Evaluating Two Types of Cognitive Training in Veterans With Schizophrenia
Phase: NA
Conditions: Schizophrenia
Sponsor: VA Office of Research and Development

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Study Protocol 
 
Evaluating Two Types of Cognitive Training in Veterans with Schizophrenia 
 
NCT 01891721 
 
11/24/14 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Background and Significance  
One of the most exciting developments in the treatment of schizophrenia in the past decade has been 
the rise of cognitive remediation (CR). CR is a “behavioral training based intervention that aims to 
improve cognitive processes (attention, memory, executive function, social cognition, or 
metacognition) with the goal of durability and generalization” [1]. This collection of interventions aims 
to restore cognitive functioning by targeting different levels of cognition from basic perceptual 
processes (e.g., auditory or visual processing) to the more molar and complex cognitive skills (e.g., 
memory, problem solving). CR has been used in disorders other than schizophrenia, such as stroke, 
TBI, PTSD, and ADHD. Yet, its popularity in schizophrenia has grown because cognitive impairments 
are a core feature of the illness and remain unsuccessfully treated with the available antipsychotic 
medications. Schizophrenia is a disorder that affects both higher-level neurocognitive operations and 
lower-level perceptual processes. These deficits contribute to the poor community outcome and high 
levels of functional disability seen in patients [2]. Therefore, treatment of the cognitive dysfunction 
associated with this illness is important to achieve improvements in daily functioning. Numerous 
evidence-based approaches to CR have been developed to treat the cognitive deficits in 
schizophrenia. In general, improvements in cognition have been found with both cognition-enhancing 
approaches that attempt to restore neuronal and neurocognitive functioning, as well as compensatory 
approaches that seek to circumvent cognitive impairments to improve broader aspects of function [3]. 
Recent meta-analytic studies on cognitive training in schizophrenia [4, 5] report that cognitive training 
has a moderate effect-size impact on cognitive functioning (0.45) and a lower impact on daily 
functioning (0.36) and clinical symptomatology (0.28). Based on these studies, 2104 inpatients and 
outpatients with schizophrenia (with a mean age of 36 years old and a high school education) have 
participated in randomized controlled trials (RCTs) of cognitive interventions. They were typically 
exposed to 17 weeks of treatment, receiving about 32 hours at a dosage of 2 to 3 times a week. The 
interventions in these RCTs consisted of drill-and-practice training, as well as strategy-based 
learning. 
 
CR has been shown to produce changes in the brain. In a recent study, patients who received CR 
demonstrated a reduced loss in the hippocampus, and in some cases, an increase in gray matter 
volume in the amygdala [6]. CR is considered to be a learning activity and as such, it relies on 
neuroplasticity and occurs when neurons adjust their activity and organization in response to new 
situations or to changes in the environment. CR is designed to leverage the brain’s plasticity to create 
additional processing capacity by exposing subjects to cognitive exercises that challenge their 
attention and memory. According to principles of systems neuroscience, the brain adapts to training 
by representing the relevant sensory stimuli and action outputs with disproportionately larger and 
more coordinated populations of neurons [7]. This principle implies that all brains are capable of 
adaptive plastic change, even if there is underlying neuropathology.  
 
At this point, it is unclear whether training lower-level perceptual processes (bringing in sensory data 
into the brain) or higher-order cognition (strategies, problem-solving, ability to make more complex 
inferences about the world) will most benefit patients with schizophrenia. Most training interventions 
for schizophrenia have only targeted higher-order cognitive processes [8]. However, patients with 
schizophrenia also have deficits in basic visual processing, such as visual motion perception [9] and 
backward masking [10], as well as deficits in preattentive auditory processing, such as automatic 
sensory discrimination [11] and gating [12]. The abnormal signal detection at these early stages of 
processing combined with the impaired coordination of neuronal responses throughout the cortex [13] 
are thought to lead to abnormal higher-level cognition in schizophrenia.   
 
A few recent interventions in schizophrenia have targeted basic perceptual processing and these 
studies have shown that auditory [14] and visual [15] perceptual abilities can be trained and improved 
in patients with schizophrenia, suggesting that perceptual plasticity is intact in schizophrenia. 

Improvements associated with lower-level perceptual training programs can extend beyond 
perceptual measures to include improvements in neural responses and higher-order cognition. For 
instance, visual perception training led to changes in electroencephalographic (EEG) indices of early 
visual processing (N100), and these changes were correlated with working memory improvements in 
a non-clinical sample of older adults [16]. Moreover, intensive auditory training in patients with 
schizophrenia improved verbal memory and auditory neural responses (M100) assessed with 
magnetoencephalography (MEG) [17, 18]. These training-induced gains were associated with 
improvements in community functioning 6 months later [19]. This series of studies was conducted by 
Dr. Vinogradov’s research team and suggests that a bottom-up auditory training results in improved 
cognitive performance and restoration of neural correlates of both elemental and complex operations. 
These studies compared the experimental approach to a control condition consisting of commercial 
computer games. A vital question that remains is whether a neuroplasticity-based, bottom-up 
intervention is more effective than an intervention that targets top-down functions like attention, 
working memory, and executive functioning. Only one study [20] made this direct comparison and 
found that a bottom-up treatment targeting basic auditory processing normalized sensory gating 
(measured with MEG by the M50), and improved cognitive performance more than a top-down 
treatment targeting a broad range of higher-order cognitive functions. Unfortunately, this study had a 
relatively small sample of 39 patients total between both groups.   
 
One index of neural functioning that is of particular interest for understanding outcome in 
schizophrenia is mismatch negativity (MMN). MMN is an event-related potential (ERP) that is elicited 
in response to infrequent, physically deviant tones interspersed in the repeated presentation of a 
standard tone [21]. MMN is thought to index automatic, preattentive information processing, as it can 
be elicited without directing attention to stimuli [22]. MMN has shown stable, large deficits in 
schizophrenia [23] that have downstream effects on more complex cognitive operations, such as 
verbal learning [24], social cognition [25] and social functioning [26]. MMN is often followed by P3a, 
another ERP component that is assumed to reflect the covert shift in attention [27]. Similar to MMN, 
reductions in P3a amplitude have been documented in schizophrenia [28]. MMN has never been 
studied within a non-pharmacological RCT. It has been studied in pharmacotherapy trials with mixed 
results. Some reports found that MMN is partially normalized by second-generation antipsychotic 
medications [29], and others did not [30]. Given the robust MMN abnormality in schizophrenia and its 
relationship to higher-order cognition and real-world functioning, it will be useful to ascertain whether 
MMN is an appropriate treatment target and can be influenced by CR.   
 
The proposed study aims to contrast a bottom-up intervention targeting auditory processes and a top-
down intervention targeting higher-order cognitive functions, compared with a control condition, in 
Veteran and non-Veteran patients with schizophrenia. These interventions will be assessed by their 
effects on representative measures from three outcome domains: neurocognition, EEG (MMN), and 
functional capacity. We will also assess the effects of these interventions on social cognition and 
community functioning as part of our exploratory analyses. This proposal extends the study by Popov 
et al. by: 1) including a much larger sample size, 2) adding a control treatment condition to the 
bottom-up and top-down conditions, 3) investigating a different neural measure of auditory processing 
that is more closely associated with daily functioning, 4) using a broader and well-normed 
neurocognitive test battery, and 5) including measures of functional capacity/community functioning to 
evaluate whether the effects of treatment generalize to a more distal outcome. We will study a 
neuroplasticity-based training focused on auditory rather than visual systems given that verbal 
learning/memory tends to be the most impaired cognitive domain in schizophrenia [31] and a strong 
predictor of work performance and functional outcome. We will utilize EEG techniques, ERPs in 
particular, because they allow us to examine early perceptual processes with a high level of precision 
and temporal resolution [32]. 
 

This proposal will determine which training approach leads to the largest magnitude of improvement 
in neurocognition, functional capacity, and neural functioning measured with EEG. Moreover, it will 
shed light on the underlying mechanism of action associated with the observed improvements in 
cognition. Based on the neuroscience-guided theoretical framework described above, we expect that 
the effects of the bottom-up training 1) will result in robust changes in higher-order cognitive 
operations, 2) will be evident at the earliest stages of auditory processing (normalization of MMN), 
and 3) will generalize to functional capacity. We also expect that the bottom-up training will lead to 
superior effects on the primary and secondary outcomes relative to the top-down training. The 
proposed study will help to decide how best to implement CR interventions to improve the cognitive 
and social functioning of patients with schizophrenia. Subsequent studies could consider additional 
research questions, such as whether the benefits of training are maintained over time. Depending on 
the results of this study, treatment providers at the VAGLAHS will be able to decide which version of 
CR will lead to more substantial gains. Our prediction is that it will be the neuroplasticity-based 
intervention. However, this study will provide a clinically meaningful answer, even if our hypothesis is 
incorrect.   
 
Preliminary Studies  
 
Previous Work on Neurocognition in Schizophrenia 
During the first part of my doctoral training, I worked under the supervision of Dr. Kristin Cadenhead 
at the UCSD Cognitive Assessment and Risk Evaluation (CARE) program. My first publication from 
this laboratory [33] examined the course of neurocognitive functioning in the prodrome and first 
episode of schizophrenia. This study demonstrates my skills in neurocognitive assessment and 
familiarity with the challenges of assessing change in neurocognitive functions across repeated 
testing in a clinical sample. I learned how to analyze longitudinal data while statistically accounting for 
problems such as practice effects and regression to the mean. The study included 48 subjects at risk 
for psychosis (AR), 20 patients in their first episode of schizophrenia (FE), and 29 normal comparison 
subjects (NC) who were assessed 
on a neurocognitive battery at 
baseline and 6-month follow-up. 
We found that the AR group’s 
overall baseline performance 
(global neurocognitive index mean 
score) fell between the NC and FE 
groups’ performance. There were 
significant group differences across 
all cognitive domains, significant 
time effects for executive 
functioning, processing speed, 
verbal learning, and general 
intelligence, as well as a significant 
group by time interaction for verbal 
learning. Whereas the NC and AR 
groups remained stable over time 
in their verbal learning 
performance, the FE group 
demonstrated a significant 
improvement in verbal learning 
over the test-retest interval (see 
Figure 1). 
 

We also examined the pattern of change in neurocognitive performance over time at the individual 
level. For each subject, we determined whether the observed fluctuations represented meaningful 
changes or normal variability in performance using a regression-based approach that controls for 
practice effects and regression to the mean. We found that a high proportion of FE subjects showed 
an improvement in verbal learning, and a significant number of AR subjects improved in general 
intelligence. Moreover, a higher than expected percentage of FE subjects, as well as AR subjects 
who later converted to psychosis, showed deterioration in working memory and processing speed. 
Our results suggest that cognitive functions do not follow a unidimensional trajectory in schizophrenia, 
but rather vary by cognitive domain and phase of the illness. Unlike the neurocognitive deficits in 
chronic schizophrenia, which tend to be fairly stable [34], there may be more changes during the 
prodromal period and right after the illness sets in. 
 
Previous Work on Electrophysiology in Schizophrenia 
After studying the course of cognitive deficits in the early stages of schizophrenia using behavioral-
based measures, I developed an interest in the neural mechanisms of these disturbances. During the 
second part of my doctoral training, I joined the laboratory of Dr. Gregory Light to learn how to apply 
EEG techniques. For my dissertation [35], I assessed three ERPs of automatic, preattentive 
information processing in 26 individuals at risk for psychosis, 31 recent-onset and 33 chronic 
schizophrenia patients, as well as 28 healthy control subjects. The primary aim of the study was to 
examine mismatch negativity (MMN), P3a, and RON (reorienting negativity) in these three patient 
samples. As described in the previous section, MMN is an index of automatic change detection. It is 
largest at central midline scalp sites and typically peaks between 160 to 220 ms after the onset of the 
deviant stimulus. P3a is a positive going wave that follows MMN and measures the orienting of 
attention. It is frontally maximal and peaks between 250 and 300 ms post-stimulus. RON is thought to 
measure the 
automatic 
preparation for 
detecting 
subsequent 
stimulus changes. 
This attentional 
reorienting is 
reflected in a 
negative going 
wave that follows 
the P3a, peaks 
between 400 and 
600 ms, and is 
centered on 
frontocentral 
electrodes [36].  
 
Our findings showed that robust frontocentral deficits in MMN and P3a were present in all patient 
groups. The at-risk group’s MMN and P3a amplitudes were intermediate to those of the healthy 
control and recent-onset groups, with the chronic group having the most pronounced reductions (see 
Figure 2). The recent-onset and chronic patients, but not the at-risk subjects, showed significant RON 
amplitude reductions, relative to the healthy control subjects. Although this is a cross-sectional study, 
the findings suggest that MMN and P3a abnormalities precede the onset of psychosis while RON 
deficits do not emerge until after the full manifestation of the illness. These results support the 
continued examination of MMN and P3a as potential early biomarkers of schizophrenia and raise the 
possibility of progressive worsening in early auditory information processing with illness chronicity. 
 

Since starting my postdoctoral 
training 1.5 years ago, I have 
continued to use EEG techniques 
and behavioral measures to study 
the cognitive and perceptual 
impairments in schizophrenia. I have 
been involved in several studies, 
including one that examined how 
early preattentive abnormalities in 
bipolar disorder compare to those 
found in schizophrenia. Our lab’s 
research efforts have increasingly 
focused on understanding bipolar 
disorder because of the 
pathophysiological features it shares 
with schizophrenia, including genetic 
risk factors [37], high rates of 
functional disability, and notable 
cognitive impairment. In a recent 
paper [38], we assessed the MMN 
and P3a ERP components in 52 
bipolar patients, 30 schizophrenia patients, and 27 healthy controls during a duration-deviant oddball 
paradigm. We found impairments in both MMN and P3a in bipolar disorder (see Figure 3). At the 
earlier stage of automatic sensory discrimination reflected by MMN, bipolar patients showed deficits 
that were similar to patients with schizophrenia, but to a lesser degree. This finding suggests that 
both groups of patients may have problems detecting changes in their auditory environment. At the 
slightly later stage of orienting to salient auditory stimuli reflected by P3a, bipolar patients showed 
pronounced deficits, and these impairments were non-significantly larger than those in schizophrenia. 
This proposal will use the same auditory oddball paradigm, which has been tested in a large number 
of patients and healthy controls in our lab, to measure MMN and P3a.  
 
Previous Work on Cognitive Remediation in Schizophrenia 
I currently am lacking skills and experience in cognitive remediation with psychiatric patients, and I 
have identified this missing skill set as important to develop as part of my CDA training plan. Dr. 
Green’s lab provides a conducive environment to filling that gap in my experience, given its long-
standing research program focused on cognitive and social cognitive rehabilitation using both 
pharmacological and behavioral approaches. Moreover, the availability of local experts (Drs. Green, 
Kern, and Horan) in addition to the identified co-mentor (Dr. Vinogradov) will help me achieve my 
training goal.  
 
Dr. Green’s lab has had considerable success in applying compensatory and functionally-relevant 
remediation programs to Veterans and non-Veterans with schizophrenia. Previous studies have 
shown that the performance of schizophrenia patients on selected neurocognitive tests could be 
modified under carefully controlled training conditions [39], and that the durability of these training 
effects can be enhanced by using a compensatory approach, errorless learning [40]. Errorless 
learning is a remediation approach based on findings that learning is stronger and more durable if it 
occurs in the absence of errors. Errorless learning training methods can be applied to complex 
behaviors in patients with a psychotic diagnosis, as demonstrated in a study in which Veteran and 
non-Veteran patients assigned to an errorless learning group showed more improvements in social 
problem solving ability than those assigned to a symptom management group [41]. Ongoing efforts 
have examined the effects of errorless learning on vocational rehabilitation.  In a recent publication 
[42], work performance, tenure, and personal well-being were compared with conventional job 

training in a community mental health fellowship club that offered a 12-week time-limited work 
experience. Patients were randomly assigned to errorless learning or conventional instruction at a 
thrift-type clothing store. Errorless learning showed benefits on work quality compared with 
conventional instruction, and the group differences were relatively consistent over time. There were 
no group differences in personal well-being (self-esteem, job satisfaction, work stress) but for job 
tenure, results revealed a non-significant trend favoring errorless learning.    
 
In addition to experience and publications on a compensatory remediation approach like errorless 
learning, Dr. Green’s laboratory is familiar with direct training approaches relevant to the current 
proposal. Dr. Green previously served as a consultant for Posit Science (the software company for 
the training methods in the bottom-up arm of the proposal). His lab has collected data and published 
on one of their CR programs (the Aristotle package), that is focused on sustained attention, speed of 
processing, and response inhibition [43]. This training software is less established than the auditory-
based Brain Fitness Program. The Horan et al.’s RCT evaluated the efficacy of social cognitive skills 
training for patients with schizophrenia using the Aristotle program as one of the treatment 
comparison conditions. We have no published data on Cogpack. Yet, we piloted this training program 
with schizophrenia patients (n = 11) to demonstrate its feasibility.  
 
We piloted the Cogpack in two stages. Initially, we piloted with 5 patients who each completed a one-
hour session that included a range of exercises (at least 4 different ones) and rated how much they 
liked the program on a Likert scale ranging from 1 (not at all) to 10 (very much). All patients were able 
to understand the tasks following instructions, and they rated the exercises as highly tolerable 
(average rating of 8.8). Following the session, all 5 patients commented that they found the tasks to 
be engaging. This first piloting stage established that the tasks were well tolerated in this patient 
group.   
 
We then wanted to see if the Cogpack procedures were feasible for multiple sessions with patients.  
We piloted Cogpack on 6 additional patients who received training twice a week for four weeks. Each 
one-hour session consisted of different 3-7 exercises targeting higher-order cognitive functions. All 
patients successfully completed the 8 sessions, except for one patient who was hospitalized after 
completing 2 sessions. Based on this information, we consider the Cogpack exercises to be feasible 
for repeated and regular administrations.  
 
To assess the magnitude of improvement in performance over the duration of the 8 training sessions, 
3 of the exercises were administered with 
the same parameters 3 times (in sessions 1, 
4, and 8).  
These exercises included: 
1) “Eyewitness”, an attention and 
memory task that involves recalling 
short street scenes with random 
combinations of image, text, sound, and 
movement elements;   
2) “Connect”, a cognitive flexibility/ 
executive functioning task that involves 
connecting dots while switching 
between numbers and letters;  
3) “Confusion”, a problem-solving task 
that requires search strategies and 
involves reproducing a diagram using 
different keys without knowing what 
each key does.  

 
Figure 4 illustrates the mean performance of the 5 patients who completed these same 3 exercises in 
3 separate sessions. Raw scores were converted into z-scores and averaged across subjects for 
each time point. The z-scores were rectified so that higher is always better. As seen in the figure, 
patients did show improvement across time; there was a medium to large effect-size improvement 
from Time 1 to Time 2 across all exercises with a slight improvement from Time 2 to Time 3 (see the 
Power Considerations section as well).  
 
Research Design and Methods  
Subject recruitment will be coordinated through Dr. Green’s ongoing studies.  The availability of 
recruitment infrastructure, trained clinical interviewers, and cognitive remediation software will greatly 
facilitate the launch and conduct of the project. All subjects interested in the study will be prescreened 
for general inclusion and exclusion criteria by the recruiter using HIPAA compliant procedures. During 
the first visit (approximately 2 hours), participants will be consented and receive standardized clinical 
interviews to ensure diagnosis and eligibility. Participants will also receive symptom ratings of general 
psychiatric and negative symptoms, as well as mood symptoms. Subjects who fit selection criteria for 
the study will be scheduled for another visit, within 1 week of their first visit. During the second visit, 
(approximately 3.5 hours), subjects will be administered a comprehensive battery of cognitive, 
electrophysiological, and functional capacity/community functioning measures. Subjects will then be 
randomly assigned to one of the two cognitive remediation treatments (BFP and Cogpack) or to the 
control treatment (see randomization and treatment procedure below). Subjects will participate in 3 
treatment sessions a week (1 hour each) for 12 weeks. After 18 treatment sessions, subjects will 
come back for a midpoint assessment visit (1.5 hours) in which they will be administered the 
electrophysiological measures again and two brief questionnaires. Upon completion of treatment, 
subjects will be scheduled for a post-treatment visit within 2 weeks of the last treatment session. This 
visit will last approximately 3.5 hours and will include the same clinical, cognitive, electrophysiological, 
and functional capacity/community functioning assessments that were administered prior to 
treatment. A urine toxicology screen will be conducted as part of each assessment visit. In the rare 
instance when a subject tests positive on the urine toxicology screen, he/she will be rescheduled to 
come back on a different day to complete the assessments. Overall, the study will consist of 4 visits 
(11 hours total) and 36 treatment sessions (36 hours total). Subjects will be compensated $15/hour 
for the interview and testing sessions (first 2 visits, mid- and post-training visits) and $10/hour for the 
treatment sessions, a rate deemed acceptable by our IRB. Funding is requested for four years of data 
collection (see Table 1). The IRB application will be prepared prior to the grant being funded. 
 
Randomization and Treatment Procedure 
To optimize power for the primary comparison between the active treatments, we will use a 2:2:1 
asymmetrical randomization procedure resulting in a total of 48 subjects in the BFP group, 48 in the 
Cogpack group, and 24 in the control group. Subjects will be given sequential identification numbers 
and randomly assigned in blocks of 5 or 10 to maintain balance throughout the study. A random 
mixture of block lengths will be used to help ensure the integrity of the process and the preservation 
of the blind. The MIRECC Data Core will create an online randomization system for the project, which 
will be accessible only to the study coordinator who will perform the assignments. Randomization will 
be programmed in ASP (Active Server Pages). 
 
 
             Table 1: Enrollment for Each Year 

 
 
 
 
 
 
 
 
 
Patients will be scheduled for training during specific 60-min blocks of time (between 10:00 AM and 
2:00 PM) every Monday, Wednesday, and Friday. Treatment will be administered individually in a 
designated room. However, up to 6 patients may be sharing the treatment room at a time. Each 
patient will work through different exercises (depending on their assigned treatment condition) on a 
personal computer station. Patients will be told that they are going to receive training exercises that 
might or might not improve their cognitive functions. The testers will be blind to the patient’s treatment 
group membership. A staff person will be present in the treatment room and will be aware of the type 
of training that each patient is receiving, but this person will not administer any outcome measures. 
They will install the appropriate computer session for each patient and give individualized instruction 
in the use of the equipment and training program. To ensure maximum compliance, the trainer will 
provide encouragement, observe patients’ behavior throughout the session, and monitor data storage 
after each session. 
 
Recruitment will be ongoing and we expect to enroll 30 subjects/year. Based on dropout rates in our 
previous training intervention studies, we project 20% attrition, which will leave us with an estimate of 
96 completers: 38 getting BFP training, 38 getting Cogpack training, and 19 getting the control 
intervention. We will make every effort to hold patients in the study protocol while emphasizing that 
their participation is strictly voluntary and that they can withdraw at any time. To minimize attrition, we 
will inform subjects that they will be in the study up to 17 weeks and ensure that they will not be 
leaving town or relocating during the study period. We will contact those who opt to discontinue 
treatment to request that they participate in a final outcome assessment. Details of the plan for 
handling missing data and minimizing potential threats to randomization caused by differential 
dropout rates are further described in the data analysis section. 
 
Subjects 
120 patients with schizophrenia and schizoaffective disorder will be included in the study. Our sample 
will consist of Veterans and non-Veterans who will be recruited from VA outpatient treatment clinics 
and board-and-care residences in the community through staff presentations and referral. All 
recruiting efforts will be coordinated through Dr. Green’s laboratory. Approximately 8-10 patients with 
a schizophrenia/ schizoaffective diagnosis are admitted to VA clinics each week. The laboratory has 
had a successful history of meeting recruitment goals outlined in funded VA and NIMH projects. We 
will select clinically stable outpatients between the ages of 25 and 65 years old. Patients will be 
considered clinically stable if they had no medication changes in the past six weeks, no psychiatric 
hospitalization in the past three months, and no changes in housing in the past two months. Exclusion 
criteria will include having an estimated premorbid IQ below 70 based on reading ability, not meeting 
full criteria for schizophrenia or schizoaffective disorder, having an identifiable neurological disorder, 
seizures, or history of serious head injury, meeting criteria for substance dependence in the past 6 
months or abuse in the past month, or being insufficiently fluent in English as determined by the 
participant’s ability to understand the consent form. Most of the patients will be chronic and 
medicated, though we will not select patients based on chronicity. Duration of illness and medication 
information will be obtained through self-report and examination of medical records. All psychoactive 
medications and their dosages will be carefully recorded. Antipsychotic medication dosages will be 
 
Year 1 
Year 2 
Year 3 
Year 4 
Interviews, BFP, Pre- and Post-
Treatment Assessments 
12 
12 
12 
12 
Interviews, Cogpack, Pre- and 
Post-Treatment Assessments 
12 
12 
12 
12 
Interviews, Computer Games, Pre- 
and Post-Treatment Assessments 
6 
6 
6 
6 

converted to chlorpromazine (CPZ) equivalent units [44, 45]. Specific selection criteria as well as 
projected demographic distribution are listed in the Human Subjects section.  
Clinical Evaluation 
All patients will receive a diagnostic interview with the Structured Clinical Interview for DSM-IV (SCID-
I; [46]) as part of their participation in Dr. Green’s lab. The SCID-I will be conducted by interviewers 
trained to reliability through the Treatment Unit of the Department of Veterans Affairs VISN 22 Mental 
Illness Research, Education, and Clinical Center (MIRECC) based on established procedures [47]. 
Psychiatric symptoms will be evaluated using the expanded 24-item UCLA version of the Brief 
Psychiatric Rating Scale (BPRS; [48]) and negative symptoms will be assessed with the Scale for the 
Assessment of Negative Symptoms (SANS; [49]). The Hamilton Depression Rating Scale (Ham-D; 
[50]) and the Young Mania Rating Scale (YMRS; [51]) will also be administered to assess depression 
and mania, respectively, in schizoaffective patients. All symptom rating scales will be administered by 
the PI pre- and post-treatment.  
 
Electrophysiological Recording Procedures 
EEG Recording  
All EEG recording and processing will be conducted using existing equipment in Dr. Green’s lab at 
the VA. EEG recordings will be acquired with a 64-channel BioSemi ActiveTwo amplifier (Biosemi B. 
V., Amsterdam, Netherlands). Data will be sampled at 1024 Hz with filter settings of 0 to 100 Hz. 
Electrode caps using an array of 64 active electrodes will be attached in accordance with the 
international 10-10 scheme. To monitor blinks and eye movements, four additional electrodes will be 
placed above and below the left eye (to measure vertical electrooculogram; EOG) and at the outer 
canthi of both eyes (to measure horizontal EOG). Biosemi utilizes active electrodes that are 
measured with respect to a common mode sense electrode during data collection, forming a 
monopolar channel. An additional electrode will be placed at the nose tip and all EEG data will be re-
referenced offline to this electrode.  
 
Visual Long-Term Potentiation (LTP) paradigm 
The paradigm will involve assessment of visual evoked potentials (VEPs) before and after exposure 
to tetanizing visual high frequency stimulation (HFS). While maintaining focus on a central fixation 
cross, subjects will view visual stimuli presented centrally against a white background on a computer 
monitor located 57 cm in front of them. Each 2-minute VEP assessment block will consist of a 
pseudorandom oddball sequence of 90% standard (circle) and 10% target (square) stimuli (duration 
33 msec) presented at ~.83 Hz (1216 msec mean SOA, range 1075-1340 msec). Subjects will be 
asked to respond to the target square with a right-handed button press. VEP assessment blocks will 
be administered 4 minutes (baseline-1) and 2 minutes (baseline-2) before HFS and 2 minutes (post-
1), 4 minutes (post-2), and 20 minutes (post-3) after HFS. The 2-minute HFS block designed to 
induce potentiation will consist of repeated presentation of the standard circle at ~8.87 Hz (113 msec 
mean SOA, range 99-116 msec), a rapid flicker rate below the perceptual fusion threshold. Subjects 
will be administered the auditory MMN paradigm (described below) in the interval between the post-2 
and post-3 VEP blocks. 
 
Mismatch Negativity (MMN) Paradigm 
A passive auditory oddball paradigm will be used to assess basic auditory processing. Subjects will 
be presented with standard and duration-deviant tones binaurally using foam ear inserts (1 kHz 85 dB 
sound pressure level, with 10 ms rise/fall) with a fixed stimulus onset asynchrony of 500 ms, using E-
Prime 2.0 (Psychology Software Tools, Inc., Pittsburgh, PA). Standard (90% probability; 50 ms 
duration) and deviant (10% probability; 100 ms duration) tones will be presented in a fixed, 
pseudorandom order (with the restriction that at least 4 standard tones are presented between 
deviant tones). Two-thousand total trials will be administered. During the 25-minute EEG recording, 

subjects will be instructed to watch a silent movie to divert attention from the stimuli. The EEG 
session (including electrode placement and recording) will last approximately 45 minutes. 
 
EEG Processing  
Data processing will be performed offline using BrainVision Analyzer 2 software (Brain Products, 
Gilching, Germany). Based on visual inspection, bad electrodes will be removed from the recording 
and a spherical spline interpolation will be used to recreate the electrode [52]. Data will be high-pass 
filtered at 1 Hz to remove slow drifts. Eye movement artifacts will be removed from the data using a 
regression-based algorithm [53]. Continuous data will then be divided into epochs relative to stimulus 
onset (-100 to 500 ms) and baseline corrected to the average of the prestimulus interval (-100 ms to 
0). Only electrodes at frontocentral sites that are representative of neural activity generated by the 
MMN paradigm based on our previous studies (AF3, AF4, AF7, AF8, AFz, Cz, F1, F2, F3, F4, F5, F6, 
F7, F8, FC1, FC2, FC3, FC4, FC5, FC6, FCz, Fp1, Fp2, Fpz, Fz) will be examined. Following 
eyeblink correction, epochs that contain activity exceeding ± 75 V at these electrode sites will be 
automatically rejected. Only data from subjects who have at least 100 acceptable deviant trials (out of 
200) will be included in the analyses. MMN waveforms will be generated by subtracting ERP 
waveforms in response to standard tones from the ERPs generated in response to the deviant tones. 
The resultant MMN subtraction waveforms will then be low-pass filtered at 20 Hz (zerophase shift, 24 
dB/octave rolloff) to remove any residual high-frequency artifact. MMN amplitude will be measured as 
the mean activity (expressed in µV) in the 135-205 ms latency range. This time window was chosen 
based on prior studies in schizophrenia [25]. Butterfly plots and 2-dimensional scalp topography of 
grand average MMN responses will be inspected to ensure that each subject is showing the expected 
pattern of activity (i.e., negativity at frontocentral regions and polarity inversion at the mastoids). 
Furthermore, only MMN responses that are at least 2 times the amplitude of any activity present in 
the 100 ms before stimulus onset will be considered valid [26]. The MMN amplitude at Fz will serve 
as the primary EEG outcome measure.  
 
Behavioral Assessments  
Neurocognition  
To assess neurocognitive functioning, the MATRICS Consensus Cognitive Battery (MCCB; [54]) will 
be administered. The tests in the MCCB were selected from over 90 nominated tests and represent 7 
separable cognitive domains [55, 56]. The MCCB takes approximately 60 minutes to administer and 
provides normed scores, including a summary score and cognitive domain scores. The MCCB 
includes one social cognition domain (the Managing Emotions component of the MSCEIT) which will 
not be included in the summary score but rather incorporated into a social cognitive composite score 
(see below). The remaining 6 domain t-scores from the MCCB will be averaged to create a composite 
score representing basic cognition as has been done previously [43]. Table 2 shows the tests that 
comprise the battery and the 6 cognitive domains they represent. The MCCB composite score will 
serve as the primary cognitive outcome measure. The individual MCCB domain scores will be used in 
secondary analyses to determine whether an overall effect is driven by any particular aspect of 
neurocognition. 
 
Table 2: MCCB Cognitive Domains and Tests  
 
      Domain Assessed 
Measure 
Speed of Processing 
Trail Making Test (TMT): Part A 
Brief Assessment of Cognition in Schizophrenia (BACS): 
Symbol Coding 
Category Fluency: Animal Naming 
Verbal Memory 
Hopkins Verbal Learning Test–Revised (HVLT-R) 
Visual Memory 
Brief Visuospatial Memory Test–Revised (BVMT-R) 

Working Memory 
Wechsler Memory Scale–Third Edition (WMS-III): Spatial Span 
Letter–Number Span (LNS) 
Attention / Vigilance  
Continuous Performance Test–Identical Pairs (CPT-IP) 
Reasoning and Problem Solving 
Neuropsychological Assessment Battery (NAB): Mazes 
 
Social Cognition 
To assess emotional processing, the Managing Emotions component of the Mayer-Salovey-Caruso 
Emotional Intelligence Test (MSCEIT; [57]) will be administered. Managing Emotions has 2 subscales 
that examine the regulation of emotions in oneself and in one's relationships with others. These 
subscales include vignettes of various situations, along with ways to cope with the emotions depicted 
in these vignettes. Subjects are required to indicate the effectiveness of each solution, ranging from 1 
(very ineffective) to 5 (very effective). It takes about 15 min to complete this measure.   
 
In addition to this high-level social cognitive test, a low-level social cognitive test, the Affective 
Prosody Task (APT; [58]), will be used to measure auditory emotion recognition. Stimuli consist of 
audio recordings of semantically neutral sentences spoken with different voice tones. The sentences 
are either statements or questions and conveyed in 6 emotions (fear, anger, happiness, sadness, 
disgust, or neutral). After each stimulus, a list of the 6 possible choices is presented on the computer 
screen and the participant selects one emotion. It takes about 15 min to complete this task.  
 
A social cognitive composite score will be created by standardizing (z-scoring) then summing the total 
scores from the MSCEIT Managing Emotions subtest and the APT. The social cognitive composite 
score will be included in exploratory analyses. 
 
Functional Capacity and Community Functioning 
To assess functional capacity, the UCSD Performance-based Skills Assessment (UPSA; [59]) will be 
administered. The UPSA assesses five skill areas that are considered essential to functioning in the 
community: General Organization; Finance; Social/Communications; Transportation; and Household 
Chores. The UPSA involves role-play tasks with props that are administered in the laboratory as 
simulations of events that the person may encounter in the community. These tasks are similar in 
complexity to situations that a community-dwelling person with chronic mental illness is likely to 
encounter. Inter-rater reliability of ratings are excellent (intraclass correlation coefficient = .91, 
p<.001). The UPSA takes 25 minutes to administer and yields a total score and domain scores. The 
UPSA total score will serve as the primary functional outcome measure. 
 
To assess community functioning, the Role Functioning Scale (RFS; [60]) will be administered. The 
RFS assesses patients’ current level of functioning in four areas: independent living skills, social (both 
family and non-family) functioning, and work functioning. The subscale ratings range from 1 (severely 
impaired) to 7 (maximal functioning) and include anchor points that detail both the quantity and quality 
of functioning. The RFS will be administered as part of an approximately 30-minute interview and 
rated by one of several trained interviewers in our lab. The RFS yields a total score and domain 
scores.  
 
Although we are evaluating whether our relatively brief clinical trial affects proximal constructs such 
as cognition and functional capacity, we are unlikely to see significant changes in real-world 
functioning after only 3 months of cognitive training. Nonetheless, we will include the RFS total score 
in exploratory analyses, and these results might provide a basis for future work. 
 
Half-way through the training, subjects will be administered two questionnaires, the Intrinsic 
Motivation Inventory for Schizophrenia Research (IMI-SR) and Theories of Intelligence Scale (TIS). 
The IMI-SR is a task-specific measure of intrinsic motivation. It consists of 21 items rated on a 7-point 
Likert scale with responses ranging from “not at all true” to “very true”. It is designed to assess 

patients’ subjective experience of an activity in an experimental setting (i.e., cognitive training). The 
instrument has 3 subscales: 1) perceived interest and enjoyment due to task, 2) perceived value and 
usefulness of the task, and 3) perceived autonomy to perform the task. The TIS assesses subjects’ 
beliefs about the nature of intelligence (as an unchangeable, fixed entity or as a malleable quality that 
can be developed). It consists of 8 items: 4 entity theory statements (e.g., “You have a certain amount 
of intelligence, and you really can’t do much to change it”) and 4 incremental theory statements (e.g., 
“You can always substantially change how intelligent you are”). 
 
Cognitive Training Interventions  
Specific Perceptual Training: Brain Fitness Program, Posit Science, San Francisco, California 
www.positscience.com 
This computerized cognitive intervention is designed to improve the speed and accuracy of auditory 
information processing through increasingly more difficult stimulus recognition, discrimination, 
sequencing, and memory tasks under conditions of close attentional control, high reward, and novelty 
[61]. BFP consists of 6 exercises (Table 3). Stimuli across the exercises are chosen such that they 
span the acoustic and organizational structure of speech, from very simple acoustic stimuli and tasks 
(e.g., time order judgments of rapidly successive frequency-modulated sweeps) to complex 
manipulations of continuous speech (e.g., narrative memory). The exercises adaptively progress 
based on the subject’s individual performance during a training session and become more 
challenging as the subject’s abilities improve. Participants will work with 4 of the 6 exercises (for 15 
min per exercise) in each session. Duration of training is 1 hour per day, 3 days per week, for 12 
weeks, for a total of 36 hours. 
 
         Table 3: Brain Fitness Program Exercises 
 
Exercise Name 
Description 
High or Low? 
Reconstruct the identity (upward or downward) and sequence of 
frequency-modulated sweeps. The task progresses by changing 
the duration and interstimulus interval between the sweeps  
Tell Us Apart 
Identify a synthetically generated syllable (e.g.,_ba_) from a 
confusable pair (e.g.,_ba_vs._da_). The task progresses by 
changing the duration and intensity of the sweep component of 
the initial consonant. 
Match It! 
Match short spoken confusable consonant–vowel–consonant 
words (e.g., bad, dad) from a spatial grid. The task progresses 
by changing the number of potential matches and processing the 
spoken speech to stretch and emphasize rapid transitions. 
Sound Replay 
Reconstruct a sequence of short spoken words (identical to the 
third exercise stimuli). The task progresses by changing the 
number of words in the sequence and the level of speech 
processing. 
Listen and Do 
Reconstruct a spoken series of instructions by using the 
computer mouse to click and drag icons on the computer screen. 
The task progresses by changing the number and complexity of 
the instructions and the level of speech processing. 
Story Teller 
Answer questions regarding short narratives. The task 
progresses by changing the length of the narratives and the level 
of speech processing. 
 
BFP has a strong theoretical rationale based on systems neuroscience principles. The goal of this 
neuroplasticity-based training program is to harness the brain’s inherent plasticity through implicit 

learning mechanisms. This training approach relies on the premise that the effects of implicit learning 
and repetitive practice are intact in schizophrenia despite the fact that explicit learning/memory and 
the motivation/reward systems are impaired [62]. The training employs intensive, repetitive, adaptive 
practice of well-defined skills to maximize enduring plastic changes in the brain. To drive learning and 
preserve reward schedules [63], the difficulty level for each subject is adjusted to maintain an 
approximately 85% correct rate and each correct trial is rewarded immediately with points and 
animations.  
 
A large-scale RCT comparing BFP to a general cognitive stimulation program in healthy adults found 
greater improvements in auditory processing and better performance on untrained neurocognitive 
measures of attention and memory in the BFP group [64]. As mentioned above (Preliminary Studies), 
our laboratory has previously used Posit Science software with patients and found it to be very well 
tolerated.   
 
Broad Cognitive Training: Cognitive Package (Cogpack; version 8.5, Marker Software, Ladenburg, 
Germany) www.cogpack.de 
This computerized cognitive intervention is designed to provide training across a broad range of 
cognitive functions. Cogpack is well established in psychiatric hospitals and clinics in German-
speaking countries [65] and has been translated into several languages, including English. Cogpack 
consists of domain-speciﬁc exercises, aimed at training speciﬁc cognitive areas (attention, working 
memory, verbal and visual memory, executive functioning, reasoning, language) and non-domain-
speciﬁc exercises that require the use of several functions at a time. Although Cogpack includes low-
level cognitive exercises (i.e., scanning, hand-eye coordination, and psychomotor speed), these 
exercises will not be included in this protocol to better separate bottom-up from top-down training 
interventions. Participants will complete a total of 48 exercises. All exercises are included within the 
first 9 sessions. Then, variants of the same exercises with different levels of difficulty are repeated 
over the remaining 27 sessions for further practice. In each session, the participant will work on a 
different subset of 4 to 6 exercises. Duration of training is 1 hour per day, 3 days per week, for 12 
weeks, for a total of 36 hours. 
 
         Table 4: Cogpack Exercises 
 
Domain Trained 
Examples of Exercises 
Attention 
Sort out products on a conveyer belt, find the repeated 
character on a screen full of characters, press the bar 
when a number directly follows the previous one 
Verbal and Visual Memory 
Learn and memorize a list of words, remember 
addresses, images, labels, patterns, routes, details from 
lively scenes 
Reasoning and Executive 
Functioning 
Solve arithmetic problems and deductive comparisons, 
complete a block, continue a series, connect dots 
Language  
Use various clues to find words, answer questions about 
text-content, attribute quotations to authors or titles to 
poems, place syllables in order, solve anagrams 
Knowledge and Everyday 
Skills 
Demonstrate knowledge of facts, history, geography, 
country abbreviations, count bills, balance scale, use 
compass, estimate calories 
          
Similar to the Brain Fitness Program, a motivational enhancement component is embedded in 
Cogpack to enhance intrinsic motivation and perceived competency, two client factors that influence 
responsiveness to treatment [66]. The exercises are designed to be enjoyable, reinforcing to 

complete, and challenging, with difficulty gradually increasing over time. The level of difficulty is set 
based on the subject’s performance during the course of the session. Moreover, the program 
provides regular individualized feedback on the subject’s performance during the session and over 
the course of treatment.  
 
Control Treatment: Commercial Computer Games (CCG).  
This treatment condition is designed to control for the effects of computer exposure, contact with 
research personnel, time spent being cognitively active, and financial compensation for participation. 
A similar control condition of commercially available computer games has been used in previous 
cognitive remediation studies with schizophrenia [14]. This “placebo” condition also controls for the 
non-specific engagement of attentional systems through the reinforcement of graphics-based 
computer games and allows for responses to visual and motor stimuli and action events via 
computer-generated tasks. However, these games do not have the specific and systematic approach 
of highly focused, intensive, individualized neuroadaptive training of BFP, and they do not have the 
conceptual and higher-level training of Cogpack.  
 
Participants in this condition will play highly enjoyable commercially available computer games for a 
total of 36 hours and will receive the same amount of contact with personnel and the same monetary 
and other reinforcements as participants in the experimental treatment groups. Subjects will 
participate in three 60-min sessions per week and will play 4 computer games, at 15 minutes per type 
of game, in each session. We will use 10 computerized games (e.g., visuospatial puzzle games, 
pinball-style games, target-aiming games). These games have been used by Dr. Vinogradov’s group 
and selected according to the following criteria: 1) The game is subjectively challenging, reinforcing, 
and can hold subjects’ interest and motivation for the required intervention period; 2) the game 
encourages the development of psychomotor skills (e.g. reaction time, hand-eye coordination); and 3) 
the game has no disturbing or highly emotional violent or sexual content as rated by the 
Entertainment Software Rating Board.  
 
Data Management 
Data management and statistical support will be provided by the VISN 22 MIRECC Data Core, 
directed by the co-investigator and statistical consultant, Dr. Sugar. The data core is made up of 
multiple senior consulting faculty from the UCLA Departments of Biostatistics and Psychiatry as well 
as full-time staff statisticians, database and applications programmers, data managers and web 
designers. Its personnel have extensive experience supporting studies ranging from small pilot 
projects to large multisite centers and have a long history of collaboration on schizophrenia studies at 
the VA with Drs. Jahchan, Green and their research team. For this project, the data core will develop 
a customized VA intranet-based data system, including the subject registry, data dictionary, 
randomization system, data entry forms, project management tools and the centralized database 
which can accommodate both manual entry and electronic upload and merging of data from other 
sources. In particular, EEG data will be collected and processed on a separate computer, and the 
primary amplitude measures will be extracted and uploaded into the primary database. The system 
will be housed on the data core’s secure VA servers and will feature numerous security and quality 
assurance features including double entry to verify data correctness, automatic logic and range 
checking, and strict protocols for data confidentiality, transfer and back-up including anonymized ID 
coding to protect subject privacy. All files are encrypted and the systems and tools are protected by 
128-bit SSL, the secure socket layer technology used for sensitive transactions on the web. The 
system will be accessible only via the VA intranet and will employ  a hierarchical system of password 
protected logins, allowing differential access to project team members as appropriate to their roles. 
Data will be accessed only through the system, not transported, and analyses will be performed on 
de-identified and aggregated data in consultation with the MIRECC Data Core.  
 
 

Statistics and Power Analysis 
Statistical Plan 
The experimental design for this study is a 3-group randomized clinical trial, with assessments at 
baseline and the 12-week treatment endpoint. The aims correspond to comparisons of the effects of 
two active treatments to each other and to a control condition on neurocognition, EEG, and functional 
capacity. For each of these domains, we specify a primary outcome measure. For neurocognition we 
will use a composite score created by averaging the t-scores for the 6 neurocognitive domains of the 
MCCB. The main EEG measure will consist of the MMN amplitude at electrode Fz. For functional 
capacity we will use the total score from the UPSA. If significant treatment effects are found on any of 
the primary outcomes, we will perform secondary analyses on the corresponding components or 
subscale scores to determine whether the results are driven by particular aspects of the main 
constructs. To further characterize the treatment response profiles, exploratory analyses will be 
performed to examine the effects of the interventions on composite scores of social cognition and 
community functioning. We are well aware of the risk of Type I error inherent in a study with a large 
battery of assessments and have protected against it by clearly specifying a limited a priori set of 
primary outcome measures and contrasts of interest and designating all others as exploratory. 
However, since this is a preliminary study, designed to obtain estimates of treatment effects and to 
identify optimal intervention components and measures for a future definitive efficacy study, it is 
equally important not to miss any potentially relevant outcomes. All results will therefore be reported 
using an uncorrected two-sided significance level of α=.05. 
 
Prior to performing the primary analyses, descriptive statistics and graphical summaries will be 
obtained for all outcomes to check for missing data, outliers and the need for transformations or non-
parametric methods. To assess the success of randomization, ANOVAs and chi-square tests will be 
used to test for baseline group differences on the primary outcomes as well as on demographic (age, 
gender, parental/personal education) and clinical (medication, duration of illness, and symptom 
severity) characteristics. Measures that show significant differences will be included as covariates in 
subsequent analyses. Below we give a detailed description of the analytic plan by specific aim. 
 
Analysis Plan By Specific Aim: 
Specific Aim #1: To compare the treatment effects of bottom-up training (BFP) to top-down 
training (Cogpack) as well as to a control condition on neurocognition. 
Specific Aim #2: To compare the treatment effects of bottom-up training (BFP) to top-down 
training (Cogpack) as well as to a control condition on EEG (MMN). 
Specific Aim #3: To compare the treatment effects of bottom-up training (BFP) to top-down 
training (Cogpack) as well as to a control condition on functional capacity. 
Exploratory Aims: 1) To compare the treatment effects of bottom-up training (BFP) to top-down 
training (Cogpack) as well as to a control condition on social cognition and community functioning and 
2) to assess whether changes in MMN are associated with changes in cognition and functioning.  
 
Primary Analyses: To make the most efficient use of our data, our primary analytical technique will be 
the general linear mixed model (GLMM). GLMMs account for correlations induced by repeated 
measures within subjects, allow for both fixed and time-varying covariates and automatically handle 
missing data, producing unbiased parameter estimates provided that observations are missing at 
random. This allows us to include all available data from all subjects in the analyses, regardless of the 
degree of study participation or treatment dosage received, consistent with the intent to treat 
framework. For each of our primary outcomes (MCCB neurocognitive composite for Aim1, MMN 
amplitude at Fz for Aim 2, UPSA total score for Aim 3), our core model will include group (BFP, 
Cogpack, control) as the between subject factor, time (baseline, end of treatment) as the within 
subject factor, and a group by time interaction. Our primary hypotheses correspond to the group by 
time interactions comparing the outcome trajectories for the two active treatments, which can be 
obtained as post-hoc contrasts. Such contrasts can also be used to compare each of the active 

treatments to the control condition, to test for within group change and to examine the magnitudes of 
group differences at the end of treatment.  
 
Exploratory Analyses: Significant results for the primary global measures will be followed by 
equivalent models for the component subdomain scores to identify the primary drivers of treatment 
effects. Parallel models will also be fit for the exploratory analyses of social cognition and community 
functioning measures. To examine the relationships between MMN and cognition and functioning, we 
will add this EEG index as a time-varying covariate to the primary GLMM models for the other 
outcome domains. Although we are underpowered for a full mediation analysis, this will also allow us 
to obtain a preliminary indication of whether treatment effects operate through their effect on 
electrophysiology. Given that age, duration of illness, symptom severity, medication (indexed by CPZ 
units) and dosage of treatment (number of sessions) may all impact treatment response, we will also 
add these measures and their interactions with treatment group and time to the primary models to (i) 
determine whether they explain additional variation in the outcomes and (ii) obtain preliminary 
information about potential treatment moderators.    
 
Attrition and Missing Data: We plan an intent-to-treat approach, using all available data from all 
subjects, regardless of the degree of program participation. As noted above, our GLMM models 
automatically handle missing data, making the most efficient use possible of available measurements. 
However, with this study population there is likely to be moderate data loss (up to 20% due to attrition 
and EEG artifacts based on our prior experience) and we recognize the potential for bias due to 
differential dropout. The impact of attrition will be evaluated by comparing dropout rates in the 
treatment arms using chi-square tests, and by comparing baseline characteristics of dropouts with 
those who have outcome data. If there is evidence that attrition patterns might introduce bias into the 
analyses, we will perform supplementary analyses adding propensity-score adjustments to the 
primary models. In the propensity score framework, baseline characteristics are used to develop a 
predictive model for attrition (e.g., via logistic regression), and the probability of dropout is used either 
as a covariate or to weight the observations in the subsequent models. In essence, cases who are 
similar to dropouts are weighted more heavily to “make up” for others like them who dropped out. As 
noted above, we will also explore treatment dosage as a covariate in secondary models. Finally, 
scattered missing data on covariates will be handled using multiple imputation procedures.  
 
Power Considerations 
We plan to enroll 120 subjects (n=48 for each of the two treatment conditions and n=24 for the control 
group) to obtain a final sample of n=96 subjects with complete data after accounting for attrition and 
data loss. Power calculations are conservatively based on these numbers and assume a two-sided 
significance level of α=.05. We also assume a within-subject autocorrelation of r = .7, a value based 
on our experience with similar studies in the past. Our primary hypotheses all involve comparisons 
(parameterized as group by time interactions) among the 3 treatment groups. Our design provides 
over 80% power to detect overall effects as small as f=.13 which is sufficient to detect any pattern of 
changes in the three study arms for which the difference between the two most extreme groups is at 
least d=.6 at study endpoint. For the post-hoc comparison of primary interest, namely the group by 
time interaction examining the outcome trajectories for the two active treatment groups, this design 
provides sufficient power to detect an effect equivalent to a change from no difference at baseline to a 
difference of d=.5 at the post-treatment point. In addition, we note that we have over 80% power to 
detect within group changes from baseline to end of treatment of d = .35 in the active treatment 
groups and d = .5 in the control group, small to medium effects using the conventions of Cohen. For 
the exploratory analyses, the relationships will be assessed using the entire sample. This yields 80% 
power to detect a correlation of r = .28 between measures at any time point; power for the model with 
time-varying covariates will be higher due to the repeated measures.  
 

In our pilot data, which examined performance on Cogpack training tasks in patients receiving two 
sessions per week over a 1 month period, we observed within group changes ranging from d = .5 
(connect task) to d = 2.5 (confusion task). While these effect sizes cannot be used directly to compute 
power for our primary hypotheses (since they involve different measures and only a single group) 
they do show that patients can experience large cognitive changes over a much shorter period and 
with a lower intensity intervention than what is planned for this study. Since we are powered to detect 
small to medium effect-sizes magnitudes, we should be in a strong position even if effects are smaller 
on the global cognitive and functioning batteries.