Chronic Aphasia Clinical Trial
Official title:
Does Inner Speech Improve Access to Overt Speech in Aphasia Following Stroke? An fMRI Study Utilising Computerised Rehabilitation Software.
The few studies looking systematically into the neurophysiological and neuropsychological
components of available therapies for chronic aphasia are highly heterogeneous in nature.
Results from these studies have, unsurprisingly, indicated heterogeneous results, such as
dissimilar neural outcomes associated with neuropsychological gains. There is, therefore, no
consensus of how a successful therapy— that is, one that produces a measurable language gain
in either production or comprehension —impacts the functional language networks of the brain
in a specific type of aphasia population.
A recent study has shown that inner speech (the imagination of speech) involves networks and
areas dissociable from those implicated in speech production. Further, behavioural analysis
has shown an interesting discrepancy between inner speech and overt speech (also called
speech production) in a small chronic aphasia population: some participants elicited poor
inner speech coupled with relatively intact overt speech, while others elicited relatively
intact inner speech coupled with poor overt speech. This unexplored discrepancy implies that
inner speech and speech production are dissociable, though share similar networks.
This discrepancy, and the notion that these speech components share a similar network, drives
this study's hypothesis that improvement in speech production after rehabilitation might be
facilitated by an intact inner speech network. Much as good athletes visualise their
performance before the actual event in order to increase their chances of success, so too
might intact inner speech facilitate speech production, helping to visualise the word in
order to increase the success of produced speech.
By studying a specific component of speech—inner speech—in a relatively homogeneous
population of chronic expressive aphasics, the present study provides an explicit, critical
means of understanding neurophysiological (as assessed by functional magnetic resonance
imaging) and neuropsychological (as assessed by language batteries and personal
questionnaires/interviews) changes occurring during speech therapy.
As a secondary objective, this study will explore the effectiveness, feasibility and
adherence to an at-home computerised aphasia software delivered via a portable tablet.
15 million people worldwide have a stroke each year, with 152,000 in the United Kingdom.
Recent estimates suggest that roughly 33% of patients suffering a stroke develop aphasia, a
loss or impairment of language function caused by brain damage, which can have a significant
impact on all aspects of an individual's life, as well as that of their carers. Aphasia can
often be long-term, or chronic, affecting patients at least a year or more after their
initial stroke.
Few studies have systematically investigated the effects of rehabilitation on brain
mechanisms recruited to support recovery in stroke. Studies in this area are highly
heterogeneous. The heterogeneity largely stems from 'lesion-related or language
deficit-related differences in the patients studied'. Participants across and sometimes
within the few studies conducted in this area vary with regard to the type of aphasia or
time-following-stroke. These studies also boast differences including the type and dosage of
treatment, the type of scanning task used to evaluate the desired effects of treatment, and
the type of data analysis employed. Results from these studies have, unsurprisingly,
indicated dissimilar neural outcomes associated with neuropsychological gains, such as
increased right hemisphere (contra-lateral) involvement, or, in contrast, increased
peri-lesional activation. There is, therefore, no consensus of how 'successful therapies'
(that is, those that elicit some kind of language gain, either in comprehension or
production) impact the language networks of the brain.
"It is well known that individuals with aphasia differ greatly with often varying language
patterns and associated lesions, and even study participants carefully selected for their
deficit patterns are seldom, if ever, homogeneous" . People with aphasia will, and do, differ
markedly. Given this predicament, it becomes necessary to systematically control the other
parts of the study, which includes limiting the imaging tasks and analysis to one component
of the language system and using a powerful design, such as a crossover with two therapeutic
conditions.
This study therefore aims to use systematic methodology to add information to the diminutive
body of literature concerning chronic aphasia rehabilitation by exploring a specific
component of the language network, inner speech, and its potential influence on speech
production (neurophysiologically and neuropsychologically).
A previous study has shown that inner speech involves networks and areas dissociable from
those implicated in speech production, such as the left inferior frontal gyrus, especially
the pars opercularis and the supramarginal gyrus. Further, behavioural analysis has shown an
interesting interaction of inner and overt speech in a small chronic aphasic population,
whereas some chronic stroke patients showed poor inner speech coupled with good overt speech,
while others showed good inner speech coupled with poor overt speech. This finding implies an
unexplored relationship between the two networks: conceivably, that improvement in speech
production during rehabilitation might be facilitated by an intact inner speech network.
There are hundreds of aphasia therapies on the market today. In general, two types of therapy
exist: impairment-based and communication-based. Impairment-based therapies are those that
specifically target increasing the ability of components of the language system, such as
naming, reading, writing and sentence structure, and comprise most of the therapies on the
market. Communication-based therapies are more informal, aiming to stimulate conversation by
any means. The most utilised therapies for aphasia include constraint-induced therapy, which
involves constraining the participant to using only words and not gestures in their
communication, thus hoping to free the individual of non-speech compensatory strategies;
melodic intonation therapy, based on the observation that people with aphasia have a better
success rate if singing words rather than just saying words, uses melody as a crucial
component for relearning speech; and various phonological cueing or naming therapies, which
use repetition, semantic and phonological cueing based on specific anomia (naming) deficits.
Aphasia therapies are so prevalent because, unlike drug therapies, they carry very little
risk. This does not mean, however, that each aphasia therapy on the market is effective for
all types of aphasia deficits. The scientific community lacks understanding of these
therapies in several facets: understanding which treatments produce language gains in
specific populations (i.e., chronic vs. acute individuals, fluent vs. non-fluent aphasia
types); how language gains map onto changes in neurological function; and the trajectory of
language gains over time, neuropsychologically and neurologically.
Utilising an at-home computerised aphasia rehabilitation program, this study will explore
whether inner speech can assist patients in restoring access to spoken language, therefore
resulting in improvement of language production (as assessed by neuropsychological
examinations) and instigating changes in functional networks (as assessed by functional
magnetic resonance imaging).
The computerised therapy was chosen because of its detailed clinical output system, its
ability to be personalised to each individual, and its ability to adapt difficulty levels to
the needs of the user. A successful at-home therapy program may provide a means to combat the
lacking resources for continued rehabilitation outside of acute, hospital settings. As a
secondary outcome, this study will investigate the success, feasibility and adherence to this
software by collecting qualitative patient feedback and by analysing the software's
quantitative outputs, such as exercise completion and number of times attempted, total time
used and overall performance on the exercises.
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