Changes in dynamic resting state network connectivity following aphasia therapy.

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging

Background:

• Resting state functional magnetic resonance imaging (rsfMRI) reveals intrinsic brain networks.
• Plasticity of these networks post-stroke and with therapy is under-investigated.
• Aphasia, a language disorder post-stroke, affects narrative production.

Purpose of the Study:

• To investigate the plasticity of resting state networks after stroke.
• To examine the relationship between network dynamics and language recovery after imitation-based aphasia therapy.
• To identify dynamic brain states associated with therapeutic gains.

Main Methods:

• rsfMRI data from 12 individuals with aphasia were collected at multiple time points.
• Group independent component analysis (ICA) identified resting state networks.
• A sliding window approach assessed dynamic network correlations, clustering data into ten states.
• Correlation analysis linked time spent in specific states to narrative task performance.

Main Results:

• A specific dynamic state, characterized by minimal network correlation, was positively associated with narrative task improvement at 6-week follow-up.
• This association was observed when comparing post-therapy maintenance to baseline and immediate post-therapy assessments.
• Increased functional independence and segregation of resting state networks correlate with improved narrative production.

Conclusions:

• Imitation-based aphasia therapy promotes functional independence and segregation of resting state networks.
• This network reorganization underlies behavioral improvement in narrative production post-stroke.
• Findings have clinical implications for targeting non-invasive brain stimulation in stroke rehabilitation.