Understanding the Effects of Non-invasive Transauricular Vagus Nerve Stimulation (taVNS) on Neural Networks and Autonomic Nervous System: a Randomized Double-blind Sham-control Mechanistic Trial in Healthy Participants
Phase: NA
Conditions: Healthy Volunteers
Sponsor: Spaulding Rehabilitation Hospital

 
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Institutional Review Board 
Intervention/Interaction Detailed Protocol 
 
 
Principal Investigator: 
Felipe Fregni 
 
Project Title: 
Understanding the effects of non-invasive transauricular vagus nerve 
stimulation (taVNS) on neural networks and autonomic nervous system: a randomized double-blind 
sham-control mechanistic trial in healthy participants 
 
Version Date: 
08/01/2023 
 
 
Version Name/Number: 
2022P0023200 
 
 
 
1. 
 Background and Significance 
 
Transauricular vagus nerve stimulation (taVNS) is a newer delivery system, using a non-invasive 
stimulation device placed at the concha or tragus of the ear, which does not require surgery; therefore 
it is more accessible and naturally less risky to patients(1). The taVNS field is growing exponentially in 
the last few years, and has been predominantly focused on clinical trials showing potential therapeutic 
benefits for various pathologic conditions, such as epilepsy, schizophrenia, migraine, Parkinson’s 
disease, tinnitus, impaired glucose tolerance, and atrial fibrillation(2). 
There is much to discuss about taVNS and its effects on biological processes in the central and 
peripheral systems. To study how taVNS impact physiological activity, ideally, a biological marker could 
provide information that the auricular nerve was truly stimulated, causing an effect on intracranial 
structures. However, without a reliable biomarker, we may not thoroughly learn from the taVNS results 
and may not have the best interpretation of its effects. 
Electroencephalography (EEG) has proven to be a useful tool in understanding the mechanisms 
behind non-invasive brain stimulation and its effect on brain connectivity. EEG measurements are based 
on electrical potential differences between electrodes on the scalp. A potential difference is caused by 
the propagation of the current flow induced by synchronized postsynaptic potentials in pyramidal 
neuron cell membranes. These measurements allow for the evaluation of effective connectivity 
between different cortical and subcortical regions and provide high temporal and spatial resolution for 
the analysis of brain stimulation effects, such as those of Transcranial Magnetic Stimulation (TMS) and 
transcranial direct current stimulation (tDCS)(3, 4). 
Based on that, EEG is seen as a promising imaging tool to provide biomarkers for taVNS. It is a 
reliable, non-invasive, and inexpensive method to measure and quantify cortical activity.  Following 
through this thought process, our team of researchers has performed a systematic review, 
demonstrating preliminary information that taVNS could influence cortical activity, mainly increasing 
EEG power spectrum activity in lower frequencies (delta and theta). However, divergent results in higher 
frequencies (alpha), and in changes on early ERP components related to inhibitory tasks were also 
detected. A high heterogeneity between the studies was found; therefore future more homogeneous, 

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bigger, and well-designed studies are needed to make stronger conclusions about the effects of taVNS 
in brain activity measured by EEG(5). 
Alpha asymmetry, which assesses the relative alpha band activity between the brain hemispheres, 
particularly at frontal electrodes, is a frequently researched EEG biomarker. Previous literature has used 
this biomarker to analyze the approach-withdraw hypothesis(6, 7), which holds that the right frontal 
side of the brain is associated with withdrawal behaviors while the left frontal side is associated with 
approach behaviors. Since alpha is associated with low brain activity, an increase in alpha on the left 
side of the brain suggests lower activity and may therefore suggest a lack of approach behavior. This 
concept helps to explain some results in the alpha band at the left side hemisphere in depressed 
patients(8). 
Additionally, EEG electrodes record the activity of neuronal populations(9). Using this data, it is 
possible to examine the relationships between several brain regions and the brain's network structure 
and activity. Functional Connectivity (FC) is a general term used to describe connections between brain 
regions. It can be assessed in a variety of methods, such as utilizing coherence to denote synchronized 
activity between brain regions(10). Studies have shown that changes in the normality of large-scale 
brain networks, such as the default mode network (DMN) (11, 12) and affective network (AN)(13), or 
the dysconnectivity of some brain regions, such as corticolimbic pathways(14), are related with the 
psychiatric conditions, for example depression. So, FC has proven to be effective to investigate network 
dysfunction (15). Based on that, quantitative electroencephalography can be used to assess the effects 
of taVNS on brain activity; however, more studies are needed to systematically establish the specific 
effects and metrics that would reflect the non-invasive stimulation through the auricular branch of the 
vagus nerve.  
Peripherally, the vagus nerve and sympathetic nervous system mediate the heart’s contractile 
and electrical function(16). This regulation promotes the heart’s pacemaker ability and controls it 
through physiological manifestations of the body, known as sinus depolarizations. Heart rate variability 
(HRV) records the changes per beat of sinus depolarization, thus, non-invasively describing vagal 
influences on the sinus node(17). Given this function, HRV has been seen and studied as a prominent 
biomarker for neurocardiac function, being associated with an individual’s well-being and the likelihood 
of morbidity, mortality, and stress(18, 19). 
           In the context of taVNS, HRV has been recorded in many trials, and stimulation has been thought 
to modulate HRV(16, 20, 21). Considering that a decreased HRV has been related to morbidity and 
mortality of different diseases through mechanisms such as over-activity of the sympathetic nervous 
system, inflammatory response, and oxidative stress, the vagal nerve modulation of taVNS is thought 
to directly impact HRV and its sinus regulation(22, 23). In fact, some trials have already conveyed that 
taVNS can increase HRV in healthy subjects, thus sustaining this hypothesis(20). However, there is still 
a lack of understanding on whether different taVNS parameters can affect HRV differently. 
According to some studies(24, 25), taVNS may also influence nociception and pain perception, and that 
can lead to potential applications to a variety of painful illnesses, including headache, trigeminal 
allodynia, chronic pelvic pain, and fibromyalgia(26). The overlapping anatomical pathways between the 
nociceptive system and the central projections of the vagal afferents may be the cause of the potential 
mechanisms by which VNS modifies pain perception(27). 
 
Regarding the vagal projections, some studies have demonstrated the vagal role in modulating 
pain pathways(25, 28-36), the inflammatory system and cortisol levels (37-40), and the gut microbiota 
(41-43). Several markers such as quantitative sensory testing (QST) (44-46), salivary cortisol (37, 47, 48), 
and salivary microbiota (49) have been used to measure pain and inflammatory systems, and the gut 
microbiome respectively. Although, there is still a need for more data to understand the mechanisms 
of taVNS on these systems. 

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Indeed, taVNS have been shown to be a safe, portable, and feasible tool (50, 51). Our group has 
demonstrated its safety through a systematic review and meta-analysis on the topic (Safety of 
transcutaneous auricular vagus nerve stimulation(taVNS): A systematic review and meta-analysis – peer 
review). Moreover, several studies have shown promising results of taVNS to treat various disorders 
such as depression, anxiety, Alzheimer’s disease, headache, obesity, and diabetes(2, 52-55). However, 
no mechanistic studies have investigated the taVNS neural network and autonomic nervous system's 
effects of this technique. Therefore, we aim to assess how taVNS can affect EEG metrics and HRV and 
assess its safety. Also, we aim to evaluate predictors that can influence the response to taVNS, so 
understanding the variables associated with response to taVNS can help the design of future clinical 
trials to maximize the effects of this intervention. 
 
 
2. 
Specific Aims and Objectives  
 
Our goal is to perform an exploratory, mechanistic randomized double-blind sham-control trial in 
healthy participants, to assess the physiologic effects of a single session of bilateral taVNS, on neural 
networks and autonomic function.  
 
The specific aims of this experiment are as follows: 
 
Aim 1:  We aim to compare the neurophysiologic effects of a single session of active taVNS versus sham 
taVNS in Frontal Alpha Asymmetry, Functional Connectivity and Phase Synchrony of DMN using EEG on a 
processing emotional facial expressions and a Go/NoGo task. We expect to find differences in face-related 
frontal alpha asymmetry between active taVNS versus sham taVNS in healthy controls. Also, regarding the 
DMN, we expect that taVNS decreases FC between DMN and other areas. 
 
Aim 2: As a second aim, we will measure the effects of one active taVNS session versus sham in heart rate 
variability total power, very low frequencies (VLF), low frequencies (LF), and high frequencies (HF), and 
LF/HF ratio. We expect the taVNS to increase HF and decrease LF/HF ratio due to parasympathetic 
activation. Furthermore, the standard deviation of the R-R intervals (SDRR), the count of R-R intervals that 
differed more than 50 ms (NN50), the percentage of NN50 (pNN50), and the root mean square of the 
difference between successive R-R intervals (RMSSD) will be measured and we expect an increase on 
those metrics as well. We will also explore a non-linear method to calculate the short-term detrended 
fluctuation exponent (DFA-alpha1). 
 
Additionally, we aim to assess the effects of taVNS in healthy subjects after one single session in some 
exploratory related outcomes. 
 
 
3. 
General Description of Study Design 
 
We will perform a randomized double-blind sham-control trial. We will randomize 44 healthy 
subjects, who will receive one single session of active taVNS or sham taVNS at the Neuromodulation 
Center/ Cambridge Spaulding Hospital. 
 
 
 

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4. 
Subject Selection 
 
In this study, we will randomize 44 healthy subjects, and they will need to meet the following 
inclusion criteria and none of the following exclusion criteria: 
 
Inclusion Criteria: 
1. Able to provide informed consent to participate in the study. 
2. Subject is older than 18 years. 
3. Subjects should be naive to the stimulation (taVNS) 
 
Exclusion Criteria: 
1. Pregnancy. 
2. Subjects who have had a neuropsychiatric or a cardiac disorder diagnosis and have received treatment 
and chronic medication in the past six months, or who have functional deficits as a result. 
3. History of alcohol or drug abuse within the past 6 months as self-reported. 
4. Presence of the following contraindication to transauricular vagus nerve stimulation 
a. Ferromagnetic metal in the head and in the cranium (e.g., plates or pins, bullets, shrapnel) 
b. Implanted cranial electronic medical devices (e.g., cochlear implants)  
c. Implanted cardiac devices (e.g., pacemaker)  
5. Unstable medical conditions (e.g. uncontrolled diabetes, uncompensated cardiac issues, heart failure 
or chronic obstructive pulmonary disease). 
6. Uncontrolled epilepsy, as defined by previous clinical seizure in the past 3 months in patients with 
treatment for epilepsy. 
7. Suffering from severe depression (as defined by a score of >30 in the Beck Depression Inventory).* 
 
*If a subject screens out due to severe depression they will be provided with a local resource list (as 
recommended by Cheatle, 2014) (56). If the subject is presenting with suicidal ideation, the medical 
monitor will be contacted to provide further evaluation and instruction. Study participant will be escorted 
to the emergency room for assessment and triage if: spontaneous expression of suicidal ideation and/or 
BDI question 9 answers of 2 or 3. 
 
The safety of taVNS in the pregnant population (and children) has not been assessed and therefore 
pregnant women (and children) will be excluded. Women of child-bearing potential will be required to 
take a urine pregnancy test during the screening process. 
 
Potential subjects will be identified by the following sources: 
1. Flyers posted in public areas across the Boston-land region. 
2. Internet and newspaper advertisements. 
3. Advertisements posted in public transportation (The T) 
4. Via the Rally platform by Mass General Brigham Research. 
5. Potential subjects might also be identified though their medical records (epic LMR, etc.) 
6. Via the Partners Healthcare Research Patient Data Registry (RPDR) and Patient Gateway (Research 
Invitations allow for direct communication with any eligible subjects who have not opted out of 
receiving Research Invitations.) 
 
Eligible subjects will contact, or give permission to be contacted, by a co-investigator to obtain more 
information about the study. At the first point of contact (usually a phone call or Zoom Enterprise call), a 

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study co-investigator will administer an online-prescreening questionnaire. Once the online pre-screening 
process is complete, the information gathered by the co-investigator will be taken to the PI of the study 
for further review to confirm eligibility. Data obtained from the pre-screening will be stored in an 
encrypted web-based platform (REDCap).  
 
When contacting subjects by email, we will communicate through the Massachusetts General 
Brigham network as per the institutional policy regarding secure email communication using encryption 
by Mass General Brigham / Partners Healthcare “Send Secure” function.  If the first method of contact 
with the subject is through email, we will explain that they will receive encrypted emails going forward. 
This initial unencrypted email will have instructions on how to open encrypted emails. We will also explain 
that they can opt out of secure emails after informing them of the possible security risks. If they choose 
this option, this preference will be noted in our contact log. 
 
The online informed consent will be obtained by the study PI and/or a co-investigator using the 
REDCap platform approved by Massachusetts General Brigham network (MGB REDCap eConsent). The PI 
will be available if the subject wants to discuss the trial with them or have any questions. The study 
procedures will be described, and the equipment will be shown to the subject. Study co-investigators will 
clearly explain all the procedures and risks of the testing outlined in the consent form. The subject will be 
given the time needed to consider their decision and will be encouraged to ask questions, both during the 
initial online interview (phone or Zoom Enterprise call) and throughout the study. The PI or a co-
investigator will answer any questions regarding the study at the time consent is given.  Once enrolled, 
the subject may pause or terminate his/her participation at any time during the study. 
 
 
5. 
Subject Enrollment 
 
We will enroll up to 60 subjects to find about 44 subjects, that will be randomized (by web-based program 
randomization.com) into 2 Groups (allocation ratio 1:1): active taVNS group (active taVNS) or sham taVNS 
group (sham taVNS). Randomization order will be placed into sequentially numbered sealed envelopes by 
an otherwise uninvolved staff member. Allocation concealment will be maintained throughout the study. 
Blinding will be maintained for participants and co-investigators not performing taVNS, including outcome 
assessors. 
All study procedures will be done at the Spaulding Neuromodulation Center/Spaulding Cambridge 
Hospital. 
 
In case of non-English speakers, a translated version of a ‘short form’ consent document will be used to 
document the informed consent when a non-English speaking individual is unexpectedly encountered and 
a written translation of the Mass General Brigham IRB-approved consent form is not available. In that case 
the consent process will follow these procedures: 
- The subject will be given a written translation of the ’short form’ consent document in the 
language understandable to them to read and must have the opportunity to ask and receive 
answers to questions. 
- The entire consent process will be witnessed by an individual who is fluent in both English and 
the language understandable to the subject. The interpreter may serve as the witness, if they are 
willing to do so, to the consent process (presentation of the information in the consent form in 

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the language understandable to the subject and the opportunity to ask and receive answers to 
questions) 
- The Mass General Brigham IRB-approved English version of the consent form will be signed by 
the investigator obtaining informed consent and the witness to the consent process. 
- The written translation of the ‘short form’ must be signed by the subject and the witness to the 
consent process.  
- The translator present for the consent process will be from the MGB Interpreter Services 
 
6. 
STUDY PROCEDURES 
 
Study Outline 
 
Pre-screening Procedures: 
During the pre-screening process, the subject can contact a co-investigator, usually via encrypted 
Zoom Enterprise call, and REDCap form. During the pre-screening process, the co-investigator will 
discuss the details of the study, explain the study procedures, and encourage the subject to ask 
questions. In the privacy of the encrypted Zoom Enterprise call for healthcare, the co-investigator 
will ask the subject questions from the following: 
1)     Online Screening questionnaire 
2)     Phone Pre-screening questionnaire  
Once this information is collected, the co-investigator will consult with the PI regarding the eligibility 
of the subject, who will then give the approval for the subject to come to our laboratory for the 
screening procedure.  
  
Visit 1 
 
Online or in-person Screening and Consent Visit – (Approximate Time: 1 hour) 
 
If in-person, the visit 1 can be performed together with the visit 2 - (Approximate Time: 3 hours 
and 30 min). 
If done remotely; the documentation would be signed electronically, and the visit would be done 
by telephone or using Zoom Healthcare) 
 
During the Screening, the PI and/or a co-investigator will conduct once more a review of 
inclusion/exclusion criteria to determine the subject’s eligibility for enrollment. If the consent is 
conducted by the co-investigator, the PI will review and sign off. Study procedures will be reviewed 
with the subject, and documentation of informed consent will be obtained. We will use an 
encrypted web-based platform (REDCap e-consent module) via Zoom call (Enterprise plan). Both 
services are already validated and in use by the MGB network.  
  
• 
Discuss study-specific procedures with the subject. 
• 
Review inclusion and exclusion criteria. 
• 
Obtain a signed and dated consent form. 
• 
Conduct a Demographics Survey, Brief Medical History, Beck depression inventory (BDI), and 
the Edinburg Handness Inventory Short form (EHI/SF). 
 
Visit 2  
Baseline Visit and First taVNS session – (Approximate Time: 2 hours and 30 min). 

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Urine pregnancy exam (if applicable). 
 
Baseline assessments: 
• 
EEG 
• 
HRV 
• 
QST 
• 
The Brief Mood Introspection Scale (BMIS) 
• 
Visual Analogue Scale to Evaluate Fatigue Severity (VAS-F) adaptation using tiredness item. 
  
After the Baseline assessments: 
Subjects will receive one session of either active taVNS or sham taVNS for 60 min. During the 
stimulation both groups will also be assessed with EEG, HRV,  and VAS-F. 
 
After the session, subjects will complete the following assessments: 
• 
Side Effects Questionnaire for taVNS. 
• 
Questionnaire to assess the success of blinding in clinical trials. 
• 
EEG 
• 
HRV 
• 
QST 
• 
BMIS 
• 
VAS-F 
 
 
Upon arrival and prior to the application, taVNS intensity will be measured for each participant 
separately, as above the detection threshold and below the pain threshold. The stimulation electrodes 
will be applied bilaterally to the ears, and in order to individually adjust the stimulation intensity, 
participants will receive increasing and decreasing series of 10-s stimulation trials and will rate the 
subjective sensation of the stimulation in a 10-point scale, ranging from nothing (0), light tingling (3), 
strong tingling (6), to painful (10). The increasing series of trials will start from an intensity of 0 mA and 
increase by 0.3 mA on a trial-by-trial basis until participants report it is uncomfortable to continue. This 
procedure will be repeated a second time. The final stimulation intensity for the experimental procedure 
will be calculated based on the average of the two intensities just below pain threshold. 
 
We will use a Healaon Transcutaneous Auricular Vagus Nerve Stimulation (taVNS) device (Neurive 
Inc., Gimhae, South Korea), which consists of an earset, with conductive eartips placed on the auricular 
concha of the ears. Electrodes are connected to a stimulator, and during active stimulation, both the 
cymba conchae of the auricular are stimulated at 30Hz, 200-250 us, with adjustable intensity for 60 min.   
The sham intervention will be done at the same location bilaterally to the cymba conchae of the auricular, 
however the device will be off during the 60 min session. 
 
 
Data for this study will be collected from subjects using an electronic format capture system 
(REDCap), and each subject will be assigned a de-identified code to collect the data. The data entered will 
be securely transferred to the Mass General Brigham REDCap database, to which only IRB-trained and 
approved study staff will have access. The following assessments will be performed: 
 
Demographic data: This survey will ask about demographic characteristics, including age, gender, sex, 
race, ethnicity, educational level, hand dominance, weight, height, and body mass index. 
 

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Medical history form: We will ask the history of medical conditions, a list of medications currently used, 
allergies, history of hospitalizations or visits to an emergency room in the last year, tobacco and alcohol 
consumption, and emergency and primary care physician contact. 
 
BDI: This self-report inventory consists of 21 multiple-choice questions and is a widely used method to 
classify depression severity. It assesses the presence of several symptoms related to depression, such as 
irritability, hopelessness, and decreased cognitive performance. Physical symptoms such as weight loss 
and fatigue are also included.  
 
EHI/SF: This short-form, self-report measure will be used to assess handedness in participants, asking their 
hand preference for 4 everyday tasks: writing, throwing, using a toothbrush, and using a spoon. 
 
Eletroencephalogram: We will record the EEG using a 64-channel EGI system (Electrical Geodesics, Inc) 
(EGI, Eugene, USA) in resting and continuously during visual task stimulus presentation. 
EEG phase synchronization of the DMN will be assessed in resting state with particular interest in the 
connectivity between mPFC to other brain regions in this network. EEG will be recorded using a high-
density electrode array from two resting state conditions: eyes-open and eyes- closed. Oscillatory activity 
will be measured in the regional sources of interest that comprises nodes from the DMN, and phase 
synchrony between DMN regions of interest with reference to the medial prefrontal regions using phase-
locking value (PLV). A data-driven statistical approach will be used to analyze the effects of taVNS on PLV. 
PLV, a measure of phase synchrony (i.e., the average of phase angle difference between two time series), 
can examine the synchronization in oscillatory activity between brain sources representative of the DMN 
(57). PLV can range from 0 to 1, with values close to 1 indicating strong synchronicity (i.e., perfect phase 
locking), while values close to 0 indicate substantial phase variation between the two signals, and thus 
low synchronicity between the two regions (i.e., no phase synchrony and randomly dispersed phases). To 
transform EEG data from scalp electrode space into source space, we will use a Matlab to model resting 
state activity representative of the DMN.  
The DMN resting state montage comprised six regional sources of interest: medial prefrontal cortex 
(mPFC), posterior cingulate cortex (PCC), left and right Angular Gyru (AG), and left and right lateral 
temporal cortices (LTC). As the multiple discrete sources approach is applied to source montages (58), 
activity from other brain areas can affect source waveforms of the DMN sources if only these DMN sources 
of interest are included in the source montage. Therefore, six additional noise sources were also included 
in the montage to measure brain activity that were not part of the networks associated with resting state 
activity in the DMN and to increase the sensitivity of the sources of interest. These noise sources 
comprised left and right occipital sources, left, right, and midline frontal sources, and a middle parietal 
source. To measure PLV, a complex demodulation method with 0.5 Hz wide frequency bins and 100 ms 
time resolution in the range of 1 to 50 Hz is used for decomposing the single-trial EEG data into 2-second 
time–frequency representations of temporal spectral evolution (TSE, an equivalent measure of oscillatory 
power) normalized to the power spectrum per participant. PLV will be measured from the radial 
component of each source of interest relative to the mPFC source as the seed (i.e., between mPFC and 
each of the sources at the PCC, left/right LTC, and left/right AG).  
 
Functional connectivity: Fourier transformation (STFT) will be applied to filter the data into five typically 
analyzed frequency bands, delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz) and gamma 
(30–80 Hz) bands, then we will apply the phase lag index (PLI) method to calculate the connectivity 
matrices and graph theory-based methods to measure the topology of brain networks across different 
frequency bands.  

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In this study, phase synchronization will be measured between all the pairs of channels by the Phase 
Length Index method, which is an asymmetry index that measures the distribution of phase differences 
(59, 60). Due to the instantaneous spread of current, the same sources collected by two electrodes are 
considered to cause a zero-lag phase difference, which is rejected by PLI. Therefore, PLI is less sensitive to 
the volume conduction effect, and it can reveal the true coupling strength between pairs of channels.  
The value of PLI index varies between 0 and 1. A value of 0 indicates no coupling or coupling with a phase 
difference centered around 0 mod p, and a value of 1 indicates perfect phase synchronization between 
two signals at a constant lag except 0 or p.  
 
Frontal alpha asymmetry (FAA): After transforming to average reference, the continuous EEG signal will 
be segmented (1000 ms after stimulus onset), Fast-Fourier will transform after the data had been 
weighted with a Hamming window that tapered the distal 5% of each epoch and averaged without 
overlap. As the result of the weighting functions in the windowing process, the ends of any 1000 ms-
segment will be less weighted.  
Power for theta (4-7 Hz), alpha-1 (8-10 Hz), and alpha-2 (11-13 Hz) frequency bands will be extracted 
separately for happy and sad face stimuli for the left (mean of F3, F5, and F7 electrodes) and right (mean 
of F4, F6, and F8 electrodes) frontal hemisphere for further statistical analysis.  
 
Tasks and Stimuli 
 
1) The task will consist of alternating trials showing a consecutive series of either sad or happy facial 
expressions randomized by sex. One trial consists of a series of five to eight faces of one emotion with a 
varied number of faces per emotion to maintain subjects’ attention on the task. To further enhance 
attention, Participants will be instructed to press a button as they noticed a switch from one emotional 
expression to the other, i.e., switch from the happy to the sad or from the sad to the happy trial. After six 
trials, the participants will be asked, "To what extent were you able to emphasize with the faces?" 
followed by a short break of about 10 seconds until the next six trials are presented. Subjects will need to 
self-report to what extent they fell empathy towards the face stimuli on a Likert scale ranging from 1 (very 
much) to 4 (very little). There will be two long breaks of about 20 seconds. During this break and at the 
end of the task, participants will be also asked, "How do you feel?". Subjects will self-report how they 
themselves feel on a Likert scale ranging from 1 (very good) to 4 (very bad). Altogether, there will be 24 
trials of sad and 24 trials of happy facial expressions, and 6 short and two long breaks (duration of face 
stimuli presentation: 1000 ms). We will use happy and sad emotional face stimuli from “The Karolinska 
Directed Emotional Faces” database (61), which have been evaluated on emotional content, intensity, and 
arousal. 
 
2)The go/no-go task consists of randomly displayed visually cued tasks, including 150 go trials and 50 no-
go trials. Each trial started with a white light presented centrally on a gray background for 1,500 ms, 
followed by a color cue that subtended 20°. Go trials are cued with a “long green” light presented centrally 
until the response button is pressed or for 300 ms if there is no response. No-go trials are cued with “short 
green (50 ms) + short red (100 ms)” lights which are displayed for 150 ms. Trials order is pseudo-random 
and permuted such that on 15% of trials, a no-go cue is shown after three, five, and seven go trials, and 
on 10% of trials, a no-go cue is displayed after two, four, and six go trials. Participants are instructed to 
focus on the white light and press the response button with their right hand as quickly as they could every 
time the go cue appeared and not to press the button when the no-go cue is shown (62). 
 

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Heart Rate Variability (HRV): HRV will be collected with a CorSense (EliteHRV, USA) device (an FDA cleared 
and validated device) from the third finger of the non-dominant hand following a standardized protocol. 
The measurements will be taken at baseline, during, and after stimulation. As both short- (5 min) and 
long- (24 hours) duration ECG are valid options for measuring HRV, the data will be stored in a web-based 
secure system. The recording will be performed for 5 min minutes as recommended in previous trials (63, 
64). The HRV metrics will be: (1) total power ≤ 0.04 Hz; (2) very low frequencies ≤0.04 Hz (VLF), (3) low 
frequencies 0.04–0.15 Hz (LF), (4) high frequencies 0.15–0.4 Hz (HF), and (5) LF/HF ratio, as we performed 
in previous studies from our group (65, 66); (6) the standard deviation of the R-R intervals (SDRR); (7) the 
count of R-R intervals that differed more than 50 ms (NN50); (8) the percentage of NN50 (pNN50); and (9) 
the root mean square of the difference between successive R-R intervals (RMSSD) will be measured. 
Finally, since the HRV random fluctuations and fractal components, we will perform a non-linear method 
to calculate the short-term detrended fluctuation analysis (DFA-alpha1) (66-69). 
 
Qualitative sensory testing (QST) 
Conditioned Pain Modulation Test (CPM-test): We will follow the adapted protocol by Granot et al., 2008 
and Nir et al., 2011(70, 71). We will first determine the pain-60 temperature by applying a thermode on 
the right forearm and delivering  a short heat stimuli generated by a TSA-II Stimulator (Medoc Ltd) using 
the FDA approved safety temperature range of the device that goes up 48°C (118,4 degrees Fahrenheit), 
each lasting 7s. Subjects will be asked to rate the pain intensity with a numerical pain scale (NPS). Once 
determined, we will administer the test stimulus for 30s at that temperature and will be asked to rate 
their levels of pain at 10, 20 and 30s. For the conditioned stimulus, the left hand of the subject will be 
immersed in water at 10 to 12°C for 30s. Then, the same temperature will be applied on the right forearm 
(left hand will still immersed) at 10, 20 and 30s. CPM response will be calculated as the difference between 
the average of pain ratings from the test stimulus minus the conditioned stimulus. 
 
Temporal Slow Pain Summation (TSPS): Heat pulses will be delivered to the right dominant proximal volar 
forearm using an appropriate size embedded HP-thermode. We will follow the adapted protocol 
suggested by Staud et al, 2014, in which the HP-thermode was programmed to deliver pulses rising/fall of 
1-2-s, depending on subject’s heat-evoked pain threshold, from adapting temperatures to peak 
temperatures, with a plateau of .7-s(72). Subjects will be trained to determine the temperature necessary 
to elicit pain-60 (see CPM protocol below). Subsequently, they will receive one train of 15 repetitive heat 
stimuli at 0.4 Hz to the same area, in which by being suitable for eliciting TSPS in most subjects, it allows 
the rating of individual pain stimuli and is unlikely to induce peripheral sensitization. TSPS will be 
calculated as the difference between heat pain rating after the 15th stimulus minus the 1st stimulus 
 
Brief Mood Introspection Scale (BMIS): The BMIS scale is a mood scale consisting of 16 mood-adjectives 
to which a person responds (e.g., Are you "happy"?). The scale can yield measures of overall pleasant-
unpleasant mood, arousal-calm mood, and it also can be scored according to positive-tired and negative-
calm mood.Demographic data, medical comorbidities and adverse effects will be assessed using a 
standardized questionnaire. 
 
Visual Analogue Scale to Evaluate Fatigue Severity (VAS-F): We will use an adaptation of the VAS-F 
assessing only the first question related to tiredness. The scale consists of 18 items relating to the 
subjective experience of fatigue. Each item asks respondents to place an “X,” representing how they 
currently feel, along a visual analogue line that extends between two extremes (e.g., from “not at all tired” 
to “extremely tired”). In contrast to discrete, Likert-type scales, the VAS-F places fewer restrictions on the 
range of responses available to individuals. 

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Side Effects Questionnaire for taVNS: After the stimulation session, subjects will complete a 
questionnaire to evaluate potential adverse effects of taVNS on a 4-point scale (None, mild, moderate, 
and severe). They will be asked whether they have experienced any side effects in an open-ended manner 
and they will then be specifically asked about ear pain, headache, tingling, dizziness, skin redness, fatigue, 
prickling, pressure, itching, unpleasant feelings. If any side effects are reported, the degree of relatedness 
to the intervention will be assessed on a 5-point scale. This type of adverse events questionnaire has been 
suggested in our recent systematic review and meta-analysis on safety of taVNS and has been used 
similarly in all the tDCS studies of the group. 
 
Questionnaire to assess the success of blinding in clinical trials: After the stimulation session, subjects 
will be asked to guess their treatment assignment, and they may be allowed to express treatment guess 
or uncertainty, i.e. subjects will be asked to guess their treatment assignment among active, sham or do 
not know. After that they will be asked how confident they are from 0 to 5 on their choice. 
 
 
7. 
Risks and Discomforts 
 
Transauricular vagus nerve stimulation (taVNS): it is a technique that poses a non-significant risk to 
subjects. The safety of taVNS has been addressed and tested by multiple researchers who have concluded 
that taVNS, as applied in a manner similar to our proposed protocol, induces only temporary mild effects. 
A review study in 2018 was the first to systematically report transcutaneous vagus nerve stimulation 
treatment safety(73). The author concluded that transcutaneous vagus nerve stimulation is well tolerated 
and safe, with only mild side effects(73). Recently, we have just conducted a systematic review and meta-
analysis with 167 clinical trials involving 6,322 subjects, and we concluded that active taVNS and controls 
were not different in the risk of developing an AE and in the intensity of the events. In general, the 
incidence of AE was low, being ear pain, headache, and tingling the most frequent ones. No severe adverse 
event was shown to be caused by taVNS. We also found that more than half of the studies did not mention 
the presence or absence of AEs, and these studies did not differ from those that reported no AE or the 
presence of at least one AE regarding sex, age, study design, number of sessions, or parameters, such as 
stimulation intensity, pulse width, and frequency of the stimulation. Thus, we postulate that taVNS is a 
safe and feasible treatment option.  
 
Electroencephalography (EEG): The EEG procedures are performed to measure the electrical activity in 
the brain and to examine the dynamic changes. It also allows for better understanding of the effects of 
electrical activity generated in different areas of the brain. EEG only measures brain activity and does not 
induce electrical current. These procedures are non-invasive and have been used extensively in clinical 
practice for diagnosis of neurological conditions such as epilepsy. Therefore, EEG poses no significant risk 
or anticipated discomfort. 
 
Heart rate variability (HRV): As the EEG, the electrocardiogram (ECG) device is used to measure the 
electrical activity in the heart and its variability. ECG only records heart activity and does not deliver any 
electrical current. The procedure is non-invasive and has been used extensively in clinical practice for 
diagnosis of heart conditions. Therefore, ECG and the HRV recording poses no significant risk or discomfort 
to the subjects. 
 
Quantitative sensory testing (QST) 

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Temporal slow pain summation (TSPS) and Conditioned Pain Modulation (CPM): Temporal slow pain 
summation (TSPS) is thought to represent summation of C fiber mediated pain and is being used to probe 
pain processing abnormalities in several chronic pain disorders(74, 75). In this protocol short duration 
noxious heat stimuli are delivered at 0.4 Hz with the destination temperature set to 44°C, 46°C, and 48°C. 
  
Conditioned pain modulation (CPM) is a laboratory method to evaluate the individual capabilities to 
inhibit pain. This phenomenon is based on the fact that when a pain test stimulus is given together with a 
conditioning pain stimulus, the test stimulus is perceived as less painful than when it was given alone. In 
this protocol the conditioning pain stimulus will be performed by using a cold bath of water set to 12°C 
(76). 
  
TSPS and CPM have no potential risks and are non-invasive. However, these tests assess pain, so a 
transitory level of discomfort is expected momentarily. These effects are brief and have no health 
repercussions. The subject can choose to stop this test at any time if they do not feel comfortable 
continuing. 
 
Behavioral assessments/Questionnaires: All questionnaires and clinical evaluation scales will be 
administered in the privacy of a closed room. There are no potential risks posed to participants with 
respect to behavioral tasks and questionnaires. If participants become fatigued during testing or are 
uncomfortable answering any personal questions, they will be informed that they are allowed to take a 
break at any point during the experiment and that they may end their participation at any time. 
 
 
8. 
Benefits 
 
The results of this study will provide a ground for future studies and may benefit subsequent future 
subjects to the application of taVNS therapy.          
 
 
9. 
Statistical Analysis 
 
Sample size calculation: 
We planned a sample size using the available preliminary data from previous mechanistic studies in 
taVNS and HRV, and transcranial direct current stimulation (tDCS) and EEG metrics. From our knowledge, 
there is no previous data on the effects of taVNS in FAA, synchrony of DMN, or functional connectivity. 
For this reason, we calculated the sample size for these outcomes based on an analogous intervention, 
the tDCS in the left dorsolateral prefrontal cortex. Based on that, we considered some scenarios based on 
our aims. We could detect a variety of scenarios and different magnitudes of sample sizes, and we decided 
to choose a more conservative approach taking in consideration the main outcome domains in EEG and 
HRV that we aim to test in our study with some the smallest effect sizes calculated (See Table 1). We 
assumed a type I error of 5% (alpha), a type II error of 20% (beta), and a power of 80%. Therefore, taking 
in consideration the most conservative scenario, we estimated a sample of 36 subjects. However, we 
expanded the sample in 20% to account for a conservative attrition rate and to increase power for 
secondary outcome analysis. Then, we will include a total sample size of 44 subjects, this will lead in 22 
subjects each group. 
 
 

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Table 1. Sensitivity analysis for sample size calculation 
Questions 
Intervention 
Previous 
studies 
Study 
effect 
size (Cohen's d, 
95% CI) 
Needed 
sample 
size 
(power 
80% 
and alpha 5%) 
Final 
sample 
increasing by 20% 
Aim 1: One active taVNS session effects on frontal alpha asymmetry (FAA), functional connectivity and phase 
synchrony of DMN using EEG on a processing emotional facial expressions and a Go/NoGo task. 
Effects in alpha 
asymmetry 
modulation 
Left 
DLPFC 
tDCS 
Liu 2022 (77) 
F4-3: 
1.03 
(0.31 to 1.73) 
30 subjects 
36 subjects (18 each 
arm) 
F6-5: 
0.94 
(0.23 to 1.65) 
36 subjects 
44 subjects (22 each 
group)  
Effects in gama 
band 
FC 
between 
the 
posterior 
cingulate 
cortex and r-
IPL 
Left 
DLPFC 
tDCS 
Koizumi 2020 
(78) 
Pos-pre: 57.71 
(43.16 
to 
72.24) 
2 subjects 
4 subjects (2 each 
group) 
Aim 2: One active taVNS session effects in heart rate variability  
Effects 
in 
LF/HF ratio 
taVNS 
Vosseler 2020 
(cross-over) 
(79) 
-2.22 (-3.13 to -
1.29) 
8 subjects 
10 subjects (5 each 
group) 
Effects in HF 
taVNS 
Geng 
2022 
(cross-over) 
(20)  
13.72 (9.93 to 
17.49) 
2 subjects 
4 subjects (2 each 
group) 
Effects 
in 
RMSSD 
taVNS 
Vosseler 2020 
(cross-over) 
(79) 
-1.54 (-2.35 to -
0.71) 
14 subjects 
18 subjects (9 each 
group) 
Geng 
2022 
(cross-over) 
(20) 
2.35 (1.36 to 
3.32) 
6 subjects 
8 subjects (4 each 
group) 
Effects 
in 
pRR50 
taVNS 
Geng 
2022 
(cross-over) 
(20) 
1.53 (0.67 to 
2.37) 
14 subjects  
18 subjects (9 each 
group) 
Effects in SDRR taVNS 
Geng 
2022 
(cross-over) 
(20) 
2.79 (1.72 to 
3.83) 
6 subjects 
8 subjects (4 each 
group) 

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Effects in total 
power 
taVNS 
Geng 
2022 
(cross-over) 
(20) 
1.01 (0.22 to 
1.80) 
32 subjects 
38 subjects (19 each 
group) 
 
AIM 1: Data forms and questionnaires will be coded in a standardized manner, and double-entered into 
our database. Digital measures/recordings will be similarly tracked in our database and regularly backed 
up. Analyses will be conducted using standard statistical software such as STATA and MATLAB toolboxes. 
All analyses will be performed on an intention-to-treat basis (using the method of multiple imputations 
for missing data). We will also perform an additional sensitivity analysis using completers only. The 
primary outcomes for this aim will be the EEG biomarkers (alpha asymmetry, functional connectivity, and 
phase synchrony of the default mode network). We will obtain all the measurements at baseline and 
during the stimulation period. Linear mixed models will be used to test for differences between the active 
and sham group, adjusting for covariates when necessary. Further exploratory analysis to detect 
predictors of response to taVNS will be performed taking in consideration the covariates assessed. 
Statistical significance will be considered if p-values < 0.05.  
 
The between subjects’ factor and measures on hemisphere (left and right), and emotion (happy and 
sad) will be performed for alpha-1, alpha-2, and theta. All the power will be ln-transformed. The significant 
main effects will be further analyzed with Cohen's d effect sizes and the interactions will be divided in 
simple effect and graphical interpretations.  
 
In order to analyze phase synchrony of the default mode network, a non-parametric cluster-based 
permutation testing will be performed. A software identifies clusters in specific locations that are different 
regarding oscillatory amplitude and phase-locking within a frequency range between the groups. Power 
spectra and phase synchrony data-driven tests are also allowed by the software. The phase-locking value 
(PLV) from eyes open and close will be assessed between treatment groups. Then, we will perform a 
permutation testing with a Monte-Carlo resampling approach to localize the clusters higher than 95% of 
all clusters from random permutation of the data. For cluster building we will set an alpha of 0.01 and a 
number of permutations at 3000. 
 
Functional connectivity will be analyzed by a software that can determine significant differences 
between the treatment groups. The network-based-statistic (NBS) identifies significant brain networks 
built by suprathreshold links, but not individual links. We will compute each test for each pairwise network 
using this threshold. The statistical analysis between treatment groups will be performed after taking the 
average of the matrices through the time windows. We will set a significant p-value < 0.05 and non-
parametric permutation test in 5000.  
 
AIM 2: We will have a similar statistical analysis plan as in Aim 1. The differences between the metrics 
during the after, during stimulation and baseline will be calculated. The HRV metrics will be summarized 
as means and standard deviations will be used to represent the variance. Linear mixed models will be used 
to test for differences between the active and sham group, adjusting for covariates when necessary. 
Further exploratory analysis to detect predictors of response to taVNS will be performed taking in 
consideration the covariates assessed. Statistical significance will be considered if p-values < 0.05.  
 
 
   
 

 
 
 
 
 
 
 
 
 
 
 
 
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