Uncovering hidden pathways: structural brain networks under connected speech in post-stroke aphasia

Area of Science:

• Neuroscience
• Speech and Language Pathology
• Cognitive Science

Background:

• Post-stroke aphasia presents significant communication challenges.
• Understanding the neural underpinnings of connected speech in aphasia is limited.
• Previous research often focuses on single-word processing, neglecting higher-level connected speech.

Purpose of the Study:

• To investigate the relationship between brain structural network efficiency and connected spoken language abilities in individuals with post-stroke aphasia.
• To explore how focal brain lesions impact bilateral language and multiple-demand networks.
• To develop a framework for assessing brain-behavior relationships in aphasia.

Main Methods:

• Utilized T1 volumetric MRI scans and a lesion quantification toolkit.
• Applied graph theory analyses to measure brain structural network efficiency.
• Quantified connected speech abilities using frequency language analysis tools (bigram frequency, collocation, speech connectivity).

Main Results:

• Higher structural efficiency in bilateral language networks correlated with better connected speech.
• Focal lesions impacting bilateral language and multiple-demand networks explained variance in connected speech.
• Word-level behaviors linked to left temporo-parietal regions, while higher-level speech relied on bilateral network efficiency.

Conclusions:

• Connected speech in post-stroke aphasia depends on distributed bilateral anatomical networks, not just localized areas.
• The proposed framework using structural MRI and connected speech analysis is clinically accessible for aphasia research and treatment.
• Focusing on structural network efficiency offers a transformative approach to understanding brain connectivity and improving aphasia interventions.