Improving Neurocognitive Deficits and Function in Schizophrenia With Transcranial Magnetic Stimulation
Phase: NA
Conditions: Schizophrenia, Schizoaffective Disorder
Sponsor: VA Office of Research and Development

 
 
Improving Neurocognitive Deficits and Function in 
Schizophrenia With Transcranial Magnetic Stimulation 
 
 
June 18th, 2018 
 
NCT03037983 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
Background and Significance 
 
General Background. Schizophrenia confers significant disability and morbidity to the affected individual and 
substantial financial burden to society [1].  While schizophrenia has a significant impact on the overall Veteran 
population, its impact is particularly acute for Veterans of recent conflicts. Among Veterans of wars in the Middle 
East treated within VA health care facilities within a recent 4-year period, the prevalence of schizophrenia has 
been estimated to be 2% [2], a rate considerably higher than that found in non-Veteran populations in the U.S. 
and worldwide [3]. The significant impact of schizophrenia on Veterans’ welfare is perhaps best illustrated by a 
recent study that identified schizophrenia, along with major depression, as conferring significant risk for 
homelessness [4].   It is now recognized that cognitive deficits are a major source of disability in schizophrenia 
[5]. Cognitive deficits are enduring, essentially treatment refractory, and largely responsible for the difficulty that 
the vast majority of individuals with this condition experience in maintaining meaningful employment or living 
independently. Psychosis, in contrast, although impairing in its own right, often responds to treatment and has 
been shown to have less impact on long-term functionality [6]. These features of cognitive deficits suggest that 
developing new and effective treatments for cognitive deficits will have significant impact on the health and well 
being of Veterans.    
 
Repetitive transcranial magnetic stimulation (rTMS) May be Beneficial for Cognitive Deficits. rTMS is a non-
invasive procedure, in which the administration of a transient magnetic field induces electrical currents in specific, 
targeted brain regions. rTMS is FDA approved for the treatment of depression and is being investigated in the 
treatment of a wide variety of neuropsychiatric conditions, including PTSD, OCD, bipolar disorder and 
Alzheimer’s Disease. For schizophrenia, rTMS represents one of the most promising treatments for cognitive 
deficits. Not only is there evidence that rTMS can improve cognition among non-patient samples, as 
demonstrated by a recent meta-analysis [7]; several studies have also reported improvements in cognition in 
schizophrenia following rTMS to the prefrontal cortex [8]. This includes a recent randomized control study 
showing fairly strong improvement in working memory (WM) performance following bilateral dorsolateral 
prefrontal cortex (DLPFC) rTMS (Cohen’s d = .92 when comparing rTMS treated vs. sham groups) [9].   
 
Proposed Research will Address Gaps in the Literature. The application of rTMS for cognitive deficits in 
schizophrenia is in its infancy and we currently do not have any information on the effectiveness of rTMS for U.S. 
Veterans with schizophrenia.  This population possesses unique characteristics and challenges for the 
application of new treatments such as rTMS.  Therefore, the primary objective of this study is to obtain pilot data 
supporting the efficacy of rTMS to remediate cognitive deficits in schizophrenia among Veterans. This data will 
be necessary to implement future effectiveness trials with larger samples sizes that will be needed to establish 
rTMS as a viable treatment modality for Veterans.   
 
Impairments in Gamma Oscillations Hypothesized to Underlie Cognitive Deficits in Schizophrenia. A secondary 
goal of this study is to advance our understanding of the neural mechanism of cognitive deficits.  Toward this 
goal, we will test the gamma oscillation hypothesis of cognitive deficits in schizophrenia.  Gamma oscillations 
are high frequency (30-80 Hz) oscillations resulting from the synchronization of activity among neuronal 
populations during cognition and information processing [14, 15].  While the precise mechanisms for cognitive 
deficits in schizophrenia are likely complex, involving multiple systems and processes [10], several lines of 
evidence converge on the centrality of impaired gamma oscillations in this condition [11-13]. This evidence 
includes findings pointing to a reduction in GABAergic signaling in schizophrenia.  GABA is the major inhibitory 
neurotransmitter in the brain and GABA signaling is thought to be critical for the synchronization of firing among 
populations of pyramidal neurons. One of the most important physiological consequences of deficits in GABA 
signaling and synchronization of neuronal activity in schizophrenia is the inability to generate oscillations in the 
gamma range during cognition [11]. Our group and others have reported consistent evidence that gamma 
oscillations are disturbed in schizophrenia [16-20] during a range of PFC-dependent higher-order cognitive 
processes, including WM. We will test our hypothesis by determining whether rTMS induces changes in the level 

of cognition-evoked gamma oscillations measured by electroencephalography (EEG), and whether these 
changes are associated with improvements in cognitive performance. 
 
Gamma Oscillation as a Potential Marker of rTMS Effects on the DLPFC. A better understanding of neural 
mechanisms holds the potential to yield clinically useful biomarkers predictive of rTMS treatment response. The 
availability of predictors would be useful because psychiatric treatments typically are ineffective for a substantial 
proportion of subjects and predictors would promote the judicious use of treatments so that only those individuals 
most likely to benefit are exposed to the risks and costs of treatment.. The emerging literature on rTMS suggests 
that this treatment modality also suffer from this limitation.  In the study by Barr et al., a substantial proportion of 
subjects did not benefit from TMS. In fact, a close examination of their data indicates that ~31.5% of subjects 
experienced lower performance post treatment compared to pre treatment.  Although rTMS is generally 
considered safe, it, nonetheless, is a procedure that alters function of the targeted brain tissue. Thus, an 
additional goal of this proposal is to obtain preliminary support for pretreatment (baseline) gamma activity as a 
predictor of rTMS remediation of cognitive deficits in schizophrenia. We will evaluate the potential utility of 
gamma oscillations as a response predictor by testing whether baseline levels of gamma is associated post-
treatment improvements in cognitive performance.  
 
Innovation.  The proposal represents an innovative approach to new treatment development for cognitive deficits 
associated with schizophrenia.  We are not aware of any studies that have applied rTMS to Veterans for this 
purpose. The use of EEG frequency analysis to gauge the neurophysiologic effects of rTMS represents a novel 
combination of sophisticated methods. This combination also represents a mechanism-based approach to 
treatment development.   Moreover, this approach promises to yield early indications for clinically relevant 
predictive information. We are not aware any studies that have examined potential predictors of rTMS efficacy 
to remediate cognitive deficits in schizophrenia.  With the successful completion of this project, there is the 
potential translate our findings towards personalized treatment for Veterans suffering from cognitive deficits in 
schizophrenia.  
 
Preliminary Studies 
 
Evidence of the ability to study Veterans with schizophrenia. The PI of the grant has applied his extensive 
experience in conducting schizophrenia studies to establish the necessary clinical research infrastructure to 
enroll research subjects with this condition at the VA Palo Alto Health Care System. Within a recent six-month 
period, his research group has enrolled 15 subjects with schizophrenia for a pilot cognitive neuroscience at 
the VAPAHCS, which translates into a recruitment rate of 30 subjects/year. 
 
Experience conducting studies with rTMS 
enhancing cognitive performance.  The PI 
and a Co-Investigator (MM) have recently 
completed a study investigating the effects of 
rTMS on cognition. Although the primary 
goals of this study differ from this proposal, it 
nonetheless demonstrates the investigators’ 
experience in administering rTMS to improve 
cognition, and to safely and effectively 
complete rTMS studies. A total of 27 subjects 
completed this prior experiment, which 
experienced no adverse outcomes and no subjects dropping out. Figure 1 displays the results of one arm of 
this study and shows rTMS was associated with speeding of responses with preserved accuracy, during a 
cognitive control task. A manuscript summarizing these results is currently undergoing peer-review.  The 
growing experience of the PI with rTMS will be further supported by Dr. Yesavage and Dr. George, who each 
have extensive track records in using rTMS with diverse neuropsychiatric populations.   
 
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Baseline
Post rTMS
RT (msec)
Figure 1. Group mean 
performance on a working 
memory task (RT – reaction 
time) in 14 healthy subjects 
in response to rTMS to right 
DLPFC, vs no-stim; effect of 
rTMS on RT p < 0.05 
(paired t test). 

Measuring cognition associated gamma oscillations. The investigators of this study have extensive experience 
conducting the sophisticated analytic methods necessary to quantify cognition associated gamma oscillations. 
To illustrate this point, we present the following two sets of preliminary data.  First, the PI and one of the Co-Is 
of this grant, MM, were among the first investigators to report cognition-associated deficits in gamma oscillations 
in schizophrenia, Fig. 2 [16].  
 
Second, we conducted a pilot study to demonstrate our ability to measure gamma oscillations during the 
execution of the proposed WM task. Individuals with schizophrenia (n=5) and demographically matched healthy 
control cohort (n=5) completed the WM task (Fig. 4) while undergoing EEG recording. Figure 3 shows the EEG 
time-frequency spectrograms within the gamma range (30-80 Hz) using the proposed processing and analytic 
procedures. Although we will not be studying control subjects in this proposal, the results from control subjects 
from the pilot study are shown to illustrate the elicitation of gamma oscillations by the proposed WM task, 
particularly during the delay period. In contrast, there is relatively little gamma activity found in the schizophrenia 
sample. This deficit is further illustrated by the contrast between groups.  Patients responsive to rTMS are 
predicted to show increased gamma activity, resembling the control subjects’ results. 
 
 
 
Research Design and Methods 
 
Overview of General Design  
 
We will utilize a randomized, double-blind, parallel-groups design.  After clinical assessment to confirm diagnosis 
of schizophrenia (SZ) or schizoaffective disorder (SAD), subjects will be randomized (by computer algorithm) to 
either the active or sham arms.  During the pre-treatment phase, subjects will be tested on the WM task while 
undergoing EEG to determine baseline cognitive performance and gamma levels.  They will then receive rTMS 
or sham in the 4-week treatment phase, at the end of which subjects will be tested again on the WM task with 
EEG.  
 
Subjects 
Table 1.  Experimental Design 
 
Phase 
Clinical Assessment Baseline 
Randomization 
Treatment 
Post-treatment 
 
Week 1  
End of Week 1 
Wk 2 → Wk 6 
Wk 7  
Telephone Screen 
WM Task 
 
rTMS 
WM Task 
Figure 2. Scalp topography of control-related 
gamma oscillation power de cits in schizophre-
nia group compared to a healthy comparison 
group during the delay period of cognitive 
control task.  Right frontal EEG leads show the 
most prominent de cits in schizophrenia.  Left 
and right panels show superior and right lateral 
views respectively. From Minzenberg et al. [17].

Office Evaluations 
(SCID) 
EEG 
Functional 
Status 
[rTMS, Sham] 
Sham 
EEG 
Functional Status 
A total of 24 subjects (12 rTMS and 12 sham) with SZ or SAD between the ages of 18 and 55 will be studied. 
Veterans will be recruited from a variety of sources including VAPHCS mental health clinics. We will consult with 
our system’s Office of Data Analytics to identify potential subjects. We have already identified 366 veterans 
within the VAPAHCS population meeting the inclusion/exclusion criteria. We will work with this office to identify 
these veterans’ VA clinicians who will assist in recruitment efforts. The study will be open to both men and 
women, regardless of race and ethnic origin.  Details of demographics of the local VA population can be found 
in pg. 1 of the Human Subjects section.  
 
Initial Telephone Interview.  Respondents will be given a brief description of study procedures and research 
goals.  If interested, subjects will be interviewed by telephone regarding their current symptoms, psychiatric and 
medical histories to determine if we should proceed to an in-person clinical assessment.   
 
In-person assessment. Inclusion and exclusion criteria, outlined in Table 2, will be reviewed in person. For those 
meeting these criteria, a doctoral level clinician trained to administer the Structured Clinical Interview for DSM-
IV Axis I Disorders (SCID) will conduct interviews to confirm diagnosis of schizophrenia or schizoaffective 
disorder.  Subjects with history of other Axis I conditions will not be excluded. However, other Axis I conditions 
have to be either in remission or symptomatic control within at least a 3 month period preceding study entry.  
Symptoms will be quantified with the Brief Psychiatric Rating Scale (BPRS) [22], Scales for the Assessment of 
Negative Symptoms (SANS) [23]  and Scales for the Assessment of Positive Symptoms (SAPS) [24]. Sub-scores 
from the BPRS, SANS, and SAPS will be used to derive an index of disorganization [25].  These symptoms will 
allow for exploratory analyses to determine whether rTMS improves symptoms other than cognitive deficits.   
 
Discussion of Inclusion/Exclusion Issues. Most antipsychotics and antidepressants are thought to lower seizure 
threshold [21] and this may prompt questions on the safety of administering rTMS to individuals taking these 
medications.  The best available evidence suggests that these agents likely do not significantly increase the risk 
of rTMS induced seizures.  A review of the effects of various psychoactive agents, including antidepressants and 
antipsychotics [26], revealed that these agents in general do not affect motor threshold, which can be taken as 
a proxy measure for an agent’s effect on cortical excitability, and hence a mediator of seizure potential. A recent 
review of TMS administered to individuals with schizophrenia in the context of on going antipsychotic treatment 
concluded that TMS is safe to administer in this population [27]. However, due to the particularly higher seizure 
risks associated with a few psychotropic agents [21], we will exclude subjects taking these agents. A recent 
review of TMS for the treatment of PTSD concluded that this treatment is well tolerated [28], suggesting that 
Table 2. Inclusion and Exclusion Criteria 
Exclusion Criteria 
Inclusion Criteria 
1) Pregnant or lactating female  
1) Age 18-55 years 
2) History of prior adverse reaction to TMS  
2) SCID confirmed diagnosis of SZ or SAD 
3) On medications known to significantly lower seizure 
threshold, e.g. clozapine, chlorpromazine, buproprion, 
clomipramine [21]  
3) Stable medication regimen (no change in dose or 
agents within the 4 weeks prior to study entry and 
throughout the duration of the study) 
4) History of seizures or conditions known to substantially 
increase risk for seizures 
4) Stable social environment and housing to enable 
regular attendance at clinic visits  
7) Implants or medical devices incompatible with TMS  
5) Ability to undergo cognitive testing, EEG scans 
and rTMS 
8) Acute or unstable chronic illness that would affect 
participation or compliance with study procedures, e.g. 
unstable angina 
6) IQ > 80 (WASI full scale score) 
9) Substance abuse/dependence (not including caffeine or 
nicotine) with in one-month period prior to study entry or 
during study participation 
7) In general good medical health 
10) Unstable psychiatric symptoms that precludes consistent 
participation in the study, e.g. active current suicidal intent or 
plan; severe psychosis 

PTSD or history of psychological trauma does not likely represent increased risk for adverse events. Therefore, 
history of trauma will not be an exclusionary factor. 
 
Cognitive Task:  We will administer a visual delayed response WM paradigm as a measure of cognitive function 
(see Fig. 4). We and others have previously published studies using similar WM paradigms [29] that have 
revealed robust performance deficits in schizophrenia compared to healthy control subjects with p values ranging 
between .001-.002 and effect sizes ~ 1.1. This task will be administered at baseline and post treatment to quantify 
changes in cognition resulting from rTMS. 
Subjects will be presented with cue stimuli, and 
after a  delay, a probe stimulus will be presented. 
At this point the subject is to determine if the probe 
matches one of the cue images.  Match probability 
will be 50%. Trial duration will be 6 sec, with a 
variable inter-trial interval (1000–2000 ms). Grey 
scale fractal images were selected for the task 
because these stimuli are affectively neutral and 
less prone to verbal encoding compared to most 
other types of visual stimuli. This feature will 
discourage variable or shifting encoding strategies 
across individuals, groups and testing sessions, 
which, if  present, could significantly diminish our ability to detect true treatment effects. There will be a control 
condition in addition to the WM condition. The trial structure and stimuli of the control trials will be identical to 
those of the WM trials but subjects will be instructed to passively view the stimuli and register a response with a 
button press when the probe image appears. Control trials will facilitate more accurate assessment of WM 
associated gamma oscillations by allowing the investigators to subtract out non-WM associated EEG signals. 
This will also minimize inter-subject differences that may confound the detection of true experimental effects.   
There will be 40 trials in each condition and trials will be blocked by condition, with 10 trials/block and a brief rest 
period between blocks. The condition for the upcoming block will be indicated by text and the condition block 
order will be pseudorandomized.  
 
Assessment of Functional Status: To assess the effect of rTMS on real world functioning, we will utilize the 
Global Functioning: Role Scale (GF). This scale is a well-validated measure of occupational/role functioning in 
individuals with schizophrenia and related conditions [30, 31].  It is a brief easy to apply 6-item scale that avoids 
confounding functioning with psychiatric symptoms, a problem found in other commonly used scales such as 
the Global Assessment of Function. We recently assessed the reliability of this scale in our group. Two raters 
independently applied this scale on 10 subjects with schizophrenia and these ratings yielded an intraclass 
correlation = 0.88. 
 
Electroencephalography during Cognitive Task Performance: All EEG gamma procedures have been 
employed in our published papers [16, 32, 33]. EEG data will be acquired in a shielded room using a Neuroscan 
64-electrode Quik-Cap and Neuroscan SynAmps2 hardware, with 1000 Hz sampling rate and 100 Hz low-pass 
hardware filter, using 32-bit encoding software, eliminating the need for high-pass recording filters, and 
electrode impedances < 5 kΩ. All channels will be referenced on-line to Cz.  Malfunctioning electrodes are 
excluded and data imported into EEGLab, re-referenced against the average reference, downsampled to 250 
Hz, and high-pass filtered at 0.5 Hz. Epochs are extracted from continuous EEG data on each task, from -500 
to +3000 ms relative to stimulus onset, and baseline-corrected with pre-stimulus interval (-500 to 0 ms). Trials 
with incorrect responses are removed. Individual electrodes are excluded if voltage within that trial is > 5 
standard deviations from the mean of all electrodes. Independent Components Analysis (ICA) follows ([34] 
using the “logistic infomax” ICA algorithm [35] with “extended” option of [36]); 75 principal components 
accounting for the most variance in the signal are derived. Components among the top 15 are identified for 
rejection via visual inspection of equipotential scalp topography maps, component waveforms, and component 
time-frequency distributions, and comparison with the data in [37] and [38]. Time-frequency transformation of 
the data is performed [39] by convolving the epoched EEG with a complex Morlet wavelet function on individual 
trial segments to identify time-frequency components between 30-80 Hz. Each 1 Hz sub-band is defined by a 
logarithmically-increasing central frequency and range subject to a Gaussian kernel with constant c = 6. Average 
gamma power during the baseline is subtracted from task-related gamma power during the trial. Time-frequency 

spectrograms are established by pooling oscillatory power across electrodes grouped by topography. Statistical 
thresholds are empirically-derived via a permutation method [40], to preserve frequency and time-specificity of 
task and treatment effects and to support statistical inferences made directly upon visual inspection of 
spectrograms [33, 41].  
 
rTMS Treatment: The rTMS treatment will closely follow that of the Barr et al. study [9], which documented 
significant improvement in WM performance with rTMS applied to the DLPFC.  All rTMS treatments will be 
administered at the VA Palo Alto Health Care System (VAPAHCS), where several groups are conducting rTMS 
studies for other neuropsychiatric conditions, including a VA Co-op study on depression led by Dr. Yesavage, 
one of the collaborators on this study.  rTMS will be administered on a MagVenture MagPro R30 unit.  Subjects 
with schizophrenia will receive 20 treatments of rTMS occurring once a day, 5 days a week for 4 weeks, to 
DLPFC (alternating sessions between left and right hemispheres) at 20 Hz (non-patterned), at 90% resting motor 
threshold for 25 trains, 30 pulses/train, inter-train interval of 30 sec (750 pulses/hemisphere, a total of 1500 
pulses/session/day) in accordance with published safety guidelines [42]. Total duration of daily TMS sessions 
will be ~50 min. The resting motor threshold will be defined as the lowest intensity that produces a motor evoked 
potential (measured by EMG of non-dominant abductor pollicis brevis) of at least 50 mV in 50% of the trials.  
Trained physicians or RNs will administer rTMS blinded to treatment condition, to which subjects will be 
randomized by software contained in the TMS system. rTMS stimulation coils have a built-in position sensor that 
ensures that the correct (active or sham) side of the coil faces towards the patient's head. If the coil position is 
wrong, the operator will get a "Flip Coil" prompt, while maintaining the blind. Blinding will be further facilitated by 
the delivery of white noise during stimulation to mask the characteristic sounds associated with rTMS, as well as 
low voltage electrical stimulation of the scalp designed to mimic skin surface stimulation that sometimes occurs 
with active rTMS administration. 
 
Statistical Analysis 
 
Hypothesis Testing, Aim 1 - Subjects receiving rTMS will show improvements in a) WM performance, 
and b) occupational/role functioning compared to subjects receiving sham treatment:  Change scores 
(post-TMS vs. pre-TMS) for WM performance accuracy (ΔWM Acc) and Global Functioning (ΔGF) will serve as 
dependent measures for testing the hypothesis that rTMS improves cognition and functioning, respectively. The 
hypothesis will be supported if we find greater ΔWM or ΔGF in the active compared to the sham rTMS treated 
groups.  We will use independent samples t-tests and two-sided tests for significance testing, with an alpha level 
of 0.05. However, given the limited scope of the SPiRE award, our primary goal is not on finding statistically 
significant differences but rather on determining the directionality of changes and the effect sizes of treatment 
effects. These data will be critical for determining if there is preliminary evidence that could support proposals 
for future larger scale studies.  
 
Hypothesis Testing, Aim 2 - Subjects receiving active treatment compared to those receiving sham 
treatment will show a) increased cognition associated gamma oscillation power, and b) an associated 
improvement in task performance:  Hypothesis 2 will be supported if we find significantly greater Δgamma in 
the active rTMS compared to the sham treated group. In addition, in the active rTMS treated group, we will 
conduct Pearson’s bivariate correlation between Δgamma and ΔWM. A positive correlation between these 
variables will support the hypothesis that rTMS improves cognition by increasing gamma oscillations. We will 
explore the possibility that pre-treatment gamma predicts rTMS responsiveness.  We will evaluate this possibility 
by conducting a median split analysis in which subjects will be binned by their baseline gamma levels.  We 
predict that those in the lower half of the distribution will show higher Δgamma and ΔWM.  
 
Intent-to-treat:  We will conduct a modified ITT analysis for hypothesis testing.  We will use a modified ITT, 
which includes only subjects with outcome data, e.g. cognitive performance and EEG at the end of treatment 
[43], since good proxy measures cannot be imputed. To minimize missing data, we will acquire cognitive 
performance and EEG within one week of their last TMS session, including those intending to drop out. We will 
supplement this analysis with a per protocol analysis in which only subjects who completed all TMS treatments 
will be compared.  This is done to determine, in a proof of concept manner, if TMS has the capacity to improve 
cognition in schizophrenia.  We will include a careful examination of whether bias has been introduced due to 
dropout by determining if there is greater dropout in the treatment group and if significant differences exist in 

major demographic and clinical variables of individuals who have dropped out compared to those who have not. 
We will correct for any significant differences using covariates in our statistical models.