# Dynamic functional network connectivity and neuroplasticity in post-stroke aphasia

> **NIH NIH F30** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $30,157

## Abstract

PROJECT SUMMARY/ABSTRACT
 Language impairment, known as aphasia, is very common after stroke and the extent to which patients
recover and respond to language therapy varies greatly. Functional MRI, including resting-state functional
connectivity, is a widely used tool to study reorganization in the brain after an acquired brain injury such as
stroke. Specifically, resting-state functional connectivity measurements can provide important information on
the connectivity and organization of functional networks in the brain and changes in that connectivity over time
(i.e., functional network plasticity). This project will make use of both static and dynamic resting-state functional
connectivity to identify relationships between the short-term (seconds to minutes) temporal dynamics of
functional network connectivity and long-term (months) functional network plasticity in people with post-stroke
aphasia. We have previously shown that baseline measures of both static functional connectivity and variability
in dynamic functional network connectivity are predictive of treatment response in people with post-stroke
aphasia. However, it is not known whether this association is mediated by differences in functional network
plasticity. For the studies proposed in this application, we will test the following hypotheses in three aims: (1)
that patients with post-stroke aphasia have altered dynamic functional connectivity compared to healthy
controls characterized by decreased temporal variability and (2) that higher baseline temporal variability of
dynamic functional connectivity (i.e., more like that of healthy controls) is related to greater treatment-induced
changes in functional network topology. For the first aim, dynamic functional connectivity will be computed from
resting state functional MRI data for 40 individuals with post-stroke aphasia and 40 healthy controls, currently
being collected as part of a larger ongoing study. Temporal variability will then be compared between the two
groups. For the second aim, the temporal variability of dynamic functional network connectivity computed from
existing resting-state functional MRI data from 30 individuals with post-stroke aphasia will be related to
changes in graph theory measures of static functional connectivity from pre- to post-treatment. For the third
aim computational modeling will be used to test the following proposed mechanism: (1) Transient
synchronization between brain regions facilitates activity dependent plasticity and (2) greater diversity of
transient connectivity configurations provides a wider range of opportunities for this facilitation of plasticity
resulting in greater treatment-induced reorganization of functional networks. The results will yield insights into
the factors and mechanisms underlying variation in language recovery after stroke and may inform the
development of new or improved tools for prognostication in these patients. These studies will be carried out in
the Center for B...

## Key facts

- **NIH application ID:** 10928147
- **Project number:** 5F30DC021092-02
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Isaac B Falconer
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $30,157
- **Award type:** 5
- **Project period:** 2023-08-18 → 2024-11-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10928147

## Citation

> US National Institutes of Health, RePORTER application 10928147, Dynamic functional network connectivity and neuroplasticity in post-stroke aphasia (5F30DC021092-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10928147. Licensed CC0.

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