(C-STAR) Center for the Study of Aphasia Recovery Modeling Treated Recovery From Aphasia
Phase: NA
Conditions: Aphasia, Stroke, Stroke, Ischemic, Aphasia, Broca, Aphasia, Global, Aphasia, Mixed, Aphasia, Jargon, Aphasia, Expressive, Aphasia, Conduction, Aphasia, Fluent, Aphasia, Anomic
Sponsor: University of South Carolina

 
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C-STAR – Center for the Study of Aphasia Recovery Modeling Treated Recovery from 
Aphasia 
NCT03416738 
Unique Protocol ID: Pro00053559 
U.S. NIH Grant/Contract Award # P50DC014664 
 
Study Protocol (Version 14) and Research Plan 
April 20, 2020 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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Human Subjects Research Proposal 
Study Title: Center for the Study of Aphasia Recovery (C-STAR)  
Project 001(032)1: Modeling Treated Recovery from Aphasia 
Project 003(038): Combining Behavior, Neuroimaging and Biomarkers to Predict 
Language Deficits after Stroke 
Principle Investigators: Julius Fridriksson, Ph.D., Christopher Rorden, Ph.D. 
 
Table of Contents: 
A. Abstract………………………………………………………………………………………..p. 3 
B. Background and Significance…………………………………………………………p. 3 
C. Specific Aims and Hypotheses………………………………………………………..p. 6 
D. Data Collection…………………………………………………………………………….. p. 8 
E. Data Analysis………………………………………………………………………………...p. 14 
F. Protection of Human Subjects……………………………………………………….. p. 15 
G. References and Literature Citations………………………………………………..p. 20 
H. Appendix A – Study Protocol….………………………………………………………p. 24 
I. Appendix B – Scripts for Treatment Tasks……………….………………………p. 34 
J. Appendix C – COVID Remote Protocol………………………….………………….p. 49 
K. Appendix D – POLAR Research Plan………………………………………………p. 50 
L. Appendix E – Clinical Core Research Plan……………………………………….p. 65 
 
 
 
1 Note, project times here are consistent with project names in attached grant 
submission  

 
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A. Abstract 
 
Stroke is the leading cause of serious adult disability in the United States. One of the 
most devastating impairments resulting from stroke is aphasia, a language impairment 
caused by left hemisphere damage involving cortical language areas. Although it is generally 
accepted that behavioral aphasia treatment is effective, different patients experience very 
different degrees of benefit from aphasia treatment, and the relationship between patient 
factors and treatment response is poorly understood. Moreover, few reliable prognostic 
indicators have been identified. Therefore, the purpose of the current project is to investigate 
a variety of factors (e.g., biographical, cognitive/linguistic, and patterns of brain damage) 
that predict an individual's response to aphasia treatment. To this end, the current 
submission is one part of a large, multi-center collaboration, with this specific project 
focused on assessment and treatment of 120 post-stroke individuals in the chronic phase of 
stroke (>12 months post-onset). In a crossover design, two different treatments will be 
studied, over the course of a 39-week period (including rest periods). Following the 
completion of treatments, we will model participants' response to therapy based on 
biographical, cognitive/linguistic variables, as well as patterns of brain damage. An 
additional 30 individuals will be recruited for evaluation, but will not complete treatment.  In 
the protocol to follow, we have outlined human subjects information relevant to testing that 
will take place at the University of South Carolina or the Medical University of South 
Carolina.  
 
Please note that this constitutes the first phase of the overall project (NIH submitted 
grant is included in this submission), and that additional projects will stem from the results 
found here (and in turn, will likely require either amendments to the current IRB or entirely 
new IRB submissions at later dates). 
 
  
B. Background and Significance 
Background 
Speech/language therapy for the management of aphasic impairments is generally 
shown to be effective. However, the reasons that certain treatments may work for some 
individuals, and not others, and why some individuals do not respond to treatment is 
largely unknown.  Two recent Cochrane reviews of behavioral aphasia treatment suggest 
that although aphasia treatment may be effective, no specific treatments have emerged as 
standards of care (1, 2). After decades of research, no general consensus has been reached 
regarding which aspects of language or communication abilities should be treated, how 
treatment should proceed, or which factors are important for predicting aphasia treatment 
success. As a result, individuals with aphasia receive treatment relying on an assortment of 
approaches, often with very minimal scientific data to support their utility. Additionally, 
prediction of long-term outcomes typically takes a “wait and see” approach. Accordingly, 
clinicians who routinely treat patients with aphasia have very limited empirical data to 
guide their treatment and predict outcome. Whereas biomarker studies are common in 
medicine, almost no studies have been carried out to understand the relationship between 
patient factors and aphasia rehabilitation potential in stroke (3-5). This is a major problem, 
as valuable resources are probably wasted because time and funds available to rehabilitate 
individual patients are likely limited. Whereas single case or small-group studies are helpful 
for testing different aspects of aphasia treatment, the time is ripe for larger scale studies 
that rely on “big data” approaches to answer general questions regarding what should be 
treated and who is most likely to respond to treatment. Over time, such studies should be 

 
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transformative for the field as standards of care may be established based on the patient 
characteristics that are most important for determining the aspects of speech and language 
that should be targeted in treatment. In addition, large well-controlled studies have the 
potential to provide credibility for the field and influence public policies regarding 
appropriations of rehabilitation funds. 
Existing evidences suggests that aphasia severity is one of the few factors that reliably 
predicts performance in speech and language therapy (herein referred to as SALT). It is 
generally accepted that more severe aphasia is associated with poorer treatment outcomes. 
However, aphasia severity is a multidimensional construct, and patients with similar overall 
severity scores might demonstrate very different language impairment profiles.  
Over the past decade, our group has sought to identify factors that predict post-stroke 
impairment and response to treatment. In a recent pilot study, data from our group has shown that 
different patterns of brain damage may influence treatment outcomes (6). In this study, treatment 
approaches were theoretically driven by the dual stream model (DS model; (7)). The dual stream model 
proposes that the brain has two "streams" for processing speech/language - a dorsal stream in charge of 
production, and a ventral stream in charge of semantic processing.  Based on this model, it was predicted 
that participants with dorsal stream damage would respond to dorsal treatments (i.e., 
phonological/production based treatments) and those with ventral stream damage would respond 
better to ventral stream treatments (i.e., semantically based treatments).  Participants underwent two 
types of treatment - one that was based on phonological processes (sounds of words) and one that was 
based on semantic processes (meanings of words). Results of this work (6) show a wide range in 
treatment responses across the patients, but generally, our results showed that responses to 
different treatment approaches may differ based on patterns of brain damage. However, there 
are a number of other variables that may influence an individual's response to treatment, which were not 
investigated. For example, several studies suggest that factors such as aphasia severity (8-11), 
lesion location (9, 12), and time post-stroke (13) are related to aphasia treatment outcome.  
Therefore, to better understand how language impairment relates to treatment 
outcomes, the current project will again consult the DS model. Specifically, we will test whether 
measures of proportional damage to the cortical areas that comprise the DS model improve 
prediction of aphasia treatment response, beyond biographical and cognitive/linguistic 
factors. Accordingly, we will investigate whether the DS improves prediction of treatment 
response better than a "default" model (i.e., cognitive/linguistic factors alone). To 
understand whether our predictive model can be generalized across different kinds of 
treatment foci, each participant will undergo two types of treatment devoted to phonological 
stimulation, and a separate treatment phase focusing on semantic stimulation.  
Relying on a large participant sample, we plan to identify and model the interaction of 
biographical, cognitive, and linguistic factors that predict aphasia treatment outcome. This 
model will provide clinicians with crucial information to make more accurate prognoses 
regarding participants' treatment outcomes. Whereas identifying biomarkers of positive 
aphasia treatment may be important, we believe that such an endeavor may be improved if it 
takes models of speech and language processing into account. That is, cortical damage that 
affects specific speech and language processes may not only have a particularly negative 
effect on communication, but also may affect aphasia treatment success. Furthermore, prior 
research in aphasiology has shown that theory-driven treatments are more effective, but 
unfortunately, few treatments are indeed motivated by well-supported theories. Hence, the 
current project will test the utility of the DS model, arguably the most influential 

 
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contemporary model of speech and language processing to guide the clinical management 
of aphasia. 
In addition to identifying patterns of brain damage that predict treatment outcomes, 
this study will investigate the role of learning potential on treatment success. Learning 
potential is a concept that has received relatively little attention in the aphasia rehabilitation 
literature. Although treatment-assisted improvements in speech and language processing 
probably reflect learning (or relearning), the relationship between participants’ capacity to 
learn and response to aphasia treatment is poorly understood. The relatively recent emphasis 
on individual differences rather than group averages has highlighted very clear differences in 
learning capacity and potential in the normal population (14-17). We will investigate whether 
participants’ ability to learn at baseline predicts long-term success in aphasia treatment. If 
this study yields positive results, it will further improve clinicians’ ability to guide aphasia 
management. 
In sum, there is a great need for prognostic indicators of aphasia treatment response. At 
the completion of our research, we will understand why some participants respond better 
to aphasia treatment than others. We have selected treatment approaches that are 
routinely used in clinical practice, allowing for immediate translation of the findings 
directly into participant management. The current project will yield a vast dataset that will 
be made publicly available allowing others to study further aphasia treatment response in 
relation to cognitive/linguistic and lesion factors (please see Data Analyses section for 
human subjects protection related to this available dataset). 
Significance 
An important contribution of this project to the literature of aphasiology will be 
results from a large sample of participants. In the most downloaded article in the history of 
the Public Library of Science, “Why Most Published Research Findings Are False,” Ioannidis 
(18) noted that when all factors are equal, in fields where smaller studies are the norm, the 
chances of research findings being false is much higher than in fields where larger studies 
are typical. The norm in aphasia treatment studies, including our own previous studies, is to 
rely on single-subject design or very small group studies. It is straightforward to 
understand why this is the state of affairs. Treatment studies take a relatively long time and 
a disproportionate level of resources compared to most other kinds of research in aphasia. 
Also, subject recruitment is often an issue, especially in studies that target participants with 
specific cognitive/linguistic impairment profiles. Nevertheless, our field needs larger 
treatment studies to reveal specific trends that can be generalized to the larger population 
of participants, not just to a narrow number of cases. We believe that our past success, 
institutional environment, and collaborative spirit puts us in a position to conduct a 
relatively large aphasia study that has the potential to exert a sustained impact on the field 
of clinical aphasiology. In the context of previous aphasia treatment studies, project 1 
entails a relatively large sample size of treated participants (N=120; rational for sample 
size is described in the Human Subjects Protection section) and extensive 
cognitive/linguistic testing, including assessment of learning potential and a neuroimaging 
workup. As we contend that recent meta-analyses studies have demonstrated the value of 
aphasia treatment, the purpose of this project is not to test the efficacy of treatment, but 
rather to determine why some participants respond better to treatment than others and 
whether treatment response relates to which language domains are targeted in treatment. 
The overall significance of this work points to the fact that the clinicians who provide most of 

 
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the aphasia therapy in the United States could far better serve their patients if they were 
armed with prognostic factors that would indicate whether a given patient was likely to 
respond to direct SALT, and what focus that treatment should assume for maximum 
recovery.  
Finally, the significance of this project lies in the multi-center collaboration as outlined 
in the P50 submission attached. In addition to testing the hypotheses outlined here, this data 
will be used in concert with data gathered from Project 2 (PI: Argye Hillis, M.A., M.D., Johns 
Hopkins University) to fuel Projects 3 (PI: Rorden; USC) and 4 (PI: Hickok; University of 
California, Irvine). 
 
C. Specific Aims and Hypotheses  
To test whether contemporary models of speech processing can be used to predict 
response to aphasia treatment in chronic stroke patients. The goal is to develop a model that 
includes biographical and cognitive/linguistic factors to predict who is likely to respond to 
aphasia treatment and what kinds of stimuli (phonological vs. semantic) should be emphasized in 
treatment. The specific aims are as follows:  
 
1. To identify biographical and cognitive/linguistic factors that predict aphasia treatment 
outcome. Construct a predictive model of aphasia treatment success (herein referred to as the 
"default model") and make that model available on-line to clinicians. 
 
2. To test whether the DS model (as an anatomical model of speech and language processing) 
improves outcome prediction beyond what can be inferred based on biographical and 
cognitive/linguistic factors. Essentially, this aim will test whether the DS model provides 
greater improvement in outcome prediction compared to the default model and classical 
models based on localizationist approaches to brain-language relationships (i.e., the classical 
Wernicke-Lichtheim-Geschwind model; WLG(19-22)). 
 
To test whether measures of learning potential predict overall treatment outcome. Three 
learning tasks will be administered by the end of treatment phase one – two will be 
linguistic learning, whereas the third will be a nonlinguistic learning task.  
 
Specific Aims 1 and 2: Models of Treated Aphasia Recovery   
Aim 1 will rely on participant and caregiver questionnaires, direct behavioral testing, 
and MRI scanning. Specific details for each of these components are presented in the 
Research Activities, Protection of Human Subjects section and the Appendix. As we explain in 
Data Analysis section, this information will be used to determine treatment outcomes 
based on these different variables. We will model response to treatment based on: 1. 
Biographical factors: Age (23, 24); education (25, 26); gender (27); handedness (28); age at 
stroke, type of stroke, number of strokes, and time post first stroke that caused the aphasia 
(29); 2. Cognitive/linguistic factors: Clinical assessment of aphasia (10, 11), motor speech 
production (30), grammatical processing (31), semantic processing of verbs and nouns (32), 
phonological processing (33), speech discrimination (34), speech repetition (35), executive 
functioning (36), and verbal short-term memory (37). Once we have built our final data-
driven model(s), it will be possible to examine the specific interactions between these 
factors that make up each model. 
 
 

 
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Hypotheses Aims 1 and 2. Along with several other groups, we have demonstrated 
that functional brain changes in the residual language areas of the left hemisphere support 
treated improvement in naming in aphasia (21, 38). Based thereon, we could conclude that 
strengthening of the residual left-hemisphere language network, the areas that remain 
intact after stroke, leads to improved language processing in aphasia. However, as far as we 
can tell, no research has examined whether this kind of network compensation relies on 
overall network integrity or survival of specific sub-components of the network. We suggest 
that the DS model offers a principled approach to answer such questions. For example, for 
cases of damage to the ventral stream, and concomitant semantic impairment, treatment 
might focus specifically on semantic stimulation. Here, one could assume that preservation 
of the ventral stream would be related to treatment success, so that patients with greater 
damage to the ventral stream are less likely to respond compared to others whose ventral 
stream is relatively more preserved. This view would contend that successful rehabilitation 
relies on the survival of the network that is being stimulated. However, an opposing view 
could argue that what really matters is cross-domain compensation where the dorsal 
stream is forced to become more strongly involved to support improvements in language.  
Along these lines, we propose that reliance on the DS model may improve our 
understanding of why some patients show greater improvements than others and to relate 
the findings in neuroanatomy.  
To test this, the data collected from the treatment and assessment of the individuals enrolled 
in this project will inform further projects (i.e., specifically Dr. Rorden’s project, Project 3). This 
project will rely on the same behavioral data collected here, but it will focus on developing 
sophisticated neuroimaging analyses to understand the relationship between localized 
brain damage and aphasic impairment/recovery. The benefit of this setup is that each 
project may yield complementary results that can better explain differences in treatment 
response among participants. 
 
Specific Aim 3: 
Unlike the measures included in Aims 1 and 2 that mostly represent static factors 
(e.g., performance on cognitive/linguistic tests, proportional damage to specific brain 
regions), learning potential represents dynamic change, something that could be assessed at 
baseline to understand if prolonged aphasia rehabilitation is likely to be effective. Aim 3 
therefore investigates the predictive value of learning potential for aphasia treatment 
outcome. One way to estimate learning is to measure changes in contextual support (e.g. 
cueing) needed to evoke the correct response (124). In a previous study (N=30; 10, 85) our 
group investigated the level of cueing needed to elicit correct naming response to stimulus 
presentations across multiple treatment sessions.  Results revealed that changes in cueing 
strength during the initial treatment sessions (for the phonological and semantic 
treatments) strongly predict overall treatment outcome. These results suggest that 
participants whose level of cueing strength needed to elicit correct naming decreases during 
the initial treatment session are far more likely to respond to the overall treatment, 
regardless of initial aphasia severity. We recognize that decreased reliance on cues during 
naming may not be a classical learning task and that what we deem “learning” in this context 
could also be called “stimulability” or priming. Regardless, performance on the cueing 
hierarchy task by our 30 participants was a highly robust predictor of outcome and no other 
factor – behavioral or neuroimaging – came even close in terms of predictive power. From a 
theoretical perspective, it is a caveat that we do not know whether the changes in cueing 

 
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level represent a general learning mechanism or something that is language specific. 
Therefore, in addition to measuring potential changes in cueing strength during a baseline 
session that uses cueing hierarchies to elicit picture naming, all participants will also 
complete a separate learning task that does not explicitly rely on language processing. As a 
result, it will be possible to determine if initial success in treatment is related to language 
independent learning or is language specific. 
 
 
Hypothesis Aim 3. Learning is driven by neuroplasticity – the ability of the brain to 
continuously adapt its structure and function based on internal and external environmental 
changes. Neuroplasticity occurs due to changes in neuronal morphology, glia, and vascular 
and metabolic processes and can be stimulated by a variety of sensory-motor experiences (5, 
39, 40). Learning potential is a common concept in the education literature (41, 42). It 
assumes that not all individuals have the same ability to acquire new information and 
probably reflects flexibility of neural systems to adapt to internal changes or external 
stimulation. Although most clinicians probably assume that some aphasic participants have 
greater rehabilitation potential than others, it is not clear whether participants’ learning 
potential is related to aphasia treatment outcome. Nevertheless, we predict that learning 
potential will be related to treatment outcomes.  
 
D. Data Collection 
Comparing Biomarkers as a Function of Treatment Foci 
One of the challenges to interpreting the value of aphasia treatment biomarkers is 
the generalizability across different kinds of treatment types and foci. For that reason, this 
project will rely on a crossover design where each participant completes one treatment 
phase that focuses on semantic stimulation and another treatment phase where the focus is 
on phonological stimulation. Accordingly, we will be able to compare biomarkers of 
treatment outcome and determine if the same factors predict success, regardless of 
treatment focus, or whether biomarkers are dependent on treatment focus.  
 
Research Design and Methods and Data Analysis 
 Our plan is to treat 120 participants with chronic aphasia caused by damage to the left 
hemisphere. Utilizing a crossover design, each participant will receive 45 minutes of aphasia 
treatment per weekday (5x/week) focusing on treatment tasks that emphasize semantic or 
phonological stimulation (Table 1). Half of the participants will receive treatment in the following 
order: a. 15 treatment sessions utilizing phonological stimulation tasks; b. 4-week inter-
treatment interval; c. 15 treatment sessions with semantic stimulation oriented tasks. The 
remaining half of participants will receive treatment administered in the opposite sequence. 
Participants will be randomized to receive treatment in either order.  
During the first baseline visit (referred to as W0 here, but W1 in the consent form), 
participants’ biographical and testing information is entered into online modules in WebDCUTM 
(see P50 Administrative Core). All subsequent participant data, including testing and treatment 
scores, MRI related information, and treatment fidelity information, will also be entered and 
stored using WebDCUTM. To establish treatment baselines and for the purpose of in-depth 
characterization of the participant sample, each participant will undergo extensive testing during 
the week prior to treatment.  
To assess treatment related changes in speech and language processing, testing will occur 
during the weeks immediately before and after each treatment phase. Follow-up testing will occur 

 
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4-weeks and 6 months (at or around week 39) after completing the second treatment phase. To 
assess damage to the cortical areas included in the WLG and DS models, participants will undergo 
MRI (see P50 Neuroimaging Core) at baseline during the week before treatment is initiated. 
Additionally, participants will undergo MRI testing following each treatment phase and at 6-
months post treatment completion to assess functional brain changes. Approximately two-thirds 
of the participants will be enrolled at the University of South Carolina. The remaining one- third 
will be enrolled at the Medical University of South Carolina under the supervision of Dr. Bonilha, a 
stroke neurologist with ample experience managing aphasia, and a long-time collaborator of the 
PI.  Individuals will be asked to complete an anonymous participant satisfaction survey at the 
week 15 visit to provide feedback on their clinical research experience. 
 
Timeline for testing and treatment. G1 notes a group of participants who first undergo aphasia treatment utilizing 
tasks that target phonological stimulation. Then, during the second treatment phase, these participants will cross 
over to receive treatment focused on semantic stimulation. G2 (group 2) will undergo treatment using the opposite 
order of treatment phases. W=Weeks; Eval=Evaluation of performance (testing); Phon. Tx.=Phonological processing 
focused treatment; Sem. Tx.=Semantic processing focused treatment.  
 
 
Group 
W1 
 
W2-4 
W5 
W6-7 
W8 
W9-11 
W12 
W15* 
W 39# 
G1 
MRI & 
Eval 2-3 
days 
15 Phon. 
Tx 
MRI & 
Eval 1-
2 
days 
 
Rest 
Eval 1-2 
days  
15 Sem.  
Tx 
MRI & 
Eval 1-
2 
days 
Eval 1-
2 
days 
MRI & 
Eval 1-
2 
days 
G2 
MRI & 
Eval 2-3 
days 
15 Sem.  
Tx 
MRI & 
Eval 1-
2 
days 
Rest 
Eval 1-2 
days 
15 Phon. 
Tx 
MRI & 
Eval 1-
2 
days 
Eval 1-
2 
days 
 
 
MRI & 
Eval 1-
2 
days 
*W15 denotes 4-week follow-up testing    
#W39 denotes 6-month follow-up testing (this testing should take place at or around week 39) 
 
Additional Follow-Up 
 
A subset of participants will be called back for a long-term follow-up, at least six months 
after the 6 month follow-up (i.e., one-year post-treatment). The purpose is to extend the follow-up 
window for the POLAR study, to one-year post aphasia treatment. There is evidence to suggest 
that declining performance in stroke-induced aphasia is attributed to pathologic changes in the 
brain's white matter, referred to as leukoaraiosis (Basilakos et al., in press). Leukoaraiosis is 
common in stroke survivors, and is often attributed to age, as well as cardiovascular health and 
other health concerns. In the general population, it has been associated with cognitive decline and 
loss of functional ability. By extending follow-up interval for the POLAR study, this study will 
address a new aim of evaluating the progression of leukoaraiosis and how it affects overall 
cognitive-linguistic ability in stroke survivors. To this end, participants will undergo a subset of 
the same speech/language and cognitive testing administered at study baseline, as well as testing 
with the NIH Toolbox. Participants will also undergo a magnetic resonance imaging (MRI) 
protocol (about one hour in duration). The extent of behavioral change will be evaluated and 
related to neuroanatomical changes. The role of cognitive reserve and other personal factors in 
mediating the effects of leukoaraiosis will also be explored. The Appendix outlines additional 
measures that will be obtained at this testing time point.  
 
Recruitment 
Identification of eligible participants.  For Project 1, the Clinical Core team will 
focus recruitment efforts on referrals from rehabilitation professionals as outlined in our 

 
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Patient/Participant Referral Program (PRP).  This program provides a monetary 
incentive of $100 to any rehabilitation professional who refers a patient who comes in for 
an evaluation and is deemed eligible for this study. We will continue to use online and 
social media outlets as well as community activities to reach out potential participants.  
 
Aphasia Treatment 
Since our primary goal is to assess predictors of treatment that can be applicable to 
existing practices, we selected treatments that are typically employed. Neither semantic nor 
phonological processing exists independently of each other in oral language use. Accordingly, the 
treatment approaches to be used here do not focus exclusively on either semantic or phonological 
processing; they each involve both, but place different emphasis on semantics versus phonological 
processing. In fact, even when semantic processing is the treatment emphasis, these treatments 
also affect phonological processing and vice versa. We stress that the main purpose here is not to 
assess whether one treatment focus is more potent than the other for improving language 
processing. Rather, we only include the two treatment foci to understand if factors that predict 
outcome with one treatment approach also predict success using the other treatment approach. In 
addition, we include two semantic and phonological treatment foci to explore whether damage to 
the dorsal and ventral streams differentially predicts response to phonological and semantic 
treatment.   
 
Semantically focused treatment tasks. Three types of tasks will be featured. Please see 
the Appendix for scripts and examples for each treatment task. Tasks are as follows: 1) Semantic 
feature analysis (SFA) has a relatively long history as a treatment approach for aphasia (43-45). 
For each pictured stimulus the participant is prompted to name the picture. Then, he or she is 
encouraged to produce semantically related words that represent features similar to the target 
word (e.g. superordinate category, use, action, physical properties, location, and association). For 
example, to elicit a location feature, a clinician might say “where do you typically find this object?” 
If the participant is not able to name the target item once each word feature has been produced, 
the clinician will say target word. Regardless of naming accuracy on the last item, treatment 
continues on to the next stimulus item. Because both nouns and verbs(46, 47) have been used for 
SFA focused activities, stimuli for SFA tasks here will utilize both. 2) The second semantic 
treatment approach is the semantic barrier task. This approach includes features of the Promoting 
Aphasics’ Communication Effectiveness (PACE) approach (48-51) and has also been included as 
part of constraint-induced language therapy (52). It relies on a stack of picturable stimuli, which 
are split between the participant and clinician and placed face up on a table. A visual barrier is 
placed between the clinician and the participant so they cannot see each other’s pictures. The goal 
of the task is for one participant (e.g., participant) to describe each card so that the other 
participant (e.g., clinician) can guess the picture on the card. Participants are only allowed to 
describe the semantic features of the target and the clinician models the kinds of cues that are 
allowed. The clinician and participant take turns describing pictures. 3) The third approach, Verb 
network strengthening treatment (VNeST), is a semantic treatment approach that targets lexical 
retrieval of verbs and their thematic nouns (53). The objective of VNeST is for the participant to 
generate verb-noun associates with the purpose of strengthening the connections between the 
verb and its thematic roles. VNeST can be modified to fit participants with very limited speech 
output (e.g., using sentence completion). 
 
Phonologically focused treatment tasks. Three approaches, also with sound research 
pedigrees, will be used. 1) The first is the phonological components analysis task (54), which was 
modeled after semantic feature analysis. It requires the participant to first name a given picture 
and then to identify the phonological features of the target words (e.g., first sound, syllables, last 

 
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sound, association, and rhyme). Once the features have been identified, participants are 
required to attempt to name the picture again. Then, the treatment moves on to the next item in a 
stack of targeted imageable nouns and verbs. 2) Phonological production task is a phonologically 
based therapy that focuses on the identification of phonological features using a stack of targeted 
imageable nouns and verbs. It requires the participant to first sort the stack of picture stimuli 
based on the number of syllables by tapping out each syllable. Once the participant has sorted the 
targeted words into two stacks, the treatment moves on to identifying the following hierarchy of 
phonological features using a pair of the targeted imageable nouns/verbs: a. first syllable-first 
syllable; b. first syllable-last syllable; c. last syllable-last syllable; d. last syllable-first syllable; e. 
first syllable-first sound; f. last syllable-last sound; g. first syllable-last sound; h. last syllable-first 
sound.  Once each targeted feature is identified for the pair of words, the participant is required to 
blend the syllables/sounds together. 3) The phonological judgment task relies on computerized 
presentation of verbs and nouns where participants are required to judge whether pairs of words 
include similar phonological features. The task is comprised of five conditions that entail 
determining if a set of words: a. Includes the same number of syllables; b. Includes the same initial 
syllable; c. Includes the same final syllable; d. Which word has more syllables; and e. rhyme. 
Participants respond to each condition by pressing one of two response buttons depending on the 
task requirements and instructions. Additional information regarding all treatment tasks can 
be found in Appendix A. 
 
 
Biographical Factors and Cognitive/linguistic Assessments 
Biographical factors. For the purpose of recording data on biographical factors, each 
participant (and/or caregiver) will be required to fill out a case history form and a questionnaire 
on previous medical events, years of education, etc.  
 
Cognitive/linguistic testing. The following tests and tasks will be utilized to assess 
cognitive/linguistic status at baseline, before any treatment starts: 1. The revised version of the 
WAB will be used to assess overall aphasia severity and type (55). Although the WAB does not 
provide in-depth analysis of speech and language impairment, it is a test that is commonly used in 
clinical practice as well as a reasonable measure of overall aphasia severity; 2. The Apraxia of 
Speech Rating Scale (ASRS; (56)) will be utilized to rate the presence and severity of apraxia of 
speech AOS (note: the ASRS constitutes a major component of project 3); 3. To assess grammatical 
processing (agrammatism), we will rely on the Northwestern Assessment of Verbs and Sentences 
(57). The NAVS was designed for participants with aphasia and allows for detailed examination of 
verb processing (e.g. verb naming) as well as production and comprehension of canonical and 
non-canonical sentences; 4. The Pyramids and Palm Trees Test (PPTT; (58)) and the Kissing and 
Dancing Test (KDT; (59)) will be used to assess amodal semantic processing of nouns and verbs, 
respectively; 5. To assess phonological processing, several sub-tests from the Psycholinguistic 
Assessments of Language Processing in Aphasia (PALPA; (60)) will be utilized (a. Auditory 
discrimination of nonword minimal pairs; b. Auditory discrimination of word minimal pairs; c. 
Rhyme Judgments for pictures and words; d. Phonological Segmentation of initial and final 
sounds); 6. To assess speech repetition ability we will rely on the Philadelphia Repetition Test 
(PRT), a low-imageability word repetition test (61), and the non-word speech repetition sub-test 
from the PALPA (65); 7. For analysis of cognitive status, the Matrix test on the Wechsler Adult 
Intelligence Scale (WAIS; (62)) will be administered; 8. To assess verbal short-term memory, we 
will use tasks described by Martin et al. (63). Their tasks allow for detailed evaluation of lexical-
semantic performance in relation of verbal short-term memory load. All participants will be 
screened for visual field cut and visual neglect during the neurological examination as a part of the 
NIH Stroke Scale. To minimize the influence of test fatigue, the assessment battery will be spread 

 
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over three sessions administered on three separate days during the week before the first 
treatment phase starts. The motivation for the extensive behavioral test battery included here is to 
provide a comprehensive set of factors used to predict treatment outcome. In addition, the 
behavioral data collected here will also feed into projects 3 and 4 (e.g. non-word repetition and 
PRT). For details on test reliability, validity, and clinician training, please see the Clinical 
Core section in the overall P50 Grant Application (relevant pages beginning on p. 264). 
Additionally, scripts that will be used for each treatment approach are presented in 
Appendix B.   
 
Learning tasks for specific Aim 3  
 
All participants will complete three learning tasks; two linguistic based learning tasks 
(phonological and semantic) and one nonlinguistic learning task (spatial). These will be 
administered in random order for each participant and will be completed by the end of treatment 
phase one. The tasks are set-up similar to the classical computer game “PONG.” 
 
Linguistic learning is completed by a game-like interface, where four words fall at randomly 
generated speeds from the top of a computer screen. Participants are asked to mouse over the 
words that fit the category of the game, such as ‘animal’ or ‘has the “s” sound’, and to avoid words 
that are not targets but may be semantically or phonologically related or unrelated.  
 
Nonlinguistic learning will be tested by the same game-like interface. The task involves shape-
patterns where participants are required to identify identical shapes to the target shape and to 
avoid distractor shapes. In this way, we circumvent internal language representations of task 
stimuli. Before beginning the task, the participant is shown a target shape and told that they will 
be presented with a computer screen where a variety of different shapes will fall from the top of 
their screen. The participant’s objective is to mouse over the target shape and to avoid the other 
shapes (distractors). 
  
All learning tasks will be conducted 5 times consecutively for 2 minutes each time. The accuracy 
score will be recorded for each session. The participant’s learning ability is summarized as the 
increase in accuracy between baseline and final session. The study will compare linguistically 
based task vs nonlinguistic learning tasks (each to be completed by the end of treatment phase 1) 
to determine whether learning potential relates directly to prognosis. 
 
Treatment Outcome Measures  
Consistent with previous work in our lab and Project 2, change in correct naming on the 
Philadelphia Naming Test (PNT; (64)) will be assessed as an outcome measure. Confrontation 
naming is included on most comprehensive aphasia tests and is commonly assessed in aphasia 
treatment research, making it possible to compare the findings in the current project to other 
studies. The PNT will be administered twice at baseline and then once during the week before and 
the week after each 3-week treatment phases. For follow-up testing, the PNT will be administered 
again at four weeks and six months after completion of the second treatment phase. The primary 
outcome measure, however, is specifically defined as change in correct naming immediately 
before and after each treatment phase. The PNT is a computer-based assessment of naming for 
persons with aphasia and includes 175 pictures representing mid- and high-frequency nouns from 
a word frequency list compiled by Francis and Kucera (65). Participants are videotaped during 
assessment and responses are scored offline. In addition to assessing changes in correct naming, 
potential treatment-related changes in naming errors will also be scrutinized. The Treated Naming 
40 is a computer-based assessment created for this study to assess changes in correct naming of 

 
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targeted nouns and verbs from treatment.  There are a total of 40 pictures representing 
targeted nouns and verbs from treatment (20 from phonological and 20 from semantic). Of those 
20 from each deck they were equally matched by nouns and verbs. The nouns included are 
matched by equal number of high frequency and low frequency words as well as by syllable 
length. The verbs are matched only according to syllable length. Additionally, any words that 
appear on the PNT were excluded. Unlike the PNT, the Treated Naming 40 is administered only 
once during each assessment time point: baseline, before and after each treatment phase, and at 4 
weeks and 6 months post completion of treatment.   For a more detailed description of PNT and 
Treated Naming 40 scoring and training of clinicians, see Clinical Core.  
To evaluate the effects of treatment on discourse abilities, participants will complete a 
discourse protocol included in AphasiaBank, an archival database of discourse samples funded by 
the NIDCD since 2007. Three discourse tasks will be administered before and after each treatment 
phase: 1. Broken Window picture sequence description (66); 2. Cinderella story telling (67); and 3. 
A procedural description of how to make a peanut butter and jelly sandwich (first introduced by 
Davis, 1901 (68), as referenced in Lau, 2013 (69). Transcription will be accomplished through the 
Clinical Core using transcription (CHAT) and the automated coding analysis (CLAN) systems 
available through AphasiaBank. We have already used this setup to assess outcome in aphasia 
treatment (30). As in the CATES trial, the analyses used for discourse samples will focus on lexical 
and syntactic aspects of spoken discourse: 1. Content words/min (excludes repetitions and 
nonwords); 2. Propositional density (70, 71); 3. Verbs/utterance. Each of these three measures is 
already included in AphasiaBank and it is a particularly nice feature that our data can be 
compared against the 440 aphasic participants included in AphasiaBank. This feature is especially 
important for determining variance across participants. In addition, we will assess potential 
changes in participants’ ability to generate main concepts (72). Finally, to assess the effects of 
treatment on functional communication ability, all participants will be administered the Adaptive 
Aphasia Communication Outcome Measure (CAT-ACOM; (73)). The CAT-ACOM test adaptively 
administers 12 items from the 59 item ACOM item bank. A content-balancing strategy is used to 
select items from each domain (talking, writing, number use, comprehension, and naming) to 
insure that the content balance of each CAT-ACOM administration is reflective of the content 
balance of the full 59 item bank. The test items administered probe different aspects of real life 
communication situations and can be administered with a short administration time. The ACOM 
will only be administered at baseline and at six months post treatment completion.  
 
Neuroimaging  
MRI data will be collected at USC and MUSC. Both sites are equipped with a Siemens 3T 
Trio and an established quality assurance protocol is already in place to ensure that the same MRI 
sequences yield comparable data on both scanners. The MRI scanner at USC is housed at the 
McCausland Center for Brain Imaging (MCBI), a facility that is co-directed by Fridriksson and 
Rorden. At MUSC, MRI scanning will take place at the Center for Biomedical Imaging, a facility 
Bonilha routinely uses for MRI data collection. Once MRI scanning is complete, all data are 
transferred to and stored on a secure server housed at University Technology Services (UTS), USC. 
Extensive data backup and data mirroring is included as part of UTS services.  All preprocessing of 
MRI data will occur at USC under the direction of Dr. Rorden as part of the Neuroimaging Core. We 
have already constructed a state-of-the-art data pipeline for preprocessing various MRI data 
modalities as well as a new software package to relate various types of MRI data to aphasia 
impairment and recovery. 
 
DNA Analyses  
 
All participants will be asked to provide a saliva sample for the purpose of genotyping for 
BDNF (brain derived neurotrophic factor) and the FOXP2 gene (forkhead box p2).  

 
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BDNF is a growth factor that has been shown to promote plasticity. Some individuals are 
carriers of the VAL66MET polymorphism, which leads to reduced BDNF secretion, and potentially 
decreased outcomes in aphasia therapy (74).  
The FOXP2 gene is the first gene that has been implicated in speech-language impairment. 
Specifically, the FOXP2 polymorphism rs17137124. This gene has been implicated in neurogenesis 
and synaptogenesis, but little is known about is role in post-stroke recovery in humans. However, 
in a mouse model, FOXP2 expression has been related to recovery of vocalization (75).  
We will investigate the extent that the presence of these polymorphisms affects therapy 
outcomes. To do so, a DNA Genotek Oragene-DNA-OG500 kit will be used. Each kit contains a small 
tube that collects saliva. Participants will be asked to spit into the tube until 2 milliliters of saliva 
has been acquired.  Participants will be provided with written/picture instructions (see attached 
Oragene DNA User Instructions). The process of delivering a saliva sample takes approximately 2-
5 minutes. Sample tubes will be labeled with participant number and date of acquisition. For 
participants who have already completed the study, we will request that they either: i) come to the 
Aphasia Lab to supply a sample, ii) allow us to meet them at their home to obtain sample, or iii) for 
participants not living in the Columbia area, we will ask them to complete the sample by mail.  
If participants are to complete the sample by mail, they will be asked to complete and 
return the provided consent form with their sample. We will ask that they call one of the treating 
clinicians if they need help providing the sample, and a SLP will guide them through the 
instructions. We will provide all postage for participants to mail their sample to the lab. Also, we 
will use the Aphasia Lab’s address as the return address to ensure confidentiality.  
  
All samples will be stored in DNA Genotek DNA storage boxes and locked in a storage 
cabinet in the lab. Samples are stable at room temperature for up to 5 years. All samples will be 
labeled with participant numbers.  
 
 
E. Data Analyses  
Specific Aim 1  
To construct the default model of recovery, both biographical and cognitive/linguistic 
factors are entered into a step-wise regression analysis using a leave-one-out method. This 
approach narrows down the number of factors that provide independent prediction of treatment 
outcome. The leave-one-out method controls for selection bias where the same subjects are not 
used to select the factors and test the model. The factors that survive in the final step-wise 
regression model are then entered into the support vector regression (SVR) analysis to determine 
how well the default model predicts actual outcome in participants. SVR is a more 
robust alternative to multiple linear regression. Both methods use a linear model to characterize 
the relationship between the predictors and the target variable (e.g, change in correct naming); 
that is, the target variable is modeled as a weighted sum of predictors, plus the offset term. The 
difference between the two methods is in the estimation of the model parameters (the weights 
and the offset). In multiple linear regression, it is done by computing the Moore-Penrose pseudo 
inverse of the predictor matrix; this minimizes the prediction errors in the least-squares sense, 
but leads to highly unstable estimation if there is correlation between the predictors (76). Also, 
the pseudo inverse cannot be computed if the number of predictors is greater than the number of 
observations. In support vector regression, we do not attempt to minimize the prediction errors; 
rather, we allow for a certain amount of errors, and set an upper bound on permissible prediction 
errors (77). In this formulation, the stability of estimation is not affected by correlations between 
predictors, and by the number of predictors relative to number of observations. The superiority of 
support vector regression over linear regression models has been demonstrated by Drucker et al. 
(78). We expect that the final default model will include a combination of several factors that 
together contribute to outcome prediction. As not every factor will contribute equally to the 

 
15
proportional reduction in error, beta weights (converted to Z-scores) will be calculated so that 
clinicians can better understand the relationship between predictors.  
 
Specific Aim 2  
To compare the default model to previous models of speech/language processing (the WLG 
model and the DS model) we will also rely on SVR. Here, all factors that comprise each model are 
entered into an SVR analysis and the R2 for the correlation between the actual scores (e.g., change 
in correct naming or propositional density) and the predicted scores is calculated. Then, a 
statistical comparison is made between the R2 yielded by the different prediction models. The 
model with statistically significantly highest R2 compared to other models will be determined as 
the best prediction model. Separate analyses will be conducted for each treatment focus (semantic 
vs. phonological) and overall treatment outcome.  
 
Specific Aim 3  
Separate SVR analyses will be conducted to test whether change in cueing in a single 
naming session or performance on the hit-and-avoid task predicts aphasia treatment outcome. 
The learning curve (slope of the regression line) will be calculated for each participant. The same 
SVR analyses planned for Aim 1 will be run again but now with the learning factors also included 
to assess whether the default model can be improved by including assessments of learning 
potential. Potential concerns: Without collecting further data, it is impossible to estimate the 
necessary length of the learning paradigms. This is a potential concern as administering an hour-
long learning task to participants in clinical care is probably not feasible. Thus, we will calculate 
learning curves for progressively longer increments (e.g. for the first 10, 20, 30, or 40 minutes of 
the task) to appreciate the necessary length of each learning task. For example, it could be the case 
that improvement in performance over the first 20 minutes of the language-learning task is 
sufficient to predict treatment outcome. 
 
Making the Default Model Available On-line  
Once the default model (i.e., response to treatment based on biographical and 
cognitive/linguistic factors) has been constructed, we will make the algorithm available to 
clinicians who can then assess their own participants and plug in the results to estimate treatment 
response relying on either semantically or phonologically focused treatment. For this purpose, we 
will design a website that includes detailed instructions regarding what factors need to be 
assessed and the strengths and limitations of this approach. Similarly, we will provide guidance 
regarding assessment fidelity, threats to assessment reliability and validity, as well as disclaimers 
about potential abuse of the model (e.g., denying participants treatment based on model 
prediction of poor outcome). Importantly, when datasets from this project are made available, no 
individually identifying information will be shared.  
 
 
F. Protection of Human Subjects 
Human Subjects Involvement and Characteristics 
 
Approximately 150 participants with left hemisphere ischemic or hemorrhagic stroke will 
be included in this study (120 will receive aphasia treatment). For the purposes of future projects 
(outlined in the P50 plan, Projects 3 and 4), we will also test (but not treat) additional 30 
participants with chronic left stroke who do not present with aphasia. We will not exclude 
participants with recurrent stroke unless one or more strokes included the right hemisphere. In 
general, aphasia recovery associated with spontaneous healing (i.e., recovery not attributed to 
specific external intervention) is thought to mostly subside between 6 and 12 months post-stroke. 
Therefore, to establish a stable behavioral baseline, only participants who are at least 12 months 

 
16
post-stroke will be enrolled in this research. The age range will be set at 21-80 years. The lower 
limit is based on evidence suggesting that brain-language development is not complete until in the 
late teens (79). The upper limit is set in an attempt to exclude participants with dementia. To 
increase the chance that all participants can perform the selected treatment tasks, potential 
participants will be excluded based on aphasia severity if their spontaneous speech score on the 
WAB is lower than 2 or if their auditory comprehension sub-score on the WAB is lower than 2. 
Participants who have contraindications for MRI will be excluded, as we will not be able to 
determine the extent of damage to the cortical areas that comprise the DS model or the WLG 
model. Participants will not be excluded based on AOS or dysarthria severity unless it is clinically 
determined by the PIs that speech intelligibility is too poor for accurate assessment of naming 
performance on the primary outcome measure (PNT). Each participant will undergo in-depth 
assessment of speech and language abilities allowing for detailed description of the participant 
sample 
 
Rationale for Sample Size 
For Aim 1, the primary goal is to construct a model that predicts aphasia treatment success. 
We have used results from prior work (80) to conduct a power analysis for the current project.  
We used the factors from this data to compute exhaustive leave-one-out regression values, 
resulting in the more conservative R2=.088, R2=.27 and R2=.36 for phonological, semantic, and 
overall treatment effects (rather than .22, .44 and .46). This suggests that a sample size of 120 
individuals provides 0.95 power at p < 0.05, and 0.85 power at p <0.01. Deriving power estimates 
for Aim 2 is more speculative: rather than comparing against a static null hypothesis (e.g., 
treatment has no influence) we are comparing against different dynamic models that will each 
benefit from a larger sample size. Conventional analyses suggest that a sample size of 120 
individuals will provide 0.92 power at p <0.05 for supporting the weakest effect, shown in Figure 
3 (default model’s ability to predict phonological treatment benefits) and 0.72 power at p < 0.05 
for distinguishing the difference between the default model and the Default+DS model. We note 
that a null result for the latter in the presence of a robust result in the former could still be 
clinically meaningful, potentially suggesting that initial behavioral tests are sufficient for 
treatment planning.  
 
Research activities  
Participant involvement will take approximately eight weeks (excluding time between 
treatment phases) with an inter-treatment interval of four weeks and follow-up testing scheduled 
at four weeks and six months after treatment completion. Each participant will undergo 
neuropsychological testing, including baseline testing of naming ability, and complete three 
learning tasks, as well as an MRI session during the first week before treatment starts. The next 
three weeks will be devoted to behavioral aphasia treatment (with five treatment sessions 
administered on Monday-Friday each week) followed by a 4-week rest period, and, finally, 
another 3- week treatment period. Before and after each of the two treatment phases, participants 
will be tested with the primary and secondary outcome measures. Participants will also undergo a 
follow-up MRI session after each of the two treatment phases and at 6-months post treatment 
completion. 
Over the past 15 years, we have established a large pool of participants with chronic 
aphasia (N=145) from which we will recruit for the current project. The Midlands area of South 
Carolina, where the University of South Carolina is located, has one of the highest stroke rates in 
the United States. As a result, the number of stroke participants with chronic aphasia that live in 
Columbia and the surrounding areas is relatively high. In an ongoing unrelated study, we are 
testing participants with left hemisphere stroke in acute care, providing us with a pool of 
participants with and without aphasia. Many of these participants end up coming to our weekly 

 
17
aphasia support groups (current enrollment=37) and are eager to participate in research, 
especially treatment studies. Based on our previous success in recruiting participants for our 
treatment studies as well as a major recruitment effort that will reach South Carolina and 
neighboring states, we see no reason why we would not be able to enroll and treat 120 
participants with chronic left hemisphere stroke.  
 
Eligibility 
Participants with chronic aphasia (>12 months from stroke) as a result of left hemisphere 
stroke (ischemic or hemorrhagic) will be included. Persons who incur more than one stroke will 
be excluded only if the subsequent stroke(s) includes the right hemisphere. Inclusion/exclusion 
criteria are summarized as follows.  
 
Inclusion Criteria 
1. Participants must have incurred a left hemisphere ischemic or hemorrhagic stroke. 
2. Participants must be greater than 12-months post-stroke onset. 
3. Participants must between 21 and 80 years of age. 
4. Participants must have spoken English as their primary language for the last 20 years.  
5. Participants must be willing and able to provide informed written or verbal consent.  
6. Participants must be MRI-compatible (e.g. no metal implants, not claustrophobic, etc.) 
Exclusion Criteria 
1. Severely limited verbal output (WAB Spontaneous Speech rating scale score of 0-1) 
2. Severely impaired auditory comprehension (WAB Comprehension score of 0-1).  
3. Bilateral stroke 
 
Source Materials 
Medical information will be obtained from study subjects. Results of assessments obtained 
during each subject contact will be recorded in the research record. In the event that the 
participant’s prior medical record is required to document medical history, an authorization for 
records release will be obtained from the subject. Each subject that signs the consent form and 
meets the study eligibility criteria will have a unique study identifier assigned to them by the 
WebDCUTM system upon enrollment into the study. The DCU computers and servers will not 
store any personal health identifiers (i.e., name, medical record number); rather, the subject will 
be tracked during the study period through the assigned unique identifier. Only the appropriate 
local site study personnel will have access to a participant's personal identifying information. All 
paperwork that includes participant identifiers (e.g., medical records) will be kept in a locked 
cabinet in the PI’s office. Once a participant’s baseline information has been reported in 
WebDCUTM, all subsequent testing and treatment data are entered online using customized case 
report forms (CRF) that are specifically designed with the specific needs of project 1 in mind. In 
addition to the use of passwords and other security measures, all documents containing 
identifying information on individuals or physicians are considered confidential materials and are 
safeguarded to the greatest possible extent. No information that identifies a specific person, 
hospital, or physician is released to or discussed with anyone other than study staff members. All 
employees are informed of this policy before being hired and required to sign a pledge to maintain 
the confidentiality of all information. In addition, a set of guidelines are developed for the staff 
dealing with the specific office and data processing procedures to assure the confidentiality and 
security of all data. 
 
Consent 
Informed consent will be obtained from participants during their initial assessment 

 
18
session. The speech-language pathologist in charge of testing will obtain the informed consent. 
For participants whose auditory comprehension is severely impaired, every effort will be made to 
convey what study enrollment entails and caregivers will be included in the process. An additional 
consent form will be completed to allow participants and caregivers (if applicable) to choose 
whether or not they give consent for media release of video files or pictures for use of educational 
purposes and/or shared on social media.  
 
Potential Risks and Discomforts 
For the current research, three areas are of paramount interest with regard to the 
protection of human subjects: 1) Potential adverse effects associated with MRI scanning; 2) 
Potential adverse effects associated with behavioral testing and treatment; and 3) Maintenance of 
participant confidentiality. We will address each of these below on point-by-point basis. 
 
1. MRI Scanning. For the purpose of determining the extent of cortical damage, each 
participant will undergo one pre-treatment MRI session as well as three additional MRI sessions. 
Additional MRI scans will be completed following each treatment phase and at 6-months post 
treatment completion. This will allow us to assess potential treatment related changes in 
functional brain activation, functional brain connectivity, and structural brain connectivity. We 
have conducted extensive research using MRI in stroke. Overall, the number of stroke participants 
who have received MRI in our studies exceeds 270 (includes both acute and chronic stroke). 
Among participants with chronic stroke who have participated in our research, we have 
occasionally had to exclude participants because of factors contraindicative to MRI. We find that 
most participants who have reported negative reaction to past MRI experiences do not have 
problems with our MRI setup. The MRI scanners used for this research at USC and MUSC are 
short-bore magnets (Siemens 3T Trio) with a wider bore than most older generation scanners. 
This allows the participant rather easily to see through either end of the scanner bore without 
shifting head position.  
 
All participants will undergo thorough screening to check for factors counter-indicative for 
MRI scanning (e.g., metal implants, pregnancy [women who are of child bearing age will be 
required to take a pregnancy test], pacemaker, severe claustrophobia, etc.). We will follow the 
same protocol that we have used with past participants. First, each person fills out a questionnaire 
in collaboration with a clinician and, when needed, a caregiver. Then, we give each participant 
ample time to get familiar with the scanner (we show them the stimulus presentation hardware, 
the computer console, the headphone/microphone used to record speech) before the actual 
scanning session starts. We find that taking this extra time to familiarize participants and, when 
appropriate, family members, with the MRI setup, participants usually feel comfortable with the 
MRI session. 
 
2. Participant Testing/Treatment. In our experience, occasional participants will have a 
negative reaction to neuropsychological testing. For example, this can be caused when 
participants realize that their performance on a given test is far worse than they would have 
expected. We always make sure that ample time is allotted for neuropsychological testing and that 
participants are allowed breaks as needed. So far, we have never had a participant discontinue 
study participation because of adverse reaction to study testing. Almost without exception, 
participants who participate in our treatment studies wish to continue study participation even 
when the treatment period has expired as it allows them access to free aphasia treatment. With 
regard to the behavioral treatment, the only adverse reaction that we occasionally see is fatigue. 
This is something that we warn participants about ahead of time. 
 

 
19
3. Participant Confidentiality. All study investigators participating in the current 
project must ensure that the confidentiality of personal identity and all personal medical 
information of study participants will be maintained at all times. Additionally, the clinical sites are 
to follow privacy obligations to study participants under the Health Insurance Portability and 
Accountability Act (HIPAA). Because the DCU uses a web-based system, source documents and 
CRFs will remain at the site. The study database and any study documents submitted to the DCU 
will only identify study subjects by unique study identification codes. All data will be stored in a 
manner that is HIPAA compliant, without the ability to track the information back to a specific 
subject except through a password protected system (all collected information about a subject will 
be stored by a unique identification code). All DCU personnel are certified by the NIH Office of 
Human Subjects Research in the Protection of Human Research Subjects course. 
 
Potential Benefits 
The participants enrolled in this research will receive behavioral aphasia treatment, gratis, 
something that few participants with chronic aphasia receive through third-payer insurance. 
 
Importance of Knowledge to be Gained 
 
Aphasia is common in stroke, the leading cause of adult disability in the United States. 
Although gradual, long-lasting aphasia recovery is probably common, most participants with 
chronic aphasia remain aphasic for the rest of their lives. Aphasia therapy can improve aphasia 
recovery; however, very little is known about what kind of participants benefit from different 
kinds of treatment. The current research will inform the relationship between language 
impairment profiles and responses to treatment.  
 
Data Sharing Across Research Projects, Service Cores, and Ongoing Study Trials: 
 
Because the current submission is part of a larger multi-site collaboration, all data 
collection for the entirety of the collaboration will occur as part of the treatment studies 
planned in projects 1 (PI: Fridrikson) and 2 (PI: Hillis). The same data will also feed into 
projects 3 (PI: Rorden) and 4 (PI: Hickok) to predict treatment outcome. Project cores will be 
managed to support the overall project (Clinical Core, Neuroimaging Core, and the Administrative 
Core). The two service cores – the Clinical Core (PI: Hillis) and Neuroimaging Core (PI: 
Rorden) – will support data collection and analyses. In addition, we will incorporate data 
from two ongoing NIDCD funded trials: 1. tDCS to Treat Aphasia: A phase II trial (CATES 
trial; DC011739; PI-Fridriksson); and 2. Neural Bases of Language and Cognitive Deficits in 
Acute Stroke and Recovery (Early Aphasia Recovery; DC005375; PI–Hillis). The CATES trial 
will provide outcome data for a behavioral treatment that combines semantic and 
phonological stimulation, which will be compared to outcomes from treatments that 
assume only a semantic or phonological treatment focus (Project 1). Data from Dr. Hillis’ 
Early Aphasia Recovery project will be utilized in project 3 to predict treatment outcome 
using neuroimaging factors. The Early Aphasia Recovery project uses DWI and PWI data to 
predict recovery from aphasia within the first year of stroke onset. This project is in its 15
th 
year of funding. We propose that the analyses planned in project 3 can further bolster the 
impact of the Early Aphasia Recovery project by applying the state-of-the-art neuroimaging 
analyses designed as part of analysis programs created by Dr. Rorden (i.e., NiiStat software: 
https://www.nitrc.org/projects/niistat/). In addition, project 3 will use baseline data 
collected for projects 1 and 2 to predict treatment outcome. Project 4 will primarily rely on 
treatment data collected in projects 1 and 2 to refine and integrate the DS model and other 
contemporary models to better understand the underlying mechanisms that give rise to 

 
20
speech errors in aphasia as well as predict recovery. The vast data collection planned 
here also provides an opportunity for others affiliated with the project (Bonilha, Den Ouden, 
and Desai) to further study language impairment and aphasia recovery. It should be 
stressed that any data shared will be de-identified; all participants will be referred to by 
an assigned study number and all documents shared will use this number to identify 
participants.  
 
In addition to the above collaborations, Dr. Guorong Wu at the University of Chapel Hill 
will assist with processing of the MR images. Dr. Wu is an expert in image segmentation, 
registration, and normalization, and will assist with the processing of the longitudinal data 
that are acquired. He will be provided with access to MRI scans and de-identified 
behavioral data. This data will be shared with him via the HIPPA compliant Dropbox.  
 
Dr. Brielle Stark at Indiana University will also have access to data for the purpose of 
analysis and interpretation. There is an MTA agreement with IU and USC to allow for data 
sharing (dated 12/18/18) of “Audiovisual data of neurophysiological testing, including 
tasks evaluating language.”  Data will be shared via the HIPPA compliant Dropbox. She will 
have access to MRI data and behavioral testing.  
 
G. References: 
 
1. 
Brady MC, Kelly H, Godwin J, Enderby P. Speech and language therapy for aphasia following 
stroke. Cochrane Database Syst Rev. 2014;5(CD000425). doi: 
10.1002/14651858.CD000425.pub2. 
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Kelly H, Brady MC, Enderby P. Speech and language therapy for aphasia following stroke. 
2010. 2010;5(CD000425). doi: 10.1002/14651858.CD000425.pub2. 
3. 
Burke E, Cramer SC. Biomarkers and predictors of restorative therapy effects after stroke. 
Curr Neurol Neurosci Rep. 2013;13(2):329. doi: 10.1007/s11910-012-0329-9. PubMed PMID: 
23299824; PMCID: 3580200. 
4. 
Floel A, Cohen LG. Recovery of function in humans: cortical stimulation and 
pharmacological treatments after stroke. Neurobiol Dis. 2010;37(2):243-51. doi: 
10.1016/j.nbd.2009.05.027. PubMed PMID: 19520165. 
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Milot MH, Cramer SC. Biomarkers of recovery after stroke. Current opinion in neurology. 
2008;21(6):654-9. doi: 10.1097/WCO.0b013e3283186f96. PubMed PMID: 18989108; PMCID: 
2882885. 
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Thors H, Richardson JD, Fridriksson J, editors. Dual stream model guided treatment of 
aphasia. Society for the Neurobiology of Language; 2015; Chicago, IL. 
7. 
Hickok G, Poeppel D. The cortical organization of speech processing. Nat Rev Neurosci. 
2007;8(5):393-402. doi: 10.1038/nrn2113. PubMed PMID: 17431404. 
8. 
Baird AE, Dambrosia J, Janket S, Eichbaum Q, Chaves C, Silver B, Barber PA, Parsons M, 
Darby D, Davis S, Caplan LR, Edelman RE, Warach S. A three-item scale for the early prediction of 
stroke recovery. Lancet. 2001;357(9274):2095-9. PubMed PMID: 11445104. 
9. 
Kertesz A. Recovery from aphasia. Adv Neurol. 1984;42:23-39. PubMed PMID: 6209949. 
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Appendix A 
Study Protocol 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
26
1. SELECTION OF PARTICIPANTS 
All participants in this study will have chronic left hemisphere stroke. Diagnostic evaluations 
will be conducted during the participants' initial visit to confirm aphasia diagnosis for treatment 
inclusion. Participants with aphasia diagnosis that are currently receiving speech and language 
treatment (apart from aphasia support groups) will be required to temporarily discontinue 
involvement until study completion. A total of 120 subjects with aphasia will be enrolled. A total 
of 30 subjects without aphasia will be enrolled. 
 
1.1 Participant Inclusion Criteria 
1. Participants must have incurred a left hemisphere ischemic or hemorrhagic stroke. 
2. Participants must be greater than 12-months post-stroke onset. 
3. Participants must between 21 and 80 years of age. 
4. Participants must have spoken English as their primary language for the last 20 years. 
5. Participants must be willing and able to provide informed written or verbal consent.  
6. Participants must be MRI-compatible (e.g. no metal implants, not claustrophobic, etc.) 
 
1.2 Participant Exclusion Criteria 
1. Severely limited verbal output. (WAB Spontaneous Speech rating scale score of 0-1) 
2. Severely impaired auditory comprehension (WAB Comprehension score of 0-1).  
3. Bilateral stroke 
 
2. STUDY PROCEDURES 
2.1 Study Procedures Overview  
After informed consent is received, a neurological examination utilizing the NIH Stroke Scale 
will be performed and multiple screening assessments will be conducted including a MRI 
safety screening. If the participants pass the initial screening portion, multiple speech and 
language diagnostic tests will be conducted. Participants will also undergo two baseline 
assessments of naming- and discourse ability (primary and secondary outcome measures) 
and structural/functional MRI examination. During the next three weeks the participants with 
aphasia will receive 45 minutes of treatment every day, Monday through Friday (weekend 
treatment/assessment may take place with schedule conflicts). After the first treatment phase 
concludes, participants will be tested, on one-two consecutive days, with the primary and 
secondary outcome measures and undergo a MRI examination. After that there will be a 4-
week break between treatment phases. In the week before starting the next treatment phase 
there will be one-two baseline testing sessions to test the primary and secondary outcome 
measures. During the next three weeks the participants will receive 45 minutes of treatment 
every day, Monday through Friday (weekend treatment/assessment may take place with 
schedule conflicts). After the second treatment phase is completed the participants will be 
tested again, on one-two consecutive days, with the primary and secondary outcome 
measures and undergo a MRI examination. Follow-up testing will occur at 4-weeks and 6-
months (at or around week 39) after completion of the second treatment phase. Participants 
will complete an anonymous satisfaction survey at the 4-week follow-up time point.  During 
testing at 6-months post treatment completion, participants will undergo a final MRI 
examination. 
 
2.1.1 Procedures for Screening (Visit 1) 
The following procedures will be performed: 
1. Obtain written informed consent: 

 
27
• A signed and dated informed consent form will be obtained from each participant 
before conducting any screening procedures. Participants will then be assigned an 
identification number by the WebDCUTM for purposes of confidentiality.  
• A media release form will be completed with each participant and caregiver if 
applicable. 
• All research staff authorized to obtain informed consent will have completed the 
Miami CITI course in the Responsible Conduct of Research and Protection of 
Human Subjects prior to their involvement with the study. Furthermore, they will be 
oriented to the study and trained by the study PI and study co-investigators who 
have extensive training and experience in the ethical and practical aspects of 
informed consent procedures.   
2. Review inclusion/exclusion criteria. 
3. Obtain medical history. 
4. Conduct neurological examination. 
5. Administer the MRI safety screening. 
 
2.1.2 Procedures for MRI Examination (Week 1, 5, 12, 39, and 52+ (if eligible for the one-
year post treatment follow-up)) 
1. Run the participant on high-resolution anatomical MRI scans during visit 1: 
• The participant will complete the fMRI Naming 40 where they will be instructed to 
name the pictures presented on the screen. If they see an abstract picture they are 
instructed to be silent. Administration time is approximately 10-15 minutes. 
• Following the fMRI Naming 40, the participant is instructed to lay still.  
• Complete additional functional and structural scans per follow-up  
 
2.1.3 Procedures for Diagnostic Testing (Collected only once. Baseline may be split 
over three days (Visit 1, 2, and 3) 
1. Administer the Western Aphasia Battery-Revised (WAB-R).  
• The WAB-R will characterize a participant’s overall language impairment through the 
evaluation of the main clinical aspects of language functioning, including speech 
content, speech fluency, auditory comprehension, repetition, naming, and reading. The 
WAB-R allows for the differentiation of these specific language abilities, as well as the 
classification of aphasia type. The WAB-R also yields a composite score, the Aphasia 
Quotient, which provides an overall measure of severity, in which lower scores denote 
more severe aphasia (Kertesz, 2007). The reading section of the WAB-R: Part 2 will be 
completed to measure participants’ oral reading ability and his or her reading 
comprehension of words and sentences. Speech- language pathologists (SLPs) will 
refer to the manual for explicit instructions regarding administration and scoring 
procedures. Administration time will range between 30-45 minutes. 
 
2. Administer the Pyramids and Palm Trees Test (PPTT).  
• The PPTT is a test of semantic processing. This test assesses the degree to which a 
participant can access meaning from pictures and words. Information from the test will 
help determine whether a participant’s difficulty in naming or pointing to a named picture 
is due to a difficulty in retrieving semantic information from pictures, or a difficulty in 
retrieving semantic information from words, or, in the case of a naming failure, a 
difficulty in retrieving the appropriate spoken form of the word (Howard & Patterson, 
1992). SLPs will refer to the manual for explicit instructions regarding administration and 
scoring procedures. Administration time will range between 10-20 minutes. 
 

 
28
3. Administer the Kissing and Dancing Test.  
The Kissing and Dancing Test is a short test to distinguish the lexical and conceptual 
contributions to noun/verb and action/object dissociation (Bak & Hodges, 2003). SLPs 
will refer to the manual for explicit instructions regarding administration and scoring 
procedures. Administration time will range between 10-20 minutes. 
 
4. Administer sub-tests 1, 2, 8, 14, 15, 16 and 17 from the Psycholinguistic Assessments of 
Language Processing in Aphasia (PALPA):  
1. Same-Different Discrimination Using Nonword Minimal Pairs.   
• All the materials in this task are monosyllabic real words with a CVC structure and 
are designed for use in conjunction with word minimal pairs (see below). Good 
discrimination of nonwords implies that Auditory Phonological Analysis is intact. Poor 
scores may be due either to impaired hearing or to impaired phonemic perception. 
Stimulus pairs are minimally different according to voice, manner or place of articulation. 
Differences occur either in initial or final positions of pairs or in pairs that are 
metathetically related (in which the order of the sounds is reversed). 
2.   Same-Different Discrimination Using Word Minimal Pairs. 
• All the materials in this task are monosyllabic real words with a CVC structure and 
are designed for use in conjunction with nonword minimal pairs (see above). By 
comparing results on this task with that using nonword minimal pairs, one can look 
firstly for any impairment in phoneme perception and secondly for whether impairment 
is reduced by lexical information. 
8. Nonword repetition. 
• All the materials in this task are nonwords. The purpose of the task is to test the 
integrity of sub-lexical acoustic –phonological conversion. It examines ability to repeat 
unfamiliar yet word-like sound forms in which length of utterance is systematically from 
one to three syllables. Although syllable length is manipulated, phoneme length is 
constant across the items.  
14. Rhyme Judgment Requiring Picture Selection. 
• This task assesses whether a subject can select a picture whose name rhymes with 
a given stimulus picture. The task requires that the subject is fist able to retrieve picture-
names from the phonological output lexicon. 
15. Word Rhyme Judgments: Auditory Version.  
• This task aims to find out if the subject can detect whether a pair of words rhyme. 
For the task to be carried out successfully, the two items must be held in storage 
temporarily while the relevant parts of the word are segmented and compared. The task 
therefore tests the integrity of phonological short-term storage systems (Monsell, 1987), 
as well as input processing abilities and segmentation skills.  
16. Phonological Segmentation of Initial Sounds. 
• All the materials in this task are monosyllabic words and nonwords of CVC 
structures. This task provides information about a person’s ability to segment at least 
the initial sounds of a heard string. By including nonwords as well as words, auditory 
analysis skills can be tested independently of lexical phonological processes. 
17. Phonological Segmentation of Final Sounds. 
• All the materials in this task are monosyllabic words and nonwords of CVC 
structures. This task provides information about a person’s ability to segment at least 
the final sounds of a heard string. By including nonwords as well as words, auditory 
analysis skills can be tested independently of lexical phonological processes. 
 

 
29
SLPs will refer to the manual for explicit instructions regarding administration and scoring 
procedures. 
 
5. 
Administer the Northwestern Assessment of Verbs and Sentences (NAVS) 
• The NAVS was designed for participants with aphasia and allows for detailed 
examination of verb processing (e.g. verb naming) as well as production and 
comprehension of canonical and non-canonical sentences  
(Cho-Reyes and Thompson, 2012). 
• SLPs will refer to the manual for explicit instructions regarding administration and 
scoring procedures. Administration time will range between 50-60 minutes. 
6. Administer subtest 7 (Matrix Reasoning) on the Wechsler Adult Intelligence Scale (WAIS) 
• This subtest is composed of four types of nonverbal reasoning tasks: pattern 
completion, classification, analogy and serial reasoning. The examinee looks at a matrix 
from which a section is missing and either identifies by number or points to one of five 
response options that complete the matrix. This test will allow for analysis of the 
cognitive status of the participants (Wechsler, 2008).  
• SLPs will refer to the manual for explicit instructions regarding administration and 
scoring procedures.  
 
7. Administer tasks used for scoring the Apraxia of Speech Rating Scale (ASRS) 
• This rating scale will be utilized to rate the presence and severity of apraxia of speech 
(AOS). It quantifies the frequency and severity of the characteristics associated with 
apraxia of speech (Strand et al., 2014). 
• SLPs will refer to (Strand et al., 2014) for explicit instructions regarding administration 
and scoring procedures. 
• To score the ASRS (offline), the following tasks should be administered:  
o DDK rates (alternating and sequential motion rates) 
o Sustained phonation (do 3x, record duration of “ah”) 
o Mayo Clinic “supplemental tasks for the ASRS." This includes word and sentence 
repetition tasks.  
o Cursory oral mechanism evaluation (ROM/strength/coordination of lips, tongue, 
jaw) 
 
8. Administer Philadelphia Repetition Test (PRT) 
• This test was designed to test speech repetition ability. It uses the same items as the 
Philadelphia Naming Test, but instead of showing the pictures to the participants, the 
names are spoken to them, once only, and participants must repeat the names back to 
the experimenter (Dell et al., 1997). 
 
9. Administer TALSA Battery (short term memory tasks) from Martin et al. (2012) 
• These tests assess verbal short-term memory. 
• TALSA Word Rhyming Triplet Judgment. This task assesses the ability to identify two 
rhyming words out of a selection of three. The non-rhyming foil will overlap 
phonologically with one of the rhyming words in one of three ways: same initial 
phoneme, same stressed vowel, or same final phoneme.  
• TALSA Rhyming Judgments. This task assesses the ability to identify if the words or 
nonwords presented rhyme with a 5 second delay presented and additionally a five 
second delay with a distraction presented. The nonwords are derived from the real 
words by altering one or two phonemes. The words and nonwords are presented 
separately. 

 
30
• SLPs will refer to Martin et al. (2012) for explicit instructions regarding administration 
and scoring procedures.  
 
10.  Administer the Hit and Avoid Learning Tasks (Phonological, Semantic, and Spatial) 
• All participants will complete three learning tasks before initiation of treatment; two 
linguistic based learning tasks (phonological and semantic) and one nonlinguistic 
learning task (spatial). These will be administered in random order for each 
participant and will be completed by the end of treatment phase one. The tasks are 
set-up similar to the classical computer game “PONG.” 
• Linguistic learning is completed by a game-like interface, where four words fall at 
randomly generated speeds from the top of a computer screen. Participants are 
asked to mouse over the words that fit the category of the game, such as ‘animal’ or 
‘has the “s” sound’, and to avoid words that are not targets but may be semantically 
or phonologically related or unrelated.  
• Nonlinguistic learning will be tested by the same game-like interface. The task 
involves shape-patterns where participants are required to identify identical shapes 
to the target shape and to avoid distractor shapes. In this way, we circumvent 
internal language representations of task stimuli. Before beginning the task, the 
participant is shown a target shape and told that they will be presented with a 
computer screen where a variety of different shapes will fall from the top of their 
screen. The participant’s objective is to mouse over the target shape and to avoid 
the other shapes (distractors). 
• All learning tasks will be conducted 5 times consecutively for 2 minutes each time. 
The accuracy score will be recorded for each session. The participant’s learning 
ability is summarized as the increase in accuracy between baseline and final 
session. The study will compare linguistically based task vs nonlinguistic learning 
tasks (each to be completed by the end of treatment phase 1 to determine whether 
learning potential relates directly to prognosis. 
 
11. Obtain Arterial Blood Pressure and Stiffness 
• Arterial stiffness plays a role in outcomes following cardiovascular disease and 
stroke, especially in individuals with hypertension. Accordingly, we will obtain 
measures of arterial stiffness using the SphygmoCor device. We will use data from 
this measue to inform our MRI analyses pertaining to brain health and its 
relationship with overall health.  
• SphygmoCor XCEL PWA (pulse wave analysis) uses a standard cuff to measure 
systolic and diastolic pressures, and capture a brachial waveform. The brachial 
waveform is then analyzed by SphygmoCor to provide a central aortic waveform. 
Central blood pressure measurements such as central aortic systolic blood 
pressure, and central pulse pressure. Aortic stiffness is approximated with non-
invasive measurement of carotid-femoral pulse wave velocity, with improvements 
made with time to make the assessment procedure quicker and more user 
independent.  
• Participants will lay supine resting for 5 minutes prior to measurement.  They will 
have a blood pressure cuff placed on their thigh.  Trained study staff will make three 
key measurements (cm) from the placement of the cuff to the major physical 
landmarks.  Study staff will locate the carotid and femoral arteries.  Using the wand, 
gentle pressure will be placed on the neck of participants at the strongest pulse 
point and study staff will move the wand slowly on the neck area around the carotid 

 
31
artery.  Participants will feel pressure on their thigh, as is normal with having blood 
pressure taken.  It will take approximately 15 minutes and participants will remain in 
the supine position resting throughout the testing.   
 
 
2.1.4 Procedures for the Computerized Naming Assessments  
Philadelphia Naming Test  (Week 1, 5, 8, 12, 15, & 39 [Administered twice- Week 1]) 
1. Turn on the laptop computer and position in front of the participant 
2. Open PNT application 
• Go to “Utilities” and “Start Webcam Preview” and stop when positioned correctly. 
• Enter participant number and session and click “Start.” 
3. Administer the Philadelphia Naming Test (PNT; Roach et al., 1996) on a laptop computer. 
The PNT is a picture-naming task consisting of 175 high- and medium-frequency nouns that 
vary in length from 1-4 syllables.  
• Instruct the participant to overtly name each picture as soon as it is displayed. 
• Trials will end following a response or after 30-seconds have elapsed. 
4. Once completed, the video file will automatically save to Dropbox and you may exit the 
application. 
 
Treated Naming 40 (Administered once on Week 1, 5, 8, 12, 15, & 39) 
 
1. Turn on the laptop computer and position in front of the participant 
2. Open Treated Naming 40 application 
• Go to “Utilities” and “Start Webcam Preview” and stop when positioned correctly. 
• Enter participant number and session and click “Start.” 
 
3. Administer the Treated Naming 40. The Treated Naming 40 is a picture-naming task 
consisting of 40 target words including 20 target words from the Semantic treatment protocol 
and 20 from the phonological treatment protocol. The target word lists will include an equal 
number of nouns and verbs. 
• Instruct the participant to overtly name each picture as soon as it is displayed. 
Trials will end following a response or after 30-seconds have elapsed. 
4. Once completed, the video file will automatically save to Dropbox and you may exit the 
application. 
 
 
2.1.5 Procedures for Discourse Assessments (Administered once on Week 1, 5, 8, 12, 15, 
& 39) 
 
1. Turn on the laptop computer and position in front of the participant 
2. Open Discourse application 
• Go to “Utilities” and “Start Webcam Preview” and stop when positioned correctly. 
• Enter participant number and session and click “Start.” 
3. Administer picture description task: Broken Window 
• Press esc when completed and file will save automatically 
4. Administer Story Narrative: Cinderella Story 
• Press “Select to finish” button on screen when completed and file will save automatically 
5. Administer Procedural Discourse Task: Making a peanut butter and jelly sandwich 

 
32
• Press esc when completed and file will save automatically 
6. Once completed, you may exit the application 
7. SLPs will refer to the manual for explicit instructions regarding administration and scoring 
procedures. Administration time will range between 20-30 minutes. 
 
 
2.1.6 Procedures for the Aphasia Communication Outcome Measure (ACOM) (Week 1 
and Week 39) 
• Administer the Adaptive Aphasia Communication Outcome Measure (CAT-ACOM; 
Doyle et al., 2013).  
• The ACOM consists of 12 items from the 59-item ACOM item bank using a content-
balancing strategy from each domain (talking, writing, number use, comprehension, and 
naming) to insure that the content balance of each CAT-ACOM is reflective of the 
content balance of the full-length ACOM. 
• SLPs will refer to the manual for explicit instructions regarding administration and 
scoring procedures. Administration time will be approximately 15 minutes. 
 
2.1.7 Procedures for Treatment (Aphasia Participants Only) (Weeks 2-4 and 9-11) 
Two different types of treatment will be used in this study; one primarily semantically focused 
and one primarily phonologically focused. Participants with aphasia will receive both types of 
treatments but in different order. The order of the sequence of treatments will be randomly 
assigned. 
 
 
 
Semantically focused treatment tasks: 
 
1. Semantic Feature Analysis. This task requires participants to actively analyze a concept 
and to attempt to generate its semantic features. 
 
2. Semantic Barrier Task. Clinician and participant sit opposite to each other with a barrier 
between them so that they cannot see the picture the other one has in front of them. 
Both have a set of pictures and they take turns giving the other individual enough 
semantic information to identify the picture they have in front of them. 
 
3. Verb Network Strengthening Treatment (VNeST). This treatment approach targets 
lexical retrieval of verbs and their thematic nouns. The objective is for the participant to 
generate verb-noun associates with the purpose of strengthening the connections 
between the verb and its thematic roles and ultimately improve sentence production. 
 
 
 
Phonologically focused treatment tasks: 
 
1. Phonological Components Analysis. This task requires participants to first name a given 
picture, and then identify the phonological features of the target word. Once the features 
have been identified, participants are required to attempt to name the picture again.  
 
2. Phonological Production Task. This task requires participants to first sort a stack of 
targeted imageable nouns and verbs by one syllable and more than one syllable words 

 
33
by tapping out each syllable. The treatment then continues to focus on the identification 
of a hierarchy of phonological features with a given pair of targeted words. Once each 
targeted feature is identified for the pair of words, the participant is then required to 
blend the syllables/sounds together.  
 
3. Computerized Phonological Judgment Task. Participants will watch videos of a speaker 
producing words and nonwords, and will press a button (green for yes, red for no) to 
indicate whether successive stimuli rhyme, start with the same syllable, have the same 
number of syllables, etc.  
 
Each treatment task will take about 15-minutes so the total treatment time will be 45 minutes 
per day.  
 
2.1.8 Data Collection for Treatment Tasks 
 
Semantic Feature Analysis: 
 
• Target word is presented prior to beginning the feature analysis to determine if 
participant can independently name. Credit given if the participant can name correctly, 
or with >50% of the phonemes correct and being intelligible to an unfamiliar listener.  
 
• Once the analysis is completed, and also reviewed, the participant is again asked to 
name the target word a second time. Same criteria for correct/incorrect is used.  
 
 
  
Semantic Feature Barrier Task: 
 
• Document numbers of the target words that were used in the task (ex: cards #21-28), 
and whether it was a closed set (where both clinician and participant have the 
exact same cards, per example both persons would have cards #21-28 in front of them) 
or an open set (where the clinician and participant have different cards in front of them, 
per example: clinician would have #21-24, and participant would have #25-28, each 
having only four cards in front of them)  
  
Verb Network Strengthening Treatment (VNeST):  
 
• 
After STEP 4 in VNeST protocol, Data is collected for Steps 5 and 6. The either do or 
do not receive credit for being able to: recall the target verb correctly, as well as 3 WHO’s 
and 3 WHAT’s. Credit can be given for any 3 correct WHO’s and WHAT’s even if they vary 
from the original 3 that were discussed during the VNeST activity.   
  
Phonological Components Analysis:  
  
• 
Target word is presented prior to beginning the feature analysis to determine if 
participant can independently name. Credit can only be given if participant names target 
correctly without any phonemic errors.  
  
• 
Once the analysis is completed, and also reviewed, the participant is again asked at the 
end to name the target word a second time. Same criteria for correct/incorrect is used.  

 
34
 
Phonological Production Task: 
 
• 
Data is kept on which of the levels the participant participated and how many trials were 
completed in that day. Typically, 5 or more repetitions of one level are to be completed 
before moving on to the next combination; however, clinician can use judgment to move on 
to the next level if participant completed less than 5 in the time allowed, but was not 
exhibiting significant difficulty with the task.    
  
• 
If participant goes through all of the levels, start over again at “First Syllable – First 
Syllable” and move through the cycle a second time. 
  
Phonological Judgment Task: 
 
• 
Data is kept on which of the 10 Levels the participant worked on, and what the % of 
accuracy was for the level(s) that day. Sometimes with time required for training the task 
there is only time for one attempt, but often time the task will be completed twice in one 
session. Clinician can use clinical judgement as to when to stay at a certain level even if 
the percentage was low, or when to move up even if the participant has not mastered that 
level at 80% (ex: if frustration level gets too high on a certain level, switching to a different 
task)  
  
  
 
 
2.1.9 Procedures for Completion of Participant Satisfaction Survey 
• At or around the 4-week follow-up testing date, all treated participants will be asked to 
complete an anonymous participant satisfaction survey.  Participants may complete this online 
through a link that we email to them or will be given a paper copy of the survey with an 
addressed, stampled envelope to return the survey.  A family member or friend will be asked to 
assist the participant in answering the questions on the aphasia-friendly survey. 
  
2.1.10 Procedures for >one-year follow-up  
• Participants who are at least one-year post-treatment will be called back for follow up testing 
to determine change in performance on a subset of the initial baseline measures or treatment 
outcomes. They will also be asked to complete the entire battery of MRI sequences. 
Participants will be paid $100 for this visit (in the form of a Visa giftcard). They will be provided 
lodging and roundtrip mileage reimbursement if they reside outside of the Columbia, SC 
metropolitan area (>35 miles travel distance).  
• They will be asked to fill out a payment form and a W-9 so that the payment can be processed.  
• Specific measures that will be administered at this time include the:  
• Western Aphasia Battery-Revised 
• Philadelphia Naming Test  
• Philadelphia Repetition Test  
• Pyramids and Palm Trees Test, Kissing and Dancing Test  
• Aphasia Bank Discourse Assessments  
• Updated case history form/health history form  
• PALPA subtests 
• National Institutes of Health Toolbox – Cognitive Battery  

 
35
• Aphasia Communication Outcome Measure (ACOM)  
• WAIS Matrix Reasoning Subtest  
• Sphygmacor aterial stiffness measure  
  
  
  
  
  
  
  
  
  
 

 
36
 
  
 
 
 
 
 
 
 
 
 
Appendix B 
Scripts for Treatment tasks 
 
 

 
37
 
 
 
 
 
 
 
 
 
Semantically focused treatment tasks  

 
38
SEMANTIC FEATURE ANALYSIS (nouns & verbs) 
 
• We are going to look at some pictures. We will name the items in the pictures and 
also talk about many different features of these items.  
• Get whiteboard 
• I am going to place a picture in the middle of the board, and I would like for you to 
name the item in the picture if possible. (place in center) Can you tell me the name of 
this item? 
o If they are able to correctly name, then “Great, you said _________. Now let us 
review the different features.” (write name of the item) 
o If they approximate with an artic error, semantic or phonemic paraphasia, then 
“Very close, you said ________. The name of the item is _______________ (and 
write the name of the item on the whiteboard). Now let us review the different 
features.” 
o If they are unable to name, then “The name of the item is ___________ (and write 
the name of the item on the whiteboard). Now let us review the different 
features.” 
o *Note when reviewing features below – NOT EVERY FEATURE IS APPROPRIATE 
FOR EVERY TREATMENT STIMULUS. ONLY ELICIT THOSE FEATURES 
APPROPRIATE FOR THE STIMULUS ITEM.  
• The first feature is group or category membership. (For very first session, “For 
example, a triceratops is a dinosaur.”) Your item (or just name it) is a member of 
which group? 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• The second feature is use or utility. (For very first session, “For example, a telescope 
is used to look into outer space.”) What is ________ used for? 
o *If animal or person, SKIP 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• The third feature is action. (For very first session, “For example, a triceratops eats 
plants and runs from the t-rex”). What does ________ do? 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• The fourth feature is properties, or a description. (For very first session, “For example 
a triceratops has three horns and four legs”). What are some properties of _______? 
(max 3) 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 

 
39
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• The fifth feature is location. (For very first session, “For example, a telescope is found 
near a window or on a rooftop”). Where do we find _______? 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• The last feature is association. (For very first session, “For example, a triceratops 
reminds me of a rhinoceros”). What does _______ remind you of? 
o If produced, write in box and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), write in box, move to 
next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), write in box, move 
to next feature. 
• To review the features again, try to say them with me 
o it is a _________ (group),  
o it is used for __________, it _______ (action),  
o it has/is __________,  
o it is found _________,  
o and it reminds you of ________.   
• What is the name of this item? 
o If produced, then “Great, next item.” 
o If approximated, shape to correct, have them repeat correct form after you, and then 
“Great, next item.” 
o If not produced, then “Say this after me: _____________” OR “Say it with me: 
_________” “Great work on that. Lets move to the next item.”  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
40
SEMANTIC FEATURE - BARRIER (nouns & verbs) 
 
• I am going to deal some cards out to the both of us. We will each have a matched 
deck of X* cards (*5-10, depending on participant ability). ^ We will take turns 
describing the pictures to each other without saying the name of the pictures to try 
and get the other person to guess which picture we are describing.  
o ^If the participant is very good at this and/or as the treatment progresses, you may 
not need a matched deck. The matched deck is really to help narrow the field and 
give options for the participant to choose from.  
• Before we start giving clues to each other, I want to quickly review the semantic 
features that you may decide to use as clues.  
• Get semantic barrier sheet 
• For example, if you were holding a picture of __________ (select sample card), you 
might provide a clue like (give an example sentence about ‘group’ feature) or (give an 
example clue about ‘use’ feature). If I am not able to guess which picture you are 
describing, you could provide another clue like (give an example sentence about 
‘physical properties’) or (give an example sentence about ‘association’).  
• If you have a hard time giving me clues, I will ask you to describe, draw, write, or 
gesture some features. If you are still having difficulty, I will ask you to describe or 
gesture the use or action. If we are still stuck, I will ask you to name the picture if 
possible and/or show me your card. We will review a few features together before 
moving to the next picture. 
• Place barrier between you and client, give stack of cards 
• For very first session, clinician goes first to model  
• Okay, I am going to give you 2 clues.  
o First – (give group info), and 
o Second – (give use info, gesturing when appropriate) 
• Can you guess which picture I am describing? 
o If correct guess, “Yes, I was describing ___(target word)____. (summarize 
features). Now, your turn.” 
o If incorrect guess, provide 2 additional clues/features appropriate for the stimulus 
item, gesturing when appropriate. “Can you guess which picture I am 
describing?” 
 If correct guess, “Yes, I was describing ___(target word)___. (Summarize 
features). Now, your turn.” 
 If incorrect guess, review features you have already provided, provide 1-2 
more if appropriate, then “I was describing ___(target word)___. Can you 
say that word with me? __________.” 
• All right, now it is time for you to give 2 clues. You can use your feature visual to 
help get you started. 
o Hopefully they provide 2 clues. **If they do, and if it is obvious, guess correctly. If 
they do, and if you are pretty confident you know what it is but if it is the least bit 
ambiguous, guess incorrectly, choosing the alternative. They would then need to 
provide more clues.  
o If they are only able to provide 1 clue, ask them if they can give you more 
information. ** 
o If they are unable to provide clues, ask them to describe, draw, write, or gesture 2 
specific features (name the specific features on their chart, direct them to their visual 
aid). ** 

 
41
 If still having difficulty, ask participant to describe or gesture the use or action. 
** 
 If still having difficulty, ask participant to name the picture if possible and/or 
show the card.  
o Once clinician has correctly guessed or participant has named or shown picture, 
review features. “You were describing ___(target word)___. Can you say that 
word with me? __________” Now, please fill in the blank with the features you 
provided: (review only those provided, unless unable to provide, in which case, 
select 2-3 features to review) 
 it is a _________ (group),  
 it is used for __________, it _______ (action),  
 it has/is __________,  
 it is found _________,  
 and it reminds you of ________.   
• Take turns until time is up. 
 
For week 2, we can consider alternating between Clue-giving and 20 questions during the 
semantic barrier portion of the session.  
 
 
 
 

 
42
VERB NETWORK STRENGTHENING TREATMENT (VNeST) 
 
• Now we are going to talk about some verbs and try to make sentences using some 
cards.  
o Pick a card with a target verb for the session out of the 10 possible verbs and put it 
on the table in front of you. 
Step 1. Generation of 3 agents and patients for targeted verb. 
 
1. For this step I want to ask you to tell me who can __(target verb)__ (e.g. ‘tell me 
who can measure’) * The participant does NOT have to say the verb, only the nouns. 
o Write down the word ‘who’ at the top left corner of a dry erase board. For each word 
generated, write the word underneath ‘who’ or place a card with the word written on 
it. Encourage the participant to provide personal responses.  
o A minimum of 3 words is required before moving to next step. If correct, move on to 
the next step. 
o If participant cannot produce 3 words, give the participant 2 cards with appropriate 
responses on them and 1 foil written on them. “Now I have given you some cards 
to choose from. Can you tell me which ones you think go with the verb and 
which ones do not?”  
o If still incorrect, provide the participant with the correct answer and get them to say it 
with you. 
2. Now,  I want to ask you to tell me what can be_(target verb)_ (e.g. ‘what can be 
measured’. 
o Write down the word ‘what’ at the top right hand corner of the dry erase board. For 
each word generated, write the word underneath ‘what’ or place a card with the word 
written on it.  
o If participant cannot produce 3 words, give the participant 2 cards with appropriate 
responses on them and 1 foil written on them. “Now I have given you some cards 
to choose from. Please read the word pairs aloud and then tell me which ones 
you think go with the verb and which ones do not?”  
o If correct, move on to the next step. 
o If incorrect, provide the participant with the correct answer and get them to say it 
with you. 
o Once 3 agents and 3 patients have been produced, move on to next step. 
 
Step 2: Read aloud each triad. (it’s not important to conjugate the verb or add any 
articles to the nouns (e.g. ‘farmer drives tractor’).  
o They may be read aloud independently, in unison with clinician, or repeated 
after the clinician. 
 
Step 3. Answer wh-questions about agent-patient pair 
• Now I want you to pick one pair of person and item that you want to discuss further. 
o Write or move the pair of words (agent-verb-patient) that they choose out of the list 
of agents and patients to focus attention. Write or place cards with  ‘where’, ‘why’ 
and ‘when’ on the dry erase board. 
• Now I am going to ask you to answer some questions about this pair of words. (The 
participants do NOT have to respond with complete sentences). A) Where does a _(agent-
verb-patient)_? (e.g., where does a chef measure sugar B) Why does a _(agent-verb-
patient)_? (e.g., why does a chef measure sugar?) C) When does a _(agent-verb-
patient)_? (e.g., when does a chef measure sugar?)  

 
43
o If correct, move on to the next step. 
o If incorrect, give the participant options to choose from and say it with them. 
Step 4. Semantic judgment of sentences. 
• Remove all the cards from the table. 
• Now I am going to read some sentences and I want you to tell me if the sentences 
make sense (are semantically correct) or not. 
o Read the 12 sentences containing the target verb (3 correct, 3 with inappropriate 
patient, 3 with inappropriate agent, 3 with agent and patient switched).  
o After each sentence, “Did this one make sense?” 
o If participant answers 5 out of 6 correctly, you may move on.  
o To challenge participant you may ask them to correct the sentence. 
o Once successful, move on to the next step 
Step 5. Produce target word independently 
o 
Now I want you to tell me what verb we were working on today. If they are unable to 
produce independently then say the verb and have them repeat. 
Step 6. Generation of 3 agent-participant pairs (repeat Steps 1-2) 
• Now we are going to go back to the first thing that we did today, but this time we are 
not going to use the cards. 
o Ask the exact same questions that were asked in Step 1, but without the cards. (i.e., 
Tell me who (or what, to be alternated throughout a session) can __(target 
verb)__ (e.g. ‘tell me who can measure’) (be _(target verb)_ (e.g. ‘tell me what 
can be measured’).) 
o Provide the participant with general feedback (e.g. “good job” etc.)  
• Once successful, start over from the top using a different verb. 

 
44
 
 
 
 
 
 
 
 
 
 
Phonologically focused treatment tasks 
 
 

 
45
PHONOLOGICAL COMPONENTS ANALYSIS  
 
• We are going to look at some pictures. We will talk about different sound features of 
the objects or actions in the picture. 
• Get whiteboard 
• I am going to place a picture in the middle of the board, and I would like for you to 
name the item in the picture if possible. (place card in center). Can you tell me the 
name of this item?  
o If they are able to correctly name, then “Great, you said _________. Now let us 
review the different features.”  
o If they approximate with an artic error, semantic or phonemic paraphasia, then 
“Very close, you said ________. The name of the item is _______________). 
Now let us review the different features.” 
o If they are unable to name, then “The name of the item is ___________  
Now let us review the different features.” 
• The first feature is the first sound of the item you see. (For very first session, “For 
example, the word lotion starts with the sound ‘l’.) What is the first sound of this 
item?  
o If produced, write in box, then read together* “the first sound is ____” and move to 
next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the first sound is ____” and move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the first sound is ____” and move to next feature. 
 *for all features, the participant does NOT have to say the carrier phrase if 
they cannot or do not wish to, just try to encourage them to fill in the blank 
with you. 
• The second feature is the number of syllables. (For very first session, “For example, 
the word lotion has two syllables”(tap out 2 syllables).) How many syllables does this 
word have?  
o If produced, write in box, then read together “the number of syllables is ______ 
(then tap), and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the number of syllables is ______ (then tap), and 
move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the number of syllables is ______ (then tap), and 
move to next feature. 
• The third feature is the last or final sound of the item you see. (For very first session, 
“For example, the final sound of the word lotion is “n”.) What is the final sound?  
o If produced, write in box, then read together “the last sound is ____” and move to 
next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the last sound is ____” and move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the last sound is ____” and move to next feature. 
• The fourth feature requires us to think of or make up a word that rhymes with our 
item. (For very first session, “For example, a word that rhymes with lotion might be 
“ocean” or “motion”.) What is a word that rhymes with ___________?  (max 2) 

 
46
o If produced, write in box, then read together “____(target)___ rhymes with 
____(rhyming word)___” and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “____(target)___ rhymes with ____(rhyming 
word)___” and move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “____(target)___ rhymes with ____(rhyming 
word)___” and move to next feature. 
• The fifth feature is the vowel sound of the first syllable. (For very first session, “For 
example, the vowel sound of the first syllable of lotion is “o”). What is the vowel 
sound of the first syllable? (If the word is monosyllabic, acknowledge that and feel free to 
change your script to “the vowel sound of this word”.)  
o If produced, write in box, then read together “the vowel sound of the first syllable 
(or word) is _______” and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the vowel sound of the first syllable (or word) is 
_______” and move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the vowel sound of the first syllable (or word) is 
_______” and move to next feature. 
• The last feature (IF MORE THAN ONE SYLLABLE) is the vowel sound of the last 
syllable. (For very first session, “For example, the vowel sound of the last syllable of 
lotion is “uh”.) What is the vowel sound of the last syllable?  
o If produced, write in box, then read together “the vowel sound of the last syllable 
is _______” and move to next feature. 
o If approximated, shape to correct (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the vowel sound of the last syllable is _______” 
and move to next feature. 
o If unable to produce, provide answer (model w/ carrier sentence), prompt to repeat, 
write in box, then read together “the vowel sound of the last syllable is _______” 
and move to next feature. 
• Great, we’ve reviewed all of the features. I want to go over them again, and I want 
you to say each feature with me. (provide carrier phrase, they fill in with you with unison 
speech)  
o The first sound is __________, 
o The number of syllables is ____#____,(and then tap out together) 
o The last sound is __________, 
o A rhyming word is ___________, 
 (if listed 2, Another rhyming word is _________), 
o The vowel of the first syllable is ________, 
o The vowel of the last syllable is _______. 
• What is the name of this item? 
o If produced, then “Great, next item.” 
o If approximated, shape to correct, have them repeat correct form after you, and then 
“Great, next item.” 
• If not produced, then “Say this after me: _____________” OR “Say it with me: 
_________” “Great work on that. Lets move to the next item.” Go through all the steps 
using a different picture. 

 
47
PHONOLOGICAL PRODUCTION TASK  
 
• We need to sort the picture cards into words that have only 1 syllable and words that 
have 2 or more syllables.  
• I’ll do the first few. (Pick a card and tap the word while you say it.) That had X syllable(s) 
so it goes in this pile. (Do for a few more cards.) 
• Okay, now we will work together. This word is “_______” (and tap at same time). How 
many syllables does it have? OR Can you tap it out for me?  
o Let them try independently first.  
o If incorrect, “Close, but watch me – (say the word and tap). X syllable(s).” 
•  Complete entire stack or stop at 5 minutes.  
 
• “Now we have a stack of single syllable words and a stack of multi syllable words. 
We are going to break these words down into smaller syllables and sounds and then 
mix them all up to make new words. These words will not make any sense most 
likely, but they will be new words we are creating.” 
 
• First syllable – First syllable (with multisyllabic cards only) 
o “First we will focus on the first syllable of words.”(Place target picture on 
board.)  
 This word has X syllables. (tap all syllables). The first syllable of this 
word is “___” (write syllable on white board)  
 Place next picture on board. 
 This word has X syllables. (tap all syllables). The first syllable of this 
word is “___”(write syllable on white board) 
 Now, let us make a new word with the first syllables of these words. 
“______” plus “______” makes “___________” (touch syllables while 
saying the isolated syllables, and then pull written syllables together to make 
the final nonword while you are talking) 
 “Now, let’s review and say these together.” 
• The first syllable of this word is “_________” (say together) 
• The first syllable of this word is “_________” (say together) 
• “_____” plus “______” makes “___________” (say together, the 
syllables and nonword, or the nonword at the very least) 
• Complete 5 trials. 
• Follow the same steps with the given hierarchy: 
 First syllable – First syllable (multisyllabic cards only) 
 First syllable – Last syllable (multisyllabic cards only) 
 Last syllable – Last syllable (multisyllabic cards only) 
 Last syllable – First syllable (multisyllabic cards only) 
 First syllable – First sound (multisyllabic cards for first, single syllable cards for second) 
 Last syllable – Last sound (multisyllabic cards for first, single syllable cards for second) 
 First syllable – Last sound (multisyllabic cards for first, single syllable cards for second) 
 Last syllable – First sound (multisyllabic cards for first, single syllable cards for second) 
 
DECISIONS 
 Monitor what subtask they finish each day and start with next level on the hierarchy if 5 
trials have been completed. If less than 5 trials were completed and participant is 
exhibiting significant difficulty, repeat current level. Use clinical judgment to move 
throughout each level. 

 
48
 
COMPUTERIZED PHONOLOGICAL JUDGMENT TASK 
 
• Open Phonological Video Treatment application on the laptop  
o Enter participant number, session number and treatment level.  
o Press start.  
 
 
• Read the instructions that come up on the computer screen out loud to the participant and 
make sure they understand what is being asked of them. Give them an example of the 
task, e.g. if they’re doing the first task you give them an example of two words that have the 
same number of syllables and two that don’t.  
o “In this task, you will see two videos at a time. Each video is of a person's mouth 
saying a single word. Listen closely to both words” 
o Complete the practice first.  
o Once the practice is completed, press start to begin task 
 
LEVEL 1: Same number of syllables? 
• You will see 2 videos.  
• Press GREEN if they have the SAME number of syllables.  
• Press RED if they do not. 
LEVEL 2: Which has more syllables? 
• You will see 2 videos. 
• Press GREEN if the FIRST word has more syllables. 
• Press RED if the SECOND word has more syllables. 
LEVEL 3, 4, & 5: Start with the same sound? 
• You will see 2 videos. 
• Press GREEN if they START with the SAME sound. 
• Press RED if they do not. 
LEVEL 6, 7, & 8: End with the same sound? 
• You will see 2 videos. 
• Press GREEN if they END with the SAME sound. 
• Press RED if they do not. 
LEVEL 9 & 10: Do they rhyme? 
• You will see 2 videos. 
• Press GREEN if they rhyme. 
• Press RED if they do not. 
 
Criteria for each level: 
o If participant scores <60% the program will recommend they move down a level. 
o If participant scores between 60%-80% then they remain at the same level. 
o If participant scores 80% or above, they should move up to a harder level. 
o If a participant were to achieve an 80% or above on all levels prior to completion of treatment 
phase. Begin at level 1 and increase the target score to 90% or higher for each level. 
 
DECISIONS: 
o Clinical judgment may be used to determine whether the participant moves up or down a level in 
certain circumstances. For example, if the participant has just moved on to a new level and they are 
not demonstrating understanding of the task and they score below 60%, clinical judgment can be 
used to override the protocol for dropping back a level. Another example would be if the participant 
is frustrated and stuck on a particular level for several attempts, clinical judgment can be used to 
allow them to try the next level up (particularly if it is a separate targeted skill).  

 
49
Appendix C: Alternative Remote Protocol During COVID 19 Quarantine 
 
A.  Modifications for Remote Assessment 
 
To continue to enroll participants during the Covid 19 quarantine, some procedures will 
be adapted to be able to administer assessments online.  Changes are listed and explained 
below. 
 
1.  Online Platform – Individuals completing the assessments will be assigned a private, zoom 
account.  This online platform allows researchers to connect to participants in their own homes 
via video-conferencing.  Video-conferencing will be password-protected and any 
videorecordings made during the assessment will be saved to the researcher’s local computer 
and then transferred to a HIPAA-compliant dropbox account.  Participants will be asked to 
have a friend or family member (assistant) to be present throughout the assessment to assist 
with the technology. 
 
2.  Informed Consent – Potential participants will be mailed 2 copies of the informed consent 
document with a pre-addressed, stamped envelope in advance of the assessment session.  
The individual consenting the participant will review the informed consent via video-
conferencing with his/her assistant who can assist with the technology as needed.  The 
participant (or his/her assistant) will sign the consent and show it to the clinician via his/her 
webcam.  The clinician will take a screen shot of the form for a digital copy.  The participant will 
be asked to mail the original, signed form back to the Aphasia Lab in the stamped, pre-
addressed envelope provided. 
 
3.  Behavioral Assessments – Behavioral assessments have been adapted to be administered 
online.  A brief training session will take place before administration of assessments to make 
sure that the participant and his/her assistant can demonstrate how to use controls in the zoom 
platform to point to pictures on a shared screen.  The assistant will also be instructed on how 
to alter the webcam to allow the clinician to view the participant completing different tasks. 
 
4.  MRI/fMRI Tasks – MRI scans and the fMRI tasks will be postponed for participants until the 
COVID 19 quarantine is over.  At that time, participants will be contacted for an MRI/fMRI 
scanning appointment at MCBI.   
 
B.  Modifications for Remote Treatment 
 
1.  Teletherapy Kits – Each enrolled participant will be mailed a teletherapy kit to complete 
treatments.  These kits will include: 
• A laptop, touchscreen computer pre-loaded with the treatment apps, zoom for online 
videoconferencing with the SLP and Team Viewer which will allow the SLP to see the 
participant’s computer to help with initial set-up and troubleshooting. 
• A high quality headset with a microphone to maximize communication with the SLP 
online. 
• A mouse for optional use. 
• A mobile WiFi hotspot if a participant does not have adequate WiFi connection at 
home. 
 
2.  Treatment Apps – Participant laptops will be preloaded with both semantic and 
phonological treatment apps which wil allow the SLP to interact with the participant during 
treatments.  The assistant will be asked to help with the treatment technology if necessary. 
 

 
50
Appendix D. POLAR Research Plan 
1. Significance.  
Although some stroke patients experience significant spontaneous recovery in the first few days and 
weeks following onset, approximately 30-40% of patients are left with persistent aphasia affecting 
communication ability and life participation. Stroke is generally associated with older age, but a 
significant proportion of patients incur stroke in the fourth to sixth decade of life (15). Once spontaneous 
aphasia recovery has ceased, patients’ greatest chance at significant communication improvement is 
by means of aphasia treatment. Although considerable evidence suggests that aphasia treatment is 
effective, the problem is that very little is known about what kind of treatment works best, and for whom 
(2, 3, 16, 17). As suggested in a recent paper by Fama and Turkeltaub (18), the standard of care for the 
treatment of aphasia in the United States is behavioral speech-language therapy. However, what 
exactly this therapy consists of probably varies widely - what might be common practice at one clinical 
facility might be very different than what is practiced somewhere else. As anyone who has extensive 
experience treating aphasia knows, it is simply not the case that all treatment approaches work equally 
well, not even for patients with similar impairments (19). Nevertheless, we believe that an appropriately 
weighted use of combined behavioral and neurophysiological biomarkers should improve our ability to 
predict treatment outcome, as well as aid in the choice of optimal treatment targets for individual 
patients with aphasia.  
In the most downloaded article in the history of the Public Library of Science, “Why Most Published 
Research Findings Are False,” Ioannidis (20) noted that when all factors are equal, in fields where 
smaller studies are the norm, the chances of research findings being false is much higher than in fields 
where larger studies are typical. The norm in aphasia treatment studies, including our own previous 
studies, is to rely on single-subject design or very small group studies. It is straightforward to 
understand why this is the state of affairs. Treatment studies take a relatively long time and a 
disproportionate level of resources compared to most other kinds of research in aphasia. Also, subject 
recruitment is often an issue, especially in studies that target patients with specific cognitive/linguistic 
impairment profiles. Nevertheless, our field needs larger treatment studies to reveal specific trends that 
can be generalized to the larger population of patients, not just to a narrow number of cases. We 
believe that our past success, institutional environment, and collaborative spirit puts us in a position to 
conduct a relatively large aphasia study that has the potential to exert a sustained impact on the field of 
clinical aphasiology. In the context of previous aphasia treatment studies, the project proposed here 
entails a relatively large sample size of treated patients (N=120) and extensive cognitive/linguistic 
testing, including assessment of learning potential and neuroimaging workup. As we contend that 
recent meta-analyses studies have demonstrated the value of aphasia treatment, the purpose of project 
1 is not to test the efficacy of treatment, but rather to determine why some patients respond better to 
treatment than others and whether treatment response relates to which language domains are targeted 
in treatment. In addition to testing hypotheses in project 1, the data collected here will also fuel projects 
3 (PI: Rorden) and 4 (PI: Hickok).  
1.1 Biomarkers of Treated Aphasia Recovery. In 1972, Darley (21) suggested that factors such as 
age, education, intelligence, social status, health, time post-stroke, and aphasia type are related to 
success in aphasia therapy, but that very few studies had actually incorporated these factors as 
predictors of outcome. More than four decades later, the situation has not improved much, as limited 
research has established a strong relationship between specific patient factors and treated aphasia 
recovery. A few studies have related patient characteristics to spontaneous recovery (6, 7, 22-24); 
however, it is not known whether the same factors would predict aphasia treatment outcome. 
Accordingly, clinicians who routinely treat patients with aphasia have very limited empirical data to 
guide their treatment and predict outcome. Whereas biomarker studies are common in medicine, 
almost no studies have been carried out to understand the relationship between patient factors and 
aphasia rehabilitation potential in stroke (25-27). This may not be a particular problem in academic 
settings where extensive diagnostic behavioral tests can be administered. But in clinical settings such 
as rehabilitation hospitals, sub-acute nursing facilities, long-term care facilities, and home health care 

 
51
settings, financial and personnel resources are limited and often allow for only one initial assessment 
session (28). The point here is that the clinicians who provide most of the aphasia therapy in the United 
States could far better serve their patients if they were armed with prognostic factors that would indicate 
whether a given patient was likely to respond to direct speech and language therapy (SALT), and what 
focus that treatment should assume for maximum recovery. In the spirit of Darley’s argument, we 
believe that patient factors such as aphasia severity and patterns of cognitive/linguistic impairment 
may, indeed, provide clinicians with the necessary biomarkers regarding the type of treatment that 
should be utilized and the extent of expected improvement. Therefore, the major goal of Aim 1 is to 
build a predictive model of treated aphasia recovery based on biographical and cognitive/linguistic 
factors. Henceforth, we refer to this model as the “default model” of outcome prediction.  
1.2. Models of Treated Aphasia Recovery. In a recent publication, Geranmayeh, Brownsett, and 
Wise (29) proposed a model to explain where in the brain plastic changes that support aphasia 
recovery occur. Their model is mostly based on neuroimaging studies conducted in the past two 
decades, but it provides far greater insight into spontaneous rather than treated aphasia recovery. As 
such, this model offers minimal guidance regarding the current project where the goal is to predict 
outcome based on biographical, cognitive/linguistic, and neuroimaging factors. It is widely assumed that 
a large number of factors predict how likely a given patient is to respond to aphasia treatment. 
However, we are not aware of comprehensive theories that attempt to predict aphasia treatment 
outcome. As a first step, we adopt a data-driven approach to explain response to aphasia treatment. By 
most accounts, the process of theory building includes the following steps: 1. Observation; 2. 
Description; 3. Categorization; and 4. Analysis and a statement about causality. For Aim 1, the first 
three steps are accomplished by data collection and data organization that rely on patient and caregiver 
questionnaires, direct behavioral testing, and MRI scanning. As we explain in section 3.10 (Data 
Analyses), the final step is achieved by first using step-wise multiple regression to identify the most 
important predictors and then rely on support vector regression analyses (SVR; See Neuroimaging 
Core for details) to compare different explanatory models. For the sake of clarity, we are not going to 
focus on the potentially very complex interactions between the environment (e.g., family support, 
access to healthcare, and residential setting) and treatment outcome, as doing so would probably 
constitute an increase in effort that far exceeds what can be supported in the current project. Instead, 
our default model focuses on two sets of factors that we propose are related to aphasia treatment 
response. 1. Biographical factors: Age (30, 31); education (32, 33);, gender (23, 34); handedness (35); 
age at stroke, type of stroke, number of strokes, and time post first stroke that caused the aphasia (36); 
2. Cognitive/linguistic factors: Clinical assessment of aphasia (6, 7, 37), motor speech production (38), 
grammatical processing (39), semantic processing of verbs and nouns (40-42), phonological 
processing (43, 44), speech discrimination (45-47), speech repetition (48-50), executive functioning 
(51-56), and verbal short-term memory (57-60). We have chosen to cite research that supports the role 
of the aforementioned factors as predictors of aphasia treatment outcome; however, it is beyond the 
scope of the proposal to speculate how these factors might interact to support treated aphasia 
recovery. Once we have built our final data-driven model(s), it will be possible to examine the specific 
interactions between the factors that make up each model.  
Aphasia severity is one of the very few factors that has been identified as a reliable predictor of aphasia 
treatment outcome, and it is generally accepted that more severe patients are less likely to respond 
(61, 62). It is a caveat, however, that aphasia severity is a multidimensional construct where different 
patients with severe aphasia might present with very different language impairment profiles. We believe 
that contemporary neuropsychological models of speech and language processing can help us better 
understand which aspects of language impairment predict response to aphasia treatment. This may 
seem like a straightforward notion. However, it is important to note that neuropsychological models of 
speech and language are typically designed to explain how specific processes are rooted and related in 
the brain, but not to account for dynamic changes in response to behavioral manipulation. 
Nevertheless, if speech and language impairment can be predicted based on lesion data (63-73), it 
seems reasonable to expect that the extent of brain damage and lesion location in relation to the 
cognitive processes they support may also aid in the prediction of aphasia treatment outcome. The dual 
stream (DS) model was conceived to explain how auditory information maps onto the phonological-

 
52
articulatory (dorsal stream) and conceptual systems (ventral stream) in the brain (1, 74, 75). Even 
though this model has been highly influential in speech and language research for over a decade, it has 
not gained much traction in the aphasia rehabilitation literature. In Aim 2, we will test whether 
proportional damage to the anatomically defined dorsal and ventral streams improves outcome 
prediction beyond what can be achieved with the default model in Aim 1. Specifically, by adding factors 
that comprise the default model and DS model factors (proportional damage to the dorsal and ventral 
streams) we will be able to predict treatment outcome with greater accuracy compared to the default 
model alone. We refer to this as the “default model + DS model” (D+DS model). Note, however, that 
damage to any area that is supplied by the middle cerebral artery in the left hemisphere is likely to 
improve prediction beyond the default model. Hence, we will compare the utility of the DS model to the 
Wernicke-Lichtheim-Geschwind anatomical model (76-78) to predict aphasia treatment outcome. 
Accordingly, the crucial questions we aim to answer are whether the default model can be improved by 
combining it with the DS model and whether the DS model fares better in comparison to its older 
counterpart, the Wernicke-Lichtheim-Geschwind model (D+WLG model). We certainly recognize that 
the WLG model has been fervently challenged for well over a century and that its power to explain 
individual patients may be limited. However, most published aphasia research (e.g., 79-82), including 
contemporary lesion studies (83, 84), continues to report aphasia types based on the WLG model and, 
in some ways, the model could be considered a simpler version of contemporary dual stream models of 
speech processing. It is widely recognized by clinicians in neuropsychology, behavioral neurology, and 
speech-language pathology. As such, the WLG model serves as a reasonable control to which to 
compare the DS model.  
Figure 1. A schema depicting the three models that will be tested for predicting aphasia treatment outcome in Aims 1 and 2.  
 
Figure 1 shows the relationship between the models that will be tested in Aim 1. The default model 
(yellow) includes biographical and cognitive/linguistic factors that are collected in the first few patient 
sessions. A different model assumes improved outcome prediction by combining the default model with 
proportional damage to the cortical areas that comprise the WLG model (red; D+WLG model). We 
hypothesize that the strongest prediction of outcome will be achieved by combining the default model 
and the DS model (blue; D+DS model).  
Along with several other groups, we have demonstrated that functional brain changes in the residual 
language areas of the left hemisphere support treated improvement in naming in aphasia (77, 78, 85-
87). Based thereon, we could conclude that strengthening of the residual left-hemisphere language 
network, the areas that remain intact after stroke, leads to improved language processing in aphasia. 
However, as far as we can tell, no research has examined whether this kind of network compensation 
relies on overall network integrity or survival of specific sub-components of the network. We suggest 
that the DS model offers a principled approach to answer such questions. For example, for cases of 
damage to the ventral stream, and concomitant semantic impairment (a component of the default 
model), treatment might focus specifically on semantic stimulation. Here, one could assume that 
preservation of the ventral stream would be related to treatment success, so that patients with greater 
damage to the ventral stream are less likely to respond compared to others whose ventral stream is 
relatively more preserved. This view would contend that successful rehabilitation relies on the survival 
of the network that is being stimulated. However, an opposing view could argue that what really matters 

 
53
is cross-domain compensation where the dorsal stream is forced to become more strongly involved 
to support improvements in language. The same logic could be applied to the WLG model, but with less 
detail, as it is a relatively cruder model compared to the DS model. Hence, because the DS model 
provides a more detailed model of language organization in the brain, we hypothesize it will outperform 
the WLG model and provide better prediction of treatment outcome. Along these lines, we propose that 
reliance on the DS model can potentially improve our understanding of why some patients show greater 
improvements than others and relate the findings in neuroanatomy. As the DS model is a functional 
model that is grounded in neuroanatomy, it could be the case that measures of proportional damage to 
dorsal and ventral streams are redundant with the speech and language measures included in our test 
battery. In that case, the D+DS model will not outperform the Default model. Dr. Rorden’s project 
(Project 3) will rely on the same behavioral data collected here, but unlike the current project, it focuses 
on developing sophisticated neuroimaging analyses to understand the relationship between localized 
brain damage and aphasic impairment/recovery. The benefit of this setup is that each project may yield 
complementary results that can better explain differences in treatment response among patients.  
1.3. Comparing Biomarkers as a Function of Treatment Foci. One of the challenges to interpreting 
the value of aphasia treatment biomarkers is the generalizability across different kinds of treatment 
types and foci. For example, in one of our previous studies (38), the severity of apraxia of speech 
(AOS) was found to be a strong negative predictor of success in speech entrainment treatment, a 
training program that emphasizes real-time mimicking of audio-visual speech narratives by patients with 
non-fluent aphasia. Although AOS is generally recognized as a deterrent to aphasia treatment success 
(88), it is not guaranteed that the same relationship between AOS severity and patient improvement 
would have been realized had the treatment included a different approach such as Melodic Intonation 
Therapy (89, 90), a treatment program also specifically designed to improve speech production in non-
fluent aphasia. For that reason, Project 1 will rely on a cross-over design where each patient completes 
one treatment phase that focuses on semantic stimulation and another treatment phase where the 
focus is on phonological stimulation. Accordingly, we will be able to compare biomarkers of treatment 
outcome and determine if the same factors predict success, regardless of treatment focus, or whether 
biomarkers are dependent on treatment focus. In one of our previous studies (10, 85), a group of 30 
patients with aphasia underwent anomia treatment in a cross-over design where one half of the patients 
first received 15 hours of treatment using a phonological cueing hierarchy and then later received 15 
hours of treatment with a semantic cueing hierarchy. The remaining half of the patients received 
treatment in the opposite order, semantic treatment first and then phonological treatment. Overall, there 
was a wide range in treatment responses across the patients, and treatment success with phonological 
stimulation was not correlated with success in the semantic treatment. Relying on data from this study, 
we conducted post hoc analyses to provide proof of concept for the current project (see Section 3.1 – 
Preliminary Studies). Specifically, we used a subset of the factors that comprise the models shown in 
Figure 1 (default model, D+DS model, and D+WLG model) to predict success in semantically and 
phonologically focused anomia treatments. Our decision to divide the treatment phases to target 
semantic versus phonological stimulation was based on the fact that most impairment based treatment 
approaches tend to assume a semantic or phonological focus (10, 91-99). However, despite the fact 
that aspects of semantic and phonological processing are thought to dissociate at both the behavioral 
(40, 91, 92, 100-104) and cortical level (105-107), it is practically impossible to dissociate semantic and 
phonological stimulation in aphasia treatment. Accordingly, we emphasize that we use treatment 
methods that stress phonological stimulation but will also induce semantic processing, and vice versa. 
The key here is treatment focus rather than complete dissociation of targeted processes in treatment.  
In addition to relating patient factors to treatment outcome, Aim 1 will take advantage of data collection 
in the CATES trial (‘Trans-cranial Direct Current Stimulation to Treat Aphasia: Phase II Trial’ U01 
DC011739). As we discuss in greater detail in section 3.1 (Preliminary Studies), the aphasia treatment 
in the CATES trial relies on a computerized training task that includes both phonological and semantic 
stimulation. Each of the two treatment phases used in the current project will emulate the timing 
components (timing of pre-post treatment testing, length and number of treatment sessions) of the 
treatment phase in the CATES trial. Accordingly, we will be able to compare potential predictors of 
aphasia treatment success across the current project and the CATES trial.  

 
54
1.4 Learning Potential as a Biomarker of Aphasia Treatment Outcome. Learning is driven by 
neuroplasticity – the ability of the brain to continuously adapt its structure and function based on 
internal and external environmental changes. Neuroplasticity occurs due to changes in neuronal 
morphology, glia, and vascular and metabolic processes and can be stimulated by a variety of sensory-
motor experiences (108-112). Learning potential is a common concept in the education literature (113, 
114). It assumes that not all individuals have the same ability to acquire new information and probably 
reflects flexibility of neural systems to adapt to internal changes or external stimulation (112, 115-117). 
Although most clinicians probably assume that some aphasic patients have greater rehabilitation 
potential than others, it is not clear whether patients’ learning potential is related to aphasia treatment 
outcome. Unlike the measures included in Aims 1 and 2 that mostly represent static factors (e.g., 
performance on cognitive/linguistic tests, proportional damage to specific brain regions), learning 
potential represents dynamic change, something that could be assessed at baseline to understand if 
prolonged aphasia rehabilitation is likely to be effective. Aim 3 is therefore to assess the predictive 
value of learning potential for aphasia treatment outcome.  
2. Innovation.  
2.1 Developing a Model to Predict Aphasia Treatment Outcome. Comparing the outcomes of 
treatments that assume either a semantic or phonological focus is not new in the aphasia literature (91, 
93, 94, 96, 98, 99). However, most of this research has relied exclusively on single-subject design or 
very small group studies. To the best of our knowledge, no previous studies that included relatively 
large sample sizes have attempted to identify biomarkers of aphasia treatment outcome. Each patient 
enrolled here will undergo a comprehensive cognitive/linguistic test battery, including measures of 
learning potential. Relying on the same SVR approach used in Project 3, we will construct a 
computational model that includes the factors that strongly predict treatment success. Then, we will 
make that model available on-line in a web based format so that clinicians can find out which tests to 
administer. They can then plug in their test results to predict the likelihood that a given patient will 
respond to speech and language treatment. Furthermore, at the end of Project 2 (PI: Hillis) we will also 
be able to explore whether a default model predicts response to speech and language therapy (SALT) 
with a phonological-semantic focus.  
2.2 Relating Dual Stream Damage to Aphasia Treatment Outcome. Since its inception, the dual 
stream model of speech processing (1, 74, 75) has been highly influential in the field of cognitive 
neuroscience and neurolinguistics. Published in 2007 (1), the most comprehensive article that 
describes the model has now been cited over 1,400 times. As far as we can tell, the current project is 
the first to study whether damage to the cortical areas that support the dorsal and ventral streams 
predicts outcome in aphasia therapy. We suggest that this is not only a highly innovative approach but 
also has theoretical and practical implications for understanding the factors that drive successful 
treatment outcomes in patients with aphasia. As we explained earlier, by relating damage in the dorsal 
and ventral streams to treatments with semantic versus phonological focus, it will be possible to judge 
whether outcomes depend on relative intactness of each processing stream. The initially broad focus of 
the phonological and semantic treatment approaches is necessary to relate ventral and dorsal stream 
damage to treatment outcome. Later, we can focus on what specific aspects of treatment contribute to 
aphasia recovery.  
2.3 Measuring Whether Patients’ Ability to Learn Predicts Treatment Success. Normal subjects’ 
ability to learn new information has been studied extensively for many decades (11, 12, 118, 119). 
Whereas it is beyond the scope of the current project to summarize the findings, it is clear that the 
ability to learn varies quite significantly among the general population (11, 13, 14, 120-122). As 
recovery from aphasia requires a (broken) system to relearn information, it is plausible that learning 
ability, as measured at baseline, should be related to how well a given patient responds to treatment. 
Our approach to take learning potential into account is innovative, given that this is an area of study 
that has received very little attention in previous aphasia treatment research. By charting short-term 
improvement on two separate tasks – one that relies on language processing and one that does not – it 
will be possible to understand if learning potential as a predictor of aphasia treatment outcome is 

 
55
domain general or domain specific. If Aim 3 yields positive results, it would indicate that learning 
tasks could be added as part of the baseline test battery to inform the default model.  
3. Approach  
3.1 Preliminary Studies. As we discussed earlier in section 1.3, one of our previous aphasia treatment 
studies (N=30 chronic patients with aphasia) related lesion and fMRI data to improvements in naming 
following 30 hours of anomia treatment (10, 85). Each patient completed two 15-hour treatment phases 
separated by one week where one treatment phase focused on a semantic cueing hierarchy and the 
other used a phonological cueing hierarchy (123). To provide support for Aim 1, we reanalyzed some of 
the data from this study to explore whether biographical factors (gender, chronological age, age at 
stroke, time post-stroke, and race) and cognitive/linguistic factors (Western Aphasia Battery subtests; 
WAIS Matrix Subtest; Pyramids and Palm Trees test [PPTT], Boston Naming Test [BNT]) predict 
treatment outcome. These factors would be a part of our “default model” of outcome prediction. As this 
was an exploratory analysis, we used multiple step-wise regression with a liberal p-value threshold for 
significant predictors (p<.10).  
Figure 2. The relationship between age at stroke (y-axis) and treatment related changes in correct naming (x-axis).  
 
Treatment outcome (change in correct naming before and after treatment) was predicted separately for 
the phonological treatment, the semantic treatment, and overall treatment (collapsing across the 
phonological and semantic treatments). Two statistically significant regression models predicted 
phonological treatment outcome, Model 1: Age at stroke (F=3.6, p=.06, R2=.11); Model 2: Age at stroke 
+ scores on the PPTT (F=3.9, p=.03, R2=.22). Similarly, two models emerged as significant predictors 
of semantic treatment outcome, Model 1: BNT scores (F=16.2, p<.0001, R2=.37); Model 2: BNT scores 
+ Age at stroke (F=10.7, p<.0001, R2=.44). Finally, two models predicted overall treatment outcome, 
Model 1: BNT scores (F=9.8, p<.0001, R2=.26); Model 2: BNT scores + Age at stroke (F=11.5, 
p<.0001, R2=.46). In relation to the current proposal, we find that these results are particularly important 
for three reasons: First, in a sample that only included 30 patients, one of our models (Model 2 for 
overall outcome: BNT scores + Age at stroke) accounted for almost half (46%) of all the variance in 
predicting which patients are likely to respond to treatment. Second, it appears that among the 30 
patients who completed our study, the age when they had the stroke was a particularly important 
predictor of who was likely to respond to treatment (Figure 2). Finally, a combination of both 
biographical factors (Age at stroke) and cognitive/linguistic factors (PPTT and BNT) provided the best 
outcome prediction. Although the cognitive/linguistic test battery we used was not ideal for predicting 
outcome, we contend that these data provide strong support for Aim 1, which will rely on a more 
targeted cognitive/linguistic test battery and a far larger patient sample than our preliminary study.  
To provide support for Aim 2, we further analyzed the dataset discussed above to test whether adding 
the WLG model (proportional damage to the arcuate fasciculus, Broca’s area [pars opercularis+pars 
triangularis+pars orbitalis] and Wernicke’s area [STG]) to the default model (based on the regression 
analysis above: Age at stroke; PPTT, & PNT) would improve outcome prediction. Similarly, we 

 
56
combined the factors in the default model with the DS model (proportional damage to the dorsal 
stream [pars triangularis+pars opercularis+posterior STG] and ventral stream [posterior MTG+posterior 
ITG+temporal pole]) for outcome prediction. The results are summarized in figure 3. We compared the 
models using SVR (leave-one-out method) where the factors in each model were used to predict 
treatment related changes in correct naming. The output from this analysis is the correlation 
coefficient between the actual improvement scores and the predicted scores. For improvements in 
correct naming associated with semantic treatment, phonological treatment, or overall treatment 
(collapsing across phonological and semantic treatments), the D+DS model provided the strongest 
outcome prediction. In fact, the D+DS model accounted for approximately 30-40% better reduction in 
error (R2) than the D+WLG model across the three treatment outcomes. Although our research only 
included 30 patients, the results strongly support our plan in Aim 2 to add behavioral and lesion factors 
to predict treatment success using SVR.  
Figure 3. A comparison of the three models for predicting anomia treatment success. Color coding of the models corresponds to Figure 1.  
 
To provide proof of concept in support of Aim 3, we also analyzed data from the study described above. 
One way to estimate learning is to measure changes in contextual support (e.g. cueing) needed to 
evoke the correct response (124). The cueing hierarchies used in our study were ordered so that the 
weakest cues were presented first but proceeded to stronger cues if correct naming was not achieved. 
We recorded the level of cueing needed to elicit correct naming for each stimulus presentation across 
all treatment sessions. This allowed us to calculate change scores for the level of cueing needed to 
elicit correct naming during the beginning compared to the end of the first treatment session. Then, 
these change scores were used to predict overall improvement in correct naming following 
completion of all 30 hours of treatment (Figure 4).  
Figure 4. Changes in the level of cueing in the initial phonological treatment session predict overall treatment outcome. Outliers are in red box.  
 

 
57
The results revealed that changes in cueing strength during the initial phonological treatment session 
strongly predict overall treatment outcome, F(1,29)=25.28, R2=.50, p<.0001. When two outliers were 
removed, these statistics changed to, F(1,27)=89.34, R2=.78, p<.0001. Changes in cueing during the 
first semantic treatment session also predicted overall change in correct naming, F(1,29)=21.3, R2=.45, 
p<.0001. When aphasia severity was included as a cofactor, both regression analyses remained 
statistically significant and the R2 only showed a minimal decrease. These results suggest that patients 
whose level of cueing strength needed to elicit correct naming decreases during the initial treatment 
session are far more likely to respond to the overall treatment, regardless of initial aphasia severity. We 
recognize that decreased reliance on cues during naming may not be a classical learning task and that 
what we deem “learning” in this context could also be called “stimulability” or priming. Regardless, 
performance on the cueing hierarchy task by our 30 patients was a highly robust predictor of outcome 
and no other factor – behavioral or neuroimaging – came even close in terms of predictive power. From 
a theoretical perspective, it is a caveat that we do not know whether the changes in cueing level 
represent a general learning mechanism or something that is language specific. Therefore, in addition 
to measuring potential changes in cueing strength during a baseline session that uses cueing 
hierarchies to elicit picture naming, all patients will also complete a separate learning task that does not 
explicitly rely on language processing. As a result, it will be possible to determine if initial success in 
treatment is related to language independent learning or is language specific. For the purpose of 
control, we will use a hand-eye coordination task that is similar to the classical computer game 
“PONG.” Available at USC and MUSC, the hardware used for the control task is a KINARM End-Point 
Lab with Dexterit-E software (BKIN Technologies, Kingston, Canada). Patients are seated in a modified 
wheelchair base designed for stroke survivors who grasp a handle with their left hand. The patients 
move their less-affected hand in the horizontal plane to interact with visual targets displayed in the 
same plane as their hand by a virtual reality system. The actual task is a two-minute ‘object hit and 
avoid task’ where the patients use a virtual paddle attached to left hand to hit away two kinds of visual 
targets (n=160) while trying to avoid other kinds of non-targets (N=80). The task is repeated five times 
and accuracy is collected for each run. Target shape, location and speed are randomly distributed, 
ensuring that every task repetition is distinct. Task difficulty increases slightly over time by slowly 
increasing the number of objects and their movement speed. To provide ‘proof of concept’ that aphasic 
patients show learning on this task, we had 11 patients complete this task five times each. Figure 5 
shows that the overall accuracy (average number of target shapes hit and non-targets avoided) 
increased over the five runs.  
Figure 5. Task accuracy (y-axis) by 11 aphasic patients on the control learning task over five runs (x-axis). Error bars denote standard error.  
 
For Aim 3, our plan is to plot a learning curve over the five runs and use the slope of the curve to 
predict overall outcome in aphasia treatment. Along with many other groups, we have demonstrated 
that audio/visual (AV) speech perception modulates frontal areas typically implicated in motor speech 
output (125-127). Our studies were specifically conducted to inform aphasic impairment and to 
understand if AV speech processing has implications for aphasia treatment. In Fridriksson et al (2009; 
125), we demonstrated that a training task that involves picture-word matching where the words are 
presented as AV stimuli (seeing just the mouth of a talker) yields greater improvement in naming 
compared to a treatment that relies on picture-word matching with audio-only stimuli. The treatment 

 
58
task used in this study was fairly simple: Patients see a picture of an object on a computer screen (2 
sec) followed by AV or audio-only presentation of a noun. The noun either matches the preceding 
picture or includes a phonemic, semantic, or an unrelated foil. The phonological relatedness of 
semantic and phonological foils to the target noun is parametrically varied. Patients must determine 
whether the picture and AV (or audio-only) stimulus match by pushing a green (correct match) or red 
(incorrect match) response button. Immediate feedback is provided in the form of a “smiley” face for 
correct responses and a “frowny” face for incorrect responses. We found that patients show greater 
improvement in picture naming following a training phase that includes AV stimuli compared to training 
that relies on audio-only stimuli. This method was used in two subsequent pilot studies using anodal 
tDCS to enhance aphasia treatment outcome (128-130). Moreover, we continue to rely on the AV 
version of this treatment approach in our current CATES trial and plan to use it in project 2 (PI: Hillis). 
Although there is limited consensus on what constitutes “typical” aphasia treatment, we suggest that 
our approach builds on some of the same treatment principles often incorporated in current aphasia 
treatment approaches. For example, it includes a parametric relationship between treatment targets 
and cues (92, 123) and response-contingent feedback (93, 131). Besides taking into account literature 
on AV speech processing, this approach incorporates both phonologically and semantically related 
distractors. Therefore, it relies on both phonological and semantic stimulation within the same treatment 
task. For the purpose of the current project, we simply refer to the approach as ‘speech and language 
treatment’ (SALT) for aphasia. We will examine whether the same factors that predict outcome in 
treatments that assume a phonological or semantic focus also predict outcome in the CATES trial.  
3.2 Study Aims – Overall Strategy. Our plan is to treat 120 participants with chronic aphasia caused 
by damage to the left hemisphere (Appendix I: Study Protocol). Utilizing a cross-over design, each 
participant will receive 45 minutes of aphasia treatment per weekday (5x/week) focusing on treatment 
tasks that emphasize semantic or phonological stimulation (Table 1). Half of the patients will receive 
treatment in the following order: a. 15 treatment sessions utilizing phonological stimulation tasks; b. 4-
week inter-treatment interval; c. 15 treatment sessions with semantic stimulation oriented tasks. The 
remaining half of patients will receive treatment administered in the opposite sequence. Patients will be 
randomized to receive treatment in either order. During the first baseline visit (W0), patients’ 
biographical and testing information is entered into online modules in WebDCUTM (see Administrative 
Core). All subsequent patient data, including testing and treatment scores, MRI related information, and 
treatment fidelity information, will also be entered and stored using WebDCUTM. To establish treatment 
baselines and for the purpose of in-depth characterization of the patient sample, each patient will 
undergo extensive testing during the week prior to treatment. Data from baseline testing will also be 
used for the purpose of projects 3 (PI: Rorden) and 4 (PI: Hickok). To assess treatment- related 
changes in speech and language processing, testing will occur during the weeks immediately before 
and after each treatment phase. Follow-up testing will occur 4-weeks and 6 months after completing the 
second treatment phase. To assess damage to the cortical areas included in the WLG and DS models, 
patients will undergo MRI (see Neuroimaging Core) at baseline during the week before treatment is 
initiated. Approximately two-thirds of the patients will be enrolled at the University of South Carolina. 
The remaining one- third will be enrolled at the Medical University of South Carolina under the 
supervision of Dr. Bonilha, a stroke neurologist with ample experience managing aphasia, and a long-
time collaborator of the PI.  

 
59
 
3.3 Sample Size. The data described in section 3.1 provide the basis for our power analysis. For Aim 
1, the primary goal is to construct a model that predicts aphasia treatment success. We recognize that 
correlations based on small sample sizes can be influenced by outliers, and therefore using the full 
model results described in 3.1 could provide liberal estimates. Therefore, we used the factors described 
in 3.1 to compute exhaustive leave-one-out regression values, resulting in the more conservative 
R2=.088, R2=.27 and R2=.36 for phonological, semantic, and overall treatment effects (rather than .22, 
.44 and .46). This suggests that a sample size of 120 individuals provides 0.95 power at p < 0.05, and 
0.85 power at p <0.01. Deriving power estimates for Aim 2 is more speculative: rather than comparing 
against a static null hypothesis (e.g., treatment has no influence) we are comparing against different 
dynamic models that will each benefit from a larger sample size (as we discuss in more detail in section 
4.7 of project 3). Conventional analyses suggest that a sample size of 120 individuals will provide 0.92 
power at p <0.05 for supporting the weakest effect, shown in Figure 3 (default model’s ability to predict 
phonological treatment benefits) and 0.72 power at p < 0.05 for distinguishing the difference between 
the default model and the D+DS model. We note that a null result for the latter in the presence of a 
robust result in the former could still be clinically meaningful, potentially suggesting that initial 
behavioral tests are sufficient for treatment planning (as we discuss in section 2 of project 3). For the 
purposes of projects 3 and 4, we will also test (but not treat) additional 30 patients with chronic left 
stroke who do not present with aphasia. Accordingly, the total number of patients enrolled here will be 
120 for project 1 with additional 30 patients tested for projects 3 and 4 (total sample = 150 patients).  
3.4 Patient Eligibility. Participants with chronic aphasia (>12 months from stroke) as a result of left 
hemisphere stroke (ischemic or hemorrhagic) will be included (specific inclusion/exclusion criteria are 
discussed in Protection of Human Subjects). Persons who incur more than one stroke will be excluded 
only if the subsequent stroke(s) includes the right hemisphere. The chance of recurrent stroke has been 
reported to be as high as nine times greater than having a first stroke and at least 30% of all stroke 
patients have had more than one stroke (132, 133). Thus, excluding patients with more than one stroke 
fails to reflect the general population of stroke patients thus limiting the generalization of the findings. 
However, projects 3 and 4 will rely only on data from patients with first event stroke, because these 
projects focus on making inferences about specific brain-behavior relationships rather than application 
to clinical practice. The number of strokes will be included as co-factors in the statistical analyses 
planned for each aim. Proportional damage to different cortical areas will be determined based on 
structural MRI scans.  
Exclusion criteria are as follows: 1. Severely limited verbal output. As some of the treatment tasks rely 
on verbal output, it is pertinent to exclude patients who are essentially mute or whose speech only 
consists of stereotypies (judged as score of 0-1 on the Spontaneous Speech rating scale on the WAB); 
2. Severely impaired auditory comprehension. Potential participants will be excluded if their 
Comprehension subscore on the WAB falls in the 0-1 range. Moreover, participants will be excluded if, 
as per clinical judgment, it is determined that they do not understand treatment task instructions; 3. 
Because damage to different cortical areas will be determined using MRI, patients with 
contraindications to MRI will be excluded.  

 
60
3.5 Aphasia Treatment. Since our primary goal is to assess predictors of treatment that can be 
applicable to existing practices, we need to select treatments that are typically employed. Neither 
semantic nor phonological processing exists independently of each other in oral language use. 
Accordingly, the treatment approaches to be used here do not focus exclusively on either semantic or 
phonological processing; they each involve both, but place different emphasis on semantics versus 
phonological processing. In fact, even when semantic processing is the treatment emphasis, these 
treatments also affect phonological processing and vice versa (Appendix II: Scripts for treatment tasks). 
We stress that the main purpose here is not to assess whether one treatment focus is more potent than 
the other for improving language processing. Rather, we only include the two treatment foci to 
understand if factors that predict outcome with one treatment approach also predict success using the 
other treatment approach. In addition, we include two semantic and phonological treatment foci to 
explore whether damage to the dorsal and ventral streams differentially predicts response to 
phonological and semantic treatment. Project 4 (Hickok) will attempt to zero in on measurement of 
“computational” level deficits and assessment of the computational effects of treatment. As we discuss 
both semantically and phonologically focused treatments, this must be kept in mind.  
Semantically focused treatment tasks: Three types of tasks will be featured. 1) Semantic feature 
analysis (SFA) has a relatively long history as a treatment approach for aphasia (134-136)\. For each 
pictured stimulus the patient is prompted to name the picture. Then, he or she is encouraged to 
produce semantically related words that represent features similar to the target word (e.g. 
superordinate category, use, action, physical properties, location, and association). For example, to 
elicit a location feature, a clinician might say “where do you typically find this object?” If the patient is 
not able to name the target item once each word feature has been produced, the clinician will say target 
word. Regardless of naming accuracy on the last item, treatment continues on to the next stimulus 
item. Because both nouns and verbs (137, 138) have been used for SFA- focused activities, stimuli for 
SFA tasks here will utilize both. 2) The second semantic treatment approach is the semantic barrier 
task. This approach includes features of the Promoting Aphasics’ Communication Effectiveness 
(PACE) approach (139-142) and has also been included as part of constraint-induced language 
therapy(143). It relies on a stack of picturable stimuli, which are split between the patient and clinician 
and placed face up on a table. A visual barrier is placed between the clinician and the patient so they 
cannot see each other’s pictures. The goal of the task is for one participant (e.g., patient) to describe 
each card so that the other participant (e.g., clinician) can guess the picture on the card. Participants 
are only allowed to describe the semantic features of the target and the clinician models the kinds of 
cues that are allowed. The clinician and patient take turns describing pictures. 3) The third approach, 
Verb network strengthening treatment (VNeST), is a semantic treatment approach that targets lexical 
retrieval of verbs and their thematic nouns (144, 145). The objective of VNeST is for the patient to 
generate verb-noun associates with the purpose of strengthening the connections between the verb 
and its thematic roles. VNeST can be modified to fit patients with very limited speech output (e.g., using 
sentence completion).  
Phonologically focused treatment tasks: Three approaches, also with sound research pedigrees, will 
the used. 1) The first is the phonological components analysis task (96), which was modeled after 
semantic feature analysis. It requires the patient to first name a given picture and then to identify the 
phonological features of the  
 
target words (e.g., first sound, syllables, last sound, association, and rhyme). Once the features have 
been identified, patients are required to attempt to name the picture again. Then, the treatment moves 
on to the next item in a stack of targeted imageable nouns. 2) Phonomotor treatment is a phonologic 
sequence-based therapy that includes two stages of training that targets speech perception and speech 
production (146-150). In Stage 1, the clinician uses multi-modality stimulation to practice perception 
and production of speech sounds in isolation. Stage 2 mirrors stage 1 but focuses on speech sounds in 
a variety of consonant-vowel sequences.  

 
61
3) The phonological judgment task relies on computerized presentation of verbs and nouns where 
patients are required to judge whether pairs of words include similar phonological features (142, 151, 
152). The task is comprised of five conditions that entail determining if a set of words: a. Includes the 
same number of syllables; b. Includes the same initial syllable; c. Includes the same final syllable; d. 
Which word has more syllables; and e. rhyme. Patients respond to each condition by pressing one of 
two response buttons depending on the task requirements and instructions.  
3.6 Biographical Factors and Cognitive/linguistic Assessments. Biographical factors: For the 
purpose of recording data on biographical factors, each patient (and/or caregiver) will be required to fill 
out a case history form and a questionnaire on previous medical events, years of education, etc. 
Cognitive/linguistic testing: The following tests and tasks will be utilized to assess cognitive/linguistic 
status at baseline, before any treatment starts: 1. The revised version of the WAB will be used to 
assess overall aphasia severity and type (153). Although the WAB does not provide in-depth analysis 
of speech and language impairment, it is a test that is commonly used in clinical practice as well as a 
reasonable measure of overall aphasia severity; 2. The Apraxia of Speech Rating Scale (ASRS; 154) 
will be utilized to rate the presence and severity of apraxia of speech AOS (note: the ASRS constitutes 
a major component of project 3); 3. To assess grammatical processing (agrammatism), we will rely on 
the Northwestern Assessment of Verbs and Sentences (155). The NAVS was designed for patients 
with aphasia and allows for detailed examination of verb processing (e.g. verb naming) as well as 
production and comprehension of canonical and non-canonical sentences; 4. The Pyramids and Palm 
Trees Test (PPTT; 156) and the Kissing and Dancing Test (KDT;(157) will be used to assess amodal 
semantic processing of nouns and verbs, respectively; 5. To assess phonological processing, several 
sub-tests from the Psycholinguistic Assessments of Language Processing in Aphasia (PALPA; 158) will 
be utilized (a. Auditory discrimination of nonword minimal pairs; b. Auditory discrimination of word 
minimal pairs; c. Rhyme Judgments for pictures and words; d. Phonological Segmentation of initial and 
final sounds); 6. To assess speech repetition ability we will rely on the Philadelphia Repetition Test 
(PRT), a low-imageability word repetition test (159), and the non-word speech repetition sub-test from 
the PALPA (158); 7. For analysis of cognitive status, the Matrix test on the Wechsler Adult Intelligence 
Scale (WAIS; 160)\ will be administered; 8. To assess verbal short-term memory, we will use tasks 
described by Martin et al. (161). Their tasks allow for detailed evaluation of lexical-semantic 
performance in relation of verbal short-term memory load. All patients will be screened for visual field 
cut and visual neglect using a short in-house test developed by Dr. Rorden. To minimize the influence 
of test fatigue, the assessment battery will be spread over two sessions administered on two separate 
days during the week before the first treatment phase starts. The motivation for the extensive 
behavioral test battery included here is to provide a comprehensive set of factors used to predict 
treatment outcome. In addition, the behavioral data collected here will also feed into projects 3 and 4 
(e.g. non-word repetition and PRT). For details on test reliability, validity, and clinician training, see 
Clinical Core.  
3.7 Learning tasks for Aim 3. All participants will complete two learning tasks before initiation of 
treatment: Language learning – We will rely on the same cueing hierarchy naming task used in 
Fridriksson (2010; 10) and Fridriksson et al (2012; 85). This task will be completed in a 1-hour session 
administered before the initiation of the initial treatment phase. Semantic and phonological cues will be 
randomized to apply to individual items and the measure of learning will be qualified as change in the 
level of cueing at the beginning of the session compared to the end of the session. Thus, it will be 
possible to separately calculate changes in naming that rely on semantic cues versus phonological 
cues. We have already demonstrated that improved performance on this task within a single session is 
a very strong predictor of anomia treatment success (see pilot data in Figure 4). Hit-and-avoid task – 
Each patient will complete the hit-and-avoid task described earlier (see pilot data in Figure 5). Mean 
accuracy for each of five runs will be plotted on patient-by-patient basis and the slope of the learning 
curve will be utilized as a predictor of aphasia treatment outcome. The total administration time of the 
hit-and-avoid task is approximately 15 minutes.  
3.8 Treatment Outcome Measures. Consistent with the CATES trial and project 2, change in correct 
naming  

 
62
 
on the Philadelphia Naming Test (PNT; 162) will be assessed as an outcome measure. Confrontation 
naming is included on most comprehensive aphasia tests and is commonly assessed in aphasia 
treatment research, making it possible to compare the findings in the current project to other studies. 
The PNT will be administered twice during the week before and twice during the week after each 3-
week treatment phases (scores averaged to reduce variability). For follow-up testing, the PNT will be 
administered again at four weeks and six months after completion of the second treatment phase. The 
primary outcome measure, however, is specifically defined as change in correct naming immediately 
before and after each treatment phase. The PNT is a computer-based assessment of naming for 
persons with aphasia and includes 175 pictures representing mid- and high-frequency nouns from a 
word frequency list compiled by Francis and Kucera (163). Participants are videotaped during 
assessment and responses are scored offline. The clinicians who score the PNT will be blinded to 
when each assessment video was recorded, either before or after each of the two treatment phases. In 
addition to assessing changes in correct naming, potential treatment-related changes in naming errors 
will also be scrutinized. For a more detailed description of PNT scoring and training of clinicians, see 
Clinical Core.  
To evaluate the effects of treatment on discourse abilities, patients will complete a discourse protocol 
included in AphasiaBank, an archival database of discourse samples funded by the NIDCD since 2007. 
Three discourse tasks will be administered before and after each treatment phase: 1. Broken Window 
picture sequence description (164); 2. Cinderella story telling (165); and 3. A procedural description of 
how to make a peanut butter and jelly sandwich (first introduced by Davis, 1901 (166), as referenced in 
Lau, 2013 (167)). Transcription will be accomplished through the Clinical Core using transcription 
(CHAT) and the automated coding analysis (CLAN) systems available through AphasiaBank. We have 
already used this setup to assess outcome in aphasia treatment (38). As in the CATES trial, the 
analyses used for discourse samples will focus on lexical and syntactic aspects of spoken discourse: 1. 
Content words/min (excludes repetitions and nonwords); 2. Propositional density (168, 169); 3. 
Verbs/utterance. Each of these three measures is already included in AphasiaBank and it is a 
particularly nice feature that our data can be compared against the 440 aphasic patients included in 
AphasiaBank. This feature is especially important for determining variance across participants. In 
addition, we will assess potential changes in patients’ ability to generate main concepts (170). Finally, 
to assess the effects of treatment on functional communication ability, all participants will be 
administered the Aphasia Communication Outcome Measure (ACOM; 171). The ACOM consists of 59 
items that probe different aspects of real life communication situations and can be administered in 15-
30 minutes. Whereas the PNT and discourse measures will be administered during the weeks 
immediately before and after each treatment phase, the ACOM will only be administered at baseline 
before both treatment phases and again at four weeks after completion of each treatment phase. By 
only administering the ACOM four weeks after treatment completion it may allow participants more time 
to realize potential treatment effects on functional communication ability.  
3.9 Neuroimaging. The effects of stroke on cortical areas that are described in the DS model 
(proportional damage to the dorsal stream [pars triangularis+pars opercularis+lateral precentral 
gyrus+area Spt] and ventral stream [posterior MTG+posterior inferior MTG+temporal pole]) and WLG 
model (Broca’s area [pars opercularis+pars triangularis+pars orbitalis], arcuate fasciculus, and 
Wernicke’s area [STS+STG]) will be qualified as proportional damage to each cortical region. Excluding 
area Spt (Sylvian fissure at the parietal- temporal boundary), the regions of interest (ROIs) for each 
cortical region will be selected using the Johns Hopkins University standardized brain atlas (172). We 
note that there is no standard way to determine what ROIs should be included in either model. The 
ROIs for the DS model were selected in consultation with Dr. Hickok, including an ROI for area Spt that 
was derived from a previous fMRI study (173). The ROIs for the WLG model were selected based on 
input from Drs. Hillis and Bonilha, both of whom have extensive history with lesion-symptom mapping 
research in aphasia. Note that in comparison to the current project, Project 3 will accomplish much 
more detailed analyses of our neuroimaging data in relation to treatment outcome.  

 
63
3.10 Data Analyses Aim 1 – To construct the default model, both biographical and 
cognitive/linguistic factors are entered into a step-wise regression analysis using a leave-one-out 
method. This approach narrows down the number of factors that provide independent prediction of 
treatment outcome. The leave-one-out method controls for selection bias where the same subjects are 
not used to select the factors and test the model. The factors that survive in the final step-wise 
regression model are then entered into the support vector regression (SVR) analysis to determine how 
well the default model predicts actual outcome in patients. SVR is a more robust alternative to multiple 
linear regression. Both methods use a linear model to characterize the relationship between the 
predictors and the target variable (e.g, change in correct naming); that is, the target variable is modeled 
as a weighted sum of predictors, plus the offset term. The difference between the two methods is in the 
estimation of the model parameters (the weights and the offset). In multiple linear regression, it is done 
by computing the Moore-Penrose pseudo inverse of the predictor matrix; this minimizes the prediction 
errors in the least-squares sense, but leads to highly unstable estimation if there is correlation between 
the predictors (174). Also, the pseudo inverse cannot be computed if the number of predictors is 
greater than the number of observations (175). In support vector regression, we do not attempt to 
minimize the prediction errors; rather, we allow for a certain amount of errors, and set an upper bound 
on permissible prediction errors (176). In this formulation, the stability of estimation is not affected by 
correlations between predictors, and by the number of predictors relative to number of observations. 
The superiority of support vector regression over linear regression models has been demonstrated by 
Drucker et al. (177). We expect that the final default model will include a combination of several factors 
that together contribute to outcome prediction. As not every factor will contribute equally to the 
proportional reduction in error, beta weights (converted to Z-scores) will be calculated so that clinicians 
can better understand the relationship between predictors. Potential concerns: Relying on a relatively 
large sample of patients, it is possible that many biographical and cognitive/linguistic factors may 
correlate with treatment success. This is potentially problematic for clinicians who may not have time to 
administer the test battery necessary to assess each factor. Therefore, we will calculate several 
separate models that include sub-sets of predictors. Then, it will be possible for clinicians to estimate 
success based on a more restricted version of the default model.  
Aim 2 – To compare the default model to the D+WLG and D+DS models, we will also rely on SVR. 
Here, all factors that comprise each model (e.g., D+DS model includes the default model factors in 
addition to proportional damage to the dorsal and ventral streams) are entered into an SVR analysis 
and the R2 for the correlation between the actual scores (e.g., change in correct naming or propositional 
density) and the predicted scores is calculated. Then, a statistical comparison is made between the R2 
yielded by the different prediction models. The model with statistically significantly highest R2 compared 
to other models will be determined as the best prediction model. Separate analyses will be conducted 
for each treatment focus (semantic vs. phonological) and overall treatment outcome. Potential 
concerns: Although we have been highly successful in attracting patients to our treatment studies, we 
have never carried out a project that requires the sample size proposed here. If actual patient 
recruitment lags far behind planned recruitment at the University of South Carolina and the Medical 
University of South Carolina, we will initiate enrollment of chronic patients at Johns Hopkins University. 
In such a case, .5 SLP appointment will be moved from South Carolina to Johns Hopkins University. It 
is also a concern that patient recruitment for the current project (C-STAR) and the CATES trial will 
overlap by approximately 4-6 months. During this time, we will randomize patients to be enrolled in 
either C-STAR or the CATES trial. We emphasize that we have always had a waiting list for patient 
enrollment in the CATES trial and at the time when the current proposal was submitted, 52/74 patients 
had been enrolled in the CATES trial (nine more patients are scheduled to complete enrolment in 
summer 2015).  
Aim 3 – Separate SVR analyses will be conducted to test whether change in cueing in a single naming 
session or performance on the hit-and-avoid task predicts aphasia treatment outcome. The learning 
curve (slope of the regression line) will be calculated for each patient. The same SVR analyses planned 
for Aim 1 will be run again but now with the learning factors also included to assess whether the default 
model can be improved by including assessments of learning potential. Potential concerns: Without 
collecting further data, it is impossible to estimate the necessary length of the learning paradigms. This 

 
64
is a potential concern as administering an hour-long learning task to patients in clinical care is 
probably not feasible. Thus, we will calculate learning curves for progressively longer increments (e.g. 
for the first 10, 20, 30, or 40 minutes of the task) to appreciate the necessary length of each learning 
task. For example, it could be the case that improvement in performance over the first 20 minutes of the 
language-learning task is sufficient to predict treatment outcome.  
3.11 Making the Default Model Available On-line. Once the default model has been constructed, we 
will make the algorithm available to clinicians who can then assess their own patients and plug in the 
results to estimate treatment response relying on either semantically or phonologically focused 
treatment. For this purpose, we will design a website that includes detailed instructions regarding what 
factors need to be assessed and the strengths and limitations of this approach. Similarly, we will 
provide guidance regarding assessment fidelity, threats to assessment reliability and validity, as well as 
disclaimers about potential abuse of the model (e.g., denying patients treatment based on model 
prediction of poor outcome).  
 
 

 
65
Appendix E.  Clinical Core Research Plan 
1. Significance.  
1.1 Background. Speech-language therapy to treat aphasia is supported by evidence - individuals with 
aphasia who participate in speech-language treatment demonstrate greater improvements than those 
who do not.1-4 Nonetheless, individual response to treatment varies greatly and little is known about 
how factors related to assessment, treatment, and patient characteristics interact to engender a positive 
treatment outcome. Different assessment foci can contribute to the mixed results.5-8 For example, if 
discrete language abilities are treated and assessed, improvement in those language abilities (relative 
to a control condition) may be considered to support treatment efficacy. However, an alternative view is 
that treatment is only efficacious if there is a demonstration of improvement in communication activities 
or life participation that is clearly associated with the treatment, and not the control, condition. Different 
assessment administration procedures, particularly those involving the patient response and resultant 
score (e.g., item time limits, multidimensional scoring, self-corrected responses counted as accurate, 
etc.), can also lead to a patient being labeled as a “responder” with one set of procedures and as a 
“nonresponder” with another. In addition, treatment factors (e.g., treatment elements, dose, etc.) are oft 
studied, but despite emphasis, results are not straightforward. While the “more treatment is better” view 
is generally supported,1,3,9-11 which treatment elements and targets should be practiced more,1,3,12 and 
which outcome domains (e.g., body functions, activity limitations, participation limitations) benefit from 
intensive treatment schedules6, is unclear. Finally, numerous patient factors, including stroke-related 
(lesion site and size, type of stroke, etc.), demographic, and neurophysiological variables have been 
the focus of many investigations, often with conflicting results.3,13-17  
This P50 grant application systematically investigates many of these factors. Some elements (e.g., 
patient variability) may also be thoroughly discussed in “Limitations” and “Future Directions” sections of 
numerous journal articles, and solutions to preserve the validity of the study may be readily located in 
research design references. However, in the speech-language or stroke rehabilitation literature, 
relatively little attention has been paid to other threats to a study’s validity that relate to correct 
implementation of treatment, and also assessment, procedures. Statistical conclusion validity, referring 
to inferences about the presence of a relationship between two variables and the strength of that 
relationship, can be threatened by measurement error, unreliable treatment implementation, and other 
sources of variance introduced into the experimental setting, as well as low statistical power (which can 
also be a result of the random variance introduced by the forenamed threats).18 These threats can 
increase the chance of Type I or Type II error, or the additional error (“Type III”) of concluding 
significance or nonsignificance when in fact the tests or the treatments were not correctly 
implemented.19-21 Internal validity, referring to whether or not causation can be inferred from the 
statistical conclusions, can be threatened by those same threats to statistical conclusion validity, patient 
selection and attrition, and various assessment factors.18 (Note: All threats to statistical conclusion and 
internal validity are not listed here, only those most critical to implementation of clinical procedures, 
which will fall under the aegis of the Clinical Core.) In other words, an additional contributor to the 
historically mixed results in aphasia treatment research emphasized by Project 1, Project 2, and here 
in the Clinical Core could also be those variables related to fidelity, or adherence to the study 
procedures. In the absence of fidelity monitoring, investigators are unable to confidently determine 
whether or not results (significant or nonsignificant) were caused by the targeted independent variable 
or were due to other random factors introduced because the clinician “drifted” from the protocol, or 
“contaminated” the protocol by adding or omitting elements.19  
1.2 Treatment fidelity. Treatment fidelity, or how well the essential treatment elements were delivered 
as intended and were distinguishable from comparison conditions,19,20,22 has so far been the focus of 
most implementation discussions. In general psychology research, several meta-analyses demonstrate 
that studies taking steps to ensure treatment fidelity have larger effect sizes (two to three times higher) 
for treatment outcomes compared to those studies that do not.23 School psychology researchers have 
revealed that as the degree of treatment fidelity increases, the rates of positive outcomes also 

 
66
increase.24 In addition, treatment fidelity (or “program integrity”) affects a number of variables in 
abuse prevention research.25,26 Thus, implementation can be a determinant of success. Hinckley and 
Douglas20 recently examined the reporting of treatment fidelity in aphasia treatment studies (reviewing 
149 aphasia treatment articles published between 2002-2011), revealing that while almost half of the 
studies reported treatment methods that would enable replication, only 21/149 (14%) of the studies 
specifically described methods for establishing or monitoring treatment fidelity. Twenty of those studies 
utilized only a single treatment fidelity method - monitoring of adherence to treatment protocol, 
supervising treatment sessions, utilizing a training manual, or pre-implementation role-playing. Only 
one study utilized more than one treatment fidelity method, combining the use of a training manual with 
monitoring of adherence to the treatment protocol.  
The NIH has recently established a treatment fidelity workgroup within the Behavior Change 
Consortium (BCC) in recognition of poor monitoring of treatment fidelity in behavioral research. This 
workgroup is tasked with defining treatment fidelity and offering guidelines for researchers. According to 
the BCC workgroup, establishing treatment fidelity should address the following five components19: (1) 
study design – the study should be designed appropriately so that hypotheses can be tested and 
inferences are valid; (2) training – training procedures should be standardized across clinicians; (3) 
treatment delivery – treatment should be monitored to ensure it is delivered as intended; (4) treatment 
receipt – the patient should understand the treatment procedures and demonstrate utilization of them 
within experimental sessions; and (5) treatment enactment – the patient should utilize behaviors 
targeted in treatment in real-world settings. The intricacies and the defense of study design for Projects 
1 through 4 have been laid out in their corresponding research plans. The training, treatment delivery, 
and treatment receipt components of treatment fidelity will be addressed in the Approach section of this 
Clinical Core proposal. Consistent with Gearing et al.,22 the Clinical Core will not address treatment 
enactment since it is more about generalization of behavior and less about adherence to clinical 
procedures.  
1.3 Assessment fidelity. Compared to treatment fidelity, similar guidelines to ensure adherence to an 
assessment protocol have not been established. The general impression is that selection of tests with 
good reliability and validity, and perhaps performing rater reliability checks within the study, is enough 
to ensure assessment fidelity. However, just as there can be clinician drift from treatment procedures 
(e.g., cueing hierarchy not delivered as designed) and contamination of treatment procedures (e.g., 
clinician is incorporating cues from Treatment B into Treatment A), assessor and/or rater drift and 
contamination are just as likely to occur, especially when administering lengthy assessment batteries 
that include tests with different administration procedures (e.g., item time limits, assessor cueing) and 
complex scoring systems (e.g., discourse, Philadelphia Naming Test), and are given repeatedly over a 
long period of time. Borrowing from treatment fidelity guidelines, assessment fidelity components of 
training and assessment delivery will be addressed in the Approach section of this Clinical Core 
proposal.  
1.4 Role of the Clinical Core. Efforts to optimize assessment and treatment fidelity are critical to the 
projects proposed by Fridriksson, Hillis, Rorden, and Hickok. As displayed in Table 1, 12 of 13 project 
aims require recruitment and retention of patients and collection of high quality data that can be entered 
into the WebDCUTM (Clinical Core Aim 1). Those same 12 project aims rely on data collected by an 
assessor using prescribed administration procedures and scored by a rater adhering to prescribed 
scoring procedures (Clinical Core Aim 2). Seven of 12 project aims rely on treatment (Clinical Core Aim 
3).  

 
67
 
The assumption of the investigators is that assessors, raters, and clinicians adhere to well-defined 
study protocols. The Clinical Core will exist to make that a reality. By doing so, the Clinical Core will 
guard against threats to statistical conclusion validity and internal validity, increasing the power to 
detect effects and increasing investigator and consumer confidence in the results. By reducing the 
chances of making Type I, II, or III errors, we would decrease the probability that this ambitious 
endeavor (C-STAR) would result in research waste, the costs of which can only begin to be fathomed if 
one recognizes that the impact of those errors would not only be felt in this study, but throughout the 
entire research community.19,27-29 This responsibility is not taken lightly and is why the Clinical Core is 
essential to the research activities of C-STAR.  
 
2. Innovation.  
The innovative projects proposed in this application are dependent upon clinical activities. For the 
correct inferences to be made, adherence to assessment and treatment protocols must be continually 
monitored. It is important that the Clinical Core also apply the most up-to-date and innovative 
procedures for ensuring collection of high quality data. The following methods will be implemented, all 
of which appear to be novel among aphasia treatment studies.  
2.1 Centralized training of all personnel in contact with patients. The Clinical Core will be 
responsible for training all personnel who will have contact with patients and/or friends and family 
members to ensure that all exchanges are ethical, respectful, and employ successful communication 
strategies. For Aim 1, this will include training for communication during initial recruitment and patient 
identification, for the informed consent process, and for participant retention. For Aim 2, this will include 
training of assessment administration procedures, and for Aim 3, treatment procedures. This training 
will help to reduce variance introduced by clinicians communicating or carrying out procedures with 
different styles than others. As far as we can tell, training of personnel in this manner has not been 
reported so far in the aphasia treatment literature.  
2.2 Monitoring participant recruitment and retention. To increase the efficiency of recruitment and 
to ensure resources are not wasted due to patient withdrawal from the project, the Clinical Core will 
monitor the rate of recruitment with a recently developed “recruitment index”. The Clinical Core has an 
adaptive plan for recruitment in place so that advertising and recruitment efforts will be modified if the 
recruitment index shows Projects 1 and 2 are not on target for meeting proposed recruitment numbers. 
The recruitment index has not been used in the speech-language literature, and participant retention 
plans have not been reported upon in previous research in this area.  
2.3 Optimizing treatment fidelity. No aphasia treatment studies to date have reported more than two 
tools or methods used to monitor or attempt to establish treatment fidelity. The aphasiology community 
has been slow to respond to the treatment fidelity guidelines set forth by the BCC workgroup. The 
Clinical Core will optimize treatment fidelity by monitoring multiple components, specifically clinician 
training, treatment delivery, and treatment receipt. This is an ongoing process, not only occurring at the 
onset of the project, but rather continually performed over the entire duration of the project to ensure 

 
68
that treatment implementation on the first day of the first year of the project is the same as on the 
last day of the last year of the project.  
2.4 Optimizing assessment fidelity. In the aphasia literature, relatively little attention has been paid to 
the training of assessment personnel, other than ensuring a minimum training standard (e.g., clinician 
with at least 3 years of experience, etc.) or presenting intra- and inter-rater reliability information. Given 
the importance of assessment to nearly all of the aims proposed in all projects, it is important that we 
take additional steps to ensure that data will be collected with appropriate administration procedures 
and will also be scored appropriately. This will entail training of both assessors, who will also score 
baseline tests, and blinded raters, who will score repeated measures. Borrowing from treatment fidelity 
guidelines, the Clinical Core will coordinate assessor and rater training, assessment delivery, and 
reliability of raters.  
3. Approach  
3.1 Capability of the Clinical Core team. Dr. Argye Hillis is a Professor of Neurology, Physical 
Medicine & Rehabilitation, and Cognitive Science, as well as Director of the Cerebrovascular Division of 
the Department of Neurology at Johns Hopkins Medical Institutions (JHMI). She has 10 years of 
experience as a speech- language pathologist and Director of Neurological Rehabilitation, prior to 
becoming a stroke neurologist. She directs a large, multidisciplinary Stroke Prevention and Recovery 
Center (SPARC), which has been certified by the American Heart Association as a Comprehensive 
Stroke Center. Hillis is experienced in organizing national and international multidisciplinary groups; for 
example, she was recently President of the World Federation of Neurology Research Group on 
Aphasia and Cognitive Disorders and is on the Board of Directors of the American Neurological 
Association. As PI of the Clinical Core, she will be responsible for overseeing all aspects of the core. 
She will work closely with the Clinical Core Coordinator (located at USC – to be hired) to carry out the 
plans described herein, and that the goals of the core are being met. To ensure that the ideal staff 
members are hired and trained appropriately, Dr. Jessica Richardson, Assistant Professor of Speech 
and Hearing Sciences, University of New Mexico, will serve as consultant and provide initial training to 
the Clinical Core Coordinator, speech-language pathologist (SLP) Clinical Core Project 1 Leader, and 
raters. Dr. Richardson is a certified SLP, with 13 years of experience providing (and supervising the 
provision of) diagnostic and therapeutic services to aphasic adults. Richardson is uniquely suited for 
this role given her previous contributions to some of the studies (published and pilot) that have 
motivated this P50 application, with roles ranging from treatment designer to assessor to clinician to 
trainer, including both behavioral and brain stimulation methods. Dr. Leonardo Bonilha is a neurologist 
and neurophysiologist at the Medical University of South Carolina (MUSC), where he is actively 
involved in the care of patients with stroke within the large MUSC stroke center. Besides his clinical 
expertise, Dr. Bonilha is a researcher with experience in behavioral and neuroimaging assessments of 
aphasia, being the leading neurologist at MUSC in the NIDCD supported clinical trial “Transcranial 
Direct Current Stimulation (tDCS) to Treat Aphasia: Phase II Trial” (CATES trial; DC011739, PI: 
Fridriksson) and the PI on the NIDCD supported project “Brain Connectivity Supporting Language 
Recovery in Aphasia” (NIH R01DC014021).  
Aim 1: To supervise data collection and data management at each clinical site.  
3.2 Rationale. Perhaps the most important aspect of data collection is ensuring that there are 
participants from whom to collect data. Our discussion of data collection and management thus begins 
with participant recruitment and is followed by plans for participant retention. The Clinical Core’s 
recruitment plans focus on pre-enrollment activities while retention plans include post-enrollment 
activities designed to promote study completion.30 These plans will guard against selection bias and 
attrition threats to internal validity.18 Next, plans for ensuring collection of high quality data are 
presented, as is information about data storage and security. Other processes involved in promoting 
data quality that are dependent on assessment or treatment implementation will be discussed in fidelity 
sections.  

 
69
3.3 Baseline training. The Clinical Core will ensure that all study personnel having any contact with 
participants and/or the friends and family members of the participants will have a basic understanding 
of the communication needs and obstacles for this population, and also some understanding of their 
experience. While most study personnel will have had a background with adult neurogenic 
communication disorders, standardizing this baseline training for all personnel, from those who might 
only be escorting them to the elevator to those who will be spending hours with them in treatment 
sessions, will ensure that no erroneous assumptions about qualifications are made. This baseline 
training (see Appendix 1) comprises many components that are already implemented by Richardson’s 
lab, with positive feedback and results. The Clinical Core will facilitate the training and will maintain 
compliance logs.  
First, all study personnel will complete human subjects training (CITI) to understand ethical treatment of 
human research participants, which is essential training even in the earliest stages of a study (e.g., to 
avoid coercion and/or bias during advertising and recruitment efforts). Second, all personnel will 
independently read two articles by the Hilari research group discussing the impact of aphasia: 1) 
“Aphasia blog talk: How does stroke and aphasia affect a person’s social relationships?” (Fotiadou, 
Northcott, Chatzidaki, & Hilari, 2014); and 2) “Aphasia blog talk: How does stroke and aphasia affect 
the carer and their relationship with the person with aphasia.” (Winkler, Bedford, Northcott, & Hilari, 
2014). Third, all personnel will independently view four videos available via AphasiaBank 
(http://talkbank.org/AphasiaBank/; participants consented to be videotaped by AphasiaBank) during 
which persons with aphasia discuss their stroke story. Two videotaped persons will have nonfluent 
aphasia (1 high, 1 low severity) and two will have fluent aphasia (1 high, 1 low severity). Finally, the 
Clinical Core will lead small group sessions that will include a brief lecture on “How to communicate 
with individuals with aphasia”, a lecture used by Fridriksson when training speech-language pathology 
students to be aphasia group leaders. This lecture will be followed by an experiential learning session 
utilizing the program “Experiencing Aphasia: An Inservice Model Demonstrating Aspects of Aphasia.”31 
The stated goals of the program are: (1) To give participants an opportunity to experience what it is like 
to be communicatively impaired; (2) To encourage participants to discuss their emotional responses to 
being treated as an impaired individual; and (3) To instruct participants about the different modalities 
that may be impaired as a result of stroke or head injury. This session will provide opportunities for 
personnel to participate in simulations of communicating with aphasia through receptive language, 
expressive language, reading, and writing stations. Richardson has used this for training her lab 
members and social workers (with Adult Protective Services).  
3.4 Participant recruitment. 
Advertising and identification of eligible participants – For Project 1, the Clinical Core team will focus 
advertising efforts on approaches that have yielded participants for our previous studies and are proven 
to be among the most effective strategies for recruiting elderly patients,32-34 which forms the bulk of the 
target participant base (Table 2). We will depend on local and state news broadcasts and newspaper 
advertisements. If the yield is limited, radio advertisements and group presentations to stroke and 
aphasia support groups will be added into the advertising plan.32,33 At the same time, the usual lab 
recruitment activities will continue, and include networking with colleagues, advertising studies through 
statewide directories (http://scresearch.org/) and a lab website 
(http://www.mccauslandcenter.sc.edu/aphasia/), and referrals from well-established area contacts 
(community, in-state, out-of-state). For Project 2, these same advertising efforts are not required, as 
this project recruits participants with acute stroke directly from the inpatient stroke wards at JHU and 
Johns Hopkins Bayview Medical Center, and also the follow-up clinic, the Stroke Prevention and 
Recovery Center (SPARC) at JHMI. The stroke neurologist who is attending on the wards or in SPARC 
is approached by a study team member on a daily basis, and identifies potential participants who have 
agreed to be approached by the study team member about the research.  
 
 

 
70
 
As Projects 1 and 2 address relevant health issues, we expect interest and willingness to participate 
from potential participants with aphasia once they are made aware of the projects.34 Following 
successful advertising efforts, identification of eligible potential participants by screening for inclusion 
and exclusion criteria is completed by interview (phone or face-to-face) and/or case history review for 
Project 1, and by record review and interview for Project 2. Given the complexity of recruitment for 
these types of studies and in this population, it is essential that potential participants have a positive 
and informative interaction with the initial contact person.34 The Clinical Core will work with project 
investigators to coordinate the hiring of study personnel, screening for excellent interpersonal skills and 
a background communicating with persons with communication impairment (speech-language 
pathologists, clinical coordinators with experience with this clinical population, speech-language 
pathology graduate students, etc.). The Clinical Core will ensure through training that anyone 
performing recruitment duties is well-informed about the study details (i.e., expectations, timelines, 
etc.), because individuals are likely to be more responsive if they are confident in the knowledge of the 
person they are speaking with.34 Training will include independent reading of the full study protocol, the 
informed consent document, and any other related documents, followed by a review of the documents 
with a member of the Clinical Core team (Appendix 1). In addition, we will provide scripts to assist with 
communicating about the study via e-mail, telephone, or in-person. As discussed in Project 1 
(Research Plan, 4.4) and Project 2 (Research Plan 4.4.9), we do not anticipate difficulty recruiting 
participants, but these efforts will only serve to enhance the already successful recruitment strategies 
employed by both project leaders (Fridriksson, Hillis) and the other Clinical Core team members (to be 
hired Clinical Core Coordinator, Bonilha) in their laboratories.  
Informed Consent – For both projects, study explanation and informed consent can be a challenging 
process. The potential participants not only have limitations in producing and/or understanding 
language, but are also being approached after what is often the most devastating event so far in their 
lives. For Project 2 in particular, the reality of this event has had little time to be fully realized. For these 
reasons, the person obtaining consent must be a skilled and supportive communicator who is aware of 
the realities faced by this clinical population and respectful of their decisions and requests for 
information, more time, etc. The person obtaining consent should also be skilled enough to recognize 
when the aphasic participant has a comprehension impairment (e.g., Wernicke’s aphasia or Global 
Aphasia) so that they seek informed consent from the participant’s spouse, adult child, legal 
representative, or identified decision maker, with accompanying assent from the aphasic individual. The 
person obtaining consent will be a Clinical Core leader (Hillis, Bonilha, to be hired Clinical Core 
Coordinator at USC) or another speech-language pathologist with informed consent training.35,36 The 
required human subjects training will have already been completed as part of baseline training. 
Additionally, the Clinical Core will facilitate the following informed consent training procedures 
(Appendix 1) for both Project 1 and Project 2: (1) independent reading of informed consent articles 
(“Informed consent and aphasia: Evidence of pitfalls in the process” 37 and “Discrepancy between 
participants’ understanding and desire to know in informed consent: Are they informed about what they 
really want to know?” 38 with an additional reading for Project 2 members (“Informed consent: The rate-
limiting step in acute stroke trials” 39); (2) observation of a minimum of three expert (Hillis, Richardson, 
or Bonilha) consent sessions; (3) supervised consent sessions with expert feedback; and (4) yearly 
review of consent information plus expert supervision of 1-2 sessions. This training will ensure that the 
informed consent process is informative, respectful, and ethical, and will positively influence 
retention40,41.  
 

 
71
Research suggests that comprehension of written materials is significantly improved in people with 
aphasia when the following modifications are made: language simplification, increased font size, 
increased spacing, increased white space, and use of pictures.42,43 The Clinical Core will develop 
aphasia-friendly consent documents using these modifications, additionally incorporating feedback from 
persons with aphasia. Figure 1 highlights sections of modified documents created (with aid of 
consultants with aphasia) and used by Richardson. Though not to scale (font size is actually 14-point), 
aphasia-friendly features are clear: increased spacing between words, increased white space overall, 
and use of changes in typography, organizational tools, and pictures.  
Figure 1. Sample elements from aphasia-friendly ICFs.  
 
 
3.5 Participant retention. While efforts to attract participants to the study and then initiate their 
participation is essential, and challenging enough, efforts to ensure participation should not end there. 
It is vital to the majority of aims across all projects that participants complete all arms of study and that 
they are available for follow up assessments (see Table 1). Participant retention plans are therefore 
crucial.44 Though we refer to participant retention activities here as those engaged after enrollment to 
ensure project completion (as in Blanton et al.30), pre-enrollment activities or factors, such as study 
design and the informed consent process, can also influence participant retention.40,41 In regard to study 
design, studies that provide some benefit and make efforts to reduce participant burden (e.g., travel 
reimbursement), such as Project 1 and Project 2, are likely to have higher retention rates.40 Project 1 
and Project 2 employ therapeutic approaches that have been shown to offer benefit, though, as 
emphasized in the informed consent process, benefit cannot be guaranteed. Even in the case of 
Project 2, which has a sham group, participants are likely to benefit from the computerized treatment 
alone.45 Regarding informed consent, if full disclosure and adequate study explanation has occurred 
during informed consent, then the participant should have realistic expectations of the study (schedule, 
burdens, benefits), and is less likely to drop-out because they were surprised or caught off-guard by 

 
72
expectations.40 The participant will be given a copy of the consent form and will be encouraged to 
refer to it and ask questions throughout the study, as informed consent should be an ongoing 
process.37  
After a participant is enrolled, several additional steps coordinated by the Clinical Core will assist with 
successful participation and completion, and concern the following: study personnel, study identity, 
contact and scheduling methods, and other visit characteristics.40 First, as detailed in 3.3 and Appendix 
1, all personnel will have baseline training in communication with persons with aphasia and their friends 
and family members and will be screened for characteristics important for working with this population. 
Each participant will be assigned one primary contact person with whom they will communicate,40 
reducing the confusion that can accompany communicating with multiple contacts through multiple 
outlets (e-mail, phone) and reducing the potential for mixed messages and lost information. Second, for 
Project 1 and Project 2, a study logo, study name, and study-specific typography (font color, font style, 
etc.) (i.e., “study identity”40) will be used for all written and digital communication to promote easier 
discrimination of important study-related communications from others (e.g., junk mail, telemarketing 
calls, etc.) and a sense of study team membership. Third, once the aphasic individual has consented to 
participate, they will be mailed a packet that will include the following documentation marked with the 
study identity: aphasia-friendly study explanation with a personal message from the Clinical Core team 
and the project PI, aphasia-friendly calendar of scheduled sessions (time, place, etc.), and a contact 
sheet with pictures and contact information of relevant study personnel.40 To promote successful follow-
up after breaks from regular contact, the Clinical Core will also coordinate reminder phone calls and/or 
emails to remind of upcoming appointments. Fourth, in regard to both personnel and visit 
characteristics, the Clinical Core will train all study personnel to be responsive to the participant (and 
friends and family members of the participant), quickly returning phone calls or emails and never 
hesitating to answer any and all questions they may have.30,40 Further, during the session, the 
participant will have the full attention of the study personnel and sessions will not be rushed or 
unorganized. Finally, already in place for the lab of Project 1, and to be initiated for Project 2, a 
newsletter will be sent frequently to everyone in database (see archived Aphasia Lab newsletters at 
http://www.mccauslandcenter.sc.edu/aphasia/links-resources/). At the end of the study, participants will 
be sent a thank you card as well as a report of the assessment and treatment results.  
The Clinical Core will monitor the success of participant recruitment and retention activities throughout 
the entire study so that changes to recruitment and retention efforts are modified accordingly. We will 
utilize an index introduced by Rojavin46 and endorsed by clinical trial investigators,30 called the 
recruitment index (RI), which provides an estimate of the number of days required to recruit one 
analyzable (completed the study) participant. It is calculated by:  
RI=[(LPFV–FPFV)xS] ÷ P  
where LPFV – FPFV is the number of days between “last patient first visit” and “first patient first visit”, S 
is the number of recruitment/study sites, and P is the number of participants who completed the study. 
The RI for each project will be calculated every 9 months to determine whether or not the target 
enrollment would be reached with the current recruitment rate, and recruitment plans will be adjusted if 
needed. The Clinical Core will also collect information related to participant attrition, to monitor whether 
or not it is systematic (e.g., drop- outs more likely to occur during Phase X than Phase Y) and therefore 
a threat to internal validity,18 if it should occur.  
3.6 Data capture and management. Data capture and management plans are recommended to 
ensure high data quality for eventual analysis.44 It is critical to have high quality audio and video for 
Projects 1, 2, 3, and 4, as all projects rely on one or more of the following that will be performed offline, 
and most often by blinded raters: detailed analysis of naming performance and errors, detailed 
transcriptions of discourse, and judgments of motor speech behaviors that rely on motor speech and 
discourse tasks. It is also important that audiovisual recordings of assessment and treatment sessions 
are recorded for fidelity monitoring.  

 
73
Assessor – The Clinical Core will ensure that the assessor-rater will have multiple checks in place to 
ensure recording of assessment sessions. (We refer to these individuals as assessor-raters because 
they are responsible for administering the assessment and also scoring or rating those measurements 
that are not repeated measures. Those scoring repeated measures are referred to as blinded raters, or 
raters. For the remainder of the document, we will refer to them as assessors and raters.) There will be 
two recording devices in use for each assessment session - for Project 1, a laptop camera and a 
standalone digital camera, and for Project 2, a laptop camera and an audio recording device. Quick 
A/V checks will be performed immediately before the session to ensure devices are working properly. 
Both recording devices will then be used to record assessment, and the assessor will be reminded to 
check the indicator lights to make sure capture is in progress. Immediately after the session, the 
assessor will log information about the session into an experiment manual, checking procedures off of a 
list developed by the Clinical Core and recording any observations regarding anything of note during 
the session (e.g., participant very tired; alarm went off during PNT administration; etc.). Then, the 
assessor will check capture quality and file integrity and back up all recordings to data storage 
described in Project 1 and Project 2.47  
Following completion of assessment, the assessor will have a maximum of one week to complete 
scoring, which will include a combination of their online and offline scoring. For both Projects 1 and 2, 
the assessor will score the Apraxia of Speech Rating Scale,48 Pyramids and Palm Trees Test,49 and 
Western Aphasia Battery- Revised.50 For Project 1, the assessor will also score the Kissing and 
Dancing Test,51 Northwestern Assessment of Verbs and Sentences,52 Philadelphia Repetition Test 
(PRT),53 subtests of Psycholinguistic Assessments of Language Processing in Aphasia (PALPA),54 
matrix subtest of Wechsler Adult Intelligence Scale,55 short-term memory tests,56 and visual perception 
tests. For Project 2, the assessor will also score the Boston Naming Test (BNT),47 Patient Health 
Questionnaire-9 (PHQ-9),57 Raven's Coloured Progressive Matrices (RCPM),58 NIH Stroke Scale59 (with 
analysis of the Content Units, syllables/Content Unit in the “Cookie Theft” picture,60-62 and Modified 
Rankin Scale.63 Assessors will then immediately input the data into WebDCUTM. As described in the 
Research Plans for Project 1 and Project 2, the following data are automatically stored on the 
WebDCUTM: for Project 1 and 2, audiovisual files for pre-treatment and all follow- up assessments of 
naming untrained pictures (Philadelphia Naming Test [PNT]64,65 Roach et al., 1996; Walker  
 
& Schwartz, 2012) and discourse measures; for Project 1, output for Aphasia Communication Outcome 
Measure (ACOM; Doyle et al., 2013); and for Project 2, output for computerized treatment measures. 
Logging of these behavioral data, as well as scoring and analyses will be conducted by the Clinical 
Core staff through the WebDCUTM (the videocam in the computer sends videos and responses directly 
to the WebDCU)TM. These steps will be detailed in the assessment procedure manual that will be 
created by the Clinical Core and reviewed thoroughly in training.  
Rater – After a participant has completed all phases of the study, raters will obtain color-coded media 
files (with participant and session codes that do not reveal the treatment condition or order) for outcome 
measures (e.g. PNT, discourse).The order in which the blinded rater will score these assessments is 
determined by a random sequence generator, and will differ for each participant and for each repeated 
measure. After scoring, raters will immediately input the scored data into WebDCUTM as above.  
Clinician – For Project 2, several additional data points need to be entered by the clinician following 
select sessions. These include participant code, heart rate, blood pressure, Wong-Baker FACES Pain 
Rating Scale (Wong, 1988), any symptoms noted by the participant, and evaluations of blinding. Date, 
time, and tDCS blinding is automatically recorded by the WebDCUTM . In addition, the Clinical Core will 
coordinate the videotaping of randomly selected treatment sessions (1-2 per week) to be used for 
monitoring of treatment fidelity, discussed in 3.15 and 3.16.  

 
74
3.7 Data security and storage. Back-up audio and audiovisual files will be stored on equipment 
supplied by Project 1 and Project 2. All behavioral data, both scored, and unscored, will be stored by 
the DCU, described in the Administrative Core.  
Aim 2: To optimize and monitor assessment fidelity.  
3.8 Rationale Poor adherence to assessment procedures threatens both statistical conclusion and 
internal validity. Specifically, the reliability of measure and the stability of the measurement instrument 
over time are important for arriving at the correct conclusions about relationships between variables 
and for ensuring that a false treatment effect is detected when in fact it could be due to change in the 
instrumentation.18 While Projects 1 and 2 rely upon reliable instruments and have no plans to change 
measurements mid-study, it must be remembered that the clinician is a part of the instrumentation. For 
most tests, the clinician, operating from an assessment manual, sets the pace, monitors the time limits, 
gives instructions and in some cases cues or feedback, and must make judgments when scoring 
performance. The instruments are therefore only as reliable and resistant to change over time as the 
person administering them.  
If assessment instruments were more aligned in their procedures, perhaps this would be less of a 
concern. However, as is illustrated in Table 3, this is not the case, unsurprising as they originate from 
different authors, publishers, theoretical underpinnings, etc. Though not an exhaustive review of the 
variability of assessment administration and scoring procedures included in Project 1 and Project 2, 
we highlight differences in instructions to the assessor regarding how the clinician is allowed to respond 
following item presentation, timing, and scoring (focusing on the language tests). As is evident, there 
are multiple opportunities for drift from assessment procedures and contamination of one assessment 
instrument by another. For some measures, feedback is not allowed (e.g., KDT) while for others it is 
prescribed (e.g., PNT). Time limits, if provided, differ between measures and often even between 
subtests of the same measure (e.g., NAVS). Regarding scoring, some measures score the final 
attempts (including self-corrections) (e.g., NAVS), others score only the first attempt (e.g., PNT), and 
some measures even give credit for no responses (e.g., PPTT). So far, this has only highlighted 
variability; when the complexity of some of the scoring systems is also considered, specifically for 
discourse and PNT, the need for a plan for monitoring assessment fidelity is obvious. Combining 
information regarding threats to validity,18,22 we have identified the following threats that will fall under 
the purview of the Clinical Core: variability in clinician qualifications, drift, contamination, and clinician 
turnover. We will apply well- established treatment fidelity guidelines19,22,27,66,67 to our assessment 
process and outline here the assessment fidelity plans that focus on assessor and rater training, 
assessment delivery, and scoring reliability.  
Table 3. Sample instructions to clinician regarding assessment administration and scoring.  
WAB-R, 
Naming  
“If the patient does not respond or responds incorrectly, ask him or her to hold the object (tactile cue) 
and to tell you what it is. If the patient still does not respond or responds incorrectly, present the first 
phoneme of the word (phonemic cue), or, if it is a compound word, the first half of the word (semantic 
cue).” (cueing)  
KDT  
(Following two practice items with feedback), “No more feedback is provided to the participant. If the 
participant does not know what a picture is, do not tell them. If they are unsure of the answer, 
participants should be encouraged to guess.” (feedback)  
PNT  
 
“After the subject has finished responding to an item, give him/her feedback: e.g., “good, that’s a fish”, 
or “actually, they’re looking for garage here”, or some variation thereof.” (feedback)  
NAVS, 
VCT/SCT  “Items/Sentences may be repeated once.” (repetition)  
WAB-R, 
AC  
“Repeat the directions and the question if the patient gives an ambiguous or confabulatory response.” 
(repetition)  

 
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Timing  
NAVS, 
VCT  
Allow 5 seconds to respond for both first and (after prompt) second attempts.  
NAVS, 
SPPT  
Allow 15 seconds for both first and (after prompt) second attempts.  
WAB-R, 
Naming  
Allow 20 seconds maximum for each item. [including cues]  
PNT  
Allow a 30 second deadline to name each picture  
Scoring and Attempts  
PALPA, 
Rhyme  
“In a few instances, regional pronunciation differences may result in disagreement about whether 
stimulus and target rhyme. Check by testing appropriate control subjects and do not count any of 
these items in your analyses.”  
PNT  
“On each trial, score the subject’s first “Complete Attempt”, defined as the first minimally CV 
(consonant-vowel) or VC response (schwa is not counted as a vowel) that meets one of the following 
criteria: 1) The attempt is not self-interrupted (cut-off) and has clear downward or upward/questioning 
intonation; may or may not be separated from a subsequent attempt by a noticeable pause; 2) The 
attempt is not self-interrupted (cut-off), is spoken with level intonation,....”  
PPTT  
“When a subject completely refuses to respond to a triad, it should be given a chance score – 0.5.”  
NAVS, 
VNT  
“If the subject self-corrects within 10 seconds, score the final response produced.”  
NAVS, 
ASPT  
“Self-corrections/reformulations should be put in parentheses. Score only the final attempt at a target 
utterance.”  
WAB-R, 
AC  
“Score 3 points for each correct response and 0 points for each incorrect (ambiguous or 
confabulatory) response. If the patient self-corrects, score the last response he or she gives.”  
WAB-R, 
Naming  
“Score 3 points if the object is named correctly or with a minor articulatory error (e.g., dysarthric 
slurring) and no cue is needed. Score 2 points if the object name is recognizable, but with a phonemic 
paraphasia (e.g., “fife” for “knife”) and no cue is needed. If a tactile, phonemic, or semantic cue is 
needed... score as 1 point. Score an incorrect or no response after cueing as 0 points.”  
3.9 Assessor Training One suggestion for improving the quality of assessment measures, and thereby 
improving study validity and increasing power, is to conduct “better training of raters” (reference 18; p. 
49). The Clinical Core will standardize assessor training for Projects 1 and 2, beginning with the 
development of an assessment manual containing the following sections: project explanation, 
relationship of assessment measures to project goals, administration procedures for each individual 
test, and integrated information across the tests highlighting “danger zones” for contamination. Though 
assessors will be speech-language pathologists who should already have a basic understanding of the 
project (through baseline and informed consent training, see sections 3.3 and 3.4), illustrating the 
relationships between the assessments the clinicians are giving and the specific project goals will 
emphasize the importance of the assessment process and adherence to prescribed procedures. This 
development of clinician “meta-competence” or “buy-in” is thought to be important in treatment 
fidelity22,27 (Borrelli, 2011; Gearing et al., 2011), and is intuitive in assessment as well – understanding 
the “why” facilitates investment in the “how”, or adherence to procedures. In addition, highlighting the 
opportunities most susceptible to drift or contamination serves to bring the information to the forefront 
so that it can be actively avoided. Finally, clinician attrition is likely to be observed less in clinicians who 
are invested in the project goals and feel as if their contribution is important.  
The Clinical Core will facilitate the following assessment training procedures (Appendix 1) for both 
Project 1 and Project 2: (1) independent reading of the assessment manual; (2) video observation of 
expert administration of each test, administered to persons with varying types and severity of aphasia; 
(3) small group  
training session that will include manual review, highlighting of similarities and differences between 
administration procedures via discussion and video observation, and supervised role-play with 
feedback; (4) at project initiation, three supervised assessment sessions with expert feedback; and (5) 
throughout study, yearly “booster” small group training and 1-2 supervised assessment sessions with 

 
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expert feedback. These training procedures will guard against clinician-to-clinician variability, drift, 
and contamination.  
3.10 Assessment Delivery. The Clinical Core will monitor adherence to assessment administration 
procedures throughout the entire study. A trained independent rater will watch videos of recorded 
sessions and rate the following for all assessments except the repeated measures (discourse, PNT): 
adherence to assessment administration procedures; frequency of additional, non-prescribed elements; 
frequency of omitted prescribed elements; frequency of cross-contamination; and assessor enactment 
and engagement. The blinded rater will conduct the implementation assessment for the repeated 
measures, as they will already be spending ample time observing the videos (as discourse transcription 
and PNT scoring often requires multiple viewings) and will also have expert knowledge of the 
assessment procedures and scoring. Each assessor will have 20% of their total assessment session 
time monitored quarterly for accurate implementation. Continuous monitoring the delivery of the 
assessment will further guard against drift and contamination and alert the Clinical Core to the need for 
action if fidelity is compromised.  
3.11 Rater Training  
Assessor – As described in 3.6, the assessor will administer and score several tests for each project. 
The assessor training described above (3.9) includes several opportunities for expert feedback. The 
feedback will address administration procedures for all assessments as well as scoring procedures and 
accuracy for all assessments except the repeated measures.  
Rater – Blinded raters will be responsible for scoring of the repeated measures. There will be some 
overlap between training of the assessor and blinded raters. The Clinical Core will expect blinded raters 
to complete the following alongside assessors (Appendix 1): (1) independent reading of the 
assessment manual; (2) video observation of expert administration of the repeated measures 
administered to persons with varying types and severity of aphasia; and (3) attendance to small group 
training session that will include manual review, highlighting of similarities and differences between 
administration procedures via discussion and video observation, and supervised role-play with 
feedback.  
Raters will then participate in specialized training sessions for the repeated measures that serve as the 
primary and secondary outcome measures for the proposed projects. For Project 1, this includes the 
PNT and the discourse production tasks. (The ACOM is also given more than once, but since it is 
computerized, the only rater responsibility will be checking the files and entry into DCU). For Project 2, 
this includes also the PNT and a discourse production task.  
The specialized training for PNT will include the following phases, facilitated by the Clinical Core: (1) 
independent reading of material included in a blinded rater manual, which will contain “The Philadelphia 
Naming Test: Scoring and Rationale” 64, the “Detailed Guide to PNT Scoring” (Moss Rehabilitation 
Institute), and the “Scoring Protocol” (Moss Rehabilitation Institute); (2) co-scoring of two PNT training 
videos (one mild aphasia, one moderate-severe aphasia) during which the expert rater will narrate the 
decision-making process and discuss with the trainee any pertinent topics; (3) independent scoring of 
four PNT training videos, two with nonfluent aphasia (1 high, 1 low severity) and two with fluent aphasia 
(1 high, 1 low severity), to be checked by the expert rater; (4) feedback session reviewing independent 
scoring; (5) repeat of steps 2 and 3 if acceptable point-to-point agreement (> 95%) was not achieved; 
and (6) throughout the study, yearly “booster” small group training and scoring review. Raters will also 
be instructed about a scoring modification needed for Project 4, where the final self-corrected 
responses are also scored with PNT scoring conventions. This means that for the majority of aims, the 
“first complete attempt” is rated as indicated by PNT scoring guidelines and used for analyses, but for 
Project 4, it is necessary for the raters to also score self corrections on the PNT.  

 
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The specialized training for discourse assessment will include the following phases, facilitated by the 
Clinical Core: (1) direct instruction regarding use of Codes for the Human Analysis of Transcripts 
(CHAT) and Computerized Language Analysis (CLAN) tools,68 including EVAL,69 with relevant sections 
of corresponding manuals thoroughly reviewed; (2) independent reading of training documents 
available via AphasiaBank (“Coding Cheat Sheet”, “Error Coding”, and “CLAN Glossary”; 
http://www.talkbank.org/AphasiaBank/) and two journal articles (“Presence, completeness, and 
accuracy of main concepts in the connected speech of non- brain-damaged adults and adults with 
aphasia;” 70 and “Main concepts for three different discourse tasks in a large non-clinical sample;” 71 (3) 
guided transcription of four training videos, two with nonfluent aphasia (1 high,  
1 low severity) and two with fluent aphasia (1 high, 1 low severity) to be checked by the expert 
transcriptionist/rater; (4) feedback session reviewing transcription; (5) co-scoring of lexical and gist 
discourse measures for two of the four transcribed sessions, during which the expert rater will narrate 
the decision- making process and discuss with the trainee any pertinent topics; (6) independent scoring 
of the remaining two transcribed sessions; (7) feedback session reviewing independent scoring; (8) 
repeat of steps 5 and 6 if acceptable point-to-point agreement (list from literature) was not achieved; 
and (9) throughout the study, yearly “booster” small group training and transcription and scoring review.  
These thorough training procedures for scoring of naming and discourse performance will improve 
reliability (discussed below) and guard against rater drift. The blinding of raters further improves study 
validity by reducing the potential for scoring bias. Raters will also be trained how to rate the assessor’s 
adherence to administration procedures, rating the following (as described above): adherence to 
assessment administration procedures; frequency of additions, omissions, and cross-contamination; 
and, assessor enactment and engagement.  
3.12 Reliability Point-by-point72 intra- and inter- rater reliability will be conducted for 25% of PNT 
sessions and 25% of discourse sessions, equally distributed across raters. Intra-class correlation 
coefficients for 25% of all assessment measures will be calculated.  
Aim 3: To optimize and monitor treatment fidelity.  
3.13 Rationale As discussed in the Significance section of this Research Plan, treatment fidelity can 
determine the detection (and if present, magnitude) of treatment effects. Eights of the 13 aims of this 
P50 application rely on the assumption that treatment will be implemented as intended across 
clinicians, settings, participants, and for the entire duration of the study. Unreliable treatment 
implementation is a known threat to statistical conclusion validity;18 and Gearing and colleagues22 
identified threats to treatment fidelity at every component (design, training, delivery, receipt), which we 
use here to outline the Clinical Core strategy for optimizing treatment fidelity. The strategies for Project 
1 and Project 2 will be discussed separately.  
3.14 Clinician Training  
Project 1 – Standardized clinician training, relying upon a detailed manual of treatment procedures, is 
recommended if treatment fidelity is desired.19 The Clinical Core will be responsible for the development 
of the treatment manual, which will include the following sections22,66: project explanation, relationship 
of treatment activities to project goals, treatment administration procedures, comparison of active 
ingredients of each treatment approach (including highlighting of “danger zones” for contamination as in 
the assessment manual), and troubleshooting tips. Similar to the assessment manual, the purpose of 
explaining the project and emphasizing the importance of treatment activities, and the differentiation 
thereof, promotes clinician buy-in and subsequent adherence to procedures.22,27 Explicit instructions for 
treatment tasks are included and are likely to reduce the likelihood of cross-contamination.66 The (non-
computerized) tasks used in Project 1 are no more complex than those practiced in everyday clinical 
practice, as indeed they arose from those practices; they are simply operationalized so that procedures 
would be standardized across persons and settings.  

 
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The Clinical Core will facilitate the following treatment training: (1) independent reading of the 
treatment manual; (2) video observation of treatment delivery (available from pilot study) to persons 
with varying types and severity of aphasia; (3) small group training session that will include treatment 
manual review, with highlighting of “danger zones”, as well as supervised role-play with feedback; (4) at 
project initiation, three supervised sessions of each treatment arm with expert feedback; and (5) 
throughout the study, yearly “booster” small group training and 1-2 supervised treatment sessions (both 
treatment arms) with expert feedback. These training procedures will guard against clinician-to-clinician 
variability, drift, and contamination.  
Project 2 – Standardized training for Project 2 will also include a detailed manual of treatment session 
procedures, though the challenges for treatment fidelity are different from Project 1 due to the 
computerized nature of the speech-language treatment, and the inclusion of brain stimulation. Because 
of steps taken during stimuli development, there is little threat of contamination. The threats to 
treatment fidelity that need to be addressed during training are related to the administration of brain 
stimulation. Perhaps the most complex element of treatment for Project 2 is electrode placement for 
transcranial direct current stimulation (tDCS). With training and experience, this process becomes 
simple and routine. We have had no difficulty training clinicians to do this for the CATES trial (PI: 
Fridriksson) or for the studies at JHMI (Hillis). During the first two years of the project, Dr. Richardson 
will visit JHMI to ensure the electrode placement (particularly for participants randomized to fMRI-
guided localization of electrode placement) is conducted in the same way as in the CATES trial. The 
greatest potential threat to validity concerns blinding, and automatic blinding of both the participant and 
the clinician the WebDCUTM makes this threat negligible. The clinician enrolling the participant will not 
see the treatment assignment, only a numeric participant number generated by the DCU server, which 
is entered into a software package that controls whether tDCS or Sham is delivered to the participant. 
The in-house software/hardware setup allows for switching the tDCS on and off without any 
involvement from the participant or experimenter. The Clinical Core will develop the treatment manual 
for Project 2, which will include the following sections: project explanation, relationship of treatment 
activities to project goals, treatment administration procedures, and troubleshooting tips.  
Training procedures facilitated by the Clinical Core for Project 2, most of which have been 
implemented with success for CATES, will include the following (Appendix 1): (1) independent reading 
of the treatment manual; (2) video observation of treatment delivery; (3) small group training sessions 
that will include treatment manual review, with a focus on the importance of blinding, as well as direct 
instruction and practice with electrode placement and device operations; (4) at project initiation, two 
supervised treatment sessions, with brain stimulation portions co-led with experts (Celnik, Richardson); 
(5) two supervised treatment sessions with expert feedback; and (6) throughout study, yearly booster 
training. These training procedures will guard against clinician-to-clinician variability, drift, and 
unblinding.  
3.15 Treatment Delivery The Clinical Core will monitor adherence to treatment procedures throughout 
the entire study. Based upon recommendations by Gearing et al.22, a trained independent rater will 
watch videos of recorded sessions and rate the following for both Project 1 and Project 2: adherence 
to treatment procedures (Project 1, Appendix 2; Project 2, Appendix 1); frequency of additional, non-
prescribed elements; frequency of omitted prescribed elements; frequency of cross-contamination; and 
clinician enactment and engagement. Each clinician will have 20% of their total treatment session time 
monitored quarterly for accurate implementation. Continuous monitoring of treatment delivery will guard 
against drift and contamination, and alert the Clinical Core to the need for action if fidelity is 
compromised.  
For Project 2, the rater will also make a judgment about whether or not they thought the brain 
stimulation was sham or active. The rater will enter this information into the DCU, so that they can be 
alerted if the match of rater judgments to actual administration is above chance, which would indicate 
that there might be something observable in the treatment that could potentially unblind the participant 
that would need to be addressed immediately.  

 
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3.16 Treatment Receipt Another component of treatment fidelity involves monitoring whether or not 
participants demonstrate behaviors that indicate they have received the treatment, which can be 
assessed by rating within-session participant comprehension or utilization of treated behaviors.22,66 The 
trained independent rater assessing treatment delivery (3.15) will also rate the following for Project 1: 
participant engagement, participant comprehension of treatment activities, and frequency of participant 
attempts to perform treatment activities. This information combined with the within-session data 
collected by the clinician regarding success, cueing needed, etc. will serve as an indicator of treatment 
receipt. For Project 2, the rater will also assess participant engagement, and this rating combined with 
data produced after each computerized session will indicate treatment receipt.  
3.17 Clinical Core Management Plan – Overall management of the Clinical Core will be in the hand of 
Dr. Hillis. She will be assisted by Drs. Fridriksson (USC), to be hired Clinical Care Coordinator (USC), 
and Bonilha (MUSC). The Clinical Core Coordinator will manage and implement day-to-day operations, 
as described above, with ad hoc supervision by Hillis. Priorities will be determined by Hillis, Clinical 
Core Coordinator, and Fridriksson together in weekly videoconferences via www.GoToMeeting.com. 
Potential disputes will be resolved by this core leadership, using a conflict resolution model described 
by Shearouse,73 as described in detail in the Administrative Core.  
3.18 Potential Overlap - There is no budgetary overlap between the Research Subprojects and the 
Clinical Core. Dr. Hillis will devote a total of 35% effort to the C-STAR (25% to Project 2, 10% to the 
Clinical Core).