Clinical Trial Details
— Status: Not yet recruiting
Administrative data
NCT number |
NCT06405594 |
Other study ID # |
2044118-1 |
Secondary ID |
|
Status |
Not yet recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 2024 |
Est. completion date |
June 2029 |
Study information
Verified date |
May 2024 |
Source |
University of Maryland, College Park |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The proposed research is relevant to public health because stroke is a leading cause of
long-term disability among older adults and communication impairments resulting from stroke
have a significant negative impact on quality of life. By seeking to better understand
post-stroke aphasia, this project lays the groundwork for development of new interventions,
and aligns with NIDCD's priority areas 1 (understanding normal function), 2 (understanding
diseases), and 3 (improving diagnosis, treatment, and prevention).
Description:
Post-stroke agrammatic aphasia (PSA-G) is characterized by a cluster of symptoms (fragmented
sentences, errors in functional morphology, a dearth of verbs, and slow speech rate), yet
extant theories and language interventions focus on individual symptoms. This single-symptom
theoretical and intervention focus results in limited gains in functional communication. The
long-term goal of this research is to improve the clinical effectiveness of interventions for
PSA-G.
As a first step towards this goal, this project's objective is to advance the theoretical
framework of PSA-G by addressing two critical gaps. The first gap is in the mechanistic
understanding of how lexical, grammatical, motoric, and cognitive processes work together to
enable fluent sentence production and how this breaks down in PSA-G. The second gap is in the
understanding of neural mechanisms underlying how sentence production planning normally
unfolds over time and what crucial spatiotemporal alterations give rise to PSA-G versus other
variants of post-stroke aphasia with predominantly lexico-semantic deficits (PSA-LS). The
central hypothesis is that agrammatic language production results from spatiotemporal
alterations in the neural dynamics of morphosyntactic and phonomotor processes, causing a
cumulative processing bottleneck at the point of articulatory planning. This Synergistic
Processing Bottleneck Model of Agrammatism will be tested with two specific aims.
Specific Aim 1 will elucidate the relative contribution of syntactic and non-syntactic
processes towards sentence production in aphasia by using speed metrics and a path modeling
framework. The expected outcomes of this aim are an improved understanding of the extent to
which delays in different linguistic processes underlying the agrammatic symptom cluster
impair fluent sentence production in aphasia generally, and in PSA-G versus PSA-LS more
specifically.
Specific Aim 2 will determine the neural mechanisms underlying sentence production across
language deficit profiles. Magnetoencephalography (MEG) will be used to compare alterations
in timecourse and functional connectivity of key perilesional and contralesional syntactic
hubs across increasingly demanding morphosyntactic production tasks. The expected outcome of
this aim is a spatiotemporally specified neural model of sentence production in neurotypical,
PSA-G, and PSA-LS speakers.
The significance this research is that it will forward an empirically established
multidimensional model of sentence production, which will lay the foundation for developing
more targeted and effective language interventions for agrammatic aphasia. It will also
contribute to a better understanding of agrammatism in neurodegenerative aphasias. The
innovative aspects of this project include: a novel multidimensional theoretical framework
that incorporates non-syntactic dimensions of phonomotor planning, processing capacity and
speed, and neurophysiological dynamics; direct comparisons between PSA-G and PSA-LS groups;
and MEG analysis of spoken language with simultaneous electromyographic measurement.