Visual Remediation in Schizophrenia
Phase: NA
Conditions: Schizophrenia, Schizoaffective Disorder
Sponsor: University of Rochester

 
 
Cover Page: Visual Remediation in Schizophrenia 
 
Study Numbers: 
NIMH: R61MH115119 
Rutgers IRB Protocol: Pro20170000922 
 
Date uploaded to Clinicaltrials.gov: October 13, 2017 
 
 
 
 

 
B. Significance 
 
There is a large body of research indicating that schizophrenia is characterized by visual perceptual 
deficits, with some impairments predating psychosis onset33-35. Indeed, visual distortions and anomalies, which 
are found in ~2/3 of individuals with schizophrenia36-38, are among the strongest predictors of conversion to 
schizophrenia-spectrum disorders among high-risk youth34;35;39. It has been shown that in many cases, the 
impairments on visual processing tasks observed in schizophrenia are not manifestations of a generalized 
deficit, and are independent of medication effects10;40-42. Importantly, visual impairments in schizophrenia are 
significantly related to poorer performance on tasks of visual-related cognitive functions (e.g., visual working 
memory13;29;43-45), impaired social cognitive function4;14;27;46-55, and worse community functioning1;14;47. Despite 
this growing literature regarding the significance of visual processing impairments in schizophrenia, there are 
no accepted visual remediation strategies for schizophrenia, and indeed, this issue has received almost no 
attention in the literature. Therefore, the goal of the proposed project is to identify a treatment that fills the 
unmet therapeutic need of alleviating visual perceptual difficulties and related cognitive and behavioral 
impairments in the disorder. We propose to assess the effects of two complementary forms of visual 
remediation. One targets the mechanism of gain control, and the other targets the mechanism of integration. 
We are using established tests of contrast sensitivity (CS) to operationalize gain control, and established tests 
of perceptual organization (PO) to operationalize integration. Gain control and integration were identified by the 
NIMH-sponsored Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia 
(CNTRICS) initiative as the two core impairments responsible for altered visual processing in schizophrenia26. 
CS and PO have been extensively studied in schizophrenia, their neural mechanisms are relatively well-
understood (as described later in this section), and their impairments predict higher-level dysfunction. For 
example, impaired CS has been demonstrated in psychophysical, electrophysiological, and brain imaging 
studies1;27-31, and is associated with failures in the later process of PO [Section D.1 Preliminary Data], as well 
as with poorer facial affect recognition27, reading13;43, cognition [29 and Section D.1], and community 
functioning1 in schizophrenia. PO impairments in schizophrenia have been observed in over 50 laboratory 
studiesreviewed in 7;8;10, including psychophysical10, ERP7;56 and fMRI investigations7;57;58. These visual integration 
difficulties have also been reported in the clinical literature, an example of which is: “I have to put things 
together in my head. If I look at my watch I see the watch, the watchstrap, face, hands, and so on, then I have 
to put them together to get it into one piece”59 (p 229). As with CS, PO deficits are associated with decrements in 
higher-level function: They are related to impairments in constructing visual representations such as faces from 
degraded stimuli4;46, forming visual memory representations44;45, and facial emotion decoding54. PO 
impairments are also related to poorer functional outcomes60;61. In addition, abnormal visual PO negatively 
predicted discharge to the community from a long-term inpatient psychiatric rehabilitation program better than 
neuropsychological measures of reaction time, attention, memory, and executive functioning, over a 3-year 
period62. Thus, impairments in both CS and PO have predicted poorer functioning. Consistent with this, 
structural equation modeling (SEM) studies indicate a single pathway from visual dysfunction to functional 
outcome, with mediating variables that include social cognition14;47;63. The finding of a single pathway supports 
a cascade model in which degraded visual representations contribute to difficulties in higher-level 
processing14;64, and “helps to provide a rationale for early perceptual and cognitive interventions, such as 
plasticity-based training”65;15 (p1223)
.   
 
Further motivation for a systematic attempt at visual remediation comes from a growing number of 
studies demonstrating that plasticity-based visual perceptual learning can occur in both healthy controls and 
individuals with schizophrenia20-24,25. We recently published a series of case studies demonstrating 
improvements in CS in schizophrenia using the CS training program proposed for the current project (66, and 
see section D.1). Moreover, previous studies of visual interventions with non-psychiatric samples, including the 
CS intervention proposed here, have demonstrated treatment-related gains that generalized beyond the 
trained visual function, including improved reading skills in controls21 and people with dyslexia67-69, and 
improved batting averages in college baseball players70, suggesting that improvements in low-level visual 
processes such as CS can lead to gains in real-world functioning. Regarding PO, we previously published a 
review on improvements in PO in schizophrenia after repeated task performance (typically over several days), 
based largely on a number of our earlier contour integration studies25. Several studies from other labs have 
also shown positive effects of perceptual learning-based training programs on visual function in schizophrenia. 
As noted, however, these investigations used small samples, lacked a control group, used training paradigms 
with a limited number of sessions, and/or focused on only a single visual task17-19. Finally, a body of work 
evaluating the effects of a cognitive training program that emphasizes auditory sensory processing has 
demonstrated significant treatment-related improvements in higher-level auditory and verbal functions in 

 
schizophrenia, such as verbal working memory and verbal learning65;71;72;73, suggesting that training low-level 
processes can contribute to improving higher-order cognitive functions dependent on that sensory modality. In 
short, enough evidence exists to suggest that remediation of visual function is possible, and that it could lead 
to gains in higher functions that rely on vision. However, despite this promise, and despite visual remediation 
being a well-developed field in its own right74;75, what is not known is whether, in a well-controlled study 
with a sufficient sample size and duration of treatment: a) visual processing can be significantly 
improved in schizophrenia; and b) improvements in visual processing will lead to improvements in 
higher-order cognition, social cognition, and functional capacity. Therefore, we propose to examine these 
important questions. We will do so by studying the effects of interventions that have either demonstrated 
positive effects on visual processing in multiple studies in non-psychiatric populations, or that are based on 
laboratory measures on which individuals with schizophrenia have demonstrated impairments, but also 
perceptual learning-based improvements, in multiple prior studies1-5;7;10;25;67-70;76. Based on: a) data showing 
strong evidence for visual impairments in schizophrenia that are thought to reflect core components of the 
disorder; b) relationships between these impairments and cognition, social cognition, functioning, illness 
course, and treatment outcome in cross-sectional, SEM, and longitudinal studies; and c) knowledge that visual 
processing can be improved in psychiatrically-healthy subjects and (based on preliminary data) in people with 
schizophrenia66, this intervention, if effective, has the potential to significantly reduce the burden of serious 
mental illness by improving perceptual and cognitive functioning in schizophrenia.  
 
As noted, the first level of remediation that we will evaluate targets gain control, in the form of CS. To 
remediate CS impairments in schizophrenia, we will use the ULTIMEYES (UE) computerized intervention, 
which targets CS across a wide range of spatial frequencies. UE is ready for early-phase testing in 
participants with schizophrenia, as it has been successfully developed as a computer application by Dr. Aaron 
Seitz (a co-investigator on this grant proposal)21;70;76.  
 
To assess target engagement for CS, we will use two complementary paradigms, one psychophysical 
and the other electrophysiological, both of which were recommended by the CNTRICS initiative to assess the 
construct of gain control in vision77;78. Psychophysical CS assesses the lowest level of contrast needed to 
detect stimuli presented at different spatial frequencies (SFs) (i.e., fine to broad lines corresponding to high to 
low SF, respectively). Studies of psychophysical CS show that people with schizophrenia need greater contrast 
(i.e., show lower CS) than controls to detect contrast across the ronange of SFs, although deficits in 
processing low SF (LSF) stimuli have been more pronounced in most studies of schizophrenia1;27;29;79. In 
addition, deficits in LSF processing are related to object recognition79 as well as to face and facial emotion 
processing deficits in schizophrenia4;46;48-52;55. Therefore, we focus primarily on CS for LSF stimuli. Because 
features within LSF stimuli are relatively large, there is less of an effect of acuity on those responses as 
opposed to fine-grained HSF stimuli that rely heavily on acuity. This helps to address the potential confound of 
impaired acuity in people with schizophrenia on task performance80. However, supporting the hypothesis that 
acuity was not driving past CS results are findings that the relationships between impaired CS and poorer 
facial emotion recognition, reading, visual learning, and PO in people with schizophrenia (13;27;29;81 and 
Preliminary Data) are strongest for LSF stimuli13;27;29;81. Electrophysiological CS involves recording the steady-
state visual evoked potential (ssVEP) in response to stimuli varying in contrast1;77;78;82;83. The ssVEP measure 
provides rapid, objective assessment of visual cortical responses to a range of contrast levels without requiring 
behavioral responses from participants. Studies of ssVEP in schizophrenia consistently show impairments, and 
these are most pronounced at low contrast levels1;27;84;85. Weaker ssVEP responses to contrast changes in 
schizophrenia are significantly correlated with behaviorally-assessed CS1, facial emotion recognition27, Global 
Assessment of Functioning (GAF) scores, and Problem Solving Factor scores on the Independent Living 
Scale1. 
 
The neural mechanisms involved in CS are relatively well understood. As noted above, CS has been 
viewed as a form of gain control77;86. Gain control involves both amplification and suppression of signals to 
keep neural activity at or near optimal levels; this homeostatic function thereby serves to reduce the risk of 
sensory deprivation-induced hallucinations with insufficient cortical activation87, and stimulus overload with 
excess activation26;86;88. Weaker signals, such as those involving low contrast and/or LSFs are amplified, and 
stronger signals are attenuated, with the full contrast-response function therefore following a classic sigmoidal 
curve. At the neural level, both amplification and attenuation are thought to arise from divisive normalization89-
91, in which target signal strength is modulated as a function of total activation in the cortical region1;27;82-84;92. 
Evidence that observer CS in a psychophysical task corresponds with level of neural activation, and that it is 
modulated by gain control, comes from several sources. One is that, using single-unit microelectrode recording 
in cat V1, the inverse U-shaped psychophysical CS function (CSF) was highly correlated with the neuronal 

 
CSF93. Another is that the fMRI BOLD response in V1 in humans covaries with contrast enhancement94 and 
SF95, with the relationship being especially tightly coupled for LSF stimuli96. In short, gain control keeps 
responses within an adaptively limited signaling range, and both of the CS assessment formats we propose to 
use generate data that can be interpreted clearly within cognitive neuroscience models of gain control in 
schizophrenia and healthy populations. 
 
The second level of remediation in the R61 targets integration, in the form of PO. We are focusing 
specifically on the visual PO function of contour integration. We have developed a program for contour 
integration training (CIT), via modification of a contour integration task developed for use in schizophrenia by 
Dr. Silverstein and colleagues, and used previously in multiple behavioral, ERP, and fMRI studies8;53;56-58;80. 
Our hypothesis regarding the ability of CIT to drive gains in PO is based on prior demonstrations of perceptual 
learning in controls and participants with schizophrenia (albeit at a slower rate in the latter group) with similar 
versions of this task8;25;60. For example, healthy controls showed improved detection of a collinear path over 12 
days of training97, improved performance on a closed contour integration task across test sessions that 
spanned 2 consecutive days98, and gains in identifying interpolated shapes over 4 days99. In addition, in 
monkeys, behavioral performance and V1 activity increased consistently over 10 days of contour integration 
training100. People with schizophrenia showed improved contour integration performance following 2-4 days of 
exposure to the task in the study cited above in which controls reached asymptotic performance after 2 days60, 
and improved pattern recognition across a single session of training involving 600 trials45;62. In addition, there 
are numerous studies that provide validity, reliability, and short-term perceptual learning data for the contour 
integration paradigm8;25;100. A further advantage of this task is that the neural mechanisms underlying 
performance have been demonstrated in monkeys and healthy humans101-105, and neural correlates of 
impairment (e.g., in V2, V3, V4, LOC, and frontal-parietal regions) have been identified in participants with 
schizophrenia57;58. Therefore, demonstration of improved performance after remediation would lead naturally to 
EEG and fMRI studies of training-related activation changes in specific regions of interest and brain networks. 
 
To assess target engagement for the PO intervention (CIT), we will use two tasks. The first is the 
original contour integration test recommended by the CNTRICS initiative for use in treatment studies of 
schizophrenia8, namely the Jittered Orientation Visual Integration (JOVI) task8;25;58. The JOVI involves 
identifying the direction of an egg-shaped contour made up of individual Gabor elements with gaps between 
them so that the participant has to perceptually integrate the Gabors to perceive the egg (see Fig. 3). The task 
has been optimized for use in clinical trials8;58 (see D.6.b). Although there are differences between the PO 
training task (CIT) and the JOVI in terms of the specific stimuli (i.e., circular vs. oval shapes, respectively) and 
response requirements (identifying the location of the target circle vs. indicating whether the centrally-
presented egg-shaped contour is pointing left or right), which should preclude confounds based on low-level 
perceptual learning (e.g., learning that is specific to one area of visual space, or to a single shape), we will also 
include a second outcome measure, one that does not share method variance with the training task. The 
second PO task uses the Ebbinghaus illusion, in which a center circle appears smaller if it is surrounded by 
(i.e., grouped with) larger circles and appears larger if it is surrounded by smaller circles (see Fig. 5). The task 
requires subjects to choose which display (on the left or right of the screen) contains the array with the larger 
central circle. By manipulating the difference between the actual sizes of the central circles, and whether the 
size of the surrounding circles causes the inner target circle to appear smaller or larger than its actual size, a 
psychophysically precise measure of illusion strength is obtained. Dr. Silverstein has used this task 
extensively106-109, and one of its appealing aspects is that, due to their reduced grouping of the central target 
and the surrounding circles, people with schizophrenia perform more accurately (in all studies cited above) 
than controls on trials in which surrounding context is normally misleading (e.g., when the larger of the two 
inner circles is made to appear smaller by surrounding it with large circles). Evidence that both the JOVI and 
Ebbinghaus tasks involve PO comes from a significant inverse correlation between scores such that a lower 
score on the JOVI is associated with higher scores in the misleading condition on the Ebbinghaus task107. 
 
As with CS, the neural mechanisms of PO, and of contour integration in particular, are relatively well 
understood. One involves long-range horizontal connections between orientation-tuned spatial frequency 
detectors in V1 (especially important for integrating closely spaced elements)97. A second involves reentrant 
feedback from V4 and higher visual areas to V1 and V2 (most important for grouping more distantly spaced 
elements)110-113 to amplify processing of elements belonging to a single contour, surface, or shape. Importantly, 
contour integration cannot be implemented purely by local spatial frequency detectors, or by orientation-tuned 
neurons with large receptive fields111;114; rather, integration of activity across sets of neurons is required. 
Single-cell studies in V1 suggest excitatory (facilitating) effects when contour elements are collinear, but not 
orthogonal, with a central target115;116. fMRI data in humans and monkeys101;102;105;117 indicate that V1, V2, V3, 

 
V4, and the LOC are more activated when processing Gabor-defined contours, in contrast to randomly-
oriented Gabors. In addition, activation of the prefrontal cortex and posterior parietal lobe are associated with 
successful contour integration, presumably as a source of feedback to occipital regions. However, it has been 
shown that impaired contour integration in schizophrenia is not due to inattention or random responding during 
task performance58;80. Both lateral excitation and top-down feedback, as implemented in contour integration, 
and in PO in general, are thought to involve synchronization of beta- and gamma-band oscillatory activity 
between neurons signaling contour elements (which are typically collinear or co-circular), and also between 
these temporary networks and top-down attention signals10;118-120. Relatedly, impaired PO in schizophrenia is 
associated with reduced synchrony within these bands119;121. This impairment is thought to reflect both NMDA 
receptor hypofunction and reduced GABAergic signalingreviewed in 86;122;123.   
Clear and refutable hypotheses of the R61 are: H1a) UE or UE&CIT will lead to significantly greater gains in 
CS than will ACCT and/or H1b) CIT or UE&CIT will produce significantly greater improvements in PO 
compared to ACCT. The Go Signal for continuing to the R33 will be a differential improvement, with an effect 
size of at least d=0.4, favoring UE or UE&CIT compared to ACCT on the psychophysical and/or 
electrophysiological CS task, and/or CIT or UE&CIT compared to ACCT on the JOVI and/or Ebbinghaus task. 
If a “go” signal is obtained, results of the R61 will be used to identify the most effective and efficient treatment 
(UE, CIT, or UE&CIT), and duration/dose, for use in the R33. 
Clear and refutable hypotheses of the R33 are: H1) The optimal treatment identified in the R61 (e.g., 
UE&CIT) will be more effective than the control treatment (ACCT) in improving CS or PO in a new and larger 
sample; and H2) Improvements in target function will be related to changes on visual cognitive (i.e., visual 
learning and memory, reading), social cognitive (i.e., facial emotion recognition) and functional capacity 
measures. If the hypotheses in the R33 are confirmed, the results will inform the design of a later RCT to 
assess the efficacy of a visual remediation treatment for schizophrenia on a wider range of outcome variables. 
Instructions for the R33 state that it “should not be powered as strong tests of clinical efficacy but rather should 
test the link between… target engagement and functional outcome.” Therefore, while we expect the 
correlations for R33 Aim 2 to be statistically significant, we do not hypothesize what the effect sizes will be. 
However, we would power a subsequent study based on the observed effect sizes in the R33.  
This project will advance knowledge of intervention and disease mechanisms, whether the trial results 
are positive or negative. In the R61, we will learn whether targeting either or both levels of visual function 
improves the perceptual targets. The assessment of whether changes in the visual targets drive changes in 
other functions in the R33 will provide information about disease mechanisms by clarifying the links between 
visual perception and cognitive and social cognitive function. We also wish to note that although there are 
multiple ways that a ‘go’ signal in the R61 can be achieved, each of these possibilities would represent a novel 
finding in its own right and motivate further studies of visual remediation in schizophrenia. More importantly, 
however, the R33 will serve, in part, as a replication and extension study of the R61: Observing that the 
optimal R61 intervention is effective in a second study, with a new and larger patient sample, and a similar 
degree of target engagement, would provide confidence that any R61 findings are not spurious.   
 
At a more basic level, as noted above, we are studying the effects of targeting basic forms of gain 
control and integrative processes on higher-level perceptual and cognitive processes. We are including two 
intervention components (UE and CIT) in order to explicitly target both CS and PO because there is evidence 
that both aspects of visual function are impaired in schizophrenia AND that impairments in both are related to 
poorer functioning in multiple domains. Because this is the first controlled study of perceptual remediation of 
these functions in schizophrenia, we wish to remain agnostic regarding whether the combined treatment 
(UE&CIT) will be more effective than either UE or CIT alone, although we anticipate that the combination may 
have additive or synergistic effects on one or both levels of vision. By assessing improvements related to the 
single treatment (UE or CIT) AND to the combined intervention at each level of vision, we will be able – at the 
end of the project – to provide a strong initial statement regarding the important question of differential and 
combined intervention effects. Future clinical trials will determine whether there are subgroups of individuals 
with schizophrenia (e.g., those who are more impaired on CS or PO at baseline) who are especially likely to 
benefit from these interventions. This is not a specific aim for this initial clinical trial because even people 
without visual impairment can improve their visual functioning21;70;76; however, our data will allow us to assess 
the degree to which improvement is a function of baseline CS and PO.  
C. Innovation 
This proposal is innovative in several respects. First, while there is a burgeoning literature on cognitive 
remediation in schizophrenia (e.g., 65;124-126), most of this work targets higher cognitive processes such as 
executive functioning and working memory, and assumes that perception is intact. As a result, despite the 

 
Figure 1 
 
Left:  Change in binocular acuity from pre- to post-test in UE-trained  
and untrained baseball players; Right: Change in contrast sensitivity 
from pre- to post training (higher scores represent better performance). 
 
large body of evidence showing impaired visual perceptual function in schizophrenia, the effects of visual 
training modules alone are virtually unstudied in this disorder. While CS and PO have been shown to be plastic 
in terms of performance improvement with repetition in prior laboratory studies, including in people with 
schizophrenia21;23;25;70;76, the effects of systematic visual training of these processes for longer than a few days 
have not yet been studied in this population in a controlled study. Second, unlike many cognitive remediation 
interventions that use games with unclear ‘doses’ for specific functions, we are targeting two well-understood 
perceptual processes with interventions that clearly target these processes26;77;78. Third, UE has been shown to 
improve CS in non-psychiatric samples, but has never been used in a controlled study of schizophrenia. 
Fourth, many current perceptual learning approaches emphasize single processing mechanisms and produce 
results that are specific to the trained stimulus features100;127, which has limited generalizability. The UE 
program addresses these issues by combining multiple perceptual learning approaches (e.g., engagement of 
attention, reinforcement) - each of which has been shown in past studies to contribute to increasing the speed, 
magnitude, and generalizability of improved CS - into an integrated perceptual learning application. UE has 
been shown to improve not only CS but also functioning in real-world activities21;70;76 (see Section D.1). Fifth, 
the PO training program we developed (CIT) is innovative (we were able to identify only one published paper 
on improving PO in any population128, and this was over 30 years old). Our proposed intervention is based on 
knowledge gained from our 30 years of studies in controls and patients about what factors contribute to PO, 
and how performance can change over time. Despite extensive evidence for PO impairment in schizophrenia7, 
little is known about the maximum extent to which it can be improved, the amount of training needed to obtain 
gains, the durability of gains, and their functional significance. Sixth, the additive and/or interactive effects of 
multiple forms of visual remediation have never been investigated. This would be the first examination of 
whether targeting both CS and PO is more effective than targeting either single process alone. The construct 
of gain control (operationalized here in the form of CS) and the construct of integration (operationalized as PO) 
were identified by the NIMH-sponsored CNTRICS initiative, and the RDoC cognitive domain, as high-priority 
cognitive neuroscience constructs relevant to schizophrenia and its treatment26. This study targets both levels. 
Seventh, we will examine training effects on higher-level processes with a focus on comparing effects on visual 
vs. non-visual cognition, which has not yet been done in a controlled study. 
D. Approach 
D.1 Preliminary Data  
 
UE pilot study: Pilot data from patients with schizophrenia at the Nathan Kline Institute (NKI) and 
Rutgers show good retention with 6 of 7 patients (86%) completing at least 30 sessions. This is similar to 
previous single-site cognitive remediation studies65;124 and to an average retention rate of 87% in a meta-
analysis of 40 cognitive remediation studies in schizophrenia129. This also matches the 93% retention rate of 
UE studies in healthy young adults carried out by Dr. Seitz (co-investigator and developer of UE). Preliminary 
data show UE is well tolerated, and even enjoyed, as described in our recent publication66. Across participants, 
CS improved 32%, with an increase in the peak contrast spatial frequency of 1 cycle/degree (pre-training peak 
spatial frequency of 3.14 ± 0.24 vs. post-training of 4.15 ± 0.70, p=.14, d=0.96). Additionally, patients improved 
on contour integration (p=.11, d=0.85). With such a small sample (N=6), our results were not statistically 
significant. However, the magnitude of CS improvement is similar to that from published studies of UE.  
 
UE findings in non-psychiatric samples: In previous research on UE conducted by Dr. Seitz, CS 
improved in healthy normal-sighted individuals after ~30 sessions of training76, with effect sizes ranging from 
d=1.6 for LSF to 0.63 for HSF stimuli. In another 
study, college baseball players displayed significant 
improvements in CS (Fig. 1) and batting average70 
after UE training, with effect sizes ranging from d=0.34 
to 0.59 (with the lowest effect size for CS to HSF 
stimuli). Additionally, university students demonstrated 
improved reading ability after UE training. Specifically, 
reading acuity improved an average of 13% (d=0.38), 
moving from a pre-training mean logMAR acuity of -
0.06 to a post training value of -0.11, (SD=0.02). 
Reading speed improved 13% (d=0.57), moving from 
a pre-training mean value of 240.0 words/minute to a 
post-training value of 270.6 words/minute 
(SD=8.28)21. In addition, older adults with presbyopia 
displayed improved CS after undergoing UE training21. It is important to note that in the studies of UE in which 

 
CS was assessed21;70;76, CS improved significantly, as seen in a shift upward across spatial frequencies (see 
Fig. 1). Effect sizes were relatively large in the trained group in these studies and the average d for LSFs, 
which is the target for this proposal, ranged from 0.45 to 1.0 across studies. Based on these data and our pilot 
data in patients described above, we expect UE to lead to significant gains in CS in schizophrenia.  
 
Preliminary and related data that motivate the targeting of CS: In an ongoing study in Dr. Silverstein’s 
lab (N=17 thus far), we have found that lower peak CS is related to poorer contour integration (r=.69, p<.01). In 
a recently completed study in Dr. Butler’s lab (N=32), we found that lower CS at 1 cycle/degree is related to 
poorer performance on the WAIS PO Index (r=.41, p=.02) and the MATRICS visual learning domain (r=.46, 
p=.006) in people with schizophrenia. In addition, a cluster analysis showed that people with schizophrenia 
who were more impaired on CS were also more impaired on speed of processing, PO, visual learning, and 
emotion recognition (p=0.02 to <0.001), but not on verbal working memory, verbal learning, or symptoms (p ≥ 
0.05), suggesting that our visual targets are not manifestations of a generalized deficit130. These data fit current 
models in which CS occurs very early during visual processing, whereas PO is an integrative process that 
occurs later and involves binding of feature representations (whose quality is determined in part by CS). In 
addition to effects of low CS on PO, studies have shown that participants with schizophrenia who have 
impaired CS have greater reading deficits13;43, and poorer facial emotion detection27. Further, in pilot work 
using structural equation modeling (SEM), we have found relationships between abnormal VEPs and impaired 
visual learning and PO that were significantly mediated by CS131. In short, there is reason to expect that 
improving both CS and PO will lead to higher-level changes in perception and cognition.  
D.2 Inclusion/Exclusion Criteria for R61 and R33  
Inclusion: 1) SCID-5 diagnosis of schizophrenia; 2) 18-60 years old; 3) speaks English; 4) able to complete 
the MATRICS Consensus Cognitive Battery (MCCB) at the baseline assessment (for R33); 5) a raw score of 
37 or greater on the Wide Range Achievement Test, Reading subtest (WRAT-3), to establish a minimum 
reading level (6th grade) and to estimate premorbid IQ; and 6) clinically stable as indicated by no antipsychotic 
medication changes in the last month or if on depot, no change in the past 2 months. Exclusion: 1) history of 
intellectual disability, or developmental or neurological disorder; 2) history of brain trauma associated with loss 
of consciousness for > 10 minutes or behavioral sequelae; 3) alcohol or substance use disorder within the last 
6 months; and 4) history of eye disease (e.g., glaucoma, retinopathy). Effects of tobacco use and medication 
dose equivalents132, including an index of anticholinergic load133, will be explored in data analyses.  
D.3 R61 Phase 
Aims: (i) To evaluate the effects of UE and CIT on the CS and PO targets, respectively; (ii) to determine if the 
criterion for continuing to the R33 phase is met; and (iii) if the criterion is met, to determine the most effective 
intervention condition and optimal duration of treatment, to inform the R33 study design.  
Study design: 80 subjects will be enrolled in this study: 20 per arm. 40 will be recruited at each site (Rutgers 
and NKI). The intervention will continue for 40 sessions, with targets assessed before training, after every 10 
sessions, and at 6 months post-training for a total of 6 visual assessments. With 3 sessions per week, the 
intervention will take between 13-14 weeks. Each site will enroll ~ 2 participants/month, beginning after the first 
half of Y1, which is similar to what Keefe et al.72 estimated as a “reasonable rate of recruitment for a large-
scale efficacy trial” of cognitive remediation. Because, at the 6-month follow-up, nearly all patients are 
expected to still be in the partial hospital program, or an outpatient program (at Rutgers), or on inpatient units 
at the Rockland Psychiatric Center (RPC) or NKI, we expect attrition to be minimal. However, several methods, 
including monthly phone calls (see Recruitment and Study Timeline), will be used to maximize retention.  For 
the R61 and R33, training sessions will be run in small groups by front-line staff who have already received 
training in these interventions, or whom we will train, with no more than a 3:1 participant:staff ratio. 
Randomization: Subjects will be randomly assigned, within site, to one of the 4 conditions (UE&ACCT, 
CIT&ACCT, UE&CIT and ACCT&ACCT) in a ratio of 1:1:1:1. The treatment assignment will be made after a 
subject has met all entry criteria and completed baseline testing, to avoid bias.  
Milestones (Go/No-Go Criterion): We will proceed to the R33 phase if: 1) the UE-related effect size (i.e., the 
effect size of the difference between the UE&ACCT (or UE&CIT) and ACCT&ACCT groups in the degree of 
change in CS) is greater than or equal to Cohen’s d=0.4 for either the psychophysical or ssVEP CS task; 
and/or 2) the CIT-related effect size (i.e., the effect size of the difference between CIT&ACCT (or UE&CIT) and 
ACCT&ACCT groups in the change on either of the PO tasks) is greater than or equal to d=0.4. Pre-post 
change scores for CS and PO target assessments will be calculated for each individual and used to determine 
effect sizes between groups. We will not control for baseline values consistent with recommendations to use 
“straight” change scores when examining cognitive change across two time points134-140. 
Rationale for our effect size choice: The effect size criterion we have chosen for the R61 “go” signal (d=0.4) 

 
is similar to that observed in many studies of cognitive remediation, and of other treatments for this population, 
such as skills training and family psycho-education124;126;141;142.  However, less is known about effect sizes of 
perceptual remediation, and most of the evidence on this in schizophrenia comes from studies of auditory 
remediation using the Posit Science auditory training module65;71;72, which includes training on both low-level 
auditory targets and higher-level auditory-verbal cognition (e.g., verbal working memory and learning)71;143. 
Results from one study indicated an improvement in the target of auditory-processing speed71 that was of large 
effect (d=0.875). The authors also observed a medium-large effect on global cognition (d=0.73). Results from 
other studies of this auditory training module in schizophrenia have indicated large treatment effects (d=0.86) 
for both verbal learning and global cognition, and a medium effect (d=~0.65) on the auditory target of P50 
gating65;143.  While these effect sizes are larger than our chosen criterion (d=.4), it is also important to note that 
some studies of Posit Science modules have not demonstrated significant improvement on non-trained 
tasks72;144.  Moreover, across studies, the largest effects have tended to come from studies where daily training 
(5 days a week) was used, and subjects were paid for completing training sessions, and these are two 
conditions that can rarely be met in real world psychiatric clinics. These considerations have informed our 
choice of the ‘go signal’ criterion (i.e., d=.4), because there are as of yet very few published studies of visual 
remediation in schizophrenia. One small (N=9) uncontrolled study of visual backward masking training found 
an effect size of d=.43 for improvement in the MATRICS domain of Visual Learning19. Within our group, Dr. 
Silverstein observed an improvement in contour integration performance among participants with 
schizophrenia after 4 consecutive days of practice on a contour integration task (phi=0.63, which corresponds 
to a large effect)60. Even larger effect sizes were seen for changes in CS (d=0.96), and PO (d=0.85) in our 
small pilot sample of patients with schizophrenia (Section D1), but given the small sample size and lack of a 
control group in that study it can be assumed that the real effect size is lower. Thus, findings from these initial 
evaluations of visual remediation support our use of d=0.4 as a conservative level of change on the outcome 
measures and as a “go” signal for target engagement. However, we acknowledge that it is not yet clear from 
the literature how an effect of this size relates to meaningful improvements in visual and higher-order cognitive 
processing, and/or functional capacity. The proposed R33 will allow us to address this question in a preliminary 
manner. If results from this trial are positive, we will seek funding for a larger trial to evaluate the impact of this 
treatment on functional outcomes, and to identify mediators/moderators of treatment response. 
If the Go criterion is met for any of the treatment conditions, we will perform a thorough investigation of 
the effects of UE, CIT, and UE&CIT on the CS and PO target scores to determine which remediation strategy 
to use for the R33. Analyses will also include (i) assessment of the trajectory of performance on the target 
measures over the course of treatment; (ii) determinations of whether the improvements plateau prior to the 
40th session or whether they continue throughout the training period; and (iii) evaluations of whether any 
combined effects of UE and CIT are additive or multiplicative. These goals will be accomplished by first 
graphically examining the trajectories of target change to assess whether they are linear, monotonic non-linear, 
quadratic, or any other shape. After that, appropriate models for longitudinal data analysis will be applied to 
estimate improvement rate and time to asymptote. We will account for CPZ-equivalent dose of antipsychotic 
medications in all models, using CPZ dose as a time-varying covariate if necessary, and will also account for 
type of antipsychotic medication and anticholinergic load. Those models will also be used to examine whether 
baseline characteristics moderate the effect of UE and/or CIT on the targets. These analyses will allow us to 
ascertain: 1) whether UE alone, by targeting CS function, has a cascading effect on PO; 2) whether CIT 
improves CS while targeting PO function; and 3) whether UE&CIT has a stronger effect than either intervention 
alone for any outcome. Based on these results, the optimal intervention will be determined based on it having a 
significantly larger effect size for at least one target. If all 3 treatment conditions are effective to an equivalent 
degree, the criterion will be reaching asymptotic level of improvement earliest.  
Sample size determination:  
The sample size of the R61 study (n=20/group) was selected to ensure that when the true size of the effect of 
UE or UE&CIT on the CS target, or CIT or UE&CIT on the PO target, is d=0.4, the 95% confidence interval (CI) 
for the effect size does not contain zero. Given data on the CS measure over time in the UE pilot study 
described earlier, a 95% confidence interval for an effect size of magnitude 0.4 is between .02 and .91. Since 
the observed effect size in that pilot data was actually much larger, 0.96, we are confident that we will be 
adequately powered to detect a meaningful effect. Since patients also improved on a measure of contour 
integration (d=0.85) in the pilot study, even though training was focused only on CS (our low-level visual 
target), setting the effect size at d=0.4 for both CS and PO seems reasonable. Note that although contour 
integration improved without PO training in the pilot study, this was unlikely due to practice effects on the test 
alone since two prior large studies did not find practice effects on the JOVI, in either healthy controls or 

 
patients, over two or three repeated presentations separated by days or weeks145;146, and a third study found 
improvements only with daily exposure to two versions of the task, and this did not occur for the schizophrenia 
group until the third day25;60. Subjects who do not complete all 40 sessions of training will be invited to 
complete a “post-treatment” assessment after their last session; for non-completers who decline to participate 
in a post-treatment evaluation, the last post-baseline assessment will be used, unless the participant dropped 
out before the 10th session (the time of 1st post-baseline assessment), in which case his/her data will be not be 
used in the analyses. In such cases, we will recruit additional participants to reach the target sample size. We 
expect minimal dropout since most participants will be long-stay inpatients or partial hospital patients who are 
present on a nearly daily basis. For any dropout that does occur, we expect rates to be uniform across 
conditions, given that we have designed all conditions, including the active control, to be similarly engaging.  
Sufficient patients are available at both sites to recruit new subjects to replace any who discontinue.  
D.4 R33 Phase 
Aims: (i) To replicate and extend R61 results supporting initial visual target engagement using the optimal R61 
treatment, in a new and larger sample; and (ii) to determine if visual target engagement is associated with 
improvements in specific cognitive (i.e., visual working memory, visual learning and memory, reading) and 
social cognitive (i.e., facial emotion recognition) outcomes, as well as with changes in functional capacity.  
Study design: The R33 will be a two parallel-arm RCT comparing the optimal R61 treatment to the control 
(ACCT) treatment. 100 subjects will be enrolled over 3 years, 50 from NKI and 50 from Rutgers. Visual and 
clinical outcome assessments will be conducted at baseline, and at intervals determined based on R61 results, 
including a 6-month follow-up (with attrition considerations and procedures identical to the R61 (see D.3).  
Randomization: Subjects will be randomly assigned, within site, to the optimal or control treatment in a ratio of 
1:1. Treatment assignment for eligible subjects will occur after completion of baseline testing, to avoid bias.  
Assessments: Visual Targets and Cognitive, Social Cognitive, and Functional Capacity. No matter which 
intervention is used for the R33, visual tests will include both tests of CS, and both tests of PO used in the R61. 
See below (section D.6.c) for descriptions of the cognitive, social cognitive, and functional capacity measures. 
Data analysis: An intention to treat approach to data analysis will be used in this clinical trial. For all analyses, 
statistical significance will be defined as p < 0.05, unless specified otherwise. Bonferroni corrections will be 
applied to multiple testing, as appropriate. H1: The optimal R61 treatment will be more effective than the 
control treatment (ACCT) in improving CS and/or PO test scores (to be determined based on the R61 
outcome). This will be tested using a linear mixed effects model in which the values of the target(s) at each 
time point are modeled as a function of treatment group (experimental, control), time, time x group, and 
potential moderators and mediators (e.g., age). We will use Akaike’s Information Criterion (AIC) as the 
deciding metric to determine the optimal model to account for within-subject correlations between repeated 
measures (e.g., autoregressive of order 1, AR(1), which assumes stronger within-person correlation for 
measurements closer in time, or other structures). If the time x group interaction is significant, we will use 
model-based estimation procedures to estimate the magnitude of the effect. We will also explore differential 
effects of the treatment on CS vs. PO. H2: Improvements in visual processing, as observed in CS and/or PO 
(based on R61 results), will be related to changes on specific cognitive (i.e., visual working memory, visual 
learning and memory, reading), social cognitive (i.e., emotion recognition), and functional capacity measures. 
We will assess correlations between visual target scores and cognition, social cognition, and functional 
capacity, and also evaluate whether changes in the target(s) either mediate or moderate treatment effects on 
these outcomes. An approach and computational tool described by Hayes147 will be used to model any 
mediation and /or moderation effects, including indirect effects in models that involve mediation.  
Sample size determination: The sample size for the RCT in the R33 phase was selected to ensure sufficient 
power to detect medium effects of the experimental intervention on the target(s). For Aim 1 of the R33, 50 
subjects per condition allows 80% power for a 2-tailed test with a=0.05 to detect d=0.57. For Aim 2, with n=50 
in the active perceptual training group, correlations of at least r=0.38 between changes in performance on 
target measures (CS and/or PO) and changes in cognitive, social cognitive, and functional capacity can be 
detected with 80% power using a 2-tailed test with a=0.05. Also, for Aim 2, n=50 (i.e., active perceptual 
intervention only) allows for detecting a correlation of r=0.43 when making a strict Bonferroni adjustment for 3 
outcomes (2-tailed a=0.017), and r=0.51 when correcting for 15 outcomes (2-tailed a=0.003). In accordance 
with instructions that the R33 “should not be powered as a strong test of clinical efficacy…”, our focus on effect 
size is exploratory and not confirmatory. We will use our observed effect sizes to power a later RCT. 
D.5 Interventions 
ULTIMEYES (UE) Training: The UE training procedure was developed by Dr. Seitz and colleagues at 
UCR70;76. The program uses video game-based custom software, and the training stimuli consist of Gabor 

 
patches (game “targets”) at 6 SFs (1, 2, 4, 8, 16 and 32 cycles/degree), and 8 orientations (22.5°- 337.5°). We 
describe this program as a “video-game” because numerous elements were introduced to its design with the 
goal of promoting task engagement and user enjoyment. For instance, points are given each time a target is 
selected (and taken away when distractors are selected), and levels increase in difficulty throughout training. 
At the beginning of each session a calibration is run to determine the initial contrast values for each SF to be 
displayed during the training exercises. Each session consists of 8-12 training exercises that last 
approximately 2 minutes each for a total of ~25 min. The 
participant’s task is to click on all the Gabor targets as 
quickly as possible. The first few exercises consist of only 
targets, but distractors are added as the training progresses 
(Fig. 2). Throughout training, distractors become more 
similar to the targets (starting off as blobs, then oriented 
patterns, then noise patches of the same SF as the targets). 
Targets that are not selected in time start flickering at a 20-
Hz frequency, to attract attention148. At higher levels, targets 
and distractors appear and disappear when not selected 
quickly enough. Many parameters are adjusted based on 
ongoing participant performance, including contrast (using a 
3/1 staircase for each SF), number of stimuli per trial, and 
presentation rate (determined by tracking average response times on prior trials for each SF). 
Contour Integration Training (CIT): The CIT program was developed by co-investigator Dr. Seitz and is 
based largely on two contour integration tasks we developed and have used in multiple studies of visual PO in 
schizophrenia 8;80. There are two PO exercises used for this program, which are presented in alternating blocks 
of individual trials. Target stimuli in both exercises consist of 
contours that are formed by fragmented paths of individual 
Gabor elements, which are embedded within an array of 
noise Gabors. For one of the exercises, the participant’s task 
is to detect and click on the circular contour formed by a set 
of target Gabors. Difficulty level is manipulated by varying 
the degree of orientational jitter of the Gabors making up the 
target contour (see Fig. 3), which is done within block, and 
by varying the number of elements that make up the circle, 
which is done between blocks. The degree of jitter is 
determined adaptively using a ‘3 up, 1 down’ staircase at 
steps of 1 degree; jitter values and element density were 
chosen based on data from multiple previous studies with 
patients and controls8;25;58;149. For the other exercise, 
orientational and positional jitter of contour elements are 
systematically added to increase task difficulty over time. In 
addition, several basic discriminations will be included to 
promote generalization, including those involving shapes (e.g., circles vs. ellipses) and numbers (e.g., ‘2’ vs. 
‘5’). For both exercises, the arrays of Gabor elements have a peak SF of 4 cycles/degree (to eliminate potential 
effects related to impairments in processing LSFs) and a Gaussian envelope SD of 7.3 arcmin. Like UE, CIT is 
presented as a game: Participants are provided with feedback about their response accuracy, points are given 
for each correct response, and positive feedback is provided when participants progress to the next difficulty 
level. This program also uses a staircase procedure to automatically adjust the current difficulty level based on 
recent performance so that it becomes more challenging as performance improves; this feature is designed to 
drive performance gains, and to continuously challenge participants while ensuring continued success. Each 
session consists of 8-12 training exercises that last approximately 2 minutes, for a total of ~25 min.   
Active Computer-Based Control Treatment (ACCT): Our control condition is a cognitively challenging 
remediation program that does not specifically target perception. MyBrainSolutions (MBS; Brain Resource, 
Inc.) is a suite of online games and exercises targeting the domains of: 1) cognition (attention and memory); 2) 
emotion regulation (using imagery, and breathing rate–based biofeedback); and 3) goal setting and attainment 
(using individualized goals, reminders, feedback, and problem solving suggestions). It has been used 
extensively in workplace settings and via the internet to promote wellness and employee productivity150;151. Dr. 
Silverstein has previously used MBS clinically for cognitive remediation of patients with psychosis since 2010. 
Figure 2: UE targets and distractors 
 
Figure 3: Examples of 
orientational jitter 
effects added to the 
egg-shaped contour 
from the JOVI task. 
This manipulation will 
also be used for 
circular and other CIT 
stimuli. 

 
D.6 Assessments 
Standardized protocols including written instructions and scripts will be used at both sites for each test. VEPs 
will be obtained using an EvokeDx device with the active electrode over the occipital lobe (Oz). EvokeDx has 
FDA 510(k) clearance for assessment of visual neural function. It generates the stimuli, records and analyzes 
the electrophysiological signals, and stores the data. Psychophysical CS will also be performed using the 
EvokeDx, which utilizes an organic LED display that enables accurate linearization of the voltage-to-luminance 
relationship through customized gamma correction so that precise specification of contrast can be achieved. 
These features, in addition to the carefully calibrated amplifiers contained in the system, afford high 
reliability/reproducibility of stimulus presentation and VEPs collected with multiple EvokeDx devices, which is 
critical when testing at multiple sites. The same stimulus parameters and testing conditions will be used at the 
Rutgers and NKI sites, and automated luminance calibration will be performed monthly at each site using the 
photometric device provided with the EvokeDx by Konan medical. Amplifier settings will be as follows: 
gain=20K, bandpass filter=0.5–100 Hz. It should also be noted that an earlier version of the system now 
provided by Konan equipment for assessing CS was successfully used in a prior multi-site trial152. The JOVI 
has also been successfully used in prior multi-site studies8;58. For all luminance and contrast calibrations of 
monitors used for PO assessments, and for UE and CIT training, a photometer will be used initially and 
annually, and Spyder 3 Elite software will be used weekly, with gamma set to 1.0 (i.e., linearized).  
D.6.a Diagnostic and Clinical Assessments for R61 and R33  
Diagnosis: The Structured Clinical Interview for DSM-5 (SCID-5)153 and all available clinical information will be 
used to assign a consensus diagnosis. 
Verbal IQ estimate: WRAT-III, reading subtest. The recognition and pronunciation of printed words is 
particularly resistant to the effects of deterioration associated with brain disease and is considered to be an 
estimate of premorbid IQ154. 
Symptoms: The Positive and Negative Syndrome Scale (PANSS) assesses the presence and severity of 
symptoms commonly found in schizophrenia; it is a semi-structured interview. There are a total of 30 items155.   
Suicidal Ideation and Behavior: The Columbia-Suicide Severity Rating Scale (C-SSRS)156. This will allow the 
investigators to determine if participants have suicidal ideation or behavior. This will be used at baseline and at 
the end of the intervention. Crisis service staff will be contacted at once if suicidal ideation or behavior is found. 
Reliability assessment: For all clinical and cognitive assessment measures, research assistants from both sites 
will be trained by Dr. Judy Thompson at the beginning of the study, and through annual booster sessions. 
Training will follow our typical protocol and involve didactic training, group viewing and discussion of training 
videos for the interview measures and all individual items, and individual rating of additional videos until 
reliability criteria are achieved. These are: 1) for PANSS - intraclass correlations (ICC) of 0.80 or higher 
between each rater and our existing gold standard, and an overall group ICC of 0.80; and 2) for SCID and C-
SSRS, kappas of 0.80 or higher between each rater and our gold standard and between each rater pair. 
Trainees will also observe more senior interviewers administering these clinical measures (for other ongoing 
studies), and then be observed administering these measures by Dr. Thompson or Dr. Nolan before they 
conduct assessments for this study on their own, to ensure appropriate skill level in working with patients.  
Other: Smoking: Recent and typical tobacco use, and tobacco use disorder will be assessed with a smoking 
history and the Fagerström Test for Nicotine Dependence157. 
D.6.b Visual Targets 
Contrast Sensitivity: CS functions will be obtained by presenting 5 horizontal sine-wave gratings at the 
following SFs: 0.5, 1, 4, 7, and 21 cycles per degree. Spatial frequency is the number of pairs or cycles of light 
and dark bars in 1 degree of visual angle, expressed as cycles/degree, with fewer pairs corresponding to lower 
SF. Each grating will be presented for 32 milliseconds. An up-and-down transformed response method will be 
used to obtain contrast thresholds with a criterion of 70.7% correct responses for each SF. The mean of 10 
reversals will be used to obtain thresholds. Presentation of the different SF gratings will be interleaved in a 
random order. A spatial 2-alternative forced-choice procedure will be used. Gratings will be presented on either 
the right or left side of the screen, and the participant’s task is to determine on which side the gratings 
appeared. Results will be plotted as CS (which is the reciprocal of threshold) vs. SF. Increased CS indicates 
better performance. Participants will be tested binocularly after being light-adapted to the background 
luminance of the display for 15 minutes. Test re-test reliability of this measure in a group of 15 controls and 31 
patients (tested at the Butler lab at NKI) was an ICC of .76 at 0.5 cpd and .67 and 1 cpd. The test-retest 
reliability is weaker at the peak SF of 4 cpd (.25) and improves with higher SFs (ICC=.69 for 7 cpd and .57 for 
21 cpd). The target variable is the average CS for the two LSFs (0.5 cpd and 1 cpd). We expect to see more of 
an effect of the remediation on LSF, but we will also assess CS at the other SFs, and specifically compare LSF 

 
results to results at 7 cpd, which also has high reliability, to determine if effects are LSF-specific.  
VEP Contrast Responses: This VEP technique was developed by Dr. Vance Zemon and colleagues83 and has 
been used in studies of schizophrenia 1;27;28, autism82, and glaucoma detection152. The response measures are 
quickly and easily obtained, requiring no behavioral response from the participant. Parameters to be used have 
been optimized in our studies of schizophrenia1;84. Steady-state VEPs are elicited to checkerboard patterns  
that are luminance-modulated sinusoidally (~12 Hz) with contrast increases in 7 discrete octave steps. Each 
step is ~1.6 sec in duration to yield an entire contrast-
response function in less than 10 seconds (Fig. 4). The 
initial step has 0% depth of modulation (DOM) and this is 
followed by steps of 1, 2, 4, 8, 16, and 32% DOM. The 
set of steps is presented 10 times. In the contrast 
response function, as the DOM rises, the signal-to-noise 
ratio (SNR) increases from below a value of 1 to a value 
greater than 1. To obtain the contrast at which SNR=1 (i.e., the contrast threshold), linear interpolation will be 
done for the first two consecutive contrasts (DOMs) at which SNR is less than one and then greater than one 
158. Test-retest reliability of low-contrast VEP responses in schizophrenia (N=32) is good (ICC=0.70; Butler lab, 
unpublished data). In addition, the 95% confidence regions for the 10 runs per person show good reliability 
within an individual83. Dr. Butler has observed a within-subjects correlation of r=.41, (p<0.001; N=74) between 
indices from these VEP and psychophysical CS assessments.  
Jittered Orientation Visual Integration (JOVI) Task8;57;58: Stimuli consist of oval contours, made up of 18 Gabor 
elements separated by 1° of visual angle, that either point left or right (Fig. 3). The contours are embedded in 
298 distractor Gabors. Difficulty is manipulated by increasing the degree of orientational jitter of the Gabors 
making up the contour. Jitter levels will be 7°, 9°, 11°, 13°, and 15°, as in recent studies. Trials will be blocked 
according to the amount of orientational jitter, with 12 trials per block. Blocks will be presented in increasing 
order of difficulty, with each block presented 4 times for a total of 240 trials (4 repetitions x 5 blocks x 12 trials). 
In addition, each block will contain 4 catch trials in which a contour with no orientational jitter is presented 
without background elements, or is presented with background elements but with a line drawn along the 
contour. These trials are included to identify subjects who respond randomly or who are not paying adequate 
attention to the task. As in past studies, only subjects who obtain 75% or higher accuracy on these trials will be 
included in data analyses. Each stimulus is shown for 2 seconds, followed by a 1 second inter-stimulus 
interval. The participant presses a right or left arrow key to indicate the direction of the contour. There will be 
practice trials prior to the task, using the format in past studies. This task was optimized for use with 
participants with schizophrenia in a previous 5-site study8, which found good test-retest reliability145. The 
dependent variable is number correct, corrected for guessing (to equate with subjects who respond when 
unsure of the correct answer, who will be right 50% of the time).  
Ebbinghaus Illusion Task108;159-161. On each experimental trial, subjects are shown two target circles—one on 
the left of the screen and one on the right, and their task is to indicate which is larger. On half the trials, these 
circles are presented by themselves (i.e., the no-context condition). On the other half, the 
targets are surrounded by larger or smaller circles that either facilitate perceiving the true 
size difference of the target circles (helpful condition: the larger inner circle is surrounded 
by smaller circles, making it appear larger than its actual size, and the smaller inner circle 
is surrounded by larger circles, making it appear smaller than its actual size, and these 
effects combine to amplify the real size difference between the target circles; see Fig. 5, 
where the target circle on the right is 2% larger in each of the 3 panels), or hinder 
perceiving the true size difference (misleading condition: the larger inner circle is 
surrounded by larger circles, making it appear smaller than its actual size, and the 
smaller inner circle is surrounded by smaller circles, making it appear larger than its 
actual size). Stimuli remain on the screen until the subject responds or for 2 seconds 
(whichever occurs first). If a response is not recorded within 2 seconds, the trial is 
recorded as a guess (0.5 correct). Trials are separated by 200 msec. The two target 
circles always differ in actual size and this size difference varies in magnitude across 
trials. The order of trial types is randomized for each subject, as is the side on which the 
larger inner circle appears on each trial. In total, the task contains 192 trials, and typically 
takes 7 minutes. The key metric from this task is the difference between the helpful and 
misleading conditions, controlling for no-context performance, or: [(Helpful – no context) – (misleading – no 
context)].  Reduced grouping is reflected in scores closer to 0. 
Figure 4: VEP Contrast stimuli examples 
Figure 5. Examples 
of the 3 Ebbinghaus 
task conditions. 

 
Visual Acuity: While not a target for this study, acuity will be assessed to determine whether it moderates the 
effects of UE and/or CIT4;162. We will use ETDRS charts, which are the “gold standard” for acuity testing163.  
D.6.c Other Outcome Measures for R33 
MATRICS Consensus Cognitive Battery (MCCB): The MCCB assesses multiple cognitive domains: Speed of 
Processing, Attention/Vigilance, Working Memory (visual and verbal), Verbal Learning, Visual Learning, 
Reasoning and Problem Solving, and Social Cognition164;165. The ICC for the MCCB composite score was 0.9 
in the initial validation study and has been similarly high in multisite clinical trials165-168. Outcomes are T-scores 
for each of the domains and the composite score164;165 (number of scores=8). In addition, exploratory analyses 
will assess whether treatment effects on visual working memory and visual learning are stronger than for non-
visual memory and learning subtests.  
Minnesota Low-Vision Reading Test (MNREAD): This test assesses reading speed ability. The charts contain 
19 English sentences (60 characters each) with print sizes ranging from 1.3 to -0.5 logMAR at a distance of 16 
inches (0.41 meters). Participants are instructed to read each sentence aloud as quickly and as accurately as 
possible. Outcomes are reading acuity, speed, and critical print size (number of scores=3). The MNREAD is 
resistant to practice effects and has strong test-retest reliability169.  
Penn Emotion Recognition Test (ER-40): This computerized task comprises 40 photographs of actors 
expressing one of 4 basic emotions (happiness, sadness, anger, fear) or a neutral expression170. The outcome 
variable is total percent correct (number of scores=1). The ER-40 has been used widely including in multi-site 
studies (e.g.,171). The ER-40 demonstrates sound convergent and discriminant validity and good test-retest 
reliability in participants with schizophrenia [ICC=.75172]. 
University of California, San Diego Performance Based Skills Assessment, 2nd Edition (UPSA-2): This is a 
performance-based measure of the extent to which participants are capable of performing specific living skills 
such as household chores, communication, finance, transportation, and planning recreational activities173. We 
will use the total score, which ranges from 0 to 100 (number of scores=1). Test-retest reliability is 0.63-0.80 
over periods of up to 36 months174. UPSA scores significantly predict residential independence175;176.  
D.7 Clinical Research Data Management: The Innovative Clinical Research Solutions (ICRS) group at NKI 
will conduct data management and data quality assurance for this study. The ICRS has been providing data 
management support for research studies for over 35 years, including for numerous schizophrenia studies 
funded by the NIMH. ICRS will develop all study Case Report Forms to standardize data collection. A 
comprehensive web-based data acquisition and management system, Acquire, will be programmed to process, 
edit and store all study data in a centralized database. ICRS personnel will implement rigorous data 
editing/validation using the Acquire system to ensure the highest possible level of data accuracy. ICRS 
personnel will review and monitor the completeness and accuracy of study data throughout the study, and 
deliver locked data sets to Dr. Gara at the end of both the R61 and R33 phases. 
D.8 Combined Expertise of the Research Team: Drs. Silverstein and Butler have over 30 and 20 years of 
experience, respectively, in vision research in schizophrenia, expertise and publications in general and social 
cognition, track records of recruitment and assessment of individuals with schizophrenia for NIMH grants, and 
a track record of working and publishing together. Their respective foci on CS (Butler) and PO (Silverstein) 
provides particular synergy for this project. In addition, Dr. Silverstein has delivered cognitive remediation 
interventions for schizophrenia patients since 1994. Dr. Seitz is an expert in perceptual learning and in 
development of scientifically principled brain games such as UE. Dr. Gara has over 30 years of experience in 
designing and analyzing data from longitudinal efficacy and multi-site data. Drs. Nolan and Thompson are 
experienced in clinical trial project management and in cognitive and clinical assessment of individuals with 
schizophrenia. Dr. Robinson directs the NKI ICRS group, with 35+ years of experience in data management. 
D.9 Governance and Organizational Structure for Conducting Study within Specified Timelines: Drs. 
Silverstein and Butler will be PIs of the overall grant and will be responsible for its implementation, progress, 
data collection, supervision, coordination, and fiscal management. Drs. Silverstein, Butler, and  Seitz will have 
primary responsibility for the guidance and fiscal management of relevant aspects of the study at their 
respective institutions. Dr. Silverstein will lead weekly calls with key personnel to ensure that all timeline goals 
are met. He will also lead weekly data management calls with ICRS personnel and all research assistants.  
D.10 Feasibility of the Approach: All of the elements are in place to carry out recruitment, remediation, and 
data analysis in a timely manner. Rutgers and NKI have on-site clinics that will be used for recruitment and 
treatment of patients, as in many past studies. Both sites have personnel trained in use of all measures. The 
UE program is fully developed and tested, and the CIT training program is currently in use in an initial study at 
Rutgers. Target and clinical outcome measures already exist. The ICRS data management group is in place.