly enhance the accuracy of machine learning-based models of 
psychological states and behaviors. Second, it will provide a way to analyze inter-task and inter-
individual differences in the spatial topology of brain activation, providing statistical inferences 
about the location and shape of activated regions. Like existing methods, the approach aligns 
individual functional maps to a common set of functional population-level reference spaces. 
However, we align single-participant activation images based on topological properties rather 
than representational reference space.  
We will develop topological models purpose-designed for fMRI activation and inter-subject 
functional alignment, and develop methods and software for topological inference. We will 
develop and compare two approaches. First, our research team has successfully developed 
explicit models of spatial topology in structural data, based on the use of the nonlinear large 
deformation diffeomorphic metric mapping (LDDMM) algorithm, which allows shape variation to 
be uniquely encoded by a deformation field normal to the outline of the template. This algorithm 
is specifically designed to accomodate deformations while retaining the topology of the object 
(i.e., structure preserving). Our models have inspired other anatomical diffeomorphic toolboxes, 
such as SPM’s ‘DARTEL’ anatomical registration tool [88]. We propose to extend the LDDMM 
algorithm to allow for functional alignment. Local differences in the amount of transformation 
needed for different regions will be studied and compared across experimental tasks. LDMM 
provides us with geometric information regarding the spatial transformations required to align a 
functional activation image to the population-level functional reference. This information will be 
used for analyzing the population variability of brain anatomy and functional activation maps, 
through the Jacobian determinant of the deformation field.  
In a second, alternative approach, we will construct spatial models of the relative misalignment 
of the individual-subject functional images with respect to a latent activation template map based 
on the use of 3D Gaussian processes [89, 90], which models activation (or other variables) with 
Gaussian functions whose parameters vary continuously over time or space. The fully Bayesian 
formulation of the model will enable inference on the latent surface via posterior samples. 
Importantly, these two models will allow us to test several types of hypotheses fundamental to the 

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endeavor of brain mapping and cognitive neuroscience: (a) Is the extent of activation in a task 
confined to the boundaries of an anatomical region, or does it extend into neighboring regions? 
(b) Is activation for one task located in a significantly different location to activation for another 
task? (c) Do two tasks activate the same region, but with significantly different activation topology 
(i.e., shape), suggesting activation of different subregions or local circuits? (d) Do individuals vary 
in the location and/or pattern of local activation in a task, and how much of the observed 
differences are reliable individual differences vs. noise? (e) Is local activation best characterized 
by a single activation location with spread/blurring, or multiple, distinct local activation peaks? 
These tests formalize many of the concepts brain mapping researchers want to test in order to 
understand brain structure-to-function mapping. They also formalize inferences about the utility 
of multi-voxel pattern maps that are currently assumed—in particular, that the local topological 
pattern is reliable and carries more information than the voxelwise activation magnitudes.  
Here, we will test and validate the methods in an experiment (n = 150) that includes naturalistic 
narrative experiences (movies) and tasks from three functional domains (pain, emotion, and 
cognition). These tasks are designed to elicit specific brain responses, which will be utilized to 
construct a more sophisticated functional alignment for specific brain activation.  
II. 
BACKGROUND AND SIGNIFICANCE  
Neuroimaging is poised to take a substantial leap forward in understanding the 
neurophysiological underpinnings of human behavior. This is due in part to the combination of (a) 
improved analytic techniques, including machine learning and related pattern-recognition 
algorithms [1-8] and (b) improved data quality, particularly the increasing spatial resolution of 
functional Magnetic Resonance Imaging (fMRI) data [9-11]. These advances permit researchers 
to develop brain models of the functional representations underlying behavior, performance, 
clinical status and prognosis, and other outcomes. Most such models take the form of multivariate 
patterns of brain activity and connectivity (e.g., Preliminary Data in Figure 1). If such ‘signatures’ 
are generalizable across individuals, i.e., they predict outcomes in new, out-of-sample 
participants, they constitute population-level models—also called ‘signatures’, ‘neuromarkers’, or 
biomarkers in the literature—that can be shared and rigorously tested across laboratories [12-19].  

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Such models have multiple advantages. They constitute research products that can advance 
the cumulative science of brain function by testing their generalizability, sensitivity, and specificity 
for particular behaviors, mental events, and other outcomes across a widening circle of 
laboratories and conditions [6]. Because they make strong, quantitative predictions about 
outcomes, they can be falsified (in the 
Popperian sense [20]), refined, and improved. 
In addition, distributed models are suited for 
capturing 
information 
represented 
in 
distributed neural population codes, which 
recent studies show are critical for many 
aspects of cognition and behavior [21-27]. 
Because they can capture pattern information 
[28-30] within and across regions at multiple 
spatial scales, they have yielded signatures 
that 
predict 
stimulus 
conditions 
and 
experiences like pain and emotion with large 
effect sizes, which can increase statistical 
power in fMRI studies by an order of 
magnitude [31, 32] (e.g., d = 3.3 in Figure 1 
vs. average d = ~0.5 for single voxels [33]). 
We view the development of population-level 
models of clinically relevant outcomes as a 
critical step towards both understanding the 
functional anatomy of brain disorders and 
developing brain-based measures useful in 
translational contexts [6]. We also view such 
models as critical for understanding the brain 
representations underlying basic cognitive 
and emotional processes.  
Promising advances towards population-
level models have been made for many 
categories of clinical conditions (for reviews, 
see [6, 15, 34]), and such models have been 
used to successfully predict task states 
and/or performance on non-clinical and pre-
clinical outcomes [35-38]. However, much 
work remains, as most models have not been 
truly tested prospectively on independent 
cohorts of participants; in a recent review of 
nearly 500 papers using population-level 
machine learning-based models, predictive 
accuracy was tested on independent cohorts 
in only 9% of cases [6]. Accuracy for those 
models averaged around ~80% for patient 
vs. control discrimination (chance ~50%), 
arguably not high enough to be useful in 
translational 
settings. 
Our 
collaborative 
group (PI Lindquist and Co-I Wager’s labs) has been actively involved in developing such 
population-level models [38-45] (Figure 1), and accordingly, we have focused on testing 
prospectively in new samples and evaluating generalizability across scanners, task variants, 
ethnic/racial groups, and cultures. In sum, population-level multivariate brain models offer an 
exciting way to make and test strong, quantitative predictions about clinical and basic outcomes, 
and thereby understand the brain representations involved. But we clearly need ways of improving 
Figure 1. Two population-level predictive models.  A) Top: Signature 
predicting pain intensity elicited by painful heat.  Bottom: Signature 
predicting intensity of negative emotion elicited by aversive images. 
Both involve areas associated with “negative affect,” including dorsal 
anterior cingulate, insula, and amygdala. However, the patterns of 
activity that are predictive within these regions are different (spatial r = 
0.04).  B) Prospective application of the two signatures to independent 
data from new samples.  The Pattern Response (y-axis) is calculated as 
the dot product of the signature with input images from out-of-sample 
participants, yielding a single weighted average response.  Top: Pain 
signature responses predict increases in pain across levels of painful, 
but not non-painful, heat (x-axis) and closely track reported pain (not 
shown).  Bottom: Emotion signature responses track increases in 
reported negative emotion. C) The emotion signature classifies negative 
from neutral pictures in an independent sample (N = 60), with a large 
effect size (Cohen’s d = 3.3). Each line connecting a pair of dots 
represents a participant. D) Variance explained in emotion ratings by 
patterns within individual regions and the whole-brain signature. ACC is 
the dorsal anterior cingulate, and searchlight is the (optimistically 
biased) highest single region across the brain. The superior 
performance of the whole-brain signature indicates that multiple regions 
are required to accurately predict emotion from brain activity. 

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the models’ performance. Here, we identify two fundamental obstacles impeding progress in 
the field, namely the problem of individual variation in functional brain anatomy and the lack 
of formal statistical spatial inference in fMRI analysis, which motivate the new methods we 
propose.  
I. The problem of inter-subject variability in functional anatomy. Current standard 
practice is to use nonlinear transformations to warp individual participants’ anatomical data to an 
average, anatomically based 3D reference space (e.g., “Montreal Neurologic Institute” (MNI) 
space). Those transformations are then applied to functional data. Though individual-subject, 
whole-brain fMRI data can now be collected at a resolution of 2 mm3 ‘voxels’ or smaller, once 
functional maps are combined across individuals to construct a population-level model, the 
effective resolution is dramatically lower. This is largely due to inter-subject variability in the 
location and distribution of functional regions relative to anatomical landmarks (Figure 2).  
Large inter-individual differences in both brain anatomy and functional localization after 
anatomical alignment [46-63] are a major limitation in conducting group analyses and population-
level inference. For example, primary visual cortex (V1) can vary in size by as much as 2-fold 
across different subjects’ brains [53] and in location relative to other anatomical landmarks [47], 
as can sulcal locations [56]. In some cases, inter-individual differences can be accounted for by 
nonlinear warping into a common anatomical reference space, but in other cases they cannot. 
For example, the cingulate sulcus is structurally dimorphic [60]—a substantial minority of 
individuals possesses a double cingulate sulcus—precluding anatomical alignment using current 
methods. In addition, considerable variability in functional localization persists even after 
anatomical alignment [47, 49, 62, 63]. For example, the location of visual motion-sensitive area 
MT can vary by more than 2 cm. The location and extent of lateral occipital cortex (LOC; [50]) and 
fusiform face area (FFA; [46, 51]) are also highly variable across individuals and located in 
different places relative to anatomical sulcal landmarks (see Figure 2). Accordingly, functional 
connectivity is also variable across individuals even after anatomical alignment, with the greatest 
variability in areas showing significant expansion in humans relative to monkeys [52]. Such 
variability dramatically decreases the spatial resolution and precision of population-level brain 
mapping, as features will not be properly aligned for subsequent statistical analysis. 
 

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Recent approaches have sought to circumvent this problem by mapping individual brains into 
a functional population-level reference space rather than an anatomically based brain space. The 
first such model is the ‘hyperalignment’ procedure [64], Here brain activity patterns corresponding 
to stimuli and other cognitive events are represented as vectors in a neural representational 
space spanned by the voxels in a local neighborhood. Hyperalignment rotates each participant’s 
local voxel-wise activity patterns through multivariate voxel space using a Procrustes 
transformation to align the representational geometry across subjects. Mathematically, this is 
similar to Canonical Correlation Analysis (CCA). A number of refinements of hyperalignment have 
recently appeared, including: kernel hyperalignment [65] which performs nonlinear 
hyperalignment in an embedding space; regularized hyperalignment [66] which uses a ridge CCA 
formulation; the two-phase joint SVD-Hyperalignment algorithm [67], where singular value 
decomposition (SVD) provides a lower dimensional feature space where hyperalignment is 
applied; the shared response model [67] which casts the model in a probabilistic framework; and 
searchlight hyperalignment [68] which allows for whole-brain coverage. Other methods have been 
developed that align subjects based on inter-subject correlations in time-series data during movie 
viewing. One method is functional time series alignment (FTSA) [69], which matches voxels 
across subjects using a 2D ‘rubber sheet’ warping and maximizing inter-subject correlations 
across voxels [70]. Another is functional connectivity alignment (FCA) [71], which matches voxels 
to a functional reference by minimizing the Frobenius norm of the difference between a subject’s 
connectivity matrix and a reference matrix with a shape-preserving penalty function. Both 
methods use warping and penalization strategies specific to the cortex, so it is unclear how easily 
they can be adapted to include subcortical regions.  
This body of work shows great promise for allowing participants to vary in their functional 
activation patterns [64], but suffers from several shortcomings. First, hyperalignment requires 
subjects to watch a long film (up to 2 hours) to align subjects into a common representational 
space, and functional connectivity-based methods require substantial resting state data. Second, 
the choice of reference data (movie or rest) influences which types of functional patterns can be 
appropriately aligned. For example movie reference data works well for audio-visual 
representations but not prefrontal and limbic networks. Functional connectivity-based measures 
work better for limbic cortex, but are expected to perform more poorly on object and semantic 
representations. Neither type of method has been tested on subcortical representations, or on 
clinically relevant functions such as pain and emotion. Third, these methods do not include an 
explicit spatial model able to make inferences on the location or extent of activation, though a few 
recent studies have taken steps in this direction [72]. Indeed, hyperalignment is designed to 
preserve inter-item similarity at the cost of topology.  
II. The lack of formal statistical spatial inference in fMRI analysis. Topological models 
that explicitly model the shape and extent of fMRI activation are a crucial advance for the field, 
but examples are rare in the literature (cf. [73-78]). Such models are needed to make inferences 
about where brain activation is located, or if two subjects/tasks activate significantly different 
locations. Major packages (e.g., SPM, FSL, AFNI) provide no way of making such inferences. 
While standard voxel-wise brain mapping give the illusion that activation is being localized, they 
only test the magnitude of activation in a given location, providing maps of locations above a 
threshold (Figure 2). They do not provide inferences about where spatial boundaries of activation 
lie, or whether two tasks activate significantly different locations. This has caused substantial 
confusion in the field. Likewise, the use of cluster extent thresholding doesn’t provide spatial 
inferences. They simply test the null hypothesis that the extent of activation is larger than expected 
by chance [79]. This permits one to conclude there is signal somewhere in the region deemed 
active, but provides no information about spatial boundaries of activation [80]; in fact, they 
produce invalid results when used to infer the boundaries of spatial extent [80]. Finally, most 
packages use ad hoc algorithms for finding peak activation locations, which are routinely used to 
define regions of interest and conduct meta-analyses. But these algorithms provide no inference 
about variability in those locations. Peak locations are unstable and vary widely across individuals 
[71], studies [81-83], and analysis methods [84] (Figure 2). Likewise, they provide no inference 

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about whether there is a single or multiple distinct, local peaks. The lack of spatial inferences is a 
major impediment to progress in the field. 
III. 
PRELIMINARY STUDIES  
Over the past 5 years, our team47-52 and others53-58 have pioneered a new paradigm for studying 
the brain, grounded in building models of how brain regions and systems work together to 
create cognitive and affective states. Such models make quantitative, testable predictions about 
mental states that can be validated or falsified. The approach is grounded in three pillars: (i) the 
use of multivariate pattern-recognition techniques to develop brain models predictive of mental 
states; (ii) assessment and optimization of the models’ diagnostic value; and (iii) a program of 
initially broad exploration followed by increasingly rigorous assessment of generalizability 
across samples, research contexts and populations59. We have generated several preliminary 
findings (see Figure 1) that we hope to extend through this proposal by improving methods for 
aligning spatial topology in neuroimaging. 
IV. 
RESEARCH STUDY DESIGN  
N=150 participants will be recruited as outlined in the  “ABOUT THE SUBJECTS” section in this 
protocol). Considering that a possible dropout rate for behavioral studies is around 20%, and 
that we need at least 100 participants’ data to gain sufficient power, we need 150 participants. 
Based on our previous experience we expect data collection to last for approximately 18 
months. 
 
The experiment has the following 4 separate fMRI sessions (see figure 3), each at least one day 
apart, taking place at the Dartmouth College Brain Imaging Center fMRI scanner in Moore Hall, 
Hanover, NH. Below is an outline of the sessions and tasks; for a detailed description of each 
session and tasks, see Procedures section.  
 
 
  
 
This study will consist of 4 separate fMRI sessions. The sessions will include a period of time 
before the scan in which participants will become familiar with the tasks.  
 
Prior to Sessions (1 hour) 
1. Participants will be given a link to access surveys that will be filled out prior to coming in 
for their first session.  
 
Figure 3. 

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Session 1 procedures (~2.75 hours):  
 
1. Prior to scanning (1.25 hours) 
a. MRI screening form 
b. Bartoshuk scale practice 
c. Pain familiarization and site selection 
d. Practice tasks 
i. Social influence task explanation and familiarization 
ii. Video ratings explanation and familiarization, and practice ratings 
e. Preparation for fMRI scan 
 
2. fMRI tasks (1.5 hours) 
a. Social influence task  
b. Video compilation task  
c. Structural scan  
d. Diffusion Tensor Imaging (DTI) scan 
 
Session 2 procedures (~2.75 hours): 
 
1. Prior to scanning (1.25 hours) 
a. MRI screening form 
b. Instructions and practice tasks 
c. Preparation for fMRI scan  
 
2. fMRItasks: narrative task, face task, and video compilation task (1.5 hours)  
 
 
Session 3 procedures (~3.25 hours):  
 
1. Prior to scanning (1.75 hours) 
a. Instructions and practice tasks: learning and attribution phases of learning task, 
and self/other task familiarization and practice  
b. Preparation for fMRI scanning 
 
2. fMRI tasks: social influence task, self/other task, and video compilation task (1.5 hours) 
 
 
Session 4 procedures (~3 hours): 
 
1. Prior to scanning (1.25 hours) 
a. Practice tasks: fractional factorial tasks familiarization and practice  
b. Preparation for fMRI scanning 
 
2. fMRI task: social influence task, fractional factorial task, and video compilation task (1.5 
hours) 
 
3. Debriefing and payment: After completing the tasks, participants will be payed based on 
the hourly rate. Then, they will be offered a debriefing form (Attachment 2), which will 
provide the lab and PI contact information. (0.25 hours) 
 

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Pain Stimuli: During tasks that will involve heat pain, participants will receive standardized 
thermal stimuli (Medoc Pathways, Medoc, Inc.) on the outer surface of the right and left calf/arm. 
Pain stimulation will be administered in accordance with the process outlined in the pain screening 
protocol (Protocol # 31999, Attachment “stimulation_guidelines”). Pain ratings are made on a 
semi-circular scale after each trial using an MR-compatible trackball (5 sec, Current Designs, 
Inc.).  
 
Physiological measurements: Throughout the study we will passively record a number of 
physiological variables: (a) non-invasive electrodes will be placed on the left foot, in order to 
measure skin conductance, and (b) a photoplethysmogram will be placed on the big toe of the 
right foot, in order to measure heart rate/pulse. These recordings will be entirely passive and non-
invasive and will not require any additional effort on the part of the participants (except for having 
sensors attached to one’s left foot and right big toe for physiological recording). The devices used 
to record the physiological data are MRI-compatible and will be recorded using the BioPac 
Acquisition system and the Siemens Physiological Monitor system. There are no known health 
risks involved in collecting this data. 
 
Data Analysis Plan: 
 
Video Compilations: During the scanning sessions, participants will answer questions after each 
video regarding the content of the video (see Attachment 3). We will code semantic concepts 
using categories from Huth et al. (2016) and extract other features and codes (e.g., appearance 
of faces, expressions, social interactions in videos).  
 
Pain: Primary outcomes are effect sizes for (a) brain-based decoding of pain vs. other tasks; (b) 
brain-based prediction of trial-by-trial pain reports. In addition to nominal stimulus intensity levels, 
there is substantial endogenous variation in pain reports due to expectations, sequence effects, 
and endogenous variation in attention, which will be modeled in our trial-by-trial predictive 
analyses. 
 
Cognitive Tasks 
The primary outcomes for the tasks are as follows: 
1. Social influence task: personal pain ratings, vicarious pain ratings (estimating the degree 
of pain the other person is experiencing), cognitive difficulty rating   
2. Narratives task: judgments regarding how the participant feels and/or what they believe 
is going to happen next 
3. Face task: judgments regarding the age, sex, and emotional intensity of the expressions 
4. Fractional Factorial tasks: 1) Memory task: episodic retrieval (“Do you remember this 
item”), 2) Attention task: “Indicate target location”, 3) Theory of mind task: judgments on 
stories, 4) Why and how task: judge human faces based on set of questions 
 
Power assessment. The sample size (n = 150) was chosen to power the study at 80% power for 
voxel-wise analyses with whole-brain family-wise error rate correction (p < 0.05 corrected), for 
moderate effect sizes of Cohen’s d = 0.5 or larger. Recent estimates for voxel-wise effects in fMRI 
studies average around d = 0.5 [179]. Our proposed sample size of n = 150 provides 80% to 
detect moderate effects of d = 0.5, and over 95% power to detect “large” effects of d = 0.8. We 
will test for sex differences in exploratory analyses, with 80% power to detect very large effects 
(d = 1.1). This power calculation is appropriate for making inferences on voxel-wise contributions 
to multivariate predictive models, i.e., to identify brain regions with stable predictive weights when 
training models. When testing multivariate predictive models on new individuals, different 
calculations apply. First, effect sizes can be substantially larger, and second, multiple 

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comparisons correction is not required as information is integrated into a single measure. 
Estimated effect sizes for the Neurologic Pain Signature response tested on data from the 
Colorado 3T scanner (n = 23) were d = 2.12 for a 2-degree difference in painful heat. In our other 
prior work, the effect size when testing our high vs. low negative emotion signature was d = 4.7 
[149], and testing our vicarious pain signature (also on the Colorado scanner) was d = 3.9, all in 
out-of-sample participants. For testing, our proposed sample sizes are powered to detect much 
smaller effects: With n = 150, we have 80% power to detect small effects (d >= 0.26) at p < .05 
two-tailed, and sex differences in predictive accuracy for effects of d >= 0.52. If effect sizes for 
multivariate models are as large as in our previous work (d = 2.0 and above), we will be able to 
make accurate inferences about individuals. Thus, our proposed sample sizes are appropriate for 
identifying regions that contribute consistently to multivariate predictive models across individuals, 
and testing those predictions with high power. 
 
fMRI acquisition and preprocessing. Images will be acquired on a Siemens Trio (3T) MRI 
scanner the Dartmouth Brain Imaging Center. We will collect a T1-weighted anatomical image, 
scout EPI images, and functional images. High-resolution T1-weighted anatomical scans will 
serve as a reference for localizing functional activity. Head movement will be minimized by 
padding and soft restraint as is standard for the Dartmouth Brain Imaging Center. We expect a 
maximum of 1 mm displacement / 1.5° rotation within-run is achievable in ~95% of participants152. 
State-of-the art image preprocessing techniques (SPM12; Wellcome Department of Cognitive 
Neurology, UCL), use procedures detailed in our published work153-159. 
 
Total participation time for the entire study will be approximately 12.75 hours. Duration of the 
session is dependent on the tasks before, during, and after the scan.  
 
 
Name of procedure/instrument/tool 
Purpose (i.e., what data is being 
collected?) 
Consent form (Attachment 4) 
Information pertaining to the study in order to 
inform the participant of the procedures 
Pre-Session Surveys, Online 
(Attachment 5) 
The following measures will be used to 
assess personality, mod, Perceptual/Affective 
Bias, and Cognitive Control 
a) Jessor demographics 
Measures 
Demograpics 
b) Multidimensional 
Assessment of Interoceptive 
Awareness 
Measures interoception 
c) PROMIS-57 Profile v2.1 
Measures physical function, anxiety, 
depression, and pain 
d) Canlab Pain Survey (Pain 
Symptoms) 
Records any pain disorders or sensitivies 
e) Life Orientation Test 
Revised (LOT-R) 
Trail levels of optimism and pessimism 
f) Positive and Negative Affect 
Scale 
Trail levels of positive and negative affect 
g) Fear of Pain (FOP) 
Measures fear and anxiety associated with 
pain 

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h) Behavioral 
Inhibition/Behavioral 
Activation (BIS/BAS) 
Trait levels of approach and avoidance 
behavior 
i) The “Big 5” Inventory Brief 
Version 
Survey designed to measure various 
personality traits 
j) Ego-Resiliency Scale (ER89) 
Ability to respond adaptively and 
resourcefully to new situations 
k) Adverse Childhood 
Experience (ACE) 
Questionnaire 
Measures childhood trauma (if any) 
l) Marlow-Crowne Social 
Desirability Scale 13-Item 
Short Form 
Measures social desirability  
m) Interpersonal Reactivity 
Index 
Measures thought and feelings in a variety 
situations 
n) Phenx Alcohol Lifetime Use 
Degree of lifetime use of alcohol 
o) Phenx Alcohol Age of First 
Use 
Age of first alcohol use 
p) Phenx Alcohol 30Day 
Quantity and Frequency 
Quantity and frequency of alcohol use  
q) Phenx Substances Lifetime 
Use 
Degree of lifetime substance use 
r) Phenx Substance Age of 
First Use 
Age of first substance use 
s) Phenx Substance 30Day 
Frequency 
Frequency of substance use 
t) Phenx Cigarette Smoking 
Status Adult 
Status of cigarette smoking 
u) Phenx Tobacco Age of 
Initiation of Use 
Adolescence 
Age of tobacco initiation 
v) Phenx 3Tobacco 30Day 
Frequency 
Frequency of tobacco use 
w) Self-Report Psychopathy 
Scale 
Identification of psychopathic traits and 
behaviors 
x) Balanced Inventory of 
Desirable Responding 
(BIDR) Short-Form  
Measure of socially desirable responding  
y) 20-Items Prosopagnosia 
Index 
Measure of face recognition abilities 
z) Tendency to Conform 
Measure of social conformity  
aa) Therapeutic Reactance  
Measure of psychological reactance 
bb) Revised Self-Monitoring  
Measure of sensitivity to expressive behavior 
and ability to monitor self-representation 
cc) Concern for 
Appropriateness 
Measure of tendency to conform 
In-Session Behavioral 
Tasks/Surveys  
The Following tasks or assessments will 
be conducted during the in-person 
sessions 

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a) MRI Safety Screening Form 
(Attachment 6) 
Used to confirm fMRI eligibility  
b) Visual Semicircular Analog 
Scale (Bartoshuk Scale 
practice and use; see 
Attachment 7) 
Scale used to submit ratings regarding 
questions pertinent to each task (e.g., pain 
ratings)  
c) Pain Familiarization 
Familiarizing the participants with the range 
of thermal temperatures  
fMRI Cogntiive Tasks 
Brief Description of Tasks (for examples 
see Attachment 7) 
a) Social Influence Task 
Effect of social infuelnce on one’s own 
ratings across a variety of domains 
b) Video Compilation 
Videos for functional alignment; questions 
regarding current feelings (e.g., happy, sad, 
afraid) 
c) Narrative Task 
Narratives that vary in emotional content; 
judgments about how they feel and/or what 
they think will happen next  
d) Face Identification Task 
Brief videos of facial expressions; judgments 
about age, sex, and emotional intensity of 
facial expressions 
e) Self/other Task 
Neurological differences in types of social 
judgments; judgments made about the target 
character 
f) Fractional Factorial 
Four different tasks 
a. Theory of Mind Task 
True of false questions 
b. Why/how Task 
Yes or no questions  
c. Posner Task 
Identify which direction a target was 
presented 
d. Memory Task 
Memorize items, indicate whether they 
previously saw the items 
Other 
 
Biopac Systems 
Utilized for physiological measurements: 
Heart rate and skin conductance 
Pain Medication Assessment 
Administered each session to determine if 
participants have utilized pain medication 
within 12 hours of their visit 
Menstruation Questionnaire 
Administered once to assess menstruation 
 
V. 
FUNDING 
National Institute of Health, Spatial Topology Grant, Principle Investigator: Tor Wager 
National Institute of Health, Placebo Effects Grant, Principle Investigator: Tor Wager 
VI. 
ABOUT THE SUBJECTS  

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All participants will be recruited and screened prior to consent. We will primarily recruit individuals 
aged 18-55 years who have no reported substance abuse within the last six months, are capable 
of performing experimental tasks (e.g., are able to read), are fluent or native speakers of English, 
and have no current or recent history of pathological pain or reported neurological disorders. 
Individuals who are left-hand dominant only will not be eligible; eligible participants must be right-
handed or ambidextrous. Participants less than 18 years old will be excluded because of 
population vulnerability issues. Participants over 55 years of age will be excluded based on a 
diminished sensitivity to pain and changes in brain structure that require special studies of older 
populations, which is outside the scope of this study. Participants with current psychiatric or major 
neurological diagnoses will be eligible to participate because we want to account for broader 
individual differences and maintain a population that is neurodiverse. Only patients who are 
competent and have the cognitive ability to provide informed consent will be allowed to participate. 
For full capacity, participants must be able to: (a) make choices, (b) understand the given 
information, (c) appreciate its content, and (d) rationally process the information (Amer, 
2013; Gupta & Kharawala, 2012;  Grisso & Appelbaum, 1998). At the first study visit, the research 
staff will review the study procedures with the participant and verify that the participant displays 
sufficient understanding of the study as well as its risks and benefits. At each study visit, the 
participant will be asked if they would like to continue their participation and will then be asked to 
re-sign the consent form, accordingly. 
 
In addition, participants who have currently or recently suffered from chronic pain will be excluded, 
as they are unlikely to successfully complete a pain study and provide informative results. Chronic 
pain status will be initially assessed via self-report and verified by additional screening questions. 
We will also exclude people who cannot tolerate the maximum level of thermal pain stimuli (for 
thermal stimuli: 50 °C). 
 
Participants who have any contraindication to magnetic resonance scanning (e.g., metal in body, 
claustrophobia, pregnant) will be also excluded. These exclusions are specific to MRI and are 
consistent with most studies involving MRI. Potential participants will be screened for the 
presence of any of these exclusion criteria prior to participating in this MRI study. 
 
VII. 
VULNERABLE POPULATIONS 
We will not exclude anyone based on class or income so there is a possibility that economically 
disadvantaged individuals will be enrolled in this study, but no other vulnerable populations will 
be included, and recruitment will not target vulnerable populations. 
VIII. 
RECRUITMENT METHODS 
Recruiting will take place through community flyers, university mailing lists, newspaper ads, social 
media platforms (e.g. Facebook ads), online bulletin boards such as craigslist, and via word-of-
mouth. Data collected over the Internet will be kept confidential and made available only to the 
Screening Coordinators. We may also refer to approved recruitment procedures from CPHS 
31999. 
Subject Population(s) 
Number to be enrolled in each group  
fMRI experiment participants 
150 

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IX. 
COMPENSATION  
Laboratory participants will be compensated $400 at the conclusion of the four sessions, including 
a $150 bonus for completing the study (all four sessions). Subjects who discontinue participation 
will be paid a prorated rate for the time of participation based on the $250 rate. Specifically, we 
will offer participants $57-64 for each completed session, and a prorated rate for partially 
completed sessions ($25/hour of scanning, $10/hour of online/behavioral testing, and 
$7.25/hour of behavioral setup).  
 
Undergraduates at Dartmouth College may opt to receive compensation via SONA T-points. 
Eligible students will receive 1 T-point/hour of scan participation and they will receive 
monetary compensation for every hour of behavioral participation ($10/hour of 
online/behavioral testing and $7.25/hour of behavioral setup). Subjects who discontinue 
participation will be given prorated compensation based on their time. Participants who select 
this compensation method will also be eligible for the same monetary completion bonus. 
 
Additionally, participants may receive up to $20 based on their performance in the fractional task. 
This compensation will be issued to participants with the overall study compensation, after 
debriefing.    
 
All participants who have completed the study will be contacted via email and asked to complete 
a brief online survey to provide additional demographic data necessary for grant reporting 
requirements. As a retention incentive, participants who previously completed the study will be 
offered $15 in compensation for providing this data. Active participants will be issued the 
demographic survey during their participation. Additional compensation will not be offered to 
active participants because the effort required to complete the survey is minimal and retention is 
not a motivating concern. 
 
We may offer eligible participants the opportunity to be scheduled as a backup participant. Backup 
participants will participate in the experiment (and be compensated at the regular compensation 
rate) if our originally scheduled participant unexpectedly can't be present. Otherwise, the session 
will proceed with the originally scheduled participant and the backup participant will be 
compensated for their time (i.e., $20 payable via check, cash, or gift card for each backup 
session). Our study will collect and store information necessary to pay participants via a secure 
database such as REDCap. 
X. 
INFORMED CONSENT  
We will obtain a general consent following the process outlined in the pain screening protocol 
(Attachment 1: Protocol # 31999), which involves a screening form. After filling out the screening 
form, and passing our laboratory’s eligibility, potential participants will be contacted by an 
experimenter and sent a link to an experiment-specific electronic copy of the consent form via 
RedCap e-Consent. The consent form will provide information regarding the fact that the study 
involves: 1) viewing video clips that vary in emotional content and listening to narratives from 
storytellers; 2) experiencing thermal stimuli that are painful but tolerable, according to their 
individual sensitivity; and 3) engaging in several cognitive tasks. The participant will read and 
electronically sign the consent form. The signed copy will be saved to the RedCap project’s File 
Repository, as well as on a password protected computer accessible only by study team 
members. Once participants have signed the electronic consent form, they will be sent a link to 
complete the required online surveys (Attachment 5). Upon arrival for their first session, 

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participants will be asked if they have any questions or would like any clarification on any of the 
items included in the consent form. The participant’s voluntary participation is stressed in that they 
are informed, both verbally and in writing, that they can discontinue the study at any time. Subjects 
who discontinue participation will be paid a prorated rate for the time of participation based on the 
hourly rate established for the study. Participants will be given the option to receive a paper copy 
of the signed consent form.   
XI. 
PROCEDURES  
Each eligible participant will be assigned two IDs prior to data collection: 
1. REDCap generated ID  
2. BIDS random ID  
Identifying information from REDCap may be used by a single member of the research staff to 
verify eligibility and confirm completion of surveys and other study requirements. Once a 
participant is determined eligible, this research staff member will assign the BIDS IDs to the 
participant and will maintain a restricted-access spreadsheet that links the REDCap ID and 
BIDS ID. Additional members of the research staff will be permitted to access deidentified data 
only. 
 
Prior to their first session, participants will be sent a link in order to complete a series of pre-
session surveys at home and online (Attachment 5). Completion of the surveys will take roughly 
one and a half hours. We are administering these surveys, along with the others, in order to 
study the basis of emotion in a novel way. The relationship between emotions, drug use, and 
early life experiences are crucial to capture, because they may be important moderators of 
emotion-related activity in our sample and they also serve as outcomes of interest for population 
models that we are going to develop. 
 
Each session will begin with the initial preparation that is required to conduct the MRI.  
 
Preparation for each scan: after having signed the consent form via RedCap e-Consent at 
home, and completing our facility’s MRI screening form, and prior to going into the MRI scanner, 
the MRI technologist on duty will ask participants to remove all jewelry and metal objects from 
their pockets. Participants will be required to change into scrubs to prevent any possible risk 
from metallic objects or decorations in their clothing. 
 
In an MRI scan the subject lies down on a table and is placed into a long donut-shaped magnet.  
A specially designed coil will be placed around the head to provide better images (as is done 
with standard clinical examinations). As the MRI scan is performed, the participant will hear loud 
rapping and knocking noises that are normal for an MRI scan. Participants will be provided with 
earbuds that block out some of the noise from the MRI scanner; they will also have access to a 
squeeze ball that they can squeeze in order to get the attention of the MRI technologist and stop 
the scan. MRIs will be conducted according to the policies and procedures of the Dartmouth 
College Brain Imaging Center, 6207 Moore Hall, Hanover, New Hampshire.  
 
Below is a detailed explanation for each session. The term paradigm is used to refer to the 
design of a task during the fMRI session. For a comprehensive explanation of cognitive tasks, 
questions being asked during the tasks, and examples, see Attachment 7.  
 
Session 1:  
 

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Upon arrival participants will complete our facilities MRI safety screening form (Attachment 6). 
Next, they will practice using the Bartoshuk scale, which they will use in the scanner to make pain 
ratings. Next, participants will be familiarized with the range of temperatures used during the 
tasks. Finally, participants will be familiarized with the session specific tasks (the social influence 
task and the video questions/ratings).  
 
This session begins with a structural scan and a DTI scan. Next, participants will complete the 
first part of the social influence task. The aim of this task is to investigate the effect of social 
influence on one’s own rating across a variety of domains, including affective and cognitive 
experiences. Therefore, we will incorporate three conditions where participants experience the 
following – 1) personal pain, 2) vicarious pain, and 3) a cognitive condition -- in order to assess 
whether other people’s opinions of these experiences can affect one’s experience across a 
number of cognitive and affective settings. 
 
The sequence of one trial is as follows (see figure 4): participants will see a fixation cross (fixation), 
followed by rating bars that indicate other people’s opinions (cue), thus instigating social influence. 
Then they will be prompted to rate their own expectations for this upcoming experience 
(expectation). Next, participants will go through the three conditions, 1) personal pain (heat pain 
for three to four seconds), 2) vicarious pain (three- to four-second video clips of patients with 
shoulder pain), and 3) a cognitive condition (participants will perform a cognitively demanding 
“mental rotation” task while responding quickly to instructions. Participants are required to 
mentally rotate two 3D objects and indicate whether they are the same or different). Lastly, 
participants will rate their experience. For personal pain they will rate how painful the experience 
was; for vicarious pain they will rate how much pain it seemed that the patient was in; and for the 
cognitive conditions the participant will rate how difficult the task was. In total, the task will be from 
30-40 minutes.  
 
 
 
Figure 4. Social influence task experimental design.  
 
 
 
During the last segment of the first session, participants will watch a compilation of short to 
medium length videos and will be asked a series of questions regarding the videos.  
 
Session 2: 
Upon arrival, participants will complete forms and receive task instructions and/or complete 
practices. 
 

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The first segment of session two will be an fMRI paradigm, in which participants will listen to brief 
narratives (3 to 5 sentences each) describing situations that vary in emotional content. Each 
narrative will be presented in two segments. Between the two sections, participants will make 
judgments about how they feel and/or what they think is going to happen next. Four runs of 
scanning lasting approximately 8 minutes will be completed, with different narratives presented in 
each run.  
 
The next task will be the face identification fMRI paradigm, in which participants will be presented 
with brief videos of computer-generated facial expressions. Following each video, participants will 
make judgments about the age, sex, and emotional intensity of the expressions. Three runs of 
scanning lasting approximately 5 minutes will be completed, with different videos presented in 
each run.  
 
During the last segment of the first session, participants will watch a compilation of short to 
medium length videos and will be asked a series of questions regarding the videos.  
 
Session 3:  
 
Upon arrival participants will be familiarized with the session specific tasks (social influence and 
self/other task). 
 
Participants will complete the second part of the social influence task, as described above. 
 
 
The next task is a self/other task, which is designed to investigate the neurological differences in 
related types of social judgements and to develop a neurological biomarker for self-referential 
processing. Participants will view a series of 5-10 second video clips portraying a character 
(target) from longer videos with which the participants are already familiar. After each video clip, 
participants will be asked to make one of three types of judgements about the target: 1.) a 
judgement of how similar the target is to themselves 2.) a judgement of how much they like the 
target or 3.) a judgement about what the target is thinking or feeling.  
 
During the last segment of the first session, participants will watch a compilation of short to 
medium length videos and will be asked a series of questions regarding the videos.  
 
 
Session 4: 
 
Upon arrival, participants will complete forms and receive task instructions and/or complete 
practices. 
 
The first segment of session four will be the third run of the social influence task, as described 
above.  
 
The next segment of session four will be a fractional design with four different tasks.  
Task one will be a theory of mind task. The aim of this task is to investigate the ability to think 
about others mental states. Participants will read stories and answer true or false questions. There 
will be two types of stories:  1) stories describing false beliefs ("belief") and 2) stories describing 
outdated, i.e. false photographs and maps ("Photo"). Both sets of stories require participants to 
represent false content; the critical difference is in the type of false content represented (i.e., a 

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belief versus a photograph/map). Stories were followed by a true/false question that referred 
either to the situation in reality or to the false representation. We use the false belief task localizer 
task from Dodell-Feder and colleagues (2010).  
 
Task two will be a social why/how task. The aim of the task is to identify human brain regions 
associated with answering why and how questions about human behavior. Participants will be 
prompted with a question, followed by pretested photographs of naturalistic human behaviors. 
After observing the image, participants are to determine “Yes/No” to answer the prompted 
question.  
 
The questions used in the Yes/No Why/How Task will be used to manipulate and measure 
attention to “why” versus “how” for actions and expressions. All questions began with the string 
“Is the person”. The questions used in the task is presented in the table below. The task is the 
replicate the findings from Spunt and Adolphs, therefore, we use the exact same task design that 
is shared by the authors.  
 
Task three will be a Posner task. The aim of this task is to investigate visual search facilitation 
with visual cues. Participants will be asked to look for a target and identify which direction it was 
presented, left or right, as fast as they can. In addition to the target, cues will be presented to 
facilitate the visual search process. Cues will be in the form of colored squares, which will 
indicate the location of the upcoming targets. We hypothesize that congruent trials will help 
visual search where people will be faster at identifying the target. This study will be a replicate of 
the Posner cueing task (1984). 
 
Task four will be a memory task; specifically, an episodic memory retrieval task. Participants will 
view a number of black-and-white drawings. They will be asked to memorize the items ("encode"). 
Afterwards, they will be shown a number of drawings - some will have been presented during the 
"encode" stage, some will be novel drawings. Participants will determine whether they saw the 
item before or not. Responses will be collected with a button press.  
 
Task incentive  Participants will receive extra payment based on their task performance, in order 
to incentivize their behavior. Payment will range from $0-$20. 
 
After the scan participants will be taken to a behavioral testing room where they will complete the 
recall memory task. Next, they will be debriefed and compensated for their participation.  
Session # 
Procedures/Tools 
Location 
How much time 
the visit will take 
Session 1 
• 
Task practice and 
preparation for MRI 
scanning  
• 
fMRI scanning  
• 
Scheduling next visit  
-Moore Hall 
-Dartmouth Brain 
Imaging Center 
2.75 hours 

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XII. 
SPECIMEN MANAGEMENT 
N/A 
XIII. 
DATA MANAGEMENT 
Data Security Risk = Level 2 
 
Strict standards of confidentiality are maintained for each experiment and any follow-up 
procedures. MRI data and questionnaire data will be electronically stored and analyzed using ID 
codes. If the data are published subjects will remain anonymous in all publications. Data will be 
stored indefinitely and will not be shared with other investigators without explicit permission from 
the Dartmouth College IRB.  
 
Basic identifying information (name, address, phone number/email address) is collected from 
every research participant for the purpose of research logistics (schedule visits, etc.) and 
mailing of the radiological review letter, as appropriate.  
 
MRI data will be stored according to standard DBIC data management procedures. MRI images 
will be housed on a Dartmouth server.  
 
It is now common practice in MRI research to store de-identified data and use them for future 
research. It is increasingly common for NIH-funded studies to require public sharing of de-
identified data in a public NIH-sponsored or researcher-maintained data repository, as they are 
a valuable resource for large-scale scientific efforts.  Our analysis plan includes sharing and 
reuse of de-identified data after the end of the study period. Upon the completion of the data 
and sharing of de-identified data, codes linking participants’ data to identifying information will 
Session 2 
  
• 
Preparation for fMRI 
scanning  
• 
fMRI task  
• 
Scheduling next visit  
-Moore Hall 
-Dartmouth Brain 
Imaging Center 
2.75 hours 
Session 3 
• 
Task practice and 
preparation for fMRI 
scanning  
• 
fMRI task  
• 
Scheduling next visit (10 
min)  
-Moore Hall 
-Dartmouth Brain 
Imaging Center 
3.25 hours 
Session 4 
• 
Preparation for fMRI 
scanning  
• 
fMRI task  
• 
Debriefing and payment  
-Moore Hall 
-Dartmouth Brain 
Imaging Center 
3 hours 

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be removed and potential features (e.g., facial information) will be removed from structural MRI 
scans, so that the data shared/reused are anonymized. 
XIV. 
WITHDRAWAL OF PARTICIPANTS 
Participants will be ruled ineligible for further participation if pain thresholds fall outside a safe 
range and/or scientifically useful range. Participants who are ruled ineligible for subsequent 
studies will be compensated for their time at the normal rate but will not be further contacted or 
invited to participate in subsequent study opportunities. 
 
Participants may withdraw voluntarily from a study at any time. Participants may either withdraw 
from a particular experimental session, or request that they be removed entirely from the 
laboratory subject pool. In the latter case, all of the participant’s partial or full data will be 
destroyed immediately. 
XV. 
RISKS TO PARTICIPANTS 
1) Burn due to thermode malfunction: There is a very slight risk to the participant in case of 
thermode malfunction. Thousands of participants are tested using this equipment (Pathway 
system, Medoc, Inc.) annually throughout the U.S., usually without adverse events. However, 
several reported cases of thermode malfunction have occurred in the past 5 years (four cases, to 
our knowledge), which have resulted in minor 1st or 2nd degree burns. The manufacturer (Medoc, 
Inc.) has responded to these reports by building in enhanced hardware safety mechanisms; thus, 
we do not anticipate a substantial risk. The PI's lab has conducted experiments on approximately 
400 subjects at Columbia University and over 400 at UC-Boulder with no adverse events. 
Although it is not possible to precisely determine the probability of a burn, we estimate based on 
our prior experience that it is considerably below 1%. We also note that the vast majority of 
potential burns that could potentially result from equipment malfunction would consist of minor 
blistering that would heal naturally without any treatment within several days.  
 
2) Safety concerns in MR environment:  
Ø The magnetic field of the MR environment has the potential to cause burns or bodily 
injury if ferrous metal objects are implanted in the body, or if personal articles 
containing ferrous material are brought into the environment. 
Ø The risk of MRI to pregnant women and fetuses is currently unknown.   
Ø The MRI may cause discomfort due to scanner noise.  
Ø There may be some discomfort from lying still and in one position for a long time 
Ø Peripheral nerve stimulation (PNS/tingling). At sufficient exposure levels, peripheral 
nerve stimulation is perceptible as “tingling” or “tapping” sensations. PNS symptoms 
will usually subside shortly after the scan is completed. 
Ø Subjects may experience nervousness and/or claustrophobia during the MRI. While 
generally safe, it is not known whether an MRI would harm a fetus. 
Ø There is a risk that the image will reveal an observation concerning an individual 
research participant that has potential clinical importance but is beyond the aims of 
this protocol. In the event of the confirmation of a significant anomaly in a participant’s 
brain image, this information will likely be distressing to the participant. 
Ø Participants will be screened for the possibility of being or becoming pregnant during 
the online pain screening (Protocol 10-0243) prior to participation.  
 

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3) Psychological discomfort: Studies involving administration of pain by definition require the 
induction of psychological discomfort, so this is an unavoidable risk of participation. However, as 
described above, the level of pain administered is calibrated to always be within participants’ 
tolerable level, and participants are informed prior to each session involving pain that they are 
free to discontinue the experiment (e.g., removing the thermode) at any time should they wish.  
 
As the emotional stimuli (audio narratives, and movie) may evoke emotional reactions, 
participants may experience some emotional distress. Participants will be informed about these 
possible reactions upfront and can quit the study at any point by just discontinuing the study. We 
predict a low probability, magnitude, and duration of psychological discomfort to emotional stimuli.  
 
4) Cognitive task risks: There are no known risks for completing the various cognitive tasks. If 
any issues arise, participants are free to discontinue the task at any time.  
 
There are no known less risky alternatives to the use of any of the procedures proposed in these 
experiments that would provide comparable scientific information.  
XVI. 
MANAGEMENT OF RISKS 
1) Burn due to thermode malfunction: Pain stimulation will always occur within well-tested and 
verified parameters (Protocol # 31999, Attachment “stimulation_guidelines”). The equipment used 
is widely available and includes several built in safety mechanisms including an auto-shutoff as 
well as maximum temperature restrictions. Additionally, participants are given an emergency shut-
off button that they can press at any time and instantly stops heat delivery. The equipment is 
regularly maintained and tested by our trained personnel. All personnel who use the equipment 
are trained on equipment procedures. 
 
2) Safety concerns in MR environment: This protocol will be performed using an MR scanner 
employing pulse sequences and hardware that have been approved by the FDA for human clinical 
use. The field strength is 3 Tesla and all relevant operating characteristics (RF power deposition, 
rate of change of the field gradients, coil design) fall within the limits of FDA guidelines for NMR 
exposure. Participants will be carefully screened to exclude those who may have metal in or on 
their bodies that cannot be removed (e g., bullets, metal filings, body piercings, etc.). MR Facility 
rules strictly forbid staff from entering the magnet room carrying metal objects. The risk of 
claustrophobia is minimized by screening subjects for self-reported claustrophobia and making 
sure the subject is lying comfortably with head and neck supported and providing ear protection 
with headphones, a mirror to see out, a button to signal distress, and an intercom.  Scan time will 
be kept to a minimum.  If they are unsure about whether or not they may be pregnant, female 
participants will be given the opportunity to complete a urine pregnancy test immediately before 
the scanning period, and those with a positive result will not be scanned. With regard to PNS, 
participants are given a squeeze ball to use in case of an emergency. They are informed that if 
they experience PNS related sensations or are otherwise uncomfortable, they can alert the MRI 
technologist via the squeeze ball and the technologist will stop the scan immediately.  
 
3) Incidental findings:  MRI data collection performed at the Dartmouth Brain Imaging Center 
(DBIC) is not optimized for use as a diagnostic medical tool. However, in the event of incidental 
findings, DBIC administration will be contracted due to their established protocols to handle 
such circumstances. 
 

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4) Psychological discomfort: Participants are clearly informed of this risk prior to participation 
during the instruction period, and the ability to tolerate heat pain is explicitly listed as one of the 
first screening questions. There is virtually no possibility of long-term psychological distress or 
unanticipated psychological discomfort that exceeds the proximal response to pain, as the 
amount of pain delivered is comparable to or less than that experienced in many day-to-day 
situations (e.g., holding a hot cup of coffee). However, they will be encouraged to inform the 
experimenter if they are uncomfortable with the nature of the stimuli. There is no evidence for 
long-term psychological distress or discomfort associated with viewing emotional videos, 
listening to audio narratives, or completing the cognitive tasks. If participants experience any 
lasting negative effects related to the emotional content of this study, they will be encouraged to 
contact the Principal Investigator, Dr. Tor Wager, at tor.d.wager@dartmouth.edu. He will 
discuss options for counseling referrals and provide a referral. The cost of any follow-up 
counseling, should any be required, would be borne by the participants and/or their insurance 
provider. The participant will be informed that neither the study team nor any of its individual 
members will be responsible for follow-up treatment.   
XVII. 
POTENTIAL BENEFITS  
There is no direct benefit to the subject from this screening protocol save for the knowledge that 
their participation may help scientists understand the psychological and neural mechanisms 
involved in pain processing and self-regulation of brain activity. 
XVIII. PROVISIONS TO MONITOR THE DATA FOR THE SAFETY OF PARTICIPANTS 
In the event that a medical professional determines that tissue damage occurred due to study 
procedures, the study will be put on hold until the cause of the issue is determined, the IRB will 
immediately be notified via email, and a formal report will be filed with the IRB by one of the study 
co-investigators. 
The MRI technologists are not trained to identify potentially significant clinical anomalies in the 
brain images. Should the MRI technologist notice something he or she believes to be a potential 
anomaly in a brain image, he or she will follow the procedure noted in section XVI to ensure 
appropriate radiological review. The participant will be contacted if the radiologist recommends a 
scan to determine the clinical significance of any anomaly. Additional action will be taken to ensure 
the subject’s personal safety as per recommendations made for that specific subject. 
 
The research coordinator will conduct monthly reviews of the safety information for this protocol 
to determine if any changes need to be made.  
XIX. 
PROVISIONS TO PROTECT THE PRIVACY INTERESTS OF PARTICIPANTS  
Observations or data collection will occur in a private laboratory setting. We do not anticipate any 
issues for each participant’s ability to interact with researchers and provide information about 
themselves.  
XX. 
MEDICAL CARE AND COMPENSATION FOR INJURY 

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In the event that a participant has experienced a burn, they will be directed to rinse the affected 
location under cool water for several minutes, and to seek independent medical attention if 
symptoms persist after a day or two. If there is any unexpected medical issue, we will call 911. 
No on-site medical care will be provided, and no compensation is available in the event of 
research-related injury. This is clearly explained on the informed consent sheet participants must 
agree to before they may participate in any study involving pain 
XXI. 
COST TO PARTICIPANTS 
Participants who travel to the research site with their own vehicle will not be compensated for gas 
or wear and tear. However, we will reimburse participants for, or cover, all other expenses 
associated with participation, such as parking. Participants who must travel a long way to reach 
the research site (> 30 minutes each way) will be compensated for travel time at the normal rate, 
to a maximum of 2 hours for a round trip. 
XXII. 
DRUG ADMINISTRATION 
N/A 
XXIII. INVESTIGATIONAL DEVICES 
N/A 
XXIV. COLLABORATIVE STUDIES 
All laboratory procedures will be performed at the Dartmouth College Brain Imaging Center in 
Hanover, NH. An IAA will be in place with John’s Hopkins University (JHU) ceding IRB review to 
Dartmouth. Only de-identified data will be sent to JHU as per the coded agreement form. The 
oversight plan for PI Tor Wager can be found in attachment “PI_Oversight_Plan_Att10.” 
XXV. SHARING OF RESULTS WITH PARTICIPANTS 
There are no plans to share the results of this study with participants as a standard procedure. 
Participants or any other individuals who inquire about the results of the study at a later date will 
be informed of any publications that have resulted from the study. 
 
Participants may be given a copy of their structural brain scan on CD, if they choose to receive a 
copy. They will be required to sign an Image Release Form if they take a copy of their brain scan 
(see attached), to ensure they understand that the scan was not collected for medical purposes.