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

Individuals with post-stroke aphasia, an acquired language disorder, face significant communication challenges essential for daily life. Surprisingly, little is known about how focal brain damage disrupts the bilateral anatomical integration of language and multiple-demand brain networks required for higher level, connected spoken language following aphasic stroke. To address this, we investigated the anatomical network correlates of spoken language abilities in a selective subgroup of thirty-six individuals with chronic post-stroke aphasia who had preserved single-word comprehension and monosyllabic word repetition (mean age 59 ± 12.51 years; 26 males/10 females) using an innovative methodological framework. Employing a lesion quantification toolkit and graph theory analyses of T1 volumetric MRI brain scans we measured individual's brain structural network efficiency. We then quantified the efficiency of their spoken language abilities using measures of bigram frequency, collocation, and speech connectivity using a frequency language analysis tool. Combining these brain and behavioural data, we found that higher structural efficiency in bilateral language networks significantly correlated with better connected speech abilities. By quantifying the impact of focal lesions on not only the left (dominant) language network but also bilateral language and multiple-demand networks, we were able to account for variance in aphasic's higher level, connected speech abilities. Post hoc analyses showed (i) word-level spoken language behaviours were associated with discrete left temporo-parietal, using voxel-based correlational methodology; (ii) while bilateral language and multiple-demand structural network efficiency was primarily sensitive to higher-level language behaviours, loading additional brain-behaviour variance beyond distributed voxels. These findings replicate prior research on word-level language behaviours and extend our insights into how bilateral brain networks are integrated in connected spoken language. Taken together, our findings illustrate how connected speech abilities, beyond the single-word level, in post-stroke aphasia rely on distributed bilateral anatomical networks. By utilizing widely available structural MRI brain scans alongside connected speech analyses mirroring more closely real-life speech communication, the framework we propose here offers a clinically accessible approach to enhance aphasia research and treatment. By focusing on structural network efficiency, it provides a transformative method to better understand the relationship between brain anatomical connectivity and spoken language skills, potentially guiding more effective aphasia interventions.