The Dyadic Inter-Brain Signaling (DIBS) Project With Parent-Adolescent Training on Neurofeedback and Synchrony
Phase: NA
Conditions: Testing Protocol With Healthy Individuals for Feasibility
Sponsor: Oklahoma State University Center for Health Sciences

Parent-Adolescent Training on Neurofeedback and Synchrony 
NCT03929263 
Study Protocol and Sta@s@cal Analysis Plan 
3/15/2019 
 

SPECIFIC AIMS 
Depression among adolescents has increased significantly over the past decade, and adolescent girls have a 
threefold incidence of depression as compared to their male peers.1 Nearly 4 in 10 girls will experience a major 
depressive episode during adolescence.1 Importantly, youth who experience difficulties with emotion 
regulation, which is the ability to manage emotions in order to engage in appropriate and goal-directed 
behaviors, are at greater risk for depression, and the parent-adolescent relationship strongly influences this 
risk.2 The parent-adolescent relationship is thus a prime target for intervention and prevention efforts for 
adolescent depression. The overall impact of the proposed study will be the development of a protocol to 
promote parenting practices in support of adolescent emotion regulation that may ultimately be used as an 
intervention in adolescent depression. This study combines: (1) hyperscanning, an innovative approach using 
concurrent functional magnetic resonance imaging (fMRI) to simultaneously measure neural responses of two 
interacting individuals; and (2) real-time fMRI (rt-fMRI) neurofeedback, a method used for training participants 
to regulate activity in a specific brain region. Our preliminary studies suggest that neurofeedback is effective in 
reducing symptoms of depression, and that supportive parent-child relationships are associated with increased 
activation in brain regions important for emotion regulation during parent-child interactions and with fewer 
depressive symptoms in adolescents. 
Our long-term research goal is to implement an effective parenting-based intervention for adolescent 
depression. Building on pilot data from past projects separately utilizing fMRI hyperscanning and 
neurofeedback, the objective of the current study is to develop a dyadic fMRI neurofeedback protocol using 
hyperscanning that will train mothers to regulate their daughters’ activation in a brain region associated with 
emotion regulation (i.e., anterior insular cortex [aIC]), as well as to promote synchronous parent-child brain 
activity, which we and others have shown to be associated with positive emotional outcomes. The study will 
test this protocol for feasibility with ten mothers and their psychiatrically healthy adolescent daughters (ages 
13-17), with the eventual goal to test this in a sample of depressed adolescents in a future study. Participants 
will complete a resting-state fMRI scan at the beginning and end of each hyperscanning session. Participants 
will also complete an ecologically valid emotion discussion task during hyperscanning, in which the daughter 
will describe a recent situation when she experienced strong negative emotions. The mother will then respond 
to the daughter while the mother is simultaneously receiving dyadic neurofeedback (dnf) of the daughter’s aIC 
activation with the goal of decreasing it. Following the conversation, both participants will be asked to mentally 
reflect on the discussion while both receiving dnf representing the synchrony between the mother’s and 
daughter’s aIC activation. We have the following specific aims: 
 Aim 1. To develop and test the feasibility of a hyperscanning fMRI neurofeedback protocol in mothers 
and their adolescent daughters. Hypothesis 1A. Mothers will perceive that they are able to influence their 
daughters’ aIC activation using the daughter’s fMRI neurofeedback signal (e.g., dnf), based on rating scales 
presented at the end of each run (i.e., average rating of ability to move bar ³ 5/10). Hypothesis 1B. Mothers 
and daughters will be able to establish and maintain temporal synchronous alC activation while reflecting on 
their interaction. 
Aim 2. To determine preliminary effects of neurofeedback on neural activation and emotional 
experience during the dyadic social interaction. Hypothesis 2A. Mothers’ own aIC activation while 
listening to their daughters will be positively correlated with that of their daughters’ during the mothers’ 
response. Hypothesis 2B. Stronger temporal synchrony and coupling between mothers’ and daughters’ aIC 
activation during the reflection condition will be associated with more validating statements made by the 
mother during the task and lower self-report ratings of negative emotions in both participants. 
Aim 3. To identify short-term effects of neurofeedback training. Hypothesis 3A (Exploratory). Mothers’ 
and daughters’ neural activation of resting-state networks will be more temporally synchronous at the end of 
the hyperscanning session (following neurofeedback), as compared to their first resting-state fMRI scans in the 
hyperscanning session. Hypothesis 3B. Ratings of positive emotions will be higher and negative emotions will 
be lower following the hyperscanning session as compared to ratings taken before the scan. 
The expected outcome of the proposed study is a rt-fMRI neurofeedback-hyperscanning protocol that will be 
available for implementation in future studies with larger samples in order to study its effects on adolescent 
depression. The protocol and data from the first five dyads will be used for a K award submission in the fall of 
2019. A manuscript will be prepared and submitted following the end of data collection in the summer of 2020. 
The protocol developed in this study will provide the foundation for future prevention and intervention efforts 
aimed at the effects of parenting on the development of emotion regulation skills and depressive symptoms. 
 

SIGNIFICANCE: Depression is a debilitating illness that often begins during adolescence. In 2015, an 
estimated 3 million adolescents aged 12 to 17 in the U.S. had at least one major depressive episode in the 
past year – an increase of 44% over the past ten years.3 The peak onset of depression is around age 15.4 For 
adolescent females, rates of depression are three times that of adolescent males, with some studies indicating 
that 50% of females will have an episode of depression during adolescence.5 Furthermore, higher rates of 
depression in females persist into adulthood, with serious consequences for social and emotional health and 
well-being.6 Therefore, it is critical to research and understand the precursors to the onset of adolescent 
depression and identify intervention targets that forestall depressive episodes and the resulting health effects.   
Parenting and emotion regulation are two key factors that affect risk for depression, with a significant impact 
on the development of mental health during childhood and adolescence.7,8 Emotion regulation difficulties are a 
core vulnerability that underlie adjustment problems that emerge during adolescence, including depression.9,10 
How parents react to and socialize their children’s emotion regulation is critical to youth’s mental health.11,12 
Numerous studies show better emotion regulation among children of emotionally supportive parents compared 
to emotionally unsupportive parents who ignore and sometimes denigrate their children’s emotions.13 Children 
who have warm, open, and supportive relationships with their parents have more positive emotional and 
mental health outcomes.13 Fostering such relationships may therefore aid in the prevention of and intervention 
for adolescent depression. Parenting influences emotion processing and emotion regulation neurocircuitry, as 
well as the development of psychopathology.14 Supportive parenting is associated with adaptive structural 
changes in limbic-striatal brain regions over time15 and adaptive functional responses to emotional stimuli.16,17 
Parents and adolescents with more synchronous resting-state networks have similar daily emotional 
synchrony, and adolescents who have greater synchrony with their parents also show higher levels of 
emotional competence.18 When listening to critical comments made by their mothers, adolescents exhibit 
increased brain activity (relative to neutral comments) in subcortical-limbic regions but decreased activity in 
regions subserving cognitive control of emotion, such as the dorsolateral prefrontal cortex (dlPFC) and caudal 
anterior cingulate cortex.19 These findings suggest that typically developing adolescents fail to recruit cognitive 
control networks to help them regulate emotion when listening to critical comments from their mothers. Using a 
similar task in a study conducted with adolescent girls, Dr. Amanda Morris (a mentor on the current proposal) 
and colleagues demonstrated that symptoms of anxiety and depression are associated with a blunted left 
amygdala response to maternal criticism and praise paired with increased right amygdala response to 
criticism.20 Taken together, these regions (dlPFC, anterior cingulate, amygdala) constitute an emotion 
regulation network in which the aIC plays a key role. Adolescents’ regulation of the aIC through neurofeedback 
influences information flow between the amygdala and higher cortical structures such as the dlPFC.21 
Additionally, across numerous studies depressed adolescents show hyperactivation of the right aIC.22 
Parenting effects on aIC activation can be seen in child maltreatment, which is also associated with increased 
aIC activation.23 Collectively, these findings support the scientific premise that parenting influences 
adolescents’ emotion regulation-related neurocircuitry, and parenting alters functioning in brain 
regions that support emotional reactivity and regulation in response to feedback from parents.  
INNOVATION: This study will integrate two cutting-edge, state-of-the art neuroimaging methods: 
hyperscanning and neurofeedback. This is the first study to our knowledge to simultaneously scan two 
individuals while they are interacting and being provided with real-time dnf. Using these techniques, mothers 
will be able to see in real-time how what they say to their daughter affects her brain function, and they will be 
able to use this feedback to respond more effectively and supportively to her. This will also be the first study to 
our knowledge to utilize a neurofeedback signal indicative of inter-brain synchrony. Parent-child neural 
synchrony has been shown to be associated with emotional health,18 and this study provides the opportunity 
for mothers and daughters to receive neurofeedback on inter-brain synchrony in order to enhance it. Due to the 
high ecological validity of this paradigm, we expect effects to generalize to future real-world interactions 
between the participants after study completion. 
PRELIMINARY DATA: The proposed emotion discussion task has been used in previous studies with parents 
and adolescents.24,25 Our lab has experience with both hyperscanning and neurofeedback with parent-
adolescent dyads. In the past 18 months, 40 parent-adolescent dyads completed a free-speech conflict 
discussion task while undergoing hyperscanning. The currently proposed project builds on acquired experience 
and acquired data and analyses. Preliminary analyses provide support for targeting the aIC as a key region for 
emotion regulation within the context of the parent-adolescent relationship. Our recent project included a task 
wherein each participant was led to believe the other had made a costly error during a cooperative game. A 

whole-brain analysis using the AFNI program 3dTcorrelate was conducted to 
identify brain regions where parent and adolescent activity was correlated 
during the ‘costly error’ condition, and evidence for co-activation was found in 
bilateral aIC (Figure 1). aIC activation can be successfully regulated with rt-
fMRI neurofeedback in adults, adolescents, and children.21,26-28 Importantly, 
down-regulation of aIC activation is associated with reduced anxiety in 
phobic participants at 3-month follow-up28 and, in healthy adolescents, has 
effects on a network of regions associated with emotion regulation.21 The aIC 
is thus a prime target for dnf with the goal of increasing emotion regulation in 
adolescents.   
 
 APPROACH: This study will utilize a rigorous multi-method, multi-informant 
design to examine the effects of dnf on adolescent brain activation with fMRI 
hyperscanning (see Table 1 for Project Timeline). Parents and adolescents 
will also report on emotion regulation, depressive symptoms, and parenting practices. Data collection 
procedures will take place at the Laureate Institute for Brain Research (LIBR), which is equipped with two 
identical scanners  
that have 
advanced real-time 
fMRI systems 
capable of 
conducting parallel 
fMRI 
hyperscanning, 
including the 
capacity for 
neurofeedback 
developed by Dr. 
Jerzy Bodurka, 
who is also Dr. 
Kerr’s mentor. IRB 
approval will be 
obtained from the 
Oklahoma State University Center for Health Sciences.  
Parents will complete a phone screen to determine initial 
eligibility (see Inclusion/Exclusion criteria in Table 2). If 
initial study criteria are met, a 2-hour in-person lab visit will 
be scheduled where mothers and daughters will complete 
consent/assent; diagnostic interviews (the Mini-
International Neuropsychiatric Interview [parent MINI 7.0, 
adolescent MINI KID 7.0]); surveys on emotion regulation, 
parenting practices, depression, and anxiety (Table 3); 
and additional screening. Survey data will be used for 
preliminary exploratory analyses. Based on data collected 
from the screening visit, participants will be invited to 
participate in the full study: a 4-hour visit where mothers 
and daughters will complete emotion ratings, mock 
scanner training, and fMRI tasks individually and together 
using hyperscanning (scan time = 16 min resting-state [2 
runs], 7 min structural MRI, 40 min fMRI tasks, 10 min clinical MRI scans).  
Participants. 10 adolescents (ages 13-17; all female) and their biological mothers, total N=20, recruited using 
electronic flyers distributed through local schools and from a previous lab project (Dyadic Inter-Brain Signaling 
study). Our sample will include ~40% from ethnic/racial minority groups. 
Consideration of biological variables. This study will result in pilot data and a protocol for a future 
intervention study in depression. Scientific reasons to only include females are: (1) rates of depression are 
three times higher among females than males29; (2) during adolescence, female and male brains develop at 
Table 2: Inclusion/Exclusion Criteria 
 
 
Criteria 
Moms 
Girls 
Inclusion 
Eligible for fMRI 
P 
P 
Sufficient English fluency to complete tasks 
P 
P 
BMI 
18.0-40.0 
16.0-40.0 
Right-handed 
P 
P 
Biological female 
P 
P 
Biological mother 
P 
 
Co-residing at least 4 days/week 
P 
P 
Primary caregiver > 50% of child’s lifespan 
P 
 
Age 13-17 
 
P 
Exclusion 
Current psychiatric diagnosis 
X 
X 
Medications influencing fMRI 
X 
X 
Medical conditions influencing fMRI 
X 
X 
Alcohol or psychoactive drug on scan day 
X 
X 
Neurodevelopmental delay 
 
X 
History of mood or psychotic disorder 
 
X 
History of OCD or ADHD 
 
X 
3/15/2019 - 
8/15/2019
8/16/2019 - 
12/15/2019
12/16/2019-
4/14/2020
4/15/2020 - 
8/15/2020
8/16/2020 - 
12/15/2020
12/16/2020-
3/14/2021
General Project Activities
Weekly meetings with mentors
x
x
x
x
x
x
Protocol development and testing
x
Train and hire RA
x
Recruitment and Data Collection
Recruitment and screening
5 dyads
5 dyads
Scan sessions
5 dyads
5 dyads
Data Entry, Analysis, and Coding
Data entry and cleaning
x
x
fMRI data processing and QA
x
x
x
Transcription and coding of tasks
x
x
x
x
Hypothesis testing
x
Conference presentation
x
x
Manuscript preparation
x
x
Preparation for K99/R00 Application
Preliminary data analysis
x
Draft research plan/revisions
x
Finalize proposal and submit
x
Year 1
Year 2
Task
Figure 1 
z = 6
1
-1
r
p < .005
Parents and adolescent 
dyads display co-activation 
in the anterior insula.
Table 1: Project Timeline 

different rates, with some studies indicating a gap in brain maturation due to the onset of puberty occurring two 
years earlier for girls30; (3) many adolescents do not have a consistent father figure in the home, with rates of 1 
in 4 children living in single mother families31; and (4) mothers and fathers diverge in emotion socialization 
techniques and parenting styles that could impact results.32  
fMRI hyperscanning. All hyperscanning experiments will be conducted on 
two MR750 3T MRI scanners with fMRI imaging protocols and parameters 
described elsewhere.33,34 Prior to scanning, participants will complete a brief 
training session in the mock scanner to desensitize them to the MRI 
environment and to practice talking while remaining as still as possible. After 
this training, subjects will complete an 8-minute eyes-open resting-state scan 
followed by the dnf training and transfer runs. Subjects will then undergo a 
second resting-state scan and complete post-scan emotion rating scales. 
Emotion Discussion with Dyadic Neurofeedback Task. This task will be 
completed in the scanner using simultaneous hyperscanning data collection. 
Prior to the fMRI, adolescents (without the parent present) will be asked to 
think of recent situations when they were feeling strong negative emotions, 
such as anger, sadness, and/or anxiety. They will be informed that they will be 
talking to their mother about each situation during the scan. The mother 
(without the daughter present) will be provided with task instructions and informed that while talking to her 
daughter she will be receiving neurofeedback from a region in her daughter’s brain. The mother will be told that 
her goal is to decrease activation in that region by calming her daughter and decreasing the intensity of her 
daughter’s emotional response. The emotion discussion task will consist of four types of trials, each lasting 
40s: Rest trials, Count trials, Discussion trials, and Reflection trials. During the first Discussion trial, the 
adolescent will describe the emotional situation. This will be followed by a second Discussion trial during which 
the mother will respond to the adolescent while receiving neurofeedback from the adolescent’s aIC. This will be 
followed by a Count trial during which participants will mentally count backward from 300 by a number 
specified on the screen (for example, by 6: 300, 294, 288…) in order to bring aIC activation back to baseline. 
This will be followed by a 40s Rest period. Following the Rest trial, the adolescent will be provided 40s to 
respond to her mother (no neurofeedback presented), and the mother will subsequently respond again to the 
adolescent while receiving neurofeedback from her daughter’s aIC. This will again be followed by a Count and 
Rest trial. Finally, both the adolescent and her mother will be asked to mentally (i.e., silently) reflect on the 
discussion while receiving neurofeedback representing the synchrony between both participants’ aIC 
activation. This will be followed by another 40s Count trial and 40s Rest trial, for a total runtime of 8 minutes. 
Participants will complete three runs of the emotion discussion task with dnf, followed by a fourth transfer run in 
order to determine if the effects of the training persist. During the transfer run, the task will be exactly the same 
except no neurofeedback will be presented. 
Audio Collection and Coding. Although collection of valid fMRI data during free speech requires extra care,35 
we can correct for speech-related signal artifacts. In addition to standard pre-processing including volume 
registration and inclusion of motion parameters as covariates in regression analyses, we will use a continuous-
speech ‘de-noising’ procedure developed by Xu et al.36 that employs a dual-mask spatial independent 
component analysis (ICA) method to identify noise components based on spatial origins. We will use active 
noise-cancelling microphones and headphones (OptoActive II NC Microphones and ANC Headphones, Opto 
acoustics Ltd.) and an intercom link between the scanners that produces voice/audio quality equivalent to most 
mobile phone calls. To avoid motion artifact interfering with the neurofeedback signal, neurofeedback will not 
occur when the subject of the neurofeedback is talking. The audio during the emotion discussion task will be 
recorded and later transcribed. The parents’ responses will be coded for specific types of statements using the 
parent-child validation/invalidation behavior coding scales.37 Validating statements are supportive of the 
adolescent’s emotional experience and show empathic understanding, while invalidating statements minimize, 
dismiss, or criticize the adolescent and/or her expressed emotions. In the proposed study, all transcriptions will 
be double-checked, and at least 2 of the 5 conversations will be double-coded. PI Kerr will oversee coding, 
transcription, and reliability checks (80% agreement or higher).   
fMRI Data Acquisition Parameters.  fMRI data will be collected on two GE MR750 3 Tesla MRI scanners 
(scan time = 1hr 30m). Functional images will be acquired as echoplanar imaging (EPI, optimized to minimize 
signal dropout and image distortions; 46 contiguous 2.9-mm thick slices collected in the axial plane, ensuring 
whole-brain coverage [TR/TE = 2000/30 ms, SENSE acceleration R=2, flip angle = 90°, voxel size = 
2.5´2.5´2.9 mm3]). Both LIBR scanners are equipped with advance real-time fMRI systems, allowing for EPI 
Table 3: Survey Measures 
Parenting 
Child Report of Parent Behavior Inventory 
Alabama Parenting Questionnaire 
Emotion Socialization and Regulation 
Emotion as a Child Scales 
Difficulties in Emotion Regulation Scale 
Mental Health – Adolescent  
Mood and Feelings Questionnaire 
Screen for Child Anxiety Related Disorders 
Depression, Anxiety, and Stress Scale-21 
Achenbach’s Child Behavior Checklist 
(parent report) 
Mental Health – Parent 
Quick Inventory of Depressive 
Symptomatology – Self Report 
Beck Anxiety Inventory 
Depression, Anxiety, and Stress Scale-21 

image quality examination and artifact troubleshooting before the subject begins the task scans, as well motion 
tracking during the scans. T1-weighted MRI anatomical MPRAGE high resolution (voxel size = 1´1´1 mm3) 
images will be acquired. All imaging parameters, synchronization, audio, and visual coupling among the 
scanners have been, and will be, determined in consultation with LIBR’s physicist, Dr. Jerzy Bodurka, who has 
developed and has experience with fMRI hyperscanning and will also serve as a mentor on the project.  
ANALYSES: Data will be analyzed in real-time with LIBR software.33,34 An automated script will generate an 
anatomically-defined spherical region-of-interest (5mm radius) centered at the aIC (locus: [38, 16, 4], MNI 
space).38 The dnf, updated every 2s and shown as a bar with moving height, will be measured as % signal 
change relative to baseline (obtained by averaging the fMRI signal for the preceding 40s rest block). To reduce 
bar fluctuations due to noise in the fMRI signal, bar height will be computed at every time point as the mean of 
the current and two preceding fMRI signal change values. All offline fMRI data preprocessing and analyses will 
be conducted as described elsewhere.33,34 General Linear Models (GLM) will be used to analyze individual 
subjects’ data with predictors in the model. Regressors of non-interest will be included in all models to account 
for each run’s signal mean, linear, quadratic, and cubic signal trends, as well as motion parameters. 
Regressors will also include the block stimulus conditions (daughter: Describe/Respond, Listen, Count, Rest, 
Reflect; mother: Respond [dnf], Listen, Count, Rest, Reflect) and five polynomial terms for modeling the 
baseline. The GLM β coefficients will be computed for each voxel and converted to % signal change for 
contrasts of interest (e.g., Listen versus Count, Listen versus Rest, Count versus Rest, Reflect versus Rest, 
and Reflect versus Count). Statistical contrast maps for exploratory whole-brain analyses will include 
corrections for multiple comparisons.  
Hypothesis 1A. Mothers will perceive that they are able to influence their daughters’ aIC activation 
using the daughter’s fMRI neurofeedback signal (e.g., dnf), based on rating scales presented at the end 
of each run (i.e., average rating of ability to move bar ³ 5/10). We will ask the mother to rate how effective 
she felt she was at changing her daughter’s brain activity on a Likert scale from 0-10. For this analysis, we will 
simply take the mean of all parent participants’ responses over all runs and determine if it is at least 5, 
providing evidence that mothers perceived they were able to effectively regulate their daughter’s brain activity. 
Hypothesis 1B. Mothers and daughters will be able to establish and maintain temporal synchronous 
alC activation while reflecting on their interaction. Correlations will be calculated between mothers’ and 
daughters’ aIC timecourses (Reflect vs Rest contrast).  
Hypothesis 2A. Mothers’ own aIC activation while listening to their daughters will be positively 
correlated with that of their daughters’ during the mothers’ response. The correlation between the 
mothers’ and daughters’ average beta weights for aIC activation during each participant’s Listen trials will be 
calculated. 
Hypothesis 2B. Stronger temporal synchrony and coupling between mothers’ and daughters’ aIC 
activation during the reflection condition will be associated with more coded validation statements 
during the task and lower self-report ratings of negative emotions in both participants. a) Coupling will 
be measured as the correlation between timecourses for aIC activation as described in Hypothesis 1B, 
transformed to z-scores (Fisher’s r-to-z transformation). b) Participants will be asked to rate the intensity of 
various emotions they felt during the scan (0-10 Likert scale). Correlations will be calculated between the z-
scores (a) and 1) the number of validating statements made by the mother across the scan and 2) ratings of 
negative emotions (b). 
Hypothesis 3A (Exploratory). Mothers’ and daughters’ neural activation of resting-state networks will 
be more temporally synchronous at the end of the hyperscanning session (following neurofeedback), 
as compared to their first resting-state fMRI scans in the hyperscanning session. Similarity of resting-
state networks will be evaluated as described in Lee et al. (2017).18 ICA will identify intrinsic resting-state 
networks at the group level. On the individual level, a matrix of correlation coefficients for all possible pairs of 
resting-state networks will be created and transformed to Fisher’s z, then vectorized and correlated between 
each pair of mother-daughter dyads to determine the level of synchrony within the dyad. A paired t-test will be 
conducted to determine if there is a significant difference between resting-state synchrony at the beginning 
versus end of the scanning session. 
Hypothesis 3B. Ratings of positive emotions will be higher following the hyperscanning session as 
compared to ratings taken before the scan. Paired t-tests will be conducted separately for mothers and 
daughters to determine if ratings of positive emotions (e.g., “happy,” “calm”) made on a 0-10 Likert scale before 
the scan differ significantly from those made after the scan. 
 

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