Effects of Non-invasive Transcranial Electrical Stimulation on Cognition in Patients With Multiple Sclerosis
Phase: NA
Conditions: Multiple Sclerosis, Cognitive Impairment
Sponsor: University of California, San Francisco

PI: Riley Bove, MD. 
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Clinical Research Protocol 
 
Effects of non-invasive brain stimulation on cognitive function in patients with multiple 
sclerosis 
Protocol Number: 
1.0 
Version Date: 
Oct 1st, 2020 
Investigational Product: 
n/a 
IND Number: 
n/a 
Development Phase: 
Phase 1 
Sponsor: 
Riley Bove 
675 Nelson Rising Lane 
San Francisco, CA 
Funding Organization: 
National Multiple Sclerosis Society 
Principal Investigator: 
Name: Riley Bove 
 
Telephone: (415) 353-2069 
 
Fax: 
 
 
E-mail: riley.bove@ucsf.edu 
Medical Monitor: 
Name:  
 
Telephone: 
 
Fax: 
 
 
E-mail:  
 
Coordinating Center: 
If applicable 
 

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Approval: 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
    
Assistant Professor, Neurology  
UCSF Weill Institute for Neurosciences 
 
 
 
 
 
 
 
 
 
 
10/1/2020 
PI or Sponsor Signature (Name and Title)  
 
 
 
 
 
 
 
 
 
Date 

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This confidential information about the research study protocol is provided for the exclusive 
use of investigators of this study and is subject to recall at any time. The information in this 
document may not be disclosed unless federal or state law or regulations require such 
disclosure.  Subject to the foregoing, this information may be disclosed only to those 
persons involved in the study who have a need to know, with the obligation not to further 
disseminate this information.   
 

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PROTOCOL AGREEMENT 
 
I have read the protocol specified below. In my formal capacity as Investigator, my duties include ensuring 
the safety of the study subjects enrolled under my supervision, as outlined in the protocol. It is understood 
that all information pertaining to the study will be held strictly confidential and that this confidentiality 
requirement applies to all study staff at this site. Furthermore, on behalf of the study staff and myself, I 
agree to maintain the procedures required to carry out the study in accordance with accepted GCP 
principles and to abide by the terms of this protocol. 
 
Protocol Number:  1.0 
 
Protocol Title:  Effects of non-invasive brain stimulation on cognitive function in patients with multiple 
sclerosis 
 
 
Protocol Date:  10/1/2020 
 
10/1/2020 
Investigator Signature  
 
Date 
Riley Bove,  
Print Name and Title 
Site # 
1 
 
Site Name 
UCSF mission bay 
Address 
675 Nelson Rising Lane, San Francisco, CA 94158 
 
 
 
 
 
 
Phone Number 
 (415) 353-2069 
 
 
 
 
 
 
 

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Study Background 
Multiple sclerosis (MS) is a neurological disorder characterized by a wide variety of disabling symptoms 
including motor and sensory disturbance, cognitive deficits, visual impairment, pain, fatigue and 
spasticity. Notably, cognitive impairment (CI) occurs in up to 70% of people with MS (Chiaravalloti & 
DeLuca, 2008) and has a profound influence on a patient’s personal functioning, social interaction, 
employment status and overall quality of life. The most commonly affected cognitive domains are 
attention, speed of information processing, executive function and memory (Achiron & Barak, 2003; 
Rogers & Panegyres, 2007), and influence everyday life, from finding an individual’ telephone number in 
the telephone directory to making a plan for a day. Although disease modifying therapies (DMTs) that 
target primarily the inflammatory immunopathology of MS (Birnbaum, 2010; Lopez-Diego & Weiner, 
2008) can slow progression of impairments including CI, existing DMTs are only partially effective or 
ineffective in improving impaired cognition in MS patients (Geisler et al., 1996; Lovera et al., 2010; 
Shaygannejad, Janghorbani, Ashtari, Zanjani, & Zakizade, 2008). Therefore, it is of utmost importance 
to develop alternative therapeutic approaches to alleviate CI in MS.   
Recently, different forms of non-invasive transcranial electrical stimulation (tES) have been 
probed as non-pharmacological interventions in several neurological and psychiatric disorders given its 
safety, portability and potential for at-home application. The two main forms of non-invasive tES are: 
transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS). 
Preliminary studies have shown promise that tDCS may serve as a tool to ameliorate cognition (Mattioli, 
Bellomi, Stampatori, Capra, & Miniussi, 2016), pain (Ayache et al., 2016; Mori et al., 2010), fatigue 
(Ferrucci et al., 2014; Hanken et al., 2016) and sensory deficits (Mori et al., 2013) in patients with MS. 
For example, Mattioli et al (2016) reported that tDCS over the prefrontal cortex improves attention, 
information processing speed and executive function (Mattioli et al., 2016). Furthermore, this 
improvement in cognition was sustained six months after the last treatment. While these studies provide 
intriguing support for tES as a new therapeutic strategy for MS patients, tES research in MS remains in 
its infancy and there are no consensus recommendations for its use in MS. Furthermore, the effects of 
the tACS form of tES on cognitive function in MS patients have not yet, to our knowledge, been assessed.  
TACS applies weak sinusoidal currents to the brain through the scalp in a frequency-specific 
manner and is capable of entraining endogenous brain oscillations and enhancing cognitive function 
including attention (Hsu, Zanto, & Gazzaley, 2019; Hsu, Zanto, van Schouwenburg, & Gazzaley, 2017), 
working memory (Meiron & Lavidor, 2014; Polania, Nitsche, Korman, Batsikadze, & Paulus, 2012; 
Vosskuhl, Huster, & Herrmann, 2015), response inhibition (Joundi, Jenkinson, Brittain, Aziz, & Brown, 
2012), and fluid intelligence (Pahor & Jausovec, 2014; Santarnecchi et al., 2013). TACS capitalizes on 

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the fact that a wide range of cognitive capabilities are mediated by the dynamic modulation of rhythmic 
oscillatory activity, whereas tDCS only applies broad increases or decreases in cortical excitability. 
Therefore, tACS could provide an advantage over tDCS through a more principled approach by 
specifically targeting deficient oscillatory neural activity. Importantly, abnormalities in oscillatory brain 
dynamics have been associated with impaired cognition in MS (Kiiski et al., 2012; Van der Meer et al., 
2013). For example, MS patients have significantly reduced theta power in the prefrontal cortex (PFC) 
compared to both healthy controls and MS patients without CI (Kiiski et al., 2012), indicating theta power 
reduction in the PFC is a feature of more advanced cognitive impairment in MS. Indeed, PFC theta 
oscillations are related to information processing tasks, especially those of attention and other executive 
functions (Gevins, Smith, McEvoy, & Yu, 1997; Klimesch, 1999; Mizuhara, Wang, Kobayashi, & 
Yamaguchi, 2004). A collective view of these findings leads to the hypothesis that cognitive disturbance 
in MS may be mitigated by targeting disturbances in oscillatory brain dynamics by applying theta-tACS 
over the PFC. 
 
 
Study Objectives 
The goals of this proposed study are to 1) evaluate the potential of using frontal theta-tACS during a 
cognitive task to mitigate cognitive disturbance in MS, specifically, information processing speed and 
attention, and 2) understand stimulation response variability at the individual-level. Processing speed and 
attention will be targeted for remediation due to the prevalence of their decline in MS and our previous 
research (and others) that show tACS may improve these cognitive functions.  
 
 
Study Design  
Overall strategy. We will enroll forty adult 
MS patients (aged 18-65 years) randomly assigned 
to one of two groups: either a Verum (6 Hz) tACS 
group or a Frequency Control (1 Hz) group. Twenty 
participants in each group will correspond with >80% 
power (1-) at a 95% significance level (1-) as 
calculated from our preliminary studies. The two 
groups will be age-matched. A randomized double-
blinded, 
placebo 
controlled, 
multi-session 

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experiment is proposed to assess whether tACS may yield improvements in divided attention and 
information processing speed in MS (Specific Aim 1) and identify predictive factors of response to tACS 
(Specific Aim 2). The experimental paradigm consists of 5 daily sessions (conducted over up to 10 days) 
(Fig 1). During session 1 (baseline; pre-tACS) and session 5 (follow-up; post-tACS), participants will be 
assessed on divided attention while electroencephalography (EEG) data is acquired. EEG data will 
enable assessments of neuroplastic changes associated with tACS effects on divided attention and it will 
also serve to quantify cortical excitability as a predictor for tACS effects. Additionally, processing speed 
will be assessed along with questionnaires on pain and fatigue. During sessions 2-4, tACS will be applied 
while participants are engaged in a tablet-based multitasking task, which includes divided attention and 
processing speed components, but is distinct from the primary outcome measures.  
 
Inclusion/Exclusion Criteria. Inclusion Criteria: age 18-65, diagnosis of MS (relapsing or 
progressive) according to McDonald criteria (Polman et al., 2011), Expanded Disability Status Scale 
(EDSS)≤6.5 (Noseworthy et al., 1990), no paresis of the upper limbs, a minimum of 3 months since the 
last relapse, no severe depression (Beck Depression Inventory<19), normal hearing, and no changes in 
MS or symptomatic medications in past 2 months. Exclusion Criteria: prior brain surgery, clips in brain, 
epilepsy or other neurological or non-affective psychiatric disorders, pregnancy. 
 
Outcome measures (Sessions 1 and 5). 
o 
Primary outcome measure: Divided attention (Specific Aim 1). This (and all) outcome 
measure(s) will be assessed at baseline (pre-tACS; session 1) and at follow-up (post-tACS; session 5). 
Divided attention will be measured by a divided attention task module (Table 1). The divided attention 
module is comprised of 3 tasks: visual perceptual discrimination (single task), visuomotor tracking (single  
 
task) and multitasking (dual task; both single tasks simultaneously). Performance during perceptual 
discrimination will be measured with a metric of discrimination performance (d-prime), which is estimated 
for each participant by comparing hit rates (correct responses to target signs) and false alarm rates 
(responses to non-targets) and calculated as d’ = Z(hits)–Z(false alarms). D-prime cost (dual task - single 
Table 1. Divided Attention Task Module
TASK
DESCRIPTION
Perceptual 
discrimination 
Go/No Go like-paradigm; respond to target stimuli while ignoring distractors  
Visuomotor tracking 
Navigate a character along a dynamically moving road while avoiding walls and 
obstacles  
Multitasking ability 
Perform perceptual discrimination and visuomotor tracking tasks simultaneously

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task) from the discrimination task will be used as our measure of divided attention because we have 
previously observed this metric to improve with tACS during this task (Hsu et al., 2019; Hsu et al., 2017)  
(Preliminary Study 1). 
o 
Primary outcome measure: Information processing speed (Specific Aim 1). 
Information processing speed will be assessed with the Symbol-Digit Modalities Test (SDMT). SDMT is 
widely used in MS clinical trials to measure speed of information processing (Van Schependom et al., 
2014). SDMT requires the participant to substitute geometric symbols for numbers while scanning a 
response key. Verbal, not written, responses will be recorded.  The quantity of correct items will serve as 
the primary measure of processing speed because we have previously demonstrated that this metric 
improves with cognitive training in MS patients (Preliminary Study 2). Importantly, we will employ the 
same cognitive paradigm during tACS as we previously used in Preliminary Studies 1 and 2. 
o 
Secondary outcome measure: Frontal theta power (Specific Aim 1). The visual 
discrimination task (single and dual task) will be used to assess neuroplastic changes in divided attention. 
We have previously demonstrated (and replicated) that theta-tACS above PFC is able to enhance divided 
attention abilities (i.e., dual - single task discrimination performance) in healthy adults (Preliminary Study 
1). Importantly, increases in midline frontal theta power is correlated with improvements in divided 
attention. EEG data will be collected during the divided attention task module with a 64-channel BioSemi 
ActiveTwo system. Raw data will be segmented into epochs beginning 1000 ms before to 1000 ms post 
stimulus onset, demeaned/detrended and referenced to the average EEG signal. An independent 
component analysis will be performed to remove components consistent with topographies for blinks and 
eye movements. Epochs that exceed a voltage threshold of 80 μV will be rejected. EP data will focus on 
amplitudes and latencies of the P1 and N1 components. For the spectral analysis, a fast fourier 
transformation will be performed from 4 to 30 Hz. The data will be multiplied by a hanning taper, using a 
sliding time window. Power changes of oscillatory activity as a function of time will be calculated for theta 
(4-7Hz), alpha (8-12Hz), and beta (13-30Hz) bands with one power value every 10 ms.  
o 
Exploratory measures (Specific Aim 1). Three exploratory measures will be used to 
assess whether tACS effects extend beyond our hypothesized changes in divided attention and 
processing speed. Specifically, during sessions 1 and 5 (pre- and post-tACS) we will assess changes in 
cortical excitability, fatigue and pain. 1) Cortical excitability will be assessed via EPs due to their 
sensitivity to tACS effects (Jamil et al., 2017). 2) Fatigue and 3) pain will be assessed because previous 
studies have shown that tDCS improves pain (Ayache et al., 2016; Mori et al., 2010) and fatigue (Ferrucci 
et al., 2014; Hanken et al., 2016) in patients with MS. To assess fatigue, the Modified Fatigue Impact 
Scale (MFIS) will be used, which consists of 21 items from the Fatigue Impact Scale (Fisk et al., 1994; 

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Kos et al., 2005), a multidimensional scale assessing the perceived impact of fatigue on three subscales 
(Physical, Cognitive, and Psychosocial) of activities, resulting in a total MFIS score. Pain will be assessed 
via the Brief Pain Inventory (BPI), a 32-item self-administered questionnaire to measure a pain severity 
score and a pain interference score (Daut, Cleeland, & Flanery, 1983). 
o 
Covariates to be included in Regression Analyses (Specific Aim 2). Regression 
analysis will be performed to identify predictors of tACS effects on the primary outcome measures: divided 
attention and processing speed. Three classes of predictors will be assessed: neuroanatomy, cortical 
excitability, and clinical severity, in addition to those typically accounted for in MS studies: demographic 
(age, gender, education) and clinical features (MS duration, EDSS). 1) Neuroanatomy. Differences in 
the thickness of the skull, cerebrospinal fluid, subcutaneous fat, as well as gyral pattern, and local tissue 
heterogeneities (such as atrophy) yield differences in resistivity that will differentially impede current flow 
to cortex (Opitz, Paulus, Will, Antunes, & Thielscher, 2015; Shahid, Wen, & Ahfock, 2013; Truong, 
Magerowski, Blackburn, Bikson, & Alonso-Alonso, 2013). The consequence of this anatomical variability 
can lead to 1.5 to 3-fold differences in the induced electric field in cortex (Datta, Truong, Minhas, Parra, 
& Bikson, 2012; Russell et al., 2013), contributing to variable tES outcomes. Indeed, we have recently 
demonstrated that the amount of current that reaches the brain predicts tACS efficacy (Preliminary Study 
1). Therefore, to assess the amount of tACS-induced current that reaches the brain, individual MRI data 
will be used to model the electric field within each patient’s brain. Standard modeling software will be 
used for this task (Huang, Datta, Bikson, & Parra, 2019). As patients’ annual clinically-acquired brain 
MRIs are available in Dr. Bove-led BRIDGE platform (bridge.ucsf.edu), funds are not requested to collect 
MRI data. The average modeled electric field magnitude within the PFC will be used as a predictor 
variable for the regression analysis. 2) Cortical excitability. Evoked potentials (EPs) from the single task 
version of the discrimination task will be used to assess cortical excitability as a predictor variable in the 
regression analysis. In MS, demyelination and axonal loss occur, which not only changes the current flow 
of tES, but alters cortical excitability as measured by EPs (Caramia et al., 2004). EP abnormalities in MS 
include morphological changes, delayed latencies, wave cancellation and increased refractory period 
(Iodice et al., 2016). Importantly, baseline cortical excitability, as measured by EPs, has been shown to 
be a significant covariate associated with variable effects of tES across individuals (Jamil et al., 2017). 
3) Clinical severity. In a meta-analysis of non-invasive neurostimulation effects, we have shown that 
patients with the greatest clinical severity are the ones who benefit most from neurostimulation (Hsu, Ku, 
Zanto, & Gazzaley, 2015). Here, we will use the MS Functional Composite 4 (MSFC4) as a metric of 
clinical severity and assess it as a predictor variable in the regression analysis. The MSFC4 assesses 
four key MS-related functional domains: ambulation (timed 25 foot walk), upper extremity dexterity (9-

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Hole Peg Test), vision (low contrast visual acuity) and cognition (PASAT, a test of information processing 
speed, flexibility, attention, and working memory (Rosti, Hamalainen, Koivisto, & Hokkanen, 2006; 
Tombaugh, 2006)). 
 
Interventions (Sessions 2 – 4). 
o 
Transcranial alternating current stimulation (tACS). TACS will be applied at 6 Hz for 
the Verum tACS group and 1 Hz tACS for the Frequency Control group because higher frequencies of 
stimulation (above theta) may introduce visual flickering (or phosphenes) that could confound the 
interpretation of the data (Paulus, 2010; Schutter & Hortensius, 2010). Moreover, 1-Hz tACS has not 
been associated with cognitive alterations (Antal et al., 2008; Castillo Saavedra et al., 2014) and we have 
verified its use as a control in Preliminary Study 1. A sinusoidal alternating current of 1mA peak amplitude 
(2mA peak-to-peak amplitude) will be delivered via a pair of Ag/AgCl electrodes (3.14 cm2) through a 
Starstim-32 device (Neuroelectrics, Spain) while patients are engaged in a tablet-based cognitive task 
(EVO, see below). During each session, participants will receive 20 min of stimulation with a 15-s ramp 
up and 15-s ramp down. The stimulation electrodes will be located at F3 and F4 of the 10–20 electrode 
coordinate system (above PFC). Impedance will be kept below 10 kΩ. In order to confirm that the 
frequency control was an appropriately blinded manipulation and all patients tolerate tACS well, all 
patients will be asked to complete a 1-min survey to scale the perception of stimulation (headache, scalp 
pain, tingling, burning sensation) from 1 (mild) to 10 (severe) at the end of each session. If the score on 
the stimulation perception survey is below 4 for each item, tACS will be considered well-tolerated.  
o 
Cognitive paradigm. During tACS, participants will be engaged in a divided attention 
paradigm known as EVO (Akili Labs, Boston) (Anguera et al., 2017; Anguera, Jordan, Castaneda, 
Gazzaley, & Arean, 2016; Arean et al., 2016; Davis, Bower, & Kollins, 2018). The EVO paradigm consists 
of a divided attention paradigm that combines visuomotor tracking and perceptual discrimination tasks 
similar to, but distinct from, those used for our outcome measure of divided attention. EVO utilizes 
adaptive algorithms to change game difficulty on a trial-by-trial basis for both the perceptual 
discrimination (adapting the response window for a target) and visuomotor tracking (adapting the 
speed of the forward path and sensitivity of the user’s motions), with real-time feedback making the 
patients aware of their performance. More specifically, the adaptive algorithm makes proportional 
changes in gameplay difficulty when the participant’s performance deviates from an 80% accuracy 
median, which ensures that task difficulty is equated across participants and enhances participant 
engagement so that the paradigm is never too easy (or boring) nor too difficult (or frustrating). Each task 
lasts approximately 4 minutes, with 7 task runs comprising one session (experimental day). As the 

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patients improve their performance throughout gameplay, they are transported to different visual “worlds” 
in the EVO universe, meant to immerse the participant and enhance the depth of engagement and 
compliance. Audio and visual cues are continuously available to the participant so they are given 
feedback as to their performance. Since the adaptive mechanics strive to keep the participant at ~80% 
accuracy, the participant is challenged to constantly improve upon their own cognitive control 
performance in order to reach the next level.  
Using this cognitive paradigm, we have previously demonstrated that frontal theta activity is 
related to divided attention processes (Anguera et al., 2013). Importantly, because tACS can help entrain 
intrinsic neural oscillations during task performance, Preliminary Study 1 demonstrated that theta tACS 
during this cognitive paradigm improves divided attention abilities more so than control stimulation. 
Furthermore, Preliminary Study 2 has shown that a longitudinal intervention with EVO in MS patients 
improves processing speed. Together, these Preliminary Studies provide confidence that tACS will 
enhance divided attention and processing speed in MS patients through the entrainment of frontal theta 
oscillations that are inherent to EVO task performance.  
 
 
Recruitment and Retention Plan 
Recruitment. Participants will be recruited from the UCSF Center for MS and Neuroinflammation, 
a clinic that sees over 6,000 patients annually with MS and related disorders, with a track record of 
mHealth studies and trials including those led Dr. Bove. Patients will be recruited via multiple channels:  
• 
Study investigators or staff will identify prospective subjects through chart review. For prospective 
participants who have been deemed eligible, coordinator will contact their clinician for permission to 
contact in-person at their scheduled visit, or by phone at a later date. 
• 
Direct referral from affiliated clinicians -- study staff will follow up in person, on the phone, or over 
email. 
• 
The study will be listed on ClinicalTrials.gov with contact information for responsible research staffs. 
In our experience, these are generally sufficient, but if additional participants are required, 
Advertisements (flyers, brochures, radio or TV ads, posting on clinical research sites or social media, 
presentation of the study at community events/media, etc.) will be distributed. In the rare occurrence that 
these recruitment methods do not yield sufficient participation, we will contact previous patients from our 
other studies who have expressed interest in future research with us.  
 

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Retention. The proposed research requires participants to come into our lab at UCSF for 5 visits 
over 2 weeks. Our retention plan will focus on patient comfort and engagement. Physical comfort is 
achieved by placing participants in an adjustable ergonomic chair that is designed for long periods of 
seated activity. Additionally, breaks are offered as needed to get up, walk around, and use the restroom. 
Finally, water and light snacks are offered to our participants. Psychological comfort is first achieved by 
training all research personnel in how to be courteous and friendly with participants over email, phone 
and in person. Next, our research space is painted in warm and inviting colors and decorated to facilitate 
a relaxing experience. Finally, psychological comfort is achieved by clearly explaining the consent forms, 
their rights, and the tasks that the participant will be engaged in so there is no confusion or unease – and 
offering participants multiple opportunities to ask questions. Regarding engagement, participants are 
given information about the experiment that highlights the importance of this work in broader context 
without compromising the integrity of the experimental design. Next, the research paradigms are created 
to be optimally challenging, such that they are never too hard so as to be frustrating, nor are they too 
each so as to be boring. We believe that optimally challenging cognitive functions is the ideal way not 
just to keep participants engaged in the research, but will more likely yield better data. Together, our 
efforts to provide a comfortable and engaging research experience has historically served us well to 
retain participants.   
 
 
Preliminary Studies 
o 
Preliminary study 1. We have previously demonstrated (and replicated) that theta-tACS 
above PFC is able to enhance divided attention abilities in healthy young adults with a large effect size 
(d = 0.96) (Hsu et al., 2019; Hsu et al., 2017). More recently, we replicated these effects again in healthy 
older adults (aged 60 – 80 years) and further demonstrated that this improvement in attention sustains 
for at least a month following the last tACS treatment (manuscript in preparation). Moreover, the 
improvements in divided attention were correlated with increases in PFC theta activity. Although we did 
not assess processing speed, we did observe changes in response times during the divided attention 
task, suggesting processing speed may have contributed to (or co-occurred with) the improvements in 
divided attention. These studies support the notion that the proposed tACS approach is a promising for 
treatment for cognitive decline in MS – specifically divided attention and processing speed (Specific Aim 
1).  In this preliminary study, we also observed tACS effects were positively correlated with the magnitude 
of the individual MRI-based modeled electric field in the brain. This provides support for our hypothesis 
that anatomical factors affect tACS outcomes (Specific Aim 2).  

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o 
Preliminary study 2. We have recently demonstrated the utility of the proposed 
experimental paradigm (i.e. EVO) and the proposed processing speed outcome measure in people with 
MS. Specifically, in a behavioral intervention study, MS patients who played EVO improved information 
processing speed (p=0.003) (Bove et al., 2019). In a follow-up randomized controlled pilot trial, the mean 
increase in SDMT was 6.10 for EVO task group compared with 3.55 for an active control group, with 
clinically improvement significantly more likely to be retained for at least two months in the EVO group 
(Bove et al., 2019). These preliminary results provide additional support for the feasibility of using the 
proposed experimental paradigm in MS and the selection of outcome measures for Specific Aim 1. In 
this preliminary study, we also demonstrated that SDMT improvement was found to be associated with 
clinical severity, which revealed that clinical data contributes to the change of SDMT scores. This shows 
that, given the heterogeneity of MS, understanding individual variability is critical for clinical trials 
assessing cognitive function interventions in MS, and underscores the importance of Specific Aim 2 (Bove 
et al., 2019). 
 
 
Statistical Design and Power 
Power. Twenty participants in a group will correspond with >80% power (1-) at a 95% 
significance level (1-) as calculated from our preliminary studies (detailed below).  
 
Primary outcome measure: Divided attention. Results from Preliminary Study 1 showed that 
Verum (6 Hz) tACS, and not control tACS, yielded improved divided attention discrimination performance 
in healthy adults, as indexed by d-prime (F(1,35) = 6.63, p = 0.01, p2 = 0.16). Here, it is hypothesized 
that MS patients who receive Verum tACS will exhibit comparable performance gains in divided attention. 
To test this, a divided attention index will be calculated from performance during the discrimination task 
as the cost in d-prime (i.e., d-prime dual task minus d-prime single task). Data will be submitted to an 
ANCOVA with Group (Verum, Control) and Session (pre-tACS, post-tACS) as factors. Although age will 
be matched across groups, age will serve as the covariate to account for within-group differences. A 
Group x Session interaction is expected to show that the Verum tACS group, compared to the control 
group, will exhibit a larger reduction in d-prime cost post-tACS, indicating enhanced divided attention 
ability. For this interaction, 20 participants per group will yield >95% power (1-) at a 95% significance 
level (1-) with an expected effect size of f = 0.28.  
 

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Primary outcome measure: Processing speed. Results from Preliminary Study 2 showed that 
cognitive training with EVO improves processing speed, as indexed by the SDMT score (t(17) = 3.19, p 
= 0.005, d = 0.34). Here, it is hypothesized that MS patients who receive Verum tACS will exhibit 
comparable performance gains in processing speed. To test this, SDMT score will be submitted to an 
ANCOVA with Group (Verum, Control) and Session (pre-tACS, post-tACS) as factors. Although age will 
be matched across groups, age will serve as the covariate to account for within-group differences. A 
Group x Session interaction is expected to show that the Verum tACS group, compared to the control 
group, will exhibit a higher SDMT score post-tACS, indicating enhanced processing speed. For this 
interaction, 20 participants per group will yield 80% power (1-) at a 95% significance level (1-) with an 
expected effect size of f = 0.19.  
 
Secondary outcome measure: Frontal theta power. Results from Preliminary Study 1 also 
showed that the Verum tACS group, and not control tACS, exhibited a correlation between divided 
attention and frontal theta power such that those participants with the greatest increase in frontal theta 
power yielded the greatest improvement in divided attention ability (r = 0.50, p = 0.04). Here, it is 
hypothesized that MS patients who receive Verum tACS will exhibit similar neuroplastic changes in frontal 
theta activity. To test this, frontal theta power will be extracted during the discrimination task (theta dual 
task minus theta single task) and a change score will be calculated (post-tACS minus pre-tACS). A 
regression analysis will be conducted between theta power and the change in the divided attention index 
(post-tACS minus pre-tACS) described above. It is expected that increases in theta power only the Verum 
tACS group will be related to improvements in divided attention ability. To further characterize between 
group differences, theta power will be submitted to an ANCOVA with Group (Verum, Control) and Session 
(pre-tACS, post-tACS) as factors. Although age will be matched across groups, age will serve as the 
covariate to account for within-group differences. A Group x Session interaction is expected to show that 
the Verum tACS group, compared to the control group, will exhibit a larger increase in theta power post-
tACS, indicating enhanced neuroplasticity. For this interaction, 20 participants per group will yield >95% 
power (1-) at a 95% significance level (1-) with an expected effect size of f = 0.28.  
 
 
Dissemination Plan 
Registration. PI and co-PI will ensure that the clinical trial is registered and results are 
submitted to ClinicalTrials.gov as outlined in the NIH policy and according to the specific timelines 
stated in the policy. 

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Informed Consent. Informed consent documents for the clinical trial will include a specific 
statement relating to posting of clinical trial information at ClinicalTrials.gov. Importantly, it will be clear 
that privacy will be maintained. Only group averages will be reported in scientific communications. 
Where individual data are reported (e.g., showing example representations of brain activation), 
individuals are not identified. 
 
Compliance. UCSF internal policy will ensure that clinical trials are registered and results 
reporting occur in compliance with policy requirements.  
 
 
Protection for Human Subjects 
Risks To The Participants. 
a. Human Participants Involvement and Characteristics: In this proposal, we will recruit people 
with MS. General inclusion criteria for all participants are: age 18-65, diagnosis of MS (relapsing or 
progressive) according to McDonald criteria, Expanded Disability Status Scale (EDSS)≦6.5, no 
paresis of the upper limbs, a minimum of 3 months since the last relapse, no severe depression (Beck 
Depression Inventory<19), normal hearing, and no changes in MS or symptomatic medications in past 
2 months. Exclusion: prior brain surgery, clips in brain, epilepsy or other neurological or non-affective 
psychiatric disorders, pregnancy. Because of the difficulties in interpreting cognitive studies in 
participants with English as a second language, only native-English speakers will be asked to 
participate in the study. Participants will be selected in an unbiased fashion with regard to sex and 
race. Gender and minority representation issues do not interact with any of our hypotheses. Therefore, 
the participants that we recruit will be representative of previous populations studied at University of 
California, San Francisco and will be represented in the approximate proportions that we have listed. 
Every effort will be made to ensure that the participant population conforms to the NIH policy on 
Gender and Minority Inclusion in Research Study populations.  
b. Sources of Materials: Behavioral and EEG data will be collected from each individual. Information 
obtained from the studies in the research plan will be strictly confidential, except as required by law, 
but will be made available to the participant in response to a specific request from the participant. All 
data will be identified only by a code number. There will be only one “key” linking a participant’s name 
and personal information with their code number. This key, and all participant information and data, is 
maintained in files in locked cabinets in locked lab space or password protected computer files. Only 

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the Principal Investigator and research staff has access to these files. Typically, only group averages 
are reported in scientific communications. Where individual data are reported (e.g., showing example 
representations of brain activation), individuals are not identified. 
c. Potential Risks: 
 Electroencephalography: There are no known risks associated with EEG procedures, all of 
which have been used extensively in previous research. Conventional EEG recording and sensory 
stimulation techniques with standard subject grounding procedures are always employed. Some 
electrode paste may remain on the scalp, but it can be easily removed with shampooing. 
 Transcranial alternating current stimulation: Although uncommon, tACS has some risk for 
headache, dizziness, nausea, itchy sensation, irritation under the area of the electrodes and the 
sensation of shock. TACS has also been reported to cause brief flashes of light ("phosphenes") in 
humans, but these are not discomforting. Should an adverse effect occur in a participant, that 
participant will be excluded from continuing the intervention. The protocol described here uses 
stimulation levels that fall well within safety limits established by basic research investigating neural 
tissue damage and other possible physiological effects in both humans and animals. Overall, tACS is 
generally considered a safe, noninvasive and painless technique for modulating neural excitability. 
 
Adequacy Of Protection Against Risks. 
a. Recruitment and Informed Consent: Participants will be recruited from the UCSF Center for MS 
and Neuroinflammation, a clinic that sees over 6,000 patients annually with MS and related disorders. 
All participants will participate in the informed consent process. They will be familiarized with the 
protocol by the experimenter, including risks and benefits, and informed consent will be documented 
according to the regulations governing human beings as experimental participants at the University of 
California, San Francisco. 
 
b. Protection Against Risks: All participants will be under close supervision throughout the 
experiments. All tACS, and EEG recordings are done with state of the art technology. Equipment is 
routinely screened to assure all components, cables etc are in perfect working condition and standard 
grounding techniques are always employed. All information collected from the proposed experiments 
will remain strictly confidential, except as required by law, and will be made available to the participant 
and his/her physician upon the participant’s request. Personal identification of a subject will be 
excluded from all scientific communications. TACS studies are closely monitored for subject comfort 
and tACS will be discontinued if stimulation ever feels painful. Low intensity tACS (2mA peak-to-peak 

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or less) will be used in the proposed studies, and research utilizing similar stimulation parameters as 
proposed here have reported no adverse mental or health effects lasting longer than the testing 
session in normal healthy subjects. Much care will be taken to ensure that stimulation parameters are 
within the range of published safety guidelines. Although no cases of seizures have been reported 
using tACS with the proposed stimulation parameters, participants will be screened for past 
occurrence of seizure and a family history of epilepsy as part of the inclusion/exclusion process. 
Participants will be fully informed of all procedures and the known and potential risks associated with 
tACS. Trained personnel will be present during all experimental procedures and all research staff are 
required to maintain current CPR certification. Drs. Bove (PI), Zanto (co-PI), Hsu (co-investigator) and 
Gazzaley (co-investigator) will distinguish between a serious adverse event from a non-serious 
adverse event and an unanticipated problem. In response to an adverse event, Dr. Bove, a board-
certified neurologist at the UCSF Multiple Sclerosis Center, will monitor participants until they are either 
deemed fit to go home or are directed to the UCSF Medical Center for additional care. In over 33,000 
sessions with over 1,000 participants using stimulation similar to the proposed protocol, here is no 
evidence for irreversible injury produced by transcranial electrical stimulation (tES) protocols within a 
wide range of stimulation parameters (≤40 min, ≤4 mA). This includes a wide variety of participants, 
including persons from potentially vulnerable populations. The analysis consolidates and adds to 
existing evidence on tES safety and facilitates further research of tES in human subjects (Bikson et 
al., 2016). A more recent review article suggested that safety is established for low-intensity 
conventional tES defined as <4mA, up to 60 min duration per day. Using tACS stimulation, fewer 
adverse effects were reported compared to tDCS. In specific paradigms with amplitudes of up to 10 
mA, frequencies in the kHz range appear to be safe (Antal et al., 2017). 
 
Potential Benefits Of The Proposed Research To The Participants And Others. 
Participants may gain some insight into the scientific process and human cognition and, in addition, 
they may benefit psychologically from knowing that they are participating in important research. 
Participants may also experience slightly improved cognitive control abilities following tACS. The 
potential benefits anticipated in improved treatment and management of MS patients with cognitive 
decline are expected to far outweigh the minimal risks associated with these studies. 
 
 
 
 

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REFERENCES 
 
Achiron, A., & Barak, Y. (2003). Cognitive impairment in probable multiple sclerosis. J Neurol Neurosurg 
Psychiatry, 74(4), 443-446. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12640060 
Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., . . . Gazzaley, A. 
(2013). Video game training enhances cognitive control in older adults. Nature, 501(7465), 97-
101. doi:10.1038/nature12486 
Anguera, J. A., Brandes-Aitken, A. N., Antovich, A. D., Rolle, C. E., Desai, S. S., & Marco, E. J. (2017). 
A pilot study to determine the feasibility of enhancing cognitive abilities in children with sensory 
processing dysfunction. PLoS One, 12(4), e0172616. doi:10.1371/journal.pone.0172616 
Anguera, J. A., Jordan, J. T., Castaneda, D., Gazzaley, A., & Arean, P. A. (2016). Conducting a fully 
mobile and randomised clinical trial for depression: access, engagement and expense. BMJ Innov, 
2(1), 14-21. doi:10.1136/bmjinnov-2015-000098 
Antal, A., Alekseichuk, I., Bikson, M., Brockmöller, J., Brunoni, A. R., Chen, R., . . .  Paulus, W. (2017). 
Low Intensity transcranial electric stimulation: Safety, ethical, legal regulatory and application 
guidelines. Clin Neurophysiol, 128 (9), 1774-1809 
Antal, A., Boros, K., Poreisz, C., Chaieb, L., Terney, D., & Paulus, W. (2008). Comparatively weak after-
effects of transcranial alternating current stimulation (tACS) on cortical excitability in humans. 
Brain Stimul, 1(2), 97-105. doi:10.1016/j.brs.2007.10.001 
Arean, P. A., Hallgren, K. A., Jordan, J. T., Gazzaley, A., Atkins, D. C., Heagerty, P. J., & Anguera, J. A. 
(2016). The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote 
Clinical Trial. J Med Internet Res, 18(12), e330. doi:10.2196/jmir.6482 
Ayache, S. S., Palm, U., Chalah, M. A., Al-Ani, T., Brignol, A., Abdellaoui, M., . . . Lefaucheur, J. P. (2016). 
Prefrontal tDCS Decreases Pain in Patients with Multiple Sclerosis. Front Neurosci, 10, 147. 
doi:10.3389/fnins.2016.00147 
Bikson, M., Grossman, P., Thomas, C., Zannou, A. L., Jiang,  J., Adnan, T., . . .Woods, A. J. (2016) 
Safety of Transcranial Direct Current Stimulation: Evidence Based Update 2016. Brain Stimul. 
doi:10.1016/j.brs.2016.06.004. 
Birnbaum, G. (2010). Current and future treatments for relapsing-remitting multiple sclerosis. Curr Opin 
Drug 
Discov 
Devel, 
13(2), 
214-225. 
Retrieved 
from 
http://www.ncbi.nlm.nih.gov/pubmed/20205055 
Bove, R., Rowles, W., Zhao, C., Anderson, A., Friedman, S., D., L., . . . Anguera, J. (2019). A novel 
home-based digital treatment to improve processing speed in people with multiple sclerosis: a 
pilot study. Paper presented at the ECTRIMS, Stockholm, Sweden.  
Bove, R., Rush, G., Zhao, C., Rowles, W., Garcha, P., Morrissey, J., . . . Anguera, J. (2019). A 
Videogame-Based Digital Therapeutic to Improve Processing Speed in People with Multiple 
Sclerosis: A Feasibility Study. Neurol Ther, 8(1), 135-145. doi:10.1007/s40120-018-0121-0 
Caramia, M. D., Palmieri, M. G., Desiato, M. T., Boffa, L., Galizia, P., Rossini, P. M., . . . Bernardi, G. 
(2004). Brain excitability changes in the relapsing and remitting phases of multiple sclerosis: a 
study 
with 
transcranial 
magnetic 
stimulation. 
Clin 
Neurophysiol, 
115(4), 
956-965. 
doi:10.1016/j.clinph.2003.11.024 
Castillo Saavedra, L., Morales-Quezada, L., Doruk, D., Rozinsky, J., Coutinho, L., Faria, P., . . . Fregni, 
F. (2014). QEEG indexed frontal connectivity effects of transcranial pulsed current stimulation 
(tPCS): 
A 
sham-controlled 
mechanistic 
trial. 
Neurosci 
Lett, 
577, 
61-65. 
doi:10.1016/j.neulet.2014.06.021 
Chiaravalloti, N. D., & DeLuca, J. (2008). Cognitive impairment in multiple sclerosis. Lancet Neurol, 7(12), 
1139-1151. doi:10.1016/S1474-4422(08)70259-X 

PI: Riley Bove, MD. 
  Confidential 
 
Version #: 1.0 
Version Date: 10/1/2020  
Page 19 of 21
 
 
Datta, A., Truong, D., Minhas, P., Parra, L. C., & Bikson, M. (2012). Inter-Individual Variation during 
Transcranial Direct Current Stimulation and Normalization of Dose Using MRI-Derived 
Computational Models. Front Psychiatry, 3, 91. doi:10.3389/fpsyt.2012.00091 
Daut, R. L., Cleeland, C. S., & Flanery, R. C. (1983). Development of the Wisconsin Brief Pain 
Questionnaire to assess pain in cancer and other diseases. Pain, 17(2), 197-210. Retrieved from 
http://www.ncbi.nlm.nih.gov/pubmed/6646795 
Davis, N. O., Bower, J., & Kollins, S. H. (2018). Proof-of-concept study of an at-home, engaging, digital 
intervention for pediatric ADHD. PLoS One, 13(1), e0189749. doi:10.1371/journal.pone.0189749 
Ferrucci, R., Vergari, M., Cogiamanian, F., Bocci, T., Ciocca, M., Tomasini, E., . . . Priori, A. (2014). 
Transcranial direct current stimulation (tDCS) for fatigue in multiple sclerosis. NeuroRehabilitation, 
34(1), 121-127. doi:10.3233/NRE-131019 
Fisk, J. D., Ritvo, P. G., Ross, L., Haase, D. A., Marrie, T. J., & Schlech, W. F. (1994). Measuring the 
functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis, 18 Suppl 
1, S79-83. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8148458 
Geisler, M. W., Sliwinski, M., Coyle, P. K., Masur, D. M., Doscher, C., & Krupp, L. B. (1996). The effects 
of amantadine and pemoline on cognitive functioning in multiple sclerosis. Arch Neurol, 53(2), 
185-188. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8639070 
Gevins, A., Smith, M. E., McEvoy, L., & Yu, D. (1997). High-resolution EEG mapping of cortical activation 
related to working memory: effects of task difficulty, type of processing, and practice. Cereb 
Cortex, 7(4), 374-385. doi:10.1093/cercor/7.4.374 
Hanken, K., Bosse, M., Mohrke, K., Eling, P., Kastrup, A., Antal, A., & Hildebrandt, H. (2016). 
Counteracting Fatigue in Multiple Sclerosis with Right Parietal Anodal Transcranial Direct Current 
Stimulation. Front Neurol, 7, 154. doi:10.3389/fneur.2016.00154 
Hsu, W. Y., Ku, Y., Zanto, T. P., & Gazzaley, A. (2015). Effects of noninvasive brain stimulation on 
cognitive function in healthy aging and Alzheimer's disease: a systematic review and meta-
analysis. Neurobiol Aging, 36(8), 2348-2359. doi:10.1016/j.neurobiolaging.2015.04.016 
Hsu, W. Y., Zanto, T. P., & Gazzaley, A. (2019). Parametric effects of transcranial alternating current 
stimulation 
on 
multitasking 
performance. 
Brain 
Stimul, 
12(1), 
73-83. 
doi:10.1016/j.brs.2018.10.010 
Hsu, W. Y., Zanto, T. P., van Schouwenburg, M. R., & Gazzaley, A. (2017). Enhancement of multitasking 
performance and neural oscillations by transcranial alternating current stimulation. PLoS One, 
12(5), e0178579. doi:10.1371/journal.pone.0178579 
Huang, Y., Datta, A., Bikson, M., & Parra, L. C. (2019). Realistic volumetric-approach to simulate 
transcranial electric stimulation-ROAST-a fully automated open-source pipeline. J Neural Eng, 
16(5), 056006. doi:10.1088/1741-2552/ab208d 
Iodice, R., Carotenuto, A., Dubbioso, R., Cerillo, I., Santoro, L., & Manganelli, F. (2016). Multimodal 
evoked potentials follow up in multiple sclerosis patients under fingolimod therapy. J Neurol Sci, 
365, 143-146. doi:10.1016/j.jns.2016.04.026 
Jamil, A., Batsikadze, G., Kuo, H. I., Labruna, L., Hasan, A., Paulus, W., & Nitsche, M. A. (2017). 
Systematic evaluation of the impact of stimulation intensity on neuroplastic after-effects induced 
by transcranial direct current stimulation. J Physiol, 595(4), 1273-1288. doi:10.1113/JP272738 
Joundi, R. A., Jenkinson, N., Brittain, J. S., Aziz, T. Z., & Brown, P. (2012). Driving oscillatory activity in 
the 
human 
cortex 
enhances 
motor 
performance. 
Curr 
Biol, 
22(5), 
403-407. 
doi:10.1016/j.cub.2012.01.024 
Kiiski, H., Reilly, R. B., Lonergan, R., Kelly, S., O'Brien, M. C., Kinsella, K., . . . Whelan, R. (2012). Only 
low frequency event-related EEG activity is compromised in multiple sclerosis: insights from an 
independent 
component 
clustering 
analysis. 
PLoS 
One, 
7(9), 
e45536. 
doi:10.1371/journal.pone.0045536 

PI: Riley Bove, MD. 
  Confidential 
 
Version #: 1.0 
Version Date: 10/1/2020  
Page 20 of 21
 
 
Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a 
review and analysis. Brain Res Brain Res Rev, 29(2-3), 169-195. Retrieved from 
http://www.ncbi.nlm.nih.gov/pubmed/10209231 
Kos, D., Kerckhofs, E., Carrea, I., Verza, R., Ramos, M., & Jansa, J. (2005). Evaluation of the Modified 
Fatigue Impact Scale in four different European countries. Mult Scler, 11(1), 76-80. 
doi:10.1191/1352458505ms1117oa 
Lopez-Diego, R. S., & Weiner, H. L. (2008). Novel therapeutic strategies for multiple sclerosis--a 
multifaceted adversary. Nat Rev Drug Discov, 7(11), 909-925. doi:10.1038/nrd2358 
Lovera, J. F., Frohman, E., Brown, T. R., Bandari, D., Nguyen, L., Yadav, V., . . . Bourdette, D. (2010). 
Memantine for cognitive impairment in multiple sclerosis: a randomized placebo-controlled trial. 
Mult Scler, 16(6), 715-723. doi:10.1177/1352458510367662 
Mattioli, F., Bellomi, F., Stampatori, C., Capra, R., & Miniussi, C. (2016). Neuroenhancement through 
cognitive training and anodal tDCS in multiple sclerosis. Mult Scler, 22(2), 222-230. 
doi:10.1177/1352458515587597 
Meiron, O., & Lavidor, M. (2014). Prefrontal oscillatory stimulation modulates access to cognitive control 
references in retrospective metacognitive commentary. Clin Neurophysiol, 125(1), 77-82. 
doi:10.1016/j.clinph.2013.06.013 
Mizuhara, H., Wang, L. Q., Kobayashi, K., & Yamaguchi, Y. (2004). A long-range cortical network 
emerging with theta oscillation in a mental task. Neuroreport, 15(8), 1233-1238. Retrieved from 
http://www.ncbi.nlm.nih.gov/pubmed/15167540 
Mori, F., Codeca, C., Kusayanagi, H., Monteleone, F., Buttari, F., Fiore, S., . . . Centonze, D. (2010). 
Effects of anodal transcranial direct current stimulation on chronic neuropathic pain in patients 
with multiple sclerosis. J Pain, 11(5), 436-442. doi:10.1016/j.jpain.2009.08.011 
Mori, F., Nicoletti, C. G., Kusayanagi, H., Foti, C., Restivo, D. A., Marciani, M. G., & Centonze, D. (2013). 
Transcranial direct current stimulation ameliorates tactile sensory deficit in multiple sclerosis. 
Brain Stimul, 6(4), 654-659. doi:10.1016/j.brs.2012.10.003 
Noseworthy, J. H., Vandervoot, M. K., Wong, C. J., & Ebers, G. C. (1990) Interrater variability with the 
Expanded Disability Status Scale (EDSS) and Functional Systems (FS) in a multiple sclerosis 
clinical trial. Neurology, 40, 971–975. 
Opitz, A., Paulus, W., Will, S., Antunes, A., & Thielscher, A. (2015). Determinants of the electric field 
during 
transcranial 
direct 
current 
stimulation. 
Neuroimage, 
109, 
140-150. 
doi:10.1016/j.neuroimage.2015.01.033 
Pahor, A., & Jausovec, N. (2014). The effects of theta transcranial alternating current stimulation (tACS) 
on fluid intelligence. Int J Psychophysiol, 93(3), 322-331. doi:10.1016/j.ijpsycho.2014.06.015 
Paulus, W. (2010). On the difficulties of separating retinal from cortical origins of phosphenes when using 
transcranial alternating current stimulation (tACS). Clin Neurophysiol, 121(7), 987-991. 
doi:10.1016/j.clinph.2010.01.029 
Polania, R., Nitsche, M. A., Korman, C., Batsikadze, G., & Paulus, W. (2012). The importance of timing 
in segregated theta phase-coupling for cognitive performance. Curr Biol, 22(14), 1314-1318. 
doi:10.1016/j.cub.2012.05.021 
Polman, C.H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M.,…  Wolinsky, J. S. (2011) 
Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol, 
69(2): p. 292-302. 
Rogers, J. M., & Panegyres, P. K. (2007). Cognitive impairment in multiple sclerosis: evidence-based 
analysis and recommendations. J Clin Neurosci, 14(10), 919-927. doi:10.1016/j.jocn.2007.02.006 
Rosti, E., Hamalainen, P., Koivisto, K., & Hokkanen, L. (2006). The PASAT performance among patients 
with multiple sclerosis: analyses of responding patterns using different scoring methods. Mult 
Scler, 12(5), 586-593. doi:10.1177/1352458506070624 

PI: Riley Bove, MD. 
  Confidential 
 
Version #: 1.0 
Version Date: 10/1/2020  
Page 21 of 21
 
 
Russell, M. J., Goodman, T., Pierson, R., Shepherd, S., Wang, Q., Groshong, B., & Wiley, D. F. (2013). 
Individual differences in transcranial electrical stimulation current density. J Biomed Res, 27(6), 
495-508. doi:10.7555/JBR.27.20130074 
Santarnecchi, E., Polizzotto, N. R., Godone, M., Giovannelli, F., Feurra, M., Matzen, L., . . . Rossi, S. 
(2013). Frequency-dependent enhancement of fluid intelligence induced by transcranial 
oscillatory potentials. Curr Biol, 23(15), 1449-1453. doi:10.1016/j.cub.2013.06.022 
Schutter, D. J., & Hortensius, R. (2010). Retinal origin of phosphenes to transcranial alternating current 
stimulation. Clin Neurophysiol, 121(7), 1080-1084. doi:10.1016/j.clinph.2009.10.038 
Shahid, S., Wen, P., & Ahfock, T. (2013). Numerical investigation of white matter anisotropic conductivity 
in defining current distribution under tDCS. Comput Methods Programs Biomed, 109(1), 48-64. 
doi:10.1016/j.cmpb.2012.09.001 
Shaygannejad, V., Janghorbani, M., Ashtari, F., Zanjani, H. A., & Zakizade, N. (2008). Effects of 
rivastigmine on memory and cognition in multiple sclerosis. Can J Neurol Sci, 35(4), 476-481. 
Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18973065 
Tombaugh, T. N. (2006). A comprehensive review of the Paced Auditory Serial Addition Test (PASAT). 
Arch Clin Neuropsychol, 21(1), 53-76. doi:10.1016/j.acn.2005.07.006 
Truong, D. Q., Magerowski, G., Blackburn, G. L., Bikson, M., & Alonso-Alonso, M. (2013). Computational 
modeling of transcranial direct current stimulation (tDCS) in obesity: Impact of head fat and dose 
guidelines. Neuroimage Clin, 2, 759-766. doi:10.1016/j.nicl.2013.05.011 
Van der Meer, M. L., Tewarie, P., Schoonheim, M. M., Douw, L., Barkhof, F., Polman, C. H., . . . Hillebrand, 
A. (2013). Cognition in MS correlates with resting-state oscillatory brain activity: An explorative 
MEG source-space study. Neuroimage Clin, 2, 727-734. doi:10.1016/j.nicl.2013.05.003 
Van Schependom, J., D'Hooghe M, B., Cleynhens, K., D'Hooge, M., Haelewyck, M. C., De Keyser, J., & 
Nagels, G. (2014). The Symbol Digit Modalities Test as sentinel test for cognitive impairment in 
multiple sclerosis. Eur J Neurol, 21(9), 1219-1225, e1271-1212. doi:10.1111/ene.12463 
Vosskuhl, J., Huster, R. J., & Herrmann, C. S. (2015). Increase in short-term memory capacity induced 
by down-regulating individual theta frequency via transcranial alternating current stimulation. 
Front Hum Neurosci, 9, 257. doi:10.3389/fnhum.2015.00257