Brain Network based Language System Neuromodulation for Aphasia
- Institution
- University of Pennsylvania, PA
- Principal investigator
- Shreya Yogesh Parchure
- Funding
- $55K
- Duration
- 2025–2027
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Abstract
ABSTRACT Patients with stroke affecting left hemisphere brain regions commonly develop aphasia - major language deficits highly limiting their quality of life. Key to developing novel, targeted treatments for these deficits is better understanding how the brain manages the many cognitive processing demands of language, including semantic demands, which relates to understanding word meanings. These include the ability to retrieve a word with the right meaning from memory or the ability to select the right word from those of similar meaning. While neuroimaging and stroke lesion studies have revealed which isolated brain regions underlie language ability, little is known about how complex interactions between these brain network regions contribute to semantic cognition for language production. The proposed research uses network control theory (NCT), an emerging branch of systems engineering computation applied to neuroimaging - to model cortical brain regions and their white matter tract connections as a network of nodes and edges, respectively. NCT quantifies the properties of anatomical brain network structure that can constrain and control cognitive dynamics that drive complex human behaviors like language production. In Aim 1, I will study how brain network controllability influences healthy language production, and how an individual’s network control characteristics predict language behavior changes after manipulation by focal neuromodulation. Specifically, we used repetitive transcranial magnetic stimulation (rTMS) to experimentally modulate brain connectivity in healthy adults, to discover which language network topologies control word selection and retrieval during open-ended language generation tasks. In Aim 2, I apply these NCT methods in people with chronic post-stroke aphasia, to determine brain network predictors of optimal semantic responses to rTMS, using data from a completed clinical trial of rTMS for language recovery. The proposed work will be carried out in the world class training environment at the University of Pennsylvania’s Laboratory for Cognition and Neural Stimulation. These resources combined with an expert sponsorship team, including experts in studies of aphasia, network control theory and neuromodulation, will fully support completion of this proposal and facilitate my professional development as a future physician-scientist leading rigorous and reproducible clinically relevant research. Ultimately, the results of my proposed work will be key to improving the efficacy of noninvasive neuromodulation by personalizing therapies for aphasia rehabilitation - and will provide an advanced understanding of the neural basis of language more broadly.
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