New Applications of Neuroplasticity Biomarkers in Veterans With Traumatic Brain Injury or Schizophrenia
Phase: NA
Conditions: Schizophrenia, Traumatic Brain Injury
Sponsor: VA Office of Research and Development

Neuroplasticity in TBI and Schizophrenia 
Principal Investigator: Jonathan K. Wynn, Ph.D. 
NCT03995368 
February 26, 2024 
 
 

A. Research Plan 
Veterans with cognitive deficits represent a substantial service and financial burden at the Veterans 
Administration (VA). Importantly, even with treatment, these Veterans have severe problems with community 
integration1, 2, defined as the ability to return to full participation in major life roles including competitive 
employment, school, and supportive social/family networks. Two prominent patient groups within the VA with 
cognitive deficits and poor community integration are schizophrenia (SCZ) and traumatic brain injury (TBI). 
SCZ and TBI are common, devastating conditions among Veterans and require high levels of VA healthcare 
and disability resources. The average annual treatment cost is $31,000/patient with SCZ 3 and three times as 
high for Veterans with TBI compared to those without 4. While SCZ and TBI differ in terms of etiology and 
clinical presentation (SCZ is considered a neurodevelopmental disorder 5 while TBI is acquired), the 
determinants of poor community integration are overlapping in the two disorders: both share features of social 
6 and non-social cognitive deficits7, 8, which are both highly related to poor community integration9-11. Most of 
the research on connections to community integration has been done in SCZ and the associations are 
generally stronger for social cognition than non-social cognition 12.  Evidence indicates that neuroplasticity 
impairments underlie cognitive deficits in both SCZ and TBI. This SPiRE aims to examine neuroplasticity in 
these two disorders using novel neurophysiological measures and to evaluate the statistical properties of those 
measures in each patient population, a necessary step for determining whether they are suitable for assessing 
individual differences and to serve as biomarkers in future treatment studies. 
A1. Neuroplasticity: Neuroplasticity is defined as the malleability of neural organization in response to both 
endogenous experiences (e.g., cognitive functioning, emotions) and exogenous experiences (e.g., 
neurostimulation using electricity or magnetic pulses, pharmacological agents). Neuroplasticity is typically 
studied on two different time frames: short term potentiation (STP), which is the transient facilitation or 
depression of synaptic activity posited to underlie processes such as sensory adaptation on the order of 
seconds13, 14, and long-term potentiation (LTP), which is an enduring structural change of the synapse lasting 
hours to months. Neuroplasticity is posited to be the neural basis of learning and memory15. 
A2. The relevance of neuroplasticity to SCZ and TBI: There is strong evidence that both SCZ and TBI are 
associated with impaired neuroplasticity16, 17. Dysfunctional neuroplasticity is implicated in SCZ patients’ 
cognitive deficits18. Animal models demonstrate that impairments in neuroplasticity are present after injury in 
TBI17. Neuroplasticity, including both STP and LTP, is thought to be mediated by N-methyl-D-aspartate 
(NMDA) receptors. One of the leading neurochemical hypotheses of schizophrenia is that it involves NMDA 
receptor dysfunction19, with NMDA antagonists (e.g., ketamine) inducing schizophrenia-like symptoms in 
healthy individuals20. In TBI, alterations of the NMDA receptor after trauma are thought to lead to excitotoxic 
damage21 and subsequently impaired neuroplasticity. These findings implicate NMDA-mediated neuroplasticity 
in both SCZ and TBI. While the NMDA system may be involved in both disorders, we do not know if the same 
or different mechanisms contribute to dysfunctional neuroplasticity. New treatments that target the root causes 
of cognitive deficits in SCZ and TBI would be highly valuable for VA’s efforts to promote interventions in these 
Veteran populations. Correspondingly, it is critical to develop objective outcome measures to evaluate the 
efficacy of such interventions. The current proposal addresses this critical treatment development prerequisite 
by building on our work with non-invasive EEG paradigms designed to assess neuroplasticity in vivo.  
A3. EEG assessments of neuroplasticity: STP can be assessed reliably with auditory mismatch negativity 
(MMN), an EEG response to a “deviant” stimulus that interrupts a stream of identical stimuli22. MMN deficits 
have been well-documented in patients with SCZ23 and have been linked to deficits in non-social cognition, 
social cognition24 and daily functioning25. However, much less is known about MMN in people with TBI. Only 
three studies have been published and the findings are mixed (one showing a deficit, one showing normal 
response, and one showing increased MMN compared to healthy controls)26-28. “Traditional” MMN paradigms 
have been used extensively in SCZ; recently there has been work on optimizing the methods to better assess 
STP by using a “roving” type of MMN paradigm, in which the deviant stimulus becomes the standard stimulus 
until the next deviant which in turn becomes the standard. By varying the number of repetitions before a 
deviant, one can examine the capacity to encode new information via STP-related processes. As the number 
of repetitions increases, the slope (or strength) of the MMN also increases, reflecting STP29. The roving MMN 
has rarely been used in SCZ29-31 and never in TBI, making this a novel area of exploration.  
LTP assessments were previously limited exclusively to animal models or excised cortical tissue from 
humans32. However, non-invasive methods for assessing LTP-like plasticity in humans have recently been 
adapted by our lab and others30, 32, 33, and they have begun to be applied to clinical populations such as SCZ 
and depression.  These methods focus on visual plasticity and assess EEG responses before and after 
modulation using high-frequency visual stimulation (HFS) or, alternatively, using extended repeated exposure, 
which mimics electrical tetanization used in animal or cellular studies. EEG responses after modulation are 
larger in amplitude, demonstrate the LTP hallmark of input specificity (i.e., only responses to the same stimulus 

used in HFS are enhanced), and last for up to an hour31, 32. To date, there have been only four published 
papers examining LTP-like plasticity before and after visual modulation in SCZ30, 32-34, and only two of these 
examined patient-control differences32, 34, with results showing deficits in SCZ. While there are few studies, 
correlations between plasticity measures and non-social cognition have been reported in SCZ 33, 35 and HC 36. 
A4. Neuroplasticity treatment applications for SCZ and TBI: TBI and SCZ are both characterized by broad 
cognitive impairments (including both non-social and social cognition) determined by multiple factors and are 
related to community integration.  While we can measure cognition and community integration very well, we do 
not yet have a full understanding of the root causes of these impairments. We know that neuroplasticity is a 
fundamental brain process that underlies important non-social functions such as learning and memory, and 
social cognitive functions, such as emotion and facial affect processing. Thus, it is a very attractive area for 
clinical investigation as it provides a basic mechanistic understanding of the root causes underlying cognitive 
dysfunction in TBI and SCZ, at cellular and neural levels. Altered neuroplasticity can potentially explain a wide 
range of cognitive deficits affecting the daily functioning of Veterans with these conditions.  
It is clear that current treatments are limited and do not lead to functionally meaningful improvements for most 
patients. To make progress in treatment development, we need to identify clearly specified treatment targets 
that are amenable to direct intervention. Beyond providing insights into the nature of cognitive impairments in 
these conditions, this line of investigation can also guide the development of novel neuroplasticity-enhancing 
interventions for Veterans. New neuroplasticity-focused interventions that improve cognitive deficits, and 
thereby enhance community integration, in SCZ and TBI will be highly valuable for VA healthcare. Several 
behavioral and neurostimulation-based neuroplasticity treatments have emerged (e.g., cognitive remediation 
and transcranial direct current or magnetic stimulation, respectively). To apply and evaluate these methods in 
SCZ and TBI, it is important to have validated measures of neuroplasticity suitable for use as endpoints in 
clinical trials to evaluate the efficacy of these approaches. As these potential biomarkers assess neural activity, 
they provide a more direct (and perhaps more temporally associated) measure of treatment effects than 
behavioral cognitive tasks. If our results indicate that distinct aspects of neuroplasticity are differentially 
impacted in TBI vs. SCZ, this would have implications for selective, targeted interventions that address their 
core deficits. These biomarkers also have broad translational value in animal models for drug development.   
B. Innovation, Treatment Implications, and Future Directions 
We view this proposal as a necessary first step that will provide innovative insights into neuroplasticity in 
Veterans with neurodevelopmental or acquired cognitive disorders and will help inform treatment development 
in future studies. Examining EEG-based measures of neuroplasticity is a small but growing area of research 
that has not yet been extended to Veterans, except for work by our own lab in Veterans with schizophrenia. 
Regarding innovation, this would be the first study to examine in vivo neuroplasticity measures (both STP and 
LTP) in Veterans with TBI. Regarding treatment implications, we can use the assessment tools derived from 
this study to test the effectiveness of plasticity-based interventions, including specialized cognitive remediation 
or neurostimulation approaches, on improving cognition and community integration in Veterans with cognitive 
disorders. It is also possible to use the ERPs to predict treatment response; for example, MMN has been 
shown to predict treatment response to cognitive remediation in SCZ 37. Our VA Research Enhancement 
Award Program (REAP) on Community Integration in Homeless Veterans (M. Green, PI) has shown that SCZ 
and TBI are major risk factors for homelessness and barriers to community reintegration among Veterans. A 
novel future direction could extend our assessments of and treatments for 
neuroplasticity to homeless Veterans. Finally, we could examine 
physiological factors that influence plasticity biomarkers derived from this 
study. For example, evidence shows that abnormal neuroinflammation, 
seen in both SCZ38 and TBI39, impairs plasticity and cognition in 
animals38. Examining how neuroinflammation and neuroplasticity interact 
in Veterans with these disorders would be highly informative and point to 
anti-inflammatory treatments to improve plasticity and cognition. 
C. Preliminary Studies 
A focus of our lab has been to examine determinants of functional 
outcome and community integration in Veterans with SCZ and other 
serious mental illnesses using self-report, clinical interviews, behavior, 
EEG, and neuroimaging. Our work in SCZ demonstrates that the PI and 
research team are qualified to conduct the proposed research in 
Veterans with TBI, given the similar disturbances in cognition and functional outcome. In this section we 
discuss our EEG studies of neuroplasticity in Veterans with SCZ. The goals of this SPiRE are to examine 
neuroplasticity in SCZ and TBI using novel EEG methods, to provide an objective biomarker to assess 
neuroplasticity, and to understand how determinants of outcome (e.g., cognition) are related to neuroplasticity. 

Roving mismatch negativity (rMMN): We recently published a study examining the relationship between 
MMN and auditory hallucinations in SCZ40. This study utilized one version of the roving MMN paradigm that is 
proposed in the current application (see D5 below). In our study, we found that the ERP response to the 
deviant increased in amplitude as the number of standards presented increased, reflecting STP. However, this 
increase in STP was significantly smaller in SCZ than in healthy controls (Figure 1).  
Long-Term Potentiation (LTP): Our lab recently published 
on EEG-based measures of LTP in vivo in Veterans with 
SCZ and healthy controls30; this was only the third such 
study published in this population. As discussed in Section 
A, LTP is assessed in this paradigm by comparing visual 
evoked potentials before and after HFS. We performed t-
tests on post- minus pre-HFS difference waves and 
subjected them to data-driven mass univariate analyses 
(correcting for the vast number of comparisons) to identify 
time windows and electrodes with clear signals (Figure 2). 
The difference waves are plotted as topographical maps; in 
the raster plot, significant post-pre HFS differences at each time sample and electrode are shown in blue, 
demonstrating significant LTP between 140-227 ms over parieto-occipital electrodes 2 minutes after HFS. We 
utilized the same paradigm in the only other paper examining SCZ-control differences in LTP32. However, more 
recent paradigms have been developed with improved features, such as the ability to evaluate input specificity 
and longer time frames for LTP assessment, so we will use a newer approach in the current study (see D5). 
D. Research Design and Methods 
D1. Study 
Overview: 
This is a 2-
year study to 
assess EEG-
based 
biomarkers of STP and LTP in Veterans with (either SCZ or TBI) or without (healthy Veterans) cognitive 
disorders. This study will leverage three aspects of existing research infrastructure at the GLA: 1) the VISN 22 
MIRECC (laboratory assessment space, interviewer training); 2) the MIRECC Data Core (statistical and data 
management/quality assurance support); and 3) the REAP (Director: Michael Green, Ph.D.). These are fully 
described in the Resources section. Institutional Review Board (IRB) and start-up activities, including creating 
a secure on-line data entry and storage system with the Data Core, will be accomplished in the first quarter of 
the study. Recruitment will continue up through Q3, Year 2. Q4 of Year 2 will focus on data analysis, 
dissemination through scientific presentations and publications, and preparation of a MERIT application. 
D2. Participants and Recruitment: We will recruit 25 participants in each patient group and 25 healthy 
Veterans (total N = 75). The groups will be comparable on key demographics (i.e., parental education, gender). 
Veterans with SCZ will be recruited from the GLA Psychosis Clinic and our MIRECC Patient Registry. Veterans 
with TBI will be recruited from the Neurobehavior Clinic (directed by Dr. Mario Mendez, co-I on this proposal), 
and the Polytrauma Clinic at GLA. Selection criteria for all participants include: 1) age 25-55; 2) no other 
neurological or medical condition interfering with providing informed consent or valid assessment; 3) not 
meeting diagnostic criteria for current depression based on the Structured Clinical Interview for DSM-5 (SCID-
I)41 or depressive symptoms rated moderate or higher (a rating of 13 or higher on the Hamilton Depression 
Rating Scale 42); 4) no DSM-V substance use disorder greater than moderate severity in the past 3 months; 5) 
no form of cognitive remediation in the 6 months prior to testing; 6) an 8th grade reading level assessed with 
the Wide Range Achievement Test (WRAT 43); and 7) normal or corrected-to-normal vision and hearing. The 
age range was chosen to exclude younger participants whose brain development and plasticity is still 
occurring44, 45, and a conservative upper range where age-related cognitive declines may prominently begin46, 
47. Exclusion criteria for all patient participants include: 1) changes in medication dosage or type 3 months prior 
to testing; 2) hospitalization for psychiatric health in the 3 months prior to testing; 3) changes in housing status 
in the 6 months prior to testing. Full inclusion/exclusion criteria and expected ethnicity/race/gender 
breakdowns are shown in Human Subjects.  
Clinical Diagnosis: For SCZ, diagnosis will be made with the SCID-I and information from the medical chart. All 
interviewers are trained through the Treatment Unit of the VA VISN 22 MIRECC to a minimum kappa of 0.75 
for key psychotic and mood items, and a minimum intraclass correlation of 0.8048. For TBI, participants will 
have had a concussive or closed-head injury as identified in a structured TBI interview49 and meet a mild (n = 
Table 1: Timeline of Activities (per quarter of project)
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Startup
Recruitment and Data Collection (n = 12-13 per quarter)
Analysis, Write-Up, MERIT Application
Year 1
Year 2

12) or moderate (n = 13) diagnosis of TBI based on criteria adopted by the VA50. All TBI participants must be at 
least 6 months post injury to be enrolled. We elected to not recruit participants with severe TBI as this is the 
most intractable form of TBI, with lengthy hospitalization and extensive rehabilitation. For mild TBI, criteria 
include evidence of impact to the head resulting in a loss of consciousness (LOC) ≤ 30 minutes with one or 
more of the following: posttraumatic amnesia, disorientation or confusion, and best Modified Glasgow Coma 
Scale (GCS)51, 52 of 13-15 in the first 24 hours after injury. For moderate TBI, criteria include evidence of impact 
to the head resulting in a loss of consciousness (LOC) > 30 minutes and < 24 hours with one or more of the 
following: alteration of consciousness > 24 hours, post-traumatic amnesia > 1 and < 7 days, and best GCS of 
9-12 in the first 24 hours after injury. Further exclusion criteria for TBI patients include other neurological 
sequelae (e.g., focal neurological signs or symptoms or evidence of an abnormal computed tomography or 
magnetic resonance imaging scan). For SCZ, further exclusion criteria include head trauma or injury with LOC 
(LOC due to other non-concussive injuries lasting < 5 minutes will be acceptable). 
D3. Demographic and Medication Considerations: We will use a naturalistic sample of Veterans with TBI or 
SCZ, which will make the results more generalizable to these disorders. Using a naturalistic sample within the 
context of the SPiRE mechanism will inform us about how to match groups in future studies.  An additional 
methodological concern is the number and variety of psychotropic medications for those in the patient groups, 
including antipsychotics, antidepressants and mood stabilizers, stimulants, and anxiolytics. Unfortunately, there 
is little we can do about the potential concern of long-term polypharmacy, as that is inherent to the two patient 
groups. We will attempt to partially address potential effects of medications on our dependent variables using 
the following approach. We will carefully record all information, via self-report and inspection of medical 
records, about psychiatric medications and examine relationships to the plasticity measures. Sedatives and 
benzodiazepines, which may affect performance on behavioral and electrophysiological measures, will not be 
permitted within 12 hours of testing. 
D4. Clinical interviews and scales: A comprehensive psychiatric and social history form developed by our 
lab will be used to record additional information that may be of interest to consider in secondary analyses, such 
as duration of illness, socioeconomic status, and cigarette smoking status. We will administer the SCID44 to all 
potential participants, and the SCID-Personality Disorders53 to healthy Veterans only. Clinical symptoms for all 
participants will be assessed with the Expanded Brief Psychiatric Rating Scale54, the Clinical Assessment 
Interview for Negative Symptoms55, the Hamilton Depression Rating Scale42, the Patient Health 
Questionnaire56, the Young Mania Rating Scale57, PTSD Checklist (PCL-5)58, and the Addiction Severity 
Index59. These measures will be used to characterize the samples and explore relationships to plasticity. 
D5. ERP Recording and Analysis Procedures: ERP recording and processing will use existing equipment in 
the lab of Dr. Green at the VISN22 MIRECC (see Facilities and Other Resources). Stimulus presentation and 
EEG data synchronization will use Presentation (Neurobehavioral Systems, Inc, Berkeley, CA). EEG will be 
collected continuously using a 64-channel BioSemi ActiveTwo amplifier (BioSemi, Germany), sampled at 512 
Hz from DC to 100 Hz. Four electrodes to monitor horizontal and vertical electrooculogram will be used to 
correct for eye blinks and other movements using established methods60. Data will be processed with Brain 
Vision Analyzer 2, EEGLab61, Mass Univariate Analysis Toolbox62, and PCA Toolbox63 using established 
methods to obtain and analyze ERPs (e.g., 64-66).  
Evaluation of Within-Session Reliability (Internal Consistency): 
In order to validly use ERPs to make inferences, ERP 
components must demonstrate acceptable reliability67, 68. ERP 
score reliability provides an estimate of signal-to-noise ratio 
(SNR). Ensuring adequate reliability is critical when comparing 
ERP scores from different task conditions, because condition 
differences can be obscured by low SNR. Similarly, low score 
reliability imposes an upper limit on correlations with other 
variables, such as cognitive scores. Hence, poor score 
reliability can limit effect sizes for both between-condition 
differences and correlations with other variables. We will use 
the ERP Reliability Analysis (ERA) Toolbox, which utilizes G 
Theory-based algorithms to estimate reliability67. The ERA toolbox also provides an estimate for the length of a 
task that is needed to achieve a particular reliability score for all conditions and groups and in this way serves 
to optimize the length of a task for clinical research. Recent publication guidelines from leading journals require 
reliability estimates be published and recommend a cutoff of 0.8 for an ERP to be considered reliable.  
Short-term Plasticity – Roving Mismatch Negativity (rMMN) (30 min): We will utilize a rMMN paradigm69 that 
can assess STP by systematically manipulating the number of standard stimuli that appear before a deviant. 
The rMMN presents a series of identical “standard” stimuli for a set number of repetitions (i.e., either 2, 6 or 36 

times) followed by a “deviant” stimulus (differs in frequency from the standards). With each change in the 
standard series, the deviant stimulus changes in pitch (in 50 Hz steps between 700-1200 Hz) relative to the 
preceding series of standards, resulting in distinct auditory stimuli that serve as both standards and deviants 
during the run. Subjects will ignore the tones and perform a visual attention task (press a button when fixation 
cross changes contrast) which serves to direct attention away from the tones. A schematic of the paradigm is 
shown in Figure 3. Stimuli are presented in 4, 5-minute blocks, with a 60 s break after each block. rMMN will 
be presented in between post-modulation blocks in the LTP task (see below). Auditory stimuli, presented via 
earphones, consist of 80 dB tones; the interstimulus 
interval is 400 ms. There are 85 deviant trials in each 
block. Data will be processed with established methods40: 
segmented (-100 to +500 ms time-locked to stimulus 
onset), ocular correction81, baseline correction, and finally 
artifact rejection. MMN is scored as the mean amplitude 
between 100-200 ms over fronto-central electrodes (F1, 
Fz, F2, FC1, FCz, FC2) for the difference between 
deviants – standards. Plasticity is defined as the change in 
slope of MMN amplitudes over the change in the number 
of standards (i.e., difference in MMN amplitude after the 
most standards (36) and fewest standards (2)), with a 
larger slope indicating greater plasticity.  
Feasibility Data: Data from a sample of SCZ patients is 
presented in Preliminary Studies. For TBI, we piloted 
this task in two individuals to demonstrate valid ERPs 
can be obtained. Figure 4 shows ERP difference waves 
after short, medium, and long standard repetitions. 
MMN can be observed as a negative voltage between 
100-200 ms that increases in size in response to larger 
number of standard stimulus repetitions. These data 
demonstrate that people with TBI provide valid data in 
the expected direction, suggesting that this task can be 
validly administered in the proposed sample.  
Long-term Plasticity – Visual Modulation Paradigm: We will assess visual evoked potentials (VEPs) before and 
after extended exposure (i.e., “visual modulation”) to assess LTP-like 
plasticity, modeled after 70 and adapted by our lab. Stimuli consist of 
two different checkerboard pattern stimuli: one comprised of large 
black and white checks and the other comprised of small black and 
white checks. Only the large checkerboard pattern will be used in the 
modulation block; this will be done to assess input specificity (i.e., 
plasticity should only be seen to large but not small checkerboards). 
On alternating trials within a block, the checkerboard pattern reverses 
color (i.e., black becomes white and white becomes black). The 
checkerboard stimuli include a small red central dot to facilitate gaze 
fixation. The task includes 2 baseline blocks, 1 10-minute modulation 
block, and 3 post-modulation blocks occurring 5, 15, and 25 min after 
the modulation block (Figure 5). Prior to modulation, the large and 
small checkerboard stimuli are presented in separate 
(counterbalanced) blocks, for a total of 80 stimuli for each type of 
stimulus. For the modulation block, only the large checkerboard is presented for a total of 10 minutes (i.e., 
1200 reversals). A total of 40 large and 40 small checkerboard stimuli are presented in separate blocks in each 
of the three post-modulation blocks. All stimuli are presented at 2 Hz.   
We will utilize a data-driven approach to identify time windows and electrodes that show significant differences 
post-pre modulation 32, 61, focusing on time regions and electrodes overlapping with the early sensory VEPs 
C1, P1, and N1 that occur between 50-250 ms. Once these are identified, a PCA63, 71 applied to the original 
waveforms will be used to isolate ERP components (e.g., C1, P1, N1) falling within time windows showing 
significant effects. Amplitudes will be calculated for each identified component and used in analyses. This 
method provides an objective, unbiased method of selecting components that show task-related modulation.  
Feasibility Data: Data from a sample of SCZ using a similar paradigm is presented in Preliminary Studies. For 
TBI, we piloted the new task in 2 individuals to demonstrate that valid waveforms can be obtained. Figure 6 

shows VEPs recorded before modulation (“baseline”) and 5, 15, and 25 minutes after modulation (Post 1, 2 
and 3, respectively). The P1 VEP (positive voltage at ~120 ms) increases in amplitude after 10-minute 
modulation using modulated stimuli (i.e., large checkerboards; top of figure) but not to non-modulated stimuli 
(bottom of figure). These data demonstrate that people with TBI can perform the task and provide valid data, 
lending confidence that this task can be successfully used in the proposed sample.  
D6. Cognitive Assessments: 
Non-social cognition: MATRICS Consensus Cognitive Battery (MCCB)72, 73: The MCCB assesses 6 
domains of cognitive functioning: speed of processing, attention/vigilance, working memory, verbal learning, 
visual learning, and reasoning/problem solving. Raw values are converted to t-scores adjusted for age and 
gender. An overall composite score is calculated.  Time: 60 min. 
Social cognition: Empathic Accuracy (EA) task74: The EA task consists of 13 video clips lasting 2.0-2.5 
minutes of an individual (“target”) discussing a positive or negative experience. After speaking of their 
experience, the targets provided a continuous rating of how they were feeling. Participants view each video clip 
and continuously rate how they think the target is feeling. The primary dependent variable is the average 
correlation between the participant’s and target’s ratings. Time: 30 min. 
Social cognition: Facial Emotion Recognition (FER) task75: The FER consists of faces of Caucasian and 
Asian actors portraying one of 6 emotions (afraid, angry, disgust, happy, sad, surprise) or neutral, drawn from 
a facial expression stimulus data library76. The participant selects the expression they think is correct.  Eight 
trials per expression are shown. The primary dependent variable is the total number correct. Time: 15 min. 
D7. Community Integration Measures: We will use three complementary scales: 1) the Role Functioning 
Scale (RFS)77, which assesses aspects of work, independent living, and family/social connections; 2) the 
Lubben Social Network Scale (LSNS)78; and, 3) the Community Integration Questionnaire (CIQ)79. We have 
extensive experience with all scales.  We will combine the summary scores from each measure to obtain a 
standardized community integration composite score to be used in analyses. Time: 15 min. 
D8. Design Considerations:  For this SPiRE, we elected to recruit Veteran with any mild or moderate TBI 
diagnosis from local VA clinics, rather than selecting based on type (e.g., blast vs. impact, closed vs. open) as 
the sample will be more representative of our VA. We realize the sample may be heterogeneous, with 
differences in TBI injury, types/doses of medications (e.g., anxiolytics, antidepressants, stimulants), and in co-
morbid diagnoses (e.g., post-traumatic stress disorder, PTSD). Regarding PTSD, we will assess for presence 
(meeting DSM-5 criteria) and severity of symptoms (i.e., PCL-5) and examine relationships to the plasticity 
measures. We will include type of head injury in exploratory analyses. Regarding neuroplasticity assessment, 
we could have used fMRI or alternative EEG methods. We chose EEG as there are no behavioral measures, 
and EEG is easier to assess and disseminate in VA clinics than expensive and burdensome fMRI. We chose to 
assess both STP and LTP as they assess different aspects of neuroplasticity: LTP results in changes at the 
synapse (e.g., alterations in the number and location of AMPA receptors), whereas STP results in transient 
changes in synaptic activity not due to structural alterations. Group comparisons are not part of this grant or 
encouraged by this grant mechanism and we will not formally test for them. However, the data may allow us to 
see differences in patterns that will suggest differences or similarities in underlying mechanisms and 
relationships to cognition and community integration in the two patient groups.  Given the novel and innovative 
nature of the research questions, as well as the inclusion of two disorders with similar cognitive deficits, the 
data from this study will be informative in guiding paradigm development and parameters to be used in a larger 
Merit. The inclusion of healthy Veterans without cognitive impairments will also be beneficial as these plasticity 
paradigms have rarely, if ever, been used in these Veterans, and we can apply the same questions of 
tolerability and feasibility to this group to refine future versions of the tasks to be used in larger grants that will 
examine group differences. 
D9. Analytic Plan: Consistent with the SPiRE mechanism, statistical analyses will be more descriptive than 
inferential. For Aim 1 we will assess whether specific targets are met such that at least 90% of those recruited 
in each group (a) complete the EEG measures and demonstrate tolerability (based on subject self-report 
utilizing a questionnaire developed in our lab; see Appendix 1); and (b) provide high quality EEG data 
uncontaminated by noise or artifacts and cleaned via traditional methods (e.g., eye-blink correction, artifact 
rejection).  We will also determine the average number of trials needed and the fraction of subjects who fail to 
achieve within-session reliability (cutoff of 0.8 for internal consistency), allowing us to optimize the paradigms 
for future studies. For Aim 2, we will examine the distributional properties of the neuroplasticity measures in 
each group to ensure that they show sufficient variability to be useful as potential biomarkers, provide 
estimates of key parameters (e.g., mean, SD), and inform the need for transformations or other specialized 
analytic approaches. For Exploratory Aim 3 we will use correlational analyses to assess the relationships of 
neuroplasticity measures with downstream cognitive and functional outcomes as well as demographic and 
clinical characteristics, as well as the relationships between the two neuroplasticity measures themselves. 

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