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Translational Research in Aphasia: From
Neuroscience to Neurorehabilitation
SUPPLEMENT
Purpose: In this article, the authors encapsulate discussions of the Language Work
Group that took place as part of the Workshop in Plasticity/NeuroRehabilitation
Research at the University of Florida in April 2005.
Method: In this narrative review, they define neuroplasticity and review studies that
demonstrate neural changes associated with aphasia recovery and treatment. The
authors then summarize basic science evidence from animals, human cognition, and
computational neuroscience that is relevant to aphasia treatment research. They then
turn to the aphasia treatment literature in which evidence exists to support several
of the neuroscience principles.
Conclusion: Despite the extant aphasia treatment literature, many questions remain
regarding how neuroscience principles can be manipulated to maximize aphasia
recovery and treatment. They propose a framework, incorporating some of these
principles, that may serve as a potential roadmap for future investigations of aphasia
treatment and recovery. In addition to translational investigations from basic to
clinical science, the authors propose several areas in which translation can occur
from clinical to basic science to contribute to the fundamental knowledge base of
neurorehabilitation. This article is intended to reinvigorate interest in delineating the
factors influencing successful recovery from aphasia through basic, translational,
and clinical research.
KEY WORDS: aphasia, rehabilitation, plasticity
T
he empirical study of aphasia treatment has a short history, span-
ning only the past several decades. To date, the primary focus of this
research has been to determine the therapeutic value of behav-
ioral intervention in the recovery of language impairment due to acquired
brain damage. Early studies typically examined the value of language
stimulation procedures that were intended to improve overall language
performance in individuals with aphasia (e.g., Basso, Capitani, & Vignolo,
1979; Shewan & Kertesz, 1984; Wertz et al., 1981). The primary question
of interest was whether aphasia treatment improves language ability.
More recently, aphasia treatment studies have investigated the effects of
specific treatments for certain language deficits. These include studies
that involve between-groups and/or within-group comparisons, as well
as studies using single-participant controlled experimental designs. For
example, researchers have investigated the effects of treatments guided
by psycholinguistic, cognitive neuropsychological, and other models of
language for oral and written naming (Beeson & Hillis, 2001; Nickels,
2002; Raymer & Rothi, 2001; Rose, Douglas, & Matyas, 2002), sentence
production and comprehension (Marshall, 2002; Mitchum & Berndt, 2001;
Thompson & Shapiro, 2005), and other language impairments. Studies
have examined the use of computer technology to improve language be-
haviors (Petheram, 2 004; van de Sandt-Koenderman 2004; We inrich,
Anastasia M. Raymer
Old Dominion University, Norfolk, VA
Pelagie Beeson
Audrey Holland
University of Arizona, Tucson
Diane Kendall
VA Brain Rehabilitation Research Center,
Gainesville, FL, and University of Florida,
Gainesville
Lynn M. Maher
DeBakey VA Medical Center, Houston, TX,
and Baylor College of Medicine, Houston, TX
Nadine Martin
Temple University, Philadelphia, PA
Laura Murray
University of Indiana—Bloomington
Miranda Rose
La Trobe University, Melbourne, Australia
Cynthia K. Thompson
Northwestern University, Chicago, IL
Lyn Turkstra
University of Wisconsin—Madison
Lori Altmann
University of Florida
Mary Boyle
Montclair State University, Montclair, NJ
Tim Conway
University of Florida
William Hula
University of Pittsburgh
Kevin Kearns
Massachusetts General Hospital Institute
of Health Professions, Boston, MA
Brenda Rapp
Johns Hopkins University
Nina Simmons-Mackie
Southeastern Louisiana University
Leslie J. Gonzalez Rothi
VA Brain Rehabilitation Research Center,
Gainesville, FL, and University of Florida
Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008 • D American Speech-Language-Hearing Association
1092-4388/08/5101-S259
S259
Boser, McCall, & Bishop, 2001; Wertz & Katz, 2004).
Other studies have been directed toward the use of alter-
native communication strategies, such as gesture, draw-
ing (Lyon, 1995), supported conversation methods (Kagan,
Black, Duchan, Simmons-Mackie, & Square, 2001), and the
pragmatics of communication (Holland & Hinckley, 2002),
investigating their effects on functional communication
abilities. Additionally, studies have examined effects of
treatment provided in a group setting (Elman & Bernstein-
Ellis, 1999; Wertz et al., 1981). In addition to behavioral
studies, researchers have undertaken studies examin-
ing the effects of various pharmacological agents to pro-
mote recovery from aphasia (Shisler, Baylis, & Frank,
2000; Small, 2004; Walker-Batson et al., 2001).
A review of the literature today yields about 800 stud-
ies of aphasia treatment, albeit not all have included
the proper controls for internal validity purposes (see
Thompson & Shapiro, 2005). Qualitative reviews of the
accumulated research have led researchers to conclude
that behavioral intervention promotes language recovery
in adults with aphasia. In general, patients who receive
treatment improve their language ability to a greater ex-
tent than those who do not, and the improvement noted
is signifi cantly greater than the effects of spontane-
ous recovery alone (e.g., Holland, Fromm, DeRuyter, &
Stein, 1996). To estimate the weight of this evidence in
a quantitative manner, meta-analyses of treatment out-
comes studies have also been completed (Robey, 1998;
Whurr, Lorch, & Nye, 1992). Such analyses are neces-
sarily restricted to those studies that provide adequate
quantitative information, which appears to be approx-
imately one fifth of published reports. Meta-analysis has
confirmed that aphasia treatment, in general, is effec-
tive compared with spontaneous recovery alone. The ex-
tent to which different types of treatment are effective
for different forms of aphasia and different language
behaviors has not been thoroughly evaluated through
meta-analysis, however.
The research foundations for the neurorehabilita-
tion of language remain only partially studied, however.
Most previous research has been in the form of prelim-
inary Phase 1 clinical trials examining the influence of
particular treatments for impaired language behaviors
as measured by performance on various language tests
(for reviews see LaPointe, 2005; Murray & Clark, 2006).
Less well investigated is the effect of aphasia treatment
for functional use of communication. Also less thoroughly
examined is whether behavioral treatments may be en-
hanced by pharmacologic intervention.
Neurorehabilitation research, including aphasia treat-
ment research, has been influenced by several bodies
of basic research in the neurosciences and cognitive
sciences. One line of research uses animal models to
study rehabilitation following brain injury (for a review,
see the accompanying article by Kleim & Jones, 2008).
Neurorehabilitation methods also have begun to reflect
findings pertaining to the principles of learning and
memory generated by studies that incorporate computer
simulations and examine performance of healthy indi-
viduals. What is too often missing, however, is the bridge
between basic and clinical research perspectives. Rec-
ognizing the importance and need for translational re-
search from basic science to clinical science, the National
Institutes of Health, as part of its Roadmap initiative,
has instituted efforts to support translational research
that encourages greater interaction between basic and
applied rehabilitation scientists. In a recent forum of
neuroscience and clinical speech pathology researchers
sponsored by the Department of Veterans Affairs Brain
Rehabilitation Research Center, Gainesville, Florida,
and the University of Florida Department of Communi-
cation Sciences and Disorders (BRRC/UF), presentations
and discussion focused on the potential for greater inter-
action between basic and applied rehabilitation scien-
tists. The purpose of this article is to summarize those
discussions and to promote renewed efforts at research
along the continuum from basic science to translational
studies to applied clinical trials in aphasia rehabilita-
tion. We start with a description of neuroplasticity and
evidence for neural changes associated with aphasia re-
covery and treatment. We then highlight a subset of the
principles set forth in the companion article by Kleim
and Jones ( 2008) that ha ve par ticular relevance to
aphasia treatment. We review literature from animals,
human cognition, and computer simulations that serve as
a background to an ensuing discussion of aphasia treat-
ment research addressing several principles of neuroreha-
bilitation. Ultimately, we propose a framework that might
potentially guide future research efforts in neurorehabil-
itation and promote translational research initiatives in
aphasia rehabilitation.
Neuroplasticity and Aphasia Recovery
A fundamental principle underlying the research
discussed in this review is that the brain, regardless of
age, is flexible and capable of change; that is, it has the
capacity for structural and functional plasticity through-
out the human life span. Plasticity underlies normal
processes such as development, learning, and maintain-
ing performance while aging, as well as response to brain
injury. Plastic changes may be adaptive, as we expect from
therapy, or maladaptive, as when an individual loses func-
tion from failure to use a skill (Kleim & Jones, 2008).
Neuroimaging technologies have advanced research that
addresses challenging questions regarding the neural
mechanisms of aphasia recovery. Neuroimaging stud-
ies have provided evidence indicating a differential
S260 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
contribution of neural mechanisms depending on the
stage of aphasia recovery. Recovery of language function
in the subacute stage following brain damage is aided by
a neurophysiological process associated with spontane-
ous recovery. Left hemisphere brain regions involved in
language function rendered temporarily dysfunctional
by brain damage (most commonly, stroke) contribute to
early recovery (Cappa et al., 1997; Heiss, Kessler, Thiel,
Ghaemi, & Karbe, 1999). This physiological restitution
may be complemented by reorganization of brain func-
tion, the more likely mechanism of change, particularly
at later stages of aphasia recovery. In general, neuro-
imaging studies provide evidence for two mechanisms
of functional reorganization of language in aphasia:
(a) recruitment of residual left hemisphere structures
that may have been premorbidly involved in language
function and (b) recruitment of right hem isphere re-
gions, typically homologous to left hemisphere language
areas (Thompson, 2004). Recruitment of residual perile-
sional left hemisphere regions for recovery has been doc-
umented in functional imaging studies in patients with
aphasia and other neurogenic communication disorders
(Pataraia et al., 2004; Price e t al., 199 8; Rosen et a l.,
2000; Weiller et al., 1995). In addition to involvement
of spared regions within the left hemisphere language
network, a shift of language function to right hemisphere
regions has also been documented in individuals with
aphasia (Papanicolaou et al., 1988; Weiller et al., 1995).
The respective contributions of left and right hemisphere
changes are not well understood. Some researchers sug-
gest that recovery supported by the right hemisphere
may be less complete in comparison to that associated
with left perilesional areas ( Belin et al., 1996; Ka rbe
et al., 1998; Kurland et al., 2004; Winhuisen et al., 2005),
and others suggest that right hemisphere changes may
not be responsible for long-term recovery, and may even
be maladaptive (Price & Crinion, 2005). Whether pa-
tients develop intrahemispheric left hemisphere reor-
ganization or atypical right hemisphere dominance may
be influenced by factors such as the age of lesion onset or
etiology of the lesion (Pataraia et al., 2004).
Research in neuroplasticity associated with aphasia
has primarily focused on natural recovery processes, less
commonly controlling for or manipulating the effects of
behavioral treatment. Several case studies have exam-
ined changes associated with behavioral treatment.
These studies provide promising evidence that func-
tional brain reorganization underlies language improve-
ment associated with specific treatment (Adair et al.,
2000; Belin et al., 1996; Cornelissen et al., 2003; Legar
et al., 2002; Musso et al., 1999; Pulvermüller, Hauk,
Zohsel, Neininger, & Mohr, 2005; Small, Kendall Flores,
& Noll, 1998; Thompson, 2000; Vindiola & Rapp, 2005;
Weirenga et al., 2006). In addition to replicating these
initial findings, more research is needed to explore how
other stroke recovery factors (e.g., lesion size and lo-
cation, age, type of language deficit) might influence
treatment-related neural reorganization (Cramer &
Bastings, 2000). In addition to the neural correlates of
specific language changes, research is needed to explore
neural reorganization and language use during social com-
munication. Finally, wit h respect to evidence gleaned
from imaging studies, researchers and clinicians must
keep in mind the advice of Shih and Cohen (2004): Before
we ascribe too much significance to activation maps, we
need to answer basic questions such as the specific func-
tional role of activated regions, their contribution to task
performance or functional rec overy, and their signifi-
cance in terms of the activity they reflect (i.e., excitatory,
inhibitory, both; p. 1773). For example, it has been sug-
gested that right hemisphere contributions to aphasia
recovery may reflect recruitment of attention, memory, or
executive functions to support language recovery
rather than restoration of language funct ions per se
(e.g., Crosson et al., 2005).
In summary, a growing body of neuroimaging re-
search indicates a significant relation between neuro-
plastic changes and language recovery. Thus, it suggests
that a major purpose of rehabilitation is to maximize
neural plasticity and lead to functional communication
gains. To this end, researchers have attempted to ex-
plore conditions that maximize gains following aphasia
treatment. The aphasia literature has been influenced
by studies within the basic sciences that have dissected
the conditions and influences on rehabilitation outcomes
following neurological impairments.
Basic Science Evidence for
Experience-Dependent Plasticity
Several lines of evidence contribute to the science
of rehabilitation. Many studies incorporate animal mod-
els to explore conditions influencing recovery from brain
injury. Such studies often focus on motor and sensory
functions, though some studies examine recovery in cog-
nitive domains such as spatial memory and object recog-
nition (e.g., Dahlqvist, Ronnback, Bergstrom, Soderstrom,
& Olsson, 2004). Until the necessary translational re-
search is done, researchers can only make inferences that
the same principles of recovery are relevant to language
functions. Evidence from healthy individuals and com-
puter simulations also contribute to our understanding
of principles of rehabilitation, including specific exam-
ples in the language d omain. From this basic science
literature, Kleim and Jones (2008) entertain several
fundamental experience-dependent training principles
that influence neural plasticity and successful recovery
from neural lesions. Extensive reviews of the neurosci-
ence literature as it applies to aphasia recovery, in
Raymer et al. (Language Work Group): Translational Research in Aphasia S261
particular, have been provided elsewhere (Keefe, 1995;
Turkstra, Holland, & Bays, 2003). In this section, we high-
light a subset of those principles to illustrate several basic
science applications that have been particularly relevant
to research initiatives in aphasia treatment that we ex-
plore in a later section.
Timing of Treatment Delivery
One of the most provocative findings from animal
research is that intensive intervention early after injury
may adversely affect recovery (Kleim, Jones, & Schallert,
2003; Woodlee & Schallert, 2004). Schallert, Kozlowski,
Humm, and Cocke (1997) observed that two opposing
processes occur during recovery: facilitative neural com-
pensation (e.g., via reorganization of synaptic networks)
and secondary neurodegenerative processes induced by
the injury. Both of these processes may c ontinue for
hours or days postinjury and have been hypothesized
to influence stroke recovery (Seisjo, 1992a, 1992b). For
example, Schallert et al. explored whether compensa-
tory behavioral strategies may exacerbate secondary
injury when provided early postinjury. They found that
lesions of the rat sensorimotor cortex induced positive
changes in contralateral brain regions (e.g., increased
dendritic branching) only if the animal was free to use
both the affected and unaffected limbs. In other words,
there was reorganization of brain function as compen-
sation. However, if the animal was forced to use the
weak limb (whic h is a kin to constraint therapy ap-
proaches in humans), lesion size actually increased, an
example of secondary neurodegenerative injury, and
more severe and persistent symptoms were observed.
Early exposure to enriched environments, particularly
when paired with intense motor training, has been found
to have detrimental effects on neuroplasticity mecha-
nisms within both cortical and hippocampal brain regions
(Farrell, Evans, & Corbett, 2001; Kleim et al., 2003).
Importantly, this pattern of physiological response does
not persist for long after injury. Schallert and colleagues
(1997; Woodl ee & Sc hallert, 2004) have reported no
effect of weak limb overuse that occurs after the first 7–
14 days postinsult. The timing of treatment, however,
appears to interact with other variables such as lesion
site. For example, weak limb overuse during the acute
stages of recovery did not negatively affect either lesion
size or behavioral symptoms in rats when stroke affected
subcortical versus cortical b rain regions (Woodlee &
Schallert, 2004).
From a clinical perspective, Schallert and colleagues
(1997) concluded that, in the acute stage after injury,
“ behavior, including neurological assessment, might af-
fect neural events I [as] the behavioral tests themselves
might alter the process of recovery” (p. 236). Thus, tim-
ing of intervention apparently is critical. It remains to be
established what period should be considered “acute”
in humans to help guide clinicians regarding when they
can prescribe more aggressive treatment aimed at re-
instituting impaired functions. This is a very impor-
tant question, given that these findings are basically from
rats, whose life spans are considerably shorter than hu-
man life spans. That is, the first 7–14 days postlesion in
rats may in fact constitute a far longer time period than
that amount of time in humans. In contrast, intensive
intervention in the chronic stage is effective not only at
improving function, but also at preventing loss of func-
tion, in both animals and humans.
Use It or Lose It
Animal research has shown that the failure to par-
ticipate in rehabilitation has adverse effects on recovery.
More than 30 years ago, Taub and colleagues (see sum-
maries in Taub et al., 1994; Taub, Uswatte, & Elbert,
2002) demonstrated that nonhuman primates learned to
avoid using an injured limb based on negative experi-
ences in the early phase after an injury, and that this
early “learned nonuse” prevented later functional re-
covery of the affected limb. Eventually, the animals per-
manently ceased to attempt to use the injured limb.
Taub et al. found, however, that if the animal was forced
to use the injured limb (typically by binding the intact
limb), the function of that limb improved over time.
Research by Feeney and colleagues (Feeney , Gonzalez,
& Law, 1982; Feeney & Sutton, 1987, 1988) yielded find-
ings that are an interesting complement t o those of
Schallert et al. and Taub et al. Feeney et al. studied the
effects of physical and chemical restraints on recovery
from stroke, primarily in cats. They found that both types
of restraints retarded recovery, whereas animals that
received “rehabilitation” (beam-walking practice) had
significantly faster and better recovery of function. In
addition to supporting the benefits of intervention, this
finding raised questions about the use of chemical re-
straints such as Haldol in the acute and subacute
stages after neural injury.
Recently, social restraints have also been found to
have negative effects on neurological and behavioral
recovery. Craft and colleagues (2005) examined the ef-
fects of the presence or absence of social interaction on
lesion size, weak limb use, and stress levels (as mea-
sured by concentrations of certain hormones and protein
in blood samples) in rats with middle cerebral artery
stroke. Although the findings varied slightly depending
on the gender of the rats, rats that were housed with an
unlesioned rat demonstrated greater decreases in their
lesion size and stress levels and increases in their use of
their weak limb compared with rats that were isolated
during acute recovery from stroke.
S262 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
Generalization and Transfer
of Treatment Effects
When an animal undergoes behavioral stimulation,
many changes occur at the neuronal level (see review in
Kolb, 1995). These include increases in the number and
density of synapses, dendritic length, and synapse size.
The results of several experiments suggest that these
changes may allow animals to improve performance on
tasks that are not specifically trained. That is, improve-
ments on one task may generalize to novel, related tasks.
For example, Kolb reported that rats trained on a task
with one paw showed increased dendritic patterns in
homologous regions in both hemispheres. Moreover,
these changes were similar to the changes observed in
rats trained with two paws. Kolb and colleagues sug-
gested that experience may “prime” the brain for future
learning. This is an intriguing notion, as it suggests that
engagement in the therapy process itself might increase
the probability of gains beyond the behavior trained.
The complexity and richness of the training envi-
ronment can also influence the extent of the treatment
effects. For example, Komitova, Zhao, Gido, Johansson,
and Eriksson (2005) compared the effects of an enriched
environment (e.g., cages that include lots of objects, chains,
swings, etc. of different sizes and materials that are varied
over time) with that which encouraged only voluntary
running (i.e., cages that include a running wheel only) on
the neural and behavioral poststroke recovery of adult
rats. Rats exposed to the enriched environment demon-
strated significant behavioral gains (i.e., ability to
traverse a rotating pole) and positive neural changes
in ipsi- and contralateral neural regions. In contrast,
rats in the running wheel cages showed no significant
functional improvements and less neuroplasticity change
than had been anticipated. These findings as well as
those from other studies comparing the effects of train-
ing complex/skilled behaviors versus simple motor skills
(e.g., Ding, C lark, D iaz, & Rafols, 2003) suggest that
greater functional outcomes and enhancement of positive
neuroplastic changes are more likely when rehabilitation
incorporates complex tasks and/or environments.
Influence of Repetition and
Intensity of Treatment
Pascual-Leone, Wassermann, Sadato, and Hallett
(1995) showed that repetition is important in maintain-
ing changes in the brain and their corresponding func-
tional benefits. They found that changes observed in the
cortical maps of blind individuals who were proficient
Braille readers and used Braille at work depended on
whether the participants had been working for a 6-hour
period or had taken the day off work. This result may be
familiar to readers who perform skilled arts or sports,
and miss a few days of practice. From a clinical per-
spective, it supports the need for long-term, consistent
use of a skill to maintain gains in therapy.
Woodlee and Schallert (2004) suggested that be-
cause early overuse of a weak limb can result in greater
deficits, and complete disuse can also slow recovery,
acute rehabilitation should be less intense and then,
over time, become more “aggressive.” Kleim et al. (2003)
found that motor map reorganization and increased syn-
apse formation occurred only after more extended train-
ing of skilled/complex reaching in adult rats. That is,
neural differences between rats that underwent skilled
versus unskilled reaching training became apparent only
after 7–10 days of training. The rats receiving training
in skilled reaching showed the most dramatic improve-
ments in skilled reaching after just 3 days of training;
after that they continued to show behavioral improve-
ments, but the rate of improvement was much slower.
Therefore, the implication of this work is that patients
may need to be trained beyond acquisition of a com-
plex behavior (e.g., any language behavior) if we hope to
induce neural changes. Without the essential transla-
tional research, however, it is unknown whether these
findings can be extended to language or even motor
abilities in humans.
A large literature on memory and learning, partic-
ularly in motor learning tasks, conducted in healthy in-
dividuals provides another body of evidence relevant to
the intensity of training schedules. A meta-analysis of
63 studies by Donovan and Radosevich (1999) indicated
that with regard to retention of learning effects, the ef-
fects of practice provided in a distributed practice sched-
ule surpass those of a massed practice schedule. The
advantage reported for distributed practice was modu-
lated by the nature of the training task, as the effect was
somewhat less potent for more complex activities. This
observation has implications for the training schedule
used with patients in clinical settings.
Computer Models
in Rehabilitation Research
In addition to animal and human models of learn-
ing, memory, and rehabilitation, computer simulations
have provided a line of evidence that has influenced sub-
sequent studies of aphasia rehabilitation. Theories and
models of cognitive processes such as language were de-
veloped first on the basis of observations of human be-
haviors. In the past few decades, the understanding of
cognition has benefited further from computer simula-
tions of these theories and models. Computational in-
stantiations of theories can be used to generate and test
hypotheses about c ognit ive functions under both nor-
mal and impaired conditions. In the language domain,
Raymer et al. (Language Work Group): Translational Research in Aphasia S263
computational models have been used to test theories
of lexical access in word production (Dell, 1986; Harley,
1984; Levelt, Roelofs, & Meyer, 1999; McNellis &
Blumstein, 2001; Plaut & Booth, 2000), word recognition
(McLeod, Plaut, & Shallice, 2001), serial order mecha-
nisms in word production (Vousden, Brown, & Harley,
2000), and, more recently, articulatory mechanisms in
humans (Kello & Plaut, 2004). (See Nadeau, 2000; Nadeau
& Rothi, 2004, for a detailed review.) Likewise, these mod-
els have been instrumental in furthering researchers’
understanding of the nature of impairments to mecha-
nisms of lexical access (e.g., Dell, Schwartz, Martin, Saffran,
& Gagnon, 1997; Gotts & Plaut, 2002; Mikkulainen,
1997; Plaut, 2002; Rapp & Goldrick, 2000; Ruml &
Caramazza, 2000) and semantic memory (e.g., Lambon-
Ralph, McClelland, Patterson, Galton, & Hodges, 2001)
subsequent to brain damage. Computational models have
also contributed to researchers’ understanding of possi-
ble mechanisms underlying recovery of language func-
tion after damage (Martin, Dell, Saffran, & Schwartz,
1994; Martin, Saffra n, & Dell, 1996; Plaut, 1996; Schwartz
& Brecher, 2000). With respect to treatment, computa-
tional models have generated hypotheses about language
learning (Pl aut & Kello, 200 2) and the role of short-
term memory processes in word learning (Gupta &
MacWhinney, 1997). Additionally, some researchers are
beginning to use computer models to examine processes
exploited in treatment tasks such as priming (Plaut &
Booth, 2000), and others have generated predictions
about interfering and facilitating effects of priming with
semantically or phonologically related words on lexical
access (Martin, Fink, Laine, & Ayala, 2004).
Item characteristics such as concreteness and fre-
quency are known to influence normal and impaired lex-
ical access. Computational models have been used to
demonstrate these effects (Martin et al., 1996; Plaut &
Shallice, 1993) and to account for them within cognitive
theory. Moreover, computational studies have informed
researchers about how the characteristics of stimuli that
are used in training can maximi ze generali zation to
untrained items. Plaut (1996) demonstrated in his con-
nectionist model that greater relearning of a semantic
category occurred when training included both typical
and atypical members of that category. This finding was
tested by Kiran and Thompson (2003) in their study
of word retrieval treatment in aphasia. These findings
challenge conventional wisdom with a new logic that
in hindsight makes good sense: Training more complex
members highlights an array of features associated with
the category, prototypes as well as those of atypical
members; training typical items highlights only proto-
typical features. Plaut’s computer model, then, revealed
something about a principle of learning and relearning
that may be translated directly to neurorehabilitation.
As another example, Gordon and Dell (2003) used a
computer simulation to examine the influence of syntax
and semantics in lexical production for nouns and verbs.
The computer was trained to produce sentences with
either heavy or light verbs (i.e., verbs that vary accord-
ing to the number of semantic features that make up the
verb; Breedin, Saffran, & Schwartz, 1998). Ultimately,
Gordon and Dell found that semantic features were more
important for learning to produce heavy verbs and nouns,
whereas syntactic features influenced production of light
verbs and function words. Gordon (2005) used these find-
ings to motivate a study examining contrasting treat-
ments for verbal production in a patient with aphasia.
Clinical Aphasia Evidence for Principles
of Experience-Dependent Plasticity
Within the aphasia treatment literature, studies
have addressed several of the variables discussed earlier
that are hypothesized to influence treatment outcomes.
Among these are the intensity and timing of treatment
delivery. Other work has focused on variables related
to generaliza tion , or t ransf er, of treat ment effects to
untrained material. As shown next, a fair amount is
known with regard to some of these influences on apha-
sia treatment outcomes. The picture is far from com-
plete, however.
Timing of Treatment Delivery
It is a long held notion in aphasia rehabilitation
that treatment should be provided as early as possible
following the aphasia-inducing event, suggesting that
treatment provided in more chronic stages of recovery is
less likely to be effective. Wertz and colleagues (1986),
however, found that a group of participants who delayed
entry to their aphasia treatment protocol by 3 months
caught up with a group that instituted treatment in the
subacute phase of aphasia recovery. In a meta-analysis,
Robey (1998) examined the magnitude of treatment ef-
fect sizes relative to the timing of treatment and found,
however, that treatment begun during the acute period
(before 3 months postonset) resulted in almost twice the
effect size of spontaneous recovery (1.15 vs. 0.63) and
that the effect size of treatment initiated during the
subacute period (between 3 and 12 months postonset)
was small, but greater than that for untreated individ-
uals (0.57 vs. 0.34). In addition, treatment initiated
during the chronic stage (after 1 year postonset) showed
an effect size similar to that during the subacute period
and was notably larger than that for untreated indi-
viduals (0.66 vs. 0.05). These data indicate th at early
treatment may be maximally beneficial but that later
S264 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
treatment also impacts language abilit y and use. In
Robey’s meta-analysis, the acute phase encompassed a
fairly broad 3-month time frame. Studies examining re-
covery in aphasia show that most spontaneous recovery
actually occurs within the first 2 months post–aphasia
onset (e.g., Holland, Greenhouse, Fromm, & Swindell,
1989). Although treatment effects are greatest in acute
stages of aphasia recovery, several studies have reported
remarkable gains in language abilities many years fol-
lowing aphasia onset (e.g., Kendall et al., 2006).
Use It or Lose It?
Taub and colleagues (Taub et al., 1993, 1994) repli-
cated the animal research on forced use to overcome
“ learned non use” in studies of hemip aretic human
stroke patients. Based upon the notion that the potential
rehabilitation of the affected limb is detrimentally in-
fluenced by the compensatory use of the unaffected limb
through a process of learned nonuse, constraint-induced
movement therapy (CIMT) has been shown to result in
improved bimanual performance in some patients with
chronic poststroke hemiplegia (Kunkel et al., 1999;
Liepert et al., 2000; Taub, Uswatte, & Pidikiti, 1999).
The key principles of CIMT are massed practice, con-
straint of the unaffected limb with forced use of the
affected limb, and behavioral shaping of the response.
These principles have been applied to the rehabilitation
of chronic aphasia as well by Pulvermüller and colleagues
(2001). Individuals with chronic aphasia received inten-
sive massed practice with oral language over a 2-week
period, restricting responses only to spoken language in
a variety of interactive communication tasks. This inten-
sive training was associated with significant improve-
ments on standard tests and other and self-ratings of
communication in daily living. The increased benefit that
constrained therapy yielded relative to conventional ther-
apy, however, was confounded by differences in the in-
tensity with which the two treatments were delivered
(i.e., constraint therapy was provided more intensively
than conventional therapy).
Maher et al. (2003) conducted a partial replication
of the Pulvermüller et al. (2001) study that attempted
to control for intensity. In the Maher et al. study, 4 par-
ticipants underwent constraint-induced language therapy
(CILT) and a comparison group of 5 participants under-
went PACE (promoting aphasics’ communicative effec-
tiveness) therapy (Davis & Wilcox, 1985) using the same
stimulus materials and treatment schedule as the CILT
group. Whereas both groups showed some change, there
were greater treatment gains observed and maintained
in verbal measures in the CILT group compared with the
PACE group. The PACE group, in contrast, increased
use of nonverbal behaviors. This suggests that the active
components of CILT cannot be attributed to the inten-
sity of the intervention alone and supports the notion of
forced use of verbal behaviors in rehabilitation. The im-
portance of continued use is suggested in a further study
by Meinzer, Djundja, Barthel, Elbert, and Rockstroh
(2005), who evaluated the effects of two forms of constraint-
induced therapy. One form was similar to that used in
previous research, and the other included writing activ-
ities and training of daily communication activities with
the assistance of family members. Positive outcomes on
standard tests and patient and family ratings were ob-
served following administration of 10 days of treatment
(total of 30 treatment hours) for both groups, and these
gains were maintained at a 6-month follow-up. More-
over, greater gains on patient and family ratings were
observed for patients who had received treatment that
involved family members who presumably continued to
promote use of the speech modality after therapy had been
terminated.
Generalization, or Transfer,
of Treatment Effects
Many studies in the aphasia treatment literature
have addressed generalization of treatment effects to
untrained language behaviors. Results of this work have
been mixed. Whereas some studies have shown little gen-
eralization, others have shown positive effects of treat-
ment on the language behaviors tested for generalization.
One principle that has resulted from this work is that
generalization is most likely to occur to a language be-
havior that is similar to the trained language behavior.
For example, in treatment of naming impairments, train-
ing items from a particular semantic category results in
greater generalization to untrained items from the same
class than to untrained items from a different semantic
category (e.g., Kiran & Thompson, 2003; see also Nickels,
2002, for review). In the domain of sentence production
and comprehension treatment, generalization is most
likely to occur to untrained sentences that are syntac-
tically related to trained sentences (Thompson & Shapiro,
2005). These results likely reflect the organization and
processing of language in which similar processing rou-
tines and representations are utilized for similar lan-
guage behaviors. Thompson, Shapiro, Kiran, and Sobecks
(2003) showed that the complexity of language mate-
rial used in treatment also impacts generalization (i.e.,
the complexity account of treatment efficacy [CATE]).
Although counterintuitive, training complex language
material can result in improvements in less complex, un-
trained language. In contrast, training simple material
has little effect on mastery of more complex material.
Importantly, this complexity effect occurs only when the
trained and untrained material are linguistically related
Raymer et al. (Language Work Group): Translational Research in Aphasia S265
(e.g., training complex sentences that involve certain syn-
tactic constructs results in generalization only to simpler
sentences that involve the same syntactic constructs).
Furthermore, influenced by the Plaut (1996) computer
simulation mentioned earlier, Kiran and Thompson (2003)
extended the complexity effect to the semantic domain
and demonstrated improved word retrieval by training
atypical members of a category (e.g., birds: ostrich) ver-
sus typical members (e.g., robin). Overall, aphasia stud-
ies reporting generalization of training effects to untrained
language behaviors complement the findings in the ani-
mal literature reporting transfer of training effects to
untrained behaviors.
Intensity of Treatment
The notion that providing intense treatment (i.e., sev-
eral hours a day or week) enhances recovery to a greater
degree than distributed practice (i.e., 1 or 2 hr a week)
was a basic tenet of Schuell et al.’s approach to treat-
ment in the 1960s (Schuell, Jenkins, & Jimenez-Pabon,
1964). This issue has received recent attention in the apha-
sia literature, albeit few controlled studies have directly
compared intense versus distributed treatment sched-
ules. W ith respect to word retrieval in aphasia, Hinckley
and Craig (1998) reported that intensive training (>20 hr
per week) led to significant improvements in a standard-
ized word retrieval measure as compared with a noninten-
sive training protocol (3 hr per week). The intensity of
treatment (when reported) was examined in the extant
literature by Robey (1998). Results showed that the more
intense the treatment, the greater the change. In general,
it appears that 2 or more hr per week of treatment re-
sult in greater change than treatment delivered at a
lower intensity (≤1.5 hr per week). Bhogal, T eas ell, and
Speechley (2003) reviewed 10 studies of aphasia treat-
ment meeting selection criteria and found that those
studies reporting significant treatment effects provided
on average 8.8 hr of therapy per week for 11.2 weeks. In
contrast, those without significant treatment effects pro-
vided an average of 2 hr of therapy per week for 22.9 weeks.
Although the positive gains observed following constraint
therapy cannot be attributed solely to intensity (Maher
et al., 2003), these studies provide additional support
for the importance of treatment intensity as well. Indi-
viduals in the intense PACE comparison group also im-
proved, suggesting that intensity may be an active factor
in a positive treatment response.
Other Factors Affecting
Treatment Outcomes
We have highlighted evidence associated with only
a subset of the principles of use-dependent plasticity
reviewed by Kleim and Jones (2008). Other factors in-
fluence aphasia treatment outcomes, such as the per-
sonal relevance (i.e., salience) of targeted skills and stimuli,
the type of treatment experience, participant factors such
as lesion location, cognitive status, motivation, age, over-
all health status, and the interactions among these fac-
tors. With regard to each principle, however, questions
remain to be formulated and examined to determine
optimum conditions to maximize neural plasticity and
aphasia recovery.
Conceptual Framework
An emerging literature in the basic sciences of neuro-
rehabilitation in animals, healthy humans, and computa-
tional models support several principles that play active
roles in influencing treatment outcomes. The principles
outlined by Kleim and Jones (2008) ultimately suggest
several directions for additional basic and applied treat-
ment research. In reviewing the principles of neurore-
habilitation, it is worth noting that terminology at times
tends to vary across disciplines (e.g., neuroscience vs.
speech-language pathology). Table 1 specifies terminol-
ogy and a set of working definitions that serve as a back-
drop for the following discussion. In this section, we
present a framework to facilitate the discussion of these
findings in a manner that we hope will be useful in plan-
ning future research. Central to our proposed framework
is the organization of a number of the principles and
concepts that have figured prominently in the basic
science literature into the categories of dependent and
independent variables. That is, several principles of use-
dependent plasticity can be viewed as factors that can be
manipulated as independent variables within rehabilita-
tion experiments. Other principles more directly trans-
late to outcome variables or dependent variables within
experiments. A discussion of these principles of u se-
dependent plasticity in the BRRC/ UF Language Work
Group led to the development of a conceptual framework
within which rehabilitation research questions might be
systematically investigated. A schema delineating the
interplay among these independent and dependent
variables is represented in Figure 1. For the sake of this
discussion,wehaveaddedathirddimensiontoourframe-
work representing the variety of linguistic behaviors that
may be the target of treatment for individuals partici-
pating in neurorehabilitation for language impairments.
The schema could certainly be expanded in all directions
and can be readily adapted for a multitude of target be-
haviors in cognitive, motor, and sensory realms. This
framework provides an organizational scheme for system-
atically reviewing the literature and identifying areas of
research lacking empirical support and needing further
investigation.
S266 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
Table 1. Definitions.
Definition
Independent Variable
Timing The temporal relation between insult and intervention. Timing can vary from the acute
immediate effects of neurologic disease to chronic stages of recovery.
Quantity (repetition) The total number of intervention units, which varies along a numerical continuum from few
to many opportunities for practice.
Intensity The frequency of intervention unit per time unit. Intensity is usually reported as the number
of hours of intervention provided within 1 week. Intensity can vary from intensive, massed
practice (e.g., 20 hr of treatment per week) to a distributed, less intensive schedule (e.g.,
2 hr of treatment per week).
Salience The perceived value or relevance of the experience to the participant.
Treatment variables
(experience-specific training)
Any of the behavioral and/or neural manipulations that take place during the rehabilitation
activity. Some of the techni ques are intended to restore functions in a manner compatible
with normal functioning, whereas o thers a ttempt to compensate for impaire d fu nctions
in a fundamentally different way.
Neural conditions Participant characteristics (e.g., lesion site and size, participant age) that have the potential
to influence treatment outcomes. Such characteristics are often used as grouping variables
to define subsets of participants with common attributes.
Dependent Variable
Acquisition The change of behavior as a result of intervention. This is measured throughout the treatment
process and/or at the completion of training.
Generalization Response generalization is the influence of the intervention for other untrained behaviors.
The untrained behaviors may or may not have some type of systematic relation
to the untrained behavior.
Stimulus generalization is the use of the acquired behavior in contexts or conditions other
than those in which treatment occurred. Often such contexts include situations in which
the behavior is used in a meaningful way apart from the training context, discourse
sampling conditions, or functional environments.
Interference The negative impact of one behavior on the acquisition of another behavior. That is,
improvemen ts in one behavior ten d to undermine the potential for improvements
in other simi lar behaviors.
Maintenance The stability of an acquired behavioral change over time in the absence of continued
intervention. The term retention may also be used to refer to the same concept.
Neural effects (plasticity) The observed changes in neural activity associated with an intervention. These may include
perilesional regions or regions, often homologous, in the contralateral hemisphere.
Figure 1. Proposed conceptual framework.
Raymer et al. (Language Work Group): Translational Research in Aphasia S267
Implications for Aphasia
Treatment Research
This conceptual framework might potentially be
used to guide rehabilitation research in the area of ac-
quired aphasia. The practical implications of basic sci-
ence work drive us to question some of our conventional
rehabilitation practices. These become particularly
important when we recognize that some of the more
compelling evidence from basic science is counter to
conventional intuition and general, accepted clinical
practice. For e xample, results from basic ne uroscience
research suggest that treatment outcomes vary relative
to th e timing of the intervention. In the animal m odel,
early intervention provided in an extremely intense
schedule (e.g. , 24 hr /day) may have a negat ive effect
on outcome (Farrell et al., 2001; Kleim et al., 2003;
Schallert et al. , 1997). However, there i s evidence to in-
dic ate that complete disuse may also impede recovery
(Taub et al., 1994, 2002). Furthermore, earl y interven-
tion might be ne cessary to optimize response to neuro-
trophins released following brain lesions (Cramer &
Chopp, 2000). The adult clinical evi dence suggests that
aphasia treatments begun early yield larger effect sizes
than those s tarted later (Robey, 1998). Whether it is the
timing of treatment or the intense schedule that led to
negative outcomes in some animal studies is not clear.
However, these observations bring up questions that
need to be answered about the timing of aphasia
rehabilitation. Moreover, there is some quest ion about
unexpected interactions with other variables at different
times in recovery. Using notions developed from Woodlee
and Schallert (2004), we predict that conditions that
might optimize treatment outcomes in chronic aphasia
might actually be less optimal in acute aphasia. Thus,
specific guidelines regarding what time periods in re-
covery should be considered “acute” versus “subacute”
versus “chroni c” for the adult clinical population are
needed. Furthermore, factors that have the potential to
interact with timing of treatment, including site and ex-
tent of lesion, type of treatment, and the intensity of
treatment need to be explored. The conceptual frame-
work schematized in Figure 1 may facilitate the de-
sign and systematic investigation of a specific variable,
like timing, to examine interactions between the time
of treatment, the type of treatment provided, and the
language domain affected. Research efforts are ne eded
to identify at what stage rehabilitation (a) is most
effective, (b) is not effective, and (c) might actually be
harmful.
Moving down the list of independent variables rep-
resented in the conceptual framework, the need to de-
termine optimal treatment intensity is certainly prompted
by basic neuroscience as well as adult clinical evidence
and is directly r elated to models of service delivery
and funding for rehabilitation. Not only did treatment
intensity affect skill acquisition and retention in the ani-
mal model (Kleim et al., 2004), findings reported earlier
for the effect of intensity on learning in healthy indi-
viduals emphasized the advantage of distributed over
massed training practice (Donovan & Radosevich, 1999).
Likewise, a recent study showed that a distributed form
of CIMT was effective for improving motor functions
(Dettmers et al., 2005). The aphasia treatment litera-
ture, in contrast, has reported benefits of a more intensive,
condensed treatment schedule. A possible explanation for
these differences may relate to the period of time under
study; the aphasia treatment studies tended to report re-
sults at the completion of training (acquisition), whereas
the learning literature has centered on retention of learn-
ing effects. In either case, the conventional outpatient
treatment schedule (i.e., 2–3 times per week) is chal-
lenged by these data.
Yet to be determined is the influence of treatment
intensity across different domains of language or de-
pendent variables. Future research needs to examine
the relative effect of treatment intensities on behav-
iors that span domains of language and communication
(e.g., semantics, phonology, orthography, morphosyntax,
pragmatics/discourse/social). The conceptual framework
guides the design and systematic investigation of a spe-
cific variable, like treatment intensity, to address spe-
cific questions such as the following: What are relative
effects of differences in treatment intensity across do-
mains of language? Is there a differential effect of massed
versus distributed practice on the acquisition, general-
ization, or maintenance of a new language behavior?
How do variations in treatment intensity affect neural
structure and /or function? Additional studies aimed at
examining the effects of treatment intensity are cer-
tainly warranted, along with an evaluation of the effects
of language activities designed to complement treat-
ment sessions (i.e., homework).
Within rehabilitation, there will be a close interplay
between quantity (repetition) and intensity. However,
the implications from basic neuroscience and computer
models are that patients may require training beyond
the acquisition of a complex behavior (e.g., any language
behavior) for those changes to be lasting and induce neu-
ral changes (Kleim et al. 2003; Pascuale-Leone et al.,
1995). The amount of repetition required for acquisition,
maintenance, an d generalization of various language
domains, as well as to yield neuroplastic changes, needs
to be explored systematically within thi s c onceptu al
framework.
A number of factors that might collectively be
referred to as treatment variables or training experi-
ences, such as the presence of an enriched environment
(Komitova et al., 2005) or the complexity of the task (Ding
et al., 2003; Thompson et al., 2003), have been shown in
S268 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
the basic neuroscience literature to have the potential
to influence neural plasticity in fundamentally different
ways. Potential sources of data on enriched contexts in
humans can be found in studies of natural communication
and conversation. For example, researchers investigating
the efficacy of group aphasia therapy demonstrated that
group “conversation” treatment was superior to unguided
“socialization” in promoting language recovery in groups
with chronic aphasia (Elman & Bernstein-Ellis, 1999).
Whereas there is some evidence that these treatment
variables influence outcomes in the adult clinical popu-
lation, very little of this has been studied systematically,
and this conceptual framework might be used to orga-
nize these investigations. For example, exactly what con-
stitutes an enriched environment for humans and how
does it impact language acquisition, generalization, and
maintenance? Are there conditions of treatment that
might actually lead to interference when treatment moves
to other language behaviors?
Although we may accept the principle of Use It or
Lose It, what kind of use is important for yielding stable,
neuroplastic change? Is constraint to the speech modal-
ity necessary, or can it be combined with other nonverbal
strategies and be equally effective? How does treatment
complexity differ across the language domains? These
same questions also apply to the independent variable
of salience, which ultimately may need further refine-
ment. Salience may have several different dimensions,
including some associated with the external conditions
of the treatment (e.g., lexical context, perceptual attributes
of stimuli) and others with internal aspects of the reha-
bilitation task as implemented with a research participant
(e.g., meaningfulness of the stimuli for that individual,
attentional status and motivation of the participant).
Through the systematic investigation of these variables,
we may be able to determine the critical factors that ac-
count for much of the currently unexplained variance in
treatment results observed in the clinic.
Feedback to Basic Science Efforts
We have proposed several areas in which principles
of experience-dependent plasticity grounded in basic
science research might be used to guide further research
within aphasia treat ment. It should be emphasized,
however, that the interactions between basic and clini-
cal science need not evolve in one direction only. Data
emerging from aphasia research should influence re-
search questions within the basic sciences, as well. For
example,theissueoftimingoftreatmentdeliveryis
of great concern in aphasia. We certainly do not want
to provide treatment in a ti me frame that a ctually re-
ducesorinterfereswithlong-termpotentialforrecov-
ery. To address t his question, we would turn to basic
neuroscience research to identify specific biological
markers (e.g., within blood samples) that indicate
excitotoxicity or that may index severity of injury. It
maybepossibletoidentifysuchbiomarkersofacute,
subacute, and chronic phases of recovery from brain in-
jury in animal models that then could be explored in the
human model. The ultimate goal would be to time in-
tervention during the most favorable periods and to avoid
potentially vulnerable periods.
Rehabilitation specialists are also interested in is-
sues concerning the effects of lesion characteristics on
rehabilitation outcomes, an area that also might be fur-
ther evaluated in the animal model. Questions such as
effects of lesion location might be examined. For exam-
ple, given their contributions to learning and memory,
hippocampal and basal ganglia lesions need to be ex-
plored systematically. Influences of multiple lesion sites
and extent of lesions are also important topics for inves-
tigation in animal models. Aphasiologists have identi-
fied a variety of variables within the treatment context
that influence treatment outcomes. For example, recent
aphasia treatment studies have been interested in the in-
fluence of errorful versus errorless training (Fillingham,
Sage, & Lambon Ralph, 2005, 2006) and spaced retrieval
training protocols (Fridriksson, Holland, & Beeson, 2005).
Such variables might be systematically manipulated in
animal models to determine the nature of any neuro-
plastic changes that are observed and that conditions
maximize neuroplastic changes.
Much of what is known about principles of neuro-
rehabilitation comes from studies of rodents with brain
lesions. The application of rodent studies to neurore-
habilitation of language is necessarily limited. Studies
examining birdsong in birds with brain lesions (Brainard
& Doupe, 2000) may bring us a step closer to studies of
language. For example, such studies might be informa-
tive about the role the auditory system plays in recovery
of speech and language functions (Bolhuis & Gahr, 2006).
While animal models cannot answer questions that
are specific to aspects of language, computational mod-
els of cognition and language can play an important role
in future efforts to translate from animal to human mod-
els of language recovery and rehabilitation. One of the
more intriguing characteristics of computational models
is their ability to learn based on experience, and once
that learning has been established, to be “lesioned”
systematically and “rehabilitated” (Nadeau, 2000). The
output of this process can then be compared with be-
havioral data to generate and test hypotheses related to
rehabilitation. In this way, studies can examine funda-
mental principles of learning common to both animals
and humans to behaviors shared by both populations,
but not identically manifested (e.g., swallowing beha-
viors, memory skills), to language behaviors unique to
Raymer et al. (Language Work Group): Translational Research in Aphasia S269
humans, such as spoken and written language processing.
Data from aphasia treatment studies could be used to
develop and implement computer simulations that might
provide more explanatory power for the bases of rehabil-
itation effects.
From animal models to date, it seems clear that
learning and relearning any behavior will likely vary
depending on the timing of intervention as well as the
intensity and duration of treatment. What researchers
cannot learn from animal research is how such princi-
ples will interact with the content and social use of lan-
guage behavior that they aim to rehabilitate in humans.
Recent empirical studies (e.g., Martin, Fink, & Laine,
2004) of treatment for anomia suggest that responses to
such treatment vary depending on the content of treat-
ment (semantic vs. phonological) and source of naming
impairment (semantic, phonological, or both), and that
these two variables may interact with each other. Ani-
mal models cannot answer questions about aspects of
language that are impaired and how they interact with
recovery and relearning. Nor can they answer questions
about possible interactions between intensity of treat-
ment, stimulus type (e.g., semantic or phonological), and
type of impairment (e.g., semantic or phonological). We
note, however, that those sorts of questions might be ad-
dressed with computer simulations.
Recent research in errorless versus “errorful” learn-
ing provides an example of approaches to learning that
might vary in their effectiveness depending on the be-
havior to which they are applied. Errorless learning
techniques that minimize opportunities for error dur-
ing the learning process have been successful in treat-
ing memory impairments (Wilson, Baddeley, Evans, &
Shiel, 1994). In treatment of word retrieval and sentence
production disorders, this approach has fared as well as
errorful learning approaches (Fillingham et al., 2005,
2006; Maher et al., 2002). In fact, error-reducing tech-
niques for word retrieval such as repetition priming have
been found to be less effective when access to semantics
is impaired (Martin et al., 2004a). Likewise, recent inves-
tigations in memory treatment suggest that the type of
material to be learned can influence the relative advan-
tage of errorless over errorful learning (Evans et al.,
2000). Studies such as these indicate that researchers
have much more to learn about the contexts in which
errorful versus errorless learning approaches are most
effective. It may be, for example, that rehabilitation of
lexical–semantic processing impairment requires more
errorful learning approaches, as in semantic feature anal-
ysis treatments (e.g., Boyle, 2004), which encourage the
learner to generate semantic associations to a concept
and, thus, stimulate deeper processing and discrimina-
tion of many features of concepts. Questions about error-
less versus errorful learning can be answered in animal
models with respect to some b ehaviors shared with
humans (e.g., motor learning). However, translation of
those findings directly to the domain of language might be
implemented with a computational model that can test
these principles in a simulation that represents lan-
guage behavior. The role of computer models in transla-
tional rehabilitation research can be one of a bridge
between the fundamental principles of learning that are
common to both animals and humans and the manifes-
tation of those principles in the domain of spoken and
written language.
Finally, efforts also need to progress to determine
links between what is known about neuroplasticity and
to use this knowledge to researchers’ advantage when
planning patient intervention. Initial work in this direc-
tion can be seen in studies examining relations between
electrophysiological measures and aphasia assessment
(e.g., Marchand, D’Arcy, & Connolly, 2002). Repetitive
transcranial magnetic stimulation (rTMS) has a role to
play in this regard as well. In healthy individuals, the
extent to which rTMS, when applied to the left hemi-
sphere, disrupted language functions correlated with
the degree of language lateralization as determined on
functional magnetic resonance imaging (Knecht et al.,
2002). Functional neuroimaging studies of aphasia re-
covery often show right hemisphere activation that some
have argued is less suited to effective aphasia recovery
(Price & Crinion, 2005; W inhu isen et al., 2005). As a means
to promote aphasia recovery, Naeser, Martin, Nicholas,
Baker, Seekins, Helm-Estabrooks, et al. (2005) and Naeser,
Martin, Nicholas, Baker, Seekins, Kobayashi, et al.
(2005) have applied rTMS to the right inferior frontal
cortex of individuals with nonfluent aphasia and have
shown improved naming abilities that have lasted sev-
eral months. Questions that arise from intervention may
lead back to basic studies in neuroimaging and neuro-
physiology to determine markers for successful recovery
and rehabilitation potential.
The Future of Translational Research
Researchers in clinical aphasiology have always been
appreciative of and sensitive to the principles of neuro-
rehabilitation that emerge from the basic science liter-
ature as it applies to research in aphasia treatment and
recovery. Further progress in research requires much
interaction in how researchers move along a continuum
from basic science developments to translational studies
in humans to clinical trials. Studies in animal models of
neurorehabilitation, computational simulations of aphasia,
and the cognitive science work that focuses on the ac-
quisition of complex behaviors (i.e., skill acquisition theo-
ries and approaches) are all rich sources of translational
S270 Journal of Speech, Language, and Hearing Research • Vol. 51 • S259–S275 • February 2008
interest to aphasiologists. Questions, concerns, and prob-
lems encountered in human clinical interactions should
then lead back to motivate further basic science investi-
gations. A productive basic science and clinical science
research process, then, is interactive, integrated, and
complementary. More and more researchers are re-
cognizing this critical need for increased cooperation
and integration of research endeavors. With renewed
emphasis on this perspective that has been encompassed
in the NIH Roadmap initiative, the future of translational
research is indeed promising. Neurorehabilitation re-
searchers, including aphasiologists, need to continue to
build bridges among basic and clinical disciplines to pro-
mote a research agenda in which all researchers’ treat-
ment initiatives flourish.
Acknowledgments
This article is an outgrowth of the Workshop in Plasticity/
NeuroRehabilitation Research sponsored and supported by
the VA Brain Rehabilitation Research Center of Excellence,
Gainesville, FL, and the University of Florida Department of
Communication Sciences and Disorders. This work was done
under the auspices of the Language Work Group, led by
Anastasia M. Raymer.
Special thanks to Leslie Gonzalez Rothi, Jay Rosenbek,
Chris Sapienza, and Nan Musson, organizers of the event.
Thanks also to several individuals who contributed to the
Language Work Group discussions including Malcolm McNeil,
Theresa Jones, Randall Robey, Alex Johnson, Jacquelyn
Hinckley, Michael De Riesthal, Charles Ellis, and Susan Leon.
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Received February 9, 2006
Accepted September 22, 2007
DOI: 10.1044/1092-4388(2008/020)
Contact author: Anastasia M. Raymer, 110 Child Study
Center, Old Dominion University, Norfolk, VA 23529-0136.
E-mail: sraymer@odu.edu.
Raymer et al. (Language Work Group): Translational Research in Aphasia S275
