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.