Intracranial Recording and Stimulation of the Human Hippocampal-Amygdala Circuit During Virtual Reality Fear Conditioning
Phase: NA
Conditions: Anxiety and Fear, PTSD, Veteran
Sponsor: University of California, Los Angeles

 
 
 
Cover Page for ClinicalTrials.gov 
 
 
Document:  
Study Protocol and Statistical Analysis Plan 
 
Official Study Title:  
Intracranial Recording and Stimulation of the Human Hippocampal-Amygdala Circuit During Virtual Reality 
Fear Conditioning 
 
Principal Investigator:  
Anthony I. Jang, M.D. 
 
NCT Number:  
Not yet assigned 
 
Date:  
10/1/2025 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

PROJECT SUMMARY/ABSTRACT 
Anxiety disorders, including generalized anxiety disorder (GAD) and post-traumatic stress disorder (PTSD), are 
the most prevalent mental health conditions globally with a high rate of treatment resistance and significant 
healthcare costs. These disorders are believed to stem from fear responses that are excessive and 
disproportionate to the situation. Therefore, understanding how the human brain processes fear and how this 
may go awry in anxiety disorders is crucial for developing effective therapies. Research using rodent models of 
anxiety suggests that the formation and regulation of fear responses to the environment require a complex 
interplay between two brain structures, the amygdala and hippocampus. However, it is unknown whether these 
findings can be translated to the human brain, and whether directly modulating fear-related neural activity can 
be used as a therapeutic tool to treat anxiety disorders. This project aims to 1) elucidate the neural 
mechanisms governing the acquisition, extinction, and renewal of fear and anxiety responses within the 
hippocampal-amygdala circuit in humans, 2) investigate whether targeted stimulation of the amygdala, aimed 
at dampening its role in maintaining fear responses to innocuous stimuli, can facilitate recovery from 
maladaptive fear responses, and 3) explore potential differences in outcomes based on individuals’ baseline 
anxiety levels. To address these questions, we will work with participants who have previously undergone 
surgical implantation of a responsive neurostimulation (RNS) device in the amygdala and hippocampus for the 
treatment of epilepsy or PTSD. The RNS is a chronically implanted intracranial recording and stimulation 
device that provides a unique opportunity to directly record from the hippocampal-amygdala circuit and deliver 
electrical stimulation. To simulate real-world fear responses and assess the impact of environmental context on 
fear learning, we designed a virtual reality (VR) experiment where participants acquire and subsequently 
extinguish fear responses to various stimuli within different virtual environments (e.g., library, grocery store), 
providing insights into how contextual cues influence fear responses.  
This award will allow me to complete a multifaceted career development plan in a world-class academic 
institution under an interdisciplinary mentoring team consisting of experts in basic neuroscience, 
neurotechnology, virtual reality, neurosurgery, psychiatry, and psychology. Building upon my prior experience 
with acutely implanted intracranial electrodes, I will broaden my skill set to encompass mobile (chronic) 
intracranial electrophysiology and targeted electrical stimulation. I will also develop expertise in the 
implementation of immersive, ambulatory VR experiments in human neuroscience research. Lastly, through 
seminars, coursework, and conferences, I will develop both as an experimental scientist and scientific 
communicator. Taken together, this will allow me to grow into an independent physician-scientist who 
effectively leverages innovative technologies to study the mechanisms of anxiety disorders.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

PROJECT NARRATIVE 
Anxiety disorders such as generalized anxiety disorder and post-traumatic stress disorder are the most 
prevalent mental health conditions worldwide and are associated with high rates of treatment resistance, 
disability, and significant healthcare expenses. Studying the basic neural mechanisms of fear and anxiety in 
humans is crucial for gaining deeper insights into the development of anxiety disorders and pioneering novel 
therapeutic interventions. Working with individuals who are already implanted with intracranial electrodes for 
epilepsy or PTSD, our research will employ virtual reality experiments to study the neural correlates of fear and 
investigate whether direct stimulation of the fear circuitry can ameliorate anxiety-related behaviors, thereby 
paving the way for innovative neuromodulatory treatments for anxiety disorders.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

FACILITIES & OTHER RESOURCES 
Scientific environment: UCLA is a renowned research center with extensive academic resources, including 
regular scientific seminars, a comprehensive electronic library system, excellent core facilities, and 
accomplished research collaborators. The David Geffen School of Medicine at UCLA, the Ronald Reagan 
UCLA Medical Center, and the Resnick Neuropsychiatric Hospital are consistently ranked among the top 
academic medical institutions in the United States. Dr. Jang has the full commitment of his departmental 
leadership as described in the Institutional Letter of Support and the Department of Psychiatry offers generous 
internal grant mechanisms including the Friends of the Semel Institute Research Scholars Program. In 
addition, the UCLA Clinical and Translational Science Institute (CTSI) provides numerous programs (e.g., K 
Scholars Society) and support services (e.g., drop-in statistical consulting, grant application reviews, intramural 
funding opportunities) specifically designed to assist early-career investigators in their career development.  
The Suthana laboratory has two locations for mobile ambulatory virtual reality (VR) tasks in humans, one at 
UCLA (Westwood) and one in Santa Monica (3 miles away). The Westwood laboratory is a part of the UCLA 
Brain Research Institute which includes about 300 faculty members representing nearly 30 departments from 6 
different schools, serving a rich interdisciplinary academic environment. The Westwood location is on the 4th 
floor of the Semel Institute for Neuroscience and Human Behavior and consists of a computer lab (Room 47-
355) and an experimental AR/VR motion capture laboratory (Room 48-136). The computer laboratory (810 sq 
ft) consists of 16 workstations equipped with numerous Mac/PC desktop/laptop computers and a large cluster 
server and computing server available to all laboratory members for any research-related activities such as 
data analysis and manuscript preparation. It also consists of an enclosed office room with a door for behavioral 
testing for pilot projects. The experimental laboratory is a square-shaped (420 sq ft) open space room 
equipped with several pieces of equipment (see Equipment section) including multiple iterations of virtual and 
augmented reality headsets (e.g., Meta, VIVE), a computer capable of implementing graphics-intensive VR 
experiments, and wearable sensors that can measure photoplethysmography (i.e., heart rate), electrodermal 
activity (i.e., skin conductance), electromyography (i.e., startle eye-blink amplitude), pupil diameter, and gaze 
direction. It is also equipped with full-body wireless motion tracking equipment that includes 23 wall-mounted 
high-resolution cameras (Optitrack, Natural Point, Inc.,) for sub-millimeter motion capture and body positioning.  
The second location is in Santa Monica (total of 4,331 sqft) located at 1618 Stanford St, Suite D, Santa 
Monica, CA 90404, and consists of 4 office spaces, a conference room/computer lab, a break area, a large 
experimental VR/AR motion capture laboratory, and a space for sleep/nap studies and behavioral testing. The 
are a total of 20 workstations and numerous computers and servers that are available for use by laboratory 
members. The experimental laboratory is a square-shaped (1,947 sq ft) open space room equipped with 
several pieces of equipment including scalp EEG, VR/AR headsets, wearable technology (e.g., biometrics), 
eye tracking headsets, and full body wireless motion tracking equipment that includes 41 wall mounted high-
resolution cameras (Optitrack, Natural Point, Inc.).  
Software available includes Matlab, Python, SPSS, FSL, BrainLab, Vitrea, Freesurfer, ASHS, ANTs, R, Adobe 
Suite, E-prime, Steam VR, Maya, Blender, Unity, and custom design software.  
The Veterans Affairs Greater Los Angeles Health System (VAGLAHS) is one of the leading healthcare 
systems serving U.S. military veterans in Southern California. It comprises a tertiary care hospital, the West Los 
Angeles VA Medical Center, alongside several community-based outpatient clinics, fostering a robust 
environment for collaboration. This proposal features two key collaborators, Dr. Langevin and Dr. Koek, who 
hold joint VA appointments. They play integral roles as liaisons in participant recruitment efforts, with a particular 
focus on veterans with severe anxiety- and trauma-related disorders. Neurosurgical patients particularly from 
the VA have a higher prevalence of anxiety disorders including GAD and PTSD. This collaboration between the 
Suthana lab and the VAGLAHS has been ongoing successfully for the past several years yielding high-impact 
publications1,2.  
Institutional Investment in the Investigator: Dr. Jang is currently completing his third year in the Research 
Track of the UCLA Psychiatry Residency Training Program. Upon graduating from residency, the Department of 
Psychiatry fully commits to the appointment of Dr. Jang as a full-time faculty member with at least 75% protected 
time to devote to his research and career development activities, with full departmental salary support in addition 
to salary supplementation through the Suthana laboratory and external grant mechanisms. Dr. Jang’s 
appointment at UCLA is not contingent upon the receipt of the K08 Award (please see the Institutional 
Commitment Letter for details).  

EQUIPMENT 
NeuroPace RNS system: The FDA-approved RNS® System (Figure 1) will be 
used to record intracranial electroencephalography (iEEG) activity from the 
amygdala and hippocampus and deliver targeted electrical stimulation. Each 
participant in the study will have one or two implanted depth electrode leads 
1.27 mm in diameter each with four platinum-iridium electrode contacts, each 
with a surface area of 7.9 mm2, 1.5 mm long with an electrode spacing of 
3.5mm. The RNS System will continuously monitor iEEG on four bipolar 
channels at 250 samples/sec with its default closed-loop electrical stimulation 
turned off during experimental sessions. The RNS System contains a 
microprocessor that runs software that may be transmitted wirelessly to the 
device. The RNS System communicates wirelessly with a Programmer and 
Remote Monitor using secure protocols. Our group developed a specialized 
research protocol using the RNS System Programmer Accessory which allows 
for continuous iEEG recording and the delivery of electrical stimulation at 
specified times during the task. Our laboratory has also built a small oscillating 
electromagnet that emits a “Marker” signal that is inserted and delivered to the 
iEEG data in programmable time intervals (i.e. 30-240 sec) to sync the iEEG 
data with motion capture cameras and other continuous data (e.g., physiological data, scalp EEG) while the 
participant completes behavioral tasks3,4. All research accessories have been tested with the NeuroPace RNS 
System device with high reliability and repeatability. We have used this setup in more than 20 participants thus 
far, including data reported in the Preliminary Results of the Research Strategy. 
Motion capture: Recording of participant movement is done using the Optitrack system (Natural Point, Inc.) 
with 41 ceiling-mounted infrared high-resolution cameras that allow for sub-millimeter motion tracking (see 
Facilities and Resources). The motion tracking cameras detect reflective markers that are manually attached to 
the virtual reality headset which models the head as a rigid body object and tracks its center of mass (i.e., 
position) and rotational information (i.e., yaw, pitch, and roll with respect to the experimental room).  
Virtual reality setup: The VR fear conditioning paradigms will be implemented in a state-of-the-art Alienware 
Gaming Computer running the Unity game engine which is wirelessly cast to the Meta Quest Pro VR headset. 
The paradigm can be flexibly adapted to run in other VR headsets that are also available to lab members, 
including the Samsung GearVR goggles and the HTC VIVE VR headset. VR applications can also be 
configured to communicate with the motion capture system via WiFi through custom Unity scripts (Interactive 
Lab, Russia), allowing for real-time room-scale virtual navigation (i.e., the physical movement of the participant 
tracked with motion capture cameras can be mapped to their position in the virtual room, allowing for real-time 
updating of the virtual scene). A wireless joystick can be paired with the headset and used to track button 
presses during the survey portion of the VR task. The laboratory also has Microsoft Hololens and Magic Leap 
headsets for augmented reality and simultaneous eye tracking for future adaptations of the VR task.  
Wearables for physiological activity: The laboratory is equipped with the wireless BioNomadix Smart Center 
(BIOPAC® Systems, Inc.) which can record heart rate and skin conductance while the participant undergoes 
the ambulatory VR task. Data can be streamed in real-time to the computer that is running the Motion Capture 
system for synchronization of multiple data streams. The BIOPAC system is also capable of recording 
respiration and eye-blink activity if the decision is made in the future to incorporate those data into the VR 
paradigm.  
 
 
 
 
 
 
 
 
 
 
Figure 1. The RNS System 

Study Title: Intracranial Recording and Stimulation of the Hippocampal-Amygdala Circuit During Fear 
Conditioning 
 
Conditions or Focus of Study 
Intracranial electrophysiology 
Intracranial electrical stimulation 
Virtual reality 
Fear conditioning 
Fear renewal 
Anxiety 
Amygdala 
Hippocampus 
Humans 
 
Eligibility Criteria 
Inclusion Criteria: 
- Male 
- Female 
- Between 18 and 70 years of age 
- Adequate visual and auditory acuity to allow neuropsychological testing 
- Have undergone surgical placement of NeuroPace RNS System for the treatment of epilepsy or post-
traumatic stress disorder 
Exclusion Criteria: 
- History of traumatic brain injury 
 
Protocol Synopsis 
The purpose of this study is to understand the neural mechanisms that underlie fear and anxiety in humans 
using intracranial neurophysiological recordings and electrical stimulation during laboratory virtual reality-based 
tasks. We will investigate the physiological (heart rate variability, skin conductance response) and 
neurophysiological changes that occur during both conditioned and unconditioned fear responses as well as 
the consequent effects of intracranial electrical stimulation of the relevant neural circuitry. 
 
Outcome Measures 
Physiological Change 
During trials with and without intracranial electrical stimulation 
Physiology (heart rate variability and skin conductance response) will be measured using virtual reality tasks 
where participants will encounter fear-associated stimuli (e.g., light color change) and fear-inducing stimuli 
(e.g., spider jump scare).  
 
Neurophysiological activity change 
During trials with and without intracranial electrical stimulation 
Changes in theta, gamma, and theta-gamma coupling will be measured both in relation to changes in 
physiology on trials with and without intracranial electrical stimulation as well as in relation to changes in the 
contextual virtual environment. 

INCLUSION OF INDIVIDUALS ACROSS THE LIFESPAN 
Both children under 18 and adults over 70 will be unlikely to have intracranial surgery for the treatment of 
epilepsy or PTSD, and it is unlikely that they will be in the subject pool. Nevertheless, these participants would 
be excluded from the proposed study because they would introduce considerable heterogeneity in the study 
results related to age. Children are undergoing brain maturational changes and older adults are more likely to 
have neurodegenerative changes in the hippocampus and amygdala which would introduce confounding 
variables for the analysis and interpretation of the electrophysiological data from these age groups. The 
investigative team has extensive experience in clinical and research work with individuals of the ages included. 
Dr. Suthana (primary mentor) has conducted numerous research studies, including clinical trials, utilizing deep 
brain recordings via intracranially implanted depth electrodes in research participants of all ages. Dr. Jang has 
extensive experience in research with young and older adults within the age range that will be recruited for the 
proposed research. All studies will be performed in close collaboration with the clinical team including 
collaborators Dr. Jean-Philippe Langevin (neurosurgeon) and Dr. Ralph Koek (psychiatrist) to ensure a safe 
experimental environment for all research participants.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

INCLUSION OF WOMEN AND MINORITIES 
Approximately 12 participants with epilepsy and 2 participants with PTSD with the chronically implanted RNS 
system will be recruited annually, for a total of 70 participants during the total project period of 5 years. We will 
not include pregnant women, individuals who are hospitalized due to severe mental illness, incarcerated 
individuals, individuals with primary psychotic disorders, or anyone who do not have the capacity to adequately 
provide voluntary informed consent. For participants with epilepsy, we expect a roughly equal number of 
individuals assigned female versus male at birth, with no exclusion based on ethnicity or race. The estimated 
enrollment by race/ethnicity and sex/gender is summarized in the Inclusion Enrollment Report. It is based on 
the percentages of prior and ongoing enrollment of neurosurgical epilepsy patients at UCLA. UCLA serves 
large urban populations that are racially and culturally diverse, and the full array of racial/ethnic minority 
populations within the referral base includes Hispanics, Blacks, Asians, Pacific Islanders, and Native 
Americans. Between the years 2011-2021, the estimated distributions of the UCLA epilepsy neurosurgical 
study population have been as follows: Caucasian 73%, Hispanic 21%, Asian and Pacific Islander 3.5%, and 
Black 2%. For participants with PTSD recruited through a separate NIH UH3 clinical trial (PI: Langevin), only 
individuals of the male sex are eligible for the study with no exclusion based on ethnicity or race, per request 
from the NIH.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

RECRUITMENT AND RETENTION PLAN 
Recruitment 
Participants with epilepsy: All participants 18 years or older 
who have undergone implantation of the NeuroPace Responsive 
Neurostimulation (RNS) device for the treatment of epilepsy with 
at least one electrode implanted in the hippocampus or amygdala 
will be invited to participate in this study. UCLA is a worldwide 
leading center for clinical and research work with RNS patients, 
and the Suthana lab maintains a database of approximately 250 
RNS patients who have expressed interest in participating in 
research experiments and/or have already participated in the 
lab’s previous studies. Given the Suthana lab’s track record, we 
do not expect any issues with recruiting enough RNS participants 
for the proposed experiments.  
The epilepsy veteran population at the Veterans Affairs Greater 
Los Angeles Health System (VAGLAHS) will serve as the primary 
recruitment site for participants with co-morbid anxiety-related 
disorders including generalized anxiety disorder (GAD) and post-
traumatic stress disorder (PTSD). While the prevalence of 
anxiety-related disorders in epilepsy patients is around 25-30%5,6, 
in the veteran population it is a bit higher, at about 36%7. In an 
internal analysis of the epilepsy population who received care through the VAGLAHS in the year 2020, our 
group found a high rate of comorbidity (Figure 1, left) where patients with a current diagnosis of PTSD or any 
anxiety disorder comprised of 56% of the total number of patients (37 out of 66). In a portion of the patients 
who were assessed for anxiety symptom severity using standardized questionnaires such as the Beck Anxiety 
Inventory8 or GAD-79, we found that there was a balanced distribution across the spectrum of symptom 
severities from minimal to severe (Figure 1, right). Therefore, we anticipate recruiting epilepsy patients with a 
diverse range of anxiety-related symptom severities in the proposed studies.  
Participants with post-traumatic stress disorder (PTSD): We will also explore data from our ongoing 
parallel NIH UH3 Clinical Trial (PI: Langevin) that includes six PTSD participants implanted with an RNS 
system in the bilateral basolateral amygdala and ventral (anterior) hippocampus. PTSD participants will be 
enrolled in the currently proposed study once they have completed their 1-year clinical trial period.  
All participants volunteering for the study will be given their own copy of the IRB-approved informed consent 
document and a Bill of Study Subject Rights. These documents comprehensively outline the experimental 
tasks, electrode recording procedures, study duration, potential risks, discomforts, and benefits. Dr. Jang and 
Dr. Suthana will be available to address any questions the participants might have. Informed consent will be 
formalized through the participant’s signature. Duplicate copies will be retained for record-keeping in the 
research records of both Dr. Jang and Dr. Suthana's offices. 
Retention 
Our team will maintain regular telephone communication with participants both before and after the protocol to 
maintain volunteer interest. We have consistently observed a high level of cooperation from participants, even 
with multiple study visits. Study personnel will remain on call at all times to address any urgent questions or 
medical concerns participants may have. Dr. Jang and Dr. Suthana will be readily available to address study-
related inquiries and offer counseling and general information. To ensure maximum participant retention, clear 
objectives will be communicated to each participant before enrollment, ensuring they understand the study's 
commitments before consenting. Participants will also be informed about the importance of minimizing dropout 
rates in research studies, thereby encouraging enrollment only if they are confident in completing the full study. 
Recognizing potential transportation and financial limitations, participants will receive $30 per hour during 
research studies along with transportation expenses. For out-of-town participants, airfare and hotel 
accommodations will be provided. To maintain participant engagement, open communication channels will be 
maintained throughout the week of their visit, with readily available contact information for the study team. This 
approach has proven successful in previous studies with similar time commitments with nearly 100% retention 
rates and with over 30 RNS participants successfully completing similar experiments to date. 
 
 
Figure 1. Comorbidity of anxiety disorders and 
severity of related symptoms in the VAGLAHS 
epilepsy veteran population in 2020. Left: 
number of individuals with epilepsy (N=66) and 
those with a co-morbid diagnosis of PTSD (N=29), 
other anxiety disorders (N=16), or both (N=8). 
Note the high prevalence of individuals with a 
PTSD diagnosis (44%) as well as those with any 
anxiety-related disorder (56%). Right: percentage 
of patients with minimal, mild, moderate, and 
severe symptoms of anxiety in a portion of the 
epilepsy patients (N=36) who were assessed for 
symptom severity. 

STUDY TIMELINE 
For an overview of the proposed study timeline please see the figure below. To acquire sufficient data for both 
the Recording and Stimulation experiments during the first 3 years, we anticipate enrolling between 10-14 
epilepsy participants and 1-2 PTSD participants per year across the two clinical sites (UCLA and VAGLAHS). 
This will allow each study to recruit at least 20 participants which should be more than sufficient to address the 
specific aims. At the end of each year, study recruitment methods will be evaluated and modified if needed to 
meet our recruitment goals. Based on historical recruitment data from the Suthana Lab involving both returning 
RNS participants and individuals newly implanted with the RNS device for the treatment of epilepsy or PTSD, 
we do not expect any issues with recruiting these participant numbers locally. As data collection proceeds 
during years 1-3, we will develop and apply behavioral and neurophysiological analyses on an ongoing basis. 
Group statistical analyses will be performed at the conclusion of each experiment for manuscript preparation 
and submission. Years 4-5 of this award will provide time to prepare and conduct follow-up studies based on 
the findings from the previous years. Concurrently, time will be dedicated to preparing an R-level 
independence award and a move to my independent laboratory space (either through UCLA or an alternative 
institution). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

PROTECTION OF HUMAN SUBJECTS 
1. Risks to Human Subjects 
a. Human Subjects Involvement, Characteristics, and Design 
i. Study Design: Participants will perform a virtual reality (VR) task involving ambulation in a virtual 
environment (e.g., library, grocery store, museum) while intracranial electrophysiological and 
biometric data are recorded. For a follow-up study (Stimulation Experiment), intracranial recordings 
will be halted, and participants will receive targeted electrical stimulation of the right amygdala 
during specific trial periods to test for enhancement of fear extinction learning.  
ii. Subject Population: Participants between 18 and 70 years of age who underwent implantation of 
the NeuroPace responsive neurostimulator (RNS) to the hippocampus and/or amygdala for the 
treatment of epilepsy or PTSD will be recruited (see Eligibility Criteria). Importantly, our studies will 
only be performed voluntarily for individuals who already received the RNS implantation for clinical 
care. There is no instance in which the research will play any role in the clinical decision-making 
process. In particular, the placement of electrodes will strictly be based on clinical criteria. 
b. Study Procedures, Materials, and Potential Risks 
i. Study Procedures: All participants will have already completed a brain MRI, head CT, and 
neuropsychological evaluation as a part of their standard clinical evaluation. Participants can 
provide their consent to share these medical records including any other major health problems 
such as conditions limiting mobility. The discussion regarding the research studies occurs at least 3 
months after RNS surgical placement and is conducted by Dr. Jang who has no other involvement 
with clinical cases and no relationship of authority or unequal power with the participant. 
Participants will be advised that the decision to participate in the research is entirely voluntary and 
will not affect their medical care in any way. For participants traveling long distances, the in-person 
discussion may take place over the phone.  
If a participant agrees to join the study, they will follow the informed consent protocol as it is 
approved by the UCLA Institutional Review Board (IRB) committee. The RNS system has been 
approved for use since 2013 by the FDA and recently by the IRB committee at UCLA. Importantly, 
the stimulation configuration for the RNS device will be turned off during testing sessions. A staff 
member with seizure first-aid training will be present at all times during experimental sessions. No 
participant has experienced a seizure thus far during testing in more than 30 participants who 
completed similar studies in the Suthana Lab. Testing will stop at the participant’s request or when 
any of the staff members including Dr. Jang and Dr. Suthana deem it necessary for the comfort or 
safety of the participant. There will not be a conflict of interest between the medical needs of the 
patient and the research procedures.  
During the virtual reality task, participants wear a head-mounted display (i.e., Meta Quest Pro). The 
VR headset is also equipped with small reflective markers that are detected by the motion capture 
cameras installed in the laboratory for wireless 3-D motion tracking. The BioNomadix Smart Center 
(Biopac) will record heart rate and skin conductance. Data can be streamed in real-time to the 
computer that is running the behavioral task for synchronization of multiple data streams. 
ii. Materials: Electrophysiological data are recorded digitally for storage and analysis. Clinical data is 
extracted from patient records with signed consent from participants. Participants are given number 
codes for identification to maintain confidentiality, and thus data is anonymized to remove any 
personally identifiable information. The identifiers are stored on encrypted drives secured with 
UCLA standards and available only to Dr. Jang, Dr. Suthana, and Staff Research Associate Sonja 
Hiller. Local backup is also performed on encrypted hard drives. Computers are protected from 
cyber-attacks thanks to the UCLA firewall.  
Anonymized participant data may be used for teaching purposes or publication in journals, but no 
identification of patients is made on any of these materials. Data is stored on the secured UCLA 
Hoffman cluster server, computer hard disks, and external hard drives, which are secured in the 
Suthana laboratory which is dedicated to this work alone. Only researchers involved in the study 
have keys to the laboratory and thus access to the data. They do not share this data with any 
outside researchers. If applicable, we will ask the participant for permission to use photographs or 

videos that will be used only for scientific communication (e.g., presentation of results at 
conferences or as supplementary material for publications). HIPAA regulations will be carefully 
followed in all cases. 
For RNS System data, after it is collected for study participants it is also uploaded to the NeuroPace 
Patient Data Management System (PDMS). Afterward, the data will be converted to a non-
proprietary anonymized format and copied directly from the commercial RNS Programmer or 
received from NeuroPace through a secure method. From UCLA, RNS System data may be 
downloaded by authorized individuals. UCLA will provide the following information to NeuroPace: 
(1) authorization for NeuroPace to manage and transfer RNS System data as described here, (2) 
the identities of authorized users, including NeuroPace-approved individuals as authorized users, 
and (3) documentation of informed patient consent to share their RNS System data with authorized 
users and NeuroPace for research purposes.  
iii. Potential Risks: The RNS is an adjunctive therapy in reducing the frequency of seizures in 
individuals 18 years of age or older with partial onset seizures who have undergone diagnostic 
testing that localized no more than 2 epileptogenic foci, are refractory to two or more antiepileptic 
medications, and currently have frequent and disabling seizures. The VR study is completed in 30 
minutes up to 1.5 hours. During this time seizure detection and responsive stimulation are withheld 
with the participant’s informed consent. It is important to note that this does not deviate significantly 
from baseline RNS activity – since the RNS device has a prescribed daily limit on the frequency of 
therapy (i.e., stimulation), many participants already have periods during a typical day when therapy 
is withheld for an extended period. However, to minimize risks, a staff member with seizure first aid 
training will be present at all times and the patient’s behavior and real-time iEEG will be observed 
during the experiment. Therefore, the risk of a seizure will be obviated by continuous EEG 
monitoring for early signs of seizure activity and immediate cessation of the study if needed. Dr. 
Jang will be alerted if there are any signs of a seizure or psychological distress, at which point the 
session is discontinued. 
Regarding risks related to intracranial electrical stimulation, the patients recruited in this clinical 
study have already undergone the placement of intracranial electrodes to undergo electrical 
stimulation for the treatment of epilepsy or PTSD. The risk of an electrical stimulation leading to 
seizure activity has been assessed by measuring the threshold stimulation parameters that cause 
synchronous discharges that can be recorded through EEG, also known as the after-discharge 
threshold. Stimulation in our protocol will be similar to that of prior studies where it was current-
regulated, charge-balanced, with biphasic rectangular pulses set below the after-discharge 
threshold which typically ranges between 1.0 mA–2.0 mA10. For each pulse, total stimulation will 
range between 2.5-10.1 μC/cm2 per phase, which is well below the safe maximum used for chronic 
(30 μC/cm2 per phase) and acute (57 μC/cm2 per phase) stimulation11,12. The absence of any after-
discharge threshold at a particular site will be carefully established before each session and 
stimulation will always be set below the threshold. Previous human studies, using parameters of up 
to 3.0V, 450μs pulse width, and 130Hz, have shown to be safe and well tolerated in patients with 
epilepsy with depth electrodes in the temporal lobe12. Similar stimulation levels are used in our 
patients and clinical studies for seizure control13. As mentioned above, there will be continuous 
monitoring of the current charge and after discharges throughout the stimulation session to monitor 
for any possible seizure activity which will lead to an immediate reduction of the current if needed. 
We will also recruit individuals with PTSD from our ongoing UH3 clinical trial, which includes six 
participants who have RNS electrodes implanted within the bilateral amygdala and hippocampus for 
the treatment of PTSD. These participants do not have a co-morbid diagnosis of epilepsy. We have 
now completed 6 years of continuous stimulation in one patient and 2 years in a second patient with 
PTSD both of whom showed no serious adverse side effects. Further, monthly surveillance EEG 
showed no seizures or epileptiform activity in these two patients. We have found that transient 
nausea may be related to the stimulation, however, tends to improve quickly. To mitigate the risks 
of neurostimulation in patients with PTSD, the stimulation sessions will be performed with 
continuous scalp EEG monitoring. Psychological side-effects related to neurostimulation can occur 
after extensive modulation of the network. Acute short-term stimulation is not expected to be 
associated with significant emotional deterioration. In addition, PTSD patients will have completed 
the 1-year UH3 RNS clinical trial where during the trial they will have been admitted to the epilepsy 

monitoring unit to be observed during neurostimulation sessions. In case a psychological 
deterioration occurs, the study psychiatrist and team would evaluate the patient to treat the 
condition at the time during the clinical trial before considering eligibility for the proposed study. PI 
Langevin will determine the eligibility of the PTSD patient for the proposed study based on these 
outcomes assessed during the clinical trial.  
Regarding potential risks associated with the VR fear-conditioning experiment, participants may find 
the VR experiments aversive, challenging, boring, or frustrating. Participants have the option to stop 
should they feel uncomfortable for any reason. There is a small risk of dizziness or nausea 
associated with wearing a head-mounted display that is mitigated when the participant can move 
their head freely due to associated vestibular input. Of our participants thus far, no one complained 
of disorientation during ambulatory VR tasks likely because head movements are allowed during 
the tasks. Risks associated with photosensitivity in epilepsy, which ranges between 2-14% 
prevalence14, will be reduced to negligible by ensuring that characteristics (flash rate, color, 
intensity, light-dark patterns) of visual stimuli are not in the range to provoke seizures in this 
population15. 
2. Adequacy of Protection Against Risks 
a. Informed Consent and Assent 
The proposed studies are experimental in nature; none of the interventions involve clinical treatment of 
participants. However, they will strictly adhere to HIPAA regulations at every stage. Before commencing 
the study, all participants will provide informed consent following the UCLA IRB-approved protocol 
(UCLA Human Subjects Protection Committee, IRB#21-000697). To ensure compliance, all study 
personnel will have completed the HIPAA Privacy Rule Research Education Course and will undergo 
annual renewal. Additionally, study personnel will have completed Collaborative Institutional Training 
Initiative (CITI) courses, including those related to biomedical, social, and behavioral research, with 
renewal every 3 years. Initial phone screening will involve an oral screening script, and eligible 
participants will be invited to UCLA. Written consent will be obtained before proceeding with study 
procedures. Informed consent meetings will be conducted in a private research office space with Dr. 
Jang, where all legal and ethical safeguards for participants will be implemented following standards set 
by the UCLA Human Subject Protection Committee. During the informed consent process, participants 
will be presented with detailed information about the potential risks and benefits of the study, 
procedures involved (including the fear conditioning task, electrode recordings, and stimulation), study 
duration, location, confidentiality, and their right to withdraw. Dr. Jang will review the UCLA IRB-
approved informed consent document in detail, explaining the purpose of the study, potential risks and 
benefits, and participant rights, and addressing any questions. Participants provide informed consent by 
signing the consent form; one copy will be securely stored in a locked drawer in Dr. Jang’s office, while 
the other copy will be provided to the participants for their records. Additionally, participants will receive 
a copy of the California Subject’s Bill of Rights before giving consent, ensuring transparency and 
understanding throughout the consent process. 
b. Protections Against Risk 
Neurological, psychological, and psychiatric clinical data are securely stored in files within Dr. Jang's 
office, accessible only to investigators directly involved in the project within the clinical research 
program, and in compliance with HIPAA regulations. All investigators have been briefed on the 
confidential nature of this data and the imperative of maintaining strict confidentiality. In publications, 
precautions have been taken to remove any personal identifying information. No files have been 
disposed of as our program emphasizes long-term follow-up. Upon termination of the research project, 
these files will be transferred to UCLA hospital records for selection of relevant material for medical 
records, with the remainder disposed of. Referring physicians are informed of all procedures used in 
our protocol as per program policy. The principal investigator (Dr. Jang) retains the authority to withdraw 
a subject from the research if circumstances necessitate, such as posing a risk to the participant's 
safety or health. In the rare event of profound psychological distress or suicidal ideation, Dr. Jang, 
trained as a psychiatrist, will intervene to de-escalate the situation and ensure the participant receives 
appropriate emergency medical care. Participants will receive medical treatment at no cost for any 
injuries resulting directly from the research procedures, adhering to UCLA policy. The VR fear 
conditioning paradigm typically lasts between 30 minutes to 1.5 hours. For RNS patients, seizure 

detection and responsive stimulation are temporarily withheld during this period (see Potential Risks 
above). Discomfort associated with the research protocol is generally minimal compared to the 
discomfort of clinically mandated RNS electrode implantation. 
c. Vulnerable Subjects, if relevant to your study 
The proposed study will recruit and consent participants with possible co-morbid psychiatric disorders 
and therefore will evaluate each subject’s ability to participate in the consent process. The procedure 
includes the use of the UCLA Decision-making Capacity Assessment Tool, which includes a series of 
questions that are asked to determine whether the participant understands the research procedures, 
risks, alternatives to not participating, and other related topics. If it is determined that a participant does 
not have the capacity to provide consent, surrogate consent may be obtained from one who is a legally 
authorized representative with reasonable knowledge of the research participant. 
3. Potential Benefits of the Proposed Research to Research Participants and Others 
There are potential benefits of the research protocol if clinically relevant data is obtained. For example, 
recordings of a seizure may aid in understanding the neurophysiological changes occurring during epilepsy 
and seizures. The risks of the research protocols, as described above, are minimal. For the research 
studies, there are no benefits to the patients, except for incidental findings relating to cognitive abilities that 
may be useful in their clinical treatment. To achieve an understanding of the neural mechanisms of 
behaviors that are uniquely human, it is ultimately necessary to carry out observations directly in the 
human brain. Patients with epilepsy provide important opportunities to carry out studies that have been 
validated in animals. The modern development of safe, effective pre-operative techniques for evaluating 
and treating a patient has made it possible to safely carry out intracranial neurophysiology studies that will 
increase our knowledge of human brain mechanisms and ultimately lead to novel therapeutics.  
4. Importance of the Knowledge to be Gained 
Understanding human brain function is not only valuable for the pursuit of knowledge but also holds 
immense potential to unveil new treatment pathways for psychiatric conditions like PTSD and GAD. Given 
the tremendous impact of anxiety and fear-related states on daily functioning and well-being, the 
knowledge potentially gained by this project about the neural mechanisms of fear- and anxiety-related 
states and the potential for treatment of anxiety disorders are extremely important. The large number of 
people affected by anxiety disorders combined with the potential to benefit their symptoms provides a 
reasonable justification for exposure to the minimal potential risks. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

DATA AND SAFETY MONITORING PLAN 
Monitoring Procedures 
As detailed in the Protection of Human Subjects, the proposed study carries only minimal risk since it recruits 
participants who already have the RNS system implanted for the treatment of epilepsy or post-traumatic stress 
disorder (PTSD). Research considerations never influence the clinical decision-making process. In particular, 
the placement of electrodes is based solely on the data obtained from previous scalp EEG recordings, 
imaging, and other clinical tests undergone by the patient. Dr. Jang will closely monitor all study procedures 
carefully on a per-participant and per-day basis to make sure everything is carried out according to the IRB-
approved protocol. Specifically, Dr. Jang will ensure that informed consent is obtained prior to beginning any 
research procedures and that all participants meet eligibility criteria. Data will be immediately accessible to Dr. 
Jang for review. Dr. Jang will review any adverse events in real-time as well with Dr. Suthana every quarter. 
Serious adverse events will be reviewed by Dr. Jang and Dr. Suthana immediately. Dr. Jang will ensure that 
any adverse effects as well as any protocol deviations are reported to the NIH, FDA, and UCLA IRB in a timely 
fashion and according to regulatory requirements. 
Adverse Events 
For this study, the following adverse event definitions are used: 
Adverse event: Any unfavorable and unintended sign, symptom, or disease temporally associated with the use 
of a medical treatment or procedure, regardless of whether it is considered related to the medical treatment or 
procedure. 
Serious Adverse Event: Any adverse event that results in any of the following outcomes: 
- 
Death 
- 
Life-threatening event 
- 
Event requiring inpatient hospitalization 
- 
Persistent or significant disability/incapacity 
ClinicalTrials.gov 
The proposed study will be registered with clinicaltrials.gov. 
Data Management 
The data generated by this proposal will be available to the academic community after initial publication upon 
request to the PI. We recognize that we are building a unique behavioral and electrophysiological dataset that 
can be used to probe many more questions than we specifically seek to address. We anticipate a substantial 
number of data-sharing requests. Below, we outline steps that will be taken to ensure proper HIPAA-compliant 
data handling and sharing. 
Training: Before handling or collecting data, all researchers will be certified by the David Geffen School of 
Medicine at UCLA with regards to Protecting Human Research Subjects in both Biomedical and Genetics 
Research, and Social and Behavioral Research with re-certification completed every year. All researchers will 
also complete the HIPAA Privacy Rule Research Education Course.  
Data types, collection, and sharing: Demographic data, medical history, imaging data, neuropsychological 
data, behavioral task data, and contact information will be collected in addition to the neuroimaging data (iEEG, 
MRI). File types (format) include neuroimaging (.nii), electrophysiological (.cnt, .edf, .set), neuropsychological 
(.xls), demographic (.xls), and statistical output files (.mat). Participant contact and personal information will not 
be shared with researchers or any collaborators; each participant will be coded and only Dr. Jang, Dr. Suthana, 
and the Staff Research Associate (Sonja Hiller) will have access to the code. Before sharing data amongst 
researchers and the larger scientific community, Dr. Jang will ensure that data is de-identified in compliance 
with HIPAA; some information may be recoded or removed to ensure confidentiality as necessary. No private 
records or identifier information will be made available or transferred. Participant identities are never disclosed 
by publication or any other means. Informed consent forms are kept in locked files for at least 7 years beyond 
subject participation as legally required. Information in the computerized database is protected by a firewall 
and special username/password accounts are given only to authorized personnel. Designated employees 
maintain the security of computerized databases. Data will be shared between lab members using a secured 
server with encryption and performed by authorized users using password-protected accounts. We will provide 

open access to all tools developed and anonymized data using several data-sharing avenues, including the 
NIMH Data Archive (NDA), DABI (Data Archive BRAIN Initiative), Blackfynn, and Neurodata Without Borders 
(NWB). Any hardware or software developed for the platform will be shared via publications and GitHub 
repositories. A shared goal of our group is to make it possible for as many researchers to begin studies of a 
similar nature within their laboratories. 
Data Standards and Storage: Data analysis will be completed using a centralized neurophysiological and 
imaging analysis and storage infrastructure (UCLA Hoffman) under the UCLA Institute for Digital Research and 
Education (IDRE) High-Performance Computing (HPC) and Storage, Operations & Support, which will provide 
computational power to process large data. Consultation will be provided through IDRE Staff in the following 
areas: multiprocessor/multicore/GPU programming, efficient algorithms for scientific computing, code 
optimization for using HPC resources, scaling and analysis of parallel code, parallelization or porting on 
different platforms, debugging, scientific visualization with large datasets, and grid/cloud computing.  
Data Archiving: After publication or the funding period has ended, the UCLA Hoffman data will be 
compressed and archived using two enterprise-class Synology Diskstation 1815+ network-attached storage 
devices with dual 1515+ expansion units creating a combined total storage of 200TB. All Diskstation and 
expansion units are fault tolerant and have enterprise-class uninterruptible power supplies to condition power, 
protect against surges, and ensure battery backup protection against power problems. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

STATISTICAL DESIGN AND POWER 
Data Analysis Strategy 
Task-induced physiology: To assess the effect of task events on physiology (e.g., skin conductance, heart 
rate), both within and across participant analyses will be performed. Within-subject analyses will be performed 
on the mean physiological response across trial types (e.g., conditioned stimulus CS+ versus CS- trials, 
acquisition versus extinction trials). Detection of task-event-induced physiological changes observed across 
subjects will be assessed using a linear mixed-effect model. Here, each participant’s physiological variable of 
interest will be reported as a ‘response variable’ and trial type (CS+, CS-) as ‘predictor variables’ to predict 
physiological changes in response to task events. All predictor variables will be specified as fixed effects. 
Participant number will be used as a random effect variable to control for variation in the magnitude of task 
event-evoked changes across participants. 
Task-induced iEEG power: To assess the effect of task events on intracranial signals, we will calculate 
changes within specific frequency bands (e.g. theta, gamma) surrounding the presentation of various stimuli 
during task performance (e.g., conditioned versus unconditioned stimulus). Frequency power will be calculated 
using the “better oscillation detection” (BOSC) method where power is detected via continuous wavelet 
transform using a Morlet wavelet16. Unlike other time-frequency analyses, the BOSC method calculates a 
power threshold for each frequency defined as the 95th percentile of the theoretical x2 distribution of wavelet 
power values centered at a mean derived from an estimate of the local background spectrum using linear 
regression. By only detecting segments of activity that meet rigorous criteria, BOSC rejects transient, non-
oscillatory events that would otherwise be misinterpreted as rhythmic activity. For each event of interest, power 
will be calculated over an iEEG trace that extends from 2 seconds before stimulus/physiology onset to 1 
second after the event ends. Event-related spectral changes will be detected via z-scoring event activity to pre-
stimulus baseline activity, defined as 500-2000ms before the CS onset. Comparison of normalized spectral 
changes between various events will provide insight into the neurophysiological signatures underlying fear 
memory processing. The significance of within-subject event-related oscillatory power differences will be 
assessed via non-paired t-tests on mean total frequency band power (e.g., theta, gamma) across various task 
events. Detection of task-event-induced spectral changes observed across subjects will be assessed using a 
linear mixed-effect model analogous to the one describe above (see Task-induced physiology). Models will be 
implemented using each participant’s total baseline normalized power in a designated frequency (e.g., theta: 4-
8 Hz) within a task-relevant time window as a ‘response variable’ and event type (e.g., CS+, CS-) as ‘predictor 
variables’ to predict oscillatory band power variability in response to task events. Using this strategy, we can 
examine the effect of event type on oscillatory dynamics across participants despite individual differences.  
Physiological data preprocessing: Skin conductance activity, measured in units of 𝜇𝑆, will be log-
transformed to correct for known skew in distributions17, then z-transformed using the pre-stimulus baseline 
activity, defined as 500-2000ms before the CS onset. Using a previously described convex optimization 
approach18, skin conductance activity will be decomposed into two components, tonic and phasic, which have 
different time scales and relationships to fearful stimuli. Although the phasic component is theorized the 
represent the sudomotor nerve activity corresponding to acute increases in sympathetic tone, both phasic and 
tonic activity will be evaluated in their relationship to fearful stimuli. Heart rate will be computed by counting the 
number of beats within a 4s sliding window moving at 4ms (sampling frequency). Beats will be detected from 
the photoplethysmography (PPG) signal using the Multi-Scale Peak & Trough Detection (MDPTD) algorithm 
19,20.  
iEEG-physiology correlation analysis: To examine the relationship between iEEG dynamics and 
physiological parameters such as heart rate, heart rate variability, and skin conductance response, a linear 
mixed model framework will be used. Here, time-varying iEEG data is modeled as a function of the above-
mentioned variables and time delay. The design matrix, which links these variables with the iEEG data, 
consists of the following basis functions: cubic B-splines, sines and cosines, and polynomials. Model selection 
will be done using Bayes Information criteria to avoid overfitting. Additionally, to determine variables with larger 
modulatory effects, we will use the analysis of deviance coupled with the chi-squared test of significance. 
Furthermore, we will generate surrogate data by circularly shifting the iEEG data with respect to the 
physiological variables (N = 2000) to calculate a z-score value for the correlation coefficients for a given 
electrode in each participant. We will use binning methods to compute the theta or gamma power across 
behavioral tasks. Recording channel numbers will be used as random effect variables (‘blocking variables’), to 
control for the variation coming from different channels and to account for different numbers of recording 

channels between participants. All continuous predictor variables (physiological data) will be standardized (z-
scored) before model fitting to enable a direct comparison of the impact of each variable on oscillatory band 
power against each other. Each of the predictor variables’ impact on the response variable will be reflected by 
the variable’s beta weight (standardized effect size) and corresponding t-statistic. A similar strategy will be 
used to examine the relationship between neural and physiological variables with movement variables such as 
velocity, acceleration, and position.  
Inter-regional phase synchrony: The Phase Locking Value (PLV) is a statistic that can be used to investigate 
task-induced changes in long-range synchrony of neural activity21,22. This may be used as a proxy of the 
relative amount of communication within a network during different periods. The PLV assesses the degree 
phase (Φ) covariance between two channels (e.g., amygdala and hippocampus) averaged across N trials 
using the following formula: 
𝑃𝐿𝑉(𝑡, 𝑓) = 1
𝑁/0 e!(#!,#($,&)(#!,$($,&))
)
*+,
/ 
Where n = trial number, a and b designate electrodes (e.g., hippocampus vs amygdala), f = frequency, t = time 
point. PLV will be calculated for each electrode pair allowing us to assess the variability of two structures’ 
phase relationship across repeated exposure to different experimental variables. PLVs that approach 1 
indicate strong phase synchrony and little variability across trials. To test the statistical significance of PLV, a 
null distribution will be created by randomly shuffling the signal from each electrode pair and computing the 
corresponding PLV spectrograms 1000 times. PLVs that exceed the 95th percentile of the surrogate 
distribution will be deemed significant.  
Intra- and Inter-regional Phase-Amplitude Coupling: To compute cross-frequency phase-amplitude 
coupling, the Modulation Index (MI) is calculated between the phase component of a low-frequency band (e.g., 
theta; Φ-), and the amplitude component of a high-frequency band (e.g., gamma; 𝐴.) within each time point. 
To measure the strength of coupling between the theta phase (Φ-) and gamma amplitude (𝐴.), those two 
signals are combined into an analytic complex-valued signal via Euler’s formula, and then the vector mean is 
computed, with the PAC quantified as the vector length and the preferred phase measured as the resultant 
vector’s angle:  
𝑀𝐼= /𝑇(, 0 𝐴.𝑒!#%
/
$+,
/ 
Where t = time point and T = total number of time points. For example, to determine MI for N trials of a 
particular condition (e.g., CS+), a trial-by-time matrix pre-filtered at the theta (4-8 Hz) range, {𝑋-[𝑡]},:), is 
truncated to time regions [𝑡1: 𝑇] corresponding to the time window of the trial, reshaped into a 1-by-(𝑁∗𝑇) 
array of concatenated trials, then converted into a complex valued signal with the Hilbert transformation. The 
phase angle time series of this complex-valued signal results in the instantaneous phase of the low-frequency 
band, Φ-. Similarly, iEEG trials pre-filtered at the gamma range (60-120 Hz) range >𝑋.[𝑡]?,:) are truncated, 
vectorized, and converted via the Hilbert transform to complex-valued form. The complex modulus (absolute 
value) is used to compute the instantaneous high-frequency amplitude signal 𝐴.. To measure strength of 
coupling between the theta phase (Φ-) and gamma amplitude (𝐴.), those two signals are combined into an 
analytic complex-valued signal via Euler’s formula, and then the vector mean is computed, with the raw 
modulation index measured as the resultant vector length, while the preferred phase is measured as the 
resultant vector’s angle.  
For surrogate analyses potential autocorrelations in the signal are accounted for by generating 2000 surrogate 
Modulation Indices, {𝑀𝐼2344},:5111, in which the amplitude component is shifted with respect to the phase 
component by a pseudo-randomly generated lag value of at least 300 msec in duration. A normalized MI index 
is generated by z-scoring against the normal distribution fitted to {𝑀𝐼2344},:5111. 
Neural similarity analysis: To assess whether an electrode or a set of electrodes within an anatomical region 
of interest form distinct neural representations of different environmental contexts, we use a form of 
representational similarity analysis on the spectral iEEG data23,24. Within a given trial, for every 500ms time 
window spaced every 100ms, we construct a feature vector containing oscillatory z-scored power from five 
frequency bands (theta, 3.–8 Hz; alpha, 8–12 Hz; beta, 13–25 Hz; low gamma, 30–58 Hz; high gamma, 62–

100 Hz) across all relevant electrodes. For each time window (𝑖) of a given trial, we define feature vectors as 
follows: 
𝑇A⃗! = [𝑧,,,(𝑖) … 𝑧,,6(𝑖) … 𝑧7,6(𝑖)] 
Where 𝑧8,&(𝑖) is the z-transformed power of electrode 𝑙= 1 … 𝐿 at frequency band 𝑓= 1 … 𝐹 in time window 𝑖. 
For 𝐿 electrodes and 𝐹 frequency bands, we thus create a feature vector at each time window that contains a 
total of 𝐿∗𝐹 features. We quantify the neural similarity between two trials by calculating the cosine similarity 
between these feature vectors for all possible pairs of time windows, generating a precise temporal map of 
neural similarity between the two trials. We compute this neural similarity matrix for every pair of trials, then 
compare the mean similarity matrix between trials within the same environmental context (e.g., library-library) 
versus trials with mismatched contexts (e.g., library-museum).  
Stimulation effects analyses: The effect of intracranial electrical stimulation on physiology will use a 
between-subjects design. For descriptive analysis, the time series corresponding to a particular physiological 
variable of interest (e.g., skin conductance) will be averaged and compared between CS++ trials (with 
electrical stimulation) versus CS+ trials (without stimulation). Time points where there is a significant difference 
in the variable of interest will be determined using an independent samples t-test and controlled for multiple 
comparisons using the Bonferroni-corrected p-values. We will also use a linear mixed model similar to the ones 
described above where time-varying physiological data (e.g., skin conductance) is modeled as a function of 
binary dummy variables corresponding to whether a trial was CS++ or CS+.  
Justification of Sample Size 
Previous iEEG studies from Dr. Suthana’s group involving RNS participants during memory tasks found 
statistically significant effects in a sample of 5 participants25. Intracranial stimulation studies with 6 and 13 
participants yielded an effect size (Cohen’s d) of 1.74 and 1.18 respectively when comparing stimulated and 
non-stimulated trials10,26. We anticipate a minimum of 10 participants will be required each for the Recording 
Experiment and Stimulation Experiment. Since most participants have multiple electrode contacts that fall 
within both the right and left amygdala, we can test several potential stimulation regions in each participant. We 
propose to enroll 40 total participants during the proposed project period and will also combine results with our 
current preliminary findings. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

DISSEMINATION PLAN 
 
Dr. Anthony Jang will be responsible, with support from his mentor Dr. Nanthia Suthana, for handling the 
clinical trial registration and reporting requirements for this project. This includes registration of the clinical trial 
on “ClinicalTrials.gov” (or an alternative publicly available platform, as discussed below). Once a record is 
established, Dr. Jang will confirm the accuracy of the record content, resolve problems, and maintain records 
including content updates and modifications. Registration of the study on the platform will occur no more than 
21 days after the first participant is enrolled and required information will be updated annually. Dr. Jang will 
also be responsible for posting any results including adverse events no later than 12 months after the 
completion of the trial. UCLA has an internal policy in place that ensures that clinical trials are registered and 
that the results are reported in compliance with the NIH policies. In coordination with the UCLA Office of 
Contract and Grant Administration, Dr. Jang and Dr. Suthana will certify policy compliance with each 
submission of a required report. Dr. Suthana is the principal investigator of separate clinical trials funded by the 
National Institute of Mental Health (NIMH), the National Institute of Neurological Disorders and Stroke 
(NINDS), and the National Institute on Aging (NIA), and thus she is well-positioned to support and guide Dr. 
Jang in the safe and responsible conduct of clinical trials and to help him meet all required registration and 
reporting timelines. UCLA has further established two institutional accounts in the Protocol Registration and 
Results System (PRS) for “ClinicalTrials.gov” to support UCLA investigators who serve as the Responsible 
Parties on a clinical trial. Moreover, the UCLA Office of Contract and Grant Administration as well as the UCLA 
Clinical and Translational Science Institute (CTSI) have support staff to facilitate the process of registration and 
results reporting for clinical trials. Dr. Jang will work closely with them to register this trial and to submit 
summary results in a timely manner.  
 
As per the Funding Opportunity Announcement (FOA PA-20-201), the proposed study falls under the category 
defined by the NIH as “Basic Experimental Studies with Humans (BESH)”, which meets both the NIH definition 
of a clinical trial and the definition of basic research. According to the NIH (notice number NOT-OD-22-205), 
BESH studies are not required to register and report results on ‘ClinicalTrials.gov’ but can choose to register 
and report results on alternative publicly available platforms. Dr. Jang and Dr. Suthana may thus use an 
alternative publicly available registration and reporting platform instead of ‘ClinicalTrials.gov’ and adapt the 
details of the dissemination plan described above to meet the requirements of this alternative platform. 
However, this will be in close coordination with NIH officials to always ensure compliance with the NIH’s policy 
requirements. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

SPECIFIC AIMS 
Fear responses that are excessive and disproportionate to the situation are a hallmark of anxiety disorders 
such as generalized anxiety disorder and post-traumatic stress disorder (PTSD). Anxiety disorders affect up to 
25% of the adult population in developed countries27 while speciﬁc conditions like PTSD can affect up to 11.5% 
of U.S. military veterans28. Despite treatment with medications and psychotherapy, about one-third of affected 
individuals will experience residual symptoms associated with high morbidity and healthcare costs29. Despite 
advancements in animal models of fear and anxiety, there remains a substantial gap in understanding the fear 
circuitry in humans and how it may go awry in anxiety disorders. The proposed research aims to address this 
gap by combining mobile intracranial electroencephalography (iEEG) and virtual reality (VR) experiments to 
study the neural correlates of fear processing in humans and assess whether targeted stimulation can be 
employed to enhance fear-related learning, potentially offering a novel therapeutic approach30,31. 
A key component of anxiety disorders is the impairment in fear extinction, namely, the ability to extinguish a 
previously formed association between benign stimuli and a fearful experience. For example, a veteran who 
experiences explosions in the presence of helicopters in Afghanistan may panic upon hearing a helicopter in 
Los Angeles32,33. Rodent studies highlight the hippocampus and amygdala as key brain regions in the 
formation and extinction of fear34–37. It is hypothesized that the hippocampus forms a representation of the 
environmental context while the amygdala ties this context to emotions38,39. Consistent with this, when rodents 
are exposed to a room associated with electric shocks, specific oscillatory patterns (e.g., 3-8 Hz theta activity) 
are observed in the amygdala40–45 along with increased communication between the amygdala and 
hippocampus (e.g., via phase-amplitude coupling)46,47. However, human studies have largely relied on imaging 
methods without direct access to these subcortical structures (e.g., fMRI). Furthermore, traditional experiments 
delivered on computer screens had constraints in manipulating the contextual environment, limiting our 
understanding of these neural circuit mechanisms in real-world, ecologically valid settings48–57.  
In collaboration with the Veterans Affairs Greater Los Angeles Healthcare System, we will work with individuals 
who have already been implanted with a Responsive Neurostimulation (RNS) device for the treatment of 
epilepsy or PTSD. The RNS uses implanted electrodes to directly measure and modulate iEEG activity within 
the amygdala and hippocampus58. Our approach integrates mobile iEEG, peripheral physiological recordings, 
and a novel, ambulatory VR fear conditioning paradigm where participants acquire and subsequently 
extinguish associations between conditioned stimuli (CS; e.g., a change in light color) and a fearful experience 
(e.g., a large spider)3,59,60. The paradigm incorporates changes in the virtual environment to probe the interplay 
between the hippocampus and amygdala during contextual fear learning. Targeted stimulation of the amygdala 
will be used to modulate fear extinction30,31. Lastly, given the veteran population comprises a wide range of 
comorbid anxiety and PTSD symptoms, we will measure trait anxiety characteristics (e.g., generalized anxiety, 
fear sensitivity) and their relationship to neural and physiological activities involved in fear. The proposed 
research aligns with the applicant’s training goals, focusing on mobile iEEG and VR experiments in psychiatry.  
Speciﬁc Aim 1: Investigate hippocampal-amygdala iEEG dynamics that underlie the acquisition and 
extinction of contextual fear. Hypotheses 1 & 2: The fear-associated CS will lead to increased theta power in 
the amygdala (H1) and increased communication (via phase coherence and theta-gamma phase-amplitude 
coupling) between the amygdala and hippocampus (H2). Hypothesis 3: Hippocampal, but not amygdala 
activity, will exhibit distinct neural representations of different environmental contexts during fear conditioning.   
Speciﬁc Aim 2: Test the effects of amygdala stimulation on fear extinction. Hypothesis 4: Amygdala 
stimulation during the CS will facilitate fear extinction as measured by reduced fear-related physiological 
responses (heart rate and skin conductance) when compared to a separate, non-stimulated CS.  
Speciﬁc Aim 3: Characterize the physiological and hippocampal-amygdala iEEG dynamics associated 
with anxiety. Hypothesis 5: Trait anxiety across a battery of clinical assessments will be associated with 
increased skin conductance and amygdala theta power and decreased amygdala-hippocampal connectivity.  
Implications: The proposed program will characterize intracranial neurophysiological signatures of fear and 
assess the efﬁcacy of targeted neurostimulation in reducing fear-related behaviors in individuals with varying 
anxiety levels. By building on decades of ﬁndings across species, the program will uncover human-speciﬁc 
hippocampal-amygdala oscillatory mechanisms, shed light on the pathological states associated with anxiety, 
and make substantial contributions to the comprehensive understanding and treatment of anxiety across a 
wide spectrum.  

RESEARCH STRATEGY 
SIGNIFICANCE 
Anxiety disorders such as generalized anxiety disorder (GAD) and post-traumatic stress disorder (PTSD) are 
among the most prevalent mental health conditions in the world27. In the United States, GAD has an estimated 
lifetime prevalence of 5-12%61 and is associated with significant utilization of healthcare services29. PTSD has 
a lifetime prevalence of 6-9% in adults and affects up to 11.5% of U.S. military veterans28,62. While anxiety 
disorders can respond to standard treatments with antidepressants and psychotherapy, it is estimated that 
one-third of affected individuals will experience residual symptoms or remain treatment-refractory63,64, leaving 
them with a chronic illness associated with increased rates of occupational disability65, substance use 
disorders66, depression65,67, and suicide68. It is theorized that anxiety disorders result from the development of 
fear responses that are excessive and disproportionate to the situation. Our limited understanding of the neural 
mechanisms that underlie such maladaptive fear responses is a major barrier to developing new treatments. 
Recent advancements in implanted neural devices (Figure 1) originally 
used for the treatment of epilepsy provide a unique research opportunity to 
study these mechanisms through direct recordings and stimulation of brain 
regions implicated in fear and anxiety. In particular, the ability to record from 
multiple circuit nodes simultaneously (e.g., the amygdala and hippocampus) 
allows us to investigate not only distinct brain regions but also the 
communication between these structures. At the same time, technological 
advancements allow for the simulation of real-world experiences using 
virtual reality (VR) and physiological measurements through wearable 
devices. Our proposed study will leverage these innovations and a unique 
collaboration with the Veterans Affairs Greater Los Angeles Healthcare 
System (VAGLAHS) to work with individuals who have anxiety-related 
disorders and are implanted with a Responsive Neurostimulation (RNS) 
device for the treatment of epilepsy. To enhance the generalizability of our findings, we will also include 
participants without epilepsy who have an implanted RNS in the amygdala and hippocampus for PTSD through 
a separate clinical trial in our research group. Findings will provide a first insight into intracranial 
neurophysiological signals that underlie functional and dysfunctional emotional responses to threat.  
INNOVATION 
Rare access to individuals with anxiety-related disorders who have implanted electrodes: Our 
collaboration with the VAGLAHS provides the ability to recruit veterans who received the RNS for epilepsy. Our 
preliminary assessment of the VAGLAHS epilepsy population shows a 44% comorbid diagnosis of PTSD and 
56% for other anxiety-related disorders, a significantly higher anxiety disorder burden compared to the general 
epilepsy population5,69. This provides a valuable opportunity to engage with hundreds of potential participants 
with comorbid anxiety disorders with readily accessible intracranial electroencephalography (iEEG).  
Research platform combining iEEG recording, intracranial stimulation, and wearable technologies: Our 
research platform can synchronize iEEG and intracranial stimulation with external wearable sensors that can 
measure heart rate, skin conductance, gaze direction, eye movements, head rotation, body position, and 
velocity while the participant ambulates freely. This platform allows for the investigation of relationships 
between deep brain activity, anxiety-related physiological patterns, and spatial navigation in humans who are 
not constrained to the hospital bed or neuroimaging suite.  
VR to enhance immersion and translational efficacy: Traditional laboratory computer-based tasks are 
limited in their investigation of fear-related behaviors, especially in studying the impact of environmental 
context. VR environments presented on a head-mounted display provide a powerful method for removing the 
participant from the laboratory context and transporting them into an endless number of distinct environments 
while maintaining full control over the similarities and differences between them. Moreover, VR provides a 
heightened sense of presence and immersion, increasing the likelihood that our findings will be more 
applicable and transferable to real-world situations and lead to a more nuanced understanding of fear-related 
behaviors. 
 
 
Figure 1: RNS neurostimulator58. 

APPROACH 
v General Approach 
Fear conditioning as a model for anxiety disorders: Decades of research on fear and anxiety in both humans 
and nonhuman animals have predominantly used fear conditioning paradigms. In a typical fear conditioning 
task, a neutral conditioned stimulus (CS+) is repeatedly paired with an aversive unconditioned stimulus (US), 
leading to the development of fear-related behaviors in response to the CS+ such as increased skin 
conductance, change in heart rate, freezing, and fear-potentiated startle. Subsequently, the acquired fear 
response can be extinguished by repeatedly exposing the participant to the CS+ without the US. The process 
of acquiring and extinguishing fear responses serves as a model for understanding both the development and 
recovery from various anxiety- and trauma-related disorders70. For example, a military veteran with PTSD may 
exhibit fear reactions to stimuli reminiscent of combat trauma, such as the sight of camouflage clothing, the 
sound of helicopters, or the smell of smoke. Such PTSD symptoms may improve after repeated exposure to 
fear-associated stimuli through prolonged exposure therapy (i.e., fear extinction). The fear conditioning 
paradigm can also be expanded to include a test of fear renewal, a phenomenon seen in clinical settings 
where individuals may reexperience previously extinguished fear responses upon re-exposure to the CS+. For 
example, a veteran previously treated for PTSD may have a re-emergence of symptoms after watching the 
news about the war in Ukraine or the Israeli-Palestinian conflict. Our VR fear conditioning paradigm will 
address fear acquisition, extinction, and renewal thereby investigating the full spectrum of fear learning.  
Virtual reality to study fear and anxiety: VR has become an effective method of enhancing the ecological 
validity of human neuroscience research, thanks to advancements in portable VR headset technology and the 
capability to simulate life-like, three-dimensional visual environments. VR fear conditioning paradigms 
demonstrate that virtual CS+ compared to CS- contexts can elicit fear-potentiated startle responses, increased 
skin conductance, and avoidance71–78. Importantly, unlike traditional fear conditioning studies that use aversive 
unconditioned stimuli (US) such as an electric shock or air blast, VR paradigms can use stimuli that are more 
realistic and appropriate for the virtual context, such as verbal insults from another person, various insects, or 
falling from an elevated position71,76,79–81. The proposed project will combine the immersive capabilities of VR 
with simultaneous recordings of physiological and intracranial brain activity. In the VR paradigm, participants 
acquire and subsequently extinguish associations between neutral stimuli and aversive outcomes over 2 days. 
Our study comprises two experiments: The first experiment (Recording Experiment; Figure 2A) aims to 
investigate the neural correlates of fear conditioning while the second experiment (Stimulation Experiment; 
Figure 2B) will investigate the impact of amygdala stimulation on fear extinction. This dual-experiment 
approach allows for a comprehensive exploration of both fear acquisition and extinction processes. 
Participants: Participants are patients with pharmaco-resistant epilepsy who are implanted with the FDA-
approved NeuroPace RNS® system. The RNS detects abnormal electrical activity in the brain and responds by 
delivering imperceptible levels of electrical stimulation to normalize brain activity before an individual 
experiences a seizure. During our experimental studies, the seizure detection and stimulation system will be 
temporarily paused and the RNS will be used for continuous iEEG recording and/or targeted electrical 
stimulation with custom stimulation parameters (see Aim 2 for details). The two program sites, UCLA and 
VAGLAHS, already have access to a substantial cohort of over 250 participants with RNS implants in the 
amygdala and/or hippocampus. Additionally, approximately 10 new participants per year are expected to 
undergo implantation. To assist with the generalization of the data, we will also include 6 participants without 
Figure 2: Schematic of the VR fear conditioning paradigm. A: Recording Experiment to study hippocampal-amygdala circuit activity 
with fear acquisition, extinction, and renewal. B: Stimulation Experiment to determine the effects of targeted amygdala stimulation 
during extinction learning. See Experimental Design under Aims 1 and 2 for further details.  

epilepsy who have an already implanted RNS System in the bilateral amygdala and hippocampus for the 
treatment of PTSD after completing their 1-year NIH clinical trial (UH3; PI: Langevin).  
Electrophysiological and biometric data acquisition: Each participant has two implanted depth electrode leads, 
each with four electrode contacts. iEEG activity is continuously recorded at a sampling frequency of 250 Hz. 
Specially authorized research tools for the RNS system allow for wireless real-time control of the implanted 
system and synchronization with external physiological measurements via wearable sensors. To enable real-
time data storage and synchronization, we will utilize a single-board computer (i.e., Raspberry Pi) which runs a 
server-like state machine that allows any experimental device or application to connect and control the RNS 
system over a secured network. The Raspberry Pi will trigger a noise signal into the iEEG data through a 
telemetry wand (NeuroPace Near Field 
Telemetry Wand) that is secured over 
the implant site on the participant’s 
head, and these noise artifacts will be 
used to synchronize the iEEG data with 
other task variables (e.g., spatial 
location, biometrics). All necessary 
electronics are carried by the participant 
in a custom-built backpack (Figure 3)3. 
Heart rate and skin conductance will be 
recorded using the wireless wearable 
Smart Center system (BIOPAC® 
Systems, Inc.). A pulse transducer is 
secured to the participant’s middle finger 
which uses wireless 
photoplethysmography (PPG) to 
measure heart rate. Two electrodes are 
placed on the participant’s palm to 
record skin conductance as a measure 
of eccrine (skin sweating) activity.  
Electrode localization: The precise anatomical 
location of each electrode contact will be determined 
by co-registering a high-resolution post-operative 
head computed tomography (CT) image to a pre-
operative high-resolution structural MRI image82. The 
CT and MRI are also registered to a high-resolution 
T2 image where the amygdala and hippocampus can 
be automatically segmented based on atlases 
correlating MRI visible landmarks with underlying 
cellular histology83. Each MRI and CT will also be 
registered to an MNI standard brain using advanced 
normalization tools (ANTs)82 to look for left vs. right difference patterns across the group. The estimated 
electrode locations of an example participant are shown in Figure 4.  
Detection of epileptic events: The proposed research uses recordings in participants with epilepsy, which will 
limit the extent to which results can be generalized to healthy participants. Recent iEEG studies in these 
patients, however, provide evidence that neural activity is largely unaffected in brain regions outside the 
epileptic seizure onset area84–86. We will further use specialized algorithms to detect and exclude periods of 
epileptic activity in all recordings. Inter-epileptic discharges (IEDs) are abnormal electrical distortions related to 
epilepsy that can be observed in iEEG intermittently. IEDs are removed from all iEEG channels before the 
normalization of power and all additional neurophysiological analyses. For IED detection, we will use a 
previously described double thresholding approach in which a data point is identified as an IED when either of 
the following conditions is satisfied: 1) the envelope of the unfiltered signal is 6 standard deviations above the 
baseline, 2) the envelope of the signal band-pass filtered in the 25-80Hz range is 6 standard deviations above 
the baseline. Removed IED samples are replaced using cubic spline interpolation. Using this method, we 
anticipate that between 2–10% of samples will be removed per channel1,2,59.  
 
Figure 3. Mobile deep brain recording and stimulation platform. Left: example 
participant equipped with the VR headset, RNS telemetry wand (secured on the 
head), and custom backpack that carries equipment. Right: example tracings of 
two iEEG channels, heart rate (calculated as a sliding window average of 
pulses), pulse (PPG), and skin conductance.  
Figure 4. Example localizations of distal contacts in the bilateral 
basolateral amygdala. 

v Aim 1: Investigate hippocampal-amygdala iEEG dynamics that underlie the acquisition and 
extinction of contextual fear 
Background: Rodent fear conditioning studies highlight the basolateral amygdala and ventral hippocampus as 
key brain regions in the formation, expression, extinction, and generalization of fear processes34–37. It is 
hypothesized that the amygdala forms an association between stimuli and emotions while the hippocampus 
encodes the broader multisensory context such as visual, spatial, and auditory cues. Thus, the interplay 
between these two structures leads to the formation of contextual fear memories87–89. Rodent 
electrophysiological studies, investigating network oscillations through local field potential (LFP) recordings, 
consistently reveal oscillatory patterns in the amygdala within the theta (3-8 Hz) and gamma (60-120 Hz) 
frequency ranges40. These oscillations are thought to represent the synchronous synaptic activity among large 
neuronal populations90. The hippocampus encodes contextual information such as spatial location independent 
of the emotional valence38,39,91. Lastly, successful contextual fear learning in rodents involves communication 
between the amygdala and hippocampus through mechanisms like theta-gamma phase-amplitude coupling, 
phase coherence, and single-unit synchrony between the two regions43,92. Despite these advancements in 
rodent models of fear, there remains a significant gap in our understanding of these oscillatory dynamics in 
humans during the acquisition, extinction, and renewal of fear responses and whether they covary with 
clinically relevant symptoms observed in psychiatric disorders like GAD or PTSD.  
Experimental Design: Participants will undergo the 2-day Recording Experiment shown in Figure 2A. On day 
1, the task consists of two phases: acquisition and extinction. During the acquisition phase (Figure 5A), the 
participant is instructed to freely navigate a virtual environment (e.g., a library) and informed that the color of 
the room will temporarily change to one of two colors. When this occurs, they are instructed to stop walking 
and remain in place until the room returns to natural lighting. One of the colors (conditioned stimulus, CS+; 
e.g., green lighting) is followed by an aversive, audiovisual jump scare (unconditioned stimulus, US; e.g., giant 
spider). The other color (CS-; e.g., blue lighting) will not lead to the US. The CS+ and CS- are encountered 15 
times each. To assess whether the participant properly learned the CS-US associations, following the 
acquisition phase, they will be asked to rate their level of fear of each light (1-10) and state whether they 
believed each colored light led to an aversive outcome (yes/no) and their confidence in this belief (1-10). 
Afterward, participants rest for 3 minutes before entering a second environment (e.g., a museum) for the 
extinction phase (Figure 5B). During extinction, the participants receive the same instructions as acquisition 
but now neither of the colored lights leads to the jump scare. The CS+ and CS- are encountered 15 times 
each, followed by the same rating task they completed during acquisition. Day 1 of the task will take 
approximately 40 minutes excluding equipment setup. On day 2, participants will undergo another extinction 
phase that occurs in a third environment (e.g., a grocery store) to test for fear renewal, in which re-exposure to 
the CS+ in a new environment leads to renewal of a previously extinguished fear response. Other than this 
environment change, the task will be identical to the extinction phase from day 1. The color of the CS+/CS- 
lights and the order of the three environments will be randomized for each participant.  
Figure 5. VR fear conditioning. A: Acquisition phase in the library environment. The top row shows an example CS+ trial in which a 
US (i.e., a jump-scare of a spider leaping on the headset) occurs 5 seconds after the onset of the green light (CS+). The bottom row 
shows an example CS- trial in which no US follows the onset of the blue light (CS-). B: Extinction phase in the museum environment. 
Neither the green nor the blue light is paired with the US. C: Snapshot of video footage of a participant during the task. 
Analysis and Interpretation: The raw iEEG trace will undergo processing to obtain frequency-specific 
information. To compute the magnitude and instantaneous phase information in the frequency domain, the 

iEEG signals will be convolved with 6th-order complex-valued Morlet wavelets. The result of the convolutions is 
complexed-value signals from which we can extract phase, amplitude, and power to calculate time-frequency 
spectrograms2,21,93. All time-frequency points will be z-score normalized to a baseline period (500-2000ms 
before the onset of the CS). We will calculate trial-averaged normalized power for different trial conditions (e.g., 
CS+ vs CS-) in each experimental session. To assess differences in spectral power between conditions across 
recording sessions, we will use a non-parametric permutation procedure that compares the real difference to 
an empirical distribution created by shuffling the trial labels and generating the shuffled mean difference 2000 
times94. Phase-amplitude coupling (PAC) will be used to quantify the relationship between the phase 
component of a low-frequency (e.g., theta) band, and the amplitude component of a high-frequency (e.g., 
gamma) band, either within a single anatomical region or between two regions (e.g., amygdala-hippocampus). 
To measure the strength of coupling between the theta phase (Φ-) and gamma amplitude (𝐴.), the two signals 
are combined into an analytic complex-valued signal via Euler’s formula, and then the vector mean is 
computed. PAC is quantified as the length of the resultant vector: 𝑃𝐴𝐶= H𝑛(, ∑𝐴.𝑒!#%
*
$
H. To assess whether 
the hippocampus and/or amygdala form distinct neural representations of different environmental contexts 
during fear conditioning, we use a form of representational similarity analysis on the spectral iEEG data23,24. 
Within a given trial, for every 500ms time window spaced every 100ms, we construct a feature vector 
containing oscillatory power information from all frequency bands across all relevant electrodes (e.g., all 
electrodes within the hippocampus). We quantify the neural similarity between two trials by calculating the 
cosine similarity between these feature vectors for all possible pairs of time windows, generating a precise 
temporal map of neural similarity between the two trials. We compute this neural similarity matrix for every pair 
of trials, then compare the mean similarity matrix between trials within the same environmental context (e.g., 
library-library) versus trials with mismatched contexts (e.g., library-museum).  
Preliminary Results: We recorded iEEG activity in six participants with implanted electrodes in the 
hippocampus and amygdala. On average, across all electrodes and participants, we found a reliable increase 
in theta power for CS+ trials compared to CS- trials in the acquisition phase during the onset of both the CS+ 
and US (Figure 6A). We also observed an increase in skin conductance and heart rate during CS+ trials 
compared to CS- trials (Figure 6B, C), consistent with the hypothesis that both the fear-associated stimulus 
(CS+) and the fearful experience itself (US) lead to an increase in amygdala theta power and sympathetic 
nervous system activity. In contrast, trials during the extinction phase (where neither green nor blue light led to 
the jump scare) did not show this difference between CS+ and CS-, consistent with the hypothesis that the CS-
US associations are extinguished (Figure 6D-F).  
We also hypothesize that due to the hippocampus's involvement in encoding context, hippocampal activity 
patterns will be discernible between different virtual environments. Using the representational similarity 
analysis described above, we quantified the neural similarity between every pair of trials in an example 
participant who completed the 2-day task spanning three different environments (library, museum, grocery 
store). In the hippocampus, we observed significantly greater neural similarity between trials in the same 
environment when compared to trials in different environments (Figure 7A and B, left). This difference was 
Figure 6. Mean iEEG and 
physiological activity during the fear 
conditioning task. First row (A-C): 
acquisition phase, second row (D-
F): extinction phase. A: Mean 
difference in the time-frequency 
spectrogram of CS+ and CS- trials, 
pooled across participants (N = 6) 
and electrodes (4 per participant). 
Y-axis shows frequency in the log 
scale. Color represents z-scored 
power. B-C: Mean skin 
conductance response (B) and 
heart rate (C) across all CS+ 
(green) and CS- (blue) trials. 
Asterisks represent points with an 
uncorrected p < 0.05. D-F: 
Analogous time-frequency, skin conductance, and heart rate plots for the extinction phase. For all plots, the x-axis indicates time 
within a trial where vertical dotted lines denote the CS onset (first line; either green or blue light) and US onset (second line; spider). 

not seen in the amygdala (Figure 7B, right), consistent with the idea that the amygdala forms associations 
between conditioned stimuli and fear while the hippocampus encodes the broader multisensory context.  
Potential Challenges and Limitations: We anticipate challenges involving the optimization of the VR fear 
conditioning task. We have found that, out of sixteen total participants who completed the task (7 RNS, 9 non-
RNS), only eleven (3 RNS, 8 non-RNS) reliably learned the CS-US associations as measured by the rating 
task at the end of the acquisition phase. Since individuals with RNS implants are on average older with more 
psychiatric and neurological co-morbidities, they likely had more difficulty with learning the associations 
compared to the non-RNS participants consisting of college psychology majors. In consultation with my co-
mentorship team, we are currently conducting additional pilot experiments to enhance the salience of both the 
CS and the US by introducing multimodal sensory experiences such as different tones associated with the CS 
light colors and vibratory cues paired with the US. Although traditional fear conditioning studies have utilized 
painful tactile or auditory stimuli, we hope to demonstrate that context-appropriate stimuli in virtual reality can 
reliably induce fearful responses. Developing a nuanced understanding of the strengths and limitations of VR 
technology in neuroscience research is aligned with the training goals of the proposal.  
v Aim 2: Test the effects of amygdala stimulation on fear extinction. 
Background: Intracranial electrical stimulation has emerged as a potent tool to causally probe neural circuits. In 
humans, amygdala stimulation has been safely and effectively used to treat focal epilepsy for many years95–97. 
Several lines of evidence converge to suggest that amygdala stimulation will enhance fear extinction. In animal 
studies, perturbation of amygdala activity and its connectivity to the hippocampus through optogenetic 
inhibition98 or electrical stimulation99 leads to a reduction in anxiety and enhancement in fear extinction. In 
humans, amygdala stimulation appears to have two main effects: 1) elicits autonomic activity consistent with a 
response to a threat (increased skin conductance, heart rate deceleration)30 and 2) enhances declarative 
memory formation independent of its emotional content31,100. Taken together, we hypothesize that amygdala 
stimulation will enhance fear extinction similar to how prolonged exposure therapy is used to treat PTSD. 
During prolonged exposure, individuals deliberately confront fear-inducing stimuli in a controlled environment, 
allowing them to gradually learn that once-feared stimuli no longer pose a significant threat. Thus, the 
mechanism behind fear extinction is analogous to the development of a separate competing memory, with the 
new association being strengthened by repeated exposures. Importantly, this re-learning process is more 
effective when patients experience the physiological arousal associated with the traumatic memory101. 
Therefore, targeted stimulation of the amygdala during the presentation of fear-conditioned stimuli (CS+) 
during extinction will 1) amplify the physiological arousal to threat, and 2) enhance re-learning that the CS+ is 
no longer associated with the US. Encouragingly, our group has recently shown that stimulating the amygdala 
both continuously and in response to increased theta activity leads to PTSD symptom reductions2,102. This 
promising evidence underscores the potential therapeutic value of amygdala stimulation in modulating 
emotional responses and promoting recovery from treatment-resistant anxiety disorders. 
Experimental Design: Participants will undergo a 2-day Stimulation Experiment (Figure 2B), which has a 
similar structure to the Recording Experiment with the addition of an extra conditioned stimulus (CS++). 
Therefore, participants are informed that the color of the room will temporarily change to one of three colors. 
Figure 7. Neural similarity 
between trials of the same 
(e.g., library-library) versus 
different (e.g., library-museum) 
environment in an example 
participant. A: Mean neural 
similarity matrix across all 
pairwise trials with the same 
(left) versus different (right) 
environment, using electrodes 
in the hippocampus (N = 3 
electrodes). The Y and X axes 
represent time within the two 
trials being compared. Color 
represents the mean cosine similarity of neural feature vectors between pairs of time points from the two trials. B: Mean neural 
similarity within the 0-8s time window from the neural similarity matrix. The left plot shows data from the hippocampus (i.e., taking the 
average of the 0-8s windows of matrices in plot A), and the right plot shows data from the amygdala (N = 1 electrode). The asterisk 
indicates p < 0.05 using an independent samples t-test.  

Two of the colors (CS+ & CS++; e.g., green and yellow lighting) are followed by the US (e.g., giant spider) 
while the other color (CS-; e.g., blue lighting) is not. The CS+, CS++, and CS- are encountered 10 times each. 
Participants complete the ratings and rest for 3 minutes before entering the extinction phase. During extinction, 
none of the three colored lights will lead to the US. However, during the presentation of CS++, stimulation will 
be delivered to the right amygdala. Analogous to the Recording Experiment, an extinction phase will be 
completed for Day 2 in a third environment to test the effect of stimulation on fear renewal.  
The primary site for stimulation will be the right basolateral amygdala, given previous studies in humans that 
suggest the right amygdala is preferentially active during negative emotions103, states of high arousal104, and 
fear105. Further evidence comes from case reports where a lesion to the right amygdala led to reduced fear-
potentiated startle response106 and a reduction of PTSD symptoms107. If a participant only has left amygdala 
contacts, we will stimulate this site and take this into account in our analysis. Stimulation parameters will be 
derived from previous studies completed by our group using bipolar stimulation that is current-regulated, 
charge-balanced, with biphasic rectangular pulses set below the after-discharge threshold2,30,31. The absence 
of an after-discharge at a particular site will be carefully established before each session. We will use 
(putatively inhibitory) gamma frequency (130 Hz) stimulation with a 90-μsec pulse length, following previous 
studies and our protocol for deep brain stimulation (DBS) in PTSD2,4,30,31. For each pulse, total stimulation will 
range between 2.5-10.1 μC/cm2 per phase, well below the safe maximum used for chronic (30 μC/cm2 per 
phase) and acute (57 μC/cm2 per phase) stimulation.  
Preliminary Results: We hypothesize that amygdala stimulation during the CS++ will 
facilitate fear extinction as measured by reduced fear-related physiological 
responses (increase in heart rate and skin conductance) when compared to a 
separate CS+ (see Figure 2B). Individuals from our team have published several 
studies using medial temporal stimulation including the amygdala 
specifically2,30,31,102. Figure 8 shows an example raw iEEG trace from a medial 
temporal lobe electrode adjacent to one that delivered a high-frequency burst of 
stimulation repeated at a lower frequency for several seconds. We have recently 
published the preliminary results from our study utilizing electrical stimulation of the 
amygdala where two combat veterans with treatment-refractory PTSD experienced 
a significant decrease in symptoms, including one participant who has achieved and 
maintained complete remission from the disorder2.  
Potential Challenges and Limitations: We foresee potential challenges in quantifying extinction learning during 
the Stimulation Experiment. Since iEEG recording cannot co-occur with stimulation, we will rely on 
physiological measurements to measure the acquisition and extinction of fear responses. Upon completion of 
the Recording Experiment, if the skin conductance and heart rate measures appear to have inadequate 
resolution to distinguish between responses to the CS+ and CS++, we may introduce additional measures 
such as pupil dilation and startle eye blinks, both of which have been previously implemented in the lab. 
Although we will initially use stimulation parameters consistent with previously published research, we 
anticipate the parameters will require gradual titration to maximize its effect without inducing a subjective 
emotional experience30. The RNS system can deliver stimulation with configurable amplitude (0-12 mA, 0.1 mA 
steps), pulse width (40-1000μs, 40μs steps), frequency (1-333 Hz), and burst duration (10-5000 ms). In line 
with the training goals of gaining expertise in intracranial stimulation, I will work closely with our neurosurgeon 
collaborator Dr. Langevin throughout this process.  
v Aim 3: Characterize the physiological activity and hippocampal-amygdala iEEG dynamics 
associated with anxiety. 
Background: Classification of psychiatric illness is moving away from a categorical approach and embracing a 
more transdiagnostic, dimensional perspective. This involves considering diseases along a continuum of 
biological, behavioral, and cognitive factors rather than relying on a concrete list of symptoms. For instance, 
although GAD and PTSD are listed under separate diagnostic categories in the DSM-5108, we understand them 
as occupying a similar dimensional space characterized by symptoms such as excessive fear, avoidance, 
hypervigilance, heightened physiological arousal, and sleep disturbances. Consistent with this, fear 
conditioning has served as an effective model for both disorders. Given the U.S. veteran population comprises 
a wide range of comorbid anxiety and PTSD symptoms, we have a unique opportunity to investigate how iEEG 
activity from the fear circuitry relates to anxiety symptoms across a wide spectrum of illness severity.  
Figure 8. Raw iEEG trace 
during a 100 Hz intracranial 
pulse (asterisks) to an 
adjacent electrode contact.  

Given the role of the hippocampal-amygdala circuit in fear learning, there has been a concerted effort to 
investigate how the structural and functional characteristics of this circuit relate to an individual’s baseline (trait) 
anxiety. Imaging studies have shown that trait anxiety is associated with the amygdala’s surface 
morphology109, structural connectivity to higher-order brain areas (e.g., dorsal anterior cingulate cortex)110,111, 
and resting state functional connectivity to other brain regions112. FMRI studies have demonstrated that 
individual differences in trait anxiety predict activity in the basolateral amygdala in response to fearful 
stimuli113,114. Similar associations are found between hippocampal activity115 and functional connectivity116 with 
trait anxiety. We will build upon these findings by investigating whether fear-related iEEG oscillatory activity 
and connectivity measures in this circuit exhibit variations among individuals with different levels of anxiety. 
This effort ultimately aims to identify potential biomarkers associated with anxiety disorders.  
Analysis and Interpretation: All participants enrolled in the 
study will complete clinical assessments including the 
Beck Anxiety Inventory, State-Trait Anxiety Inventory, 
Intolerance of Uncertainty Scale, Fear Survey Schedule, 
Anxiety Sensitivity Index, Patient Health Questionnaire 
(PHQ-9), and the WHO Disability Assessment Schedule. 
Participants enrolled in the PTSD clinical trial will also 
complete the Clinician-Administered PTSD Scale (CAPS). 
Across participants, the composite score of each clinical 
questionnaire will be used to predict the degree of change 
in a physiological or electrophysiological variable of 
interest using a multiple linear regression model. Of note, 
we expect the total scores of many of the questionnaires 
to be correlated, leading to a multicollinearity issue. This 
will be addressed by either converting highly correlated 
metrics into a composite score or using statistical 
regularization techniques such as ridge or lasso 
regression. The choice of the time window to average data 
will be determined a priori using the same time window 
where increased activity is observed across all participants 
(e.g., 3-9 seconds after CS presentation for skin 
conductance activity seen in Figure 6).  
Preliminary Results: We analyzed data from RNS epilepsy 
participants (N = 7) and pilot participants without RNS (N = 
3). Consistent with our hypothesis, we see trends toward a 
positive association (p > 0.05 across all regression 
models) between skin conductance and theta power and 
various anxiety metrics (Figure 9, first and second rows). Interestingly, we see an opposite pattern with heart 
rate, whereby a decrease in heart rate is associated with anxiety (Figure 9, third row). This is consistent with 
the hypothesis that animals experience an initial deceleration in heart rate when faced with threatening stimuli 
to transiently enhance perceptual processing30,117. Therefore, in combination with our preliminary finding that 
heart rate is overall higher during CS+ compared to CS- trials (Figure 6C), our data suggest that participants 
engage in coactivation of both sympathetic and parasympathetic responses to VR-based threat and that these 
responses are correlated with the individual’s baseline level of anxiety across multiple symptom dimensions.  
Conclusions and Implications: Currently, a substantial gap exists between rodent fear conditioning studies 
and human laboratory-based studies of fear and anxiety. Our experimental platform bridges this gap by 
allowing for direct intracranial recording and stimulation of the hippocampus and amygdala – brain regions 
heavily implicated in contextual fear learning and anxiety disorders – while participants undergo naturalistic 
behavior using VR and wearable technologies. Moreover, the inclusion of military veterans, who exhibit higher 
rates of comorbidity with various anxiety-related disorders, enhances the translational relevance of our 
research. Taken together, our proposed project aims to elucidate the basic neural mechanisms underlying 
human fear processing, pave the way for the development of innovative therapeutic interventions for treatment-
resistant anxiety disorders, and discover biomarkers across various anxiety- and fear-related traits, thereby 
contributing to the ongoing mission to adopt a dimensional approach to psychiatric illness.  
 
Figure 9. Scatterplots showing the relationship between a 
measured variable (skin conductance, iEEG theta power, 
heart rate) and clinical assessment scores. Red lines 
indicate lines of best fit and each point represents a 
participant. The y-axis is the mean difference between all 
CS+ and CS- trials for a given variable, averaged between 
3-9s relative to CS onset. The x-axis is the composite 
score for a given clinical questionnaire.  BAI = Beck 
Anxiety Inventory, FSS = Fear Survey Schedule, ASI = 
Anxiety Sensitivity Index.  

TRAINING IN THE RESPONSIBLE CONDUCT OF RESEARCH 
UCLA offers opportunities each semester for thorough training of students, postdocs, and faculty in the 
responsible conduct of research (RCR). This includes formal courses in RCR that fulfill all requirements and 
address all components as specified by the NIH. The UCLA David Geffen School of Medicine offers two face-
to-face courses on RCR annually: “Responsible Conduct of Research Involving Humans”, a ten-week course in 
the Fall semester (2 hours of lectures and 2 hours of discussion per week for a total of 40 hours) that combines 
lectures and scenario-based interactive discussions; and “Ethics and Accountability in Biomedical Research”, a 
ten-week course in the Spring semester (2-hour discussions per week for a total of 20 hours) based on case-
study discussions. I will take one of the above courses during my first year during the K08 award period (the 
academic year 2024-2025), then again during my 5th year to fulfill the NIH requirements. Both courses cover a 
broad array of topics including mentoring responsibilities, safe laboratory practices, data ethics, intellectual 
property, conflicts of interest, misconduct, authorship, collaborative research, responsible publication, peer 
review, human/animal subjects, Institutional Review Board (IRB), and broad ethical issues. Rotating clinical 
and research faculty also participate in weekly discussion sessions in these courses.  
During my first weeks as a resident physician at UCLA (June 2021), I completed an online training program 
through the Collaborative Institutional Training Initiative (CITI) offered by UCLA’s Office of the Human 
Research Protection Program, including courses and tests on Good Clinical Practice, History and Ethics of 
Human Subjects Research, Conflicts of Interest in Human Subjects Research, IRB Regulations, Clinical Trials, 
HIPAA, and other topics. I have also completed analogous courses on the responsible conduct of research 
(RCR) through the VA system (Talent Management System VA Online University). These courses are required 
to be renewed annually to maintain my status as a resident physician in the UCLA and VA systems.  
Lastly, my primary mentor Dr. Nanthia Suthana often circulates articles to facilitate discussion of research 
ethics during lab meetings, one-on-one meetings, and while training me in collecting data from human 
participants. Dr. Suthana and my co-mentors (Dr. Craske and Dr. Fanselow) emphasize promoting the highest 
level of ethical research conduct, especially in the context of working with patient populations. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

DESCRIPTION OF INSTITUTIONAL ENVIRONMENT 
The University of California, Los Angeles (UCLA) ranks among the top research universities in the United 
States and has an established record of excellence in health science research, graduate education, and 
patient care. The university offers unique facilities that collectively create a robust network of research, 
educational, and collaborative opportunities. This environment is conducive to both my career development 
and the successful execution of the proposed research plan. At the core of the proposed research plan are 
electrophysiological recordings from patients with epilepsy who have been surgically implanted with responsive 
neurostimulation (RNS) devices. UCLA stands as a global leader in conducting clinical procedures and 
research focused on these patient groups. Multiple UCLA neurosurgeons carry out this invasive surgery on 
numerous epilepsy patients monthly. My proposed research will be conducted in direct partnership with the 
UCLA Department of Neurosurgery, with Dr. Jean-Philippe Langevin (collaborator) playing a pivotal role in the 
recruitment and retention of study participants from both UCLA and the VA systems. 
The Suthana lab at UCLA, led by my primary mentor Dr. Nanthia Suthana, has an excellent track record in 
utilizing both RNS and virtual reality technologies to study the human brain. The Suthana lab has both the 
expertise and the technical equipment (as outlined in the Facilities and Equipment sections) for this line of 
research and maintains a large database of more than 250 RNS participants who have expressed their interest 
in participating in the lab’s research studies.  Additional support for task design and data analysis regarding 
fear conditioning will come from my co-mentors Dr. Craske and Dr. Fanselow, both of whom hold the title of 
Distinguished Professor in the Department of Psychology for their contributions to fear conditioning research in 
humans and rodents, respectively. The Suthana lab and I have been successfully working on several research 
projects with all these collaborators and institutes over the past 2.5 years, which indicates that this will continue 
to be a fruitful collaboration with minimal unexpected administrative hurdles for the proposed experiments.  
UCLA also has several institutes to facilitate the career development and research success of early-stage 
investigators: The Clinical and Translational Science Institute (CTSI) supports and supervises human studies 
and clinical trials in all therapeutic areas and offers a large variety of training opportunities such as consultation 
services and formal courses on human subjects protection, IRB-related topics, the administration and 
coordination of clinical trials, study management, data management, as well as manuscript and grant 
preparation. The Institute for Digital Research and Education (IDRE) at UCLA offers courses, resources, and 
support to UCLA researchers in all areas of computational science, data science, and information science. This 
includes free-of-charge support and consulting services from the IDRE Statistical Consulting Group which 
assists in applied statistics and data analysis related to grants and publications. Several UCLA-based entities, 
such as the Brain Research Institute (BRI), the Integrative Center for Learning and Memory (ICLM), and the 
Training in Neurotechnology Translation (TNT) Program host neuroscience journal clubs and research 
seminars each week. These events often cover topics that are highly relevant to the proposed research and 
allow students and postdocs to practice formal presentations and receive feedback from the local neuroscience 
community. Moreover, the BRI hosts weekly ‘UCLA Joint Seminars in Neuroscience’ which invites world-
renowned neuroscientists and provides networking opportunities with the speakers. 
In summary, I am confident that UCLA's extensive network of resources and opportunities will create an 
excellent and collaborative environment for accomplishing the aims of my research plan and for my training to 
become a successful independent investigator. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

DATA MANAGEMENT AND SHARING PLAN 
If any of the proposed research in the application involves the generation of scientific data, this application is subject to the NIH Policy for Data 
Management and Sharing and requires submission of a Data Management and Sharing Plan.  If the proposed research in the application will generate 
large-scale genomic data, the Genomic Data Sharing Policy also applies and should be addressed in this Plan.  Refer to the detailed instructions in the 
application guide for developing this plan as well as to additional guidance on sharing.nih.gov.  The Plan is recommended not to exceed two pages.  
Text in italics should be deleted. There is no “form page” for the Data Management and Sharing Plan. The DMS Plan may be provided in the format 
shown below.  
Public reporting burden for this collection of information is estimated to average 2 hours per response, including the time for reviewing instructions, 
searching existing data sources, gathering, and maintaining the data needed, and completing and reviewing the collection of information. An agency 
may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB control 
number. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this 
burden, to: NIH, Project Clearance Branch, 6705 Rockledge Drive, MSC 7974, Bethesda, MD 20892-7974, ATTN: PRA (0925-0001 and 0925-0002). Do 
not return the completed form to this address. 
 
Element 1: Data Type 
A. Types and amount of scientific data expected to be generated in the project:  
Summarize the types and estimated amount of scientific data expected to be generated in the project,  
 
Demographic, neuropsychological, behavioral, neuroimaging (iEEG, MRI), and physiological data (heart rate, 
skin conductance) will be collected from a total of 70 participants with RNS electrodes during the 5-year award 
period. All data will be de-identified before receipt by the repository, but the information needed to generate a 
global unique identifier for the NIMH Data Archive (NDA) will be collected for each subject.   
 
B. Scientific data that will be preserved and shared, and the rationale for doing so: 
Describe which scientific data from the project will be preserved and shared and provide the rationale 
for this decision.   
 
Sufficient data from this project will be preserved to enable sharing via NDA data of sufficient quality to validate 
and replicate research findings described in the Aims.  
 
C. Metadata, other relevant data, and associated documentation:  
Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols 
and data collection instruments) that will be made accessible to facilitate interpretation of the scientific 
data. 
 
Study protocols including participant instructions for the virtual reality paradigm and setup instructions for 
physiological data collection will be made accessible to facilitate replication and extension of our study from 
other groups. 
 
Element 2: Related Tools, Software and/or Code: 
State whether specialized tools, software, and/or code are needed to access or manipulate shared 
scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they 
can be accessed. 
 
No specialized tools or software are needed to access or manipulate the shared scientific data. While we use 
custom code written in MATLAB to analyze our data, the data itself is organized into number matrices that can 
be accessed by any other analysis software. Most universities have site licenses available to MATLAB, and it 
is also possible to use an open-source alternative to MATLAB such as Octave. The code used for analysis will 
be made available to the public via GitHub and can be located by searching for “labname”.  
 
Element 3: Standards: 
State what common data standards will be applied to the scientific data and associated metadata to 
enable interoperability of datasets and resources, and provide the name(s) of the data standards that 
will be applied and describe how these data standards will be applied to the scientific data generated by 
the research proposed in this project.  If applicable, indicate that no consensus standards exist. 
 
No consensus standards exist for our demographic, behavioral, and neuroimaging data. However, within the 
Suthana laboratory group, it is strongly encouraged to keep digitized data sources in formats that facilitate 

consistent collection and interoperability across different systems, sources, and users. The clinical 
assessments we plan to collect for this study include the Beck Anxiety Inventory (BAI), State-Trait Anxiety 
Inventory (STAI), Intolerance of Uncertainty Scale (IUS), Fear Survey Schedule (FSS), Anxiety Sensitivity 
Index (ASI), Patient Health Questionnaire (PHQ-9), WHO Disability Assessment Schedule (WHODAS), and 
the Clinician-Administered PTSD Scale (CAPS).  
 
Element 4: Data Preservation, Access, and Associated Timelines 
A. Repository where scientific data and metadata will be archived:  
Provide the name of the repository(ies) where scientific data and metadata arising from the project will 
be archived; see Selecting a Data Repository). 
 
We will provide open access to all tools developed and anonymized data using the NIMH Data Archive (NDA) 
and will also consider data-sharing through DABI (Data Archive BRAIN Initiative), Blackfynn, and Neurodata 
Without Borders (NWB). Any hardware or software developed for the platform will be shared via publications 
and GitHub repositories. 
 
B. How scientific data will be findable and identifiable:  
Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or 
other standard indexing tools. 
 
Data will be findable for the research community through the NDA Collection that will be established when this 
application is funded. For all publications, an NDA study will be created. Each of those studies is assigned a 
digital object identifier (DOI). This data DOI will be referenced in the publication to allow the research 
community easy access to the exact data used in the publication. 
 
C. When and how long the scientific data will be made available:  
Describe when the scientific data will be made available to other users (i.e., no later than time of an 
associated publication or end of the performance period, whichever comes first) and for how long data 
will be available.  
 
The research community will have access to data when the award ends. As required by NDA, studies will also 
be created that contain the data used for every publication. Those studies will be shared when the pre-print is 
available. NDA studies have digital object identifiers (DOI) to aid in findability. We will include that DOI in 
relevant publications. NDA will make decisions about how long to preserve the data, but that data archive has 
not deleted any deposited data up to now.  
 
Element 5: Access, Distribution, or Reuse Considerations 
A. Factors affecting subsequent access, distribution, or reuse of scientific data: 
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. 
Describe and justify any applicable factors or data use limitations affecting subsequent access, 
distribution, or reuse of scientific data related to informed consent, privacy and confidentiality 
protections, and any other considerations that may limit the extent of data sharing. See Frequently 
Asked Questions for examples of justifiable reasons for limiting sharing of data. 
 
Any data shared with the public will be completely de-identified with only basic demographic information 
included such as age, sex/gender, and race/ethnicity. Therefore, we do not anticipate any significant limitations 
affecting the access, distribution, or reuse of our scientific data. All research participants will be consented for 
broad data sharing. 
B. Whether access to scientific data will be controlled: 
State whether access to the scientific data will be controlled (i.e., made available by a data repository 
only after approval).)  
To request access to the data, researchers will use the standard processes at NDA, and the NDA Data Access 
Committee will decide which requests to grant. The standard NDA data access process allows access for one 
year and is renewable.  

C. Protections for privacy, rights, and confidentiality of human research participants:  
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of 
human research participants will be protected (e.g., through de-identification, Certificates of 
Confidentiality, and other protective measures).   
 
Participant contact and personal information will not be shared with researchers or any collaborators; each 
participant will be coded and only Dr. Jang, Dr. Suthana, and the Staff Research Associate (Sonja Hiller) will 
have access to the code. Before sharing data amongst researchers and the larger scientific community, Dr. 
Jang will ensure that data is de-identified in compliance with HIPAA; some information may be recoded or 
removed to ensure confidentiality as necessary. No private records or identifier information will be made 
available or transferred. Participant identities are never disclosed by publication or any other means. Informed 
consent forms are kept in locked files for at least 7 years beyond subject participation as legally required. 
Information in the computerized database is protected by a firewall and special username/password accounts 
are given only to authorized personnel. Data will be shared between lab members using a secured server with 
encryption and performed by authorized users using password-protected accounts.  
 
Element 6: Oversight of Data Management and Sharing: 
Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by 
whom at your institution (e.g., titles, roles). 
 
Monitoring and compliance with this Data Management and Sharing Plan will be the responsibility of the 
project’s Principal Investigator. The plan will be implemented and managed by professional staff working under 
the direction of the PI. The final project report will summarize adherence to this data management and sharing 
plan. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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